# Cloudkeeper > CloudKeeper is a comprehensive cloud cost optimization partner helping 400+ global companies save an average of 20% on their cloud bills, modernize their cloud set-up & maximize the value from AWS, Microsoft Azure & Google Cloud — all while maintaining flexibility and avoiding any long-term commitments or cost. Trusted by 400+ Global Customers Why choose CloudKeeper as your Cloud Cost Optimization Partner? 15+ Years of experience in cloud 100+ Certified solutions architects & cloud experts 400+ Global customers 20%Average savings on the entire cloud bill * ## 15+ Years in Business * ## 400+ Active Customers * ## $120+ million Cloud Cost Savings delivered * ## 20% Average Cost Reduction * ## 350+ CKers & Growing * ## The CloudKeeper Story **Our journey began in 2009** when we deployed our first application on AWS and we immediately fell in love with the cloud. In 2013, we won an AWS hackathon, which led to an exceptional opportunity – becoming an Advanced Consulting Partner directly recommended by AWS (AWS team told us that they have not onboarded any other partner directly at this tier). And that’s how our ‘official’ journey with AWS started! Since then, we have introduced many solutions for customers across diverse geographies and industries. We have become one of the most trusted end-to-end cloud cost optimization partners. Fast forward to 2024, with a team of 350+ CKers & growing, CloudKeeper has taken a major leap forward, hiving out from TO THE NEW as a cloud cost optimization solution to an independent company. This transformation is a testament to our valued customers' unwavering support and trust. This marks a significant advancement in our capabilities, and trust us, we are only at the beginning of this exciting journey, dedicated to providing enhanced value to our customers and the cloud community. Our Milestones * 2013 * Started as an AWS Advanced Consulting Partner. * 2018 * Started “AWS Spend Management” as a dedicated AWS Cost Optimization business offering under TO THE NEW’s Cloud Business. * Certified as an AWS Premier Partner(highest tier). * 2019 * Developed & launched our cloud cost visibility platform, CloudKeeper Lens. * 2020 * Started with AWS RI management offering. * 2021 * Became a Google Cloud Partner. * Recognized by ISG for our strong competencies in Public Cloud. * Launched CloudKeeper Lens on AWS Marketplace. * 2022 * Consolidated all our cloud cost optimization services under the 'CloudKeeper' umbrella. * Ranked in the top 5 partners globally in the Well-Architected Challenge conducted by AWS. * Recognized by ISG Research for its proven capabilities in providing end-to-end FinOps solutions. * Launched CloudKeeper EDP+ to help AWS EDP customers get better benefits. * 2023 * Launched CloudKeeper Commit, an AI-powered RI Management Platform. * Achieved Top#3 leaders’ spot in the cloud cost management category by G2. * Named a Key Player in IDC Market Glance: FinOps Cloud Transparency. * Recognized in the 2023 Gartner® Magic Quadrant™ for Public Cloud IT Transformation Services. * Became a Premier Partner of the FinOps Foundation. * Awarded the AWS APN Certification Distinction for achieving 100 AWS Certifications. * 2024 * Recognized by Forrester in their Cloud Cost Management And Optimization Solutions Landscape 2024 report. * Completed audit for AWS MSP Program with a 100% compliance score. * Hived out from TO THE NEW's cost optimization solution to become an independent company. What Makes us Rare * CloudKeeper offers a one-stop solution (validated by Everest Group & ISG) that tackles your end-to-end cloud & FinOps needs. Meet the Leadership Team * ## Deepak Mittal ### Founder & CEO Deepak is a visionary leader who spearheads the development and execution of long-term business strategies, driving the company's vision to provide world-class cloud engineering services to businesses globally, enabling them to achieve their technological goals and drive innovation. * ## Aman Aggarwal ### Chief Operating Officer Aman spearheads business operations, strategic execution, and cross-functional alignment to drive sustainable growth. With deep expertise in the Cloud space, Aman blends deep domain expertise with leadership to enhance customer value, foster innovation, and scale CloudKeeper’s impact globally. * ## Naman Jain ### Chief Growth & Marketing Officer Naman is a seasoned GTM leader with deep expertise in technology sales, marketing, & strategic planning. Recognized for his strategic vision, operational rigor, and results-driven mindset, he has played a pivotal role in accelerating the company’s growth & market success. * Say Hi to the CKers! 350+ Minds, One Goal! CloudKeeper in the spotlight - The latest & greatest happenings in the news! * 04 Oct, 2023 CloudKeeper Becomes a Premier Member of the FinOps Foundation * 18 Jan, 2024 CloudKeeper awarded the AWS APN Certification Distinction for achieving 100 AWS Certifications * 24 Jan, 2024 TO THE NEW Recognised by ISG in 2023 Multi Public Cloud Services Provider Lens™ * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close × # The Only Outcome-Driven AI & Cloud Cost Optimization Partner Delivering guaranteed, ongoing cloud cost savings - **end to end!** Optimization Governance Cost Management Optimization Visibility & Analytics Cloud Support ‹› Unlike traditional providers with a fragmented approach, we combine AI-led platforms, automation, and human expertise to deliver continuous, measurable cost savings - seamlessly and at scale. ## Built for Scale. Proven in the Real World. 0+ Years of Cloud Expertise 0% Average Cloud Savings Delivered 0+ Certified Engineers & Architects 0+ Global Customers ## Cloud Cost Optimisation Solutions Built for Scale ### CloudKeeper AZ Guaranteed discounts on the entire cloud bill with zero lock-ins or commitments. ### CloudKeeper PPA+ Maximize AWS PPA value with our additional benefits. Exclusive Value Add-ons: Unlimited 24x7 cloud support Access to CloudKeeper's FinOps Platform Suite ## Our All-in-One FinOps Platform Suite Complete visibility, intelligent optimization, and measurable ROI - in one unified platform, backed by unlimited support by cloud experts VISIBILITY & GOVERNANCE ## Complete visibility into your cloud spend with real-time dashboards and intelligent analytics. Intelligent analytics Cloud spend visibility Real-time breakup trends ‹› Exclusive value add-ons at no cost: Unlimited 24×7 Cloud Support Architecture Reviews ## Proven Capabilities across the Cloud Lifecycle By Use Case By Services “Cost savings kicked in immediately and were reflected in the next month’s bill. A second set of savings came in the longer term is due to the team, process and the tools that highlighted the areas we might look in to save money.” “Having access to experts whenever we need them in terms of new services, infrastructure & if we’re trying something new, CloudKeeper has the capability to support us. ” “After onboarding in just 1-2 days, you get recommendations by Cloudkeeper about the gaps & leakage you have in your AWS account, underutilized resources, data transfer leakage, RI utilization & alert mechanisms which helps in further savings.” Steven Thurlow CEO Prateek Baheti Head of Technology Dipesh Garg DevOps Lead ‹ › ## Thought Leadership In-depth, research-led content from our certified FinOps & cloud experts * * Blog How to Design the Hybrid Crossplane Architecture? * Whitepapers Best Practices to Slash Your GCP Spend by Up to 20% Instantly * Reports Navigating the FinOps Landscape: A Comprehensive Market Analysis ## Recognized by the best in the industry for end-to-end cloud cost optimization Major Player in MarketScape’s Worldwide FinOps Cloud Cost Optimization Assessment. Major Player in FinOps Cost Management Products PEAK Matrix Assessment 2025. Notable Vendor in Magic Quadrant for Public Cloud IT Transformation Services - Midmarket Global. Product Challenger in APAC for AWS Ecosystem Partners 2025. ## CloudKeeper in the Spotlight * * * * * * * * * * * * * * * * * * * * * * * * * * * ## Certified. Trusted. Industry Recognized. ## Stop paying for cloud tools. Start paying for outcomes. close close ## AWS Billing and Cost Management **AWS Billing and Cost Management** provides a suite of tools to simplify cloud spending and billing. It’s organized into three main areas: billing, cost management, and Savings. **AWS Billing** focuses on payment automation, making it easier to manage invoices and streamline payment processes. Meanwhile, **AWS Cost Management** helps optimize resource allocation, aiming to maximize the value of your cloud investment by minimizing unnecessary expenses. Usage reports enhance visibility, offering detailed insights into your cloud resource consumption. Together, these features help you control and optimize AWS spending effectively. line ### What is the AWS Billing Console? The AWS Billing Console is a feature within the AWS Billing and Cost Management console that enables users to view monthly charges, manage invoices, and customize billing preferences for tax and payment options. * **Bills** : Download invoices and detailed billing data to understand charges. * **Purchase Orders** : Create and manage orders to align with organizational procurement. * **Payments** : Track outstanding balances and payment history. * **Payment Profiles** : Set up different payment methods for various AWS providers or departments. * **Credits** : Monitor balances and select where to apply for credits. * **Billing Preferences** : Opt for emailed invoices, and manage credit sharing, alerts, and discounts. ### AWS Cost Management Features of AWS Cost Management * **AWS Cost Explorer** : Analyze your cloud spending with detailed dashboards and reports, including Reserved Instances and historical trends for future forecasts. * **AWS Cost Anomaly Detection** : Detect unusual cloud usage early with AI-powered monitoring that notifies you of potential overspending. * **AWS Budgets** : Set and track cloud budgets, and get alerts or actions when thresholds are reached. * **AWS Savings Plans** : Save up to 70% by committing to reserved compute capacity. * **Right-Sizing Recommendations** : Optimize resources by identifying underused instances, reducing costs. ### Savings and Commitments AWS Billing and Cost Management also helps lower your AWS bill by optimizing resource use and applying flexible pricing models. * **AWS Cost Optimization Hub** : Discover savings opportunities with custom recommendations, like deleting unused resources, rightsizing, and leveraging Savings Plans or reservations. * **Savings Plans** : Access discounted rates over on-demand pricing through flexible plans. Manage inventory, review purchase suggestions, and monitor usage. * **Reservations** : Reserve capacity for services like EC2, RDS, Redshift, and DynamoDB at reduced rates, ideal for predictable workloads. ### How CloudKeeper can help in AWS Billing and Cost Management CloudKeeper helps companies effectively manage AWS billing and cost management and optimize cloud costs by offering tools and services designed for cost efficiency. As an AWS Billing Partner and AWS Premier Partner, **cloud cost savings, visibility, and expert support - all in one place!** We help you access best-in-market discounts at no cost, lock-in, or commitment by leveraging the power of group buying, the scale of spend aggregation, and volume-based discounts. On top of it, we provide a comprehensive cloud cost visibility platform and proactive support acting as a cloud cost management vertical for your business. CloudKeeper’s cloud cost visibility platform Our Take the first step toward effortless AWS billing and cost management — Frequently Asked **Questions** * ### Arrow 1.What is AWS Billing and Cost Management? Q1. What is AWS Billing and Cost Management? AWS Billing and Cost Management is a suite of tools to help you simplify cloud spending and billing. It includes features for managing invoices, automating payments, optimizing resource allocation, and tracking cloud costs. * ### Arrow 2.What is the AWS Billing Console? Q2. What is the AWS Billing Console? The AWS Billing Console is where you can view and manage your AWS bills, including downloading invoices, managing payments, and customizing billing preferences. * ### Arrow 3.What are some key features of AWS Cost Management? Q3. What are some key features of AWS Cost Management? Key features include AWS Cost Explorer, AWS Cost Anomaly Detection, AWS Budgets, AWS Savings Plans, and Right-Sizing Recommendations. * ### Arrow 4.What is the difference between AWS billing and Cost Explorer? Q4. What is the difference between AWS billing and Cost Explorer? The key difference between AWS Billing and AWS Cost Explorer lies in their primary focus and functionality: **AWS Billing** * **Purpose:** AWS Billing focuses on payment management, invoice generation, and billing preferences. * **Features:** * View and download invoices. * Manage payment methods, tax settings, and purchase orders. * Track outstanding balances and payment history. * Set billing preferences like email invoices or consolidated billing for linked accounts. * **Audience:** Primarily used by finance teams or administrators to handle payments and ensure compliance with procurement processes. **AWS Cost Explorer** * **Purpose:** AWS Cost Explorer focuses on analyzing and visualizing cloud usage and costs to optimize spending. * **Features:** * Generate reports to understand usage and cost trends. * Analyze costs by service, linked accounts, or usage types. * Forecast future spending based on historical data. * Identify savings opportunities, such as underused resources or Savings Plans. * **Audience:** Useful for cloud architects, FinOps teams, and business leaders to monitor and optimize cloud costs. **Summary** * AWS Billing deals with the administrative aspects of payments and invoices. * AWS Cost Explorer provides analytical insights to track and optimize cloud spending. * ### Arrow 5.What are the advantages of billing and cost management on AWS? Q5. What are the advantages of billing and cost management on AWS? AWS Billing & Cost Management helps you understand and control your cloud spending. 1. **Enhanced Visibility:** Provides detailed cloud cost visibility and usage insights, enabling granular tracking across linked accounts. 2. **Cost Optimization:** Identifies savings opportunities through tools like AWS Cost Explorer, Savings Plans, and Reserved Instances. 3. **Control and Governance:** Enables budget creation, anomaly detection, and proactive alerts to prevent overspending. 4. **Streamlined Billing:** Consolidated billing simplifies multi-account management with a unified invoice. * ### Arrow 6.How to optimize AWS billing? Q6. How to optimize AWS billing? 5. **Monitor Usage:** Use AWS Cost Explorer for cost breakdowns and trend analysis. 6. **Custom Reports & Dashboards: **Create tailored reports and dashboards to track key metrics and monitor spending against budgets. 7. **Utilize Savings Plans and RIs:** Commit to discounted rates for predictable workloads. 8. **Implement Right-Sizing:** Use recommendations to scale down or terminate underutilized resources. 9. **Leverage Spot Instances:** Reduce costs for non-critical workloads by using Spot pricing. 10. **Enable Cost Allocation Tags:** 11. **Regular Reviews:** Conduct regular cost reviews to identify new optimization opportunities. 12. **Use AWS Budgets:** Set thresholds and receive notifications for cost and usage limits. For a comprehensive approach, consider integrating AWS-native tools with **CloudKeeper** to enhance automation, better governance and achieve significant savings. * ### Arrow 7.Which feature of AWS billing and Cost Management enables you to view costs across linked accounts and monitor spending on a daily and monthly basis? Q7. Which feature of AWS billing and Cost Management enables you to view costs across linked accounts and monitor spending on a daily and monthly basis? The AWS Cost Explorer of AWS Billing and Cost Management enables you to view costs across linked accounts and monitor spending on a daily, and monthly basis. It provides detailed dashboards and reports to analyze your cloud spending trends, usage patterns, and forecasts for better financial planning. For more granular insights you can opt for tools like * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close About Us CloudKeeper is a comprehensive cloud cost optimization partner helping 400+ global companies save an average of 20% on their cloud bills, modernize their cloud set-up & maximize the value from AWS and Google Cloud — all while maintaining flexibility and avoiding any long-term commitments or cost. Trusted by 400+ Global Customers Our customers saved an average of 20% on their monthly AWS and GCP spend through CloudKeeper We would love to stay in touch * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close **Solution Architect as a Service (SAaaS)** Build, Optimize, and Innovate Efficiently with Certified Cloud Experts * Unlimited **guidance** by certified cloud architects * Flexible, **focused** & outcome-driven engagement * Drive **innovation** with GenAI & modernization initiatives * **No lock-in** or commitment required What is Solution Architect-as-a-Service? Designing and managing cloud infrastructure is complex & cost-intensive. Without a dedicated Solutions Architect, even experienced teams risk security gaps, inefficient architectures, and rising cloud spend. CloudKeeper’s Solution Architect-as-a-Service **gives you on-demand access to senior certified cloud architects** to modernize, secure & optimize your cloud infrastructure. * Fix high-impact architecture and security gaps * Identify and tap hidden cost savings opportunities * Explore & validate new GenAI and modernization initiatives ## Why CloudKeeper's Solution Architect-as-a-Service? Delivering the perfect blend of cloud expertise, automation, and FinOps intelligence to help you innovate faster and operate smarter. * #### Unlimited Solution Architect support We act as your team extension for architecture reviews, design sessions, and expert guidance. * #### Zero-risk engagement All engagement types are included with no lock-ins or long-term commitments. * #### Customized roadmap for your architecture Our Solution Architects create an entire roadmap to assess, strategize, and optimize your cloud environment. * #### Guided workshops and assessments Address security, reliability, performance, cost, and operational excellence across your cloud workloads. Choose Your Engagement Type You can select the initiative that best addresses your cloud and innovation challenges * Technology Roadmap Planning Assess and prioritize technical initiatives across your organization. * GenAI Roadmap Planning Discover how AI can be strategically leveraged to achieve your business objectives. * Proof of Concept (POC) Validate new architecture patterns, service adoption, or modern workload implementations. * Well Architected Reviews Comprehensive review of your existing cloud infrastructure for architectural optimization. * Cost Optimization Assessment Identify hidden & untapped cost savings across your cloud environment with actionable recommendations. * Software Savings Analysis Discover third-party software cost reductions through AWS & GCP Marketplace repurchasing. * FTR Compliance Assessment Fast-track your Cloud Marketplace "Qualified Software" badge with our readiness assessment. * GenAI Workshop Hands-on exploration of generative AI applications for your business challenges. * Migration Assessment Plan and optimize your workload migrations to the cloud with expert guidance. We are on Frequently Asked **Questions** * ### Arrow 1.What's the minimum cloud spend required? Q1. What's the minimum cloud spend required? You must have a minimum cloud consumption of $15,000 MRR (Monthly Recurring Revenue) to be eligible for the program. This threshold ensures we're working with organizations that have meaningful cloud infrastructure to optimize. * ### Arrow 2.Can we combine multiple engagement types? Q2. Can we combine multiple engagement types? Absolutely! Many of our customers combine multiple engagements, for example, you might start with a Cost Optimization Assessment while running a GenAI Workshop in parallel. Our team will help you prioritize based on your objectives. * ### Arrow 3.How much time do we need to commit? Q3. How much time do we need to commit? The time commitment depends on your engagement type and organizational priorities. We work flexibly with your schedule. Expect initial alignment meetings, follow-up sessions, and collaborative work sessions. * ### Arrow 4.Who should be involved from our team? Q4. Who should be involved from our team? The ideal team includes key stakeholders from technology, operations, finance, and leadership. Depending on your engagement type, you might involve architects, DevOps engineers, FinOps professionals, and decision-makers. We'll guide you on the right mix. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close AWS Foundational Technical Review (FTR) by Certified Experts * 150+ AWS-certified experts * 100+ Successful AWS FTR submissions * 99% First-Time Pass Rate ‹› ## Why DNBs and ISVs Need AWS FTR As an AWS Premier Partner, we accelerate your FTR success - aligning your architecture to AWS Marketplace and co-sell standards with expert-led gap analysis, remediation, and end-to-end execution. * #### Earn the "Reviewed by AWS" Badge Build customer trust with AWS's highest technical validation. * #### Unlock AWS Funding Benefits Become eligible for AWS ISV Workload Migration Program (WMP) and MAP funding. * #### Accelerate Business Growth Access AWS's global sales teams and enterprise customer base. * #### Gain Co-Selling Opportunities Jointly sell with AWS account teams and participate in AWS Partner Programs. Why ISVs Struggle with AWS Foundational Technical Review * #### Unclear documentation requirement AWS expects detailed architecture diagrams, security controls, and disaster recovery plans. * #### Security and compliance gaps Encryption, IAM policies, and logging often don't meet AWS's strict standards. * #### Failed first attempts Without guidance, 40%+ of submissions get rejected, which delays launch by months. * #### No dedicated AWS expertise AWS WAR demands specialized expertise, something most engineering teams don’t have bandwidth for. * #### Remediation bottlenecks Fixing gaps without impacting production is a full-time job. * #### Time pressure to launch Every delay is a missed co-sell opportunity and lost revenue. ## The CloudKeeper Solution: **End-to-End AWS FTR Support** Comprehensive assessment Guaranteed Compliance & Remediation Reduce Risk & Identify Issues Early Full Documentation & Submission Support * Full architectural review against AWS Well-Architected Framework. * Identify gaps across Security, Reliability, Operational Excellence, and Performance Efficiency. * Prioritized remediation roadmap with timelines. * Fix security vulnerabilities: encryption, IAM, logging, monitoring. * Strengthen reliability: disaster recovery, backups, multi-AZ deployments. * We implement fixes alongside your team. * Catch compliance gaps before AWS does. * Validate with AWS-certified experts who've passed 100+ AWS FTRs. * Zero production disruption during remediation. * Prepare all technical documentation and diagrams. * Coordinate evidence collection and AWS communications. * Provide re-submission support if needed. CloudKeeper’s Foundational Technical Review (FTR) vs. Others **Capability** **Other Consultants** **CloudKeeper AWS FTR** We are on **** **** **Ready to Pass Your AWS FTR?** Simplify your AWS FTR journey with expert-led guidance, faster approvals, and zero hassle at no cost or commitment. The CloudKeeper Difference - Your Dedicated AWS FTR Squad Each customer is backed by a dedicated team that collaborates with you daily through Slack or Teams * ### FinOps Strategist Aligns AWS FTR with cost efficiency, business priorities, and governance controls. * ### DevSecOps Focuses on IAM, data protection, security, and compliance guardrails for AWS FTR checks. * ### Solutions Architect Validates architecture against AWS Well-Architected pillars and closes technical. * ### Customer Success Partner Drives milestone-based execution, coordinates remediation, tracks AWS FTR checklist completion. Frequently Asked **Questions** * ### Arrow 1.What is the AWS Foundational Technical Review (FTR)? Q1. What is the AWS Foundational Technical Review (FTR)? The AWS Foundational Technical Review is a mandatory technical assessment for ISVs who want to co-sell with AWS or list their solutions on AWS Marketplace. It validates that your architecture follows AWS best practices across security, reliability, operational excellence, and performance efficiency. * ### Arrow 2.How long does the AWS FTR process take? Q2. How long does the AWS FTR process take? With CloudKeeper's support, most ISVs complete the assessment, remediation, and submission process in 6-8 weeks. Without guidance, it can take 3-6 months - especially if your first submission is rejected. * ### Arrow 3.What happens if my AWS FTR submission fails? Q3. What happens if my AWS FTR submission fails? CloudKeeper provides re-submission support. We review AWS's feedback, address the gaps, update documentation, and resubmit until you pass. Most customers pass on the first or second attempt with our guidance. * ### Arrow 4.Do you handle the actual remediation, or just recommend changes? Q4. Do you handle the actual remediation, or just recommend changes? Both. We identify gaps and provide recommendations, but we also work alongside your team to implement fixes — whether that's updating IAM policies, configuring disaster recovery, or refactoring infrastructure. You're not left to figure it out alone. * ### Arrow 5.How does CloudKeeper ensure our production environment stays stable during remediation? Q5. How does CloudKeeper ensure our production environment stays stable during remediation? We follow a risk-based approach: start with non-production environments, validate changes in staging, implement changes during maintenance windows, and always have rollback plans ready. Your Solutions Architect coordinates every step to ensure zero disruption. * ### Arrow 6.What documentation does AWS require for FTR? Q6. What documentation does AWS require for FTR? AWS expects architecture diagrams, security control documentation, disaster recovery plans, operational runbooks, and evidence of monitoring and logging. CloudKeeper prepares all of this for you - formatted to AWS's standards. * ### Arrow 7.Can CloudKeeper help if we've already failed an AWS FTR submission? Q7. Can CloudKeeper help if we've already failed an AWS FTR submission? Absolutely. We specialize in AWS FTR resubmissions. We'll review AWS's rejection feedback, identify exactly what needs to be fixed, implement the changes, and resubmit with full confidence. * ### Arrow 8.What role does the CloudKeeper team play after AWS FTR approval? Q8. What role does the CloudKeeper team play after AWS FTR approval? Many customers continue working with CloudKeeper for ongoing AWS optimization, cost management, and architectural support. But even if you only need AWS FTR support, we ensure you're fully set up for success before we hand off. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Seamless Migration to AWS Graviton, the Future of Cloud Unlock superior processing power, unmatched flexibility, and significant cost savings with the AWS Graviton CPUs. CloudKeeper helps you make a smooth transition to the Graviton-based workloads and maximize your price-to-performance ratio. * Assessment and Workshops Evaluating your workloads for AWS Graviton migration opportunities and providing workshops to optimize your performance. * Migration Roadmap Creating a step-by-step AWS Graviton migration plan and assisting in managing the process to ensure timely and budget-friendly completion. * Continuity Planning Developing a plan to handle disruptions, including failover to a secondary AWS region or disaster recovery. * Migration and Upgrades Managing the migration and upgrading of your workloads to AWS Graviton, ensuring minimal disruption. * Cost and Performance Optimization Enhancing your AWS Graviton workload performance and optimizing costs through tuning, configuration, and continuous refinement. * Managed Services Monitoring, alerting, and troubleshooting services to manage your AWS Graviton workloads effectively. Our Capabilities * Seamless AWS Graviton migration with zero business continuity risks * Risk & Cost management expertise * Expertise in migrating complex workloads * Hands-on care with setting up & handling workloads * Conducting performance testing * Porting applications to run natively on AWS Graviton Why should you Migrate to AWS Graviton? AWS Graviton is a next-generation ARM-based processor designed to deliver the best possible performance for your cloud workloads. * Best Price-Performance Offers 40% better cost performance compared to regular x86 or x64 processors. * Energy Efficiency Uses up to 60% less energy than comparable x86-based processors. * Extensive Software Support AWS Graviton processors are supported by many popular operating systems, ISVs, and AWS Partners. * Available as managed AWS services Available in popular managed AWS services, such as Amazon Aurora, Amazon RDS, and Amazon EKS. Your one-stop destination for Cloud Cost Optimization * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud. * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure. **Related Resources** * What is AWS Graviton? Use Cases, Benefits & Key Considerations Learn the basics of AWS Graviton processors, their major use cases, the benefits of AWS Graviton migration and the factors to be considered before the transition. Blog * Acing the Cloud Optimization by choosing the right services, pricing & best practices Discover the major considerations in cloud infrastructure management and the importance of Automated Cloud Optimization solutions for a robust cloud strategy. Whitepapers * Unlocking Cost benefits in the AWS ecosystem Shifting to AWS cloud allows businesses to scale, while reducing their overall costs. Learn how to unlock the true cost benefits for your AWS infrastructure. Whitepapers Frequently Asked **Questions** * ### Arrow 1.What is the Graviton processor in AWS? Q1. What is the Graviton processor in AWS? AWS Graviton is a family of server processors designed by AWS to improve the efficiency and performance of its cloud services. Built on Arm architecture, these processors are tailored to AWS’s specific needs and power a wide range of AWS services. Here’s a * ### Arrow 2.Is AWS Graviton faster? Q2. Is AWS Graviton faster? Yes, AWS Graviton offers significantly faster performance for many workloads due to its custom-designed ARM-based processors, offering better memory bandwidth and compute capabilities compared to their predecessors. * ### Arrow 3. Is Graviton 2 better than Graviton 3? Q3. Is Graviton 2 better than Graviton 3? No, Graviton 3 offers 25% better performance and faster clock rates compared to Graviton 2, making it more suitable for demanding workloads. For example, it delivers 2x faster processing for cryptography processing and 3x for machine learning workloads. * ### Arrow 4.What is the difference between AWS Graviton 3 and 4? Q4. What is the difference between AWS Graviton 3 and 4? Graviton 4 delivers 30% better compute performance with improved clock rates and efficiency, compared to Graviton 3, along with 75% more memory bandwidth and 50% more cores. More specifically, it offers 40% faster database performance, 30% faster web applications, and 45% faster Java workloads, * ### Arrow 5.What are the key benefits of using AWS Graviton? Q5. What are the key benefits of using AWS Graviton? AWS Graviton delivers up to 40% better price-performance, enhanced energy efficiency, improved security, extensive software support, and seamless availability through AWS Managed Services, making it a cost-effective and reliable choice for scaling modern cloud-native workloads efficiently. * ### Arrow 6.What is AWS Graviton migration? Q6. What is AWS Graviton migration? AWS Graviton migration involves transitioning your AWS workloads from traditional x86-based instances to Graviton-powered instances, offering better performance, cost savings, and scalability with expert-guided migration strategies. * ### Arrow 7.What types of workloads and services are compatible with AWS Graviton? Q7. What types of workloads and services are compatible with AWS Graviton? AWS Graviton supports a variety of workloads and services, enhancing performance and cost-efficiency. Some of the major services compatible with AWS Graviton include Amazon EC2, Amazon Aurora, Amazon RDS, Amazon MemoryDB for Redis, Amazon ElastiCache, Amazon OpenSearch, Amazon EMR, AWS Fargate, Amazon EKS, and AWS Lambda. These services cater to diverse applications, from relational databases to large-scale data processing, containerized apps, and serverless computing. * ### Arrow 8.How does one migrate to AWS Graviton? Q8. How does one migrate to AWS Graviton? Migrating to AWS Graviton-powered instances requires a step-by-step approach. 1. **Assess** : Evaluate your workload’s compatibility with Arm-based processors and Graviton instances. 2. **Build** : Ensure your applications and dependencies are compatible with the Arm64 architecture. 3. **Test** : Run tests on Graviton instances to validate performance and compatibility. 4. **Migrate** : Transition your production workloads to Graviton, leveraging monitoring tools to track performance and optimize usage. AWS offers comprehensive technical documentation to support the transition. Working with an AWS Graviton Migration Partner like CloudKeeper can help streamline planning, testing, and execution, ensuring a seamless migration with optimal results. * ### Arrow 9.Why should I choose CloudKeeper for AWS Graviton migration? Q9. Why should I choose CloudKeeper for AWS Graviton migration? With 15+ years of cloud expertise and having worked with 400+ businesses globally, CloudKeeper is a trusted partner for all your cloud migration and modernization needs. CloudKeeper offers comprehensive AWS Graviton Migration Services, without compromising business continuity. This includes the following phases. **Assessment & Workshops**: Gain clarity on Graviton’s potential with tailored workload evaluations and hands-on workshops. CloudKeeper helps identify migration opportunities while optimizing for performance gains. **Migration Roadmap** : A detailed migration plan is created, offering end-to-end support to ensure timely execution while adhering to your budget. **Continuity Planning** : The CloudKeeper team develops robust disaster recovery and failover strategies, minimizing risks during and after migration. **Migration & Upgrades**: CloudKeeper manages the technical intricacies of transitioning and upgrading workloads to Graviton, minimizing downtime and disruptions. **Cost & Performance Optimization**: Post-migration, the team fine-tunes configurations and delivers continuous optimization to maximize the price-to-performance ratio. **Continued Support** : From monitoring and troubleshooting to moving applications to run natively on the AWS Graviton architecture, CloudKeeper provides end-to-end support for your entire migration strategy. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Sail smoothly through your Cloud Migration CloudKeeper is proud to be a select partner for the AWS Migration Acceleration Program (MAP). Seamlessly migrate to AWS with confidence, leveraging our expertise, tools, partner benefits, and hands-on support. ## Phase 1 ## Assess Your Readiness * Comprehensive infrastructure assessment using AWS Cloud Adoption Framework. * Developing a TCO model to justify migration projects. ## Phase 2 ## Mobilize Your Resources * Building necessary capabilities and operational foundations. * Guidance on migration planning for better decision-making. ## Phase 3 ## Migrate and Modernize * Implementation with expert assistance and automated processes. * Modernizing and cost-optimizing the new AWS environment. Achieve a smooth, risk-free, and cost-effective transition to AWS. Unlock exclusive benefits with the AWS Migration Acceleration Program CloudKeeper can help you take full advantage of the AWS Migration Acceleration program with access to AWS funding, support from certified professionals, and a tailor-made migration strategy. * Financial Assistance Offset initial migration costs with AWS-provided financial support and incentives. * Expert Guidance Benefit from the expertise of AWS-certified professionals to ensure a seamless migration. * Flexible Participation Option to participate in individual phases or the entire MAP program to suit your specific needs. * Application Modernization Receive guidance on modernizing applications to enhance performance and maximize AWS capabilities. Your one-stop destination for Cloud Cost Optimization * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud. * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure. **Related Resources** * Why Choose AWS MAP for Your Cloud Migration Journey? This blog delves into AWS MAP comprehensively, highlighting its advantages, essential elements, and how it expedites the cloud migration process while guaranteeing sustained success. Blog * Learn how to get a streamlined and cost optimized AWS infrastructure from industry experts “Due to multiple billing accounts, initially the AWS infrastructure was really messy” - Arif Shanji, Senior VP, Engineering, Wahed. Get expert recommendations on how minimize the cloud cost spends. On-Demand Webinars * AWS Migration: On-Premise Data Center to Cloud in 7 Steps Are you planning to deploy your data, applications and other business elements on the AWS cloud? Read on to learn how you can optimize the process. Blog Frequently Asked **Questions** * ### Arrow 1.What is the AWS Migration Acceleration Program (MAP)? Q1. What is the AWS Migration Acceleration Program (MAP)? The AWS Migration Acceleration Program (MAP) is a structured cloud migration framework based on AWS's experience migrating thousands of enterprises. AWS MAP uses a three-phase approach—Assess, Mobilize, and Migrate & Modernize—to reduce risks, costs, and complexity. It offers tailored tools, training, partner expertise, and AWS investments to build a strong cloud foundation. * ### Arrow 2.Why should I choose AWS MAP for migration? Q2. Why should I choose AWS MAP for migration? AWS MAP reduces the complexity, cost, and risks of cloud migration with expert guidance, automation tools, financial incentives, and a structured three-phase approach. * ### Arrow 3.What are the phases of the AWS MAP framework? Q3. What are the phases of the AWS MAP framework? * **Assess** : Evaluate readiness and build a business case for migration. * **Mobilize** : Prepare the environment and address any gaps. * **Migrate & Modernize**: Execute the migration and optimize workloads for the cloud. * ### Arrow 4.Why choose CloudKeeper for AWS MAP? Q4. Why choose CloudKeeper for AWS MAP? AWS Partners, part of the AWS Partner Network (APN), bring specialized expertise and experience to assist organizations throughout their migration journey, offering guidance, solutions, and support tailored to specific needs. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Our AWS Premier Partnership Highlights * An AWS Premier Consulting Partner since 2018 * AWS Partner Network (APN) Distinction for 100+ Certifications * Top 5 Ranking in the AWS Well-Architected Challenge, 2023 * Top AWS Reseller through Solution Provider Program * 100% Compliance in the AWS Managed Services Provider Audit * 300+ AWS Customer Launches Completed * AWS Channel Partner Private Offer (CPPO) Partnership * AWS qualified provider to deliver Partner-led Enterprise Support * Ability to manage billing for AISPL as well as Amazon Inc. accounts Our AWS Premier Partner Programs * AWS Managed Service Provider Delivering proactive management, monitoring, and optimization of your AWS environments. * AWS Public Sector Partner Empowering government, education, and nonprofit organizations with specialized cloud solutions. * AWS Solution Provider Access exclusive partner discounts, flexible contracting options, expert guidance, and round-the-clock support. * AWS Well-Architected Partner Program Optimizing cloud architectures for performance, security, and cost-efficiency powered by expert guidance and best practices aligned with the AWS Well-Architected Framework. * AWS Channel Partner Delivering end-to-end AWS cloud solutions and services through a network of expert partners, ensuring seamless implementation, integration, and support. Our AWS Competencies * DevOps Services Competency Streamline your development and operations with our expert DevOps solutions, ensuring faster delivery and enhanced scalability. * Migration Services Competency Seamlessly transition your workloads to the cloud with our comprehensive migration services, minimizing downtime and maximizing efficiency. * Data & Analytics Services Competency Unlock the full potential of your data with our advanced analytics services, facilitating actionable insights and informed decision-making. * AI Services Competency Kickstart your AI journey with our proven expertise, enabling you to build, deploy, and scale production-grade AI solutions. Our AWS Service Validations * Amazon RDS Delivery Expert deployment and management of Amazon RDS for scalable and secure relational database solutions. * Amazon CloudFront Delivery Efficient and reliable content delivery using Amazon CloudFront for fast, global access to your applications. * Amazon EMR Delivery Seamless deployment of Amazon EMR for big data analytics, and machine learning with scalable Hadoop clusters. * AWS Graviton Delivery Smooth migration, optimized performance, and efficient management of Graviton-based instances. Our AWS Certifications In-depth expertise with over 100 certifications spanning critical AWS roles and specialties * Our AWS Specific Offerings Explore our specialized AWS offerings designed to optimize your cloud experience * CloudKeeper Commit An AI-powered platform for Automated AWS RI Management, delivering on-demand EC2 instances at 3 year RI pricing. * CloudKeeper PPA+ Enhance your AWS Enterprise Discount Program benefits with additional discounts, lower commitments, and reduced AWS Enterprise Support costs. * CloudKeeper Lens Gain comprehensive cloud cost visibility with resource-level breakdowns, periodic reports, and insights into data transfer costs. * AWS Well-Architected Reviews Benchmark your infrastructure against the best practices and design principles created by cloud and FinOps experts. We are on * * * * * * * ‹› CloudKeeper Commit CloudKeeper Lens Well-Architected Review **Related Resources** * From Good to Great: Supercharge Your AWS EDP Plan with a Partner Learn how partnering with the right AWS EDP partner can simplify the complexities of AWS EDP, helping you secure great benefits at lower commitments & cost. Blog * FinOps Vendor Ecosystem you should know before nailing your Cloud Optimization Strategy Learn about the dynamics of the FinOps market and the FinOps Vendor Ecosystem to help you choose the right FinOps Partner and implement an effective Cloud Cost Optimization Strategy. Whitepapers * How to avoid the ‘AWS Flexibility Tax’ with CloudKeeper? For AWS users, it is always hard to balance operational flexibility and cloud costs. Learn how to dodge this ‘Flexibility Tax’ with the help of CloudKeeper. Blog Frequently Asked **Questions** * ### Arrow 1.What is an AWS Partner Network (APN)? Q1. What is an AWS Partner Network (APN)? The AWS Partner Network (APN) is a global community of technology and consulting companies that leverage Amazon Web Services (AWS) to build solutions and services for customers. Key Benefits of the AWS Partner Network * Specialized Expertise: APN Partners offer deep knowledge in specific industries, workloads, or solutions, helping customers implement AWS services more effectively. * Innovative Solutions: APN Technology Partners provide advanced tools that enhance AWS’s native capabilities, such as additional security features, cost optimization, and performance management. * Enhanced Support: AWS Partners offer support services that can extend beyond AWS’s native support, often with tailored, hands-on assistance. * ### Arrow 2.Who is an AWS Partner? Q2. Who is an AWS Partner? An AWS Partner is an organization approved by AWS to offer expert services, solutions, and support for AWS cloud environments. * ### Arrow 3.Why should I work with an AWS Partner? Q3. Why should I work with an AWS Partner? Working with an AWS Partner can provide you access to specialized knowledge, advanced tools, and tailored solutions that simplify cloud management, optimize costs, and improve overall performance. * ### Arrow 4.How does working with an AWS Partner differ from working directly with AWS? Q4. How does working with an AWS Partner differ from working directly with AWS? With extensive experience working with diverse customers, AWS Partners bring specialized insights, customized services, and often exclusive solutions tailored to specific needs. CloudKeeper as an AWS Partner, for example, goes beyond basic AWS offerings by providing cost management, deep-dive assessments, and expert guidance on AWS architecture to maximize your cloud investment. * ### Arrow 5.What are the AWS Partner Tiers? Q5. What are the AWS Partner Tiers? AWS has three Partner Tiers — Select, Advanced, and Premier — designed to recognize organizations based on their technical expertise and customer success. As partners progress through these tiers, they unlock more benefits and resources. * Select Tier: Partners with certified professionals and proven customer experience. * Advanced Tier: Partners with a strong team of certified experts and successful AWS deployments. * Premier Tier: Top-tier partners with deep expertise, multiple validations, and large-scale customer success. **CloudKeeper is a certified AWS Premier partner.** * ### Arrow 6.What is the difference between an AWS consulting partner and a technology partner? Q6. What is the difference between an AWS consulting partner and a technology partner? The main difference between AWS consulting partners and AWS technology partners is that consulting partners provide guidance and services, while technology partners build products and services. Both types of partners are part of the AWS Partner Network, they have distinct roles. **Consulting Partner:** Offers strategic guidance, cloud migrations, system integration, and ongoing support for AWS environments. Example: System integrators and managed service providers. **Technology Partner:** Develops software and tools that integrate with or enhance AWS services, such as security or monitoring solutions. Example: Independent software vendors (ISVs) and SaaS providers. * ### Arrow 7.What specific benefits does CloudKeeper offer as an AWS Partner? Q7. What specific benefits does CloudKeeper offer as an AWS Partner? As an AWS Partner, CloudKeeper offers end-to-end cloud cost optimization, deep AWS expertise, and comprehensive support. Our team brings in-depth expertise with over 100 certifications spanning critical AWS roles and specialties. From cloud migration to cloud cost savings, AWS Well-Architected Reviews to AWS Enterprise support, cloud cost visibility to 24*7 expert guidance & support, CloudKeeper covers it all, as your AWS Partner. * ### Arrow 8.What is the process to get started with CloudKeeper as my AWS partner? Q8. What is the process to get started with CloudKeeper as my AWS partner? To get started, simply reach out to our team for a consultation. We’ll analyze your AWS environment, develop an optimization strategy, and guide you through the implementation to ensure maximum savings and efficiency. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close ✕ * * * * * * Driving AWS Growth Through Sustainable Cloud Optimization Helping Customers Save More, Reinvest Faster, and Grow on AWS How CloudKeeper Accelerates AWS Commercial Outcomes We partner closely with AWS account teams to help customers optimize their AWS environments, unlock measurable savings, and confidently reinvest those savings into innovation, modernization, and expansion on AWS. ### Stronger PPA confidence * Higher savings, lower customer commitment * Faster conversions, validated outcomes * Greater confidence at deal close * Low-cost Partner-led Services (Optional) **How CloudKeeper PPA+ Helps Accelerate Closures** An AWS seller guide to re-risk PPAs, improve customer confidence, and close deals faster ### Technical support driving reinvestment * Unlimited access to certified AWS experts * Offshore capacity accelerates initiatives * 90%+ services delivered at no cost * Savings reinvested into innovation, growth **CloudKeeper Growth Accelerator** Unlimited Solutions Architect-as-a-Service with access to CloudKeeper Tuner and Lens for six weeks Proven Commercial Outcomes 1 **25%** average YoY customer growth 2 **31%** average YoY growth for PPA customers Our AWS Partnership Highlights * An AWS Premier Consulting Partner since 2013 * AWS Partner Network (APN) Distinction for 100+ Certifications * Top 5 Ranking in the AWS Well-Architected Challenge, 2023 * Top Reseller through AWS Solution Provider Program * 100% Compliance in the AWS Managed Services Provider Audit * 300+ AWS Customer Launches Completed * AWS Channel Partner Private Offer (CPPO) Partnership * AWS qualified provider to deliver Partner-led Enterprise Support * Ability to manage billing for AISPL as well as Amazon Inc. accounts Our AWS Partner Programs * AWS Managed Service Provider Delivering proactive management, monitoring, and optimization of your AWS environments. * AWS Public Sector Partner Empowering government, education, and nonprofit organizations with specialized cloud solutions. * AWS Solution Provider Access exclusive partner discounts, flexible contracting options, expert guidance, and round-the-clock support. * Well-Architected Partner Program Optimizing cloud architectures for performance, security, and cost-efficiency powered by expert guidance and best practices aligned with the AWS Well-Architected Framework. * AWS Channel Partner Delivering end-to-end AWS cloud solutions and services through a network of expert partners, ensuring seamless implementation, integration, and support. Our AWS Competencies * DevOps Services Competency Streamline your development and operations with our expert DevOps solutions, ensuring faster delivery and enhanced scalability. * Migration Services Competency Seamlessly transition your workloads to the cloud with our comprehensive migration services, minimizing downtime and maximizing efficiency. * Data & Analytics Services Competency Unlock the full potential of your data with our advanced analytics services, facilitating actionable insights and informed decision-making. Our AWS Service Validations * Amazon RDS Delivery Expert deployment and management of Amazon RDS for scalable and secure relational database solutions. * Amazon CloudFront Delivery Efficient and reliable content delivery using Amazon CloudFront for fast, global access to your applications. * Amazon EMR Delivery Seamless deployment of Amazon EMR for big data analytics, and machine learning with scalable Hadoop clusters. * AWS Graviton Delivery Smooth migration, optimized performance, and efficient management of Graviton-based instances. * AWS ECS Delivery Proven expertise in architecting, deploying, and optimizing AWS ECS environments for mission-critical workloads. We are on * * * * * * * ‹› CloudKeeper Commit CloudKeeper Lens Well-Architected Review Customer Success Stories Trusted for expertise, innovation and a dependable support model A Generative AI-based platform that helps companies automate document intake, data entry, and related workflows for legal, healthcare, and financial services. #### Challenges * Production downtime * EKS/RDS instability * Scaling global workforce #### How we helped * Amazon EKS v1.30 upgrade * CloudWatch performance tuning * Policy-driven Workspaces Other Key Highlights **126% Growth** ($600k → $1.4M) **700+** Man-hours saved **$200k** cost avoidance A marketing company that connects millions of local consumers to the businesses they need and helps boost the revenue and retention rates of local, regional, and national businesses. #### Challenges * High AWS spend * Low cost visibility * Manual RI/SP management #### How we helped * 100% EC2 reservation coverage * Rightsizing EC2, RDS, & S3 * Automated anomaly detection Other Key Highlights **10%** Instant savings **15%** Savings by waste reduction Well-Architected Reviews A Generative AI-based platform that helps companies automate document intake, data entry, and related workflows for legal, healthcare, and financial services. #### Challenges * Production downtime * EKS/RDS instability * Scaling global workforce #### How we helped * Amazon EKS v1.30 upgrade * CloudWatch performance tuning * Policy-driven Workspaces Other Key Highlights **126% Growth** ($600k → $1.4M) **700+** Man-hours saved **$200k** cost avoidance A marketing company that connects millions of local consumers to the businesses they need and helps boost the revenue and retention rates of local, regional, and national businesses. #### Challenges * High AWS spend * Low cost visibility * Manual RI/SP management #### How we helped * 100% EC2 reservation coverage * Rightsizing EC2, RDS, & S3 * Automated anomaly detection Other Key Highlights **10%** Instant savings **15%** Savings by waste reduction Well-Architected Reviews A Generative AI-based platform that helps companies automate document intake, data entry, and related workflows for legal, healthcare, and financial services. #### Challenges * Production downtime * EKS/RDS instability * Scaling global workforce #### How we helped * Amazon EKS v1.30 upgrade * CloudWatch performance tuning * Policy-driven Workspaces Other Key Highlights **126% Growth** ($600k → $1.4M) **700+** Man-hours saved **$200k** cost avoidance A marketing company that connects millions of local consumers to the businesses they need and helps boost the revenue and retention rates of local, regional, and national businesses. #### Challenges * High AWS spend * Low cost visibility * Manual RI/SP management #### How we helped * 100% EC2 reservation coverage * Rightsizing EC2, RDS, & S3 * Automated anomaly detection Other Key Highlights **10%** Instant savings **15%** Savings by waste reduction Well-Architected Reviews ‹› **** **** **Simplify commitments, strengthen outcomes, and accelerate deals with CloudKeeper by your side** close close Negotiating **an AWS PPA is complex—and risky if done wrong** * Getting locked into the wrong commitments Overcommit, and you're stuck overspending. Undercommit, and you leave money on the table. Either way, you lose. * Not just a discount - it’s complicated An AWS PPA/EDP comes with layers of clauses, terms, and timelines. Without the right help, it’s easy to miss something important. * Too many variables involved Future workloads, instance types, team expansion, service migrations; AWS PPA/EDP planning demands analyzing many critical factors. * AWS has the advantage They have the data, experts, and experience. If you’re not coming to the table equally prepared, it’s hard to come out ahead. * Great teams still need AWS experts Your team may be sharp, but they’re not AWS specialists. To get the best deal, you need someone who knows AWS inside out. Here’s how **CloudKeeper helps you win your best AWS PPA deal** * Smarter Commitment Planning We go beyond past usage. Our experts & tools help you forecast with precision by factoring in short & long-term goals, growth plans, seasonality, and service adoption trends. We help you determine a data-backed commitment value that’s built for today’s needs and tomorrow’s scale. * Bigger Discounts. Better Terms. We go beyond average benchmarks. With our deep AWS expertise and proven negotiation tactics, we help secure more favorable terms that most businesses can’t access on their own, whether that’s higher discounts, lower annual commitments, or both. * End-to-End Support From planning and modeling to actual negotiation and contract closure, we guide you through every step to secure the most cost-effective and value-driven AWS PPA/EDP deal. Our experts navigate all the complexities for you and ensure an agreement that maximizes both savings and flexibility. And there’s more! AWS PPA Success Management We help ensure your AWS PPA/EDP stays a growth enabler, not a cost liability. Our team of 100+ AWS-certified experts takes away the burden of continuous optimization. From proactive cost audits to architecture reviews and service tuning, we take care of it all. * We've got a deep discount with our EDP commitment and great support from the team so far. Don’t just take what’s offered, shape the deal you deserve. Whether you're entering your first AWS PPA/EDP or renegotiating a renewal, we're here to help you get it right. AWS PPA/EDP Explained, from AWS re:Invent 2023 Go Beyond Standard AWS PPA with CloudKeeper PPA+ Additional Discounts, Lower Annual Commitments, Discounted Price on AWS Support, and a lot more. Our Global Customers **Related Resources** * A practical guide to AWS EDP Learn how AWS EDP helps businesses save on cloud costs, scale efficiently, and unlock growth. Discover strategies, use cases, and expert insights. Whitepapers * From Good to Great: Supercharge Your AWS EDP Plan with a Partner Learn how partnering with the right AWS EDP partner can simplify the complexities of AWS EDP, helping you secure great benefits at lower commitments & cost. Blog * An Essential Guide to AWS EDP to Bag High Discounts The AWS Enterprise Discount Program (AWS EDP) is an enterprise-level cloud program with substantial benefits on their AWS cloud spending. Blog Frequently Asked **Questions** * ### Arrow 1.When is the right time to call CloudKeeper? Q1. When is the right time to call CloudKeeper? The best time to engage us is before negotiations even begin—ideally 3 to 6 months in advance. That’s when we can bring the most value: helping you forecast accurately, plan your commitments smartly, and build a strong negotiation plan. Whether you're just starting to explore options or nearing renewal, CloudKeeper is with you from day one to signature day—guiding you every step of the way. * ### Arrow 2.How much time does the AWS PPA negotiation process take? Q2. How much time does the AWS PPA negotiation process take? On average, the process could take a minimum of 4 weeks. That said, timelines vary based on your internal approvals, AWS response time, and contract complexity. Starting the planning phase early helps keep things smooth and stress-free. * ### Arrow 3.Will you work directly with AWS on our behalf? Q3. Will you work directly with AWS on our behalf? Yes. We act as your extended team, guiding you through the process and even engaging with AWS alongside you to help drive the best outcomes. * ### Arrow 4.Can CloudKeeper support us in the AWS PPA/EDP renewal negotiation process? Q4. Can CloudKeeper support us in the AWS PPA/EDP renewal negotiation process? Absolutely. In fact, renewals are a great opportunity to renegotiate terms and unlock better value. We’ll help you make the most of it. * ### Arrow 5.What if I’ve already signed an AWS PPA? Q5. What if I’ve already signed an AWS PPA? No worries—we can still add value. Even if your AWS PPA/EDP is active, we help optimize how you use it. From cost-saving recommendations to continuous optimization and usage tracking, we can ensure you get the most from your contract. And when it’s time for renewal, we’ll be right there to help you negotiate a better deal. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close close Our visual tale at AWS re:Invent 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ‹› In the Spotlight: Lightning Theatre Session by Aman Aggarwal Considerations for using an AWS Enterprise Discount Program For AWS enterprise customers, an AWS Enterprise Discount Program (EDP) might be on your radar as a premier savings route. In this lightning talk, Aman explained the advantages and disadvantages of an EDP, determining your ideal annual commitment amount and span, how to maximize the benefits of an EDP while retaining flexibility, and using CloudKeeper EDP+ for extended gains and flexibility. Aman Aggarwal Business Head, CloudKeeper Did you miss catching up with us at AWS re: Invent? No worries! You can still connect with our AWS experts. CloudKeeper - an AWS FinOps & Cost Optimization Solution Get instant & guaranteed savings of up to 25% on the entire AWS bill. No Cost No Effort No Access No Lock-in Unlock potential savings on your **AWS cloud usage** We have a comprehensive suite of **AWS FinOps and cost optimization solutions** tailored to meet the unique needs of different customer segments. * CloudKeeper AZ Savings, Software, and Services bundled together * Guaranteed Savings * Access to CloudKeeper Lens * Access to FinOps Experts * CloudKeeper Auto Zero-Touch, AI-driven AWS RI management * RI-like Pricing for Compute & RDS Instances * No Commitment * Buy-back Guarantee of Unused RIs * CloudKeeper EDP+ Unlock maximum potential of AWS EDP * Additional discounts on your committed usage * Lower Annual Commit * Discounted Price on AWS Support All these along with complimentary access to Cloud cost visibility & recommendation platform- CloudKeeper Lens & FinOps consulting from AWS certified experts * CloudKeeper Lens Track, Analyze, & Optimize your cloud usage with our cost visibility & recommendation platform- * Resource-level Cost Visibility * RI & Savings Plan Utilization * Report Daily Breakup * Cost optimization recommendations * FinOps Support & Consulting Establish FinOps culture & set up cost-efficient cloud operations- * AWS Well-Architected Reviews * Cost Governance Guardrails * Defining & Measuring FinOps KPIs * Commitment Planning & Management Why Choose CloudKeeper as Your FinOps Partner? $100 Mn+ Savings delivered to our customers 20% Average savings on the entire cloud bill 300+ Cloud & DevOps Professionals 12+ Years of Cloud Expertise A Glimpse of **Our Customers** $100 Million+ in Annual Savings Delivered Across 300+ Customers * USA Canada India Australia SEA Europe * Pennsylvania Vancouver Mumbai Perth Singapore London * Los Angeles Toronto Mumbai South Yarra VIC Jakarta Fife * Arkansas Petaluma Delhi NCR Brisbane Singapore London * Chicago Quebec Delhi NCR Collingwood Indonesia Alton What do our Clients Say? Hear it from those who matter most - **our valued customers**. Watch the technology leaders sharing their **first-hand experience with CloudKeeper.** **Steven Thurlow** CEO **Ben Rhodes** Program Director **Prateek Baheti** Head of Technology * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Our Azure Partnership Highlights * An Azure CSP Partner since 2019 * Multiple Competencies and Partner Programs * 30+ Certified Azure Experts * Solutions listed on the Microsoft Azure Marketplace Our Azure Competencies * ## Digital and App Innovation Creating and modernizing applications, enhancing digital experiences, and driving innovation using Azure cloud services. * ## Data and AI Expertise in harnessing the power of data and artificial intelligence to provide insightful analytics and AI-driven solutions on Azure. Our Azure Services * ## Consulting Leverage our Azure consulting expertise to align your cloud solutions with your business goals for optimal outcomes. * ## Deployment / Migration Proven methodologies to seamlessly deploy and migrate your applications and infrastructure to Azure, with minimal disruption. * ## Well-Architected Review Benchmark against the Azure Well-Architected Framework, optimizing for security, reliability, cost efficiency, and performance. Our Azure Solution Categories * Azure Stack Bring the power of Azure to your on-premises environment with our Azure Stack implementation expertise. * Cloud Database Migration Move your databases to the cloud seamlessly with our secure and efficient cloud database migration services. * Data Warehouse Make smarter business decisions with our expert data warehouse design and implementation services. * DevOps Streamline development and operations on Azure with our DevOps solutions, enhancing agility, collaboration, and continuous delivery. * Developer Tools Empower your development teams with Azure developer tools, enabling efficient coding, testing, and deployment of applications. * Microservice Applications Build scalable and resilient microservice applications on Azure with our expert guidance and support. Our Azure Certifications * * * * * * * * * * Our Azure specific Solutions Superior cost visibility, optimal savings, and enhanced performance with customized cost optimization solutions for your Azure infrastructure. * CloudKeeper Lens Offers real-time insights, cloud cost optimization recommendations, a granular view of your cloud spending, and periodic cost and usage reports. * Azure Well-Architected Reviews Optimize your architecture, streamline operations, and achieve a steady ROI on cloud investments, with the Azure Well-Architected Framework principles. We are on **Related Resources** * Top 10 Azure cost optimization best practices Uncover key strategies to cut Azure costs! Learn the top 10 Azure cost optimization practices for efficiency & savings. Start maximizing your budget today! Blog * Understanding Azure Well-Architected Review: A Blueprint for Cloud Excellence Discover the Azure Well-Architected Review and its role in crafting cloud excellence. Learn how to optimize your Azure cloud with this insightful guide. Blog * A Comprehensive Guide to Azure Cost Optimization Master Azure cost optimization with strategies and best practices. Control spending, maximize value, and ensure long-term success in the cloud. Blog Frequently Asked **Questions** * ### Arrow 1.Who is an Azure Partner? Q1. Who is an Azure Partner? An Azure Partner is a company or service provider that has been recognized by Microsoft for its expertise in delivering solutions built on Azure, offering services such as cloud migration, optimization, security, and support. * ### Arrow 2.What benefits does CloudKeeper offer as an Azure Partner? Q2. What benefits does CloudKeeper offer as an Azure Partner? As an Azure Partner, CloudKeeper provides end-to-end cloud cost optimization, tailored Azure solutions, 24*7 expert support, and guidance to help businesses reduce their Azure costs, improve efficiency, and scale their cloud environment effectively. We have a strong team that brings in-depth expertise spanning critical Azure roles and specialties. * ### Arrow 3.What is the process to get started with CloudKeeper as my Azure partner? Q3. What is the process to get started with CloudKeeper as my Azure partner? To get started, simply reach out to our team for a consultation. We’ll analyze your Azure environment, develop an optimization strategy, and guide you through the implementation to ensure maximum savings and efficiency. * ### Arrow 4.How do I find the right Azure Partner for my business? Q4. How do I find the right Azure Partner for my business? To choose the right Azure Partner, look for a provider with relevant experience, industry expertise, and certifications. Consider your specific needs (e.g., migration, optimization, or security) and assess the partner’s track record of success with Azure. * ### Arrow 5. How does working with an Azure Partner differ from working directly with Azure? Q5. How does working with an Azure Partner differ from working directly with Azure? Working with an Azure Partner provides businesses with added value through expert guidance, customized solutions, and industry-specific insights. While Azure offers core cloud services, an Azure Partner like CloudKeeper focuses on optimizing your cloud environment, helping with cost management, providing tailored recommendations, and ensuring that your cloud infrastructure is set up for success. This collaborative approach ensures you get the most out of your Azure investment with strategic, hands-on support. * ### Arrow 6.What types of Azure Partners are there? Q6. What types of Azure Partners are there? Azure Partners come in various forms, including Managed Service Providers (MSPs), Independent Software Vendors (ISVs), System Integrators (SIs), and Cloud Solution Providers (CSPs), each offering specific expertise in Azure solutions. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * Thank you **for downloading our report** About CloudKeeper CloudKeeper is a cloud cost optimization partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & usage optimization platform to reduce cloud costs & help maximize the value from the cloud. We have helped **400+ global companies** save an average of **20% on their cloud bills** , all while maintaining flexibility and avoiding any long-term commitments or costs. We have expertise across leading cloud platforms * * close close ## What makes CloudKeeper an awesome workplace? If you are a focused and ambitious individual looking for an exciting workplace to scale new heights in your career, you will love us. * Collaborate with the Coolest Minds Learn and evolve with a diverse team passionate about bringing meaningful changes in the cloud community. * Growth Mindset Your growth extends beyond your job title. We empower you to propose and test innovative ideas that make a difference. * Celebrating CKers’ Milestones The growth of a CKer is the growth of CloudKeeper and together we celebrate this. * Mindful Working We focus on results rather than hours worked and allow employees to figure out the balance between their work and their lives. * Care for our People We conduct health and mindfulness sessions to guide our employees in maintaining a healthy and positive lifestyle. * Supporting a Career you Love Your passion is as unique as you are. Thus, we provide opportunities across various roles to match your unique skills and interests. ## Beyond Work: A Culture of Growth, Trust & Transparency * Knowledge Sessions We help CKers develop soft skills and technical knowledge through our learning sessions. * CloudKeeper Townhall We regularly share performance updates, setbacks, and milestones. * One-on-one with CEO We discuss our employees' queries and concerns. * Upskill & Stand Out We sponsor certifications to help you build in-demand skills and stay competitive. * Celebrating Success We believe that every achievement, big or small, deserves to be celebrated! ## Why CloudKeeper? Let CKers Tell You * Working at CloudKeeper has been an incredible experience. The culture here is supportive and collaborative, making every day enjoyable. The leadership team is approachable and always willing to listen, fostering an inclusive and empowering environment. ### Saloni Phutela Director - Marketing * CloudKeeper truly values its employees. The collaborative culture and supportive colleagues make every day enjoyable and that foster personal growth. There’s always someone to help you and push you to achieve more. It has been a great journey here! ### Abhishek Sahni Sr. FinOps & Cloud Consultant * From being one of the first few employees to leading a new practice, the opportunities to experiment and take risks is what keeps me going. ### Aman Aggarwal Business Head * Cloudkeeper has been an amazing place to grow both personally and professionally. Collaborative environment and continuous improvement helped me grow not just as an engineer, but also as a team player. ### Yasmine Choudhary Software Engineer * Working at CloudKeeper has been an incredible experience. The culture here is supportive and collaborative, making every day enjoyable. The leadership team is approachable and always willing to listen, fostering an inclusive and empowering environment. ### Saloni Phutela Director - Marketing * CloudKeeper truly values its employees. The collaborative culture and supportive colleagues make every day enjoyable and that foster personal growth. There’s always someone to help you and push you to achieve more. It has been a great journey here! ### Abhishek Sahni Sr. FinOps & Cloud Consultant * From being one of the first few employees to leading a new practice, the opportunities to experiment and take risks is what keeps me going. ### Aman Aggarwal Business Head * Cloudkeeper has been an amazing place to grow both personally and professionally. Collaborative environment and continuous improvement helped me grow not just as an engineer, but also as a team player. ### Yasmine Choudhary Software Engineer ‹› Be the first to know the latest Cloud & FinOps insights and news! More to Explore * What's in the news? Stay updated with the latest and greatest happenings at CloudKeeper! * Who We Are? Learn more about our milestones and journey so far. * Thought Leadership! Read the latest and exclusive content curated by FinOps and cloud professionals. Frequently Asked **Questions** * ### Arrow 1.What are the growth opportunities at CloudKeeper? Q1. What are the growth opportunities at CloudKeeper? We offer extensive opportunities for professional and personal development. You'll have the chance to learn new skills, take on challenging assignments, and advance your career. * ### Arrow 2.How can I apply for a job at CloudKeeper? Q2. How can I apply for a job at CloudKeeper? You can explore the jobs listed on our careers page, select the role that best fits your skills and interests, and submit your resume. If you don’t see the relevant job listed on our portal, please feel free to share your resume at * ### Arrow 3.What is the hiring process like at CloudKeeper? Q3. What is the hiring process like at CloudKeeper? Our hiring process typically involves an initial application review, followed by interview rounds with our HR team and relevant competency leaders. Depending on the position, there may also be assessments or case studies. * ### Arrow 4.Does CloudKeeper offer a mentorship program? Q4. Does CloudKeeper offer a mentorship program? Yes, we believe in investing in our employees' growth and development. We offer mentorship programs that connect you with an experienced colleague who can provide guidance and support throughout your career journey at CloudKeeper. * ### Arrow 5.How can I stay updated on the latest job openings at CloudKeeper? Q5. How can I stay updated on the latest job openings at CloudKeeper? To stay updated on the latest job openings at CloudKeeper, follow us on our * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close ## Cloud Cost Optimization Services ### Maximize Efficiency. Minimize Cloud Spending. Scale Effortlessly Our cloud cost optimization services help organizations streamline their cloud usage, reduce unnecessary costs, and maintain performance while staying aligned with their financial goals. We act as your cloud cost management vertical, empowering your team to dedicate their time to driving growth and innovation. The Challenges we solve through Cloud Cost optimization Services * Establishing a FinOps Culture * Lack of Cloud Cost Visibility * Commitment Management * Inefficient & Under-Optimized Cloud Architectures * Cost Optimization without compromising performance * Multi-cloud management & Complex Cloud Migrations The Cloud Cost Optimization Services by CloudKeeper We provide a range of Cloud Cost Optimization Services covering everything from consulting, advisory, and implementation to ongoing management and continuous improvement, all at no extra cost! * Consult * FinOps consulting & support * Well-Architected Reviews for AWS, Azure & GCP * Implement * Cloud Migration Planning & Implementation * Cloud Modernization Strategies * Manage * 24*7 Personalized Cloud Support * AWS Enterprise at a discounted price * Improve * Architecture Guidance & Cost Optimization Support * DevOps Ensure your infrastructure is always optimized and future-proof. Our Cloud Cost Optimization Services’ Methodology - CARA Framework We leverage a unique framework - **CARA (Continuous, Assess, Review, Act)** that drives continuous and comprehensive cloud cost optimization and delivers significant and sustainable enhancements to your cloud infrastructure. How does CARA help? * Average 10-30% reduction in cloud costs within the first 90 days * Continuous optimization, not just a one-time project * Tailored for the unique needs of DNBs * Results-as-a-Service (RaaS) approach ensures tangible outcomes ### Why Choose Our Cloud Cost Optimization Services? * Certified & Experienced Team Our team of 150+ solutions architects & cloud experts holds extensive cloud certifications and proven experience across various cloud platforms. * Personalized Approach We tailor our support to your specific needs and cloud environment. * Proactive Management We go beyond reactive support and proactively identify potential issues to prevent downtime. * Leader in Cloud Cloud Cost Management Highly rated and a leader in Cloud Cost Management Platform on G2 - 4.6/5 ratings. * Backed by Industry Recognitions Recognized by IDC, Everest Group, ISG, Gartner, and Forrester. * A proven track record of success 400+ customers' success stories from all across the globe. Choose effortless cloud cost optimization today. ### The Impact of Our Cloud Cost Optimization Services * Continuous cost-efficient operations Cloud cost optimization is not a one-time fix our services ensure your cloud environment remains cost-efficient over time. * Streamlined Cloud Operations with Cloud FinOps Our Cloud Cost Optimization Services incorporate Cloud FinOps practices into our approach, bringing finance, IT, and operations teams together to optimize cloud usage. * Modern & Scalable Infrastructure Regular audits ensure your infra stays updated with the latest cloud cost optimization best practices while scaling efficiently to meet growing workloads. * Real-Time Tracking Monitor spending trends to prevent surprises, and stay within budget & forecast better. * Operational Efficiency Utilize the right tools and workflows to balance cost with performance. * Guaranteed Cost Savings Our cloud cost-saving strategies guarantee savings. Our Customer Voices **CloudKeeper is the best cloud partner. They value our time/cost/infra and provide a proper solution**. The team is always available on time. Every person in the team is supportive & energetic at work. Binod Tiwari Manager - Cloud & Virtualization It's nice to have partnered with CloudKeeper for cloud cost optimization services. **We keep receiving valuable suggestions from them on the technical and cost front**. We will continue our relationship with CloudKeeper in the future. Atul Singh Cloud & DevOps Architect CloudKeeper is always taking care of our infrastructure costs, providing recommendations for our infrastructure, and coming up with new offers to assist us on how to improve the costs and secure our infrastructure with every AWS service we use. Manuel Martinez Senior DevOps Engineer We have expertise across leading cloud platforms * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud. * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure. * A certified partner helping businesses with full-spectrum of Azure cost optimization solutions & services. Frequently Asked **Questions** * ### Arrow 1.What is Cloud Cost Optimization? Q1. What is Cloud Cost Optimization? Cloud Cost Optimization involves analyzing and adjusting your cloud infrastructure to ensure efficient resource utilization, eliminate waste, and align spending with actual business needs. * ### Arrow 2.What are Cloud Cost Optimization Services? Q2. What are Cloud Cost Optimization Services? Cloud Cost Optimization Services are a set of strategies designed to help organizations effectively manage and reduce their cloud computing expenses while maintaining optimal performance, reliability, and scalability. These services focus on optimizing the use of cloud resources to prevent over-provisioning, minimize waste, and align spending with actual business needs. The goal is to ensure that businesses only pay for what they need and use, without sacrificing the performance or availability of their applications and services. CloudKeeper offers a range of Cloud Cost Optimization Services covering everything from consulting, advisory, and implementation to ongoing management and continuous improvement. * ### Arrow 3.What are the major Benefits of Cloud Cost Optimization Services? Q3. What are the major Benefits of Cloud Cost Optimization Services? Cloud Cost Optimization Services offer several major benefits: * **Reduced Costs:** This is the most obvious benefit. By identifying and eliminating wasteful spending, such as unused resources or inefficient configurations, businesses can significantly lower their cloud bills. * **Improved Efficiency:** Optimizing cloud usage leads to more efficient resource allocation. This means applications run smoothly with the right amount of resources, avoiding bottlenecks and ensuring optimal performance. * **Enhanced Performance:** Right-sizing resources (adjusting them to the exact needs of the workload) directly impacts application performance. Optimized resources can lead to faster loading times, improved user experience, and increased responsiveness. * **Increased Agility:** Cost optimization enables businesses to adapt more quickly to changing demands. By efficiently utilizing resources, businesses can scale up or down as needed, responding to market fluctuations and new opportunities. * **Data-Driven Decisions:** Cloud cost optimization provides valuable insights into cloud usage patterns. This data can be used to make informed decisions about resource allocation, future investments, and overall cloud strategy. * **Better Budgeting and Forecasting:** With a clear understanding of cloud spending, businesses can create more accurate budgets and forecasts. This helps in financial planning and ensures that cloud costs remain within acceptable limits. * **Improved ROI:** By reducing costs and improving efficiency, cloud cost optimization directly contributes to a better return on investment for cloud computing. In essence, Cloud Cost Optimization Services help businesses make the most of their cloud investments by ensuring that resources are used effectively and efficiently, leading to significant cost savings and improved business outcomes. * ### Arrow 4.What is the best cloud strategy for cloud cost optimization? Q4. What is the best cloud strategy for cloud cost optimization? The best cloud strategy for cloud cost optimization focuses on efficient resource usage, leveraging AWS tools, and adopting cost-effective practices. 1. **Right-Size Resources:** Use platforms like CloudKeeper Tuner to manage over-provisioning and under-provisioning. 2. **Use Cost-Efficient Pricing:** Leverage discount programs such as 3. **Optimize Storage:** Transition to S3 Intelligent-Tiering or S3 Glacier for infrequent data. 4. **Enable Auto-Scaling:** Match resource capacity to demand using Auto Scaling and serverless options like AWS Lambda. 5. **Monitor and Govern Costs:** Set up tags, AWS Budgets, and Trusted Advisor to track and optimize spending. 6. **Review Architectures:** Conduct periodic These steps ensure your cloud environment remains cost-effective without compromising performance. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Build Tailor-Made Cloud Frameworks for Your Specific Business Needs with CloudKeeper’s Cloud Architecture Services A robust cloud architecture isn’t just foundational - it’s pivotal for innovation and growth. CloudKeeper leverages deep industry expertise to help you craft bespoke architectures that optimize performance and align seamlessly with your organizational goals. * Comprehensive Architecture Reviews Conducting in-depth evaluations covering architectural, operational, and security aspects to ensure a robust and secure cloud environment. * Strategic Planning & Advisory Offering expert recommendations and guidance for short, mid, and long-term cloud strategies, tailored to your business objectives. * Design & Implementation Assistance Guiding you in crafting bespoke cloud architectures, emphasizing network configuration, infrastructure modernization, and security. * Continuous Optimization and Support Providing ongoing support to address scalability challenges, enhance performance, and implement best practices. Optimize Your Cloud Spending for Peak Cost Efficiency Make sure cloud cost optimization doesn’t take a backseat while your business scales. Gain actionable insights, efficient resource management, and robust cost governance for a sustainable cloud strategy with our Cloud architecture services. * Cost Visibility and Reporting Strategize with insights from CloudKeeper Lens, our proprietary cost analytics platform, offering anomaly detection and detailed reporting. * Resource Planning Optimize resource commitment and management, focusing on waste elimination and efficiency. * Tagging and Spend Accountability Implement cost governance guardrails through effective tagging strategies for transparent spend tracking. * Proactive Support Manage infrastructure events and provide proactive assistance, including billing support, to ensure cost efficiency and operational continuity. * Well-Architected Reviews Get in-depth architectural audits by certified cloud experts, with structured optimization plans for short, medium, and long-term efficiency. * Multi-Cloud **Capabilities** Recognized for proven expertise & certifications across leading cloud platforms. * * Why should you leverage our cloud architecture services? Beyond performance enhancements and cost savings, an architectural update helps you stay ahead with the latest technology, implement security enhancements, and ensures your infrastructure can scale seamlessly with your business needs. * Customized Architectures Tailored cloud solutions to meet your specific business requirements. * Seamless Integration Integrate smoothly with other frameworks and third-party applications for enhanced functionality. * Security Enhancements Implement robust security measures and ensure compliance with industry standards. * Emerging Technologies Integrate emerging technologies like serverless computing and AI/ML to drive innovation and efficiency. * Scalability Planning Design architectures that can scale seamlessly to handle fluctuating workloads and peak user activity. * Application-level Guidance Access specialized guidance and support tailored to your application needs within the cloud environment. **Related Resources** * Maximizing AWS Cost Savings with Serverless Architecture Understand the fundamentals of Serverless Architecture and the best practices to build cost-effective cloud applications using this model. Whitepapers * Cost Optimization with AWS Auto Scaling: Architectural Best Practices and Strategies Guide to AWS Auto Scaling to maximize cost-effectiveness. Learn architectural best practices and strategies to maximize resources, improve output, and reduce costs. Blog * Reducing AWS Data Transfer Costs (Internet Out) with Architecture Optimization and Caching Strategies Learn to reduce AWS Data Transfer Costs with architecture optimization & caching strategies. Streamline data flow, save on expenses, & maximize AWS resources Blog Frequently Asked **Questions** * ### Arrow 1.What is cloud architecture? Q1. What is cloud architecture? Cloud architecture combines technology components like servers, storage, databases, and applications to deliver scalable and efficient cloud-based solutions. It’s about designing reliable, secure, and cost-effective systems, ensuring your business can scale seamlessly while meeting performance and compliance needs. * ### Arrow 2.What are Cloud Architecture Services? Q2. What are Cloud Architecture Services? Cloud architecture services involve designing, optimizing, and managing your cloud infrastructure to ensure it runs efficiently, securely, and cost-effectively. Whether you're just starting or scaling, having the right architecture ensures your applications perform well and remain cost-efficient. * ### Arrow 3.How does CloudKeeper help with cost optimization in cloud architecture? Q3. How does CloudKeeper help with cost optimization in cloud architecture? CloudKeeper offers actionable recommendations to optimize costs, enhance performance, and ensure efficient resource utilization. Our approach includes providing clear cost visibility and detailed reporting, effective resource planning, strategic tagging for spend accountability, proactive support to prevent cost overruns, and conducting Well-Architected Reviews to ensure alignment with best practices for cost efficiency. * ### Arrow 4.What cloud platforms does CloudKeeper support? Q4. What cloud platforms does CloudKeeper support? CloudKeeper supports major cloud platforms, including AWS, Microsoft Azure, and Google Cloud Platform (GCP). Our services are designed to meet the unique requirements of each platform. * ### Arrow 5.Can CloudKeeper assist with multi-cloud or hybrid-cloud environments? Q5. Can CloudKeeper assist with multi-cloud or hybrid-cloud environments? Absolutely! Our experts specialize in multi-cloud and hybrid cloud strategies, helping you optimize costs, improve interoperability, and maintain security across different platforms. * ### Arrow 6.What is the impact of cost optimization? Q6. What is the impact of cost optimization? Cost optimization in the cloud directly and significantly impacts a business's financial and operational efficiency. It reduces unnecessary cloud expenditures by identifying underutilized resources, optimizing resource allocation, and adopting cost-effective pricing models. This results in substantial savings, improved resource utilization, and better scalability. Beyond immediate cost reduction, it enhances forecasting accuracy, enables smarter financial planning, and supports long-term sustainability. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Our Cloud FinOps Consulting & Service Offerings Backed by a team of 150+ certified Cloud & FinOps Professionals, CloudKeeper offers end-to-end Cloud FinOps consulting & support for businesses across the leading cloud platforms, helping them establish a strong FinOps culture & set up cost-efficient cloud operations. * Cost Spend Accountability * Waste Elimination * Commitment Planning & Management * Proactive anomaly detection & notification alerts * Cost Governance Guardrails * Defining & measuring Cloud FinOps KPIs * FinOps Maturity Assessment * FinOps Project Management Our Expertise in Cloud FinOps * Dedicated Team of Certified Experts With us, you gain access to seasoned Cloud FinOps experts, all dedicated to helping you adopt the best practices in FinOps. Results you achieve with our Cloud FinOps offerings * Cost-efficient cloud operations on an ongoing basis * Maximized savings without compromising on performance & security * Benchmark to continuously enhance FinOps maturity * Standard organization- wide processes & tools * Successful adoption of FinOps culture across the organization Our Team in GirnarSoft has a huge cloud infrastructure to manage. **CloudKeeper acts as our FinOps vertical** and helps out in cloud financial management, ensuring that we can focus on our delivery expertise. DevOps Leader, GirnarSoft Our FinOps Customers **Related Resources** * Fumbles in FinOps Adoption and How to Avoid Them Watch this exclusive panel discussion where our industry experts talk about the common mistakes organizations make in their FinOps adoption journey. On-Demand Webinars * Decoding Cloud FinOps : Exploring the Fundamentals Understand the basic concepts of AWS Cloud Cost Optimization, the founding principles of Cloud FinOps, and the three phases of the FinOps Lifecycle. Blog * Unlock the Ultimate Guide to FinOps Strategy & Implementation Understand how to build a FinOps culture, implement cloud FinOps and the best practices to make your team accountable for every penny spent on AWS. Whitepapers Frequently Asked **Questions** * ### Arrow 1.What is FinOps? Q1. What is FinOps? FinOps is an operational framework and cultural practice that unifies finance, technology, and business teams to manage cloud costs more effectively. It brings visibility, accountability, and cost optimization by enabling teams to make data-driven decisions, aligning cloud spend with business value. * ### Arrow 2.How can FinOps consulting benefit my organization? Q2. How can FinOps consulting benefit my organization? FinOps consulting service helps organizations track, measure, and optimize cloud spending through budgeting, forecasting, and cost-allocation practices. * Setting and Measuring FinOps KPIs * Conducting FinOps Maturity Assessments * Ensuring Governance and Compliance * Establishing a Successful FinOps Culture * ### Arrow 3.What is the difference between FinOps consulting and cloud cost management? Q3. What is the difference between FinOps consulting and cloud cost management? FinOps focuses on cross-functional collaboration to achieve cost optimization by integrating finance, operations, and technology teams, while cloud cost management is primarily about tracking and controlling cloud expenses using various tools and practices. * ### Arrow 4.What is the FinOps lifecycle? Q4. What is the FinOps lifecycle? The FinOps life cycle involves the following stages: * **Inform:** Educate teams about cloud costs and financial accountability. * **Optimize:** Identify and implement cost-saving measures. * **Operate:** Continuously monitor and optimize cloud spending. * ### Arrow 5.What does it mean to be FinOps certified? Q5. What does it mean to be FinOps certified? A FinOps certified is someone who has completed comprehensive training in FinOps methodologies and best practices, officially recognized by the FinOps Foundation. This certification demonstrates a proven ability to effectively manage and optimize cloud financial operations, facilitating collaboration between finance, technology, and operations teams to drive financial accountability and cost efficiency in cloud usage. * ### Arrow 6.What results can be achieved with FinOps offerings? Q6. What results can be achieved with FinOps offerings? * Cost-efficient cloud operations that are sustainable and optimized over time * Maximized savings while maintaining high performance and stringent security standards * A benchmark for continuous improvement in FinOps maturity, keeping your organization on the path to financial optimization * Standardized, organization-wide processes and tools to ensure consistent cloud cost management practices * Successful adoption of a FinOps culture across all teams, promoting cross-functional collaboration and financial accountability * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * Amazon coupon worth $50.00 * * * * * * # Stop burning your dollars on bloated AWS bills Why should you **take this challenge** * ### Prove Your Optimization 97% of AWS teams miss critical savings in our 400+ customer analysis. Take 5 minutes to find your blindspots. * ### Find Hidden Savings Careful teams still miss 23% of potential savings. We've found six-figure gaps in "fully optimized" companies. * ### Risk-Free Assessment Our platform needs only read-only access to analyze what your current tools miss. No permissions issues, just insights. * ### 5 Minute Setup Skip weeks-long assessments. Our challenge takes minutes to set up and delivers immediate cost-saving insights. Take up the Challenge & get an #### Amazon coupon* worth $50 The **Challenge Explained** Transform your cloud infrastructure in just 30 days with our proven three-step process * Sign up & Connect AWS Account Securely connect your AWS account with CloudKeeper Tuner * Get Your Cloud Fitness Score Receive a detailed assessment of your cloud usage * Optimize & Save Implement our tailored optimization recommendations What do **our Clients say** Join our growing community of satisfied users who have achieved cloud fitness with CloudKeeper Tuner * We are very happy with the savings on our AWS Bill. I can easily see us making even more substantial savings through their tool and the recommendations they make. They always go above and beyond for every request. ### Arif Shanji Senior VP - Engineering, Wahed * Provided detailed information about the spending and helped us identify the bottlenecks of unused resources. Also, it gives us a fair idea about the projection for the upcoming month's bill. ### Surendra Reddy C V DevOps Tech Lead, Huddl * CloudKeeper Tuner helped identify issues with unused/unallocated resources easily. ### Frequently Asked Questions Everything you need to know about the Cloud Fitness Challenge * ### Arrow 1.How does the 30-Day Cloud Fitness Challenge work? Q1. How does the 30-Day Cloud Fitness Challenge work? Our challenge helps you optimize your AWS infrastructure through a structured approach. We analyze your current setup, provide a detailed assessment, and guide you through implementing cost-saving optimizations. * ### Arrow 2.How can I get the Amazon voucher? Is there an eligibility criteria?* Q2. How can I get the Amazon voucher? Is there an eligibility criteria?* Sign up for the Cloud Fitness Challenge & connect your AWS account. If your AWS bill is over $10,000/month, you'll receive the Amazon voucher. It’s that simple! * ### Arrow 3.Is it safe to connect my AWS account? Q3. Is it safe to connect my AWS account? Yes, absolutely. We use AWS's secure IAM roles with read-only permissions. Your credentials are never stored, and you can revoke access at any time. * ### Arrow 4.What kind of savings can I expect? Q4. What kind of savings can I expect? Our customers typically see 10-15% reduction in their AWS costs within the first month. The exact savings depend on your current setup and usage patterns. * ### Arrow 5.Do I need technical expertise to implement the recommendations? Q5. Do I need technical expertise to implement the recommendations? No, our platform provides step-by-step guidance, and our cloud experts are available to help you implement the optimizations. Ready to get your cloud environment in shape? * About CloudKeeper CloudKeeper is a cloud cost optimization partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & usage optimization platform to reduce cloud costs & help maximize the value from the cloud. We have helped **400+ global companies** save an average of **20% on their cloud bills** , all while maintaining flexibility and avoiding any long-term commitments or costs. We have expertise across leading cloud platforms * * # 2025 Cloud Fitness: 5 Pro-tips for Healthier AWS Infrastructure Watch now to uncover **5 expert-backed tips to reduce costs, enhance performance, and maximize cloud efficiency** —without compromising scalability or adding operational complexity. Who is it for This webinar is especially for, but not limited to: 1. DevOps & Cloud Engineers 2. IT & Cloud Architects 3. CTOs & Tech Leaders Key Takeaways from the webinar were: * Building Cost-Centric Culture for Engineering Teams * Continuous Cloud Wastage Reduction Techniques * Optimizing compute and storage workloads Speakers 1. 2. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close ## About webinar Is your cloud infrastructure costing more than it should? Without the right strategies, inefficiencies can drain resources and inflate expenses. Join us to uncover 5 expert-backed tips to reduce costs, enhance performance, and maximize cloud efficiency—without compromising scalability or adding operational complexity. ## Key Takeaways Join the experts for a 45-minute webinar for * Building Cost-Centric Culture for Engineering Teams * Continuous Cloud Wastage Reduction Techniques * Optimizing compute and storage workloads * Implementing and measuring dollar impact on your usage optimization initiatives ## Who is it for This webinar is especially for, but not limited to: * DevOps & Cloud Engineers * IT & Cloud Architects * CTOs & Tech Leaders ## Meet the Speaker * ### Praneet Chandra Senior Director, CloudKeeper About CloudKeeper CloudKeeper is a cloud cost optimization partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & usage optimization platform to reduce cloud costs & help maximize the value from the cloud. We have helped **400+ global companies** save an average of **20% on their cloud bills** , all while maintaining flexibility and avoiding any long-term commitments or costs. We have expertise across leading cloud platforms * * close close Effortless Cloud Migration for Your Business Success Feeling lost in the cloud migration maze? CloudKeeper is here to help! We partner with you every step of the way, from planning and assessment to launch, ensuring your cloud setup perfectly fits your business needs. This means a seamless journey with zero roadblocks, leading to a scalable, powerful, and cost-effective cloud environment built for your success. CloudKeeper guides you from start to finish with our structured 10-step cloud migration consulting roadmap * ## Assessment We meticulously evaluate your IT infrastructure to understand your needs and craft the best migration path. * ## Planning Based on the assessment, we create a customized plan outlining the migration approach for each application. * ## Rehost This quick-start option involves moving existing applications "as-is" to the cloud with minimal modifications. * ## Replatform We modernize your applications to leverage cloud-native features and services, enhancing performance and scalability. * ## Repurchase We analyze licensing and identify opportunities to optimize costs by transitioning to cost-effective cloud subscriptions. * ## Refactor This approach involves restructuring applications to fully exploit cloud functionalities, maximizing long-term benefits. * ## Retain Not everything needs to move! We help you identify applications better suited for on-premises due to security or compliance. * ## Retire We decommission unused or outdated applications, streamlining your IT landscape and eliminating unnecessary costs. * ## Training Equip your team with the knowledge to manage and utilize the new cloud environment effectively. * ## 24x7 Support We offer ongoing support to address any challenges and continuously optimize your cloud spending for long-term cost-efficiency. Multi-Cloud **Capabilities** With top-tier partnerships and certified cloud professionals, CloudKeeper offers migration expertise across all major cloud providers. * * Get Additional Benefits from the AWS Migration Acceleration Program (MAP) Planning to migrate to the AWS Infrastructure? Ensure a smooth and successful transition with the AWS Migration Acceleration Program (MAP). As an AWS Premier Consulting Partner, CloudKeeper offers comprehensive support, providing you with exclusive benefits such as: * Financial Assistance through AWS Funding * Access to AWS-Certified Cloud Architects * Flexibility with the Program Participation * Support for Application Modernization The CloudKeeper Advantage Over a decade and a half of cloud expertise positions CloudKeeper as your ideal migration partner, helping businesses of all sizes and industries navigate complex cloud journeys. Our seasoned team understands the intricacies of migration strategies and best practices, ensuring a flawless transition with: * Minimal Downtime Keep your business running smoothly during the migration. * Improved Performance Experience faster processing times and a more responsive cloud environment. * DevOps Support Seamlessly integrate your cloud infrastructure with your development and operations workflows. * Security Considerations Prioritize data protection and compliance throughout the migration process. * Workload Modernization Seamless transitions while updating and optimizing workloads, like migration to Graviton-based instances or GP3 storage volumes. * Cost Optimization Expertise Leverage our industry-leading Cloud Cost Optimization solutions which have delivered over $100 million in cloud savings across 400+ customers. Trusted by 400+ Global Customers Our customers saved an average of 20% on their monthly AWS and GCP spend through CloudKeeper **Related Resources** * Choosing the Right AWS Service to Optimize Your Cloud and Beyond Learn how to choose the right AWS service for your needs, that help optimize costs, while simultaneously building modern, scalable applications. Whitepapers * A complete guide to Public Cloud Security Learn some proactive approaches to Cloud workload protection and and gain an in-depth view of how to go about making your workloads on Cloud more secure. Whitepapers * AWS Migration: On-Premise Data Center to Cloud in 7 Steps Are you planning to deploy your data, applications and other business elements on the AWS cloud? Read on to learn how you can optimize the process. Blog Frequently Asked **Questions** * ### Arrow 1.What are Cloud Migration Services? Q1. What are Cloud Migration Services? Cloud migration services involve moving an enterprise's IT infrastructure, including compute, storage, databases, applications, and networks, to a cloud environment. This transition is seamless, ensuring no disruption or data loss. The assets are modernized or virtualized on a cloud platform, which is managed by the cloud provider, eliminating concerns about IT management, maintenance, security, scalability, and upgrades.’ * ### Arrow 2.What are the pros and cons of cloud migration? Q2. What are the pros and cons of cloud migration? Cloud migration offers several advantages, including cost efficiency by reducing hardware and maintenance expenses, scalability to adjust resources as needed, flexibility to access data from anywhere, and enhanced security with disaster recovery options. However, it also comes with challenges like high upfront migration costs, potential downtime during the process, complexity in managing legacy systems, the risk of vendor lock-in, and data security or compliance concerns. With careful planning, the benefits of cloud migration can outweigh the drawbacks. * ### Arrow 3.How do I assess my readiness for cloud migration? Q3. How do I assess my readiness for cloud migration? An effective cloud readiness assessment identifies your current IT landscape, business needs, and goals. It also evaluates the potential risks and benefits of moving to the cloud. * ### Arrow 4.What are the benefits of cloud migration? Q4. What are the benefits of cloud migration? Cloud migration offers several benefits, including reduced IT costs by eliminating on-premise infrastructure and management hassles. It provides on-demand scalability, ensuring smooth operations even during peak traffic. Cloud solutions offer robust security, disaster recovery, and continuous availability. Additionally, businesses can leverage native cloud tools to modernize and digitize operations, improving efficiency and flexibility. * ### Arrow 5.How do you ensure cloud migration is successful? Q5. How do you ensure cloud migration is successful? Successful cloud migration depends on careful planning, having clear goals, using the right tools and technologies, and ongoing testing and optimization during and after the migration process. * ### Arrow 6.What is post-migration optimization, and why is it important? Q6. What is post-migration optimization, and why is it important? Post-migration optimization involves fine-tuning your cloud environment for cost savings, performance, and security. It ensures that your cloud infrastructure is efficient and aligned with business goals after the migration is complete. * ### Arrow 7.What does the cloud migration process look like? Q7. What does the cloud migration process look like? CloudKeeper follows a well-structured 10-step process for cloud migrations which involves the following phases * Assessing your infrastructure to understand your needs * Creating a customized migration plan * Moving applications as-is to the cloud * Modernizing applications to leverage cloud-native features * Managing existing licenses and cloud subscriptions to optimize costs * Further restructuring your applications to fully utilize cloud functionalities * Helping you identify applications to be retained on-premise * Decommissioning unused or outdated applications * Training your team to manage cloud resources effectively * Round-the-clock support and continuous cost-optimization services * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Transform, Re-Engineer, and be Future-Ready in the Cloud Cloud modernization unlocks the full potential of the cloud, allowing you to build an agile, scalable, and cost-effective IT foundation. With a comprehensive 3-phase approach, CloudKeeper guides you from initial assessment to a fully modernized cloud environment. Evaluation and Strategy Development The first step in our cloud modernization journey involves a thorough evaluation of your current IT infrastructure and strategic planning to ensure a smooth cloud transformation. * Cloud Readiness Assessment Analyzing the IT infrastructure to determine its suitability for modernization and identifying goals and desired outcomes. * Business Needs Analysis Diving deep into your business goals to tailor a cloud strategy that meets your objectives. * Modernization Roadmap Developing a phased approach to modernize the existing cloud infrastructure, ensuring a smooth and effective transition. * Security & Compliance Integration Integrating security and compliance best practices into the cloud strategy from the outset. Implementation and Innovation In this phase, the focus is on actualizing the strategic plan through structured implementation and fostering innovation to maximize efficiency and performance. * Infrastructure and Workload Modernization Identifying and prioritizing workloads for modernization, enhancing the cloud environment with automation and AI. * DevOps Pipeline Implementation Establishing automated workflows for continuous integration and delivery (CI/CD) to enhance operational efficiency. * Data Migration and Management Securely migrating and managing data in the cloud, ensuring data integrity and seamless accessibility. * Adoption of New Services Integrating the latest cloud services and technologies to keep the infrastructure cutting-edge. * Third-Party Tech Stack Guidance Providing expert guidance on incorporating third-party technologies to complement and enhance the cloud environment. * Proof of Concept (POC) Develop and test new solutions quickly with Proof of Concept services, reducing time to market. Continuous Management and Support Ongoing support and refinement are crucial for maintaining a robust cloud environment. This phase focuses on continuous monitoring, support, and improvement. * 24/7 Cloud and DevOps Support Providing round-the-clock support for cloud and DevOps needs to ensure seamless operations and rapid issue resolution. * Cost Optimization Services Implementing proactive measures to identify and achieve cost savings through continuous cloud usage monitoring and analysis. * Resource-Level Visibility Detailed insights into cloud resource usage and performance to optimize management and control. * On-Demand Professional Services Delivering expert support and consultation as needed to address specific challenges and opportunities in your cloud environment. Multi-Cloud **Capabilities** Recognized for proven expertise & certifications across leading cloud platforms. * * **Related Resources** * Unlock Cloud Cost Savings: Your guide to a cost-efficient infrastructure Learn how to streamline expenses, enhance efficiency, and leverage cost-effective solutions for more robust and budget-friendly cloud infrastructure. Blog * Overcoming Challenges in RI Management through AI-driven Automated Solution Know about the challenges faced while managing AWS RIs & how an automated RI Management solution can help in conquering these challenges leading to optimal RI utilization & cost efficiency. Whitepapers * Optimizing AWS EBS Volumes: Strategies for Modernizing Your Infrastructure Discover the benefits of optimizing AWS EBS volumes with a deep dive into the different EBS volume types. Learn the strategies to modernize your AWS EBS storage. Blog Frequently Asked **Questions** * ### Arrow 1.What is cloud modernization? Q1. What is cloud modernization? Cloud modernization is the process of transforming outdated or legacy systems, applications, and IT infrastructure to fully leverage the capabilities of modern cloud environments. It involves a combination of upgrading technology, re-architecting applications, and optimizing resources to enhance performance, scalability, and cost-efficiency. At its core, cloud modernization aims to address the limitations of traditional IT setups by adopting cloud-native technologies like serverless computing, containerization, and microservices. It often involves rethinking the design of applications to be more agile and responsive to business needs, enabling faster development cycles and seamless scalability. * ### Arrow 2.How does CloudKeeper ensure a smooth transition to modernized infrastructure? Q2. How does CloudKeeper ensure a smooth transition to modernized infrastructure? Our certified experts follow best practices, leveraging proven methodologies, automated tools, and robust testing to ensure a seamless transition. * ### Arrow 3.Why do you need an experienced cloud modernization team? Q3. Why do you need an experienced cloud modernization team? An experienced cloud migration/modernization team is crucial for the following: 1. **Risk Reduction** : Minimizing downtime, security risks, and data loss. 2. **Performance Optimization** : Ensuring efficient, scalable, and cost-effective cloud infrastructure. 3. **Avoiding Pitfalls** : Overcoming common challenges like compatibility and integration issues. 4. **Faster Results** : Accelerating migration and realizing cloud benefits quickly. 5. **Cost Control** : Managing resources to prevent overspending. 6. **Compliance** : Ensuring alignment with industry best practices and regulations. 7. **Continuous Improvement** : Ongoing optimization after migration. 8. **Tailored Solutions** : Customizing strategies for specific business needs. * ### Arrow 4.How do I know if my business is ready for cloud modernization? Q4. How do I know if my business is ready for cloud modernization? If your applications face performance issues, rising costs, or lack scalability, it’s a good time to consider modernization. CloudKeeper offers an initial assessment to help determine readiness and potential benefits. * ### Arrow 5.What are the long-term benefits of cloud modernization? Q5. What are the long-term benefits of cloud modernization? Long-term benefits include increased efficiency, improved security, faster time-to-market for applications, better customer experiences, and the ability to innovate quickly. * ### Arrow 6.What are the different approaches to cloud modernization? Q6. What are the different approaches to cloud modernization? There are a number of different approaches to cloud modernization, depending on the specific needs of the business. Some common approaches include: * Re-hosting: This approach involves moving existing applications "as-is" to the cloud with minimal modifications. This is the quickest and easiest way to migrate to the cloud, but it may not take full advantage of all the benefits that the cloud has to offer. * Replatforming: This approach involves modernizing applications to leverage cloud-native features and services. This can improve the performance, scalability, and security of applications. * Repurchase: This approach involves analyzing licensing and identifying opportunities to optimize costs by transitioning to cost-effective cloud subscriptions. * Refactoring: This approach involves restructuring applications to fully exploit cloud functionalities, maximizing long-term benefits. * Retiring: This approach involves decommissioning unused or outdated applications, streamlining your IT landscape, and eliminating unnecessary costs. * ### Arrow 7.What is the difference between cloud migration and cloud modernization? Q7. What is the difference between cloud migration and cloud modernization? * **Cloud Migration** : This involves moving existing workloads, applications, and data from on-premises infrastructure or another cloud to a cloud environment. The primary goal is to achieve cost savings, scalability, and accessibility. Migration often follows a "lift-and-shift" approach, where applications are moved without significant changes to their architecture. * **Cloud Modernization** : This focuses on transforming and optimizing applications to leverage cloud-native features and services fully. It often includes re-architecting, re-platforming, or rebuilding applications to enhance performance, scalability, resilience, and efficiency. Modernization aligns applications with the latest technologies like microservices, serverless computing, or containerization. In short, migration gets you to the cloud, while modernization optimizes and enhances your applications for the cloud environment. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Comprehensive Suite of Services and Always-On Cloud Support CloudKeeper offers a wide range of cloud services with expert guidance and 24*7 cloud support across various critical areas, so you can focus on what matters the most – growing your business. 24*7 Technical Cloud Support Receive around-the-clock technical support ensuring prompt resolution of issues, keeping your operations running smoothly at all times. Designated Account Manager Personalized service with an account manager who understands your business needs and ensures proactive communication and support. Architecture and Business Reviews Regular reviews of your architecture and business strategies to identify opportunities for optimization and improvements. DevOps and Automation Support Extensive support for adopting and optimizing DevOps practices and cloud automation solutions. Cost and Performance Optimization Continuous monitoring and optimization strategies that ensure you achieve maximum ROI while your applications deliver peak performance. Adoption of New Cloud Services Assistance in evaluating, adopting, and integrating new cloud services and technologies that enhance your operational capabilities. Migration Support Expert support to ensure a smooth and secure transition to the cloud with minimal downtime. Third-Party Tech Stack Guidance Support for integrating third-party technologies within your cloud environment, like Snowflake, Jenkins, New Relic, and more. Proof of Concept Develop and test new solutions quickly with our Proof of Concept services, reducing time to market. Experience all these and a host of additional offerings with our full spectrum of cloud support services. **No Costs | No Commitments** Multi-Cloud **Capabilities** Recognized for proven expertise & certifications across leading cloud platforms. * * How our Personalised Support compares with the Support Tiers provided by AWS? | | | | --- | --- | | Features | AWS Developer Support | AWS Business Support | AWS Enterprise On Ramp Support | AWS Enterprise Support | CloudKeeper 24*7 Personalized Cloud Support | | 24*7 Technical Support | | | | | | | AWS Service Guidance | | | | | | | Dedicated Account Manager and Solution Architect | | | | | | | Technical Account Manager (TAM) | | | From TAM Pool | Designated TAM from AWS | Certified Cloud Expert | | Architecture Reviews | | | Max 1 Per Year | Unlimited | Unlimited | | Business Reviews | | | Max 2 Per Year | Unlimited | Unlimited | | Application Guidance | | | | | | | Infrastructure Event Management | | | Max 1 Per Year | Unlimited | Unlimited | | Training | | | | 500 Training Credits Per Year | | | Proactive Planning | | | | | | | Adoption of New Cloud Services | | | | | | | Third-Party Software Support | | | | | | | Billing and Account Management | | | | | | | DevOps Support | | | | | | | Cloud Automation | | | | | | | Cloud Migration Support | | | | | | | Cloud Cost Optimization Guidance | | | | | | | Data and Infra Security | | | | | | | POC | | | | | | | Multi-Cloud Support | | | | | AWS and Google Cloud | | Pricing | Tiered Pricing (>3% of Monthly Bills Avg) | Tiered Pricing (>10% of Monthly Bills Avg) | Tiered Pricing (>10% of Monthly Bills Avg) | Tiered Pricing (> $15,000 Monthly Avg) | Completely Free | Unlock an extensive range of cloud services, round-the-clock support and guidance by certified cloud experts! Trusted by 400+ Global Customers Our customers saved an average of 20% on their monthly AWS and GCP spend through CloudKeeper **Related Resources** * Why are end-to-end Cloud FinOps Partners leading the way? (Research Backed) Learn about the significance of comprehensive Cloud FinOps solutions and why CloudKeeper stands out as an ideal partner. Streamline cost optimization & maximize efficiency. Blog * Fumbles in FinOps Adoption and How to Avoid Them Watch this exclusive panel discussion where our industry experts talk about the common mistakes organizations make in their FinOps adoption journey. On-Demand Webinars * Acing the Cloud Optimization by choosing the right services, pricing & best practices Discover the major considerations in cloud infrastructure management and the importance of Automated Cloud Optimization solutions for a robust cloud strategy. Whitepapers Frequently Asked **Questions** * ### Arrow 1.Why is 24*7 cloud support important? Q1. Why is 24*7 cloud support important? Having round-the-clock cloud support provides peace of mind by ensuring that any issues are quickly identified and resolved before they impact your business. It also helps in proactive management, preventing potential disruptions, and offering immediate assistance in critical situations. This minimizes downtime and optimizes resource performance, driving efficiency and cost savings. * ### Arrow 2.Does CloudKeeper provide support for all cloud providers? Q2. Does CloudKeeper provide support for all cloud providers? Yes, CloudKeeper offers support for all major cloud providers, including AWS, Microsoft Azure, and Google Cloud Platform (GCP). We work with businesses to optimize their entire cloud ecosystem, ensuring seamless performance and cost-efficiency across platforms. * ### Arrow 3.What makes CloudKeeper's cloud support different? Q3. What makes CloudKeeper's cloud support different? CloudKeeper differentiates itself with: * Experienced Team: Our team of 100+ solutions architects & cloud experts holds extensive cloud certifications and proven experience across various cloud platforms. * Personalized Approach: We tailor our support to your specific needs and cloud environment. * Proactive Management: We go beyond reactive support and proactively identify potential issues to prevent downtime. * Leader in Cloud Cloud Cost Management: Highly rated and a leader in Cloud Cost Management Platform on G2 - 4.6/5 ratings. * Backed by Industry Recognitions: Recognized by IDC, Everest Group, ISG, Gartner, and Forrester * A proven track record of success: 400+ customers' success stories from all across the globe * ### Arrow 4.What types of cloud support services does CloudKeeper provide? Q4. What types of cloud support services does CloudKeeper provide? CloudKeeper offers a range of services, including: * AWS Enterprise Support at a lower cost * 24*7 Technical Cloud Support * DevOps and Automation Support * Cost and Performance Optimization * Adoption of New Cloud Services * Cloud Migration & Modernization Support * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close × Get the best AWS PPA deal with CloudKeeper PPA+ Make the most out of the AWS Private Pricing Agreement with CloudKeeper (an AWS Premier Partner) by your side. CloudKeeper PPA+ (formerly CloudKeeper EDP+) is a comprehensive solution that delivers greater benefits and added value beyond the standard AWS PPA/EDP. * Additional AWS PPA Discounts Save more with additional AWS PPA/EDP discounts for your committed usage. * Lower Annual Commitments Get AWS PPA/EDP Discounts at a lower annual spend commitment. * Discounted Price on AWS Support Partner-led enterprise support at a lower cost as compared to direct AWS Support. Go beyond discounts: Optimize your cloud infrastructure for efficiency! Get complete cloud cost visibility with CloudKeeper Lens and proactive cloud support for efficient cloud operations—all included with CloudKeeper EDP+ at no additional charge. * Access to Platform Suite * End-to-end cloud management for guaranteed results. * Savings, Visibility, Optimization & Governance – all in one. * Gen-AI Powered FinOps for smarter, faster decisions. View Details * Unlimited Cloud Support * Cloud cost optimization consulting by a designated solution architect. * Customized Well-Architected Reviews by certified experts. * Ensure ongoing cost-efficient cloud operations. View Details **** **** **Get free access to CloudKeeper Prism for Centralized Identity & Access Management** Single Sign-On across cloud, SaaS & on‑prem with enterprise‑grade security; supports different identity providers, multiple times. AWS PPA/EDP Explained, from AWS re:Invent 2023 What is the AWS Private Pricing Agreement (PPA)? AWS Private Pricing Agreement or AWS Enterprise Discount Program (AWS EDP) offers discounted usage pricing for organizations that commit to a higher volume and longer-term usage. The size of the discount scales in proportion to the committed volume and term length. There are even more factors affecting the AWS PPA discounts: * The dollar value of the annual AWS spend for the previous year. * Spend on the AWS Marketplace towards third-party listings. * Partial or full prepayment for the various services availed. * Additional AWS cloud users in immediate association, i.e., a subsidiary. Need Help with AWS Contract Negotiation? If you’re looking for **expert support in negotiating AWS PPA/EDP deal** , we do that too. From planning to negotiation, our AWS experts ensure you secure a **better AWS PPA/EDP deal.** Our CloudKeeper PPA+ Customers **Related Resources** * How to maximize the benefits of the AWS Enterprise Discount Program (EDP) Understand the basics of the AWS Enterprise Discount Program and learn some secret hacks to maximize your ROI on EDP. Also, explore the benefits of working with an EDP Partner. Whitepapers * An Essential Guide to AWS EDP to Bag High Discounts The AWS Enterprise Discount Program (AWS EDP) is an enterprise-level cloud program with substantial benefits on their AWS cloud spending. Blog * From Good to Great: Supercharge Your AWS EDP Plan with a Partner Learn how partnering with the right AWS EDP partner can simplify the complexities of AWS EDP, helping you secure great benefits at lower commitments & cost. Blog Frequently Asked **Questions** * ### Arrow 1.What is AWS Private Pricing Agreement (PPA)? Q1. What is AWS Private Pricing Agreement (PPA)? AWS PPA, also known as AWS Enterprise Discount Program (AWS EDP) is a commitment-based program offering large enterprises discounts on AWS services in exchange for agreeing to a minimum annual AWS spend, typically around $1 million or more. The program encourages a multi-year commitment (1-5 years) with discounts applied to various AWS services based on the company’s committed usage. * ### Arrow 2.How much discount does AWS PPA/EDP offer? Q2. How much discount does AWS PPA/EDP offer? Discounts vary depending on how much you commit to spend with AWS over the contract period. Generally, higher spending commitments can get you bigger discounts, based on their total AWS usage and negotiated terms. It is suggested that you opt for an AWS PPA/EDP partner like CloudKeeper to get the best-in-market discount and maximize the benefits of the program. * ### Arrow 3.What is CloudKeeper PPA+ and how does it differ from the standard AWS PPA? Q3. What is CloudKeeper PPA+ and how does it differ from the standard AWS PPA? CloudKeeper PPA+ (formerly CloudKeeper EDP+) offers additional benefits beyond the standard program. It provides lower annual commitment requirements, additional discounts on AWS services, and discounted pricing on AWS Support. Additionally, it provides * ### Arrow 4.Is AWS PPA/EDP right for every company? Q4. Is AWS PPA/EDP right for every company? Not necessarily. AWS PPA/EDP works best for companies with stable, predictable AWS needs. Companies with fluctuating usage or highly variable demand might find it risky since failing to meet the committed spend can result in extra charges. For businesses that want flexibility without long-term commitments, AWS Savings Plans or Reserved Instances could be better options. * ### Arrow 5.What’s involved in managing an AWS PPA/EDP effectively? Q5. What’s involved in managing an AWS PPA/EDP effectively? It’s all about monitoring and forecasting. Companies need to keep close tabs on their AWS usage to ensure they’re meeting their commitment without overpaying. Many use cost management tools, like AWS Cost Explorer or third-party platforms, to make sure they’re making the most of their AWS PPA/EDP while optimizing their overall usage. * ### Arrow 6.Is there any difference between AWS EDP and AWS PPA? Q6. Is there any difference between AWS EDP and AWS PPA? AWS EDP and AWS PPA are effectively the same today. AWS has rebranded the Enterprise Discount Program (EDP) as **Private Pricing Agreement (PPA)** , making PPA the active term for all new contracts. While “EDP” is largely deprecated, the terms are still often used interchangeably. Historically, there was a slight distinction between the two programs:​ * **AWS EDP (Enterprise Discount Program):** Originally focused on cross-service discounts—a flat percentage discount applied uniformly across all AWS services and regions. * **AWS PPA (Private Pricing Agreement):** Historically covered service-specific agreements, allowing for customized discounts on individual AWS services. **Current State:** Today, PPA serves as the umbrella term for all private pricing agreements—whether cross-service or service-specific— with contract details varying based on customer needs and discussions with AWS. * ### Arrow 7.Is negotiating an AWS EDP/PPA complicated? Q7. Is negotiating an AWS EDP/PPA complicated? It can be! Negotiating an AWS EDP/PPA can be complex due to AWS's strategic tactics, intricate pricing models, and commitment levels. However, thorough preparation, and potentially engaging an AWS EDP/PPA partner like CloudKeeper can simplify the process and help you secure favorable terms and the best deal. Reach out to our experts today for * ### Arrow 8.How can I get the best discounts on AWS? Q8. How can I get the best discounts on AWS? It depends on how well you Partnering with a premier AWS partner like **CloudKeeper** ensures you choose the best pricing model and get additional savings through group buying discounts, advanced cost visibility, usage optimization, and tailored recommendations, maximizing your AWS investment. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close × Your one-stop solution addressing the A to Z of cloud cost optimization CloudKeeper AZ leverages the power of group buying, the scale of spend aggregation, and volume-based discounts to help businesses achieve significant cloud cost savings that might otherwise go untapped. We ensure you access best-in-market discount rates at no cost, lock-in, or commitment. Enjoy savings, visibility, and expert support - all in one place! In addition to ensuring savings, we provide comprehensive cloud cost visibility and proactive support acting as a cloud cost management vertical for your business. * Access to Platform Suite * End-to-end cloud management for guaranteed results. * Savings, Visibility, Optimization & Governance – all in one. * Gen-AI Powered FinOps for smarter, faster decisions. View Details * Unlimited Cloud Support * Cloud cost optimization consulting by a designated solution architect. * Customized Well-Architected Reviews by certified experts. * Ensure ongoing cost-efficient cloud operations. View Details Experience these unmatched offerings at No Commitment! **** **** **Get free access to CloudKeeper Prism for Centralized Identity & Access Management** Single Sign-On across cloud, SaaS & on‑prem with enterprise‑grade security; supports different identity providers, multiple times. How does it work? Your transition to CloudKeeper AZ takes only a few minutes to complete. Step 1 Share your cloud usage details with our team for analysis. Step 2 We will confirm the guaranteed cloud cost savings that CloudKeeper AZ can offer on various cloud services. Step 3 Transfer your billing to CloudKeeper's organization account without sharing any access or credentials. Step 4 Experience instant cloud cost savings as soon as you are onboarded with CloudKeeper AZ. Our CloudKeeper AZ Customers We have expertise across leading cloud platforms * * **Related Resources** * Cloud Cost Optimization Solutions : Understanding The Key Vendor Segments The Cloud FinOps lifecycle involves three phases - Inform, Optimize and Operate. Know the FinOps vendor landscape based on their alignment with the lifecycle. Blog * How to avoid the ‘AWS Flexibility Tax’ with CloudKeeper? For AWS users, it is always hard to balance operational flexibility and cloud costs. Learn how to dodge this ‘Flexibility Tax’ with the help of CloudKeeper. Blog * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. Whitepapers Frequently Asked **Questions** * ### Arrow 1.What cloud platforms do you support? Q1. What cloud platforms do you support? We provide solutions and services for the leading cloud platforms - Amazon Web Services(AWS) and Google Cloud Platforms. * ### Arrow 2.Are cloud cost savings guaranteed? Is it on my entire cloud bill? Q2. Are cloud cost savings guaranteed? Is it on my entire cloud bill? Yes, the discount is 100% guaranteed. Our team will review your cloud bills for the past three months and provide you with a guaranteed discount percentage. The guaranteed cloud cost savings are delivered on various services of AWS including EC2 instances and GCP. * ### Arrow 3. I understand the value proposition offered by CloudKeeper. Is there any catch to this? Q3. I understand the value proposition offered by CloudKeeper. Is there any catch to this? There is no catch! With over 15+ years of experience and working across 400+ global clients, we understand the nitty gritty of the cloud ecosystem. We work with cloud service providers directly and do a 3-year usage commitment for cloud instances. In turn, we offer our customers 1-year savings plan pricing for all their on-demand usage. **We own all the risks and there is no upfront payment required and users can save on their compute usage across any region.** * ### Arrow 4.How does CloudKeeper benefit monetarily with this solution? Q4. How does CloudKeeper benefit monetarily with this solution? We stand to benefit on two fronts: * A pure play pricing arbitrage between the 3-year commitments we give to cloud service providers and the 1-year RI pricing we offer to customers like you. * Volume-pricing discounts that we get from cloud service providers and offer reduced pricing to customers for those specific services. * ### Arrow 5.How long does it take to achieve the guaranteed cloud cost savings after I get onboarded with CloudKeeper AZ? Q5. How long does it take to achieve the guaranteed cloud cost savings after I get onboarded with CloudKeeper AZ? Instantaneous - since there is no upfront payment and you start saving from Day 1. * ### Arrow 6.Is my cloud account secure with CloudKeeper? Q6. Is my cloud account secure with CloudKeeper? Absolutely, yes! You continue to control everything and CloudKeeper doesn't require any kind of access to your cloud account - including root credentials, PEM files or any passwords. * ### Arrow 7.Are the discounts applicable across servers? Q7. Are the discounts applicable across servers? Yes, it is applicable for all the servers, including the servers that are spun only during peak traffic (auto-scaled) or only during business hours. * ### Arrow 8.Does CloudKeeper AZ offer the visibility platform and cloud cost optimization services without additional charges? Q8. Does CloudKeeper AZ offer the visibility platform and cloud cost optimization services without additional charges? Absolutely! CloudKeeper AZ provides * ### Arrow 9.Why is cloud cost savings important for businesses? Q9. Why is cloud cost savings important for businesses? Cloud cost savings refer to reducing and optimizing cloud computing expenses while maintaining performance and functionality. It is crucial for businesses to prevent overspending and ensure they are using their cloud resources efficiently. * ### Arrow 10.Can cloud cost savings be achieved without compromising performance? Q10. Can cloud cost savings be achieved without compromising performance? Absolutely, cloud cost savings can be achieved without sacrificing performance. By leveraging discount programs and implementing strategies like right-sizing resources, automating scaling, and leveraging reserved or spot instances, businesses can optimize costs while maintaining high performance. CloudKeeper specializes in helping businesses achieve this balance seamlessly. * ### Arrow 11.How can CloudKeeper AZ help with cloud cost savings and beyond? Q11. How can CloudKeeper AZ help with cloud cost savings and beyond? CloudKeeper AZ is a comprehensive solution providing saving, visibility, and expert support in one place. The value we bring to your business: * We own all commitments risk on your behalf while you enjoy on-demand usage. * Get personalized support from a dedicated team of certified cloud experts, exceeding the basic support offered by your cloud provider. * As your cloud billing partner, we combine your cloud accounts for unified billing and centralized management. * We access the cloud partner network resources, programs, and incentives to further support and meet your specific business goals. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close × # CloudKeeper Commit Zero-touch, AI-driven Platform for AWS RI & Savings Plan Optimization * Instant, guaranteed savings of **30-45% from Day 1** * Continuous, AI-driven optimization across **Compute & Databases** * Reduced risk with incremental, **flexible commitments** * Outcome-based Model: **We don't get** **paid if you don't save** Before Manual Cloud Optimization Compare After Optimised Savings * Coverage 30.7% * Utilisation 100% * Discount 50% * Net Savings 15.04% * 25.5% * 05% to 25% * Coverage 87.0% * Utilisation 92% * Discount 50% * Net Savings 40.2% * 42.5% * 30% to 45% ## How CloudKeeper Commit Solves It CloudKeeper Commit uses AI/ML-driven, continuous algorithms to optimize your entire commitment layer for Compute and Databases, adapting automatically as workloads evolve. ### Real-Time Usage Intelligence Continuously monitors cloud usage in near real-time ### Dynamic Commitment Recalculation Recalculates optimal commitment levels dynamically, not on fixed cycles ### Low-Risk, Incremental Optimization Makes incremental, low-risk adjustments instead of large, upfront purchases ### Holistic Coverage Optimization Optimizes coverage across regions, instance families, and usage pools ### Smart Discount & Balancing Selects optimal RIs/Savings Plans and leverages discounted AWS Marketplace capacity. ### Automated AWS Execution Automatically executes purchases and exchanges - fully AWS-compliant Why choose CloudKeeper Commit CloudKeeper Commit delivers savings that actually show up on your bill - not just assumptions. By continuously aligning commitments to real usage, it ensures savings are immediate, measurable, and sustainable - even as environments change. **Metric** **Traditional RI / SP Management** Based on assumptions Inconsistent, unpredictable Delayed, months to realize Often underutilized High High High in changing workloads Manual tracking & planning Difficult at scale Upfront payment **CloudKeeper Commit** Guaranteed, bill-visible savings Guaranteed average savings of 30-45% on Compute and Database Instant — from Day One High, consistent utilization Minimal Reduced to near-zero Low, dynamically managed Zero-touch automation Effortless, enterprise-ready Outcome-based pricing - pay only on realized savings Get access to Unlimited Cloud Support Your platform savings are backed by expert human support, ensuring guaranteed outcomes and continuous optimization. * 24*7 Support & Designated Account Manager * Periodic AWS Well-Architected Reviews by certified experts * Actionable cost optimization recommendations * Ongoing guidance to ensure cost-efficient cloud operations CloudKeeper has not just automated commitments - we’ve mastered optimization at scale. Outcome-based Pricing Pay only when you save. No platform fee. We just take a small percentage of the total AWS cost savings you achieve through our platform, which means we only get paid when you save money. There is no additional cost or subscription fees. Our Share ## How does CloudKeeper Commit work? Quick Onboarding The entire onboarding takes less than 5 minutes. Analyze the potential savings Once onboarded, CloudKeeper runs an initial scan of your AWS account & potential. Optimize on Autopilot Turn on Commit and let it handle everything - instant savings, no effort. Track Impact Track realized savings, coverage, & utilization with full transparency and user-friendly dashboards. Our CloudKeeper Commit Customers We are on “Cost savings kicked in immediately and were reflected in the next month’s bill. A second set of savings came in the longer term is due to the team, process and the tools that highlighted the areas we might look in to save money.” “Having access to experts whenever we need them in terms of new services, infrastructure & if we’re trying something new, CloudKeeper has the capability to support us. ” “After onboarding in just 1-2 days, you get recommendations by Cloudkeeper about the gaps & leakage you have in your AWS account, underutilized resources, data transfer leakage, RI utilization & alert mechanisms which helps in further savings.” Steven Thurlow CEO Prateek Baheti Head of Technology Dipesh Garg DevOps Lead ‹ › ## Related Resources In-depth, research-led content from our certified FinOps & cloud experts * Whitepapers Overcoming Challenges in RI Management through AI-driven Automated Solution * Blog AWS EC2 Cost Optimization: Right-Sizing and Instance Selection Tips * Blog AWS Cost Optimization with Reserved Instances ## Recognized by the best in the industry for end-to-end cloud cost optimization Major Player in MarketScape’s Worldwide FinOps Cloud Cost Optimization Assessment. Major Player in FinOps Cost Management Products PEAK Matrix Assessment 2025. Notable Vendor in Magic Quadrant for Public Cloud IT Transformation Services - Midmarket Global. Product Challenger in APAC for AWS Ecosystem Partners 2025. Frequently Asked **Questions** * ### Arrow 1.What is the pricing structure of CloudKeeper Commit and what does no cost mean? Q1. What is the pricing structure of CloudKeeper Commit and what does no cost mean? We only get paid when you save money. There is no extra or hidden cost for the CloudKeeper Commit AWS RI Management solution. We only charge a small portion of your total AWS cost savings that we help you achieve through our platform. * ### Arrow 2.Is the buyback of my AWS Reserved Instances guaranteed? Q2. Is the buyback of my AWS Reserved Instances guaranteed? Yes, we guarantee the buyback of the AWS Reserved Instance purchased through CloudKeeper Commit if you use less capacity than what you paid for. Furthermore, our growing customer base of 400+ also acts as a secondary marketplace for buying and selling AWS RIs. Thus ensuring your resources never go to waste. * ### Arrow 3.What access does CloudKeeper Commit require? Is my infrastructure safe? Q3. What access does CloudKeeper Commit require? Is my infrastructure safe? CloudKeeper needs just IAM read-only access to perform the savings on compute costs. We don't need any access to your cloud environment. It’s completely secure. * ### Arrow 4.What are the manual dependencies in this solution? Q4. What are the manual dependencies in this solution? CloudKeeper is a completely AI-based Automated AWS RI Management Solution that buys & sells RI reservations based on real-time needs. * ### Arrow 5.Does the solution require any type of volume or term commitment from the user? Q5. Does the solution require any type of volume or term commitment from the user? No, we do not require any commitment. * ### Arrow 6.What additional offerings does CloudKeeper Commit provide besides automated AWS RI management? Q6. What additional offerings does CloudKeeper Commit provide besides automated AWS RI management? In addition to addressing AWS RI management challenges, CloudKeeper Commit provides * ### Arrow 7.What is a Reserved Instance (RI) in AWS? Q7. What is a Reserved Instance (RI) in AWS? A Reserved Instance (RI) is an AWS pricing model that allows you to reserve a specific instance type for a set term (1 or 3 years) in exchange for a lower hourly rate compared to On-Demand Instances. It offers significant cloud cost savings for predictable workloads by committing to use AWS resources over time. * ### Arrow 8.What is the difference between on-demand and reserved instances in AWS? Q8. What is the difference between on-demand and reserved instances in AWS? On-demand instances allow you to pay for compute capacity by the hour with no long-term commitment, offering flexibility for unpredictable workloads. Reserved Instances (RIs) provide up to 72% savings by committing to a specific instance type and term (1 or 3 years), ideal for predictable, long-term workloads. In short, On-Demand is flexible but more expensive, while Reserved Instances offer significant savings in exchange for long-term commitment. * ### Arrow 9.What is the difference between spot and reserved instances in AWS? Q9. What is the difference between spot and reserved instances in AWS? Spot Instances are cost-effective, offering significant savings by bidding for unused capacity, but they can be terminated by AWS anytime. They’re ideal for flexible, interruptible workloads. Reserved Instances (RIs) provide up to 72% savings with a long-term commitment (1 or 3 years) and guarantee capacity for stable, predictable workloads. In short, Spot Instances are cheaper but less reliable, while Reserved Instances offer savings with guaranteed availability. * ### Arrow 10.What is AWS Reserved Instance (RI) Management? Q10. What is AWS Reserved Instance (RI) Management? AWS Reserved Instance (RI) Management refers to the process of purchasing, optimizing, and managing Reserved Instances to ensure cost savings and efficient cloud resource usage. This includes selecting the right instance types, sizes, and terms that align with business needs. CloudKeeper Commit automated this process making AWS RI Management effortless. * ### Arrow 11.What are the benefits of using AWS Reserved Instances (RIs)? Q11. What are the benefits of using AWS Reserved Instances (RIs)? * Cost savings: Up to 75% savings over on-demand prices. * Predictability: Fixed pricing and capacity reservations for better budgeting. * Flexibility: Options for instance type, region, and term length. * ### Arrow 12.How can I track and manage my AWS Reserved Instances? Q12. How can I track and manage my AWS Reserved Instances? You can track and manage your RIs using the AWS Management Console, AWS Cost Explorer, or third-party tools like CloudKeeper Commit, which help optimize and monitor your Reserved Instance utilization for maximum savings. * ### Arrow 13.How to achieve 100% AWS Reserved Instances Coverage? Q13. How to achieve 100% AWS Reserved Instances Coverage? To achieve 100% AWS Reserved Instance (RI) coverage there are multiple best practices to be followed such as : * Analyze RI usage with CloudKeeper Lens to identify steady workloads. * Right-size instances to match the appropriate type, size, and region. * Maximize utilization using Auto Scaling and Trusted Advisor. * Regularly review and adjust RIs based on changing needs. * Use Convertible RIs for added flexibility. * Sell unused RIs in the RI Marketplace. Moreover, CloudKeeper Commit delivers 100% AWS Reserved Instance (RI) coverage with AI-driven automation. It provides on-demand EC2 instances at 3-year RI pricing, with no upfront costs or commitments, and offers a buyback guarantee for unused RIs. Gain full visibility with CloudKeeper Lens to track RI utilization and optimize cloud costs. Plus, access 24*7 cloud support from 300+ cloud experts to streamline operations and maximize savings. Learn more about ## Certified. Trusted. Industry Recognized. ## Stop paying for cloud tools. Start paying for outcomes. close close # Empowering immersive learning & growth with effortless cloud management ### Our Customers in **EdTech** * India Digital learning solutions provider * USA Cloud-based educational solutions provider * Nigeria Online Learning App * USA Personalized math tutoring platform * SEA Learning management for preschools * Singapore AI-driven solutions to simplify career guidance process * Singapore Cloud-based collaborative learning platform * India Exam preparation and learning ### Supporting Cloud-Driven Success for E-learning #### The education sector has rapidly evolved post-COVID, embracing digital transformation that emphasizes interactive & blended learning. The Global Digital Education Market is all set to reach $77 billion by 2028. Here’s how we simplify the cloud journey for the education industry: * Seamless Collaboration EdTech thrives on real-time, smooth collaboration between students and educators. While you focus on an interactive academic experience, CloudKeeper handles all aspects of your cloud setup. * Increased Accessibility From lecture notes to interactive learning tools, everything is just a click away. We ensure your cloud storage is efficient in handling on-demand access to resources, extending learning beyond the classroom at an optimized cost. * Scalable Digital Learning CloudKeeper enables your cloud infrastructure to scale effortlessly, handling spikes in traffic during enrollment periods, exams, or online courses without compromising performance or budget. * Virtual Learning Ecosystem We provide proactive solutions that simplify the complexities of managing multiple cloud environments while improving data security, and supporting your innovation needs. * Cloud Cost Optimization As your institution expands its digital offerings, CloudKeeper helps manage and reduce cloud expenses, ensuring you deliver high-quality education without overspending. * Push the tech boundaries With CloudKeeper, experiment with new learning tools, pilot digital courses, and adopt cutting-edge technologies without being tied to expensive cloud contracts. ### Here’s how we empower EdTech companies #### From instant cloud savings to long-term growth, we support your entire cloud journey! * Results from Day 1 Achieve instant & guaranteed cloud cost savings on your entire cloud bill, right from Day 1. * Automated Cloud Management Simplify cloud operations with a powerful suite of tools for intelligent optimization, anomaly detection & enhanced governance. * 24*7 Support by Certified Experts We act as your cloud cost management vertical, handling end-to-end cloud needs. * Cloud FinOps Services Get FinOps consulting by cloud-certified experts to establish a strong FinOps culture. * Cloud Modernization Harness the latest in cloud technology and achieve peak performance with our 3-phase approach. * Exclusive Partner Benefits Get best-in-market discounts & benefits on AWS EDP, PPA & MAP. Access top-tier cloud support at discounted rates. * We own your Commitment Risk Get the freedom to run everything on-demand at commitment-based pricing while we own your risk. * Customized WAR Get custom recommendations to ensure your setup is optimized for performance, security, and cost-efficiency. We have expertise across leading cloud platforms * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure What Our Clients Say From DevOps engineers to CTOs, CFOs, and CEOs — CloudKeeper is loved by all! * Cost savings kicked in immediately and were reflected in the next month’s bill. A second set of savings came in the longer term is due to the team, process and the tools that highlighted the areas we might look in to save money. Steven Thurlow CEO **Related Resources** * An Essential Guide to AWS EDP to Bag High Discounts The AWS Enterprise Discount Program (AWS EDP) is an enterprise-level cloud program with substantial benefits on their AWS cloud spending. * Cloud Cost Savings Definitive Guide: Proven Strategies, Best Practices & Hacks This blog deep dives into both instant and long-term cloud cost savings strategies, providing practical approaches that maximize value from your cloud investments. * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Empowering innovation while ensuring secure & cost-effective infrastructure ### Our **Fintech** Customers * India Digital wallet and payments * USA Ethical investment platform * USA Stock investment platform * Australia Credit data and analysis * UK Digital wealth management * USA Payment solutions provider * India Lending and financing platform ### Why do Fintechs love CloudKeeper? #### The global fintech cloud industry is expected to reach $196.2 billion by 2031, with a CAGR of 16.4%. Fintechs have turned cloud as a steadfast force for innovation, performance & security. * Fraud Detection & Prevention Fintechs face increasing threats of fraud, requiring real-time detection across vast datasets. CloudKeeper ensures your cloud setup is equipped to handle this. * Effective Data Management Managing large volumes of financial data is critical but costly. CloudKeeper optimizes storage, offering scalability without unnecessary expenses. * Increased Speed to Market Cloud comes with flexibility but CloudKeeper gives an added benefit to test/run POCs, free from expensive & restrictive cloud contracts, allowing faster services & feature rollouts. * Scalability on Demand From managing fluctuating workloads to rapid scaling when introducing new financial products, CloudKeeper ensures your infrastructure scales efficiently without incurring unnecessary costs. * Cloud Cost Optimization Managing financial platforms in the cloud can be costly due to high availability needs. We help you control expenses, ensuring cost efficiency without sacrificing performance and security. * Reliability & Performance We enhance your infrastructure’s reliability and efficiency through resource optimization and load balancing, minimizing disruptions for smooth operations. ### Here’s how we empower Fintech companies #### From instant cloud savings to long-term growth, we support your entire cloud journey! * Results from Day 1 Achieve instant & guaranteed cloud cost savings on your entire cloud bill, right from Day 1. * Automated Cloud Management Simplify cloud operations with a powerful suite of tools for intelligent optimization & enhanced governance. * 24*7 Support by Certified Experts We act as your cloud cost management vertical, handling end-to-end cloud needs. * Cloud FinOps Services Get FinOps consulting by cloud-certified experts to establish a strong FinOps Culture. * Risk Management Our proactive & tailored approach detects anomalies, mitigates potential overruns and cloud sprawl risks. * Exclusive Partner Benefits Get best-in-market discounts & benefits on AWS EDP, PPA, MAP. Access top-tier cloud support at discounted rates. * We own your Commitment Risk Get the freedom to run everything on-demand at commitment-based pricing while we own your risk. * Customized WAR Get custom recommendations to ensure your setup is optimized for performance, security, and cost-efficiency. ### Our **Success Story** How MobiKwik, a major fintech player, is using CloudKeeper EDP+ to reduce their AWS costs by 27% Values delivered * Immediate cloud savings of 12% on the entire bill * Further cost reduction by 15% through architectural level optimizations * Efficient resource allocation and cost savings * Enhanced financial transparency & accountability We have expertise across leading cloud platforms * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure What Our Clients Say From DevOps engineers to CTOs, CFOs, and CEOs — CloudKeeper is loved by all! * Cost savings kicked in immediately and were reflected in the next month’s bill. A second set of savings came in the longer term is due to the team, process and the tools that highlighted the areas we might look in to save money. Steven Thurlow CEO **Related Resources** * An Essential Guide to AWS EDP to Bag High Discounts The AWS Enterprise Discount Program (AWS EDP) is an enterprise-level cloud program with substantial benefits on their AWS cloud spending. * Cloud Cost Savings Definitive Guide: Proven Strategies, Best Practices & Hacks This blog deep dives into both instant and long-term cloud cost savings strategies, providing practical approaches that maximize value from your cloud investments. * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Innovate for patient-centric healthcare, while we manage your cloud ### Our **Heathcare** Customers * USA Pharmaceutical compliance solutions * Canada All-in-one healthcare coordination platform * Australia A healthcare center offering a modern experience * USA Health insurance company * USA HIPAA Compliant Digital Patient Communication Platform * USA Virtual fitness challenges app * USA Life sciences and diagnostics solutions * SEA Integrated health tech company * India Patient engagement solution * Europe Preventive health testing services ### Build a value-based healthcare with CloudKeeper by your side #### Cloud capabilities have the potential to generate value of $100 to $170 billion by 2030 for healthcare companies. Don’t just scratch the surface - here's how you can maximize your cloud investment ahead of the competition. * E-health & tele-medicines The demand for e-health services is growing. To enable efficient remote care delivery, CloudKeeper optimizes your cloud setup for peak performance while keeping the cost within budget. * Manage & Protect Patient Data Cloud-based EHRs are widely used in medical care. CloudKeeper optimizes your data storage for cost-efficiency while ensuring all security measures to safeguard sensitive information. * Infrastructure for Modern Healthcare CloudKeeper provides everything related to cloud optimization & infrastructure-as-a-service to help you address the cloud challenges of modern healthcare systems. * Flexible Scalability CloudKeeper allows seamless scaling of your infrastructure to handle surges in inquiries and telemedicine sessions, ensuring optimal performance without unnecessary cost. * Cloud Cost Optimization As your healthcare operations grow, it can lead to spiraling costs. CloudKeeper helps you manage and optimize expenses, ensuring profitability while maintaining high-quality service delivery. * Innovate Risk-Free Today’s patient expects more personalized and convenient care. Focus on continuous improvement & test new services or technologies without the burden of expensive cloud contracts, with CloudKeeper. ### Here’s how we empower healthcare companies #### From instant cloud savings to long-term growth, we support your entire cloud journey! * Results from Day 1 Achieve instant & guaranteed cloud cost savings on your entire cloud bill, right from Day 1. * Automated Cloud Management Simplify cloud operations with a powerful suite of tools for intelligent optimization & enhanced governance. * 24*7 Support by Certified Experts We act as your cloud cost management vertical, handling end-to-end cloud needs. * Cloud FinOps Services Get FinOps consulting by cloud-certified experts to establish a strong FinOps culture. * Cloud Modernization Harness the latest in cloud technology and achieve peak performance with our 3-phase approach. * Exclusive Partner Benefits Get best-in-market discounts & benefits on AWS EDP, PPA, MAP. Access top-tier cloud support at discounted rates. * We own your Commitment Risk Get the freedom to run everything on-demand at commitment-based pricing while we own your risk. * Customized WAR Get custom recommendations to ensure your setup is optimized for performance, security, and cost-efficiency. ### Our **Success Story** Solve.Care, a leading global healthcare tech company, partners with CloudKeeper to transform healthcare management using AI-powered cloud solutions Values delivered * AI-powered cloud optimization to innovate and optimize infrastructure. * Enhanced financial transparency, governance & accountability. * Comprehensive suite of services for end-to-end cloud needs. We have expertise across leading cloud platforms * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure What Our Clients Say From DevOps engineers to CTOs, CFOs, and CEOs — CloudKeeper is loved by all! * Cost savings kicked in immediately and were reflected in the next month’s bill. A second set of savings came in the longer term is due to the team, process and the tools that highlighted the areas we might look in to save money. Steven Thurlow CEO **Related Resources** * An Essential Guide to AWS EDP to Bag High Discounts The AWS Enterprise Discount Program (AWS EDP) is an enterprise-level cloud program with substantial benefits on their AWS cloud spending. * Cloud Cost Savings Definitive Guide: Proven Strategies, Best Practices & Hacks This blog deep dives into both instant and long-term cloud cost savings strategies, providing practical approaches that maximize value from your cloud investments. * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close #### CloudKeeper Lens # A Cloud Cost Visibility and Governance Platform for AWS and GCP ## Why High-Growth Teams Choose CloudKeeper Lens CloudKeeper Lens transforms the way your teams manage, monitor, and optimize cloud operations. * Resource level cost visibility * Hourly Dashboards * Advanced Cost Breakup Dashboards * No access needed to your cloud account * Slack and MS Teams Integration ## Simplified Cloud Cost Monitoring for your FinOps team Here are a **few of the many ways** CloudKeeper Lens empowers your team. Finance Team ## Own your Cloud Spend Engineering Team ## Build Smart, Spend Smarter Product Team ## Drive Cost-Aware Innovation DevOps Team ## Operate with Full Visibility ## Finance Team A simplified, high-level monthly **overview of all cost centers.** ## Engineering Team Resource coverage & utilization by cost, hourly cost breakdowns for RI planning. ## Product Team Resource-level cost insights that help teams pinpoint what’s driving spend accurately. ## DevOps Team Ensure proper tagging and visibility into **resource usage trends** across accounts CloudKeeper Lens vs. Native Tools: **Here’s How Lens Does It Better** | Exclusive Features | Native by Cloud Providers | CloudKeeper Lens | | --- | --- | --- | | Hourly Dashboard | No | Yes | | Value for Users The Hourly Dashboard offers real-time visibility into cloud costs, helping users **identify usage spikes** , any **spend anomalies** , optimize **spend patterns** , and make faster, data-driven decisions. Feature Highlights * Real-time Visibility * Granularity | | Resource-Level Visibility | No | Yes | | Value for Users Know your cloud costs to the penny. Drill down to every instance, volume, and resource to **spot cost-heavy components** , rightsize fast, and allocate spend to the smallest team or project. Feature Highlights * Precision * Traceability | | Advanced Cost-Breakup dashboards | No | Yes | | Value for Users Full-stack visibility for critical services at every level - clusters, nodes, pods, CPU, memory, and regions. Capture **hidden costs that native tools miss** , and model unit costs—per instance, per resource, with accuracy. Feature Highlights * Transparency * Control | | Contract Tracker (e.g. AWS EDP) | No | Yes | | Value for Users **Real-time visibility into AWS EDP consumption** , helping teams track usage, stay on target with commitments, and avoid chargebacks. Feature Highlights * Commitments * Utilization | | Daily Cost Digest | No | Yes | | Value for Users Receive a **daily, high-level summary** directly in the **inbox/Slack channel**. Keeps teams aware of major cost movements without requiring **console logins or context-switching.** Feature Highlights * Awareness * Alignment | | Human-assisted cost detection | No | Yes | | Value for Users Receive **actionable alerts** verified by cloud experts, filtering out noise and false positives. Saves critical time and prevents alert fatigue on the technical team. Feature Highlights * Reliability * Actionability | | RI/SP Coverage, Utilization | No | Yes | | Value for Users Track coverage and utilization, identify idle RIs/SPs, buy and renew with a simple, one-stop interface and**instant** _**Buy Again**_**option.** Feature Highlights * Efficiency * Optimization | | Custom Cost Reporting | Limited | Advanced | | Value for Users Generate **reports tailored to your team’s needs** - filter by tags, services, or projects to create detailed, drill-down insights. Feature Highlights * Customization * Clarity | | Tag Management & Compliance | Limited | Advanced | | Value for Users Highlights untagged and non-compliant resources with their costs, ensuring **better allocation** , governance, and accountability. Feature Highlights * Discipline * Governance | ### Hourly Dashboard Value for Users The Hourly Dashboard offers real-time visibility into cloud costs, helping users **identify usage spikes** , any **spend anomalies** , optimize **spend patterns** , and make faster, data-driven decisions. Feature Highlights * Real-time Visibility * Granularity ### Resource-Level Visibility Value for Users Know your cloud costs to the penny. Drill down to every instance, volume, and resource to **spot cost-heavy components** , rightsize fast, and allocate spend to the smallest team or project. Feature Highlights * Precision * Traceability ### Advanced Cost-Breakup dashboards Value for Users Full-stack visibility for critical services at every level - clusters, nodes, pods, CPU, memory, and regions. Capture **hidden costs that native tools miss** , and model unit costs—per instance, per resource, with accuracy. Feature Highlights * Transparency * Control ### Contract Tracker (e.g. AWS EDP) Value for Users **Real-time visibility into AWS EDP consumption** , helping teams track usage, stay on target with commitments, and avoid chargebacks. Feature Highlights * Commitments * Utilization ### Daily Cost Digest Value for Users Receive a **daily, high-level summary** directly in the **inbox/Slack channel**. Keeps teams aware of major cost movements without requiring **console logins or context-switching.** Feature Highlights * Awareness * Alignment ### Human-assisted cost detection Value for Users Receive **actionable alerts** verified by cloud experts, filtering out noise and false positives. Saves critical time and prevents alert fatigue on the technical team. Feature Highlights * Reliability * Actionability ### RI/SP Coverage, Utilization Value for Users Track coverage and utilization, identify idle RIs/SPs, buy and renew with a simple, one-stop interface and**instant** _**Buy Again**_**option.** Feature Highlights * Efficiency * Optimization ### Custom Cost Reporting Value for Users Generate **reports tailored to your team’s needs** - filter by tags, services, or projects to create detailed, drill-down insights. Feature Highlights * Customization * Clarity ### Tag Management & Compliance Value for Users Highlights untagged and non-compliant resources with their costs, ensuring **better allocation** , governance, and accountability. Feature Highlights * Discipline * Governance ## The CloudKeeper Lens Value Loop Analyze Identify anomalies early, track trends hourly at the resource level, and surface insights with heatmaps and utilization metrics. Discover Gain instant visibility with expert-built dashboards, customizable reports, access controls, and alerts tailored to your teams. Act Set precise alerts, customize thresholds to your needs, and receive automated optimization recommendations turning insights into measurable, organization-wide savings Trusted by 400+ Global Customers Our customers saved an average of 20% on their monthly AWS and GCP spend through CloudKeeper **** **** **Try Lens with a 30-Day Free Trial** Get a hands-on view and see exactly where your cloud budget goes and how much you can save. **How CloudKeeper Lens makes a difference: Customer Speaks** * CloudKeeper Lens, has been **instrumental in helping us set up a clear, actionable dashboard** for tracking our monthly cloud billing costs. Lead DataOps Engineer * We've achieved strong savings through their discounts, cost optimization, and technical support. The CloudKeeper Lens Platform gives **deep, well-organized visibility into costs - better than AWS Cost Explorer.** A **truly valuable partner** for AWS cost management. Principal Technical Architect * The **Platform delivers comprehensive visibility** into our cloud usage patterns and identifies actionable savings opportunities that would be **nearly impossible to detect through native AWS CloudWatch** monitoring alone. * Cloudkeeper is a game-changer for cloud cost management. It is **essential for controlling cloud spend** and making the most out of the infrastructure. It's become a **vital part of our cost management toolkit.** Lead DataOps at Seclore * Lens is a cool **tool that we use a lot more than AWS cost explorer.** Segregated daily views on various heads/resources like CDN, EC2, S3 etc help us to monitor our cloud spends manually. We also use their alerting mechanisms to detect any deviations in our spends wherein we get notified via emails. ## Easy Signup and Onboarding Setup for AWS Setup for GCP * Log in to AWS console * Create custom biling report * Enable cross-account data replication. * Log in to Google Cloud console * Grant read access to billing account * Receive CloudKeeper Lens credentials ## Plan & Pricing * For CloudKeeper customers 30-day free trial! 1% of the monthly cloud bill. * For others 30-day free trial! 2% of the monthly cloud bill. **Related Resources** * 5 Reasons Why a Comprehensive Cloud Partner is Necessary Discover why partnering with a comprehensive cloud provider is critical for optimizing your cloud strategy. Download our whitepaper to learn how expert guidance, cost efficiency, security, and scalability can transform your business with Azure. Whitepapers * Why are end-to-end Cloud FinOps Partners leading the way? (Research Backed) Learn about the significance of comprehensive Cloud FinOps solutions and why CloudKeeper stands out as an ideal partner. Streamline cost optimization & maximize efficiency. Blog * Unmasking the Hidden Cloud Cost Savings Know how a cloud cost visibility and recommendation platform like CloudKeeper Lens can be an effective tool to realize hidden cloud cost savings avenues. Blog * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Transform your AWS costs into actionable insights From **high-level trends to a granular view** of your cloud cost spending & usage, gain the clarity you need for informed decision-making and **smart recommendations** that drive real **impact to your bottom line.** * Resource level cost visibility * No access needed to your AWS account * Slack and MS Teams Integration * Unified view of multiple AWS accounts × A single platform to **achieve full cloud transparency while driving long-term savings** * #### Billing Summary & Daily Breakup Heatmap * Account & Service-wise Cost Breakup Trend (Monthly, Weekly, Daily). * Average daily spend, & precise monthly forecast. * A heatmap showcasing the cost variation for the month on a daily basis. Video file * #### Advanced cost-clarity dashboards * A comprehensive dashboard for critical services like EKS Cost Allocation, Database, and Data Transfer. * Track costs across multiple resource components like clusters, nodes, pods, CPU, memory, and regions. Image * #### Hourly Dashboards * Available for Compute, RDS, OpenSearch, ElastiCache, Redshift, DataTransfer, S3. * Last 90 days heat map to spot variances and anomalies; helps in RI/SP purchase planning. * Insights into baseline spend vs total spend. Value-added features: Compute Cost type can be sorted and viewed as **Unblended, Amortized, or on-demand Equivalent(ODE)** for better financial clarity and precision. Video file * #### Reserved Instances/Savings Plan Coverage & Utilization * Comprehensive visibility into RI/SP coverage & usage insights at the service level. * Identify unused or underutilized RI/SPs to maximize cost efficiency. * Analyze expiration timelines to plan renewals proactively. Image ## Multi-Dimensional Cost Visibility & Intelligence with Lens Analytics Our proprietary **Lens Analytics Engine** ingests your cloud billing, tags, and business taxonomy to deliver cost visibility at any level of granularity - customized to how your organization operates. Ingest Everything Normalize & Map to Your Business Analyze at Any Level of Granularity Deliver Actionable Insights ## Lens Analytics pulls in all your cloud cost signals * Usage data across AWS services * Billing & cost records * Tags and metadata * Business taxonomy (teams, products, cost center) ## Raw cloud data is transformed into your business structure * Product-level cost allocation * Feature-level cost visibility * Customer-level cost tracking * Team and workload attribution ## Multi-dimensional drill-down with access to 10,000+ filters * Hourly, daily, monthly trends * Drill-down from org → team → resource * Multi-dimensional analysis (service, region, tags, cost centers) * Team and workload attribution ## Stakeholder-ready dashboards with custom branding * Custom dashboards tailored to stakeholders * RI/SP vs On-Demand cost visibility * Cost anomalies & optimization opportunities * Fully white-labeled Simplifying **AWS Cost Monitoring** for your FinOps team Get **customized reports and notifications** to fit your team's specific cloud cost visibility needs. Here are a **few of the many ways** CloudKeeper Lens empowers your team. * Finance Team A simplified, high-level monthly overview of all cost centers. * Engineering Team Hourly cost breakdowns for precise tracking & planning for RI buying/renewal. * Product Team Insights on Cloud Cost impact by different services. * DevOps Team Visibility into resource usage trends across accounts. Try CloudKeeper Lens today to witness its impact on your AWS cloud cost! We are on Easy Signup and Use The signup process is just a few clicks away * Login to your AWS console * Create your custom AWS report * Enable cross-account replication ### That’s it. You're all set to review and track your AWS cloud cost. ## Plan & Pricing * For CloudKeeper customers 30-day free trial! 1% of monthly AWS bill for CloudKeeper AZ & EDP+ customers. * For others 30-day free trial! 2% of your monthly AWS bill after the trial period. Watch CloudKeeper Lens in action! **Customer Voices:** How CloudKeeper Lens makes a difference Provided detailed information about the spending and helped us identify the bottlenecks of unused resources. **Also, it gives us a fair idea about the projection for the upcoming month's bill.** SURENDRA REDDY C V DevOps Tech Lead CloudKeeper Lens gives excellent visibility on cost usage and a **360-degree view of our cloud spend.** Verified G2 Review CloudKeeper Lens offers a **detailed view of historical spending.** This allows us to track costs on a day-to-day or week-to-week basis. This level of visibility is very helpful in identifying potential cost-saving opportunities. **** **Verified G2 Review** Our CloudKeeper Lens - Customers **Related Resources** * Unmasking the Hidden Cloud Cost Savings Know how a cloud cost visibility and recommendation platform like CloudKeeper Lens can be an effective tool to realize hidden cloud cost savings avenues. Blog * Navigating the Cost Fog: How to Achieve Better Cloud Cost Visibility Learn the basics of cloud cost visibility to optimize your FinOps strategy. Also, understand the challenges in achieving clear cost visibility and how to tackle them. Blog * Unlock Cloud Savings: Mastering AWS Cost Anomaly Detection The guide to AWS cost anomaly detection and maximizing your cloud savings. Learn how to identify anomalies, optimize spending, and maximize efficiency for your AWS infrastructure. Blog Frequently Asked **Questions** * ### Arrow 1.Why is cloud cost visibility important? Q1. Why is cloud cost visibility important? Cloud cost visibility is crucial because it helps organizations avoid overspending and make smarter decisions about their cloud resources. Without clear insight into where the money is going, companies might end up wasting funds on unnecessary services or resources. This can also make it difficult to plan for the future or stay within budget. With better AWS cost monitoring, organizations can spot areas where they're spending too much and find ways to cut costs. It also encourages accountability among the teams. * ### Arrow 2.What are the benefits of using CloudKeeper Lens? Q2. What are the benefits of using CloudKeeper Lens? CloudKeeper Lens helps you: * Gain comprehensive & clear cloud cost visibility. * Efficient cost allocation, chargeback, and tagging. * Track and control cloud costs. * Alerts for cost spikes/unusual spending patterns. * Better cloud cost forecasting. * ### Arrow 3.Is there a free trial available for CloudKeeper Lens? Q3. Is there a free trial available for CloudKeeper Lens? Yes, CloudKeeper Lens offers a 30-day free trial. * ### Arrow 4.What cloud platforms does CloudKeeper Lens support? Q4. What cloud platforms does CloudKeeper Lens support? CloudKeeper Lens is a cloud cost visibility and recommendation platform available for both the AWS and * ### Arrow 5.How can CloudKeeper Lens help me save money on my AWS bill? Q5. How can CloudKeeper Lens help me save money on my AWS bill? CloudKeeper Lens helps you identify potential cost savings opportunities by providing insights into your spending patterns. You can use this information to optimize your resource usage and choose the most cost-effective options. * ### Arrow 6.Is CloudKeeper Lens available on AWS Marketplace? Q6. Is CloudKeeper Lens available on AWS Marketplace? Yes, CloudKeeper Lens is available on * ### Arrow 7.How much does CloudKeeper Lens cost? Q7. How much does CloudKeeper Lens cost? There is a 30-day free trial, and after the trial period, CloudKeeper Lens cost 1% of monthly bill for CloudKeeper AZ and EDP+ customers. For other users, the cost is 2% of monthly cloud bill. * ### Arrow 8.How can I sign up for a free trial? Q8. How can I sign up for a free trial? Click * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Gain a comprehensive view of your cloud costs CloudKeeper Lens is our proprietary Azure cloud cost visibility and recommendations platform. It offers real-time insights, cloud cost optimization recommendations, and a granular view of your cloud spending patterns and cost usage to empower informed decision-making. * Resource level cloud cost visibility * No access needed to your Azure account * Few clicks easy onboarding How does CloudKeeper Lens help your business? CloudKeeper Lens provides a comprehensive and unified dashboard for all Azure spends. ## Billing Summary Understand your cloud expenses better with an Azure bills summary, average daily cloud cost spent, and last 7-day cloud cost. Get insights into your monthly forecast and a daily cost breakup of Azure services. ## Resource Group & Subscription Breakup Simplify your cloud expense tracking with detailed daily and monthly breakdowns categorized by resource groups and subscriptions. ## Virtual Machine (VM) & Storage Breakup Gain clarity on the charges for all the VM instances and identify which ones are incurring the highest expenses. Additionally, explore detailed breakdowns of your cloud cost spending on VMs and storage resources. ## Daily Breakup Heatmap The Daily Breakup heatmap shows the cloud cost variation for the month on a daily basis. Drill down further to identify specific usage types for Azure service. We are on Easy Signup and Onboarding The signup process is just a few clicks away * Login to your Azure account * Create an Azure cost & usage report * Give access to your usage report That’s it! You're all set to review and track your Azure cloud cost. ## Plan & Pricing * For CloudKeeper AZ customers Free access to CloudKeeper Lens for customers who onboard with CloudKeeper AZ * For others 30-day free trial! 2% of your monthly Azure bill after the trial period Pro tip: and access to CloudKeeper Lens at no cost. Our CloudKeeper Lens - Azure Customers **Related Resources** * Unmasking the Hidden Cloud Cost Savings Know how a cloud cost visibility and recommendation platform like CloudKeeper Lens can be an effective tool to realize hidden cloud cost savings avenues. Blog * A Comprehensive Guide to Azure Cost Optimization Master Azure cost optimization with strategies and best practices. Control spending, maximize value, and ensure long-term success in the cloud. Blog * Best Practices for Cloud Cost Allocation and Cloud Tagging Cost allocation is critical for companies looking to improve cloud cost visibility thus reducing waste and optimizing cloud costs. Read more in this article. Blog Frequently Asked **Questions** * ### Arrow 1.Why is cloud cost visibility important? Q1. Why is cloud cost visibility important? Cloud cost visibility is crucial because it helps organizations avoid overspending and make smarter decisions about their cloud resources. Without clear insight into where the money is going, companies might end up wasting funds on unnecessary services or resources. This can also make it difficult to plan for the future or stay within budget. With better Azure cost monitoring organizations can spot areas where they're spending too much and find ways to cut costs. It also encourages accountability among the teams. * ### Arrow 2.What are the benefits of using CloudKeeper Lens? Q2. What are the benefits of using CloudKeeper Lens? CloudKeeper Lens helps you: * Gain comprehensive & clear cloud cost visibility. * Efficient cost allocation, chargeback, and tagging. * Track and control cloud costs. * Alerts for cost spikes/unusual spending patterns. * Better cloud cost forecasting. * ### Arrow 3.Is there a free trial available for CloudKeeper Lens? Q3. Is there a free trial available for CloudKeeper Lens? Yes, CloudKeeper Lens offers a 30-day free trial. After the trial period, the cost is 2% of your monthly cloud bill. * ### Arrow 4.What cloud platforms does CloudKeeper Lens support? Q4. What cloud platforms does CloudKeeper Lens support? CloudKeeper Lens is a cloud cost visibility and recommendation platform available for both Azure and * ### Arrow 5.How can CloudKeeper Lens help me save money on my Azure bill? Q5. How can CloudKeeper Lens help me save money on my Azure bill? CloudKeeper Lens helps you identify potential cost savings opportunities by providing insights into your spending patterns. You can use this information to optimize your resource usage and choose the most cost-effective options. * ### Arrow 6.Is CloudKeeper Lens available on Azure Marketplace? Q6. Is CloudKeeper Lens available on Azure Marketplace? Yes, CloudKeeper Lens is available on * ### Arrow 7.How much does CloudKeeper Lens cost? Q7. How much does CloudKeeper Lens cost? CloudKeeper Lens is free for CloudKeeper AZ customers. For other users, there is a 30-day free trial, and after the trial period, the cost is 2% of your monthly cloud bill. * ### Arrow 8.How can I sign up for a free trial? Q8. How can I sign up for a free trial? Click * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Comprehensive Visibility into Your Cloud Infrastructure CloudKeeper Lens is our proprietary Google cloud cost analytics platform. It offers end-to-end visibility, personalized reporting, cost saving recommendations, and a detailed breakdown of your cloud spending to make smarter, data-driven decisions. * Resource level cost visibility * No access needed to GCP Account * Slack and MS Teams Integration * Unified view of multiple accounts How does CloudKeeper Lens help your business? CloudKeeper Lens provides a comprehensive and unified dashboard for your entire spending on Google Cloud. * Billing Summary with Resource-level Breakdown * Daily, weekly, and monthly cost summaries. * Service-wise cost break downs. * Granular view of individual instances. * Custom Spend Reports Generate daily and monthly reports tailored to your needs. Filter insights by project, service, SKUs, or resource family, providing more flexibility over your Google Cloud cost tracking. * Cost Breakups by Service and Resource Types Access detailed insights into cloud spending across service and resource types including * Compute and Storage Instance types. * Container and Serverless Resources. * Networking and Content Delivery. * Logging and Monitoring Services. * Tag-Based / Project-Wise Breakups * Analyze monthly cloud costs by projects or custom tags. * Ensure full cost visibility across all projects. * Resource-level cost and usage drill-downs. * Email and Slack Alerts * Proactive alerts on budget summaries, cost anomalies, and more. * Email, Slack and MS Teams integration. * Curated alerts focused on critical issues. Simplifying GCP Cost Monitoring for your FinOps team Get **customized reports and notifications** to fit your team's specific cloud cost visibility needs. Here are a **few of the many ways** CloudKeeper Lens empowers your team. * Finance Team A simplified, high-level monthly overview of all cost centers. * Engineering Team Daily cost breakdowns for precise tracking & resource planning. * Product Team Insights on Cloud Cost impact for different services. * DevOps Team Visibility into usage trends, with cost-saving recommendations. Easy Signup and Onboarding The signup process is just a few clicks away * Login to your Google Cloud Account * Give read access to GCP billing Account * Login credentials for CloudKeeper Lens will be shared ### Done! Get instant access to resource-level insights across your entire cloud infrastructure. ## Plan & Pricing * For CloudKeeper customers 1% of monthly cloud bill for CloudKeeper AZ customers. * For others 2% of monthly cloud bill. Our GCP Customers **Related Resources** * GCP Cost Optimization: Top 10 Effective Strategies for Maximum Impact Learn the basics of Google Cloud pricing models, challenges in saving costs and the best practices for effective GCP cost optimization. Blog * An Essential Guide to Accurate Cloud Cost Forecasting This article delves into the details of cloud budgeting and cloud cost forecasting and how you can manage your cloud cost overruns in your cloud FinOps journey. Blog * Best Practices for Cloud Cost Allocation and Cloud Tagging Cost allocation is critical for companies looking to improve cloud cost visibility thus reducing waste and optimizing cloud costs. Read more in this article. Blog Frequently Asked **Questions** * ### Arrow 1.Why is cloud cost visibility important? Q1. Why is cloud cost visibility important? Cloud cost visibility is crucial because it helps organizations avoid overspending and make smarter decisions about their cloud resources. Without clear insight into where the money is going, companies might end up wasting funds on unnecessary services or resources. This can also make it difficult to plan for the future or stay within budget. With better Google Cloud cost monitoring, organizations can spot areas where they're spending too much and find ways to cut costs. It also encourages accountability among the teams. * ### Arrow 2.What are the benefits of using CloudKeeper Lens? Q2. What are the benefits of using CloudKeeper Lens? CloudKeeper Lens helps you with: * Comprehensive & clear cloud cost visibility. * Data transfer cost analytics. * Kubernetes and Serverless usage costs tracking. * Alerts for cost spikes/unusual spending patterns. * Better cloud cost forecasting. * ### Arrow 3.What cloud platforms does CloudKeeper Lens support? Q3. What cloud platforms does CloudKeeper Lens support? CloudKeeper Lens is a cloud cost visibility and recommendation platform available for AWS and Google Cloud. * ### Arrow 4.How can CloudKeeper Lens help me save money on my GCP bill? Q4. How can CloudKeeper Lens help me save money on my GCP bill? CloudKeeper Lens helps you identify potential cost savings opportunities by providing insights into your spending patterns. You can use this information to optimize your resource usage and choose the most cost-effective options. * ### Arrow 5.How much does CloudKeeper Lens cost? Q5. How much does CloudKeeper Lens cost? CloudKeeper Lens cost 1% of monthly bill for CloudKeeper AZ customers. For other users, the cost is 2% of monthly cloud bill. * ### Arrow 6.How can I sign up for a trial? Q6. How can I sign up for a trial? Click * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Bring Lens insights into AI tools with CloudKeeper LensGPT Your Agentic FinOps Consultant - Combines the Power of Multiple AI Tools Built for multiple personas Chief Financial Officer Engineering ManagerFinOps AnalystProduct Owner ‹› # We’re reshaping how organizations approach FinOps! The Challenge Getting cloud cost answers meant navigating dashboards, filters, and exports. Often, insights arrive too late to act. Not anymore! The Solution CloudKeeper LensGPT is an agentic FinOps consultant that provides real-time cost insights, optimization actions, and expert guidance through natural conversation. Decode bills with clear answers **in seconds.** Move from reactive reviews to **proactive optimization.** Action-ready cost insights for every team, in their **own language.** Ask questions like you're texting a colleague. Get answers like you hired a FinOps expert. How CloudKeeper LensGPT **Addresses the Gap & Transforms Your FinOps Practice** Problems Without LensGPT With LensGPT ### Ad-hoc analysis is slow and skill-dependent Generating ad-hoc reports requires building custom views and writing complex queries in BI platforms to answer a simple query. #### Ask. Analyze. Act. Get a comprehensive analysis instantly through simple prompts - no complex queries, no dashboards or filters. ### Reports don't translate into real FinOps advice Reports show the data not direction. It doesn't explain the root cause, estimate savings, and guide you through implementation. #### Insights That Guide Action LensGPT doesn't just show data, it acts as a consultant. It identifies the root cause, estimates savings & shares implementation steps. ### Recommendations lack architectural context Traditional tools flag recommendations and give insights based on billing exports only. #### Infrastructure-Aware Recommendations It understands your account structure, regions, environments, and how your services connect - then brings all that context together to deliver smarter, architecture-aware insights. ### Scalability & Access Bottleneck FinOps expertise is locked inside one person or a small team, creating a bottleneck for other stakeholders that delays decisions #### FinOps Insights for Anyone, Anytime. Every team member can now converse with the data directly to gain the precise insights they need. **From dashboards to dialogue: Why LensGPT stands apart** LensGPT understands your infrastructure, recommends actions, and explains trade-offs. Ask any question and get trusted, **context-rich answers instantly,** without relying on reports or bill-only tools. * **Always-on Insights** **Stop discovering issues at month-end, ask LensGPT, and it will create a dashboard and fetch analysis on the fly to support instant decision-making.** **** **** **** * **Agentic, Not Just Chatty** **Multiple specialized AI tools that work together. Chains steps to solve complex problems. Returns action plans, not just answers.** **** **** **** * **Built on Real FinOps Experience** **Powered by CloudKeeper's work with hundreds of cloud environments. Every recommendation reflects patterns we've seen work in production—not just what looks good in a chart.** **** **** **** * **Enterprise-Ready from Day One** **Role-based access and secure data handling. LensGPT fits into your compliance and governance frameworks, not around them.** **** **** **** * **** **** **Unlock Lens intelligence inside AI tools with****LensGPT MCP Server** Connect LensGPT to AI tools like Claude Desktop, Cursor, Windsurf, Kiro and more using LenGPT MCP (Model Context Protocol), and get cloud intelligence directly inside your AI tool. # Give every team the cost insights they need, in their own language Leadership & Strategy Engineering Finance FinOps & CloudOps **How LensGPT works** * ### Data & Intelligence Layer Ingests cloud cost data, enriches with metadata, and models spend across services, accounts, and environments. * ### AI & Orchestration Layer Interprets natural-language queries and runs FinOps-specific analysis workflows behind the scenes. * ### Security & Governance Encrypts data end-to-end with role-based access to control who sees what. * ### Integrations & Workflow Plug-and-play with CloudKeeper Lens to enable smooth, connected workflows. **** **** **Ready to make cloud cost intelligence as simple as a conversation?** Put an agentic FinOps consultant in the hands of every team. Just ask, act & analyze! **Related Resources** * Why 2026 Is the Year to Invest in AI-Powered Cloud Optimization This blog explores why 2026 is a pivotal year for AI-powered cloud optimization, driven by the rapid growth of AI workloads and soaring cloud expenses. Blog * Generative AI Explained: Concepts, Tools & Important Use Cases A clear, practical guide to Generative AI covering core concepts, future trends, leading tools, and real-world industry applications. Blog * FinOps for Generative AI Cost Optimization: Balancing Scale, Speed, and Spend Learn how FinOps empowers organizations to control rising Generative AI costs, optimize token and compute spend, and scale innovation sustainably. Blog * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Deliver high-quality, seamless content with a cost-efficient cloud infrastructure ### Our **Media & Entertainment** Customers * USA Digital Content Distribution * USA Cloud-based Streaming & Solution * India Satellite Television Services * UK Subscriber Management platform * Canada Online Book Publishing * India Audio Storytelling Platform * USA Virtual Event Platform ### Immersive Experience, Global Reach, & Buffer-free Content Delivery #### The Global Digital Media Market is set to hit $8 billion by 2031, driven by ultra HD & buffer-less content streaming demand. A single buffering event can cause up to 40% of viewers to lose interest. Here’s how CloudKeeper helps you keep up with modern market expectations. * Buffer-less content Billions of hours of video are watched daily, but legacy infrastructure can cause buffering, pushing viewers to leave your platform. CloudKeeper modernizes your systems for uninterrupted streaming, ensuring a seamless user experience. * Cost-Efficient Storage Solutions Non-scalable storage leads to reduced system availability and disrupts continuity. CloudKeeper optimizes your storage infrastructure cost efficiently, ensuring flexible scalability and reliable uptime, for uninterrupted operations. * Content Protection Ineffective measures against content piracy and vulnerabilities in user authentication pose significant risks. We ensure cloud security protocols and ensure secure user access. * Scalable Infrastructure Unpredictable traffic surges during live broadcasts and real-time bookings demand scalable infrastructure. CloudKeeper ensures your setup is flexible as per demand for reliable content delivery without sacrificing quality. * Cloud Cost Optimization The high costs associated with production, storage, and distribution necessitate cost efficiency. CloudKeeper's cloud cost optimization strategies help to reduce the overhead by efficiently managing resources. * Ultra-low latency Content Delivery Achieve frictionless & high-quality streaming with ultra-low latency CNDs. Ensure high-compute servers with advanced content caching to deliver smooth playback of binge-worthy content anywhere, anytime. ### Here’s how we empower Media & Entertainment Companies #### From instant cloud savings to long-term growth, we support your entire cloud journey! * Results from Day 1 Achieve instant & guaranteed cloud cost savings on your entire cloud bill, right from Day 1. * Automated Cloud Management Simplify cloud operations with a powerful suite of tools for intelligent optimization & enhanced governance. * 24*7 Support by Certified Experts We act as your cloud cost management vertical, handling end-to-end cloud needs. * Cloud FinOps Services Get FinOps consulting by cloud-certified experts to establish a strong FinOps culture. * Cloud Modernization Harness the latest in cloud technology and achieve peak performance with our 3-phase approach. * Exclusive Partner Benefits Get best-in-market discounts & benefits on AWS EDP, PPA & MAP. Access top-tier cloud support at discounted rates. * We own your Commitment Risk Get the freedom to run everything on-demand at commitment-based pricing while we own your risk. * Customized WAR Get custom recommendations to ensure your setup is optimized for performance, security, and cost-efficiency. ### Our **Success Story** CloudKeeper enables Frequency, a cloud-based streaming solution, to achieve significant cost savings with efficient cloud cost management. Values delivered * Automated cloud infrastructure management to reduce error and improve efficiency. * Implementing cost-saving strategies & eliminating unused resources. * Regularly review and refine cloud infrastructure configurations to ensure optimal performance. We have expertise across leading cloud platforms * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure What Our Clients Say From DevOps engineers to CTOs, CFOs, and CEOs — CloudKeeper is loved by all! * Cost savings kicked in immediately and were reflected in the next month’s bill. A second set of savings came in the longer term is due to the team, process and the tools that highlighted the areas we might look in to save money. Steven Thurlow CEO **Related Resources** * An Essential Guide to AWS EDP to Bag High Discounts The AWS Enterprise Discount Program (AWS EDP) is an enterprise-level cloud program with substantial benefits on their AWS cloud spending. * Cloud Cost Savings Definitive Guide: Proven Strategies, Best Practices & Hacks This blog deep dives into both instant and long-term cloud cost savings strategies, providing practical approaches that maximize value from your cloud investments. * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close CloudKeeper Prism Centralized Identity and Access Management for Enterprises Enterprise‑grade security with zero friction Single Sign-On across cloud, SaaS & on‑prem Self-hosted & hybrid deployments for data residency Supports different identity providers, multiple times ## The IAM challenges enterprises face today Modern enterprises struggle to balance speed, scale, and security as identities multiply across users, apps, and machines. * #### Fragmented access Multiple identity providers, siloed apps, and inconsistent policies lead to poor user experience and operational overhead. * #### Security vs productivity trade-offs Strong security often introduces friction - passwords, MFA fatigue, and manual approvals slow teams down. * #### Human + Machine Identities Non-human identities (APIs, bots, services) now outnumber human users. Traditional IAM wasn't built to manage this scale. * #### Visibility Gaps Organizations can't effectively monitor who has access to what. These blind spots create scope for breaches. * #### Compliance & data residency pressure Regulations demand strict control over identity data, audit trails, and where sensitive information is stored. Why Choose **CloudKeeper Prism SSO?** Powerful features, including everything you need to manage workforce access securely and at scale * Self-hosted & Data Residency Deploy Prism inside your own VPC, private cloud or on-premise environment to meet compliance and residency requirements. * 1‑click replication from AWS IAM Identity Center Replicate users and groups directly from AWS IAM Identity Center to CloudKeeper with a single click. Reduce manual work and sync errors. * Multi-Identity Provider Support Connect CloudKeeper to existing identity systems like Google Workspace, Zoho Directory, or any OIDC-based IdP with minimal setup. * Enterprise Controls & Compliance Centralized enterprise controls with role-based access, automated user provisioning, enforced MFA, and full audit visibility. How **CloudKeeper Prism Stands Apart** Features Traditional IAM/SSO Tools CloudKeeper Prism ### Deployment Options Cloud-only Cloud + Self-Hosted + Hybrid ### Identity Providers Limited (1 provider at a time) Any OIDC provider, supports multiple providers at a time ### AWS IAM Migration Manual, weeks-long process 1-Click Replication ### Enterprise Controls & Compliance Basic controls, limited compliance depth Granular RBAC, SCIM, MFA. ### Data Residency & Security Data hosted in vendor-controlled regions Full control over the identity data location **Enterprise Single Sign-On, Your Way** ## Multi-Regional Enterprise Deploy CloudKeeper in your region to ensure data residency compliance across GDPR, CCPA, and other regulations while maintaining unified identity management. ## Vendor Integration Manage contractor and vendor access with temporary credentials, time-limited permissions, and detailed audit trails for compliance. ## Multi-Cloud Architecture Support teams across AWS, GCP, and Azure with a single identity platform. Manage access to cloud resources and SaaS applications from one dashboard. ## Multi-Regional Enterprise Deploy CloudKeeper in your region to ensure data residency compliance across GDPR, CCPA, and other regulations while maintaining unified identity management. ## Vendor Integration Manage contractor and vendor access with temporary credentials, time-limited permissions, and detailed audit trails for compliance. ## Multi-Cloud Architecture Support teams across AWS, GCP, and Azure with a single identity platform. Manage access to cloud resources and SaaS applications from one dashboard. ## Multi-Regional Enterprise Deploy CloudKeeper in your region to ensure data residency compliance across GDPR, CCPA, and other regulations while maintaining unified identity management. ‹› **** **** **Ready to Simplify Identity Management?** Join hundreds of enterprises already using CloudKeeper to secure their access with flexibility and control. Trusted by 400+ Global Customers Our customers saved an average of 20% on their monthly AWS and GCP spend through CloudKeeper * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Enhance your customer experience with a cost-efficient infrastructure ### Our **Retail and E-commerce** Customers * India Multinational eyewear company * India Online healthcare platform * India Online milk and grocery delivery * USA Marketplace for local services * India Online grocery delivery app * Singapore Women’s clothing and fashion retailer * Australia Office supplies & stationery retailer * USA One Retail Execution Software for All In-Store Teams ### We help future-proof your **infrastructure** #### The retail & e-commerce landscape is highly competitive and just a one-second delay can lead to a 7% drop in conversions. Thus, delivering an outstanding customer experience is crucial and your cloud setup plays a key role here. * High speed and performance CloudKeeper optimizes your infrastructure for peak performance, ensuring speed and a seamless user experience that keeps customers coming back. * Zero Downtime Handle traffic spikes during high-demand periods, new product launches, or holiday seasons without compromising performance. We ensure zero downtime, no matter the load. * Cloud Cost Optimization Running your platform on the cloud can increase costs as you scale. We help you effortlessly manage and reduce expenses, ensuring profitability as the business grows. * Security & Data Protection We help to keep sensitive customer data protected from breaches and ensure infrastructure compliance, giving you peace of mind while maintaining customer trust. * Flexible Scalability CloudKeeper helps you easily scale your infrastructure up or down as per the demand, cutting costs on computing resources without sacrificing performance. * Risk-Free Experimentation Run pilot programs and new launches without being tied to expensive, restrictive cloud contracts. Focus on continuous innovation with the flexibility to run POCs with CloudKeeper. ### Here’s how we empower retail & e-commerce businesses #### From instant cloud savings to long-term growth, we support your entire cloud journey! * Results from Day 1 Achieve Instant & Guaranteed Savings on your entire cloud bill right from Day 1 * Automated Cloud Management Simplify cloud operations with CloudKeeper Auto, Lens, and Tuner, a powerful suite of tools for intelligent optimization. * Personalized Support by Certified Experts We act as your cloud cost management vertical, handling end-to-end cloud needs, especially during peak traffic. * We own your Commitment to Risk Get the freedom to run everything on-demand at commitment-based pricing while we own your risk. * Efficiency & Risk Management Our proactive & tailored approach detects anomalies, mitigates potential overruns and cloud sprawl risks. * Exclusive Partner Benefits Get best-in-market discounts & maximum benefits on AWS EDP, PPA, MAP. Access top-tier cloud support at discounted rates. * Improved Governance Effective cost allocation, chargeback, and tagging to enhance governance and data-driven decision-making. * Customized Well-Architected Reviews Get automated assessments and custom recommendations from our cloud-certified experts. ### Our **Success Story** How eLocal is leveraging CloudKeeper to adopt FinOps best practices & reduce their AWS cost by 25% Values delivered * Immediate cloud savings of 10% * Further cost reduction by 15% through architectural-level optimizations * Efficient resource allocation and cost savings * Comprehensive cloud cost visibility * Amit Poddar CTO, eLocal It was probably the easiest onboarding I have seen in ages. I was very delighted to see that in just one day of engagement, the savings started kicking in. The moment billing was switched, we saw that the next month's bill went down by 7-10%. The services & recommendations further led to significant savings. We have expertise across leading cloud platforms * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure What Our Clients Say From DevOps engineers to CTOs, CFOs, and CEOs — CloudKeeper is loved by all! * Cost savings kicked in immediately and were reflected in the next month’s bill. A second set of savings came in the longer term is due to the team, process and the tools that highlighted the areas we might look in to save money. Steven Thurlow CEO **Related Resources** * An Essential Guide to AWS EDP to Bag High Discounts The AWS Enterprise Discount Program (AWS EDP) is an enterprise-level cloud program with substantial benefits on their AWS cloud spending. * Cloud Cost Savings Definitive Guide: Proven Strategies, Best Practices & Hacks This blog deep dives into both instant and long-term cloud cost savings strategies, providing practical approaches that maximize value from your cloud investments. * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Enabling SaaS & ISVs to disrupt & scale fearlessly on cloud ### Our **SaaS & ISV** Customers * USA All-in-one platform for virtual events * USA Project & portfolio management software * Singapore Cloud communication services provider * India Conversational AI and chatbot solutions * USA Economic impact analysis software provider * India Scientific SaaS Enterprise Platform * India Logistics and supply chain platform ### Here’s how CloudKeeper will help you establish a resilient infrastructure and **modernized cloud strategy** * Ever-Evolving Customer Expectations Users demand free trials, fast self-service, and frictionless onboarding. CloudKeeper ensures your cloud setup is resilient enough & always optimized for high performance. * Intense Market Competition Focus on continuous innovation with the flexibility to run POCs with CloudKeeper, without being tied to expensive, restrictive cloud contracts. * Global Ambitions Be ready for new market entry with infrastructure tailored for rapid global expansion. We also provide a program for GTM enablement & scaling to support your journey. * Scaling Multi-Tenancy CloudKeeper helps to manage multi-tenancy environments efficiently while ensuring data isolation and optimal performance. * Cost Optimization Conundrum Rising cloud costs can erode your profits as you scale. Prevent this with CloudKeeper’s comprehensive suite of smart cost optimization solutions. * Cloud Commitment Liability Thinking of doing a pilot project but can’t commit even for a year? With CloudKeeper, you get to experiment without getting locked into expensive cloud commitments. ### A Partnership that benefits your Team, your Business, and your Customers #### From instant cloud savings to long-term growth, we support your entire cloud journey! * Results from Day 1 Achieve Instant & Guaranteed Savings on your entire cloud bill right from Day 1. * Better Visibility & Accountability Gain clarity & control over your cloud expenditures. * Support by Certified Experts We act as your cloud cost management vertical, handling end-to-end cloud needs. * We own your Commitment Risk Run everything on-demand at commitment-based pricing while we own your risk. * Efficiency & Risk Management Our proactive & tailored approach detects anomalies, mitigates potential overruns and cloud sprawl risks. * Exclusive Partner Benefits Get maximum benefits on AWS EDP, PPA, MAP. Access top-tier cloud support at discounted rates. * Cloud Marketplace Integration Open a new revenue channel with * Customized Well-Architected Reviews Get automated assessments and custom recommendations from our cloud-certified experts. Supercharge your growth and achieve goals faster with CloudKeeper ISV Accelerate! * Seamless Marketplace Integration * Foundational Technical Reviews * Strategic & Technical Guidance * CPPO Partnerships & More! ### Our **Success Story** How Damstra reduced their entire AWS spends by 22%, working with CloudKeeper Values delivered * Instant savings of 12% on entire AWS costs * 10% cost reduction through architectural optimizations * Enhanced cloud cost visibility & reporting * Proactive anomaly detection & resolution * Damien Camilleri Chief Technology Officer, Damstra CloudKeeper really helps us keep control of our cloud costs in a simple and concise format. It is easy to track down cost increases and anomalies across all of our cloud accounts. We have expertise across leading cloud platforms * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure What Our Clients Say From DevOps engineers to CTOs, CFOs, and CEOs — CloudKeeper is loved by all! * Cost savings kicked in immediately and were reflected in the next month’s bill. A second set of savings came in the longer term is due to the team, process and the tools that highlighted the areas we might look in to save money. Steven Thurlow CEO **Related Resources** * An Essential Guide to AWS EDP to Bag High Discounts The AWS Enterprise Discount Program (AWS EDP) is an enterprise-level cloud program with substantial benefits on their AWS cloud spending. * Cloud Cost Savings Definitive Guide: Proven Strategies, Best Practices & Hacks This blog deep dives into both instant and long-term cloud cost savings strategies, providing practical approaches that maximize value from your cloud investments. * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close CloudKeeper Tuner An Automated AWS Usage Optimization & Recommendation Platform * 50+ AWS Services included * 150+ Different recommendations * 10% Average savings delivered × Achieve the lowest possible cost without compromising performance CloudKeeper Tuner, **a real-time assistant for smarter AWS cost and usage optimization,** easily **fits into your flow of work** across multiple AWS accounts. It delivers tailored recommendations and enables you to optimize resources effortlessly while maintaining peak performance for your AWS workloads. * **Backed by 150+** **AWS-certified** engineers for faster implementation * **Seamlessly integrates** within AWS Console, with an extension * **Displays estimated savings ($ value)** for each recommendation * **Slack and MS** Teams Integrations Achieve peak AWS efficiency with targeted optimizations across 3 critical areas Recommendations * Cleaner Identifies zombie and unused resources in the accounts. * Over-provisioned Detects and optimizes over-allocated compute and storage services. * Modernization Upgrade to the latest AWS resources for better performance & savings. Scheduler * Automatically shut down idle cloud resources during off-office hours to avoid unnecessary expenses. * Reduce environmental impact by lowering energy usage through optimized resource scheduling. SpotBot * Save up to 65% by dynamically switching ECS fargate tasks between Spot and On-Demand based on availability. * Ensure seamless ECS task execution by balancing cost and instance availability. Your browser does not support HTML video. Your browser does not support HTML video. Your browser does not support HTML video. AWS Usage Optimization, Simplified for Engineers The only platform your DevOps & engineering teams need; offers the **widest AWS services coverage in the industry - covering 90% of your bill.** Your browser does not support HTML video. Upgrade Your AWS Console to **Genius Mode with Tuner Extension!** Get real-time & impactful recommendations tailored for your resources within your AWS console instantly. Add to: * * * * * The CloudKeeper Tuner Difference * Smart Data Ingestion Passively collect usage and cost telemetry from your accounts as the engineering updates occur. * Intelligent Optimization Algorithm Advanced algorithms governed by Cloud Well-Architected framework and principles. * Real-time Assistant Designed for engineering teams, fits into the flow of work offering real-time recommendations along with measurable ROI. Plan & Pricing * For CloudKeeper customers 30-day free trial! 1% of monthly AWS Bill for CloudKeeper AZ & EDP+ customers. * For others 30-day free trial! 2% of your monthly AWS bill after the trial period. How to Get Onboarded * Step 1 Sign up & create your account on Tuner. * Step 2 Connect your AWS account with read-only IAM access via the Automated CloudFormationTemplate or Manual process. * Step 3 You are now ready to access your dashboard and start optimizing your cloud usage. We are on Try CloudKeeper Tuner today to witness its impact on your AWS cloud cost savings! CloudKeeper Tuner Customers **Related Resources** * The Must-have AWS Cloud Optimization Tool for Your Engineering Team Explore CloudKeeper Tuner, an industry-first real-time & automated AWS Cloud Usage Optimization platform offering 150+ Recommendations across 50+ AWS Services. Blog * Best practices to cut down your AWS spend by 5-15% Dive deeper into some best practices, lesser-known facts and quick-fixes, to optimize your AWS spend for your business needs and reduce cloud costs. Whitepapers * 20 Tips and Tricks to Make AWS Work to Your Advantage Tap into the true potential of AWS Services with some cool hacks to save your cloud costs and to manage your cloud infrastructure effectively. Blog * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close #### CloudKeeper Tuner # An Automated Usage Optimization & Recommendation Platform for Google Cloud ### Trusted & Loved by Engineers * 100% Idle resources elimination ### Automated scheduling to cut idle spend * 10-15% Average savings delivered ### Smart recommendations with clear savings * 150+ Certified cloud engineers ### Cost optimization without performance risk **Reduce cloud usage without risking workload stability** CloudKeeper Tuner, an automated GCP optimization platform, monitors your cloud usage without disrupting your workflow. * Problem: Zombie resources are draining your budget Detect and remove zombie resources instantly. * Problem: Unclear ROI on optimization efforts Get actionable recommendations with calculated dollar-value savings * Problem: Paying for resources when not in use Automatically schedule resources to run only when needed * Problem: Engineering time lost to manual optimization Free teams to innovate by automating cost management tasks * Problem: No policy-driven resource management Implement automated compliance checks & audit trails across projects **Built for DevOps and Engineering Teams** The only platform your team needs for ongoing savings and efficient management of multi-project GCP environments * **** **Intelligent Cleaning** **Instantly identify and remove unused IPs, unattached** **disks, and "zombie" resources.** **** **** * **** **Calculated ROI** **Recommendations display the estimated savings in** **dollars before you act.** **** **** * **** **Multi-Project & Billing Visibility** **Centralized view across all your GCP projects and** **billing accounts.** **** **** * **** **Right-Sizing Alerts** **Detect over-allocated resources and get right-sizing** **recommendations to reduce unnecessary cloud spend.** **** **** * **** **Slack Integrations** **Receive daily alerts and recommendations directly in Slack,** **with human-assisted prioritization to avoid alert fatigue.** **** **** * **** **Security First** **Operates with read-only access, keeping your** **infrastructure secure and under control.** **** **** **** **** **Stop Overpaying for Google Cloud Today** Join high-growth companies saving thousands on their monthly GCP bills. Setup takes less than 5 minutes. ## Why CloudKeeper Tuner? * #### GCP-Native Intelligence Algorithms governed by Google Cloud Well-Architected principles to ensure performance never drops. * #### Policy-Based Scheduling Automate stop/start for non-production workloads with full control. * #### Unified Visibility Manage and optimize multiple GCP accounts from a single pane of glass. * #### Passive Telemetry Collects usage and cost data in the background as engineering updates occur, requiring no manual effort. * #### Human Expertise Backed by 150+ certified cloud engineers to assist with complex architectural decisions. ## How to Get Onboarded * Log in and link your GCP project using a secure, read-only IAM role. Connect * Analyze The platform ingests telemetry to identify idle resources and optimization opportunities. * Apply recommendations or set automated schedules via the dashboard to see immediate savings. Optimize ## Plan & Pricing * For CloudKeeper customers 30-day free trial! 1% of the monthly GCP Bill for CloudKeeper customers. * For others 30-day free trial! 2% of your monthly GCP bill after the trial period. Our Customers Frequently Asked **Questions** * ### Arrow 1.Does CloudKeeper Tuner require write access to my GCP account? Q1. Does CloudKeeper Tuner require write access to my GCP account? We need Read-only access for usage and cost telemetry. No write permissions are required to generate recommendations. * ### Arrow 2.How quickly will I see recommendations? Q2. How quickly will I see recommendations? Recommendations appear shortly after the initial data ingestion, typically within 24 hours of connecting your account. * ### Arrow 3.Is this tool suitable for multi-project organizations? Q3. Is this tool suitable for multi-project organizations? Yes. You can connect and monitor multiple GCP projects under a single CloudKeeper Tuner dashboard. * ### Arrow 4.Will the scheduler affect my production workloads? Q4. Will the scheduler affect my production workloads? You have full control. You define the schedules and select which specific instances to automate, ensuring production remains untouched. * ### Arrow 5.How is this different from native Google Cloud recommendations? Q5. How is this different from native Google Cloud recommendations? We provide granular, resource-level scheduling and "zombie" resource detection with a focus on workflow integration (Slack) and dollar-value clarity. * ### Arrow 6.Is there a cost to get started? Q6. Is there a cost to get started? You can sign up and receive your initial optimization report for free. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * In Association With * Networking Partner * Venue Partner ## About Ctrl+Cloud CTRL+Cloud is a tech meetup for engineers passionate about **Cloud and DevOps**. The first edition in Bengaluru is focused on empowering you to build and scale cloud infrastructure effectively. Join us for tech kickoff, expert-led discussions, and networking opportunities to explore the latest **strategies in cloud optimization** , high availability, and performance at scale. **This event is tailored for:** * DevOps Engineers * Software Developers * SREs (Site Reliability Engineers) ## Our Agenda * Time slot * Event details * 3:00 - 3:05 PM * Welcome Address * 3:05 - 3:20 PM * Ctrl + Play * 3:20 - 3:40 PM * Lightning talks * Reliability with Multi- AZ Cloud infrastructure Head- Cloud Infra, JAR * Architecting Scalable Applications in AWS Well-Architected Lead, CloudKeeper * 3:40 - 3:50 PM * Spotlight on CloudKeeper * 3:50 PM Onwards * Sync & Snacks ## Meet the Cloud Experts * Host ### Praneet Chandra Senior Director, CloudKeeper * Speaker ### Rohan George Head- Cloud Infra, JAR * Speaker ### Aditya Ajay Well-Architected Lead, CloudKeeper About CloudKeeper CloudKeeper is a cloud cost optimization partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & usage optimization platform to reduce cloud costs & help maximize the value from the cloud. We have helped **400+ global companies** save an average of **20% on their cloud bills** , all while maintaining flexibility and avoiding any long-term commitments or costs. We have expertise across leading cloud platforms * * close close # Overcome Cloud Challenges with CloudKeeper : Let's Connect! Navigating your initial cloud setup or optimizing your cloud costs and infrastructure? CloudKeeper has the solutions you need. Tell us about your challenges, and CloudKeeper will help you with: * Unlimited Cloud Support * Guaranteed Cost Savings * Enhanced Cloud Cost Visibility For any further information or queries, drop us an email at hello@cloudkeeper.com and we will get back to you. Our Offices * Singapore 3 Shenton Way, #13-05, Shenton House, Singapore (068805) **Tel: +65-98637375** * India 2nd Floor, NSL Techzone, Sector 144, Noida, Uttar Pradesh 201306, India **Tel: +91 120 4601800** * US Meril Lynch Building, 101 Hudson St, Ste 2100, Jersey City, NJ 07302 **Tel: +1 (201) 633-2314** It's official - CloudKeeper is customers’ favorite! CloudKeeper prioritizes long-term relationships based on trust & mutual growth and has been an extended arm for us to streamline our cloud infrastructure management! - Verified G2 Review Trusted by 400+ Global Customers Our customers saved an average of 20% on their monthly AWS and GCP spend through CloudKeeper Be the first to know the latest Cloud & FinOps insights and news! More to Explore * What's in the news? Stay updated with the latest and greatest happenings at CloudKeeper! * Join Our Growing Team! An awesome workplace awaits you! Explore recent job openings at CloudKeeper. * Thought Leadership! Read the latest and exclusive content curated by FinOps and cloud professionals. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close What’s **In It For You?** Over the course of a few years, you must have heard phrases like **‘cost optimization benefits’, ‘you must optimize your cloud costs’, ‘reserved instances are the way to go’ and more**. What you don’t have is a ready checklist of extremely focused questions that can enable you to carefully identify what your cloud cost reduction strategy is missing. After sitting down with our cloud experts, we’ve come up with a clear **10-pointer checklist** for reducing your cloud costs with ease. We have done the work, so you don’t have to. During the session, we’ll cover everything that you need to know to start seeing real savings. Plus, the attendees will receive an **exclusive checklist** along with early access to a detailed guide, giving them everything they need to implement these **cost-saving techniques** right away! Know the **Panelists** Meet our expert panelists, each bringing unique insights and experience to the table. * ### Praneet Chandra Senior Director, CloudKeeper Moderator * ### Ronak Goyal Senior Director of Product Management, CloudKeeper Speaker * ### Manoj Patel Chief Product and Technology Officer, Kofluence Speaker Our **Key Takeaways** * 10 Mins Introduction & Session Overview * 15 Mins Top Business & Tech Challenges in Cloud Cost Management * 20 Mins The 10-Point Cloud Cost Reduction Checklist * 15 Mins Interactive QnA & Real-World Scenarios About **CloudKeeper** CloudKeeper is a Comprehensive Cloud Cost Partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & usage optimization **platform to reduce your cloud cost & help you maximize the value from AWS, Microsoft Azure, & Google Cloud**. We have helped **400+ global companies** save an average of **20% on their cloud bills** , modernize their cloud set-up and maximize value — all while maintaining flexibility and avoiding any long-term commitments or cost. AWS Premier Consulting Partner since 2013 Premier Partner & Governing Member of the FinOps Foundation Leader in the G2 Grid for Cloud Cost Management Microsoft Solutions Partner close close What’s **In It For You?** Over the course of a few years, you must have heard phrases like **‘cost optimization benefits’, ‘you must optimize your cloud costs’, ‘reserved instances are the way to go’ and more**. What you don’t have is a ready checklist of extremely focused questions that can enable you to carefully identify what your cloud cost reduction strategy is missing. After sitting down with our cloud experts, we’ve come up with a clear **10-pointer checklist** for reducing your cloud costs with ease. We have done the work, so you don’t have to. During the session, we’ll cover everything that you need to know to start seeing real savings. Plus, the attendees will receive an **exclusive checklist** along with early access to a detailed guide, giving them everything they need to implement these **cost-saving techniques** right away! Know the **Panelists** Meet our expert panelists, each bringing unique insights and experience to the table. * ### Praneet Chandra Senior Director, CloudKeeper Moderator * ### Ronak Goyal Senior Director of Product Management, CloudKeeper Speaker * ### Aman Dixit Associate Director - Strategic Initiatives, CloudKeeper Speaker Our **Key Takeaways** * 10 Mins Introduction & Session Overview * 15 Mins Top Business & Tech Challenges in Cloud Cost Management * 20 Mins The 10-Point Cloud Cost Reduction Checklist * 15 Mins Interactive QnA & Real-World Scenarios About **CloudKeeper** CloudKeeper is a Comprehensive Cloud Cost Partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & usage optimization **platform to reduce your cloud cost & help you maximize the value from AWS, Microsoft Azure, & Google Cloud**. We have helped **400+ global companies** save an average of **20% on their cloud bills** , modernize their cloud set-up and maximize value — all while maintaining flexibility and avoiding any long-term commitments or cost. AWS Premier Consulting Partner since 2013 Premier Partner & Governing Member of the FinOps Foundation Leader in the G2 Grid for Cloud Cost Management Microsoft Solutions Partner close close Smoother, Faster, and Secure Software Delivery Bridge the gap between development and operations seamlessly. CloudKeeper empowers you to accelerate software delivery through automated workflows and industry-leading DevOps consulting services and practices. * One-click deployments and rollback * Configure Automated Alerts * Centralized Log Management * Infrastructure Security * Continuous Process * Continuous Integration * Disaster Recovery * Performance Optimization Integrated DevOps Consulting Services Toolkit Explore our holistic array of tools and platforms, designed to optimize your development and operations workflows ## Architecture * * * * * * * * * * ## Database * * * * * * * * ## Configuration * * * * * * * ## CI/CD * * * * * * ## Monitoring * * * * * * ## Log Mgmt * * * * * ## Coding & Scripting * * * * DevOps Service Capabilities Extensive DevOps consulting service designed to enhance your development and operations workflows ## DevOps Assessment * Audit existing infrastructure development pipeline * Report outlining action for automation * Evaluate DevOps practices & share implementation roadmaps ## DevOps Automation * Manage continuous health of the delivery pipeline * Release management * Replica environment or new server setup * Change management & performance optimization ## DevOps Management * Set-up & automate continuous delivery pipeline * Prevent unsecured deployment * Robust ecosystem of open- source & licensed tools Multi-Cloud **Capabilities** With top-tier partnerships and certified cloud professionals, CloudKeeper offers migration expertise across all major cloud providers. * * Trusted by 400+ Global Customers Our customers saved an average of 20% on their monthly AWS and GCP spend through CloudKeeper **Related Resources** * How to Automate AWS Resource Optimization with DevOps Tools? Learn how to Streamline AWS Resource Optimization Using DevOps Tools. Discover efficient strategies to enhance performance, reduce costs, and boost productivity. Blog * AWS RDS Cost Optimization Strategies for DevOps and DBAs Learn the provisioning best practices and cost optimization techniques that can help reduce AWS RDS costs while improving their performance. Blog * Right-Sizing Your AWS EC2 Instances: Strategies and Best Practices for Every DevOps Team Right sizing strategies for AWS EC2 instances, to help DevOps professionals prevent cloud waste, reduce AWS costs and streamline their EC2 infrastructure. Blog Frequently Asked **Questions** * ### Arrow 1.What is DevOps? Q1. What is DevOps? DevOps is a set of practices that combine software development (Dev) and IT operations (Ops) to shorten the development lifecycle and deliver high-quality software more efficiently. It emphasizes automation, continuous integration and delivery, and collaboration across teams. * ### Arrow 2.What is DevOps Consulting Services? Q2. What is DevOps Consulting Services? DevOps Consulting Services helps businesses streamline development and operations through automation, collaboration, and cloud integration. Services include workflow assessment, CI/CD setup, infrastructure automation, and performance monitoring, enabling faster delivery, disaster recovery, better reliability, and efficiency. * ### Arrow 3.How does DevOps benefit my business? Q3. How does DevOps benefit my business? DevOps helps businesses achieve faster software delivery, improved collaboration, higher deployment frequency, better resource utilization, and higher quality software. It also enables businesses to respond quickly to market demands and customer feedback * ### Arrow 4.What is the relationship between DevOps and Cloud? Q4. What is the relationship between DevOps and Cloud? DevOps and cloud computing go hand in hand. The cloud provides a flexible, scalable, and cost-efficient infrastructure for DevOps teams to develop, test, and deploy software. Cloud services allow for automation, scalability, and high availability, making it easier for DevOps teams to manage workloads, deploy applications, and integrate continuous delivery pipelines. Cloud platforms like AWS, Azure, and Google Cloud provide the tools and services that support DevOps practices, enabling faster development cycles and efficient resource management. * ### Arrow 5.Are DevOps consulting services only for large enterprises? Q5. Are DevOps consulting services only for large enterprises? No, DevOps consulting services are not limited to large enterprises. They benefit organizations of all sizes by streamlining workflows, improving collaboration, and automating processes to enhance efficiency and scalability. * ### Arrow 6.How do DevOps consulting services help startups? Q6. How do DevOps consulting services help startups? DevOps consulting helps startups by implementing efficient workflows, automating repetitive tasks, and enabling faster software delivery. This allows startups to scale quickly, reduce costs, and focus on innovation while maintaining reliability and quality. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close CloudKeeper Generative AI Launchpad: **10× Faster from Idea to PoC** * Certified AI specialists with deep cloud experience * Pre-built frameworks and reusable components * Cloud-native implementation across AWS and GCP * Built-in cost optimization from Day 1 Are your AI Pilots stuck in Proof-of-Concept stage? **Agile teams using AI grow 1.5x faster** & are more likely to achieve growth. But do you know, only about **5% of pilots have made it into production with measurable value.** Global AI investment is exploding, yet most organizations get stuck at pilots and experiments. The reason isn’t a lack of interest - it’s complexity, uncertainty, and talent shortage. * Leaders want **faster innovation** but face uncertainty around models, costs, risk, and security. * Teams want to **prototype quickly** without wasting time on trial-and-error. * Enterprises want **production-grade AI** that integrates seamlessly into cloud environments. #### GenAI PoC Accelerator: Move from Idea to Impact in a Few Weeks CloudKeeper leverages a proven 3-Phase Methodology to address the GenAI gaps & challenges. Whether you're looking to prototype a use case, evaluate different foundational models, or understand how GenAI fits into your business, we provide the architecture, guidance, and assets to achieve faster results, with minimal risk and maximum clarity. Collaborate with our AI specialists to identify high-impact opportunities Business case validation and use case selection. Training on GenAI fundamentals. Solution design and architecture planning. Readiness assessment for data, security, and governance. Why CloudKeeper Stands Apart: **Our Capabilities & GTM Readiness** * Deep Cloud AI Expertise 150+ certified architects plus a full-stack 20-member AI team capable of deploying AI workloads securely on the cloud. * Reusable AI Modules & Frameworks Growing library of prompt chains, evaluation scripts, and UI components - making it easier to spin up custom GenAI use cases. * Multi-Cloud Expertise We bring deep experience across both AWS services (Bedrock, SageMaker, Amazon Q, etc) and Google Cloud (Vertex AI). * AWS-Aligned & Co-Sell Ready Aligned with AWS’s GenAI strategy and open to joint customer engagements, co-builds, and PoC deployments. * Enterprise-Ready Designed to plug into your cloud environment with enterprise requirements in mind - secure, compliant, and scalable architecture patterns. Real-World Impact by Our **AI Center of Excellence Team** ## Model Quality, Safety & Governance #### Custom Model Evluation Framework Pipelines to evaluate models for hallucinations, latency, accuracy, and tone before production deployment. #### Enterprise-Grade Guardranils Advanced safety measures to block unsafe content, PII exposure, and off-brand responses. ## Advanced AI Innovation & Orchestration #### Agent Orchestration Platform Multi-agent coordination with session memory and secure tool invocation. #### Advanced Knowledge Management Conversational intelligent search across enterprise data. ## AI-Powered Productivity & Assistance #### SDR Copilot Real-time AI assistant delivering prospect intelligence and response optimization. #### Multimodal Enterprise Assistant Cross-functional AI helper supporting content creation, data analysis, & workflow automation. ## Model Quality, Safety & Governance #### Custom Model Evluation Framework Pipelines to evaluate models for hallucinations, latency, accuracy, and tone before production deployment. #### Enterprise-Grade Guardranils Advanced safety measures to block unsafe content, PII exposure, and off-brand responses. ## Advanced AI Innovation & Orchestration #### Agent Orchestration Platform Multi-agent coordination with session memory and secure tool invocation. #### Advanced Knowledge Management Conversational intelligent search across enterprise data. ## AI-Powered Productivity & Assistance #### SDR Copilot Real-time AI assistant delivering prospect intelligence and response optimization. #### Multimodal Enterprise Assistant Cross-functional AI helper supporting content creation, data analysis, & workflow automation. ## Model Quality, Safety & Governance #### Custom Model Evluation Framework Pipelines to evaluate models for hallucinations, latency, accuracy, and tone before production deployment. #### Enterprise-Grade Guardranils Advanced safety measures to block unsafe content, PII exposure, and off-brand responses. ‹› We are on The Power of AWS-Native AI, **supercharged with CloudKeeper Accelerators** We combine AWS-native AI services with CloudKeeper’s reusable accelerators and FinOps-first approach to get you the best of Gen AI, fully optimized for your enterprise. * ## Amazon Bedrock Rapidly prototype and experiment with foundation models, without infrastructure overhead. * ## Amazon Q A secure, enterprise-ready AI assistant to supercharge developer productivity and knowledge workflows. * ## Amazon SageMaker End-to-end MLOps pipelines for building, training, and deploying models at scale - all with CloudKeeper’s automation accelerators. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Unlock the Full Potential of your Google Cloud Infrastructure The Google Cloud Architecture Framework Reviews, also known as Cloud Wellness Reviews, combine industry best practices, evolving capabilities, and user feedback to help you build secure, high-performing, and cost-efficient cloud infrastructure. The Google Well-Architected Framework stands on five pillars. * Operational Excellence Efficiently deploying, operating, monitoring, and managing your cloud workloads. * Security, Privacy, and Compliance Ensuring data security, privacy, and adherence to GCP Well-Architected Framework. * Reliability Creating resilient, highly available workloads for uninterrupted cloud performance. * Cost Optimization Driving the best value from your Google Cloud investment with strategic cost management. * Performance Optimization The GCP Well-Architected Framework aligns resources to achieve peak performance across workloads. Get your Cloud Architecture Evaluated by a Trusted Partner With 15+ years of cloud expertise and having worked with 400+ businesses worldwide, CloudKeeper is one of the most experienced **GCP Well-Architected Framework** experts in the industry. * Google Cloud Partner * Team of Certified Google Cloud Experts * Multiple Competencies and Partner Programs How do we perform the Google Cloud Architecture Framework Reviews? CloudKeeper performs a **360-degree health check** and an in-depth review of your cloud infrastructure using a structured approach. * 1 Initial Assessment to Understand the Current State * 2 Workload Identification * 3 An In-depth Architectural Review * 4 Identification of Potential Risks & Opportunities * 5 A Personalized Roadmap for Improvement * 6 End-to-end Implementation Support **No costs involved**. Completely funded by CloudKeeper! The Google Cloud Well-Architected Reviews are entirely free. Why, you may ask? These Google Cloud Architecture Framework Reviews help showcase our capabilities and the guaranteed cloud savings we can deliver. And most organizations end up choosing us as their long-term cloud cost optimization partner. We would love to have you onboard as well! Ready for a health checkup of your Google cloud? Throughout the Google Cloud Architecture Framework Review process, we remain transparent, keeping you informed and involved every step of the way. We would love to provide Our GCP Customers **Related Resources** * GCP Cost Optimization: Top 10 Effective Strategies for Maximum Impact Learn the basics of Google Cloud pricing models, challenges in saving costs and the best practices for effective GCP cost optimization. Blog * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. Whitepapers * FinOps Vendor Ecosystem you should know before nailing your Cloud Optimization Strategy Learn about the dynamics of the FinOps market and the FinOps Vendor Ecosystem to help you choose the right FinOps Partner and implement an effective Cloud Cost Optimization Strategy. Whitepapers Frequently Asked **Questions** * ### Arrow 1.What is the Google Cloud Architecture Framework? Q1. What is the Google Cloud Architecture Framework? The Google Cloud Architecture Framework provides recommendations to help architects, developers, administrators, and other cloud practitioners design and operate a secure, efficient, resilient, high-performing, and cost-effective cloud infrastructure. * ### Arrow 2.What is a Google Cloud Architecture Framework Review? Q2. What is a Google Cloud Architecture Framework Review? The Google Cloud Architecture Framework Review or **GCP Well-Architected Framework** review is a systematic assessment based on the Google Cloud Architecture Framework. This review helps organizations evaluate their workloads against the best practices outlined in the framework. The process identifies areas for improvement to enhance the overall architecture, leading to more resilient, secure, and cost-effective solutions​. * ### Arrow 3.What are the 5 pillars of Google Cloud Architecture Framework Reviews? Q3. What are the 5 pillars of Google Cloud Architecture Framework Reviews? The Google Cloud Architecture Framework Review is conducted across the following pillars: * Operational Excellence * Security, Privacy and Compliance * Reliability * Cost Optimization * Performance Optimization * ### Arrow 4.How does CloudKeeper’s Cloud Architecture Review differ from traditional Google Cloud Architecture Framework Review? Q4. How does CloudKeeper’s Cloud Architecture Review differ from traditional Google Cloud Architecture Framework Review? CloudKeeper recognizes that every cloud environment has its unique challenges. We understand that no two organizations have the same level of maturity or capabilities. CloudKeeper, offers a smarter approach and a more customized approach to Cloud Architecture Framework Reviews, addressing challenges such as lengthy questionnaires, generic suggestions, & unclear action plans. * ### Arrow 5.Who should use the Google Cloud Architecture Framework? Q5. Who should use the Google Cloud Architecture Framework? The Framework is a valuable resource for anyone involved in the design and operation of cloud systems on GCP. This includes professionals like: * Chief Technology Officers (CTOs) * Cloud Architects * Developers * Operations Team Members * ### Arrow 6.What is the GCP Well-Architected Framework review process? Q6. What is the GCP Well-Architected Framework review process? **CloudKeeper follows a six-step review process. Before diving into the GCP Well-Architected Framework review, we conduct thorough consultations** to understand your unique infrastructure and its gaps, your capabilities, and your desired outcomes from the review. **Pre-Review Essential** : A 90-minute detailed discussion for a deep understanding of your infrastructure and goals. **Post-Review Essential** : A 90-minute detailed discussion to finalize actionable recommendations based on your maturity level. * Step 1: Initial Assessment to Understand the Current State * Step 2: Workload Identification * Step 3: An In-depth & Automated Architectural Review * Step 4: Identification of Potential Risks & Opportunities * Step 5: A Personalized Roadmap for Improvement * Step 6: End-to-end Implementation Support * ### Arrow 7.Who should participate in the Google Cloud Architecture Framework Review? Q7. Who should participate in the Google Cloud Architecture Framework Review? Ideally, a cross-functional team should be involved, including cloud architects, security experts, developers, and key stakeholders from business and financial teams. This ensures that the review comprehensively covers both technical and business objectives​. * ### Arrow 8.What are the costs associated with the Google Cloud Architecture Review? Q8. What are the costs associated with the Google Cloud Architecture Review? While the Cloud Architecture Framework is free and open source, working with a certified Google Cloud Partner may involve costs. However, CloudKeeper offers a zero-cost Google Cloud Architecture Framework Review. * ### Arrow 9.How often should I conduct a Google Cloud Architecture Review? Q9. How often should I conduct a Google Cloud Architecture Review? There isn’t a single answer for how often you should do a GCP Cloud Architecture Review—it depends on your specific situation. It is recommended to conduct an Architecture Review periodically, especially after major updates or changes in your workloads. It’s beneficial to review before significant events, like new product launches or expanding operations, to ensure infrastructure readiness.​ **Here are some cases where more frequent reviews make sense:** * Frequent Changes: If your GCP environment changes a lot with new features or updates, regular reviews help you keep things optimized and secure. * Focused Improvements: If you're especially concerned about one area, like security or cost, reviewing that pillar more often can help address it better. * Major Events or Milestones: Big events, like launching a new application or moving from test to production, are great times for a review. For stable, well-organized environments, you may not need reviews as frequently. Look at how critical your workloads are, how developed your cloud setup is, and your company’s goals to decide the best review schedule for your needs. * ### Arrow 10.How can CloudKeeper help implement the Google Cloud Architecture Framework Review findings? Q10. How can CloudKeeper help implement the Google Cloud Architecture Framework Review findings? The customized Cloud Architecture Framework Review by CloudKeeper provides a precise action plan detailing exactly what needs to be done in the next 30, 60, and 90 days. It’s like having a GPS for your cloud journey. Our action plan not only tackles current challenges but also prepares you for ongoing growth and adaptation. CloudKeeper also offers comprehensive support throughout your cloud optimization journey, ensuring that recommendations are implemented correctly and effectively. Our dedicated team of certified experts are with you every step of the way until you achieve cloud efficiency. * ### Arrow 11.How to choose the right Google Cloud Architecture Framework Review Partner? Q11. How to choose the right Google Cloud Architecture Framework Review Partner? Ensure your Google Cloud Architecture Framework Review Partner checks yes to the below questions. * Do they take the time to understand current state & company specifics(needs, challenges, desired outcomes, maturity level)? * Is their process simple, efficient, and streamlined? * Are their recommendations customized to your needs? * Do they provide a clear action plan on how to improve your infra? * Will they guide you on the implementation of the action plan? * Are they certified Google Cloud Partners and have enough experience? A Google Cloud Partner with 15+ years of cloud expertise, CloudKeeper stands out as one of the most experienced Cloud Architecture Framework Review Partners. CloudKeeper has worked with 400+ customers across the globe and has successfully completed 500+ well-architected reviews across AWS, Azure and Google Cloud. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Cloud Computing Glossary * * * * * * * * * * * * * * * * * * * * * * * * * * ## A * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ## B * ## C * * * * * * * * * * * * * * * ## D * * * ## E * * * * * * ## F * * * * * * * ## G * * * * * * * * * * * * * ## H * ## I * * ## J * ## K * * * * * * ## L * * ## M * ## O * * ## P * * ## Q * ## R * * ## S * * ## V * * ## W * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Our Google Cloud Partnership Highlights * Google Cloud Resell and Service Partner Since 2019 * Multiple Competencies and Partner Programs * 20+ Certified Google Cloud Experts Our Google Cloud Services * Consulting Strategic guidance and actionable insights to optimize your cloud infrastructure and achieve your business objectives. * Deployment / Migration Efficiently deploy and migrate your workloads to Google Cloud ensuring seamless transition, minimal disruptions, and maximum performance. * Cloud Wellness Reviews Comprehensive assessment of your current setup, identifying areas for improvement, and providing recommendations to enhance efficiency and security. Our Google Cloud Solution Categories * Infra Modernization Transform your infrastructure with cutting-edge Google Cloud technologies to improve scalability, performance, and operational efficiency. * Database Modernization Leverage Google’s advanced database capabilities enabling faster, reliable, and robust data management systems. * Data Warehouse Design and implement scalable, high-performance data warehouses on Google Cloud, enabling efficient storage, retrieval, and analysis. * DevOps Implement industry best practices and advanced tools to streamline your development processes, boost operational efficiency, and accelerate delivery. * Containerization Unlock the power of containerized applications with our expert guidance. Seamlessly deploy and manage efficient, scalable container environments on Google Cloud. * Microservice Application Design, develop, and deploy highly available, independently scalable microservices to create adaptable and scalable applications. Our Google Cloud Certifications * * * * * * * Our Google Cloud Specific Offerings Cutting-edge solutions designed to empower and elevate your Google Cloud journey * CloudKeeper Lens Gain comprehensive cloud cost visibility with resource-level breakdowns, periodic reports, and insights into data transfer costs. * Cloud Wellness Reviews Benchmark your infrastructure against the best practices and design principles created by cloud and FinOps experts. **Related Resources** * GCP Cost Optimization: Top 10 Effective Strategies for Maximum Impact Learn the basics of Google Cloud pricing models, challenges in saving costs and the best practices for effective GCP cost optimization. Blog * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. Whitepapers * FinOps Vendor Ecosystem you should know before nailing your Cloud Optimization Strategy Learn about the dynamics of the FinOps market and the FinOps Vendor Ecosystem to help you choose the right FinOps Partner and implement an effective Cloud Cost Optimization Strategy. Whitepapers Frequently Asked **Questions** * ### Arrow 1.Who is a Google Cloud Partner? Q1. Who is a Google Cloud Partner? A Google Cloud Partner is a Certified Cloud Solutions Provider, with expertise in delivering solutions and services that leverage Google Cloud's infrastructure and tools, helping businesses innovate, optimize, and scale efficiently. * ### Arrow 2.Why should I work with a Google Cloud Partner? Q2. Why should I work with a Google Cloud Partner? Google Cloud Partners bring deep expertise, customized solutions, and dedicated support to help businesses maximize the potential of Google Cloud, ensuring faster implementation and optimized performance. * ### Arrow 3.Why should you choose Cloudkeeper as your Google Cloud Partner? Q3. Why should you choose Cloudkeeper as your Google Cloud Partner? As a Google Cloud Partner, CloudKeeper delivers end-to-end cost optimization, tailored solutions, and 24/7 expert support. Our team of certified professionals brings in-depth knowledge across Google Cloud services, helping businesses reduce costs, improve efficiency, and scale effectively. * **In-depth Visibility** - Get resource-level cost and usage visibility into your Google Cloud setup with our proprietary cloud visibility platform CloudKeeper Lens. * **Certified Expertise** : Multiple Google Cloud Specializations and certified professionals ensure proven skills and successful outcomes. * **End-to-End Solutions** : From migration to optimization, we help you achieve Google Cloud’s full potential. * **Google Cloud Architecture Framework Reviews** —Get your entire cloud architecture audited by certified experts, with recommendations on optimizing performance and cost-effectiveness. * **Tailored Support** : Dedicated assistance at every step of your Google Cloud journey. * ### Arrow 4.What types of Google Cloud Partners are there? Q4. What types of Google Cloud Partners are there? Google Cloud Partners can be categorized based on their focus within the Partner Advantage Program: 1. Sell: Partners resell Google Cloud products like Google Workspace and Chrome. 2. Service: Provide consulting, implementation, migration, and optimization services for Google Cloud solutions. 3. Build: Develop and integrate products or solutions on Google Cloud, often distributed through the Cloud Marketplace. Partners are also classified into tiers: * Member: Entry-level access to training and events. * Partner: Gain a Google Cloud Partner badge, discounts, and directory listing. * Premier Partner: Top-tier benefits like advanced training, exclusive incentives, and premier discounts. CloudKeeper has been a certified Google Cloud Resell and Service Partner since 2019. * ### Arrow 5.How does working with a Google Cloud Partner differ from working directly with Google Cloud? Q5. How does working with a Google Cloud Partner differ from working directly with Google Cloud? Partnering with a Google Cloud Partner provides added value through expert guidance, customized strategies, and industry-specific insights. A Google Cloud Partner like CloudKeeper focuses on optimizing your environment, managing costs, and ensuring your infrastructure is tailored to your business goals. * ### Arrow 6.How do I find the right Google Cloud Partner for my business? Q6. How do I find the right Google Cloud Partner for my business? When choosing a Google Cloud Partner, look for a provider with relevant certifications, proven expertise, and a strong track record. Consider your specific needs, such as migration, optimization, or security, and assess the partner’s ability to deliver tailored solutions. * ### Arrow 7.How to find the Google Cloud Partners in the US? Q7. How to find the Google Cloud Partners in the US? You can find partners in your country using the Google Cloud Find-A-Partner portal. CloudKeeper is one of the most experienced and trusted GCP partners in the US and worldwide. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01/June/2026 AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27/May/2026 FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26/May/2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22/May/2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20/May/2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15/May/2026 10 Costly BigQuery Mistakes Engineers Make (And How to Avoid Them) A comprehensive guide to the top 10 BigQuery mistakes that cause cloud cost runaways and how to optimize queries, storage, and usage. By Team CloudKeeper 12/May/2026 GCP Pricing Demystified: A Comprehensive Cost Guide A simplified yet comprehensive guide to GCP pricing, covering everything you need to make informed and cost-efficient GCP decisions. By Team CloudKeeper 08/May/2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28/April/2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01/June/2026 AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27/May/2026 FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26/May/2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22/May/2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20/May/2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15/May/2026 10 Costly BigQuery Mistakes Engineers Make (And How to Avoid Them) A comprehensive guide to the top 10 BigQuery mistakes that cause cloud cost runaways and how to optimize queries, storage, and usage. By Team CloudKeeper 12/May/2026 GCP Pricing Demystified: A Comprehensive Cost Guide A simplified yet comprehensive guide to GCP pricing, covering everything you need to make informed and cost-efficient GCP decisions. By Team CloudKeeper 08/May/2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28/April/2026 Popular Blogs AWS re:Invent 2025 — 5 Days of Innovation, Insight & CloudKeeper Moments From groundbreaking AWS AI releases to CloudKeeper’s Latte on Cloud Costs podcast episodes, re:Invent 2025 packed innovation, insights, and unforgettable community moments. By Ryan Freilino 11 Dec, 2025 GCP Cost Optimization: Top 10 Effective Strategies for Maximum Impact Learn the basics of Google Cloud pricing models, challenges in saving costs and the best practices for effective GCP cost optimization. By Team CloudKeeper 31 Jan, 2025 The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Amazon Web Services (AWS) has the largest cloud computing market share (32%) amongst all leading cloud providers. It offers a far wider range of services and functionalities, be it infrastructure technologies (compute, storage, and databases) or emerging technologies (machine learning and artificial intelligence, data lakes and analytics, and the Internet of Things). This allows users to quickly, easily, and cost-effectively migrate and build the most advanced and sophisticated applications on the cloud. AWS services also offer the most comprehensive functionalities, including a wide range of purpose-built databases for But how can one choose the right set of AWS services from their wide array of offerings? Making the right choice is crucial for the success of developing or migrating an application to make sure that it meets its pre-defined objective and also achieves the business goals. When assessing an AWS service for your business, keep the following aspects in mind: **1. Establish the business context:** To make key system decisions and leverage their impact, it is crucial to have the correct business context. Below are the key points to help you identify the business context better: * The underlying workflows * The stakeholders * Volume handled in the workflows * Existing IT investments and interactions * Measured impact of disruption in the workflow **2. Check the availability of the service in your region:** AWS services and products vary from region to region. As a result, you must verify that the service you're seeking is **3. Examine performance and scalability constraints:** To avoid concerns like sluggish response times or frequent outages, your AWS cloud service should be able to support your application as it expands. Here's a checklist to help you evaluate the performance and scalability of AWS services in relation to your business needs. * Applicable limitations (especially narrow) of the service, in terms of the number of provisioned resources, data retention periods, throughput, payload size, and storage size. * AWS resources or configurations that drive scale for your applications. For example, * Scaling scenarios—handling low usage, gradual growth, and spikes. **4. Assess failure recovery options & ease of use:** Examine the most common AWS service error scenarios for accessing your existing **5. Assess control, access, and security mechanisms for resources and data** : In AWS, Identity and Access Management is the central and global system for managing authentication and permissions. Resource-based policies, CloudTrail support, and Encryption at Rest are among the additional tools available, which differ by service. It's crucial to determine whether or not a service supports resource-based policies. For an AWS service, it's critical to assess the API operations available in CloudTrail. **6. Check programming languages that are supported by the Software Development Kits (SDKs):** AWS offers a wide range of programming languages in its SDKs and includes all services in each SDK package. However, SDKs are not used to implement all application code. Check that the AWS service you're interested in supports all code components in your application, not just the SDK. **7. Check if seamless integration is possible:** AWS built-in integrations are straightforward to use, providing event-driven functionality that would have taken a lot of time and effort for you to develop and operate. Assess the implementation effort for AWS cross-service integrations that aren't built-in. It makes things a lot easier if all of the AWS cloud services are in the same area. **8. Examine the features for monitoring and incident management:** Given the importance of monitoring, consider the relevance of the metrics to your application. Ascertain that the metric dimensions and posting intervals are responsive when it comes to notifying important issues. You must assess the suitability of the existing methods for automatically triggering timely and successful remediation. **9. Assess the scope for automation:** Examine how an AWS service can help you automate the setup and deployment of apps. The automated operations that must execute before, during, or after resource creation for the AWS service must also be identified. **10. Evaluate the costs:** * Pay attention to the AWS price dimensions that apply to your application and AWS service to avoid paying a monthly fee for an AWS service you don't need. * Calculate AWS pricing for low and high application utilization. Some AWS cloud services get less expensive as consumption increases. * For a certain AWS service, compare the pricing across all AWS regions. You must be aware of the price differences between regions, as some services can be much more expensive than those in the least-priced zone. We hope that the above AWS Services cheat sheet helps you find the perfect set of services for your requirements. After you've chosen the suitable Amazon cloud services and started running workloads on it, you can concentrate on _If you need help in selecting the right AWS Services or to enhance the efficiency and cost-effectiveness of your cloud infrastructure,_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents ## **Mistake 1: Running SELECT * on Large Tables** This is the single most common and immediately expensive habit in BigQuery. Because BigQuery charges by bytes scanned on on-demand pricing, pulling every column from a wide table is the fastest way to generate a bill you did not plan for. BigQuery stores data in a columnar format. When you query only the columns you need, the engine reads only those columns. When you run SELECT *, it reads everything, regardless of what your application actually uses. **What this looks like in practice:** | **Query** | **Table Size** | **Columns Needed** | **Data Scanned** | **Cost at $6.25/TB** | | --- | --- | --- | --- | --- | | SELECT * | 2 TB | 4 of 60 | 2 TB | $12.50 | | SELECT only needed cols | 2 TB | 4 of 60 | ~133 GB | ~$0.83 | The fix is straightforward: always specify the columns you need. If you are working with a very wide table, audit your scheduled queries for SELECT * statements before the next billing cycle. ## **Mistake 2: Misunderstanding How LIMIT Works in BigQuery** Engineers coming from traditional databases assume that LIMIT 10 means BigQuery only reads 10 rows. It does not work that way. BigQuery scans the full table first, applies the query logic, and only then applies LIMIT to format the output. A preview query on a 500 TB table using SELECT * with LIMIT 10 will cost you over $3,000 for what looked like a quick data check. This is a well-documented source of unexpected billing spikes, particularly in organisations where analysts have direct access to production datasets. **How to preview data without paying for a full scan:** * Use the BigQuery table preview feature in the console, which shows rows without executing a query * Query a sample using _**TABLESAMPLE SYSTEM (1 PERCENT)**_ to read a fraction of the data * Create a partitioned or clustered view for analysts to query safely during exploration ## Mistake 3: Not Using Partitioning and Clustering Tables without partitioning force BigQuery to scan the entire dataset for every query, regardless of how narrow your filter is. This is one of the highest-leverage fixes available and one of the most frequently skipped during initial table design. Partitioning by a date or timestamp column means queries with a date filter only scan the relevant partition. Clustering by frequently filtered columns narrows the scan further within each partition. **Common partitioning and clustering mistakes:** * Partitioning on a high-cardinality column that creates too many partitions and defeats the purpose * Wrapping the partition column in a function like DATE(timestamp_column), which forces a full scan because BigQuery cannot apply partition pruning through a function * Not clustering on the columns that appear most frequently in WHERE clauses If your execution details show "Partitions scanned: 365 of 365" on a query filtering a single day, your partition filter is not working as intended. ## **Mistake 4: Using Streaming Inserts When Batch Loading Would Work** Streaming inserts in BigQuery cost $0.01 per 200 MB, which works out to $50 per TB ingested. Batch loading from Google Cloud Storage is free. For teams ingesting large volumes of data, the choice of ingestion method has a direct and often overlooked impact on the monthly bill. The common justification for streaming inserts is freshness. But most use cases that cite real-time requirements actually need data available within a few minutes, not seconds. A micro-batch approach using Cloud Functions or Dataflow to buffer records into GCS and load them every 5 to 10 minutes delivers near-real-time freshness at zero ingestion cost. **When streaming inserts are justified:** * Genuine real-time requirements where sub-minute data availability is a product or compliance requirement * Low-volume, high-frequency event streams where the ingestion cost is genuinely minimal * Workloads where the operational complexity of buffering would cost more than the streaming fees For everything else, batch loading is the right default. ## **Mistake 5: Choosing the Wrong Pricing Model for Your Workload** BigQuery offers on-demand pricing at $6.25 per TB scanned and capacity-based pricing through BigQuery Editions using slot reservations. Teams that start on on-demand and never revisit that decision often end up significantly overpaying as query volume grows. On-demand pricing works well for unpredictable workloads and low query volumes, typically under 20 TB per month. Once a team reaches consistent, predictable query patterns, capacity pricing through slot reservations almost always delivers better unit economics. | **Pricing Model** | **Best For** | **Cost Model** | | --- | --- | --- | | On-demand | Exploratory, low-volume, unpredictable | $6.25 per TB scanned | | Standard Edition (slots) | Predictable workloads, medium scale | Per slot-hour with autoscaling | | Enterprise Edition | Production workloads needing idle slot sharing | Per slot-hour with commitment options | | Enterprise Plus | Compliance-sensitive environments | Per slot-hour, the highest feature set | The transition decision should be based on at least 30 days of query pattern data, not on a point-in-time estimate. You can ## **Mistake 6: Misconfiguring Autoscaling Slots** Autoscaling sounds like the ideal configuration. Pay only for what you need, scale up when demand spikes. In practice, BigQuery's autoscaling engine is designed to run queries as quickly as possible, which means it will use every available slot up to your configured maximum, regardless of whether that speed is necessary for the workload. A reservation with 0 baseline and 500 maximum autoscaling slots will regularly consume close to 500 slots on scheduled pipelines that could comfortably run on 100. Autoscaling adjusts in 100-slot increments, recalculating once per minute, so a workload that needs 30 slots consistently gets allocated 100 slots. **How to configure autoscaling more deliberately:** * Audit whether each workload actually needs sub-minute completion or whether a longer runtime at lower slot allocation is acceptable * Set a baseline slot count that reflects steady-state demand rather than leaving it at zero * Apply workload management groups to separate interactive dashboards from batch pipelines so each gets the slot allocation appropriate to its latency requirements ## **Mistake 7: Inefficient JOIN Operations on Large Tables** Poorly structured joins are one of the most common sources of unexpectedly high slot consumption. When large tables are joined without filters applied beforehand, BigQuery must process the full dataset from both tables before it can return results. The fix involves two habits that experienced BigQuery engineers treat as standard practice but that are frequently skipped under delivery pressure. **Best practices for JOIN cost reduction:** * Apply WHERE filters to individual tables before joining them, not after * Place the largest table on the left side of the JOIN clause so BigQuery's optimiser can distribute the smaller table across worker nodes * Cluster both tables on the join keys so BigQuery can apply block pruning and skip irrelevant data segments before the join runs * Avoid joining tables that are replicated unnecessarily across regions, as cross-region joins carry both compute and potential egress costs ## **Mistake 8: No Query Cost Caps or Spending Quotas** BigQuery on-demand pricing has no default spending cap. A single misconfigured scheduled query that joins two large, unfiltered tables can scan hundreds of terabytes before anyone notices. This has resulted in $2,000 in charges from a single rogue query in documented production incidents, and it has resulted in far worse in environments without any monitoring in place. Setting custom quotas at the project and user level is a straightforward control that most teams skip because it requires a small amount of upfront configuration. **Controls worth implementing immediately:** * Set a maximum number of bytes billed per query at the project level to prevent runaway scans * Apply user-level quotas to limit daily data processed by individual analysts * Create a dedicated sandbox project with stricter quotas for exploratory analysis, separate from production * Enable budget alerts in GCP Billing to notify the team before spend crosses a defined threshold For teams looking to build more structured GCP cost control practices, starting with query quotas is one of the highest-impact, lowest-effort first steps. ## **Mistake 9: Ignoring Long-Term Storage Discounts on Inactive Data** BigQuery automatically applies a 50% storage discount to tables and partitions that have not been modified for 90 consecutive days, bringing the cost from $0.02 per GB per month down to $0.01 per GB per month. Many teams are sitting on this discount without realising it, because they have never audited which datasets are actually inactive. The missed opportunity goes in both directions. Teams that are unaware of the 90-day threshold sometimes run unnecessary updates or table modifications to keep them "fresh," inadvertently resetting the clock on the long-term discount without any operational reason to do so. **Storage cost practices worth building:** * Run a regular audit of dataset modification timestamps to identify tables already qualifying for long-term storage rates * Archive or delete datasets from completed projects rather than leaving them in active storage indefinitely * Avoid touching tables that have reached or are approaching the 90-day threshold unless there is a genuine operational reason to do so ## **Mistake 10: Running High-Cost Queries Without a Dry Run First** BigQuery's dry run feature lets you submit a query to estimate how much data it will scan without actually running it or incurring a charge. It takes seconds to run and surfaces the exact byte estimate that determines the cost of the actual execution. Despite being a native, free feature, dry runs are rarely part of the standard engineering workflow. Teams discover expensive queries after they have run, not before. **How to make dry runs part of standard practice:** * Use the --dry_run flag in the bq command-line tool before executing any large ad hoc query * In the BigQuery console, check the query validator in the top-right corner before running, which shows the estimated bytes scanned * Build dry run checks into data pipeline code review processes so expensive queries are caught before they reach production * Use ## **To Sum Up** BigQuery cost overruns are seldom the result of a single catastrophic decision; instead, they accumulate through a series of small habits that made sense when tables were small and query volumes were low and became expensive as the environment scaled. The ten mistakes above are the most consistently cited across production engineering teams, and each has a fix that does not require rearchitecting your data platform. Start with the highest-leverage changes: eliminate SELECT *, partition your tables correctly, set query cost caps, and audit your ingestion method. Those four changes alone account for the majority of addressable BigQuery waste in most environments. For teams managing GCP spend at scale, CloudKeeper's Lens for GCP Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Effective cloud cost management is crucial for companies navigating the complexity of cloud-native technologies since up to 32% of cloud budgets are in danger of being wasted. But without the right platform, it becomes difficult to see how resources are being used and how much they cost. In addition to the limitations of many current cloud cost management systems, traditional ways of managing cloud costs often result in complex, confusing bills that hide crucial information. This opacity causes inefficiencies since companies need help to pinpoint the precise reasons for their cloud spending. There is no denying that For this reason, visibility is the first step in cloud cost control. You can optimize cloud expenses by understanding your cloud usage and spending with the help of We delve further into the specifics of cloud cost visibility and the features below- ## **What is cloud cost visibility?** Cloud cost visibility refers to It is crucial to know that cloud cost visibility encompasses more than just providing access to data. The key concern is to obtain and draw conclusions from such data. Gaining visibility will be simpler the more structured the data is. Thanks to ## **Things to look for in a Cloud Cost Visibility platform** **1. Comprehensive Reporting:** Cloud cost analytics and cloud cost monitoring tools for cost visibility produce thorough reports that cover a range of cloud spending topics, including accounts, geographies, and services. These reports provide information on how resources are used, allowing companies to spot inefficient or overspending areas and make well-informed decisions to efficiently save expenses. **2. Real-Time Monitoring:** Businesses may see cost patterns and anomalies as soon as they happen thanks to real-time monitoring capabilities of cloud cost analytics and cloud cost monitoring tools. By taking a proactive stance, companies may deal with problems quickly, cutting down on wasteful spending and improving cost control. **3. Cost Allocation and Tagging:** Accurate cost allocation to designated departments, projects, or teams is made easier by cloud-based cost visibility tools. Organizations can gain insight into resource utilization and promote accountability by **4. Tools for Forecasting and Budgeting:** **5. Customizable Notifications and Alerts:** Users can set spending thresholds and get alerts when expenses go over predetermined amounts. By minimizing overspending and guaranteeing that financial goals are met, these notifications enable firms to control costs proactively. **6. Cost Optimization Recommendations:** Utilizing industry best practices and utilization analysis, advanced platforms provide practical suggestions for cost optimization. These suggestions, such as utilizing reserved capacity or rightsizing instances, help companies make the most use of their resources and cut down on wasteful spending. **7. Integration with Cloud Providers:** Access to precise cost information and optimization possibilities across multi-cloud environments are guaranteed by a smooth integration with the main cloud providers. APIs make integration simple, allowing businesses to make use of the platform's features without having to make changes to their current processes. **8. User-Friendly Interface:** Simple navigation and cost data visualization are made possible by interactive charts and intuitive dashboards that improve user experience. An intuitive user interface streamlines the process of analysis, enabling users to promptly recognize the potential for cost optimization and arrive at well-informed judgments. **9. Security and Compliance Features:** Sensitive cost data is protected by strong security mechanisms, such as role-based access control and data encryption. Compliance features guarantee that industry rules like GDPR and SOC 2 are followed, boosting user confidence in the dependability and credibility of the platform. **10. Flexibility and Scalability:** These two qualities are crucial for adapting to changing cloud environments and business needs. Large data volumes can be handled by scalable platforms, which can also adjust to new cloud services and pricing schemes. This gives businesses the flexibility they need to gradually reduce expenses. ## **Crucial features of a cloud cost visibility platform** Businesses can improve cloud cost optimization through several means by utilizing a cloud cost visibility and cloud cost monitoring tool equipped with these crucial features: **1. Cost Transparency:** Businesses can better understand their spending habits and spot inefficient or wasteful areas by having a complete picture of cloud costs. **2. Proactive Cost Management:** Businesses may prevent budget overruns, handle anomalies quickly, and control costs with the help of real-time visibility and customizable notifications. **3. Optimal Resource Allocation:** This is made possible by accurate cost allocation and tagging, which guarantees that resources are distributed effectively and that expenses are ascribed to the relevant departments or projects. **4. Better Forecasting and Budgeting:** Businesses may prepare for future costs, set realistic budgets, and prevent unanticipated cost spikes by using forecasting and budgeting technologies. Continuous Optimization: By right-sizing resources, taking advantage of cost-saving possibilities, and implementing best practices, organizations can continually improve their cloud expenses with the help of cost optimization tips and actionable insights. ## **Conclusion** To sum up, Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Amazon Web Services (AWS) is the leading cloud service provider, providing a wide range of tools and services to help businesses of all sizes achieve their goals. However, In this blog, we'll discuss 10 unconventional hacks that can help you with AWS cloud cost optimization. ## **Use Spot Instances** Spot Instances are unused EC2 instances available at a reduced cost. These instances are priced lower than On-Demand Instances, making them a great cloud cost-saving option. However, keep in mind that Spot Instances can be terminated at any time by AWS if the demand for EC2 instances increases. When using Spot instances on AWS, there are a few key metrics to monitor to ensure you are getting the most out of the lower-cost pricing model: * Spot Instance Price: This is the current price for the Spot instance you are running. The price can fluctuate based on supply and demand, so it's important to monitor this metric regularly to ensure you are not overpaying for your instances. * Interruption Rate: Spot instances can be interrupted by AWS if the Spot price exceeds your bid or if the capacity becomes unavailable. Monitoring the interruption rate will help you understand how often your instances are being terminated and allow you to adjust your strategy accordingly. * Utilization: It's important to monitor the utilization of your Spot instances to ensure that you are using them efficiently. You can use AWS CloudWatch to monitor CPU utilization, disk I/O, and network I/O. * Cloud Cost Savings: The main reason for using Spot instances is to save money on your computing resources. Monitoring your cost savings will help you understand how much you are saving compared to using On-Demand instances. ## **Use Auto Scaling** * Define proper scaling policies: Properly defining your Auto Scaling policies can lead to significant cloud cost savings. You should set your scaling policies to ensure that your instances are automatically scaled up and down based on your application's actual usage, without over-provisioning resources. * Monitor and adjust scaling policies: Monitoring your Auto Scaling group's performance is crucial to ensure that your resources are optimally utilized. You should monitor your scaling policies regularly and adjust them as needed to ensure that you're only using the resources required to handle your application's load. ## **Use Reserved Instances** Reserved Instances can be purchased for a one-time fee and offer a significant discount on the hourly rate of On-Demand Instances. This is a great way to save money if you have predictable usage patterns. * Analyze your usage: It's crucial to have cloud cost analytics to gain insights into your AWS spending patterns. Analyze your instance usage patterns to determine which instances can be reserved. AWS provides tools such as the Cost Explorer and Trusted Advisor to help you analyze your cloud usage. * Choose the right Reserved Instances type: AWS offers three types of Reserved Instances - Standard, Convertible, and Scheduled. Each type has different benefits and limitations, so it's important to choose the right type based on your cloud usage pattern. * Choose the right payment option: AWS offers two payment options for reserved Instances: All Upfront and Partial Upfront. All Upfront payments can provide the highest discount, but it requires payment for the entire term upfront. Partial Upfront payment can provide a lower discount but allows you to pay part of the term upfront and the rest in monthly installments. ## **Use AWS Budgets** AWS Budgets allows you to set custom cloud cost and usage alerts for your account. This ensures that you don't exceed your budget and helps you monitor your spending for cloud cost optimization. * Set up alerts for cost thresholds: Set up alerts for cost thresholds that you don't want to exceed. For example, you can set up a budget that sends you an alert when your monthly AWS costs exceed a certain dollar amount. This will help you proactively identify cost overruns and take action to mitigate them. * Set up utilization alerts: Set up utilization alerts for resources that you want to optimize. For example, you can set up a budget that sends you an alert when your EC2 instances are running at less than 50% utilization. This will help you identify opportunities to right-size your resources and reduce cloud costs. * Use forecasting: Use forecasting to project your future AWS cloud costs based on your historical cloud usage patterns. This can help you anticipate future cost increases and take action to reduce costs before they occur. ## **Use Instance Scheduling** AWS Instance Scheduling is a feature that enables you to automatically start and stop your Amazon Elastic Compute Cloud (EC2) instances at specified times. By using instance scheduling, you can reduce your AWS cloud costs by running instances only when you need them. If you have workloads that only run during specific hours (e.g., a development environment), you can use AWS Instance Scheduler to automatically stop and start instances during off-hours. This can save you up to 70% of the cost of running your instances 24/7. Here are some tips on how to save AWS cloud costs using instance scheduling. * Use tagging: Use tags to identify instances that are part of a specific project or environment. This makes it easy to manage and monitor the usage of instances. * Use AWS Cost Explorer: Use AWS Cost Explorer to analyze your usage patterns and identify opportunities for savings and reducing cloud costs. * Identify instances that can be stopped: Identify instances that are not required to run 24x7 and can be stopped during off-hours, weekends, or any other specific period. ## **Right-Sizing Techniques** * Network resources: To right-size network resources, use Amazon VPC endpoints to connect to AWS services without using the public internet. You can also use AWS Direct Connect to establish a dedicated network connection between your on-premises data center and AWS. * Application resources: To right-size application resources, use AWS Lambda to run your code without provisioning or managing servers. You can also use Amazon ECS or * Database resources: To right-size database resources, use Amazon RDS or Amazon DynamoDB autoscaling to automatically adjust the capacity of resources based on demand. You can also use Amazon Aurora Serverless to automatically scale database capacity based on workload demand. ## **Use AWS Lambda** AWS Lambda allows you to run code without the need for servers. This can help you save money on infrastructure cloud costs and reduce the amount of time you spend managing servers. ## **Use AWS Storage Gateway** AWS Storage Gateway allows you to store data in the cloud while still using on-premises applications. This can help you save money on storage costs while still using your existing infrastructure. ## **Remove or Right Size Underutilized or Idle resources** To remove or right-size underutilized or idle resources and save AWS costs, you can follow these steps: * Identify underutilized or idle resources: Use AWS Cost Explorer to identify resources that are underutilized or idle. AWS Cost Explorer provides cost and usage reports that can help you identify resources that are not being fully utilized. * Analyze usage patterns: Analyze usage patterns to determine if the underutilized or idle resources are no longer needed. You can use AWS CloudWatch or * Resize or remove underutilized or idle resources: If the underutilized or idle resources are no longer needed, resize or remove them to reduce costs. You can use AWS Auto Scaling to automatically adjust the capacity of resources based on demand. In addition, you can use AWS CloudFormation to create and manage stacks of AWS resources and delete resources that are no longer needed. * Optimize resource usage: Optimize resource usage by using AWS services that provide cost-effective alternatives. For example, you can use Amazon S3 Infrequent Access and Amazon Glacier for long-term storage of infrequently accessed data, and Amazon EC2 Spot Instances to reduce the cloud cost of running compute-intensive workloads. * Implement cost-saving measures: Implement cost-saving measures such as purchasing reserved instances, using AWS Savings Plans, and leveraging spot instances to reduce costs. AWS provides various cost optimization tools such as AWS Cost Explorer, AWS Budgets, and AWS Trusted Advisor that can help you identify cost-saving opportunities. ## **Properly manage your EBS and S3 storage** To properly manage your ****and save AWS costs, you can follow these best practices * Use the right storage class: AWS S3 offers several storage classes that vary in price and durability. For example, S3 Standard-Infrequent Access (S3 Standard-IA) is a lower-cost storage class designed for infrequently accessed data, while S3 Glacier is a very low-cost storage class designed for long-term archival. Similarly, EBS offers different types of volumes with varying performance characteristics and costs, so you should choose the right type based on your workload requirements. * Set up data lifecycle policies: You can use lifecycle policies to automatically transition data from one storage class to another based on its age or usage patterns. For example, you can set up a policy to automatically move data from S3 Standard to S3 Standard-IA after a certain amount of time. Similarly, you can create EBS snapshot lifecycle policies to automatically delete old snapshots after a certain amount of time. * Use data compression: Compressing your data before storing it in S3 or EBS can reduce the amount of storage you need and lower your storage costs. AWS provides several compression tools, such as Gzip and Bzip2, that can be used to compress data before uploading it to S3. * Delete unused resources: Make sure to regularly review your S3 buckets and EBS volumes and delete any resources that are no longer needed. Unused resources can accumulate over time and drive up your storage costs unnecessarily. This is what you can do to optimize your **EBS storage** * Right-size your EBS volumes: Make sure your EBS volumes are sized appropriately for your application needs. Over-provisioned volumes can result in wasted resources and higher costs. * Use Elastic Volumes: Elastic Volumes are a feature of EBS that allows you to dynamically increase or decrease the size of your EBS volumes. Using Elastic Volumes, you can avoid over-provisioning and pay only for the storage you use. * Use EBS Lifecycle Manager: EBS Lifecycle Manager is a feature of AWS that allows you to automate the creation, retention, and deletion of EBS snapshots. By using EBS Lifecycle Manager, you can ensure that you are only retaining the snapshots you need, which can save you money. ## **Conclusion** AWS provides a range of tools and services to help you with cloud cost optimization. By implementing the ten unconventional cost-saving hacks discussed in this blog, you can _To simplify the process and minimize your cost optimization efforts, consider leveraging an end-to-end AWS cloud cost optimization and FinOps Solution like CloudKeeper. CloudKeeper helps over 300+ businesses effectively manage their AWS expenses, achieve significant cost reductions, and improve overall ROI. _ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents The FinOps Foundation runs an annual survey titled as " The State of FinOps 2024 report paints a clear picture of how FinOps is adapting to a changing technological and economic landscape. Here's a closer look at some key findings: ## **1. Economic Pressures Reshape Priorities: Reducing Waste & Maximizing Discounts** With tighter budgets, reducing cloud waste and maximizing discounts by managing commitment-based offerings (Reserved Instances, Savings Plans, etc.) are top priorities. This shift reflects a need to get the most value out of cloud investments. Image source: https://www.finops.org/insights/key-priorities-shift-in-2024/ While still important, empowering engineers is no longer the top focus. This suggests a temporary shift towards centralized control to Minimizing Cloud Waste can free up resources, reduce overheads, and do much more than saving money. Furthermore, you can partner with a cloud FinOps expert who would help: * Identifying unused or underutilized resources. * Recommending the optimal commitment plans (Reserved Instances, Savings Plans) to maximize savings based on your specific usage patterns. * Providing automated management of commitment plans, to free up your IT staff to focus on other priorities. ## **2. Cloud spending priorities differ based on the budget size** **Lower Spenders:** For organizations with lower cloud spend, Image source: https://www.finops.org/insights/key-priorities-shift-in-2024/ While accurate forecasting falls at the second priority for low spenders, it stands at the fifth priority for the highest spenders. **Higher spenders:** High spenders already have strong forecasting, so their priorities shift. Their top concern is Cloud spending priorities are largely consistent across major providers (AWS, Azure, GCP) except for Image source: https://www.finops.org/insights/key-priorities-shift-in-2024/ CloudKeeper can help address the different priorities for various budget sizes. **For low spenders** , the granular **For higher spenders** , CloudKeeper can help in managing complex commitment plans and ensure the maximum discounts with a dedicated cloud FinOps Consulting and Support service. With a dedicated team of experts, CloudKeeper can help in allocating cloud costs across different teams and projects for better visibility and control. ## **3. Cloud Cost Optimization: A Focus on Compute, But Room for More** Even though cloud cost optimization is a top priority, most businesses focus heavily on optimizing compute costs (think servers) while neglecting other areas. This is likely because compute instances require heavy expenses when provisioned On Demand and also have the most readily available optimization tools. There's significant room for improvement, especially in newer technologies like containers, serverless, and AI/ML. The good news is that the cloud FinOps community has created a ## **4. AI/ML in cloud FinOps: A Two-Sided Coin** 31% of survey respondents said that the costs of AI/ML are impacting their FinOps practice today. Companies heavily invested in Artificial Intelligence and Machine Learning (AI/ML) are starting to see the impact on their cloud bills. The early days of AI/ML in the cloud mirror the initial cloud adoption phase. Uncontrolled experimentation led to unexpected cost spikes, forcing a shift toward cost management. This is a reminder that cloud FinOps best practices, which focus on managing and optimizing cloud spending, need to consider AI/ML expenses as well. Image source: https://www.finops.org/insights/key-priorities-shift-in-2024/ The FinOps Foundation recommends implementing reporting, forecasting, and basic controls for any new cloud technology. Looking forward, it's unclear if AI/ML will become a major cost burden or an enabler of intelligent optimization for FinOps. While some experience cost challenges, others hope AI/ML will streamline cost management tasks. ## **5. Sustainability and Cloud FinOps - A Budding Partnership** There's growing interest in combining cloud FinOps (cloud cost management) with sustainability efforts. This is driven by: * Availability of cloud provider sustainability data (e.g., Google Cloud, AWS, Azure). * New government regulations requiring sustainability reporting. Currently, less than 20% of FinOps teams collaborate with sustainability teams. However, half of the respondents expect this to change in the future. Collaboration is expected to move from information sharing to shared responsibilities. Image source: https://www.finops.org/insights/key-priorities-shift-in-2024/ EMEA (Europe, Middle East, Africa) leads the way in sustainability reporting, with nearly twice the collaboration between cloud FinOps and sustainability teams compared to North America. Image source: https://www.finops.org/insights/key-priorities-shift-in-2024/ The lack of established best practices for integrating cloud FinOps and sustainability highlights the newness of this area. Different maturity levels in sustainability reporting across cloud providers further complicate things. CloudKeeper, a Premier Partner of the FinOps Foundation, has the competency to support businesses in ## **6. FinOps Embraces Automation, But Humans Remain Key Players** While cloud cost optimization remains a top priority, automation is seeing a significant rise in importance, especially for smaller and medium cloud spenders. This suggests that FinOps teams are looking to automate tasks for greater efficiency. However, the survey reveals limited use of full automation. Most teams leverage automation for data gathering and identifying areas for action, but humans still take manual steps. Image source: https://www.finops.org/insights/key-priorities-shift-in-2024/ There seems to be a lack of trust in fully automated actions, especially among large spenders in regulated industries. Additionally, integrating automation with existing workflows and tools can be challenging. CloudKeeper agrees that human oversight is still crucial in cloud FinOps. We provide a Zero-touch Automated ## **7. Self-Service Reporting Empowers Engineers in FinOps** The survey shows that engineers are leading the way in leveraging self-service reporting. This highlights the value of providing reports that enable real-time decision-making for all cloud FinOps personas. Empowering employees to manage cloud costs is key to a successful cloud FinOps practice. Easy-to-understand FinOps reports (built in-house, from a 3rd party, or using cloud provider tools) should empower everyone to get their queries addressed, without relying on others. This promotes faster decision-making and greater agility. Image source: https://www.finops.org/insights/key-priorities-shift-in-2024/ However, the survey also reveals that sustainability and procurement teams are lagging behind in utilizing self-service reports. For sustainability teams, incomplete data might be a hurdle. Procurement teams may need more cloud and FinOps training to get the most value from these reports. In support, CloudKeeper provides ## **8. Cloud Cost Forecasting Needs Work** Accurate cloud cost forecasting allows businesses to take advantage of cloud provider tools and resources. It also gives leadership confidence to support experimentation and innovation. However, the State of FinOps survey reveals room for improvement in forecasting capabilities. Image source: https://www.finops.org/insights/key-priorities-shift-in-2024/ Many features haven't been implemented yet, likely due to a lack of sophisticated tools, and processes, or simply not being prioritized. While manual adjustments are common (because they're easy), This suggests that organizations need to invest in improving their cloud cost forecasting capabilities. This is where CloudKeeper Lens, our proprietary cloud cost visibility and recommendation platform works well in filling the gap. ## **Conclusion** The 2024 FinOps survey highlights how cloud FinOps practices are evolving to address current trends - economic pressures, sustainability integration, and Artificial Intelligence. FinOps plays a crucial role in aligning cloud spending with business goals. With changing priorities and continuous cloud adoption, Working with Cloud FinOps experts like CloudKeeper will help organizations act upon all their FinOps and cloud cost optimization priorities seamlessly and get maximum ROI on their cloud investments. CloudKeeper can be your one-stop solution for all your FinOps and Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents Did you know that the FinOps market is worth a massive $5.5 billion and is projected to grow at an impressive 34.8% CAGR from 2023-2025? That's right, the rising need for cloud cost management and cloud cost optimization has fueled the demand for FinOps. But it's not enough to know that Are you aware of the challenges organizations are facing today that make FinOps so necessary? Where does the FinOps market stand today and what are the key drivers and growth trajectories? Are you up to speed with these latest trends and insights in the cloud FinOps sphere? If not, this blog will be extremely helpful. This blog packed with data-driven insights is based on a By understanding these dynamics, you can benchmark your FinOps approach and identify areas for improvement. Also, learn about the market needs and how it's changing. Make sure to align your strategies following the latest trends in cloud FinOps and decoding what your competitors might be doing correctly. The insights in the blog are segregated as below: * The current state of Cloud Adoption. * The key cloud challenges driving FinOps adoption. * Global Cloud FinOps Trends and Insights. * The key challenges within Cloud FinOps adoption. * The tracking of cloud cost optimization and FinOps practices. * What’s Ahead in Cloud FinOps? * Insight on the State of Cloud FinOps Providers’ Landscape. ## **The current state of Cloud Adoption** Let's start with understanding the current scenario of cloud adoption in more detail. **1. 67% of organizations have more than 60% of their workload on the cloud.** The unique benefits of cloud services are positioning it as a strategic pillar for the next generation extending beyond just IT and becoming a more widespread and essential requirement. Many companies in Asia-Pacific (APAC) and Europe now use the cloud for 60-80% of their workloads, showing a noticeable increase in adopting cloud services in these regions. **2. 78% of organizations prefer either a hybrid cloud or multi-cloud strategy.** Most companies prefer using either hybrid cloud or multi-cloud strategies to avoid vendor lock-in issues and to adopt the best-of-breed approach for their cloud workloads. In the Asia-Pacific (APAC) region, there's a greater preference for private cloud, while in North America and Europe, multi-cloud adoption is more popular. ## **The key cloud challenges driving FinOps adoption.** Let us look at the primary challenges faced by organizations in cloud management that are fueling the demand for FinOps solutions **3. 67% of organizations experience higher-than-expected cloud costs. (Source: Everest Group’s annual key issues survey)** 67% of global organizations believe that they have experienced higher than anticipated cloud costs as opposed to their initial expectations of cost reduction from cloud adoption. **4. 82% waste at least 10% of their cloud spend. (Source: Everest Group’s annual key issues survey)** 82% of global organizations struggle with more than 10% of their cloud spending getting wasted, out of which 68% experience more than 20% wastage. **5. Cloud cost wastage is a significant concern globally with 38% of organizations experiencing more than 30% of their cloud spending getting wasted.** **** The survey suggests that most organizations are still fine-tuning their cloud operating model leading to over-provisioning and underutilization of cloud resources. This is creating a hurdle in effective cloud cost management. **6. 41% of the organizations experiencing more than 30% of wastage on cloud spend belong to Europe.** The reason behind this lies in the accelerated adoption of the cloud during the pandemic. This rapid adoption resulted in poorly planned strategies, leading to higher instances of wastage. **7. In the Asia-Pacific (APAC) region, 49% of organizations witness over 30% wastage in their cloud expenditures.** Notably, countries like India see more than 50% of organizations wasting over 40% of their cloud budget. **8. In North America, less than 25% of organizations experience more than 30% wastage.** Contrary to the statistics of the APAC region, the advanced maturity of cloud operating models is evident, emphasizing the region's well-established proficiency in cloud management. ## **Global Cloud FinOps Trends and Insights** Now that we have a clearer understanding of cloud adoption and the challenges driving the demand for cloud FinOps, let's dive into the current landscape. We'll explore key statistics and trends to gain a comprehensive insight into the global FinOps scenario. **9. 63% of organizations dedicate more than 7% of their cloud spend to FinOps.** This allocation reflects a growing awareness of the relevance of optimized cloud FinOps and potential cost-saving benefits that can be realized through strategic investments in FinOps practices. They understand the need to invest significantly in FinOps to cut costs and support business growth. **10. 34% of organizations are at the initial stage of adopting FinOps.** **** We can see a notable presence of APAC organizations in the early stages of FinOps. Meanwhile, 40% of North American players are in the growth phase of their cloud FinOps adoption journey. This highlights the increasing maturity of FinOps adoption in North America, emphasizing organizations' growing concerns about cost control and **11. IT/Technology holds the highest representation with a substantial 38% participation in FinOps activities.** **** IT/Technology holds the highest representation with a substantial 38% participation in cloud FinOps activities. Management, representing 12%, indicates a significant presence of business and management leaders in the decision-making processes related to cloud financial operations. **12. 86% of Senior Vice Presidents (SVPs) and 80% of Vice Presidents (VPs) are actively involved in their organization’s FinOps activities.** **** Senior Vice Presidents (SVPs) and Vice Presidents (VPs) play a significant role in FinOps activities, actively influencing the strategic direction of their business units. Their active involvement ensures alignment with organizational goals. Furthermore, Directors, Chief Information Officers (CIOs), and Chief Technology Officers (CTOs) regularly participate in the organization's FinOps activities. **13. 45% of organizations with advanced cloud adoption prioritize immediate cost savings.** This drives the integration of FinOps practices to ## **The key challenges within Cloud FinOps adoption** While Cloud FinOps adoption is increasing, several barriers are hindering its effective implementation. Let's uncover these obstacles. **14. 51% of global organizations struggle with managing diverse cloud platforms and hybrid infrastructure.** **** There is a requirement for best practices in optimizing these diverse environments. This is mainly due to the intricacies of cross-cloud operations, redundant costs, overprovisioned processes, and tools, as well as challenges related to data gravity and integration. Organizations also express dissatisfaction with adopting key organizational elements of FinOps. This includes issues like cross-team collaboration, **15. 46% of global organizations struggle to comprehensively grasp their cloud unit economics.** There is the difficulty faced by organizations in defining metrics and KPIs for Cloud FinOps. This challenge leads to a lack of clear correlation between cloud costs and the corresponding business value at the specific use-case level. **16. 43% prioritize overcoming ineffective cross-team collaboration during FinOps adoptions.** The organizational silos and communication barriers can hinder effective teamwork, causing misalignment between financial goals and operational realities. **17. 42% of global organizations face challenges due to a shortage of skilled personnel proficient in FinOps practices.** A lack of skilled personnel with Cloud FinOps expertise can hamper the effectiveness of FinOps teams and may impact the optimal management of cloud costs and operational efficiency. ## **The tracking of cloud cost optimization and FinOps practices** **18. More than 70% of organizations track cloud cost per application to assess FinOps practices.** **** However, this cloud cost per application metric overlooks crucial details like monitoring overprovisioned resources and continuous wastage. We can observe a growing importance of metrics related to Reserved Instances (RIs) and savings plans. However, not many organizations have adopted these metrics, indicating a limited maturity in Cloud FinOps implementation and tracking. Looking forward, as the ## **What’s Ahead in Cloud FinOps?** **19. Over 35% of organizations anticipate a rise in automation practices within FinOps.** This is due to the perceived shortcomings of current automation-led FinOps tools in meeting organizational expectations as well as the lack of a holistic approach by FinOps providers. **20. Over 50% of organizations expect FinOps tools and services to expand to cover multi- and hybrid cloud environments.** The next set of innovation areas within Cloud FinOps are expected to be ## **Insight on the State of Cloud FinOps Providers’ Landscape** Let us now understand the current state and future FinOps Providers’ Landscape through the survey insights **21. There is a strong dependence on 3rd party solutions and platforms.** * Organizations primarily opt for tools offered by Cloud FinOps solution providers, mainly because other types of solutions lack advanced Cloud FinOps capabilities. * While cloud visibility and management platforms, open-source tools, and tools native to hyperscalers are widely available, they often lack a detailed view and comprehensive support. * Furthermore, there's a shortage of internal Cloud FinOps talent, which diminishes the effectiveness of internally developed solutions. **22. 62% of organizations chose RI management providers as the preferred partner for their FinOps strategy.** **** Organizations are looking for partners to assist them in leveraging RIs across their multi-cloud environments. There's a growing need for consulting and Managed Service Provider (MSP) support, reflecting a desire for ongoing assistance throughout the Cloud FinOps journey. As the market progresses, we anticipate a consolidation in the landscape, with end-to-end Cloud **23. Over 50% of current FinOps engagement models heavily favor outcome-based and fixed price + outcome-based pricing.** Due to the nature of cloud FinOps, it is most likely to continue having a result-oriented construct. **FinOps Provider-Specific Pricing Dynamics:** * RI Management Segment: Providers in this segment are highly inclined towards outcome-based pricing. * Cloud Observability and Management Platform Providers: Prefer a fixed fee pricing model. * Consulting and MSP Providers: Show a preference for charging based on Time and Material (T&M) or fixed-price models. There's a high probability of increased adoption of outcome-based + fixed fee pricing models. This approach allows providers to charge for non-monetary and process-focused aspects of FinOps implementation. ## **Conclusion** The data and statistics indicate a rising demand for Cloud FinOps solutions despite existing challenges. However, these challenges underscore the necessity for end-to-end cloud FinOps providers capable of addressing multiple obstacles. Everest's analysis identifies CloudKeeper as one such end-to-end cloud cost optimization and FinOps provider. CloudKeeper offers a CloudKeeper has helped more than 300 organizations overcome diverse challenges associated with cloud FinOps adoption(as shown in this blog) and establish a framework to track cloud FinOps ROI using suitable metrics. It has become a one-stop solution for organizations in need of _**To understand in detail how CloudKeeper can help in your cloud FinOps journey,**__**.**_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents From Generative AI to Metaverse and Blockchain, recent years have witnessed nothing short of a revolution in technology. Cloud computing is undergoing rapid developments every other day to support and scale these innovations. And just as the cloud landscape evolves, so do the Cloud FinOps practices and principles that keep your excessive cloud costs at bay. So how would a FinOps professional keep up with these updates? Yes, with the help of knowledge repositories and thought leadership! But with a vast number of such resources out there, it might get difficult to sift through your options and find a proper knowledge base about Here is a set of five FinOps resources curated by the cloud and FinOps experts at CloudKeeper, to help build your expertise in cloud cost optimization strategies and stay informed about the latest FinOps happenings. ## **The FinOps Foundation** The real OGs of the domain, the FinOps Foundation is a project by the Linux Foundation, dedicated towards FinOps practitioners to enhance their knowledge and skill set. It involves a community of 12,000+ professionals representing 5000+ companies that acts as a knowledge center for The foundation offers an abundance of articles, research papers, and thought leadership by experts in the domain. In addition, they provide courses, training, and certifications for cloud professionals that empower them to make a difference in their organizations and their careers They also host a community of cloud FinOps enthusiasts, along with a dedicated slack channel and a podcast named ‘FinOpsPod’, which helps you interact and grow your network, and gain knowledge that you probably won’t find elsewhere. Visit the ## **YouTube channels by the hyperscalers** What’s better than to learn the cloud tactics right from the horse’s mouth? The YouTube channels of hyperscalers like AWS, Azure, and Google Cloud host a rich set of explainer videos on various concepts and ideas of cloud cost management including FinOps, Cloud Cost Analytics, DevOps, and more. These channels offer a treasure trove of educational content, from practical demos and "how-to" scenarios to updates on the latest cloud features and enhancements. They also showcase some short, informative videos, with which they _That wasn’t surprising, isn’t it? But have you subscribed yet?_ View the ## **r/FinOps - Reddit** For those not in the know, Reddit is a social news aggregation, web content rating, and discussion website, and a ‘subreddit’ means a specific community in Reddit organized by topic. Users can subscribe to subreddits that they are interested in. r/FinOps is one such subreddit dedicated to the discussion on Here are some of the things you can expect to find on r/FinOps: * News and articles about FinOps * Discussions about FinOps best practices * Questions and answers about FinOps * * Job postings for FinOps roles Check out the ## **The Cloudcast** Podcasts are a great way to learn new things, be entertained, and connect with other people who share your interests. The Cloudcast, an esteemed independent Cloud Computing podcast established in 2011, is hosted by industry experts Aaron Delp and Brian Gracely. Over the years, they have engaged in insightful conversations with influential figures in technology and business, shaping the future of cloud computing. Notably, The Cloudcast is an The podcast also covers a wide spectrum of topics including Cloud Computing, Open Source, AWS, Azure, GCP, Serverless, DevOps, Big Data, ML, AI, Security, Kubernetes, AppDev, SaaS, PaaS, CaaS, and IoT. Listen to the ## **Cloud FinOps: Collaborative Real-time Cloud Value Decision-Making** Regarded as one of the best technical guides on cloud FinOps that money can buy, this book provides a complete roadmap for adopting and maturing in the FinOps discipline. Based on the experiences of hundreds of real-world FinOps practitioners, the book explains It navigates readers through key topics such as cost optimization strategies, sustainability, and alignment with business goals. It also provides insights on The authors J R Storment and Mike Fuller are domain experts and executive leaders from the FinOps Foundation. They have an extensive background of working with some of the largest cloud consumers across the globe. Learn more about ## **Honorable mentions** * * * The above list represents only a small subset of all the various Cloud and FinOps resources available online, that could help you build and enhance your cloud cost management skillset. Exploring these options and applying their insights is not only beneficial for ## _**Have certified cloud domain experts by your side**_ _CloudKeeper, a comprehensive cloud cost management services provider, is backed by a strong team of 300+ Certified Cloud and FinOps Experts. We regularly publish blogs and whitepapers and host insightful webinars that delve into various Cloud FinOps concepts and best practices._ _We’d love to have you_ _CloudKeeper offers you instant and guaranteed cloud savings, with no commitments, no lock-ins and zero upfront costs._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents ## **Introduction** AWS Auto Scaling Groups (ASG) is a powerful tool that helps you maintain your infrastructure by automatically adjusting the capacity of EC2 instances as needed. A key feature of ASG is the ability to add or remove instances from the group. In this blog post, we'll cover some common mistakes to avoid when using scaling policies on AWS Auto Scaling groups. ## **Here are the common mistakes that we should avoid** ### **Mistake 1: Scaling too aggressively** One of the most common mistakes when setting AWS AutoScaling policies is scaling too aggressively. While it may seem like a good idea to add more instances to handle increased traffic, doing so without proper planning can result in increased costs and reduced efficiency. When creating an To avoid aggressive scaling, you should regularly monitor your scaling policy and adjust it based on the performance of your workload. This will help ensure that your scaling strategy is optimized and that you don't add or remove unnecessary instances. ### **Mistake 2: Not Considering Instance Warm-Up Time** When using AWS AutoScaling Groups (ASGs), it is essential to consider instance warm-up time. Warm-up time is the time it takes for a new instance to be fully operational and ready to receive requests. This time can vary depending on many factors, for example, its size and the workload it undertakes. If you do not take instance warm-up time into account when setting your scaling policy, you may end up with Instance Warm-Up Time matters when a new instance is added to an AWS AutoScaling group, it must warm up before it can start processing requests. During this time, the instance will download software updates, initialize the database, and perform other configuration tasks. If you do not consider warm-up time, you may add more instances to the AWS AutoScaling group, causing increased costs and reduced performance. If your AWS AutoScaling group is configured to add an instance when CPU usage exceeds the threshold, and you don't consider warm-up time, you may instinctually add unnecessary instances. On the other hand, if you don't add enough instances to the AWS AutoScaling group, you may not be able to control the traffic, resulting in performance degradation. For example, if your AWS AutoScaling group is configured to remove instances when CPU usage drops below a threshold, and you don't take into account warm-up time, you can end up removing instances too quickly. Therefore, it may not have enough capacity to handle high traffic, resulting in poor performance. How to include the warm-up period in your Scaling strategy to avoid ASG problems you should include the warm-up period in your scaling strategy. You can do this in several ways: **1.** **Using AWS AutoScaling Lifecycle Hooks:-** It allows you to perform custom actions when instances are launched or terminated. You can use life-cycle hooks to further delay your ASG until it's finished. You can use the lifecycle hook to delay adding instances until it is finished downloading a software update or initializing a database. **2.** **Use Metrics that Consider Warmup Time Instead of using metrics that measure CPU usage or network traffic:-** You can use metrics that take warm-up time into account. For example, you can use the metrics to measure how long it will take for a new instance to launch. You can then set policy metrics to add or remove instances based on that metric. This will help ensure that your ASG only adds or removes fully operational instances. **3.** **Using Predictive Scaling:-** AWS has a feature called predictive scaling that uses machine learning algorithms to predict the future needs of your workload. Predictive scaling takes warm-up time into account when deciding to scale. **Conclusion:-** Instance warm-up time is an important factor to consider when using AutoScaling groups on AWS. If you don't take warm-up time into account when setting your scaling policy, you can add and remove instances too quickly, causing increased costs and decreased performance. ### **Mistake 3: Not Considering Minimum and Maximum Instance Limits** When using AWS AutoScaling Groups (ASGs), it is important to set minimum and maximum limits to ensure that your scaling strategy is important. The minimum and maximum limits limit the minimum and maximum number of instances the AWS AutoScaling group can have at any one time. If you don't take these limitations into account when creating your scaling strategy, you may experience less or more traffic, increased costs, and poor performance. We will explore why minimum and maximum limits are important and how to incorporate them into your scaling strategy. Min and max instance limits define the limits at which the AWS AutoScaling group can operate. If ASG drops below the minimum limit, it will add a new instance to meet demand. If the number exceeds the limit, it deletes the instance to bring the number of instances back to the limit. By setting a minimum and maximum limit, you can ensure that your AWS AutoScaling groups meet your operational needs while minimizing costs. If you ignore the minimum and maximum limits, you may end up with too few or too many limits, which can lead to How to include minimum and maximum limits in your analysis to avoid the AWS AutoScaling groups problems, it is important to have a minimum and maximum limit in your scaling strategy. Here are some tips on how to do this: **1.** **Set the optimal minimum and maximum limits:-** You should consider minimum and maximum limits when setting policies using policy metrics that consider minimum and maximum limits. For example, you can configure a scaling rule that adds an instance when CPU usage exceeds a threshold, and the current state drops below the maximum. Similarly, you can configure a scaling rule that removes the instance when the CPU usage drops below the threshold and the current instance rises ASGs to the minimum. **2.** **Using AutoScaling Lifecycle Hooks:-** It can also be used to ensure your ASG stays within minimum and maximum limits. You can use loop hooks to delay or cancel until the number of instances reaches a certain limit. **3.** **Using AWS Trusted Advisor:-** It is a tool that provides recommendations for ### **Mistake 4: Not Considering Scaling Based on Custom Metrics** AWS AutoScaling Groups (ASGs) are a powerful tool for managing infrastructure and managing variable workloads. They can be used to track applications. Custom metrics can also be used to monitor certain metrics such as disk usage, memory usage, and I/O performance. Custom metrics are important because they provide for monitoring and optimizing the application or performance. By monitoring custom metrics, you can detect performance issues, identify issues, and optimize resources to optimize your application or development. ### **Why Custom Metric Scale?** Custom metrics scaling lets you tailor resources to your specific application or infrastructure needs. By monitoring custom metrics, it can help you improve your resources by discovering trends and patterns in your data. For example, if you see an increase in user interaction with your app, you can measure resources to make sure your app can handle traffic. Additionally, extension-based custom measures can help you Scaling by Custom Metrics Scaling based on custom metrics requires configuring custom metrics in CloudWatch and creating metrics using those metrics. Here are the steps to follow: **Step 1:** To configure Custom Metrics in CloudWatch, you must use the AWS Command Line Interface (CLI) or the AWS Management Console to configure custom metrics in CloudWatch. You can export custom metrics to CloudWatch using the CLI or create custom filters using the management console. **Step 2:** Creating Scaling Policies Based on Custom Metrics. After you configure custom measures, you can create scaling policies that use them. **Step 3:** To create a metering rule based on a custom metric, you must define a CloudWatch alarm to monitor the metering rule and trigger the metering rule when certain conditions are met. For example, you can configure CloudWatch alarms to monitor user engagement and trigger policy measures when the number of active users exceeds a threshold. **Step 4:** Test and Monitor Your Scaling Policy. It is important to test and monitor your scaling policies to ensure they are working properly. You should test your scaling strategy in a staging environment before deploying to production. You should follow your scaling policies to ensure they scale resources up and down as expected. ### **Mistake 5: Not considering cooldown periods** What is the cooldown time? Cooldown is a period during which the AWS Auto Scaling group does not allow further processing. The cool-down period is important because it prevents the AWS AutoScaling group from overreacting to spikes or drops in demand. By allowing time to pass before an AutoScaling Group can perform additional scaling operations, it can ensure that the resources it adds or removes are sufficient to meet new demand. For example, if you have a cooldown of 1 minute and your AWS AutoScaling group increases in response to a demand spike, but demand drops rapidly, your AutoScaling group will immediately Voluntarily reduce even with resources. On the other hand, if you have a cooldown of 1 hour and your AutoScaling group is increasing due to sudden demand, but demand continues to increase, your AutoScaling group will not increase for an hour. This can cause resource constraints that can affect the performance of your application or service. Cool down periods Configuring cool down periods in an AWS AutoScaling group is simple. You can specify cooling in seconds when creating or modifying a scaling policy. The cooling time for the contraction and expansion strategies can be adjusted separately. Cooldown Best Practices to avoid errors where cooldowns are not taken into account, it is important to follow best practices for configuring cooldowns. Here are some best practices to keep in mind: **1.** Use different cool-down periods for scaling and scaling policy. A feedback strategy may require a shorter lead time than a scaling strategy to enable the rapid addition of resources in response to rapidly increasing demand. **2.** Choose the right cooler for your application or service. This will depend on factors such as how long it takes your app to stabilize after the Zoom instance, the duration of the Zoom instance, and the desired frequency of the instance. **3.** Monitor your AutoScaling groups during and after Scaling instances. This will help you determine if your cooling time is reasonable and whether your AutoScaling group is responding appropriately to changes in demand. _With a few clicks of easy onboarding, the platform provides businesses with resource level cost visibility into their billing, RI/Savings plan utilization, EC2 & S3, and data transfer spends. _ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Generative AI Explained: Concepts, Tools & Important Use Cases A clear, practical guide to Generative AI covering core concepts, future trends, leading tools, and real-world industry applications. By Team CloudKeeper 20 Nov, 2025 Automate Beyond Limits with n8n: Your Open-Source Automation Powerhouse This blog will help you gain a working understanding of automating with n8n through a practical example and a comparison with Make and Zapier. By Pratik Singh 04 Nov, 2025 How to Maximize Cloud Cost Efficiency by Utilizing Automation and Scripting? Automation and scripting can be powerful tools for optimizing cloud costs. This blog post will show you how to use these techniques to significantly reduce your cloud bill and improve resource utilization. By Satyam Negi 25 Aug, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents It should come as no surprise that AWS provides scalable, dependable, and reasonably priced infrastructure to over 190 nations, since it holds a 32 percent global market share in the public cloud. Amazon EC2 is one of its most potent and widely utilized services (Elastic Cloud Compute). Amazon Elastic Compute Cloud (EC2) stands tall as one of the core services within Amazon Web Services (AWS), offering scalable compute capacity in the cloud. Its popularity stems from the flexibility it provides for businesses of all sizes to run applications in the cloud without upfront investments in hardware. Here are a few other reasons why several organizations around the world prefer running their workloads on EC2- * No hardware units are needed. * Easily expandable (up or down) and just charged for the resources used. * You are in total command. * Incredibly secure. * Your assets are accessible to you from anywhere in the globe. Understanding EC2 pricing models is pivotal for effective AWS cost optimization. Amidst the dynamic cloud landscape, mastering ## **Pricing models for AWS EC2 Instances** * **Free Tier** : Amazon EC2 offers a limited free tier for new users, allowing them to use a certain level of resources free for up to 12 months. This includes a range of instance types, such as T2 micro instances, T3, M5, and R5, etc. to experiment with and get familiar with the platform. It allows individuals or businesses to figure out various configurations, from smaller instances suited for basic computing tasks to more robust ones designed for high-performance applications. For instance, users can test micro instances for lightweight workloads or explore larger instance types to comprehend the platform's capabilities. * **On-Demand Instances** : Users pay for compute capacity by the hour or second without any long-term commitments. This model offers flexibility and scalability, allowing users to start and stop instances as needed, paying only for the resources used. * **Spot Instances** : These allow users to bid for spare EC2 capacity at significantly lower prices than On-Demand instances. However, they can be interrupted and terminated by AWS based on demand, making them ideal for fault-tolerant, flexible workloads or batch processing. * **Reserved Instances (RIs)** : RIs provide significant cost savings (up to 75%) compared to On-Demand pricing, suitable for steady and predictable workloads. They offer capacity reservation for a specific instance type in a particular region for a term of one or three years. * **Savings Plans:** Offering flexibility across multiple AWS services, Savings Plans allow users to commit to a consistent amount of usage measured in dollars per hour over a term. This model provides significant discounts in exchange for the commitment to usage, offering cost predictability and flexibility across various services. However, ensuring cost efficiency within an EC2 environment requires strategic optimization. Let’s delve into five effective strategies to maximize savings without compromising performance. ## **EC2 Cost Optimization Strategies** **1. Right size Your EC2 Instances** One of the most impactful ways for For example, a workload initially provisioned on a larger instance, like an M5 instance (which has high compute and memory), might, in reality, only require the memory capacity of an R5 instance. By switching to the R5 instance type, a significant EC2 cost optimization can be achieved while maintaining the necessary performance levels. ### **2. Utilize AWS Auto Scaling** Auto Scaling ensures the right number of instances are active, preventing over-provisioning. Companies like Netflix reportedly saved significantly in costs using Auto Scaling. * **Performance vs. Consumption Targets:** Netflix learned that basing Auto Scaling targets solely on consumption can lead to pitfalls. Regularly tracking both performance and consumption is vital to determine the appropriate approach. * **Changing Targets Over Time:** As software performance evolves, consumption targets can fluctuate. Continuous tracking is crucial to identify inefficiencies early on. * **Live Traffic Testing:** Netflix gains confidence in Auto Scaling by conducting live traffic tests, emphasizing the necessity for real-world performance assurance over test environments. * **Non-linear Consumption Consideration:** Understanding performance fluctuations during peak and non-busy periods is crucial. Netflix's experience highlights the need to comprehend non-linear consumption behavior for effective Auto Scaling. ### ### **3. Take Advantage of Reserved Instances (RIs)** AWS Committing to RIs for predictable workloads yields substantial savings. A company running a database 24/7 can benefit from RIs, ensuring AWS cost optimization. For example, Netflix reported saving millions by committing to RIs for its streaming services. (source: AWS) ### **4. Implement AWS Spot Instances and Savings Plans** AWS Spot Instances enable you to bid for unused EC2 capacity at significantly lower prices than On-Demand instances. Although these instances can be interrupted by AWS with short notice, they are an excellent option for fault-tolerant workloads, batch processing, or testing environments, delivering substantial savings. Savings Plans, on the other hand, provide flexibility across EC2 and other AWS services, offering significant discounts in exchange for committing to a consistent amount of usage (measured in $/hour) over a term. Companies like Lyft have used Spot Instances for cost-effective batch processing, reducing costs as compared to On-Demand instances. Upon experimenting with On-Demand Instances for simulations, Lyft's Level 5 team swiftly identified an opportunity for heightened efficiency and cost reduction. Transitioning to Amazon EC2 Spot Instances became pivotal, with over 90 percent of simulations now utilizing this resource, including Amazon EC2 P3 Instances equipped with NVIDIA V100 Tensor Core GPUs. This shift allows Lyft to leverage untapped AWS Cloud capacity, offering up to a 70 percent discount compared to On-Demand pricing. (source: AWS) ### **5. Leverage AWS Cost Explorer and Trusted Advisor** AWS provides tools like Cost Explorer and Trusted Advisor to gain insights into your AWS spending and to identify potential cost-saving opportunities ensuring AWS cost optimization. Cost Explorer offers visualization and analysis of your AWS spending patterns, enabling effective forecasting and cloud cost tracking. Trusted Advisor, a part of AWS Premium Support, offers Companies like Airbnb have reported optimizing costs by 20% using Cost Explorer insights. Airbnb harnessed AWS tools like the Cost & Usage Report for cost transparency, and optimized expenses via Amazon S3 Intelligent-Tiering and Savings Plans, fostering sustainable growth. Using the AWS Cost & Usage Report within its data warehouse, Airbnb crafts a tailored pipeline, generating a live overview of cost specifics and enabling comprehensive analytics. This pipeline integrates Amazon S3, renowned for its scalability, security, and high-performance data storage, ingesting and managing cost and usage files seamlessly. (source: AWS) ## **Maximize RI savings with CloudKeeper Auto** The versatility and cost-effectiveness of AWS EC2 make it a go-to choice for businesses globally. From dissecting diverse pricing models like free tier, on-demand, spot instances, and reserved Instances, to strategic optimization tactics such as rightsizing instances, auto-scaling, and capitalizing on flexible plans like savings plans, we talked about the path to cost efficiency. The emphasis on adaptability, precision in resource allocation, and harnessing cloud cost optimization tools underscores the importance of informed decision-making. Ultimately, mastering EC2 cost optimization and AWS cost optimization isn't just about savings; it's about maximizing performance and value within the AWS ecosystem. CloudKeeper Auto, a Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents For the first time in the brief history of cloud computing, the tech industry is facing a slowdown and the economy as a whole has turned quite stormy. With the recession looming and financial analysts struggling to predict a longer-term forecast, being more cost-efficient has become the sentiment for businesses across the world. With cloud computing taking up a substantial share of tech budgets, now would be a good time for organizations to reconsider and In this blog, we will explore five practical challenges with ## **1. Cloud Waste** Cloud waste, in simple terms, means the cloud resources that remain unused or underused. Cloud waste majorly occurs when organizations overestimate the resources required to fulfill a specific business goal. According to a Cloud waste can also happen because of the following reasons. * Availing of services for longer periods than needed * Duplicate purchases for a similar type of cloud service * Using instances with a higher number of cores than needed for the task * Resource volumes remaining attached to already terminated instances * Failing to de-provision orphaned resources like load balancers and database volumes ### **Solution** The single most important aspect is to gain Another way to Enhanced cloud cost visibility, along with the right tagging strategy, can help reduce your cloud waste. ## **2. Lack of Performance Tracking and Benchmarking** Performance tracking and the subsequent benchmarking process help understand how well a cloud infrastructure is performing against industry standards. This helps in optimizing cloud costs, maintaining business continuity, and ensuring all relevant parties gain access to the cloud services. Without such a framework, organizations might find it difficult to identify and measure the usage of cloud resources and the actual requirements. This can lead to provisioning-utilization mismatches, unnecessary costs, and missed cloud cost management and This can also result in a range of disadvantages such as - * Difficulty in identifying the root cause of performance bottlenecks * Increased downtime and bad user experience * Increased risk of security breaches * Lack of Confidence in Cloud Investments * Cloud budget cuts and organizational restrictions ### **Solution** Cloud experts recommend tracking and measuring the performance of an organization’s cloud infrastructure using metrics such as CPU Utilization, Memory Usage, Network Throughput, Storage I/O, etc. It is important to make sure that these metrics address the three important areas of cloud performance - Compute, Storage, and Network. Here, the measures of success or failure are represented in terms of Key Performance Indicators (KPIs) or Objectives with Key Results (OKRs). If a KPI of Cost per Instance Hour is used to measure the costs incurred by AWS EC2 Instances, organizations can track the costs incurred in running individual EC2 instances, This helps organizations optimize their cloud infrastructure, find opportunities for improvements, and implement better resource utilization. There are tools by cloud providers, like ## **3. Lack of Organizational Alignment** A proper cloud cost optimization practice requires the entire organization to work closely together, especially the Finance and Imagine a finance team making cloud purchasing decisions, unaware of the speed, security, and architectural considerations of the engineering team. This creates unintentional cost variances, difficulty in cloud cost analysis, degraded user experiences, and more. Making the finance, procurement, and engineering teams work in synergy is one of the biggest obstacles in cloud FinOps, as per the ### **Solution** Having all the FinOps stakeholders on common ground is one of the major steps in solving the cloud cost optimization challenges. The finance, procurement, and engineering teams must speak the same language and should be involved in all the cloud cost management decisions. This will require By doing this, organizations can make sure that their teams are more proactive, collaborative with FinOps decisions, and motivated to build more cost-effective products. Transparent interdisciplinary communication can also help in better ## **4. Lack of Accurate Forecasting** The dynamic nature and pay-per-use models of cloud computing help users ensure availability when needed, but this could also result in cloud costs that fluctuate dramatically. Continuous and Unfortunately, there is no one-size-fits-all FinOps solution for all types of cloud-cost situations. This activity requires specific tooling and data analysis capabilities to be available around the clock. Without the proper setup for accurate cloud cost analysis and forecasting, organizations can end up over-provisioning, over-buying, and paying for unused resources. ### **Solution** Once the previous challenges have been addressed with a proper cloud cost management platform for visibility, as well as better coordination between Finance and Engineering teams, the organization needs to analyze the existing cloud usage and application performance. This historical data could be used to create a trial cloud budget. Using this trial cloud budget as a baseline, further adjustments could be made to arrive at a proper cloud cost forecast and a strategy on how to reduce cloud costs. However, there are a few key aspects to be taken care of * Frequency of forecasts - The teams must arrive at a consensus on when forecasts are done and how frequently the forecast data is needed. * Forecast models - Based on the specific needs of the organization, various forecasting models could be used, like trend-based forecasting or driver-based forecasting. * Forecast accuracy - As the tracking - tagging - and forecasting exercises turn more mature, organizations can close in on the precision gaps and gradually improve the forecast accuracy. * Implementing Automation - By moving away from manual processes, organizations can improve visibility and cost governance by ensuring smarter recommendations, tagging hygiene, rightsizing, and reservation management. ## **5. Absence of a Dedicated FinOps Team** Most of the time, engineers and finance professionals will only be able to manage cloud cost optimization as a small part of a larger set of core business responsibilities. With no dedicated FinOps team, organizations won’t be able to hold anyone formally accountable to come up with solutions for cloud budget overruns and resource usage optimizations. This makes determining the hows, whys, and whats of FinOps and implementing guidelines and best practices quite overwhelming. All of these will push the concerned stakeholders and the executive management into a crisis mode which would eventually lead to a paralyzed initiative. Insufficient time and resources allocated to cloud cost optimization initiatives can also result in poor visibility into cloud costs, inability to trace back or charge back cloud costs to the cost units, cloud waste, poor user experience, missed opportunities, and more. ### **Solution** Building a FinOps team can start with nominating candidates from the Engineering, Finance, and Procurement teams, who have enough understanding of cloud technology and the related challenges. If the cloud consumption is large enough, it's better to consider hiring additional professionals for a full-time FinOps position. The FinOps team could then focus on optimizing various facets of cloud cost optimization like * Cloud Cost Analysis and Reporting * Cloud Resource Performance * Provisioning and Rightsizing * Pricing Efficiency and Discounts * Budgeting and Forecasting The FinOps practitioners could gain additional skills and knowledge from resources like the FinOps Foundation, talking to experts, and getting involved in events. Also, the FinOps team must not act as a governing or enforcing authority to other business functions. They should be a facilitator to guide them toward cost-effective cloud usage. ## **Working with a FinOps Partner** Through this blog, we have only explored some of the major cloud cost optimization challenges that organizations come across in their day-to-day cloud operations and how to tackle them by optimizing the cloud setup and organizational culture. However, cloud costs could spiral out of control for multiple reasons. Even though a dedicated Cloud FinOps team can tackle most of these problems, finding enough professionals with the right set of skills and expertise could be hard. Making up for this with training and knowledge sharing clearly would require a lot of time and effort. In addition, when companies, especially startups, are under pressure to release new products, optimize customer experiences, and increase revenue, it is easy for cloud cost optimization to take a back seat, leading to excessive cloud costs. An expert FinOps partner can free the organization from all these efforts and resource wastages and let you focus on your core business functions. With years of specialized experience in the domain, these cloud cost optimization companies will make sure that your cloud cost always remains a top priority. They will also optimize your cloud infrastructure for better performance and user experience. ## **Summary** It would be a smarter decision for organizations to * Ensuring there are no provisioning issues and cloud wastages * Providing in-depth cloud visibility and implementing tagging practices * Orienting the entire organization toward cloud FinOps awareness * Measuring cloud performance and comparing them with industry benchmarks and KPIs * Leveraging advanced technologies and tools for accurate budgeting and forecasting … and everything else that would make cloud cost optimization easier. _With a strong team of certified AWS experts and_ _enthusiasts, CloudKeeper has helped 300+ businesses across the globe achieve superior and sustainable cloud savings, without affecting their performance benchmarks. We would love to show you how we could help you too!__._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents ## **The advent of FinOps** In this era of fast digital transformation, the Cloud holds the key. According to a report by McKinsey, businesses will realize more than $1 trillion of EBITDA with a public cloud by 2030. Fast-moving digital companies are accelerating at a rapid pace to access this massive value pool by building a customer-centric business landscape, utilizing the speed, scale, and innovation of the cloud. However, to attain the desired outcomes, companies need a clear understanding of cloud-value economics. The cloud is notorious for complexity and hidden costs which can wear down the profit margins in the blink of an eye. As per Enter ## **Benefits of Cloud FinOps** Although Cloud FinOps improves the ability of a cloud organization to operate at scale and much more efficiently, it helps achieve the following tangible benefits: * Reduced cloud computing costs * Improved business profitability * Better collaboration and decision-making * Increased transparency ## **Cloud FinOps Strategies** While the benefits of Cloud FinOps are manifold, there are certain strategies that must be implemented to achieve optimal results in cloud FinOps. Let us look at the “secret” strategies in detail today. ### **1. Auto Scaling for optimal cloud resource utilization:** Auto Scaling is the one benefit that can ease much of your cloud resource utilization pains. It enables automatic allocation or removal of resources based on changing workloads or demand, thus avoiding over-provisioning or under-provisioning of resources. Businesses can avail a number of autoscaling strategies - primarily horizontal auto scaling and vertical auto scaling - to manage the fluctuating demands. Others include predictive auto scaling, reactive autoscaling, hybrid auto scaling, etc. #### **Benefits of Auto Scaling:** * Auto Scaling ensures that resources are always available to users. * Performance is optimal because of workload and resource alignment. Issues such as latency are also taken care of. * Auto scaling helps in reduced costs as it avoids over-provisioning of resources. * Scaling of AWS systems is possible because of the automatic addition or removal of resources. However, while configuring the auto scaling mechanism, one has to be mindful of the system characteristics. Needless to say, each system and application is unique. Whether the cloud system requires compute power, or storage is a factor that must be embedded in the auto scaling rules. ### **2. Utilize resource tagging:** Effective tagging is key to Cloud FinOps and cloud cost analysis so much that it is no longer a best practice - it has become an absolute necessity. With tagging, it is possible to gain better visibility into the cloud spend. By Tags are basically meta-data labels made of a combination of user-defined keys and values (e.g. AWS cost allocation tag). Tagging cloud resources enables businesses to easily manage, identify, organize, and search through information that otherwise would be impossible - especially at scale. It is possible to categorize resources by purpose, owner, environment, etc., resulting in better visibility, accountability, allocation, cost reporting and more. Tags add even greater value when it comes to compliance, as they allow for proper classification, audit, and reporting of assets - thus meeting stringent modern-day regulatory requirements. Beyond cost reporting and resource management, tagging can also help in automation within the cloud environment. ### **3. Set up anomaly alerts for cloud cost monitoring:** Cloud costs can spike unexpectedly because of fluctuations in the costs associated with cloud computing services, resources, and cloud infrastructure usage. Such accidental overspending can set you back by a large cloud bill, thus damaging your business bottom line. The threshold for deviation or the anomaly margin may differ depending on the size and type of the organization, the amount of cloud consumption, and other aspects. One of the most common reasons for anomaly is system misconfiguration - such as, an autoscaling misconfiguration can cause a rapid increase in asset allocation, thus pushing up the cloud bills. Thus, it is very important to set up anomaly alerts that would notify in case of a resource over-spend. However, setting up a baseline is also critical, otherwise, every single fluctuation could be alerted as an anomaly. Major cloud providers provide their own cost anomaly detection tools that use machine learning to notify users about any abnormal cloud spending. For example, the AWS cost monitoring console allows the setting up of such alerts and in fact can also throw light on the causes of such anomalies. Businesses can also utilize ### **4. Use Savings Plan/Reserved Instances:** ### Intelligently utilizing Savings Plans and Reserved Instances offered by cloud providers can reduce your cloud bills by up to 70%. Hence they are a critical pillar in a Cloud FinOps strategy. Reservations and Savings Plans are cost-saving mechanisms offered by major cloud providers (e.g., AWS, Azure, Google Cloud) that offer huge discounts, provided there’s a usage commitment over a period of time. They are ideal for steady-state and long-running workloads. Here’s how to utilize Reservations and Savings Plans effectively: **Reserved Instances:** With Reserved Instances, businesses can commit to using specific resources (e.g. EC2 instances in AWS or VMs in Azure) or databases, for a fixed term (usually one or three years) in return for a significant saving, as compared to on-demand prices. **Savings Plans:** More flexible than reservations, with savings plans, one can commit to a specific dollar amount per hour for a particular type of usage (e.g., compute, EC2 instances). The extent of saving will depend on the level of commitment. Reservations or Savings plans typically involve committing usage for a longer period of time. Given the underlying complexity of the billing structures of cloud providers, it is crucial that someone with strategic planning capabilities over the cloud is engaged in implementing Reservations or Savings Plans efficiently, maximizing cost savings, and ensuring a well-optimized and cost-effective cloud infrastructure. ### **5. Invest in a Cloud FinOps management solution:** Cloud systems are notorious for the complexity of underlying technologies and financial structures. While companies might opt for an internal management model for FinOps, however, it is a no-brainer that someone with proven experience can be a game-changer for any business. An efficient Cloud FinOps partner can not only help in cloud cost optimization, but also help achieve the right balance between cost, agility, and quality. CloudKeeper is one such partner that has helped more than 300+ companies achieve savings of more than $100 Mn by offering ## **Culture of cost awareness and accountability** Beyond the aforementioned 5 strategies, one strategy that is often ignored is building a culture of cost awareness and accountability. Cloud FinOps is more than a method - it is a cultural shift that requires cross-functional collaboration among IT, finance, and business teams. Fostering a FinOps mindset ensures sustainable cost optimization. Companies need to invest in FinOps centers of excellence dedicated to standardizing cloud best practices that best serve the organizational objectives. _**When it’s about a one-stop solution for all your cloud cost optimization needs, CloudKeeper stands tall as the best choice out there. With a wide array of offerings that help you**_ _**, CloudKeeper delivers instant and guaranteed cloud savings, in-depth cost analytics, and expert-backed optimization guidance.**_ _**Want to learn more?**_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents With the advent of digital transformation, businesses are migrating their core computing functions to variable, consumption-based clouds. Cloud service providers enable businesses to scale the resources up or down depending on their changing requirements in real-time while simultaneously reducing their overall costs. Along with the freedom of scalability, organizations should also have a cloud cost management plan in place. Such plans replace up-front cloud infrastructure purchases and offer an efficient pay-as-you-go model on AWS Cloud. As a result, the businesses benefit with reduced services pricing. However, while planning for AWS cost efficiencies, there are a few challenges around inefficient resource utilization that impede the process of controlling cloud spends. Most AWS users over-provision the workloads & forget to downsize later, which leads to losses due to underutilized resources. With unpredictable infrastructure requirements and unusual spends, It is about time to identify the scope of increasing cost efficiencies on AWS. To balance the efficient resource utilization & cost incurred and to ## **1. Spot idle & underutilized resources** Begin with the detailed review and utilization analysis of all your resources and categorize all your workloads into three categories - idle, underutilized, and optimally utilized (~60% and above utilization). To identify an idle workload, the key focus must be on defining the right parameters. For different resource types, there are different correct parameters. For instance, for a Load Balancer, it could be “Request Count”, in the case of Amazon EC2 it could be “Network in/out”, and for elasticache, it could be hit/miss rate. Another way to cut down costs is to eliminate unused resources. It is advised to increase the utilization footprint of all the resources to at least 50-60%. There is always the scaling option in case the utilization goes beyond 60%. Consider running multiple applications/databases on a single server if you see risks in downgrading. ## **2. Use latest generation instances** Look out for AWS’s announcements on product/feature upgrades, as these latest generation instances tend to have enhanced performance & functionality. For the optimally utilized instances (~60% and above utilization), it is always advisable to use the latest generation instances which are always cheaper and come with better hardware associated with it. ## **3. Choose appropriate storage option** Most businesses use the same standard storage class for all their storage needs, this again results in cost in-efficiencies as the storage cost can quickly pile up. The cost is determined by multiple factors, including the data storage and retrieval costs. For example, Standard Storage Class would be most appropriate for static content hosting whereas Standard S3 Infrequent Access storage types are more suitable for data backups. A deep dive into the durability and SLAs of each storage type can help ## **4. Avoid data transfer charges** ## **5. Choose the appropriate region & instance family** Choosing the right region impacts the overall cloud spend. Take North Virginia as an example; the pricing for servers, data transfer, storage, and other service components is the lowest. Hence hosting in this region could save up to 40% in costs straight away. Another factor would be the choice between processors. Amazon’s AMD-based processors have the same processing power as their Intel counterparts. However, the same processing capability from AMD would cost 10% cheaper in North Virginia when compared to Intel processors. You save some cost unless there is a specific application-based need to stick to Intel processors. ## **6. Use spot instances** Access additional compute capacity at a steep discount on Reserved or On-Demand Instance pricing. The interruptions on ## **7. Move to serverless architecture** The serverless architecture ensures that billing is done as per the actual consumption and not per the unused capacity you may have provisioned for. Serverless Architecture saves direct costs and takes away the complexity of administration & scalability. After implementing the above-mentioned recommendations, the AWS users should ensure the highest possible coverage of Reserved Instances/ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents ## **Introduction: The Case of the Stuck Amazon ECS Tasks** In large-scale cloud environments, even well-architected systems optimized after This post walks through a real-world incident in which a customer’s **e** deployment scaled flawlessly up to a few hundred tasks but consistently failed when concurrency approached **600 tasks**. At that threshold, new tasks stalled in the _PENDING_ state indefinitely, halting large-scale testing. What followed was a deep technical investigation into Amazon Fargate’s launch path, service quotas, and networking dependencies. ## **Initial Symptoms: When Elasticity Stops Being Elastic** At smaller scales, Amazon ECS Fargate tasks launched and ran without issue. But at higher concurrency (around 600 parallel tasks), a consistent pattern emerged: * Tasks entered the _PENDING_ state for minutes or failed to start entirely. * There were **no clear****errors** or service-quota alarms. * ENI attachment latency: < 10 seconds per task (normal). * No CapacityUnavailable errors for Amazon Fargate capacity. * Task CPU/memory reservations were well under the regional quota. The absence of obvious failures pointed to a more nuanced constraint, something shared and nonlinear that only became visible under load. AWS Support initially suggested common culprits such as service quotas, AWS **ENI limits** , or delays in AWS ECR image unpacking, but none aligned fully with the observed behavior. This led us to shift our approach; instead of searching for a single “hard limit,” we began **analyzing the launch process as a dependency chain** , where even small inefficiencies could magnify under scale. ## **Controlled Replication: Building a Mirror Environment** ### **Customer Configuration Snapshot** The customer ran Amazon ECS Fargate tasks in a **** in the _ap-southeast-1 region._ Their workflow involved pulling large container images (~600 MB) as part of a data processing pipeline. Tasks were launched in bulk, up to 600 in parallel, from private subnets. The VPC had both Amazon ECR and Key architectural details we captured: ## Replication Strategy Clean AWS account in the same region (_ap-southeast-1_), built from scratch to match these constraints. **The rationale** : a new account eliminates shared-resource noise, prior quota consumption, and any accumulated misconfiguration drift that could confound results. Replication steps: * Provisioned a VPC with private subnets across multiple AZs, same topology as the customer. * Replicated a Docker image to match the customer's image size profile: ~362 MB compressed in ECR and ~600 MB when extracted, ensuring identical image-pull behavior under load. * Configured**VPC Interface Endpoints** for _ecr.api_ and _ecr.dkr_ , and a **VPC Gateway Endpoin** t for Amazon S3, the standard configuration for air-gapped Fargate image pulls. * Applied identical Amazon ECS task definitions: same CPU/memory allocation, same IAM execution role permissions, same image URI pattern. * Launched scaling tests in increments: 100 → 300 → 600 tasks concurrently. ## **What the Replication Told Us** The first test (~170 tasks) showed some stalling, expected in a cold AWS account where the underlying infrastructure warms up for the first time. Tests 2 through 4 all completed cleanly at 600 concurrent tasks, with no PENDING-state delays. This result was decisive: **AWS infrastructure** in _**ap-southeast-1**_ **was not capacity-constrained**. The bottleneck was not in Fargate scheduling, ENI provisioning, or regional capacity. The failure belonged to something entirely different. That single finding redirected the entire investigation. ## **Root Cause: Misrouted Image-Pull Traffic** With AWS infrastructure ruled out, we shifted focus to the customer's network path. We requested Amazon CloudWatch metrics for the customer's ECR VPC endpoints. The result was an unambiguous **zero traffic recorded** on those endpoints. In parallel, NAT Gateway throughput metrics showed a spike to nearly **20 GB/min** , coinciding exactly with large-scale task launches. Specific metrics checked: * AWS/PrivateLinkEndpoints → **BytesProcessed** : 0 bytes. * AWS/NATGateway → **BytesOutToDestination** : Spiked to 19.8 GB/min during task launches. So, despite VPC endpoints being present in the account, ECS Fargate tasks were routing all ECR and S3 image-pull traffic through the NAT Gateway, out to the public internet, and back. ### **Why This Happens** VPC endpoints don't self-activate for ECS. For Fargate tasks to use them, several conditions must all be true simultaneously: 1. **Interface Endpoints must exist** for both ecr.api (manifest resolution) and ecr.dkr (image layer pulls via Docker protocol). 2. **A Gateway Endpoint must exist for Amazon S3** because ECR stores image layers in S3, not directly in ECR itself. 3. **Endpoint policies** must permit the relevant actions (ecr:GetAuthorizationToken, ecr:BatchGetImage, s3:GetObject, etc.). 4. **Route tables** for the private subnets where tasks run must be associated with the S3 Gateway Endpoint. 5. **Security groups on the Interface Endpoints** must allow inbound HTTPS (443) from the task's security group. 6. **DNS resolution** must point to VPC endpoint private IPs, not public ECR endpoints. (Verify with: `nslookup api.ecr.ap-southeast1.amazonaws.com` from within task subnet.) ## **The Scale Effect** At low task counts, NAT bandwidth saturation isn't visible. A single 600 MB image pull is unremarkable. But 600 concurrent pulls, each fetching the same image independently, since Fargate has no shared layer cache across tasks, translates to roughly **360 GB of data** traversing the NAT Gateway in a short burst. NAT Gateways have a baseline bandwidth of 5 Gbps (scalable, but not instantaneous), and contention at that volume introduces latency that cascades into Fargate's image-pull timeout window, leaving tasks stuck in PENDING. ### **The Fix** The remediation involved three targeted changes: 1. Verified and re-associated VPC Interface Endpoints (**ecr**.**api** , **ecr**.**dkr**) with the correct private subnets. 2. Confirmed S3 Gateway Endpoint was in the route table for those subnets; this alone accounts for the majority of image-pull bytes since ECR layers are S3-backed. 3. Updated security group rules on the endpoints to allow port 443 from the Fargate task security group. Post-fix results were immediate: ## **Lessons Learned: Troubleshooting from First Principles** This incident underscored several key lessons for Cloud architects and DevOps engineers: ### **1. Validate Both the Control Plane and the Data Plane** Scaling failures aren’t always about compute capacity. In this case, the control plane (Amazon ECS orchestration) was fine, the data plane (network path for image pulls) was the bottleneck. Always confirm that ECR and S3 endpoints are configured for private traffic to avoid NAT dependency. ### **2. Use Controlled Replication to Isolate Variables** A clean AWS environment can serve as a diagnostic sandbox. By mirroring the environment, we proved that AWS infrastructure wasn’t at fault, narrowing focus to customer configuration. Replication transforms troubleshooting from guesswork to evidence-driven discovery. ### **3. Think Architecturally About Scale** Scalability isn’t just about quotas. It’s about how shared components behave under stress, in this case, NAT Gateway bandwidth saturation. Anticipate such inter-service contention early in design reviews and capacity modeling. ### **4. Metric Identification in Troubleshooting** The key to this issue was identifying the right metrics to monitor. Only after analyzing CloudWatch metrics for both the ECR VPC endpoints and NAT Gateway throughput were we able to pinpoint the root cause. Effective troubleshooting requires knowing which metrics to examine and correlating them to reveal the underlying problem. ## **Conclusion: From Bottleneck to Breakthrough** By correctly routing ECR image-pull traffic through the VPC endpoints, we removed a hidden scaling bottleneck that only surfaced at extreme concurrency. What once caused hundreds of tasks to stall in PENDING now scales seamlessly past 600 tasks with consistent, low-latency startup. **The broader takeaway is simple:** Cloud scaling failures aren’t always caused by a lack of compute capacity, but sometimes by hidden configuration or network issues that appear only under heavy load. Solving them requires going beyond dashboards, validating network paths, replicating environments, and applying first-principles troubleshooting. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Priyansh Choudhary is a cloud and automation enthusiast focused on building scalable and reliable infrastructure. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents A survey revealed that 82% of organizations prioritize managing cloud costs in 2023. Despite this, a significant number of businesses struggle to effectively control expenses, resulting in many exceeding their allocated cloud budgets early on. In an attempt for cloud cost reduction, these organizations often end up spending even more while seeking external assistance to optimize their AWS costs. With this in mind, here are 7 proven strategies to help you manage and reduce your AWS bill by up to 15%. ## **1. Optimize AWS Infrastructure, Storage, and Instances** When selecting an **Source: AWS** AWS provides various storage classes such as Standard, Intelligent-Tiering, Glacier, and more. On the other hand, Standard S3 Infrequent Access is suitable for infrequently accessed data that can be stored for long periods. **AWS Storage Classes** Additionally, AWS regularly introduces new instance types with improved performance and cost-effectiveness. Stay informed about the latest generation instances and consider migrating to them when possible. Newer generations often provide better compute power, enhanced features, and improved efficiency. By upgrading to the latest instance types, you can benefit from increased performance at potentially lower costs per unit of computation. Picking the right instance is a vital step. Your system could face challenges if the foundation isn't solid. Try your best to ## **2. Review Utilization of Resources** Regularly assess the utilization of your AWS resources to ## **3. Review & Remove Snapshots** Regularly review your Amazon EBS (Elastic Block Store) snapshots and identify those that are no longer needed. Over time, snapshots from outdated or terminated instances may accumulate, consuming storage and incurring unnecessary costs. Utilize tools like ## **4. Leverage Time-Based Scaling** Employ time-based scaling strategies to dynamically adjust resources based on predictable patterns of demand. Schedule _**Case in Point:** An AWS user runs six large instances for a month but realizes they only need two during certain hours. By identifying and reducing servers during low-demand times, like late at night, significant cost savings are achieved. Cloud cost savings increase substantially as the user manages sizable volumes of instances. _ **Time-Based Auto Scaling of instances** Auto Scaling is a powerful tool, but using it incorrectly can have drawbacks. Be ## **5. Optimize Cost with Spot Instances** Effectively save AWS costs by prioritizing Spot Instances over On-Demand or Reserved Instances. Contrary to perceptions, Spot Instances are more reliable than often perceived, with interruptions averaging as low as one per host per month. They are particularly suitable for workloads under auto-scaling, especially in non-production environments. You can even integrate Spot Instances with containerization services for streamlined deployment and resource efficiency. ## **6. Switch to Serverless Architecture** Consider migrating to a ## **7. Strive for** Monitoring RI utilization is essential, as standard reports in AWS Cost Explorer might lack accuracy. Utilization percentages which are often tied to server count can be misleading. Custom reporting on AWS expenses provides a more granular understanding, showing cost division between Reserved Instances and On-Demand Instances. Regular monitoring enhances the effectiveness of your cost optimization strategy. Be smart with your approach and only focus on _**Bonus Tip** - Tagging resources allows you to categorize and track costs more effectively. Use tags to identify the Business Unit, Application, Environment, and owner of resources. This enables you to allocate costs accurately and identify areas where optimization is needed. You can even Employ data compression at various stages and prioritize using Private IPs for data transfer between EC2 instances in the same availability zone to further save AWS costs._ Optimizing cloud costs is an ongoing, structured effort with standardized Spend Management Practices. It involves actively monitoring instance usage, avoiding preferences, using tags, and even dashboards for better cost accountability at all levels. _Implementing the above suggestions assures you with up to 15% savings on your AWS cloud costs. If you wish to save more,_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 12 12 Table of Contents Artificial Intelligence is no longer confined to IT companies or limited to writing code for software development. Its applications now impact how we shop, travel, move, or consume content, with examples such as automated customer support, recommendation engines, and virtual shopping assistants. Major cloud providers have also begun offering AI workload services, including platforms such as AWS SageMaker, AWS Bedrock, and AWS Rekognition. However, AI computing resources are notoriously expensive. With the growing demand for innovation, organizations are facing runaway cloud spend, a challenge that already existed and is now intensified by AI workloads. Thus, cost optimization in In this blog, we’ll discuss top AI cost optimization strategies while ensuring it doesn’t impact innovation. ## **Why Is Running AI Workloads So Costly?** According to a recent report from Cushman & Wakefield, the average cost of setting up a data center in the United States can reach up to $11.6 million per megawatt of IT load. The OPEX for a 10 MW data center (a standard facility) can cost between $7 and $12 million. And since it is a fact that AI workloads are more resource-intensive, the costs increase for platform providers and, as a result, are passed down to customers, making AI cost optimization a necessity. Here’s a detailed breakdown of the top factors responsible for the high-cost nature of AI workloads: 1. ### **Specialized Hardware Requirements** Most of the production-scale AI models require GPUs as the hardware to run. This is because GPUs are designed specifically for massive parallel processing, which is ideal for heavy matrix and tensor computations — the two things AI models primarily perform. Simple CPUs, to compensate for a GPU-based instance, require a huge amount of RAM to offset the lack of parallelism. To put things into perspective, while an AWS Graviton4 c8g.16xlarge instance (with 256 GB RAM) can run Llama 3 8B, a much smaller GPU-powered instance like g5.xlarge (16 GB RAM / 24 GB VRAM) can run it more efficiently. However, GPUs are expensive. A single NVIDIA H100 GPU costs around USD 40,000, and a full H100 server can reach USD 400,000. The cost is eventually passed on to the end consumer. For example, an AWS p5.48xlarge instance costs $ 98.32 (on-demand) in US East and US West regions and costs between $24 per hour as a spot instance. 2. ### **Data Gathering and Preprocessing** For training a custom model for a custom use case, a large volume of data is required. And for specific requirements and use cases, this data needs to be annotated and labeled accordingly. The costs associated with this include storing massive datasets, often in terabytes, as well as the manual or semi-automated labeling and annotation, all of which are significant cost drivers. There are custom providers of labeled datasets who charge a substantial amount for classifying data, which eventually serves as the foundation for training the model. AI cost optimization also extends to optimization in data gathering. 3. ### **High Utilization of Computing Resources** Unlike traditional cloud resources, where there are usage spikes and lean periods, allowing for optimizations, AI workloads (such as training custom LLMs) require sustained, long-duration compute resources, leaving little room for AI cost optimization. The problem is compounded by cloud teams overprovisioning resources to be “on the safer side”. High Data Center Expenses Data centers were already an expensive affair, and with AI workloads, the associated costs have skyrocketed. On top of the high acquisition costs of computing resources (GPUs, TPUs, etc.), power densities are significantly higher. High CPU-intensive racks can consume up to 100 kW per rack, whereas traditional EC2 racks typically use only 2–4 kW per rack. Additionally, cooling systems also require upgrading, with advanced methods like liquid or immersion cooling, further compounding the infrastructure costs and further highlighting the importance of cost optimization in AI. 4. ### **Massive Data Storage Spend** Even basic AI/ML workloads, like chatbots or OCR systems, require several terabytes of data storage. Beyond compute, storage costs should also be taken into consideration when implementing AI cost optimization plans, for services like Amazon S3, EBS, and data lakes add significantly to overall cloud spend. Example: AI data is typically stored on Amazon S3 or EBS. While instances like m6i.large handle light compute, data-heavy tasks may use i3en.large or d3en.xlarge. Even storage alone can cost hundreds of thousands of dollars per month, depending on usage. ## **Achieving Cost Optimization in AI for Cloud-Based Workloads** From recommendation engines for e-commerce websites to interactive chatbots for customer support, AI has found its way into almost every industry and business utilizing a digital platform. Therefore, it is all the more important to implement AI cost optimization strategies. Since the majority of AI/ML tools and workloads run on the cloud, here are some top tips and tricks to help you carry out cost optimization in AI: 1. ### **Cut Costs with Open-Source AI Tools** For almost all AI tasks across the lifecycle, from datasets to complete models, there are free alternatives available, such as LLaMA from Meta and Mistral 7B for ML models, and datasets from platforms like Kaggle and OpenML. Leveraging these can save thousands of dollars in licensing fees and, as a result, drive AI cost optimization. However, you’ll still need to host the model yourself, which will typically incur some costs. For example, the Mistral 7B Multi-Model LLM bundle is available at $0.104 per hour across various instance types such as g5g.4xlarge, g5g.16xlarge, and others. Additionally, if your dataset needs to be annotated or tailored to specific requirements, that too will require spending. 2. ### **Explore GPU Options other than NVIDIA Hardware** While NVIDIA GPUs have been the go-to for AI workloads for organizations, they are considered to be steeply priced. For instance, NVIDIA’s H100 (considered to be the base model GPU for AI workloads) costs $30k. However, offerings from other vendors, such as AWS with Trainium and Inferentia, Google with its TPU, Intel with Gaudi, and AMD with Instinct, offer competitive pricing while matching the performance of similar offerings from NVIDIA, thus helping in AI cost optimization. Here’s a holistic analysis comparing NVIDIA GPUs and the alternatives: 3. ### **Use Spot Instances for Model Training** The only drawback is that the cloud provider can reclaim these instances at any time. However, since you're only training the model and not running a production workload, Spot Instances shouldn’t be an issue. But keep in mind to implement periodic model checkpointing to ensure that the model training process can resume once the Spot Instance becomes available again. 4. ### **Offload Inference to Client Devices** While running heavy workloads and processing on your infrastructure, save processing power for critical tasks by shifting basic functions such as document summarization to client devices like Microsoft Copilot on Windows, Apple Intelligence, and others. However, shifting workloads doesn’t necessarily result in low latency, and on devices with older hardware, it can lead to freezes and performance degradation, and consequently, harm user experience in your quest for AI cost optimization. By offloading these simpler tasks, you can reduce strain on your primary compute resources and, as a result, cut down your cloud spend. 5. ### **Fully Leverage Discount Plans** The most popular discount plans are from AWS, and they are driven by commitment. You can also negotiate custom discounts through the By utilizing these discount plans, you can offset the higher costs associated with AI workloads by saving on other resources, such as compute, storage, etc. 6. ### **Use Auto scaling for workloads** While AI workloads like data training typically remain consistently high, others can peak and drop, similar to traditional workloads. Since AI workloads are expensive, it’s important to scale down resources when not in use to avoid cost overruns to meet AI cost optimization targets. Use 7. ### **Streamline AI Model Architecture** For cost optimization in AI, the conversation begins with the model itself being sorted to extract maximum performance per gigabyte. Here are some techniques that are widely implemented for model optimization: * #### **Optimize workflow:** Consolidate API requests, as this will reduce the hit rate, and monitor and schedule regularly to know where the cloud spend is going. This can be done by integrating cost-aware scheduling. For example, if you have to train a model, you can use * #### **Caching:** Implement caching by identifying redundant computations and repeated retrievals, as these consume cloud resources and impact your AI cost optimization strategy. This is particularly useful for inference workloads. Tools such as AWS ElastiCache * #### **Task Segmentation:** Through segmentation, earlier, larger, and more complicated workflows can be executed separately. This facilitates scheduling of non-urgent segments during off-peak hours for temporal arbitrage. * #### **Run models on serverless computing:** Running models on serverless computing resources like AWS Lambda is a good practice, and orchestration tools such as AWS Step Functions simplify doing so. However, Lambda works only for sub-1s inference. 8. ### **Optimize AI Preprocessing** Processing precedes AI inference, which makes it a key driver of cloud spend and, as a result, something that needs to be optimized. Function as a Service (FaaS) helps drive cost optimization in AI, as the platform provider’s instances execute code in response to predefined events. AWS Lambda is the leading FaaS platform, costing $0.20 per 1 million requests, making it a significantly more cost-effective alternative to running a VM on a dedicated EC2 instance, all without compromising performance. ## **AI Cost Optimization Without Compromise: BMW’s Innovation Story** Document processing, compliance checks, and contract analysis are the tedious and repetitive tasks that many organizations try to tackle first when inducting AI into their workflow — and that’s what JP Morgan did with COIN, and that’s what BMW did as well. **Platforms used:** BMW primarily uses AWS as its cloud provider, and, as a given, uses its AI services: * SageMaker for model training and deployment * Textract for text extraction from scanned documents * Amazon Comprehend for NLP and entity recognition BMW, from its vehicles alone, processes 10TB of data daily from 1.2 million vehicles. Beyond serving vehicle use cases, it manages more than 4,500 AWS accounts. As a result, optimization of cloud spend is a significant challenge — yet an important task — to avoid denting their revenue (pun intended). ### **How BMW Performs Cost Optimization in AI** BMW and AWS collaborated to build**ICCA (In-Console Optimization Assistant)** , primarily built with **AWS Bedrock** , to help identify bloated resources and, as a result, assist their cloud engineers in AI cost optimization. Under the hood, ICCA gains insights from **AWS Trusted Advisor** , a visibility platform that helps users optimize costs, and **AWS Config** , which audits and evaluates current configurations. With ICCA alone, BMW Group reports that, on their AI-driven operations and some other workloads, they have saved **up to 70%** on processing costs. BMW Group is a shining example of the fact that **AI cost optimization does not result in hampered innovation**. ## **How CloudKeeper Is Helping Organizations Rein In Their Cloud Spend** Beyond our tools, which serve a variety of functions from managing AWS RIs to automated provisioning and optimization, we’re a team of 100+ AWS-certified cloud professionals with 15+ years of experience, having saved over $120 million in cloud spend for our clients. Our savings span across compute resources, storage, contract negotiations, and configuration management. Cut your cloud costs by an average of 20% starting day one. Join the growing list of organizations already saving with CloudKeeper. ## **Frequently Asked Questions** * **Q1:Should I go for cloud-based services or set up my dedicated infrastructure for AI workloads?** If your primary use case involves running AI services, then cloud infrastructure is a better choice. Setting up dedicated infrastructure is shockingly expensive — a single enterprise-level GPU setup from NVIDIA can cost up to $400,000, and that’s just the CapEx. You’ll still need to account for OpEx, including ongoing maintenance costs, which can amount to 3% of the hardware's value annually. * **Q2:How to monitor my AI-specific cloud resource utilization?** Use AWS Cost Explorer filtered by SageMaker services and instance types to track spending, monitor GPU/CPU utilization in CloudWatch for idle resources, and set anomaly alerts—third-party tools like Datadog add deeper ML-specific insights if needed. With complete visibility, you can implement an accurate AI cost optimization roadmap. * **Q3:What are the AI-specific drivers of cloud cost overruns?** The unpredictability of AI workloads often leads to overprovisioning, which is a major AI-related driver of cloud cost overruns — and a primary target in most organizations’ AI cost optimization strategies. To make matters worse, SageMaker instances cannot be sold on the Reserved Instance Marketplace, limiting an organization’s ability to recover unused spend. * **Q4:How Does Model Quantization Reduce AI Costs?** Through quantization, a 32-bit machine learning model (where higher bit-width generally means higher precision) is reduced in precision while remaining sufficiently accurate. These smaller models assist in AI cost optimization, as they require fewer computational resources. For example, reducing model weights from FP32 to INT8 brings the storage requirement down to just 25% of the original size. As a result, overall spend on AI workloads is significantly reduced. * **Q5:What is cost optimization for AI?** In the context of cloud computing, AI cost optimization refers to maximizing the efficiency of AI computing resources by putting in place strategies such as tagging, instance right-sizing, autoscaling policies, commitment-based savings plans, and workload scheduling — strategies that facilitate cutting down cloud waste spend and extracting full potential out of your investment in cloud infrastructure. * **Q6:Does AI help in cost reduction?** Absolutely! AI-powered tools such as CloudKeeper Tuner automate tasks like scheduling, shutting down idle resources, and right-sizing compute instances — all of which can help you realize significant savings on your next cloud bill. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Cloud cost management once depended on spreadsheets, static dashboards, and monthly reports to track cloud spend. That worked when cloud environments were smaller. It does not work anymore. Modern cloud infrastructure changes every minute. Containers scale up and down. AI workloads consume unpredictable resources. Multi-cloud environments create thousands of billing data points every day. Finance teams need According to the 2025 State of FinOps report, 63% of organizations already manage AI-related cloud spending, up from 31% the previous year. At the same time, cloud waste is rising again. Recent industry reports estimate that nearly 29% of cloud spend is wasted, with AI workloads contributing to the increase for the first time in five years. This is where AI FinOps is becoming important. AI in FinOps helps businesses ## **What does cloud cost intelligence mean today?** Cost intelligence goes beyond dashboards and budget alerts. Modern cloud environments generate massive volumes of usage, billing, and performance data every hour. AI FinOps platforms combine this data with operational context to help teams understand where cloud spend is increasing, why it is increasing, and what actions to take next. The focus is no longer limited to cloud cost visibility. Organizations now need real-time insights that connect infrastructure usage with business priorities, application performance, and engineering efficiency. AI in FinOps helps teams move from static reporting to continuous analysis. Modern platforms can process millions of cloud events in real time, identify underutilized resources, forecast spend trends, This creates a more proactive approach to cloud cost optimization. Instead of reacting to billing surprises after they occur, teams can make faster, more informed decisions as cloud environments evolve. ## **What are the limitations of traditional FinOps approaches?** Traditional FinOps practices helped organizations gain visibility into cloud spending. But cloud infrastructure has become far more dynamic than the systems for which these processes were designed. Many FinOps teams still depend on reporting cycles, manual analysis, and disconnected tooling to manage costs. As cloud environments grow across containers, ### **Reactive reporting cycles** Many organizations still review cloud spending through daily, weekly, or monthly reports. By the time cost spikes are identified, unnecessary spending has often already accumulated. ### **Heavy dependence on manual analysis** Finance and engineering teams spend significant time manually reviewing billing exports, utilization reports, and usage logs. This slows optimization efforts and makes it harder to identify hidden inefficiencies across large cloud environments. ### **Fragmented tools and data silos** Cloud cost data is often distributed across observability platforms, billing systems, monitoring tools, spreadsheets, and cloud provider consoles. Without a unified view, teams struggle to connect usage patterns with business impact. ### **Delayed optimization actions** Traditional FinOps tools can surface recommendations, but execution still depends heavily on manual intervention. Delays in approvals or remediation workflows often lead to ongoing waste of resources. These limitations are driving the adoption of AI FinOps platforms that can automate analysis, improve forecasting accuracy, and enable continuous cloud cost optimization. ## **How AI is transforming FinOps?** AI is changing how teams manage cloud costs. Traditional FinOps tools were built for reporting and visibility. AI FinOps platforms are built for continuous analysis and faster action. Modern cloud environments generate massive amounts of billing, infrastructure, observability, and application data. ### **Finding patterns across large-scale cloud data** AI models can process millions of cloud events, usage records, and billing entries in real time. This helps teams detect spending behavior that would be difficult to identify manually. For example, AI systems can identify workloads that scale inefficiently during peak hours, flag persistent idle resources, or detect services with unusually high storage or network costs. This becomes especially important in AI infrastructure environments where GPU usage can spike unexpectedly. A single training workload or inference deployment can increase cloud costs within hours if usage is not monitored closely. ### **More accurate cloud spend forecasting** Forecasting cloud costs has always been difficult in fast-changing environments. Static forecasting models often fail when infrastructure usage changes suddenly due to deployments, migrations, seasonal traffic, or AI workloads. AI-powered forecasting models analyze historical usage patterns, infrastructure behavior, application demand, and operational trends together. This improves forecast accuracy and helps finance teams plan budgets with better confidence. This is becoming more important as AI spending grows rapidly across enterprises. According to the 2026 State of FinOps report, 98% of organizations now manage AI-related spend, compared to 31% two years ago. ### **Real-time anomaly detection** One of the Traditional monitoring systems often identify billing issues hours or days later. AI-based systems can detect unusual spending behavior much earlier by continuously analyzing workload activity, resource consumption, and usage deviations. This helps teams respond faster to issues like misconfigured deployments, abandoned GPU instances, unexpected traffic spikes, or uncontrolled Kubernetes scaling events. Real-time visibility is increasingly important as cloud costs grow more dynamic and harder to predict. ### **Smarter recommendation engines** Modern AI FinOps platforms do more than generate static cost recommendations. AI recommendation engines continuously learn from infrastructure usage, engineering behavior, and previous optimization outcomes. This helps generate more context-aware recommendations for rightsizing, storage optimization, workload scheduling, The recommendations improve over time as systems learn which optimization actions create savings without affecting application performance. This matters because cloud optimization decisions are no longer limited to virtual machines and storage. Organizations now manage AI models, GPU clusters, token consumption, and inference workloads with highly variable usage patterns. ### **Continuous learning and automation** AI systems improve as they process more operational data. Instead of relying solely on fixed thresholds or rule-based alerts, AI FinOps platforms automatically adapt to changing infrastructure behavior. This helps reduce false alerts and improves optimization accuracy over time. Many organizations are also adopting This is pushing FinOps toward a more automated operating model, in which cloud cost optimization becomes an ongoing process rather than a monthly review. ## **What are the use cases of AI in FinOps?** Organizations are already using AI FinOps across day-to-day cloud operations. What started as reporting and budgeting has expanded into continuous monitoring, optimization, forecasting, and workload analysis. AI in FinOps is helping teams respond faster to cloud cost changes while reducing manual effort across engineering and finance operations. ### **Resource rightsizing** One of the most common AI FinOps use cases is resource rightsizing. AI systems analyze historical utilization, workload behavior, memory consumption, and traffic patterns to identify compute and storage resources that are oversized or underused. Instead of relying on fixed utilization thresholds, ### **Kubernetes cost optimization** Kubernetes environments are difficult to manage with traditional cost-optimization methods because workloads constantly scale. AI helps teams track pod utilization, cluster efficiency, node sizing, and autoscaling behavior in real time. This makes it easier to identify idle capacity, overprovisioned clusters, and inefficient scaling configurations. As container adoption grows, ### **Cloud anomaly management** Unexpected cloud spend often stems from deployment issues, abandoned resources, misconfigurations, or sudden traffic spikes. AI-based anomaly detection systems continuously monitor infrastructure usage and billing activity to identify unusual spending behavior early. This helps teams investigate problems before costs increase significantly. For example, AI systems can ### **Multi-cloud cost visibility** Many enterprises now run workloads across AWS, Azure, and Google Cloud simultaneously. Managing costs across multiple providers creates visibility challenges because billing structures, pricing models, and reporting systems differ across platforms. AI-powered analytics platforms help unify cost data across cloud environments and identify optimization opportunities that may not be visible within individual provider dashboards. This gives engineering and finance teams a more complete view of infrastructure efficiency across the organization. ### **AI workload optimization** AI infrastructure is becoming one of the fastest-growing areas of cloud spend. Training models, running inference workloads, storing vector data, and managing GPU clusters can create highly unpredictable costs. Traditional FinOps tools were not designed for token based pricing, GPU allocation tracking, or model usage analysis. AI FinOps platforms now This is becoming critical as enterprises increase investment in generative AI applications and large language model deployments. According to recent industry reports, GPU-related infrastructure demand is now one of the biggest drivers of cloud cost growth across enterprise environments. ## **What does Agentic AI mean in Cloud Cost Management?** One of the biggest developments in AI FinOps is the rise of intelligent agents. In cloud cost management, these agents continuously monitor infrastructure, identify inefficiencies, and automatically trigger optimization workflows. ### **Autonomous monitoring and remediation** AI agents can detect idle resources, shut down unused workloads, resize infrastructure, or adjust scaling policies without waiting for manual approval in low-risk scenarios. This reduces operational overhead for engineering teams. ### **Closed-loop optimization systems** Traditional optimization workflows often stop after generating recommendations. Agentic AI creates closed-loop systems in which monitoring, analysis, recommendations, and remediation occur continuously. This improves response times and reduces cloud waste. ### **Human in the loop governance** Automation still requires governance. Most enterprises prefer human approval for high-impact optimization actions. AI systems should provide explainable recommendations and maintain clear audit trails. This creates a balance between automation and operational control. ### **Conversational cost intelligence** Another major development in AI FinOps is conversational cost intelligence. FinOps teams have traditionally relied on dashboards, exports, filters, and manual reports to answer cloud cost questions. This often slows down analysis and limits access to FinOps expertise. Platforms like LensGPT acts as an agentic FinOps consultant, combining the capabilities of multiple AI-driven systems across finance, engineering, cloud operations, and optimization workflows. Instead of manually navigating dashboards, teams can ask questions in natural language about cloud spending, workload efficiency, anomaly detection, optimization opportunities, or infrastructure trends. The platform responds with contextual analysis, custom dashboards, root cause insights, projected savings opportunities, and implementation guidance in real time. This makes cloud cost intelligence more accessible across engineering, finance, leadership, FinOps, and CloudOps teams. LensGPT also addresses one of the biggest operational gaps in FinOps today. In many organizations, cloud cost expertise is concentrated within a small team. This creates bottlenecks for decision-making and slows optimization efforts. By enabling teams to interact directly with cloud cost data through natural language, AI FinOps platforms democratize access to cloud financial insights. Another important difference is infrastructure awareness. Traditional reporting tools mostly analyze billing exports. LensGPT combines cost data with account structure, service relationships, cloud architecture context, regions, and environment-level intelligence to generate more relevant recommendations. This helps organizations move from reactive reporting to more ## **What are the challenges in adopting AI for FinOps?** AI FinOps adoption also comes with practical challenges. One of the biggest issues is data quality. Incomplete tagging, inconsistent resource naming, fragmented billing structures, and disconnected monitoring systems reduce the accuracy of AI-driven analysis. Governance is another major concern. Organizations need clear approval processes, There is also the challenge of balancing optimization with performance. Cloud cost recommendations should account for application reliability, latency requirements, engineering priorities, and security considerations. Reducing spend alone is not enough if it affects customer experience or business operations. Many organizations are also facing a growing FinOps skills gap. AI in FinOps now requires ## **What is the future of AI in cloud cost intelligence?** Cloud cost management is moving toward continuous and increasingly autonomous optimization systems. Future AI FinOps platforms will combine cloud billing intelligence, observability, infrastructure telemetry, AI analytics, automation, and governance into connected workflows. Organizations will rely less on static monthly reviews and more on real-time optimization systems that operate continuously across cloud environments. AI will also play a larger role in GPU cost management, AI infrastructure optimization, sustainability tracking, workload efficiency analysis, and business-aligned governance models. As AI workloads continue to grow, cloud cost management will become more closely connected with engineering operations, infrastructure planning, and business strategy. Organizations that adopt AI FinOps early will be better positioned to ## **Practical roadmap to get started with AI for FinOps** Organizations do not need to rebuild their FinOps strategy all at once. The first step is improving visibility into cloud usage, billing, and infrastructure data. Strong tagging standards, centralized cost reporting, and clean resource metadata create the foundation for effective AI analysis. From there, teams can gradually introduce AI-powered anomaly detection, forecasting, and optimization recommendations. Automation should happen in phases. Start with low-risk workflows such as anomaly alerts, idle resource detection, or development environment scheduling before expanding into automated remediation. Governance should remain a priority throughout the process. Organizations need clear approval models, access controls, policy guardrails, and audit visibility before scaling AI-driven optimization systems. Most importantly, AI FinOps should be treated as an ongoing operational capability rather than a one-time cost reduction initiative. The long-term goal should not be only to reduce cloud bills, but to build smarter, more adaptive cloud operations that can scale with modern infrastructure demands. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 10 Costly BigQuery Mistakes Engineers Make (And How to Avoid Them) A comprehensive guide to the top 10 BigQuery mistakes that cause cloud cost runaways and how to optimize queries, storage, and usage. By Team CloudKeeper 12 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents In cloud computing, ensuring the security and efficiency of your infrastructure is paramount. AWS has revolutionized the way businesses operate in the cloud, offering a plethora of tools and services to optimize your cloud environment. One such AWS cost control tool that stands out is the AWS Trusted Advisor. In this blog, we’ll explore the benefits of using AWS Trusted Advisor and how it can help businesses to maximize their AWS experience. Firstly, let us understand what is AWS Trusted Advisor. ## **What is AWS Trusted Advisor?** Optimizing and controlling the cloud infrastructure is essential as many firms are moving their operations to the cloud. AWS provides a selection of strong tools that can help businesses in maximizing the advantages of their cloud environment. AWS Trusted Advisor is a particular standout among these tools. Let’s examine AWS Trusted Advisor's definition, attributes, and potential uses for businesses as they move toward the cloud in this blog post. ## **Understanding AWS Trusted Advisor** AWS Trusted Advisor is an automated Trusted Advisor continuously analyzes an organization's AWS environment, monitors best practices, and provides recommendations based on the ## **Why do we need this?** The primary goal of Trusted Advisor is to help organizations optimize their AWS environments by identifying areas where improvements can be made. It achieves this by analyzing your AWS resources, configurations, and usage patterns, and then providing AWS Trusted Advisor recommendations based on AWS best practices, architectural principles, and cost optimization techniques. ## **Benefits of AWS Trusted Advisor** * ### **Cost Optimization** AWS Trusted Advisor cost optimization is one of the primary advantages of using this tool. It provides recommendations and insights to help you reduce your AWS spending. It analyzes your usage patterns, identifies underutilized resources, and suggests ways to optimize your infrastructure, resulting in significant cost savings. Whether it's resizing instances, right-sizing storage, or identifying idle resources, Trusted Advisor offers actionable advice to optimize your costs without compromising performance. * ### **Enhanced Security** Security is a top concern for any organization operating in the cloud. AWS Trusted Advisor best practice checks scrutinize your AWS environment for security parameters and offers recommendations to enhance your security posture. It helps identify and close security gaps, ensures compliance, and alerts you about any potential vulnerabilities. From securing your storage and databases to implementing encryption and access controls, Trusted Advisor helps you maintain a robust and secure cloud infrastructure. * ### **Performance Improvement** AWS Trusted Advisor assists in improving the performance of your applications and services. It analyzes your infrastructure and provides insights into areas where performance can be optimized. For example, it may suggest modifying your load balancer settings, optimizing your database configurations, or implementing caching mechanisms to enhance the overall performance of your applications. By following these recommendations, you can ensure that your services are running efficiently, providing a better experience for your users. * ### **Reliability and High Availability** Downtime can have severe consequences for businesses. AWS Trusted Advisor recommendations help improve the reliability and availability of your applications and guide you on how to enhance fault tolerance and reduce downtime. It identifies single points of failure in your architecture, suggests the implementation of backup and disaster recovery mechanisms, and offers guidance on setting up auto-scaling to handle sudden spikes in traffic. By following these recommendations, you can build a highly available and resilient infrastructure. * ### **Operational Excellence** Trusted Advisor contributes to operational excellence by offering insights into your AWS infrastructure's functional health. It monitors your usage patterns, service limits, and other relevant metrics, helping you proactively address any potential issues. Whether it's optimizing your account security, managing your service limits, or staying up to date with the latest AWS service offerings, Trusted Advisor provides actionable recommendations to streamline your operations and ensure you're leveraging the full potential of AWS. * ### **Resource Utilization** AWS Trusted Advisor helps organizations maximize their resource utilization. It provides recommendations on right-sizing instances, optimizing storage utilization, and identifying unused or idle resources. By following these recommendations, businesses can eliminate wastage and make better use of their cloud resources, ultimately leading to improved efficiency and cost savings. * ### **Compliance and Governance** Maintaining compliance with industry regulations and governance standards is crucial for businesses. AWS Trusted Advisor offers checks and recommendations to ensure compliance with various frameworks such as HIPAA, PCI DSS, and GDPR. It helps identify potential compliance issues and provides guidance on how to address them, enabling organizations to meet their regulatory requirements and maintain a secure and compliant cloud environment. * ### **Notifications and Alerts** Trusted Advisor offers notifications and alerts for critical issues and best practice violations. It keeps organizations informed about potential risks, security vulnerabilities, and other important events in their AWS infrastructure. By receiving timely alerts, businesses can take proactive measures to address any issues and mitigate potential risks, ensuring the stability and security of their applications and services. * ### **Operational Efficiency** Efficient management of AWS resources is essential for smooth operations. Trusted Advisor assists in streamlining operations by providing recommendations on service limits, checking for unused load balancers or NAT gateways, and suggesting improvements in account security. By implementing AWS Trusted Advisor recommendations, organizations can enhance their operational efficiency, reduce manual tasks, and optimize the management of their AWS environment. * ### **Cost Forecasting** In addition to optimizing costs, Trusted Advisor offers insights into cost forecasting. It provides visibility into future spending based on historical data, usage patterns, and resource trends. This allows organizations to anticipate and plan for future expenses more accurately, helping them make informed resource allocation and budgeting decisions. ## **A Business example where this was****used** One example of a business benefiting from AWS Trusted Advisor is a Software-as-a-Service (SaaS) company that operates a cloud-based platform for managing customer relationships and sales processes - "CloudCRM." CloudCRM had experienced fast growth, resulting in a complex AWS infrastructure with multiple services, instances, and storage resources. As their customer base expanded, so did their AWS costs. They realized the need to optimize their infrastructure to control costs while maintaining high performance and security standards. This is where AWS Trusted Advisor came to their rescue as an AWS cost control tool. ## **Conclusion** AWS Trusted Advisor is a valuable tool that benefits businesses operating in the AWS cloud environment. From By leveraging this AWS cost management tool, organizations can reduce costs, enhance security, improve performance, and ensure the reliability of their applications and services. Incorporate AWS Trusted Advisor into your AWS workflow to unlock its full potential and achieve a more efficient and secure cloud infrastructure. _Our AI-driven RI Management solution,_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents ## **What is Amazon ECS ?** Amazon ECS (Amazon Elastic Container Service) is a highly scalable, secure, reliable, and powerful container orchestration service. It allows you to run and manage Docker containers easily and efficiently in a cluster of EC2 or AWS Fargate, a serverless compute engine for containers. ECS container orchestration allows you to launch, stop and scale containers with ease, and it provides a set of APIs and CLI tools for integrating with other AWS services and third-party tools. Businesses also use Amazon Elastic ### **Components of Amazon ECS** Amazon ECS service consists of the following components: 1. Task Definition: A task definition is a blueprint for the containers that run in an AWS ECS service. It defines the Docker images, CPU and memory requirements, networking configuration, and other parameters needed to run the containers. 2. Task: A task is an instance of a task definition that runs on a container instance in an AWS ECS cluster. 3. Service: A service is a logical grouping of tasks that perform a similar function. A service ensures that a specified number of tasks are running and provides a way to load balance traffic across them. 4. Cluster: A cluster is a logical grouping of container instances that run ECS tasks. 5. Container Instances: A container instance is an 6. Scheduler: The scheduler is responsible for placing tasks onto container instances based on their resource requirements, placement constraints, and availability. ## **What is Service-to-Service Communication?** Service-to-service communication refers to the exchange of data and messages between different microservices or containerized applications. In a microservices architecture, different parts of an application are broken down into smaller, more modular services that communicate with each other via APIs. This allows for greater flexibility, scalability, and agility when developing and deploying applications. For microservices to function properly, they need to be able to communicate with each other reliably and securely. This is where ECS comes in. ECS offers several ways to enable service-to-service communication in microservices, including: ### **1. Amazon ECS Service Discovery** ECS supports service discovery, which makes it easy for containerized applications to find and communicate with each other. ECS integrates with AWS Cloud Map, which is a managed service registry that allows you to define custom names for your applications, services, and resources. Using ECS service discovery, you can create a DNS record for your application, which can be resolved to the IP address of the container that is currently running the application. This makes locating and communicating with your application easy for other services. ### **2. AWS App Mesh** App Mesh is a networking service that shows you how your services are communicating with each other, giving you end-to-end visibility by deploying a lightweight envoy proxy alongside the container and it helps to ensure high availability for your application. ### **3. Amazon ECS Service Connect** Amazon ECS Service Connect provides managed service-to-service communication based on Amazon ECS configuration. It does this by creating both ECS service discovery and a service mesh. The complete configuration is provided inside each service. ECS Service Connect is a way to connect or refer to each of your services within the same namespace and it does not depend on the Amazon VPC. ECS Service Connect also provides logs and standardized metrics to monitor each of our services on Amazon ECS, thereby also ## **ECS Service Discovery and ECS Service Connection using AWS Cloud Map** ### **What is a Cloud map?** AWS Cloud Map is a service that helps you manage the names and locations of your cloud resources, such as virtual machines, containers, and other services For example, if you have a microservices-based application running on AWS, you can use Cloud Map to register and discover the location of each service. This allows other services in the application to easily locate and communicate with the registered services, without needing to know their exact IP addresses or locations. ### **ECS Service Discovery** Containers are immutable by nature, they can be replaced with a newer version of service or can be changed regularly. This means that we can register new or upgrade services and deregister the old or unhealthy services. To do this is a challenging task and hence there is a need for ECS service discovery. #### **Configuration** When creating an Amazon ECS service the service discovery integration is listed as the second last section of the Configure network page. As shown in Figure, a new namespace called sample-namespace is being created, along with a service name of the backend. Whenever a client needs to communicate with the backend service, they’ll simply use the backend. sample-namespace to resolve all service endpoints. The section right after service discovery is for establishing the Amazon Route 53 record types, AKA Service Discovery Instance After the successful creation of the service, we should verify whether all tasks are running or not. Once we’ve verified the tasks are all running, we should be able to hop over to the Amazon Route 53 console to also verify the existence of records that Now if we dig or curl the service using an instance or another service instance in the same VPC, we get results as shown in Figure. ### **ECS Service Connect** AWS launched ECS Service Connect, a capability of Amazon ECS providing seamless service-to-service communication across VPC and ECS Cluster that integrates the capabilities of service discovery and service mesh inside an ECS service configuration. #### **Configuration** To configure ECS Service Connect, the first step is to update or create the task definition with the additional property of app protocol in the Port Mapping section. This additional layer 7 protocol helps to get additional metrics. Allowed values for AppProtocol are HTTP, HTTP2, GRPC Create a service from task definition. When creating a new service or updating the service, click Turn on Service Connect Under the ECS service connect configuration there are two options i.e. Client side only and Client and Server. Choose the client side if the container in the task needs to connect to an endpoint from a service in a namespace. For the other option, the service does not get its endpoint Choose client and server service if the container exposes and listens on a port for network traffic. This service gets an endpoint to communicate with any service within the same namespace If you select client and server service then the service connect and discovery name configuration will appear which has a few options. The discovery name is used to create an AWS cloud map service. If this name is not specified, the port name from the task definition is used DNS Name is the one that you use in the applications of client tasks to connect to this service and the listening port number for the Service Connect proxy. Each service with client and server configuration will get an endpoint in the form of http://DNS-Name:Port Eg. http://demo:8090 To connect to services running on different ECS clusters, you must specify the same namespace in the cluster configuration so that all ECS services can communicate with each other. ECS Service Connect will make your services discoverable by all services in the same namespace. After the creation of services in the same namespace, the services can connect or communicate to this service by the endpoint given in the configuration and task ## **ECS Service Discovery and ECS Service Connect Cost** ECS Service Discovery and ECS Service Connect are two different AWS services that offer similar functionality but with different ECS pricing structures. Here's an example that highlights the cost difference between the two: Let's consider a scenario where you have a microservices-based architecture deployed on ECS. You have multiple services running as containers and must enable ECS Service Discovery or Service Connection and Communication between them. Let's compare the cost difference between ECS Service Discovery and ECS Service Connect for a typical setup: ## **ECS Service Discovery:** * It is charged for AWS Cloud Map discovery API functionality and AWS Route 53 resources. This includes the cost of creating an AWS Route 53 hosted zone and queries to the service registry. ## **ECS Service Connect:** * ECS Service Connect does not have any separate cost or pricing model. Its pricing depends on whether you use AWS Fargate or Amazon EC2 infrastructure to host your containerized workloads. Customers using Amazon ECS service connect are charged for AWS Cloud Map discovery API operations. It also provides free traffic telemetry. For more information, refer to ## **Conclusion** ECS Service Discovery and ECS Service Connect are used for service-to-service communication, but ECS Service Connect is more advanced and cost-effective as it does not have any additional cost, it can be used for communication of services in other VPCs and it also provides monitoring of traffic health of the connected services. CloudKeeper helps you optimize and streamline your AWS infrastructure, by handholding you toward the best practices and cost-efficient considerations. Want to know more about CloudKeeper Services? Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Imagine you’re working on a complex application built using a microservices architecture—where every feature, like user authentication, payment processing, or notifications, runs as an independent service. Microservices make such applications easier to develop, scale, and update, but they also come with their own set of challenges. Managing all these services, keeping them running smoothly, and ensuring they work together can feel like juggling dozens of spinning plates. Enter **Containers** - a pivotal technology in modern application architecture. Containers package each microservice with everything it needs to run—libraries, dependencies, configurations—so it works consistently, no matter where it’s deployed. But as your application grows, managing all these containers manually becomes overwhelming. This is where **Container Orchestration** steps in. It’s the backbone of modern application management, automating the deployment, scaling, and optimization of containers so you can focus on building great software. In this blog, we will be unpacking some of the core concepts of containers and container orchestration, and delve deeper into the services offered by AWS for managing and optimizing containers. ## **What is a Container?** Building on the concept of microservices, containers are a lightweight way to package and run software. Each container bundles an application’s code along with its libraries, dependencies, and configuration, ensuring it runs consistently across environments. Unlike virtual machines, containers share the host operating system, making them faster and more efficient. Their portability, resource optimization, and ability to isolate applications make containers the backbone of modern application development. Whether running a single service or hundreds in a microservices setup, containers are a game-changer for engineers managing complex, distributed systems. ## **What is Container Orchestration?** Container orchestration is the process of managing containers automatically, so applications run smoothly across multiple systems. It involves organizing and scheduling containers, balancing loads, allocating resources, and ensuring they stay up and running. Orchestration tools handle everything from deploying and updating containers to monitoring their health and recovering from failures. The open-source container orchestration tools that are widely used include Kubernetes, Docker Swarm and Openshift This makes it easier for teams to Visual representation of Container Orchestration ## **Why is Container Orchestration Necessary?** Container orchestration is essential for several reasons: * **Simplifies container management:** Helps automate the deployment, scaling, and management of containers, saving time and reducing manual effort. * **Scales applications easily:** Controls how many container instances run at any time based on demand, ensuring applications are always available. * **Improves system resilience:** Automatically detects and replaces failed containers to maintain service availability and uptime. * **Enhances visibility:** Provides real-time insights into container health, * **Supports automation:** Allows automatic deployment and updates of containers without manual intervention, streamlining workflows and reducing errors. Without orchestration, managing large-scale containerized applications becomes too complex and error-prone, making automation essential for efficiency and reliability. ## **What are the benefits of Container Orchestration?** Container orchestration offers several key advantages for organizations, making it an essential tool for modern cloud-based applications. * **Improved Scalability:** Containers can be scaled up or down based on demand, allowing applications to handle more traffic and workloads without manually managing each container. * **Enhanced Security:** By centralizing security management across containers and platforms, orchestration tools help prevent vulnerabilities and ensure consistent security policies across the stack. * **Better Portability:** Container orchestration makes it easier to manage containers across different cloud providers or environments with consistent deployment and operation, allowing applications to move seamlessly between platforms —perfect for multi-cloud strategies. * **Reduced Costs:** Containers use fewer resources compared to virtual machines, * **Faster Error Recovery:** Orchestration tools automatically detect and resolve issues like container failures, ensuring high availability and minimal downtime for applications. * **Increased Productivity:** By automating routine tasks like deployment and scaling, container orchestration frees up developers to focus on more critical work, boosting overall productivity. These benefits streamline operations, improve performance, and reduce costs, making container orchestration a vital tool for businesses adopting cloud-native applications. ## **Container Orchestration in AWS** As we’ve seen, container orchestration simplifies the management of containers in complex environments. For AWS, there are two essential services for managing containers that are comparable - **AWS ECS vs EKS**. * **Amazon ECS (Elastic Container Service):** A fully managed service that makes it easy to deploy, manage, and scale containers. ECS integrates tightly with other AWS services, making it a great choice for applications that rely heavily on the AWS ecosystem. * **Amazon EKS (Elastic Kubernetes Service):** A managed Kubernetes service that allows you to run Kubernetes-based applications without the operational overhead of maintaining the control plane. EKS is ideal for teams already familiar with Kubernetes or looking to leverage its extensive ecosystem. Both ECS and EKS provide the foundation for running containerized workloads efficiently. In the next sections, we’ll dive deeper into ECS vs. EKS, how each works, the parameters impacting ECS pricing and EKS pricing, and which might be the right fit for your use case. ## **What is Amazon Elastic Container Service (ECS)?** Amazon Elastic Container Service (ECS) is a fully managed container orchestration service designed to simplify the deployment, scaling, and management of containerized applications. ECS is deeply integrated with the AWS ecosystem, providing seamless connectivity with services like EC2, Fargate, IAM, and CloudWatch. Its AWS-opinionated design prioritizes simplicity, reducing the operational overhead of managing complex container infrastructures. AWS ECS eliminates the need for ### **Features of Amazon ECS** * **Fully Managed Service:** ECS abstracts away the complexity of container management, enabling developers to concentrate on their applications instead of the underlying infrastructure. * **Launch Types:** * **Fargate Launch Type:** Serverless mode eliminates the need to manage compute resources. * **EC2 Launch Type:** Allows fine-grained control over the EC2 instances that host containers. * **External Instances (ECS Anywhere):** Manage workloads running on on-premises servers or in other cloud environments. * **Blue/Green Deployments:** Streamlines application updates using AWS CodeDeploy to reduce downtime and minimize risks during rollouts. * **ECS Service Connect:** Simplify microservice communication with built-in service discovery and resilience features, eliminating the need for code changes. * **Task Definitions:** Specify container runtime parameters like CPU, memory, environment variables, networking configurations, and IAM roles for granular container control. * **Service Discovery:** Enable automatic service registration and name-based * **Cluster Auto Scaling:** Automatically scale EC2 instances in a cluster based on workload demands, optimizing resource utilization and costs. * **ECS Exec:** Execute commands directly in running containers, simplifying debugging, patching, and interaction with deployed applications. * **Seamless Integration with AWS Ecosystem:** Integrates deeply with AWS services like CloudWatch, IAM, Elastic Load Balancers, and Amazon ECR for monitoring, security, networking, and container storage. * **ECS Anywhere:** Extend ECS's capabilities to manage workloads across hybrid and multi-cloud environments using the same tooling and control plane. AWS ECS Architecture (Source: AWS) ### **Pros of Amazon ECS** * **Simple to Use:** ECS minimizes decision-making by handling much of the compute, network, and security configuration. This simplicity reduces the overhead for users while maintaining its robust capabilities. * **Flexible Scaling Options:** ECS supports auto-scaling, allowing applications to dynamically adjust based on demand. You can configure policies to * **Cost-Effectiveness:** ECS eliminates the need to manage a control plane, reducing operational costs. Additionally, its pay-as-you-go pricing ensures you only pay for the resources you use. * **Support for Fargate and EC2 Launch Types:** ECS provides flexibility in choosing between serverless (Fargate) and traditional (EC2) container deployment options based on your workload requirements. * **Managed Instance Draining:** ECS ensures a smooth shutdown of workloads on EC2 instances by safely stopping and rescheduling tasks on other instances, minimizing disruption. ### **Cons of ECS** * **Limited Flexibility:** Compared to Kubernetes (used by EKS), ECS lacks advanced customization and extensibility. * **AWS-Centric:** ECS is tightly coupled with AWS, making it unsuitable for multi-cloud strategies. * **Vendor Lock-In:** ECS works exclusively with AWS, and migrating workloads to another platform can be complex and resource-intensive. * **Lack of Full Control:** A fully managed service, ECS restricts deep-level infrastructure control, which might not suit applications requiring fine-grained tuning or specific infrastructure setups. ### **Amazon ECS Pricing** AWS Elastic Container Service (ECS) offers flexible pricing structures tailored to different deployment models, enabling businesses to choose the most cost-effective approach based on their application needs. * **AWS Fargate Launch Type:** You pay based on the vCPU and memory resources requested by your application. ECS Pricing is calculated from when the container images are pulled until the ECS task terminates, with charges rounded up to the nearest second (minimum one-minute charge). * **Amazon EC2 Launch Type:** There are no additional charges for the EC2 launch type. You pay only for the AWS resources you provision, such as EC2 instances, EBS volumes, and public IPv4 addresses, on a pay-as-you-go basis. * **Amazon ECS on AWS Outposts:** ECS on Outposts follows the same ECS pricing model as the cloud. The ECS control plane remains in the cloud, while your container instances run on Outposts EC2 capacity at no extra charge. _PS: AWS Outposts is a fully managed service that extends Amazon Web Services (AWS) infrastructure, services, APIs, and tools to on-premises environments._ ## **What is Amazon Elastic Kubernetes Service (EKS)?** Amazon Elastic Kubernetes Service (EKS) is a fully managed service that makes it easier to run Kubernetes on AWS. Unlike ECS, which is more AWS-centric, EKS leverages the power of Kubernetes, giving you flexibility and control over your containerized applications. It’s perfect for complex, microservices-based applications that require advanced orchestration, scalability, and portability across different environments. EKS manages the Kubernetes control plane, ensuring it’s secure and highly available, so developers can focus on ### **Features of Amazon EKS** * **Fully Managed Kubernetes:** EKS manages the Kubernetes control plane, including patching and updates, reducing operational overhead. * **Seamless AWS Integrations:** Works with AWS services like Identity and Access Management (IAM), Amazon VPC, and AWS Load Balancer for enhanced security and networking. * **EKS Anywhere:** Operate Kubernetes clusters in on-premises environments using VMware vSphere or AWS Outposts. * **EKS Fargate:** Offers serverless compute for containers, eliminating the need to manage infrastructure. * **Enhanced Networking:** Provides advanced networking with Amazon VPC CNI for better performance and resource efficiency. * **Graviton2 Support:** Enables * **Multi-Region Support:** Deploy applications across regions for disaster recovery and high availability. Amazon EKS Architectures (Source: AWS) ### **Pros of Amazon EKS** * **Accelerated Time to Production:** Simplifies cluster infrastructure management with automated provisioning and scaling. * **Flexibility Across Environments:** Supports Kubernetes clusters on AWS, on-premises, and at edge locations, offering versatile deployment options. * **Enhanced Security:** Built-in security features, including automatic patching and integrations with AWS security services. * **Cost Optimization:** Leverage Spot Instances, resource auto-scaling, and efficient compute resource management to reduce costs. * **Kubernetes Compatibility:** Supports existing Kubernetes tooling, ensuring smooth workload migration. ### **Cons of Amazon EKS** * **Complexity:** Requires a solid understanding of Kubernetes and AWS integrations, presenting a steep learning curve for beginners. * **Operational Overhead:** Responsibility for managing worker nodes, including patching, monitoring, and scaling, adds complexity. * **Cost Management Challenges:** Over-provisioning or selecting suboptimal node types can lead to increased costs. Additional fees for control planes and unsupported Kubernetes versions add to expenses. ### **Amazon EKS Pricing** Amazon Elastic Kubernetes Service (EKS) offers scalable and flexible pricing, allowing organizations to efficiently manage their Kubernetes clusters while leveraging AWS infrastructure. EKS pricing is determined by several factors, including the Kubernetes version in use, the type of instances deployed, and any integrated AWS services. * **Cluster Fee:** Amazon EKS * **EKS Auto Mode:** You pay for the EC2 instances managed by EKS Auto Mode, in addition to EC2 instance charges. This model of EKS pricing uses per second billing, with a one-minute minimum. You can choose from On-Demand, Reserved, Compute Savings Plans, or Spot Instances for EC2 pricing. * **Hybrid Nodes:** For hybrid environments, EKS pricing is based on vCPU per hour. This applies when using on-premises or edge infrastructure as nodes within the EKS cluster. Billing begins when hybrid nodes are added and stops when they are removed. Pricing tiers are based on aggregated monthly vCPU-hour usage across the region. * **AWS Services:** Additional charges apply for AWS resources like EC2, EBS, and VPC services used by your Kubernetes worker nodes. EKS Pricing for Fargate is based on vCPU and memory resources used during pod execution, with a one-minute minimum charge. * **AWS Outposts:** For EKS clusters running on AWS Outposts, the standard EKS cluster fee applies, but the fee does not include extended Kubernetes version support. ## **Choosing the Right Service for Your Infrastructure: ECS vs. EKS** When it comes to AWS ECS vs. EKS, the choice ultimately depends on the needs of your applications. Both services bring distinct strengths to container orchestration, and understanding their differences is key to making the right decision. Amazon ECS is a user-friendly, fully managed service ideal for teams already immersed in the AWS ecosystem. Its simplified operations reduce the need for extensive container orchestration knowledge, making it perfect for applications that prioritize ease of use and tight integration with AWS services. With support for serverless workloads through Fargate, ECS offers a cost-effective solution for straightforward deployments. On the flip side, Amazon EKS offers a powerful Kubernetes-based platform that excels in handling complex, microservices-driven architectures. While it demands more operational oversight and Kubernetes expertise, EKS provides unparalleled flexibility, enabling advanced workload management and portability across cloud and on-premises environments. This makes EKS a strong contender for hybrid or multi-cloud strategies and teams seeking to leverage Kubernetes’ robust ecosystem. Cost constraints can also drive a decision. AWS ECS pricing tends to have the edge with lower upfront costs, especially with Fargate. However, the EKS pricing model delivers long-term benefits for dynamic workloads through its advanced autoscaling and efficient resource management. In summary, **ECS is your best bet for simplicity and AWS-centric applications, while EKS is the solution for complex, scalable architectures requiring greater control.** The question of ECS vs EKS comes down to your technical requirements and vision for your infrastructure’s future. _For a deeper dive into service comparisons, real-world use cases, and answers to frequently asked questions about AWS ECS and EKS,_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Containers have changed how we build and deploy applications. They make it easier to package software and run it anywhere. But managing containers at scale requires orchestration tools. That’s where services like Amazon Elastic Container Service (ECS) and Amazon Elastic Kubernetes Service (EKS) come in. If you’re new to these services and want to understand their fundamentals, check out ## **Quick Comparison: AWS ECS vs EKS** Both ECS and EKS help automate the deployment, scaling, and management of containers. But they have key differences. * AWS ECS is a fully managed container orchestration service that is deeply integrated with AWS services, offering simplicity, cost efficiency, and Fargate support for serverless container execution. * AWS EKS is a managed Kubernetes service that provides multi-cloud portability, advanced orchestration, and customization capabilities but comes with a steeper learning curve. To better understand the AWS ECS vs EKS comparison, let’s take a look at a comparative table. Thus, both ECS and EKS are powerful container orchestration solutions on AWS, each offering unique advantages. While ECS provides a simpler, AWS-native framework, EKS offers greater flexibility and portability with Kubernetes. The right choice depends on your application needs and operational preferences. ## **When to choose Amazon ECS?** Amazon ECS is a great choice for a fully managed, deeply integrated container orchestration service within AWS. ECS pricing is also more cost-effective, with no additional management fees and flexible cost structures based on resource usage. It is designed to handle diverse workloads efficiently, offering seamless scalability, automation, and security. ### **Specific scenarios where ECS excels** * **Modernizing legacy applications** If you have legacy applications that need better scalability and portability, ECS makes containerization straightforward. It allows you to migrate existing applications with minimal refactoring, ensuring they run efficiently in a modern cloud environment. * **Building cloud-native microservices** ECS is ideal for organizations developing microservices-based architectures. With deep AWS integrations (like Amazon RDS and DynamoDB), ECS helps teams build and manage scalable, decoupled applications while * **Need automated CI/CD pipelines** For teams focusing on continuous integration and deployment, AWS ECS vs EKS comes down to automation and ease of use. ECS integrates seamlessly with AWS CodePipeline, enabling automated application builds, testing, and deployments. This allows teams to roll out updates with zero downtime, ensuring faster and more reliable releases. * **Running batch processing and High-Performance Computing (HPC) workloads** For applications that require high computing power, such as scientific simulations, AI model training, or large-scale data processing, running ECS on EC2 allows you to choose compute-optimized or GPU-enabled instances to match workload needs. With AWS ECS, you can perform auto-scaling of instances based on demand, ensuring optimal performance without over-provisioning resources. * **Deploying serverless and event-driven applications** When comparing AWS ECS vs EKS for serverless and event-driven workloads, ECS with AWS Fargate stands out. It eliminates the need for infrastructure management, making it an * **Consistent deployment across hybrid and on-premises environments** With AWS ECS Anywhere, you can deploy applications both on AWS and on-premises infrastructure. This ensures consistency across development, testing, staging, and production environments - reducing configuration drift and deployment risks. * **Automated scaling for cost optimization** ECS supports auto-scaling policies, dynamically adjusting the number of tasks based on demand. This ensures optimal performance during peak loads while minimizing costs during low-usage periods. * **Centralized logging and security** ECS integrates with Amazon CloudWatch for monitoring logs and setting up alerts. This makes it easier to track application health, detect anomalies, and proactively address issues before they impact users. Whether you're modernizing applications, running microservices, or seeking ## **When to use Amazon EKS** AWS EKS is the right choice if you need Kubernetes for container orchestration, hybrid or multi-cloud flexibility, or advanced networking controls. It works well for large microservices, machine learning, and applications that require persistent storage or GPU power. However, EKS pricing includes an additional cluster management fee, making it a costlier option compared to ECS, especially for smaller workloads. ### **Specific scenarios where EKS excels** * **Kubernetes-based workloads** EKS is the go-to choice for businesses that want to run applications in a Kubernetes-native environment. It allows organizations to take advantage of Kubernetes’ extensive ecosystem, including Helm charts, custom controllers, and service meshes like AWS App Mesh and Istio. _(Learn how to optimize costs in EKS with our_ _.)_ * **Hybrid and multi-cloud deployments** For businesses managing workloads across on-premises and multiple cloud environments, the choice between AWS ECS vs. EKS becomes clearer - AWS EKS is the better fit, as it simplifies hybrid and multi-cloud deployments. With EKS Anywhere, you can run Kubernetes clusters on your own infrastructure while maintaining the flexibility to move workloads between AWS and other cloud providers. Additionally, EKS integrates with * **Custom networking and advanced security** EKS offers granular control over networking through features like custom VPC configurations, security groups, and Kubernetes Network Policies. It also integrates with third-party security tools, making it ideal for businesses that require highly customized security configurations. * **Stateful applications and persistent storage** Unlike ECS, which is optimized for stateless services, EKS is well-suited for stateful applications such as databases and data-intensive workloads. It integrates seamlessly with Amazon EBS, EFS, and FSx, providing reliable persistent storage. * **Machine learning and high-performance computing** Both tools support high-performance computing, however, while comparing AWS ECS vs EKS, the latter supports GPU-powered workloads better, making it a strong choice for AI/ML applications. It works with deep learning frameworks like TensorFlow and PyTorch, and integrates with SageMaker for efficient training and inference tasks. * **Self-managed Kubernetes add-ons and customization** EKS allows teams to install custom Kubernetes add-ons, such as Prometheus for monitoring, Fluentd for logging, or custom admission controllers. ECS, in contrast, has a more rigid, AWS-managed structure with fewer customization options. * **Scalable web applications** AWS EKS enables developing highly available web applications over multiple availability zones with the Both EKS and ECS provide automated scaling, AWS integrations, and cost optimization through Spot Instances. They ensure high availability, security, and seamless deployments. However, Amazon EKS is the better choice if you need advanced networking, cross-cloud portability, or Kubernetes-specific tools. ## **AWS ECS vs EKS: Decision Framework** Selecting the right container orchestration service depends on your workload requirements, operational complexity, and cloud strategy. Here is a quick checklist to determine the best fit for your workloads: You can use this flowchart as a high-level guide to selecting the right container management service. While it doesn’t cover every specific edge case, these key factors can help determine whether ECS or EKS is the better fit for your workloads. ## **AWS ECS vs. EKS vs. Fargate** Comparing ECS, EKS, and Fargate isn’t exactly fair because Fargate isn’t a separate service - it's a compute option for running containers in ECS and EKS. While ECS and EKS help you manage and orchestrate containers, Fargate takes care of the underlying infrastructure, so you don’t have to worry about managing servers. ### **When to Use AWS Fargate?** Fargate is ideal when you want to focus on running containers without managing the underlying infrastructure. It automatically provisions and scales compute resources based on demand, making it a great option for teams that prefer a serverless approach. **Use Fargate when:** * Your workload already runs on serverless technologies or you plan to transition in the future. * Streamlining infrastructure management is a priority for productivity and cost efficiency. * You only need container-level permissions and minimal customizations. * Whether you use Docker or Kubernetes doesn’t significantly impact your decision. * Running your own components is essential, but managing EC2 instances is not. * You are comfortable using only AWS VPC networking mode. * You want a mix of Fargate and EC2 tasks within the same cluster for flexibility. * Paying only for compute time, without managing EC2 instances, aligns with your cost strategy. ## **AWS ECS vs EKS: How to make the right choice?** Amazon ECS and EKS both help you run containerized applications, but they serve different purposes. ECS is the easier, more AWS-native choice, perfect for teams that want a fully managed service with minimal setup. It’s great for EKS, on the other hand, is built for companies that need the flexibility of Kubernetes. It’s ideal for hybrid or multi-cloud deployments, advanced networking, and high-performance applications like machine learning. While ECS keeps things simple, EKS offers more control and customization, making it better suited for enterprises with complex workloads. When it comes to cost, ECS pricing is usually the more affordable option, especially for AWS-focused businesses. AWS EKS comes with extra overhead since EKS pricing includes a cluster management fee, but it makes sense if your team already knows Kubernetes and needs its advanced features. Ultimately, the right choice depends on your infrastructure, how much control you need, and your team's expertise. If you want a straightforward, AWS-managed experience, go with ECS. If you need flexibility and scalability, EKS is the way to go. ## **Simplify container orchestration and minimize costs with CloudKeeper** Choosing between AWS ECS vs EKS is just one part of building an efficient containerized environment - optimizing workloads, managing infrastructure, and controlling costs are crucial too. CloudKeeper helps businesses streamline container management by providing expert guidance on architectural improvements, orchestration strategies, and cost efficiency. With a team of certified AWS architects and cloud specialists, CloudKeeper ensures that your applications are built for scalability and performance while keeping operational complexity in check. From re-architecting workloads to implementing best practices in container orchestration, our approach helps organizations make the most of their cloud investments. ## **Frequently Asked Questions(FAQs)** ### **1. How does AWS ECS work?** AWS Elastic Container Service (ECS) is a fully managed container orchestration service that allows you to run, scale, and manage containers. It supports both EC2 instances and AWS Fargate, giving you flexibility in resource management and scaling. ### **2. How to deploy a service in AWS ECS?** Deploying a service in ECS involves creating a task definition, configuring a cluster, and setting up a service to manage container instances. ECS handles scaling, load balancing, and updates, ensuring smooth application deployment. ### **3. What is an AWS ECS cluster?** An ECS cluster is a logical grouping of tasks and services running on either Amazon EC2 instances or AWS Fargate. It helps manage resource allocation, networking, and scaling for containerized applications. ### **4. What are ECS tasks, and how do they work?** ECS tasks are individual instances of a containerized application. A task definition specifies the Docker image, CPU/memory allocation, networking, and IAM permissions required to run a container within ECS. ### **5. What is AWS Fargate in ECS?** AWS Fargate allows running containers without managing EC2 instances. It automatically provisions compute resources and scales as needed, making it ideal for serverless and event-driven applications. ### **6. When should you use ECS instead of EKS?** ECS is ideal when you need simple container orchestration with deep AWS integration, minimal operational overhead, and cost efficiency. It is a great choice for microservices, batch processing, and auto-scaling applications. ### **7. Why use EC2 in AWS ECS and EKS?** Using EC2 instances in ECS and EKS provides more control over networking, security, and cost optimization. EC2 allows for custom AMIs (Amazon Machine Images), reserved instance pricing, and better handling of workloads with specific performance requirements. ### **8. What is Kubernetes?** Kubernetes is an open-source container orchestration platform that automates scaling, deployment, and management of containerized applications. It enables multi-cloud and hybrid cloud deployments with advanced networking and security features. ### **9. How does AWS EKS work?** Amazon EKS is a fully managed Kubernetes service that simplifies running Kubernetes workloads on AWS. AWS handles the Kubernetes control plane, while you manage worker nodes and workloads. It integrates with AWS services for networking, security, and scaling. ### **10. What is an AWS EKS cluster?** An EKS cluster consists of a managed Kubernetes control plane and worker nodes running on EC2 or AWS Fargate. It provides high availability, scalability, and automation for Kubernetes workloads. ### **11. What is EKS Anywhere?** EKS Anywhere extends EKS to on-premises and hybrid cloud environments, allowing businesses to manage Kubernetes clusters outside AWS. It provides a consistent Kubernetes experience across cloud and on-prem infrastructure. ### **12. Why choose EKS instead of ECS?** EKS is better when you need multi-cloud flexibility, advanced networking, and Kubernetes-specific features like Helm charts and custom controllers. It is ideal for enterprises already invested in Kubernetes ecosystems. ### **13. Why is EKS more expensive than ECS?** EKS pricing has additional costs, including a $0.10 per hour per cluster control plane fee, higher operational complexity, and the need for specialized Kubernetes expertise. ECS pricing, in contrast, has no control plane cost and is easier to manage within AWS. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents If you have ever managed a busy Amazon EKS cluster, you have seen this happen. Most days, everything is fine. Deployments work. Controllers are happy. kubectl responds instantly . Then one day, you roll out a big change. Maybe a cluster upgrade. Maybe a node rotation. A CI job that touches thousands of pods. Suddenly, things slow down. A **kubectl get pods** that normally takes a second now takes 20 or 30 seconds. ArgoCD starts timing out. Some controllers begin throwing API errors. Nothing is fully broken, but everything feels stuck. In many cases, the problem is simple. The Kubernetes API server is overloaded, which is often the result of This exact situation is what led AWS to introduce EKS Provisioned Control Plane. ## **What Actually Happens in Standard Amazon EKS Clusters** By default, every Elastic Kubernetes Service cluster runs in what AWS calls Standard mode. ### **In Standard mode:** * The control plane is fully managed by AWS * It scales up when the load increases * It scales back down when the load drops * You do not pay anything extra beyond normal AWS EKS pricing For most clusters, this works well. The issue is timing. Control plane scaling is reactive. When you suddenly hit the API server with a burst of requests, such as updating thousands of pods at once, there is a short delay before additional capacity is ready. During that window, API calls slow down, and some requests time out. This is usually not a problem for small or medium clusters. But for large clusters, or for environments where automation depends heavily on the API server, even short slowdowns can cause trouble. To prevent the problem in the first place, it’s essential to ## **What Is Amazon EKS Provisioned Control Plane** Provisioned Control Plane is AWS’s way of letting you pre-allocate control plane capacity. Instead of relying on reactive scaling, you choose a fixed capacity tier up front. AWS keeps that capacity available at all times. **A simple way to think about it:** * Standard mode waits for the load to appear, then reacts. * Provisioned mode is already prepared. AWS offers a few predefined tiers, such as**XL, 2XL, and 4XL**. Each tier represents a higher level of guaranteed control plane capacity. ## **What the Tiers Actually Mean** **Each tier defines limits in three main areas:** * How many API requests can be processed concurrently * How fast can pods be scheduled under ideal conditions * How much etcd storage is available for the cluster state The API numbers are expressed in ### **EKS 1.28 and 1.29** ### **EKS 1.30 and later** These numbers assume healthy nodes, reasonable admission webhook latency, and well-behaved controllers. They are best-case targets, not hard guarantees. ## **Standard vs Provisioned Control Plane** **In simple terms:** Provisioned mode does not magically fix bad controllers or slow webhooks. What it does is remove control plane scaling delays from the equation. ## **When Provisioned Control Plane Actually Makes Sense** This is not for everyone. In fact, most clusters should stay on Standard mode. **Provisioned Control Plane makes sense when:** * **You do large updates often** If you regularly deploy or reschedule thousands of pods, the control plane pressure is very real. * **You have predictable spikes** Launch events, promotions, or * **You run heavy****or ML workloads** Rapid node churn and scheduling pressure can overwhelm a standard control plane. * **You want staging to behave like production** Using the same tier across environments removes one variable. * **You care about DR performance** Failover clusters behave consistently from the moment they come online. ## **Things to Be Aware Of** **Before enabling it, keep these points in mind:** * There is an additional hourly cost per tier. * Tiers do not auto-scale. Changing tiers is a manual action. * If your etcd usage exceeds 8 GB in Provisioned mode, you must reduce it before switching back to Standard mode. * Tier changes take a few minutes. * You need AWS EKS 1.28 or newer. ## **EKS Provisioned Control Plane Pricing** AWS charges an additional hourly fee for Provisioned Control Plane on top of the standard EKS cluster control plane fee. For the most current and detailed pricing information, always refer to the official Unchecked EKS usage can quickly lead to bill shocks, particularly in your AWS EKS spend. Here are These charges are in addition to the standard Amazon EKS cluster charge of $0.10 per hour for Kubernetes versions under standard support. ### **Example Monthly Costs (Approximate)** If you run a Provisioned Control Plane for a typical month (~730 hours), the approximate cost would be: ## **How to Decide If You Need It** First, review your control plane metrics. **Check:** * API concurrency * Scheduling activity * **etcd** storage usage If you consistently see spikes during deployments or upgrades and those spikes cause visible slowdowns, Provisioned Control Plane is worth testing. A practical approach is to test the highest tier in a non-production environment, simulate peak activity, and then scale down to the lowest tier that meets your needs. ## **Final Thoughts** Provisioned Control Plane is not a replacement for Standard mode. Standard mode exists for a reason and works well for most clusters. Provisioned mode is useful when you need predictable control plane performance and want to avoid scaling-related delays during known high-load events. Measure first. Test properly. Do not turn it on blindly. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Gourav specializes in helping organizations design secure and scalable Kubernetes infrastructures on AWS. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Amazon Web Services will discontinue support for Amazon Inspector Classic starting May 20, 2026. After this date, access to the Inspector Classic console and resources will be disabled permanently. Inspector Classic is already unavailable to new AWS accounts or accounts without any assessments completed in the past 6 months. Existing users will retain access until the stated end-of-support date. AWS has introduced a globally available, fully reengineered new Amazon Inspector. This advanced service provides enhanced security vulnerability management by automatically discovering AWS workloads—such as EC2 instances, container images, and Lambda functions—and continuously scanning these for vulnerabilities and unintended network exposure. Upon identifying vulnerabilities, Inspector generates findings, which are detailed reports of the vulnerability or misconfiguration. ## **Key Features of the New Amazon Inspector** 1. **Continuous, Automated Scanning:** The inspector conducts real-time vulnerability assessments across your AWS resources automatically. It initiates immediate scanning upon resource deployment or updates, such as 2. **Comprehensive Resource Coverage:** Inspector supports the following - **a) Amazon EC2 Instances:** Automated scanning of operating systems, applications, and network configurations for exposure without manual target selection. **b) Amazon ECR Container Images:** Automatic integration with **c) AWS Lambda Functions:** Scanning of 3. **Flexible Scanning Methods for EC2:** Inspector provides two distinct scanning approaches: **a) Agent-Based Scanning:** Uses AWS Systems Manager (SSM) Agent for real-time software inventory collection, including deep package analysis. **b) Agentless Scanning:** Utilizes EBS snapshot analysis to detect OS and application-level vulnerabilities without installing agents. By default, Inspector follows a hybrid approach, using agent-based scanning for SSM-based instances and switching to agentless unmanaged EBS-backed instances. Agentless scans run at least every 24 hours. 4. **Context-Aware Risk Scoring and Dashboard:** Inspector findings include CVSS severity ratings and custom risk scores (0-10) for the scanned resources. The centralized dashboard simplifies visibility, highlighting critical vulnerabilities and risk trends for prioritized remediation. 5. **Integrated Remediation Capabilities:** Findings are centralized within the Inspector console and APIs. Integration with AWS Security Hub, 6. **Enhanced Capabilities:** **a) Software Bill of Materials (SBOM):** Generates and centrally manages detailed software inventories for EC2, container images, and Lambda functions. **b) CIS Benchmark Assessments:** Performs on-demand configuration checks against CIS security benchmarks. **c) CI/CD Integration:** Seamlessly integrates into development pipelines (ex., Jenkins) for early vulnerability detection during the build process. ## **Migration Steps from Inspector Classic to the New Amazon Inspector:** While AWS will continue to support Amazon Inspector Classic for some time, and customers can use both the new Amazon Inspector and Amazon Inspector Classic in the same account. The following sections walk you through the process of moving from Amazon Inspector Classic to the new Amazon Inspector. ### **Step 1: (Optional) Export assessment reports and findings** To save the assessment reports and findings in Amazon Inspector Classic, generate an assessment report by following the steps below. On the Assessment Runs page, locate the assessment run that you want to generate a report for. Make sure that its status is Analysis complete. Under the Reports column for this assessment run, choose the reports icon. In the Assessment report dialog box, choose the type of report that you want to view (either a Findings report or a Full report) and the report format (HTML or PDF). Then choose Generate report. ### **Step 2: Delete all scheduled assessment runs in Amazon Inspector Classic** To disable Amazon Inspector Classic, delete all the assessment templates in your account in all active AWS Regions. Deleting assessment templates stops all your scheduled future assessment runs. On the Assessment Templates page, choose the template that you want to delete, and then choose Delete. When prompted for confirmation, choose Yes. **Note:** When you delete an assessment template, all assessment runs, findings, and versions of the reports associated with this template are also deleted. ### **Step 3: Enable the new Amazon Inspector** You can enable the new Amazon Inspector using the AWS Management Console or the new Amazon Inspector APIs. This is typically done by clicking “Get Started” then “Activate Amazon Inspector”. Upon activation, all available scan types (EC2, ECR, and Lambda scanning) are enabled by default, and the required service-linked role is created automatically. Inspector will immediately begin discovering resources and initiating scans. In a multi-account environment, use your Organization's management account to designate a delegated administrator for Inspector and enable the service across member accounts.(This can also be automated via API/CLI for bulk accounts.) ### **Step 4. Verify and Monitor** Once enabled, monitor the new Amazon Inspector’s coverage and findings. The Inspector dashboard will show how many EC2 instances, images, and functions are being monitored. Verify that all expected resources are listed as covered (for EC2, the “Instances” tab under Account Management shows each instance’s scanning status). Ensure SSM Agent is running on instances so they move from “Unmanaged” to managed scanning, or else agentless will cover them. It’s normal to see a surge of initial findings as the new Inspector completes its first scans – review these results and compare against what Classic had reported to ensure nothing critical is missed. ### **Step 5. Sunset Inspector Classic** After the new Inspector is running and you are satisfied with its coverage, you can fully sunset the Classic deployment. This includes informing teams of the new interface/API to use, updating any automation or reports that pulled from Classic API to instead use the new Inspector’s API (which uses a different namespace, typically inspector2 in AWS SDK/CLI), and removing any remaining Classic IAM assets. If you rely on Security Hub, note that you might have had Classic findings in Security Hub: going forward, the new Inspector will send findings there. Ensure no one is trying to access the old Classic console or endpoints. ### **Step 6. No Overlap with Classic Agent** If you previously used Amazon Inspector Classic, you may have the old Amazon Inspector Agent installed on some servers. The new Amazon Inspector does not use or need the Classic agent – in fact, the Classic agent is now obsolete. It’s recommended to uninstall the Classic agent once you migrate (after ensuring no further Classic assessments will run) to avoid confusion. The new Inspector’s use of SSM Agent means one less agent to manage on your instances. ## **Inspector Pricing (N.Virginia)** **AWS Lambda standard scanning:** 10 Lambda functions scanned for all 30 days at $0.30 per function = $3.00 per month **AWS Lambda standard and code scans:** 10 Lambda functions scanned for all 30 days at $0.90 ($0.30+$0.60) per function = $9.00 per month **EC2 Instance scanning per month (includes continual vulnerability and network reachability scans):** 10 EC2 instances scanned for all 30 days at $1.258 each = 10 * $1.258 = $12.58 per month (SSM-agent based scanning) 10 EC2 instances scanned for all 30 days at $1.750 each = 10 * $1.750 = $17.50 per month (agentless based scanning) **ECR container image scanning:** 1,000 newly pushed container images initially scanned at $0.09 each = 1,000 * $0.09 = $90.00 per month Check out the Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Associate Devops Lead Aakash is an AWS Certified Professional specializing in DevOps, with deep expertise across Cloud Automation, CI/CD Pipelines, Infrastructure as Code (IaC), and Monitoring stacks. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 13 13 Table of Contents Data is the single most crucial unit for the smooth functioning of any software-driven business, and how it’s handled defines the experience users have with your platform. For instance, customer data must be secured from unauthorized access, and databases should deliver fast I/O performance. So, if you’re a business evaluating databases, it's essential to consider all factors — including cost — as storing and managing data can be expensive. This blog explores two of the most popular AWS-managed databases that power millions of applications and store terabytes of data: Amazon RDS and Amazon Aurora. Keep in mind, there's no ‘Amazon RDS vs Aurora’ scenario; ## **Understanding the Databases: Amazon RDS and Amazon Aurora** Both Amazon Aurora and Amazon RDS are AWS-managed databases, where AWS handles provisioning, patching, backups, recovery, and routine maintenance — either through automation or manual intervention. While they share fundamental similarities, they begin to diverge when it comes to specialization in use cases. As a result, they differ in pricing, performance, flexibility, storage capacity, and more. Here’s a brief overview of the two most popular AWS-managed databases: ### **What is Amazon RDS?** Amazon RDS, short for Relational Database Service, simplifies the setup and management of complex relational databases by offloading administrative and maintenance responsibilities to AWS. It is a managed database service that supports multiple popular database engines. When RDS was launched back in October 2009, it initially supported only MySQL, but over the years, support has expanded to include SQL Server, Oracle Database, PostgreSQL, and MariaDB. ### **What are the benefits of using Amazon RDS?** * **Cost-Effective Yet Secure Storage Option:** Common DBA tasks like hardware provisioning, database setup, patching, and backups are automated, making database management easier. RDS also supports SSL/TLS-encrypted connections and offers Amazon Virtual Private Cloud (VPC) integration for enhanced security. * **Scalable Resources:** Amazon RDS is one of those AWS-managed databases that allows for vertical scaling, both manually and automatically. For automatic scaling, predefined metrics and thresholds must be configured. Additionally, RDS supports read replicas, which improve read performance and help distribute workloads efficiently. * **Support for Multi-AZ Deployment:** To ensure high availability and automatic failover, Amazon RDS supports Multi-AZ deployments across all supported database engines, offering built-in redundancy and fault tolerance. * **Integration with Amazon CloudWatch:** By integrating with Amazon CloudWatch, administrators gain detailed visibility into performance metrics and the overall health of the system, enabling proactive monitoring and management. ### **What are the major drawbacks of Amazon RDS?** * **Limited Flexibility:** For workloads such as custom backup scripting or deep performance tuning, it is recommended to avoid using AWS RDS, as users do not have root access to the database servers. To compound the problem further, you cannot save on licensing costs since AWS forces you to buy licenses through the Marketplace. * **Single Point of System Failure:** Out of all AWS managed databases, when RDS is deployed in a single AZ instance, the chance of SPOF — stretching to 30 minutes or in some cases longer— becomes significant. Thus, it is best practice always to use RDS in a Multi-AZ configuration. * **Limited Scalability:** RDS nodes do not support horizontal scaling through sharding (only through read replicas) and also have limitations with read replicas (e.g., a maximum of 5 for MySQL); therefore, it is only suitable for non-complicated or low-performance workloads. * **Manual Networking and Security Responsibility:** While AWS secures the infrastructure, users are responsible for the correct configuration of VPC, security groups, and database-level authentication and authorization. ## **What is Amazon Aurora?** Amazon Aurora is one of the database engines available under Amazon RDS. Think of it as a turbocharged version of MySQL and PostgreSQL — built by AWS to address the performance and scalability issues that traditional databases sometimes struggle with. It’s fully managed, but still feels familiar if you’ve worked with MySQL or Postgres before. ### **Advantages of using Amazon Aurora** * **Faster than traditional RDS** Aurora can be up to 5x faster than standard MySQL and 3x faster than standard PostgreSQL — without you doing much. * **Built for high availability** Your data is automatically replicated across multiple Availability Zones. Failovers typically occur within 30 seconds. * **Storage grows with you** You don’t have to provision storage upfront. Aurora automatically scales from 10 GB to 128 TB as your data grows. * **Managed by AWS** You don’t need to worry about backups, patching, or maintenance — Aurora handles all of that in the background. * **Easy to switch to** Since it’s MySQL- and PostgreSQL-compatible, most apps can switch to Aurora without major code changes. ### **Drawbacks of using Amazon Aurora** * **Expensive** It’s faster, yes — but also pricier. For small or dev workloads, the cost might not be worth it. * **Tied to AWS** Aurora is AWS-specific. So, if you ever want to move off AWS, migrating out won’t be simple. * **Not everywhere** Aurora isn’t available in every AWS region. It could be a problem if you need a specific location. * **Less control** Since it’s fully managed, you can’t fine-tune everything like you could with a self-managed database. * **Migration isn't always smooth** Even though it's “compatible,” heavily customized or large databases may still hit snags during migration. ## **The Dilemma Organizations Face When Choosing Between Amazon RDS and Amazon Aurora** When teams weigh Amazon RDS vs Aurora, the decision often comes down to balancing performance with cost. RDS offers dependable, fully managed support for multiple database engines, making it a solid choice for typical workloads where simplicity and cost control matter. Aurora steps in when high-performance, low-latency reads and built-in high availability are critical. With its distributed storage and faster failover, it's built for more demanding applications, but with a higher price tag and a deeper tie-in to AWS infrastructure. ### **Amazon RDS vs Amazon Aurora: A Holistic Comparison** ## **Amazon RDS vs Amazon Aurora Cost Comparison** When comparing AWS databases with all parameters kept static, Amazon Aurora proves to be more expensive than Amazon RDS. For example, if you're running a service that requires an upper threshold of compute and memory, say, using a db.r6g.4xlarge instance — it might cost around $1.24/hour on Amazon RDS (for PostgreSQL). In contrast, the same configuration on Amazon Aurora PostgreSQL-Compatible Edition could cost about $1.52/hour, not including additional charges for I/O and storage that Aurora bills separately. However, considering the somewhat limited performance capabilities of RDS, it becomes important to use Aurora for intense workloads. If your application demands extra power and experiences an outage or performance degradation, the resulting downtime could cost much more than the savings you made by choosing RDS over Aurora. Thus, there is no direct Amazon RDS vs Aurora comparison per se, but each has its use case. ## **Ideal Use Case for Amazon Aurora** Where low latency and resilience against traffic spikes are paramount, Amazon Aurora becomes the go-to database out of all AWS-managed databases, especially for applications like SaaS platforms and e-commerce websites that handle hundreds of thousands of read-write operations simultaneously. Its ability to autoscale storage, replicate across **Example scenario:** During a Black Friday sale, an e-commerce app running on Amazon RDS MySQL hits IOPS limits and suffers degraded performance. With Amazon Aurora, read replicas handle traffic spikes, and failover to a standby happens in under 30 seconds. Aurora’s autoscaling storage and multi-AZ replication keep the application responsive and resilient. ## **Ideal Use Case for Amazon RDS** While Amazon RDS can support It works best for applications with steady, predictable usage — things like long-running internal tools, backend systems, or budget-sensitive apps running on t3.micro or similar instances. The key here is moderate performance, predictable workload, and a strong focus on cost control over peak resilience. **Example scenario:** A startup runs an internal customer support ticketing system with a stable, low-variance workload throughout the day. Deploying it on Amazon RDS PostgreSQL with a t3.medium instance and gp2 storage is sufficient to meet performance needs at minimal cost. Running the same on Amazon Aurora PostgreSQL would inflate costs due to per-I/O billing and reserved replica overhead, without any tangible performance gains for this use case. ## **Best Practices for Amazon RDS Cost Optimization** It requires a deliberate strategy across storage, compute, backups, and monitoring — all aligned to workload patterns. While RDS offers built-in automation, cost overruns still happen when configurations aren’t fine-tuned. Whether you’re running production-grade databases or dev/test environments, following * **Right-Size Your Instances:** Regularly analyze CPU, memory, and disk I/O metrics using CloudWatch to downsize oversized DB instances. Don’t pay for unused capacity. * **Use Reserved Instances or Savings Plans :** For steady workloads, switch from * **Enable Storage Auto-Scaling — but Monitor It :** Let RDS auto-scale storage to avoid performance bottlenecks, but set alerts to avoid silent cost creep. * **Switch to Burstable Instances (T-Series) for Dev/Test:** For non-production workloads, db.t3 or db.t4g instances are cost-effective with baseline performance and CPU credits. * **Use General Purpose (gp3) Storage :** gp3 is cheaper than gp2 and allows independent tuning of IOPS and throughput — ideal for most workloads. * **Turn On Multi-AZ Only Where Needed:** Multi-AZ doubles compute cost. Use it only for production or high-availability workloads — not dev or staging. * **Leverage Read Replicas Strategically:** Offload read-heavy traffic to cheaper replica instances. For low-volume reads, avoid unnecessary replicas. * **Delete Unused Snapshots and Idle Instances:** Snapshots beyond retention and idle databases sitting in dev environments add a silent recurring cost — clean them up regularly. * **Tune Connection Pooling and Query Efficiency:** Inefficient queries and long-lived connections increase resource use. Use RDS Performance Insights and connection pooling (e.g., PgBouncer for PostgreSQL). * **Consolidate Underutilized Databases:** Multiple underused RDS instances can often be merged into a single instance or clustered environment to reduce overhead. ## **Best Practices for Amazon Aurora Cost Optimization** Amazon Aurora delivers unmatched performance, but without smart optimization, costs can spiral fast. Here’s how to maximize efficiency without sacrificing speed or reliability. ### **1) Use Commitment-Based Discount Programs** The RI programs offer up to 72% discounts on On-Demand pricing for select configurations, such as geographic regions, instance classes, and commitment terms. ### **2) Implement Rules for Storage Scalability** The hallmark feature of Amazon Aurora is that it scales automatically according to the workload. However, engineers often fail to put in place scaling-limiting mechanisms (e.g., CloudWatch alarms or AWS Budgets) and notifications, which, as a result, can lead to cost overruns. ### **3) Clear Out Old Data** To prevent storage from scaling exponentially, enable data compression and regularly clear out old logs. Many old and unused data points, such as dropped tables, partitions, databases, logs, and snapshots, can accumulate significant gigabytes of storage over time. Thus, it is important to clear out data, or if it needs to be retained, move such static data to #### **Top 5 Data Points to Clear** 1. **Old Database Snapshots** Manual or outdated automated snapshots retained beyond required retention periods can silently consume hundreds of GBs. 2. **Expired Table Partitions** Time-series or partitioned tables often accumulate old partitions that no longer serve business or reporting needs. 3. **Audit Logs and General Logs** Continuous logging (e.g., with aurora_enable_audit_log) without rotation leads to large volumes of uncompressed logs. 4. **Orphaned Temporary Tables** Leftover temp tables from aborted sessions or long-running queries can persist and consume space if not properly cleaned up. 5. **Dropped Tables and Unused Schemas** Even dropped tables can leave traces in snapshots or backups; unused schemas should also be cleaned to avoid storage waste. ### **4) Enhance Cloud Cost Visibility** Cloud cost visibility is key to cost optimization of your Aurora DB cluster. Note: In your DB instance, for the tools to access the cluster’s performance, **Performance Insights** must be turned on. Select the Instance Category That Aligns With Your Workload Instances under AWS Aurora can be categorized into two broad categories: Provisioned and Serverless v2. Provisioned Instances offered by AWS Aurora are as follows: Serverless Instances v2 offered under AWS Aurora are as follows: Also, within the same Aurora cluster, it is possible to use Serverless v2 instances alongside Provisioned instances. **Burstable Instances:** If you’re still unsure about your workload and want to gauge it in a development and testing environment, burstable instances can be a good choice. (Feature of Burstable Instance: They come with CPU credits, allowing short bursts of performance above baseline at no additional hourly charge.) ### **5) Utilize Aurora Read Replicas** Read Replicas help in optimizing read operations by shifting resource-intensive read queries to other instances, thus reducing the load on the primary instance and trimming overall costs. Aurora Global Databases, while an add-on over the standard instance, offer reduced latency, which can help offset the additional cost in globally distributed applications. ### **6) Optimize I/O Costs** Each read and write operation on AWS Aurora incurs charges; thus, all database interactions need to be optimized. Here’s how you can optimize your I/O: #### **a) Schema and Query Optimization** * Normalize to reduce redundancy, denormalize where needed to cut JOIN overhead. * Use minimal data types to save space and I/O. * Index only on frequently queried columns (WHERE, JOIN, ORDER BY). * Avoid SELECT *, use EXPLAIN to tune queries. #### **b) Batch and Bulk Operations** * Batch INSERT/UPDATE/DELETE in single transactions. * Use LOAD DATA for bulk imports instead of row-by-row inserts. #### **c) Caching and Read Replicas** * Use ElastiCache (Redis/Memcached) to offload frequent reads. * Shift read-heavy traffic to Aurora read replicas. #### **d) Connection and Transaction Management** * Keep connections and transactions short-lived. * Commit quickly to reduce locks and disk writes. #### **e) Monitoring and Tuning** * Monitor IOPS and latency with CloudWatch and Performance Insights. * Tune buffer pool and cache size to push more ops in-memory. #### **f) Application-Level Optimization** * Reduce write frequency — aggregate data before DB hits. * Use idempotency to avoid redundant writes. #### g) Data Lifecycle and Archiving * Archive cold data to S3; keep the active dataset lean. * Purge stale records regularly. ### **h) Aurora-Specific Features** * Use Aurora Serverless v2 for spiky workloads with auto-scaling. * Use Aurora Global Database to route reads locally, cut cross-region latency, and I/O. While setting up your Aurora Cluster, it is essential to ensure that cost optimization practices don’t impede availability. If they do, the savings benefit would be offset by the business loss resulting from downtime. Our blog on ensuring ## **Major Industry Applications of These Two Databases** When it comes to Amazon RDS vs Aurora, it’s not a matter of one replacing the other. Both databases serve very different purposes, based on how demanding the workload is in terms of performance, scalability, and availability. It’s common for organizations to run both RDS and Aurora together in the same environment, depending on what each workload needs. ### **Amazon RDS in the Industry** Amazon RDS runs stable, business-critical workloads across industries like banking, fintech, and gaming, where the focus is on reliability, compliance, and predictable performance. **Airbnb:** Airbnb moved from a self-managed MySQL setup to Amazon RDS for MySQL with Multi-AZ deployment on db.m5.large instances. The switch simplified scaling and replication using just an API call or AWS Console, compared to the manual setup earlier. They rely on Multi-AZ to keep things highly available and durable without manual failover handling. ### **Amazon Aurora in the Industry** Aurora is built for scale. When you need low latency, high throughput, and the ability to handle unpredictable or spiky workloads, Aurora delivers — especially for real-time, global systems. **DoorDash:** Runs a single Aurora MySQL-Compatible cluster on db.r6g.8xlarge instances to manage over 800,000 daily deliveries. That’s almost 10 TB of active data, handled with Aurora’s distributed storage and consistent performance, even under heavy traffic. **The Pokémon Company:** Migrated the Pokémon Trainer Club system from standard PostgreSQL to Aurora PostgreSQL-Compatible using db.r6g.large instances. The result: downtime dropped from 168 hours to under 1 hour over six months, thanks to Aurora’s fast failovers and built-in automation. **Best Western Hotels:** Uses Aurora with db.r6g.4xlarge and higher to run its reservation system, processing 2.3 billion availability messages in just 60 seconds. Read replicas are used to handle query loads and keep things responsive even at massive scale. ## Conclusion Ultimately, the decision hinges on your workload requirements. RDS offers stability and ease of use, while Aurora provides unmatched power for demanding environments. Assess your needs carefully—choosing the right database can mean the difference between smooth operations and costly inefficiencies. ## **Frequently Asked Questions (FAQs)** * **Q1.What are the features unique to Amazon RDS?** Amazon RDS offers multi-engine support (MySQL, PostgreSQL, etc.), simpler setup, and predictable pricing, making it ideal for traditional workloads. Unlike Aurora, it lacks auto-scaling storage and global database clusters. For AWS-managed databases, RDS balances ease and cost in the AWS database comparison. * **Q2.What are the features unique to Amazon Aurora?** Amazon Aurora provides 5x MySQL/PostgreSQL performance, auto-scaling storage, and low-latency global replication. Its serverless option and faster failovers outperform RDS in the RDS vs Aurora cost comparison for high-scale apps. * **Q3.Can I use Amazon RDS and Amazon Aurora together?** Yes! Many enterprises run both RDS and Aurora—using RDS for legacy apps and Aurora for high-performance needs. This hybrid approach optimizes AWS-managed databases' costs and performance in Amazon RDS vs Aurora setups. * **Q4.What are the advantages & disadvantages of Amazon Aurora?** **Pros:** Faster, auto-scaling, global-ready. **Cons:** Higher costs if not optimized, vendor lock-in. In the AWS database comparison, Aurora wins for scale but may be overkill for simple workloads. * **Q5.What are the advantages & disadvantages of Amazon RDS?** **Pros:** Cost-effective, easy to manage, broad engine support. **Cons:** Limited scalability, slower replication. For a cost comparison between RDS and Aurora, RDS is better suited for budget-conscious, low-traffic use cases. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 11 11 Table of Contents Amazon Simple Storage Service (Amazon S3) is a web-based cloud storage solution that is scalable, fast, and inexpensive. It is designed for archiving and backing up data on Amazon Web Services (AWS) online. In order to make web-scale computing easier for developers, Amazon S3 was designed with a minimum feature set. The Amazon S3 cloud storage service consists of object storage, unlike traditional file storage and block storage. Each object is stored as a file with its metadata included. An ID number is also associated with them for applications to access the right object. Using Amazon's S3, a subscriber has access to the same cloud storage systems used by Amazon. The vast majority of files and objects can be uploaded, stored, and downloaded via S3, but the largest single upload is capped at 5 gigabytes (GB). ## **Cost Optimization using S3** The cost-optimization metrics of S3 Storage Lens can help you * Buckets with incomplete multipart uploads older than 7 days * Buckets that are accumulating numerous noncurrent versions * Buckets that don't have lifecycle rules to abort incomplete multipart uploads * Buckets that don't have lifecycle rules to expire noncurrent versions objects * Buckets that don't have lifecycle rules to transition objects to a different storage class ## **Four Pillars of AWS Storage Cost Optimization with Amazon S3** ### **Pillar 1: Defining application requirements** The performance and data access requirements of your applications and workloads should be understood before moving workloads to Amazon Web Services. The needs of backup and archive applications are dramatically different from those of streaming media applications or e-commerce sites. Identifying how and when your data is acquired, accessed, and archived or deleted is important for cloud cost optimization. ### **Pillar 2: Data organization** In order to ### **Pillar 3: Choosing the right Amazon S3 Storage class** There are a number of Amazon S3 storage classes that are designed for different use cases, and each of these classes can be used for different data access levels at different rates. An important component of any AWS cost optimization strategy is choosing the right storage class. As a result, you can build highly scalable applications that are cost-effectively scalable for virtually any use case. S3 Lifecycle policies can be used to transition data between storage classes, or S3 Intelligent-Tiering can automate data movement and cost savings. ### **Pillar 4: Monitor, analyze, and optimize** * **Monitor:** By monitoring your usage, you can lower the S3 storage costs and manage the costs over time. By setting custom budgets, you can be alerted when your costs or usage exceed (or are forecast to exceed) your budget. Monitoring your storage and request activity growth can also be done with AWS tools like CloudWatch or third party tools like * **Analyze:** It is important to understand your data access patterns in order to determine the best S3 Storage Class. By analyzing your prior storage access patterns, you will be able to choose the best S3 Storage Class for your data based on those insights and lower your AWS storage costs. * **Optimize:** A S3 Lifecycle Policy enables you to ensure that your objects are stored in the most cost-effective S3 Storage Class throughout their lifetime. Configuring a lifecycle configuration determines whether objects in Amazon S3 will be moved into a colder storage class (e.g. Glacier) or automatically deleted after they are no longer required. ## **S3 Storage Classes** To optimize the storage costs for your data, Amazon Web Services (AWS) offers several storage classes. Below is a brief overview of the main storage classes of Amazon S3: * **S3 Standard:** For frequently accessed data, S3 Standard is an ideal solution. It charges for storage, data transfer, and requests, but the pricing is competitive compared to other cloud storage services. As a result, it offers high durability, availability, and performance; it is particularly suitable for data storage that requires low latency and high throughput. * **S3 Intelligent-Tiering:** Using S3 Intelligent-Tiering, users can store data with unknown or changing access patterns with cost-effectiveness. Compared with other cloud storage services, the pricing is competitive in terms of storage, * **S3 Standard-Infrequent Access (S3 Standard-IA):** Compared to S3 Standard, S3 Standard-IA offers lower storage costs, making it a cost-effective storage solution for less frequently accessed data. Among S3 Standard-IA storage classes, Standard-IA is ideal for storing data with low access frequency but high durability and availability requirements. This is one of the most effective methods for cloud cost optimization within AWS storage classes. * **S3 One Zone-Infrequent Access (S3 One Zone-IA):** Compared to S3 Standard-IA, S3 One Zone-IA offers a cheaper storage price since data is stored within a single availability zone instead of multiple zones within a region. Whenever a failure of an availability zone may result in a temporary loss of access to data, S3 One Zone-IA provides a great solution. It's ideally suited for data that can be easily recreated or for non-critical data that can tolerate a temporary loss of access. Along with providing a lower AWS storage cost, it also provides high durability and availability within a single availability zone. * **S3 Glacier:** It charges a very less storage price among all the Amazon S3 storage classes, but it is more expensive than Amazon S3 Glacier Deep Archive. For data that needs to be retained for long periods of time but is rarely accessed, S3 Glacier is the ideal storage class for long-term archiving. In addition to helping in AWS cost optimization, it also provides multiple retrieval options and maintains high reliability and durability. * **S3 Glacier Deep Archive:** The lowest S3 storage cost is offered by S3 Glacier Deep Archive in comparison to all other storage classes in Amazon S3. For data that rarely needs access and needs to be stored for a long period of time, such as regulatory compliance or digital preservation archives, S3 Glacier Deep Archive is an ideal storage solution. Despite its cost-effectiveness, it maintains high durability while offering infrequent access options and offers high durability. ## **Comparison Chart** Here is a comparison chart for each storage class of S3 and how much you can save with each of these classes: S3 Standard, the default storage class, is assumed as the baseline for each storage class in the above comparison chart. Data access patterns and storage classes influence the percentage of cost savings. ## **Conclusion** The S3 storage cost is an important consideration for any AWS user.It is possible to save significant AWS storage costs by understanding the different storage classes S3 offers, and then selecting the appropriate storage class based on access patterns and requirements for your data. The bottom line is that, _Did you know that CloudKeeper AZ can help you_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents AWS S3 (Simple Storage Service) is a highly scalable and cost-effective storage solution offered by Amazon Web Services (AWS). AWS S3 is implemented for storing or retrieving any quantity of data from anywhere in the world, and it offers a range of storage classes to suit different data access patterns and performance requirements. However, as with any cloud service, the cost of using S3 can add up quickly if not managed carefully. Through this blog, we will go through some of the widely used best practices for using Below are the multiple elements that influence the total expense of utilizing the service, and then optimize it: 1. Storage size 2. Storage class 3. Requests 4. Data transfer 5. Additional features Lets deep dive into this - **1. Storage size** : AWS S3 charges based on the amount of data stored in the service. Storage cost is dependent upon the amount of data stored and the storage class used. **2. Storage class** : AWS S3 offers different storage classes with varying costs. The standard storage class is the most expensive, while infrequent access and archive storage classes are cheaper. **3. Requests** : AWS S3 charges for requests made to the service, including GET, PUT, COPY, and LIST requests. The pricing for requests varies depending on the storage class used. **4. Data transfer** : AWS S3 charges for data transferred in and out of the service. The quantity of data transmitted and the endpoint location(destination) are determining factors. **5. Additional features** : AWS S3 offers additional features such as data management, monitoring, and analytics that may have additional costs associated with them. ## **Best Practices** ### ### **1. S3 Lifecycle policies** S3 Lifecycle policies allow you to automate the transition of objects between storage classes or expiration of no longer needed objects. Example, you can configure a rule which moves objects to cheaper storage classes like S3 Infrequent Access (IA) or S3 Glacier after a certain period of time, or delete them after a certain number of days. By using lifecycle policies, you can ensure that you only pay for the storage you need and not storing data that is no longer necessary. ### **2. S3 setup** Always remember, to set up your S3 bucket in the same region where your infrastructure is set up. Setting up an Amazon S3 bucket in the same region as your other AWS resources can help save money in several ways: **1. Reduced data transfer costs** : When you transfer data between S3 and other AWS services in the same region, the data transfer costs are generally lower than transferring data across different regions. For example, if you transfer data from an EC2 instance to an S3 bucket in the same region, you will incur no data transfer charges. This can help you in major cost savings, especially if you are transferring large amounts of data. **2. Reduced request costs** : When you make requests to an AWS S3 bucket, you are typically charged for each request. However, if the bucket is located in the same region as your other AWS resources, the request costs are usually lower than if the bucket is located in a different region. This is because requests made within the same region incur lower charges than those made across different regions. **3. Reduced storage costs** : S3 storage costs vary depending on the region in which the bucket is located. However, in general, S3 storage costs tend to be lower in regions where there is high competition and demand. By setting up your S3 bucket in a region where storage costs are lower, you can **3. S3 versioning** AWS recommends enabling S3 versioning, but enabling versioning is free, but use versioning comes at a cost. Using AWS S3 versioning can actually increase storage costs, as it stores every version of an object. However, it can also help you avoid data loss and potential data corruption, as you can recover previous versions of objects that have been accidentally deleted or overwritten. Disabling S3 versioning can help you save money on storage costs, as it will prevent every version of an object from being stored. However, it's important to understand that disabling versioning also means that you will lose the ability to recover previous versions of objects that might have been unintentionally removed or replaced. ### **4. S3 Object Tagging** AWS S3 Object Tagging allows you to categorize objects using tags, which can help you identify and manage objects based on their purpose or other attributes. You can use these tags to create lifecycle policies to move objects to cheaper storage classes or delete them after a certain period of time. For example, you could tag objects that are no longer needed as "expired" and set a lifecycle policy to delete all objects with that tag after 30 days. ### **5. S3 Storage Class Analysis** AWS S3 Storage Class Analysis provides you with ### **6. S3 Intelligent-Tiering** AWS S3 Intelligent-Tiering automatically moves objects between two access tiers (frequent and infrequent) based on changing access patterns. This can help you save costs by automatically moving objects that are not frequently accessed to cheaper storage classes like S3 IA or S3 Glacier. With the help of this feature, you can ensure that you are only paying for the storage you need and not storing data that is no longer necessary. ### **7. S3 Select and S3 Glacier Select** AWS S3 Select and S3 Glacier Select allow you to fetch the amount of data you require from objects stored in S3 or S3 Glacier, rather than retrieving the entire object. This can help you save costs by reducing the amount of data you need to transfer and store. By using these features, you can ### **8. S3 Transfer Acceleration** This feature helps you leverage Amazon CloudFront's globally distributed Edge locations for faster uploads to AWS S3. This also helps you reduce data transfer costs. It also ensures that you are only paying for the data transfer you need and avoid unnecessary costs. ### **9. S3 Requester Pays** AWS S3 Requester Pays allows you to require that requesters of your objects pay for the data transfer costs associated with accessing your objects. This can help you save costs by shifting the data transfer costs to the requester. S3 Requester Pays also ensure that you are only paying for the data transfer you need and not incurring unnecessary costs. ## **Conclusion** AWS S3 is a powerful cloud storage solution which helps you store the data securely, safely and efficiently. However, storing data in S3 can be expensive, when you are considering the costs associated with data storage, data transfer, and other associated fees. By implementing these best practices mentioned over this blog post, you can optimize your use of AWS S3 and save money on your storage costs. Whether you have a small business or a large enterprise, these tips can help you reduce your AWS S3 costs and make the most of your cloud storage solution. __ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents Cloud support has become one of the most critical enablers of cloud success. In the beginning, support meant little more than raising a ticket when something broke. But as businesses started running entire platforms, SaaS products, and mission-critical workloads on the cloud, expectations shifted. Companies no longer just want issues fixed - they want guidance, optimization, and assurance that their cloud is always working at its best. AWS has been at the forefront of this shift. Recognizing that different businesses require varying levels of support, it has developed a tiered model - ranging from Developer Support for teams experimenting with AWS, to Enterprise Support, which provides dedicated account managers, proactive planning, and rapid response for global, always-on environments. This structured approach has helped thousands of organizations scale with confidence, but it has also sparked a new conversation: are AWS’s native support plans the only option, or can partner-led models deliver the same - and sometimes better - value? To unpack this further, we turn to today’s guest expert. ## Today’s Featured Expert: In this edition of Ask the Cloud Expert, we speak with **Neeraj Gupta** _, Senior Director of Customer Success & DevOps at CloudKeeper_ and a seasoned FinOps leader. With over a decade of experience in enterprise Drawing on his extensive experience, Neeraj will help us understand the two models - their pros and cons, and what businesses should consider before making a decision. ## Part 1: Understanding the Two Models(AWS Enterprise Support & CloudKeeper's PLS) **Q: Neeraj, let’s start with the basics. How would you describe AWS Enterprise Support and CloudKeeper’s Partner-Led Support?** **Neeraj:** Think of AWS Enterprise Support as the gold standard of what AWS itself offers. It’s designed for organizations running mission-critical workloads, where downtime or inefficiency could mean millions in losses. You get On the other side, So at the highest level: AWS Enterprise Support is comprehensive but expensive. CloudKeeper PLS matches most of its benefits, adds more contextual services, and does so at a better cost. ## Part 2: The Limitations of AWS Enterprise Support **Q: AWS Enterprise Support offers a wide range of services, but in what scenarios might enterprises need additional guidance or a more tailored support approach?** **Neeraj:** AWS Enterprise Support pricing is tiered – often more than 10% of your monthly AWS bill. For organizations with large-scale usage, that can mean hundreds of thousands of dollars annually. Considering such a significant investment, enterprises naturally expect highly proactive support. However, while customers receive prompt responses and resolutions, the engagement could often feel reactive - you raise a ticket, they help you resolve it - but guidance on Another limitation is scope. Enterprise Support is largely focused on AWS infrastructure. If your challenge involves an application layer dependency or a third-party software integration, you may find the guidance limited. Businesses with smaller in-house teams often struggle because what they need is a strategic advisor for So, the limitations boil down to three things: high cost, limited personalization, and gaps beyond infrastructure-level support - although, these could very well be caused by the huge volume of tickets the AWS teams need to manage. ## Part 3: Why CloudKeeper's Partner-Led Support is Gaining Ground **Q: So how does CloudKeeper PLS address these gaps? Why are businesses choosing it?** **Neeraj:** The short answer is: value and flexibility. With PLS, you’re not just buying a support plan, but partnering with a team that becomes an extension of your own cloud function. The SLAs match Another reason PLS is gaining traction is contextualization. We don’t just tell you, “Here’s the AWS best practice.” We sit with your engineers, understand your environment, and tailor the guidance. In some cases, that might mean In short, businesses are realizing they can get all the enterprise-grade reliability plus a lot more personalization and optimization - without the sticker shock. ## Part 4: CloudKeeper PLS - A Smarter Support Model **Q: Can you explain what makes PLS smarter than traditional models?** **Neeraj:** Absolutely. I’d highlight five things. First, breadth of coverage. PLS isn’t limited to AWS infrastructure. It extends to devops tools, applications, third-party tools, and even modernization. That means fewer silos and fewer missed opportunities. Second, proactive optimization. AWS Enterprise Support does reviews, but PLS actively Third, personalization. Every business is different and has varying cloud needs. PLS is flexible and customized to your environment, your team’s maturity, and your growth goals. Fourth, end-to-end enablement. Along with solving today’s issues, we prepare you for tomorrow’s challenges. Whether it’s adopting a new AWS service, Fifth, cost-effectiveness. Enterprise Support comes with a premium price tag, often running into six figures annually. PLS delivers the same enterprise-grade benefits - sometimes more - at a fraction of that cost, thanks to our ## Part 5: Real-World Value with CloudKeeper PLS **Q: Can you share an example of a business that benefited from PLS?** **Neeraj:** Absolutely. A great example is Franconnect, a leading franchise management platform serving over 1500 brands worldwide. Franconnect relied heavily on Amazon SQS for messaging and workflow but faced recurring operational challenges. The team was facing challenges with configuration consistency, recurring troubleshooting needs, and a dependency on external support. On top of that, an upgrade to MSK clusters carried risks of downtime and stability issues. Here’s where CloudKeeper stepped in with the Partner-led Enterprise Support. We conducted a tailored AWS SQS training program for the Engineering Team, empowering them to manage incidents independently. We also executed a The results were transformative: * Zero SQS-related support tickets after training * Self-sufficiency within the engineering team * Flawless MSK upgrade with no post-incident issues * Faster delivery pipelines and reduced operational overhead This is the power of PLS in action - enabling teams to grow stronger, leaner, and more resilient. ## Final Verdict – Which Should You Choose? **Q: If a business is deciding between AWS Enterprise Support and PLS, how should they approach it?** **Neeraj:** It comes down to priorities. If your organization values access to AWS’s unique perks - like access to training, gamified learning challenges, or certain AWS-only tools - then On the other hand, if your priority is cost-effectiveness, personalization, application-level guidance, and continuous optimization, then My advice: evaluate your needs honestly. If you truly need the extras that only AWS can provide, go for Enterprise Support. But if you want the same SLAs, deeper engagement, proactive savings, and a ## Top-tier AWS Support at a Fraction of the Cost Cloud support is no longer optional. For enterprises running critical workloads on AWS, having expert support can mean the difference between a resilient, optimized cloud and one that bleeds money or risks downtime. AWS Enterprise Support remains the most comprehensive option directly from AWS, but its high costs and limited personalization leave many businesses underserved. CloudKeeper’s Partner-Led Support offers a compelling alternative: all the enterprise-grade benefits, plus more coverage, proactive optimization, and CloudKeeper combines AWS-level reliability with the flexibility and cost-effectiveness of a partner model. Backed by 150+ certified AWS experts, proactive monitoring, and exclusive platforms like CloudKeeper Tuner and Lens, PLS ensures your cloud journey is smarter, faster, and leaner. Ready to explore a better model AWS Enterprise Support? Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Taking your infrastructure to the cloud brings significant benefits - the most important being access to a mature ecosystem that ensures security, high availability, and uptime, along with freedom from the hassles of maintaining on-premises hardware. While these advantages make the cloud an attractive proposition, instances of bill shock running into millions of dollars remain a major cause for apprehension. That’s why we at CloudKeeper bring you the series "**Ask the Cloud Expert** ," where we cover all aspects of cloud infrastructure - from the most common queries to niche issues that typically arise only in the later stages of cloud adoption. And today, it's: **Ask the Cloud Expert: A Deep Dive into AWS WAR**. ## **Today’s featured expert: Aditya Ajay** ## **Why Does AWS WAR Matter?** The fundamental performance issues in organizations’ software — whether it's a B2B SaaS product or a consumer-facing app — are often a result of an incorrectly configured AWS infrastructure. As companies scale and continue provisioning services on top of this flawed setup, they end up with an inefficient infrastructure, both in terms of performance and cost. That’s where the **Question 1) We’ve all read the official documentation and definitions of the AWS Well-Architected Review. Can you simplify the Well-Architected Review for us?** The AWS Well-Architected Review is a thorough analysis conducted by an expert team of cloud experts of the organization's AWS infrastructure, with the AWS Well-Architected Framework as its foundation. Think of it as the architectural blueprint created by seasoned AWS specialists. The specialists at AWS work with many customers daily, helping them with architectural trade-offs as their designs evolve. While the AWS Well-Architected Framework states the best practices, AWS Well-Architected Review(AWS WAR) is a systematic process of assessing your existing AWS infrastructure against those best practices. The primary objective of the review is to identify gaps in the infrastructure, including financial cost optimization, missed opportunities, security loopholes, and ways to enhance the infrastructure’s resilience against usage fluctuations. All in all, it can be said that a Well-Architected Review is a holistic checkup of your AWS cloud infrastructure. **Question 2) What are the foundational pillars and key components of the AWS Well-Architected Framework?** Sure, I’ll walk you through each of the six foundational pillars, which act as key components of the AWS Well-Architected Framework: * **Operational Excellence:** Focuses on efficient processes and automation to improve performance and reduce manual effort. * **Security:** Ensures data protection, identity management, and strict access controls. * **Reliability:** Enhances fault tolerance and enables quick recovery from failures. * **Performance Efficiency:** Helps in selecting and configuring the right resources for optimal performance. * **Cost Optimization:** Identifies and eliminates unnecessary expenses to reduce wasteful cloud spending. * **Sustainability:** Encourages practices that reduce the environmental impact of your cloud usage. These six pillars form the foundation of the AWS Well-Architected Framework. While the review is tailored to each client’s specific workloads and needs, the evaluation is always rooted in these core principles. **Question 3) Can you walk us through the process of how you conduct an AWS Well-Architected Review?** To perform a comprehensive & customized AWS Well-Architected Review, our team has broken down the entire process into six phases: **Phase 1: Initial Assessment** To gain a deep understanding of the client’s existing AWS infrastructure and organizational practices, we conduct active discussions with key stakeholders. This helps us gather valuable context before diving into architectural analysis. Each AWS WAR done by us is tailored to the organization's maturity, objectives, and capabilities. **Phase 2: Workload Identification** Our AWS-certified experts identify the software and services currently in use. This enables us to provide tailored recommendations — whether around AWS services, instance types, discount programs, or architectural strategies. **Phase 3: Automated Architectural Review** To save valuable bandwidth for your engineering team, we leverage automated assessment process that uses advanced scripting to thoroughly evaluate your cloud infrastructure. This provides us with detailed infrastructure insights, eliminating the need for lengthy questionnaires and constant reliance on engineering input. **Phase 4: Identification of Problem Areas and Opportunities** Armed with both stakeholder input and automated insights, we identify critical issues, inefficiencies, and opportunities for improvement. These findings form the core of our optimization efforts. **Phase 5: Development of a Personalized Roadmap** At CloudKeeper, we understand that a “one-size-fits-all” approach doesn't work in cloud infrastructure. Based on our assessment, we develop a customized, actionable roadmap aligned to your specific business needs and technical goals. **Phase 6: End-to-End Implementation Support** An excellent plan is only valuable if it’s executed properly. We assist with the complete setup, integration, and implementation of recommended changes to ensure your cloud infrastructure is fully optimized. Unlike the competition, CloudKeeper doesn’t stop at just conducting an audit — we partner with clients to transform their AWS infrastructure. No other cloud cost optimization or Well-Architected Review company offers the level of assistance and guidance we provide in simplifying AWS cloud infrastructure. Here’s how we go beyond: * **Actionable Plans:** Clear recommendations for the short, medium, and long term — with a 30-day Assess, 60-day Review, and 60–90 day Implement cycle. * **Proactive Consultations:** Ongoing collaboration with clients to assist not just with review outcomes, but also the implementation and evolution of their roadmap. * **Tailored Guidance:** We reject cookie-cutter solutions. Every recommendation is customized to the client’s unique workloads and goals. * **Modernization Support:** We suggest newer, more cost-effective AWS services where appropriate, replacing legacy tools or services as needed. * **Human-Assisted Anomaly Detection:** To prevent notification fatigue and missed alerts, we offer human-assisted cost anomaly detection in case of sudden cost spikes or overruns. **Question 4) Before proceeding with the AWS Well-Architected Review, what prerequisites do you expect the client to have in place?** While we pride ourselves on handling the majority of the review process, we typically require just three simple preparations from clients to ensure a smooth and effective Well-Architected Review: * A limited read-only IAM role for comprehensive infrastructure analysis * Availability of key stakeholders for a brief kickoff meeting and final review session * Any existing architecture documentation or compliance requirements (if available) * Our automated systems and expert team handle everything else — from workload analysis to dependency mapping — even if resources aren't perfectly tagged or documented. **Question 5) Is the AWS Well-Architected Framework a rigid, standardized process, or can it be adapted based on business needs?** Traditional AWS Well-Architected Reviews can sometimes feel rigid, filled with lengthy questionnaires, broad suggestions, and unclear action steps. This one-size-fits-all approach might leave you with more confusion than clarity, using up valuable time and resources, and often missing the mark on your company’s unique objectives and maturity level. CloudKeeper takes a different & smarter approach. Our AWS Well-Architected Reviews are specifically tailored to your organization’s current capabilities and cloud maturity stage. Here’s what sets our process apart: * **In-depth & automated architectural review:** We combine deep technical analysis with automation to thoroughly evaluate your AWS environment. * **Custom recommendations:** Every suggestion is built around your specific cloud setup and business needs—no generic answers. Structured, actionable roadmap: We deliver clear short-term, medium-term, and long-term strategies so you know exactly what to do next. With CloudKeeper, you get a review that truly aligns with your goals and delivers practical value, not just a checklist. No other AWS WAR partner offers this level of individualized attention and real value. Learn in detail about our **Question 6) In what scenarios within an organization’s operations would you strongly recommend conducting a comprehensive Well-Architected Review of their entire AWS setup?** Three critical moments demand an AWS Well-Architected Review: * **Pre-IPO:** uncover hidden security and compliance gaps that could delay or derail a public listing. * **Post-Migration:** Avoid cost explosions and performance bottlenecks when transitioning infrastructure (one company found 35% savings in unused resources post-move). * **New Product Launch:** Prevent scalability failures by stress-testing the architecture before traffic surges. Each scenario risks major financial or operational blowback without proactive optimization. **Question 7) What infrastructure security concerns are typically addressed by an AWS Well-Architected Review?** An AWS Well-Architected Review identifies and suggests strategies to rectify security flaws, such as open S3 buckets, unencrypted databases, etc., in your infrastructure. These may relate to Identity and Access Management—for instance, restricting access based on roles, limiting privileges for specific business units or individuals, and enabling traceability for all provisioned resources and data movement. The review also emphasizes the automation of critical security checks, significantly reducing the chances of data leaks that could lead to multi-million-dollar losses and serious compliance issues. As a result, one of the key outcomes of an AWS WAR is a stronger alignment with security best practices and improved readiness for compliance adherence. **Question 8) Is the Well-Architected Review strictly an audit, or is it more consultative?** Fundamentally, the AWS Well-Architected Review is more of a conversation than an audit — a point even AWS itself emphasizes. Calling it strictly an audit would only be accurate if the process involved merely analyzing your infrastructure against the Well-Architected Framework and stopping at offering suggestions, leaving the implementation entirely up to the organization. At CloudKeeper, we make the AWS Well-Architected Framework work for SaaS providers, ISVs, and enterprises by extensively customizing it and involving stakeholders throughout the process. The review includes a comprehensive analysis tailored to specific workload requirements and organizational expectations, followed by hands-on assistance in implementing the recommendations. When a review deeply involves stakeholder inputs, customizes its findings, and supports actual implementation, it goes well beyond a typical audit. Therefore, it would be inaccurate to label such a review as merely an audit. **Question 9) Can you share an instance where CloudKeeper’s Well-Architected Review had a significant impact on a client’s cloud infrastructure, whether in terms of security, cost optimization, or performance?** On the security front, we’ve assisted several customers in adopting Amazon CloudFront and AWS Web Application Firewall (WAF), significantly strengthening their security posture and reducing exposure to external threats. From a cost perspective, a notable example is our work with Prodigal. Within the first week of engagement, we conducted a comprehensive review of their infrastructure and helped resolve several operational issues. These fixes not only stabilized their setup but also led to substantial cost savings, bringing their monthly AWS bill down from $60K to under $45K. Additionally, we eliminated frequent downtimes by re-architecting their Airflow workloads, improving fault tolerance, and overall uptime. These are just a few of the many real-world problems we’ve solved for our clients. This is also why a rigid, one-size-fits-all approach to the AWS Well-Architected Review doesn’t work—every workload brings its own set of unique challenges. **Question 10) What should organizations and clients know before getting started with an AWS Well-Architected Review? Will it have any impact on their normal workflow?** While we try to minimize the impact on your workflow through various measures, such as automated architectural review instead of lengthy questionnaires, we must acknowledge that the AWS Well-Architected Review is, at its core, a consultation-driven exercise. This means there will be multiple interactions with your team, whether it's engineers or a designated point of contact, which may take some time away from their regular responsibilities. However, we make every effort to keep this involvement minimal and as efficient as possible. * **Minimal disruption:** When well-managed, a Well-Architected Review shouldn’t disrupt your normal business operations. Most of the process is consultative—interviews, documentation sharing, and review sessions—often scheduled to suit your team’s availability. * **Time commitment:** You can expect a few meetings and some preparation from your technical staff, but day-to-day work continues as usual. * **Improvements, not interruptions:** The goal is to surface actionable opportunities for improvement, not slow you down. Any suggested changes happen after the review and can be planned according to your priorities and timelines. **Question 11) How to Pick the Right AWS Well-Architected Review Partner?** Here are more of the questions for which you’d want a "yes" from your * Do they take the time to understand the current state & company specifics(needs, challenges, desired outcomes, maturity level)? * Is their process simple, efficient, and streamlined? * Are their recommendations customized to your needs? * Do they provide a clear action plan on how to improve your infra? * Will they guide you on the implementation of the action plan? * Are they certified AWS Well-Architected Partners and have enough experience? Does CloudKeeper tick all the boxes? **Question 12) CloudKeeper Offers Free AWS Well-Architected Reviews. Is There a Catch?** A free WAR? You might wonder why. At CloudKeeper, our years of experience in optimizing AWS infrastructure have shown that our expert-led audits—backed by detailed, actionable recommendations—not only deliver tangible results but also build trust. That’s why many **clients choose us as their long-term partner** for optimizing costs and improving the performance of their AWS infrastructure. Thus, helping them extract “more cloud per dollar spent.” ## **CloudKeeper - A Certified AWS WAR Partner** An AWS Premier Partner, with 15+ years of cloud expertise, CloudKeeper stands out as one of the most experienced AWS Well-Architected Partners. CloudKeeper was ranked in the Claim your Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 14 14 Table of Contents Cloud infrastructure forms the backbone of many businesses—whether in the form of SaaS software, internal systems, service delivery, or connectivity—due to its benefits, such as In this edition of “Ask the Cloud Expert”, we discuss the process of negotiating and securing a Private Pricing Agreement (PPA) with AWS. Suppose your organization is facing rising AWS costs and anticipating growth. In that case, this post will guide you through the key considerations before engaging in a PPA and explain how partnering with CloudKeeper can help you maximize its benefits. ## **Today’s featured expert:** Beyond the standard documentation of AWS PPA, Aman Dixit will walk us through what AWS PPA is by sharing real-world learnings and examples he’s gained over his decade-long career, working with clients and supporting them end-to-end—from c So, let’s get started! ### **Q1. What exactly is AWS PPA, and what was the purpose behind AWS introducing it?** Before discussing PPA, it is important to note that it was previously known as the If your organization runs heavily on AWS, a Private Pricing Agreement (PPA) can be a game-changer. Think of it as a personalized contract with AWS, designed for businesses with significant cloud usage. With a PPA, you get exclusive discounts and terms tailored to your consumption patterns—helping you extract more value from every dollar spent. The * What a PPA delivers: locked-in discounts and financial benefits based on your usage. * What it does not deliver: automatic protection against cost spikes. Unpredictable spending can still occur if strong cloud practices aren’t in place, such as: Optimizing instances * Shutting down unused resources * Controlling runaway services In short, an AWS PPA guarantees predictable discounts—not predictable bills. When you combine an AWS PPA with disciplined cloud management—and CloudKeeper’s unique EDP + offerings—you not only secure savings but also gain real financial stability in the cloud. ### **Question 2. You mentioned that AWS EDP is now known as a Private Pricing Agreement. With the name change, has there been any difference in how EDP used to work compared to PPA?** The way AWS EDP and PPA function is essentially the same. AWS EDP and PPA differed slightly in scope: Earlier, EDP covered only cross-service discounts, while PPA includes both cross-service and service-specific discounts. Since the AWS EDP label has been deprecated, all new contracts that were previously called “EDP” now operate as PPAs, eliminating the earlier distinction. In short, AWS EDP as a term is now defunct. ### **Q3. What are the eligibility criteria for a company to qualify for AWS’s EDP/PPA?** AWS PPAs are not for every company. To determine if your business is eligible, you first need to evaluate your cloud spending patterns and growth trajectory. According to AWS, two key criteria define eligibility for a Private Pricing Agreement (PPA): 1. Spend and Growth Trajectory * Businesses that spend $300,000 or more annually on AWS services typically qualify. * AWS also expects a commitment to growth, usually around 20% year-over-year. Companies anticipating expansion of their cloud operations are more likely to benefit from these agreements. 2. Commitment Period * While AWS allows a minimum one-year agreement, committing to three or five years often brings greater cost savings. Additionally, to further strengthen your commitment, software purchases made through AWS Marketplace count toward your overall spending threshold, helping you optimize the agreement. ### **Q4. Can I pair discounts from RIs and Savings Plans with AWS EDP/PPA?** Yes, you can combine them. However, AWS explicitly ### **Q5. SaaS providers and ISVs often have higher cloud usage. How does AWS PPA create value specifically for such companies?** That’s where AWS PPA comes into play. Instead of paying standard rates, you secure a custom contract with predictable discounts tailored to your growth. Here’s how it creates value for SaaS and ISV businesses: 1. **Lower costs at scale** – Unit economics improve as you serve more customers. 2. **Financial predictability** – Locked-in discounts allow your finance team to forecast margins with confidence. 3. **Room to grow** – Agreements flex with your growth journey, so you don’t risk over-committing too early. 4. **Go-to-market boos** t – Participation in AWS programs opens doors to co-selling opportunities, marketplace incentives, and joint marketing. 5. **Better investor confidence** – Predictable spending and stronger margins inspire investor trust, while customers benefit from savings reinvested into your platform. In short: For SaaS providers and ISVs, AWS PPA isn’t just about cutting costs. It’s about scaling smarter, protecting margins, and growing faster with AWS as your partner. ### **Q6. What are the features of AWS PPA that make some companies hesitant to opt for it?** AWS PPA, while often seen as the go-to choice for organizations with significant cloud spend, is not always adopted by every eligible company. Despite qualifying, many organizations still opt for alternative 1. **Commitment Period** AWS PPA requires a lock-in with AWS for a significant duration, with a minimum period of 1 year, which reduces flexibility. For fast-changing businesses (startups, SaaS scaling companies), the concern is that they might outgrow AWS or want multi-cloud flexibility. 2. **Upfront Negotiation Complexity** Building an AWS PPA “construct” involves analyzing past usage, forecasting future workloads, and negotiating terms with AWS. _Hesitation_**:** Smaller teams or companies without cloud finance expertise find this time-consuming and complex. 3. **Doesn’t Solve Unoptimized Usage:** AWS - PPA guarantees discounts, not cost control. _Hesitation:_ Without good governance (shutting unused resources, rightsizing, etc.), companies can still face surprise bills. Without optimizations, clients can end up in an overcommitted state, resulting in business loss. 4. **Cashflow & Accounting Considerations** Some agreements involve prepayments or specific billing structures. _Hesitation:_ This can affect cash flow, especially for startups/ISVs balancing growth and funding cycles. 5. **Commitment vs. Innovation Uncertainty** If a company shifts workloads to SaaS tools, adopts serverless, or moves to another cloud, AWS usage might shrink. _Hesitation:_ They fear being locked into spending that doesn’t align with future architecture decisions. In short, companies hesitate because AWS PPA trades flexibility for savings. For some, the long-term commitment feels like a bet on their future growth and AWS dependency — and not everyone is ready to place that bet. Common alternatives many companies choose instead are ### **Q7. What should companies keep in mind when negotiating an AWS PPA contract?** When negotiating your PPA contract with AWS, it is crucial to prepare thoroughly by analyzing your infrastructure, forecasting usage, and planning your strategy. Here are the key areas to focus on: 1. **Optimize Your Infrastructure** Before entering contract discussions, ensure your AWS environment is already efficient and optimized for cost savings. Conducting a 2. **Accurate Predictions and Forecasting** Accurate forecasting is central to building a strong negotiation case. Tools such as Understanding your existing environment, predicting expansion needs, and aligning projected growth with AWS expectations will help you negotiate from a position of strength. 3. **Leverage Your AWS Account Managers** Your AWS Account Managers play an important role as intermediaries in the negotiation process. By maintaining a proactive relationship and engaging with them consistently, you gain early visibility into AWS’s priorities and potential discount opportunities. Building this relationship over time makes it easier to secure favorable terms when formal negotiations begin. 4. **Engage with an AWS Partner (like CloudKeeper)** While AWS offers direct PPAs, working with a partner can deliver additional advantages. 5. **Leverage AWS Marketplace** Purchases made through the AWS Marketplace count toward your committed spend, which often makes it easier to reach required thresholds. With CloudKeeper’s partnership network, organizations can further optimize this route to strengthen their agreement. 6. **Choose the Right Enterprise Support Model** When entering a Private Pricing Agreement, AWS Enterprise Support is mandatory. However, 7. **Consolidate Accounts for Bigger Discounts** The biggest driver of AWS PPA benefits is the size of the committed spend. Larger commitments consistently result in deeper discounts. If your organization operates multiple AWS accounts across subsidiaries or business units, consolidating billing under one account can significantly increase your negotiating leverage and unlock higher savings. ### **Q8. Once an organization has entered into an AWS Private Pricing Agreement (PPA), what best practices should it follow to ensure maximum value throughout the contract period?** To extract maximum value after signing a PPA, there are two key areas businesses need to focus on: 1. **Implement governance and compliance controls** Once the agreement is in place, it is essential to establish strong governance and compliance measures. AWS PPAs require organizations to closely monitor their spending and ensure it aligns with the agreed terms. CloudKeeper provides tools to track PPA commitments and usage, enabling businesses to stay compliant and avoid potential penalties. 2. **Ongoing optimization and support** Securing a PPA is not a one-time activity but an ongoing process that requires continuous management. CloudKeeper offers ongoing advisory services that help clients track commitments, adjust usage, and identify new opportunities for cost savings over the course of the agreement. ### **Q9. What are the advantages of going with a partner-led approach for negotiating the AWS PPA contract?** Going with a partner-led approach for your AWS PPA contract negotiation is generally considered a safer bet—and recommended. AWS PPA negotiations are highly nuanced, and having a partner with domain expertise and industry know-how can help you Here are the top reasons why going through a partner for AWS PPA contracts is a better choice: * **Informed contract negotiation:** Partners are well-versed in the details of PPA and other AWS discount programs. They know how to leverage usage patterns in negotiations and simplify the fine print, ensuring you secure the most favorable terms. * **Knowledge of pricing models:** Partners bring an in-depth understanding of * **Requirement analysis:** An AWS PPA partner can analyze workloads, infrastructure needs, and anticipated growth. They provide guidance on * **Discounts on Enterprise Support:** Partner-led support often comes at a lower cost compared to * **Benchmarking and negotiation intelligence:** A good partner has visibility into how similar companies structure their AWS PPA contracts. This benchmarking knowledge gives you an edge during negotiations, helping you secure stronger discounts and terms that you might not have been aware of otherwise. ### **Q10. How does CloudKeeper step in for AWS PPA, and what aspects of the program does it manage?** CloudKeeper acts as an end-to-end partner in helping our clients get the best possible deal on their AWS PPA contracts. While it is possible to negotiate directly with AWS, many organizations struggle to access these valuable agreements on their own due to intricate pricing structures and complex requirements. With our unique Here’s how CloudKeeper supports you throughout the process: * **Eligibility assessment** – We evaluate your AWS usage and growth projections to determine whether an AWS PPA is the right strategy for your business. * **Commitment planning** – Once eligibility is confirmed, we partner with you to set commitment levels that maximize discounts without the risk of overspending. * **Usage trend analysis** – Our experts analyze AWS usage patterns to help you lock in realistic commitments while securing the best possible rates. * **Negotiation with AWS** – Leveraging our strong relationship with AWS, we negotiate favorable AWS PPA terms on your behalf, ensuring agreements that balance cost efficiency with your long-term strategic objectives. With CloudKeeper managing the complexity of AWS PPA negotiations, you can stay focused on leveraging AWS for innovation and growth—confident that you are receiving the best possible value from your agreement. Our deep knowledge of AWS pricing models, instance management, and CloudKeeper covers these and many more aspects to strengthen your ## **Key Takeaways** AWS PPA (Previously known as AWS EDP) is a special, customized discounted pricing contract that AWS offers to clients billing more than USD 300k per year. These contracts lock in spend commitments for a minimum period of 1 year. However, there are caveats—such as no more than 25% of the committed spend can come from Marketplace purchases, and discounts received through AWS PPA are excluded from the committed amount. No two AWS PPA contracts are the same, as the terms heavily depend on the size of your bill and your ability to negotiate with AWS. For this reason, a CloudKeeper EDP+ goes beyond the standard program by offering lower annual commitments, deeper AWS service discounts, and reduced AWS Support pricing through partner-led support. Customers also get exclusive access to CloudKeeper Lens and ## **CloudKeeper delivers lower commitments and better discounts compared to AWS PPA.** In addition to AWS PPA, you also receive expert enterprise support at a lower cost, along with value-added services such as CloudKeeper Lens, which helps track your instance spending and maximize the benefits of PPA end-to-end. Beyond that, CloudKeeper provides cloud FinOps consulting and support services, We’re your one-stop solution for an Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Complete Guide to AWS PPA Contract Negotiation for Growing Enterprises A practical guide to AWS PPA or EDP negotiations, covering commitments, discounts, flexibility, risks, and best practices to help growing enterprises secure better pricing and long-term cloud value. By Team CloudKeeper 19 Dec, 2025 Introducing the AWS EDP Tracker in CloudKeeper Lens AWS EDP Tracker is a real-time interactive dashboard that gives you end-to-end visibility to monitor, forecast, and optimize your EDP spend throughout its term. By Harsh Agarwal 06 May, 2025 From Good to Great: Supercharge Your AWS EDP Plan with a Partner Learn how partnering with the right AWS EDP partner can simplify the complexities of AWS EDP, helping you secure great benefits at lower commitments & cost. By Team CloudKeeper 17 May, 2024 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 15 15 Table of Contents However, as much value as Kubernetes adds, it only does so when That’s exactly why we bring you the latest edition of “Ask the Cloud Expert: The ## **Featured expert for this edition:** Raghu is a Senior DevOps Architect at CloudKeeper, bringing deep experience in cloud infrastructure, with a particular focus on both devops and Let’s get started! ## **Part 1: Orchestration Basics & Why Kubernetes Matters** ### **Q1. What is cloud-based orchestration, and why do enterprises prefer Kubernetes for orchestration when hosting their software on the cloud?** Before discussing cloud-based orchestration specifically, it is essential to understand what orchestration is. Orchestration, to simplify, is coordinating multiple automated tasks into a cohesive workflow. For example, you can orchestrate **data pipelines, application deployments, server provisioning, or workflow automation across systems**. Orchestration, in the context of cloud computing, refers to using tools and code to automate key tasks required to simplify managing connections between clients and servers, and workloads as well. Orchestration technologies such as **Kubernetes, Docker Swarm, Apache Mesos, and HashiCorp** **Nomad** integrate all these into a streamlined workflow, enabling better scalability and reliability. Kubernetes, also known as * Kubernetes is an open-source platform * Provides * Portability across cloud providers, thus lifting and shifting from AWS, GCP, and Azure, won’t be a challenge if you choose to switch cloud providers * It pioneers system reliability by automatically redistributing workloads (pods) to other nodes within the same cluster for high availability and resource efficiency. However, managing workloads across different clusters requires external tools. * Automation of scaling and deployment — containers are automatically provisioned and fit into nodes to maximize resource efficiency ### **Q2. Why do SaaS providers and ISVs require orchestration, and what is the importance of software containerization for them? How does Kubernetes fit into this picture?** For To understand the importance of cloud orchestration for SaaS and ISVs, it’s essential to look at the kind of workloads they run and the scale at which they operate. A SaaS application’s or ISV’s user base can spike or drop suddenly, data processing demands can fluctuate based on customer activity, and new feature rollouts or patches can create sudden surges in traffic — all at speeds that would be impossible for a DevOps team to handle manually. That’s where orchestration steps in. **Orchestration takes care of these challenges holistically by:** * Automatically scaling workloads up or down to handle unpredictable traffic. * Managing deployment pipelines to ensure faster rollouts with minimal downtime. * Maintaining high availability with failover and recovery mechanisms. * Optimizing infrastructure usage to keep performance high while controlling costs. Coming to containerization, ISVs and SaaS companies must deliver high performance and availability irrespective of fluctuating workloads — and that’s exactly what containerization solves. Because containerization essentially works on the principle of “write once, run anywhere.” Every container contains all the dependencies required to run the software, making it easy to deploy on multiple machines and rethink virtualization at its core. **Problems containerization solves include:** * Portability across different environments (cloud, on-prem, hybrid). * Faster and more consistent deployments. * Easier isolation of workloads for security and performance. * Improved developer productivity by standardizing environments. Kubernetes then comes into the picture as the one-stop technology for containerization and orchestration. It simplifies container management with features like automated rollbacks, versioned upgrades, and self-healing measures (automatically restarting failed containers or redistributing workloads). With proper configuration, Kubernetes also automates resource management, ensuring maximum uptime while reducing operational overhead — making it the go-to tool for managing SaaS and ISV workloads at scale. ## **Part 2: Challenges in Kubernetes Adoption** ### **Q3. What challenges do DevOps teams typically face when setting up containerization, particularly with Kubernetes?** Kubernetes, while now almost a given for organizations looking to containerize their workloads on the cloud, comes with its own steep learning curve. DevOps engineers face difficulties at every stage of configuring a K8s cluster — the root cause being the complex, multi-layered configurations and the need to master new abstractions that differ significantly from traditional infrastructure practices. Issues such as**troubleshooting stuck pods, handling configuration drift, managing RBAC policies, and optimizing resource allocation** further add to the challenge, making Kubernetes harder to grasp initially. Some of the #### **1. Networking Challenges** Networking is complex and difficult to troubleshoot. The multiple networking layers in Kubernetes add to this complexity, creating many moving parts that make management even more challenging. Some networking-related issues I can think of include #### **2. Ensuring Cluster Uptime** K8s containers don’t exist for long periods in practice. Thanks to the automations written for scaling, they are frequently created and terminated depending on workload fluctuations. If you encounter a bug in such a distributed environment, debugging becomes particularly challenging. DevOps teams often struggle with setting up **centralized tracing, logging, and robust alerting for CPU/memory usage** across nodes. Without these, ensuring uptime is guesswork. #### **3. Security** Incorrect pod communications and misconfigurations are among the leading causes of Kubernetes-related security incidents. The challenge lies in correctly implementing **RBAC (Role-Based Access Control), network policies, and secrets management**. However, good network segmentation policies and proper service-to-service communication rules can mitigate most security loopholes. To add to this point, Kubernetes provides multiple security measures, but many DevOps engineers hesitate or don’t implement them. The main reason is the steep learning curve combined with the sheer number of security options—so many choices and alternatives can easily overwhelm people. #### **4. Managing Storage** If we take the example of a K8s cluster hosted on AWS, The right approach is to use Kubernetes-native features like the Container Storage Interface (CSI), StatefulSets, Persistent Volumes (PVs), and Persistent Volume Claims (PVCs) to take better control over what data goes into persistent storage — and avoid wasting money and space. ### **Q4. While deploying Kubernetes, what are the critical, non-negotiable aspects that organizations should never overlook?** While setting up a Kubernetes cluster, your priority should be to **maximize uptime** by ensuring high availability, robust security mechanisms, proper logging and visibility tools, as well as implementing CI/CD pipelines in case you need to update build dependencies for the software you’ve orchestrated. The following are some of the best practices you need to consider when setting up your K8s clusters: 1. **Use Canary and Blue-Green deployment strategies:** Unlike the running joke, you shouldn’t test in production. By following Blue-Green and Canary deployments, you can extensively test your software before releasing it into production, ensuring safer and faster rollouts. 2. **Put CI/CD configuration in place:** A strong CI/CD pipeline ensures that your deployments are automated, reliable, and repeatable, reducing manual effort and minimizing downtime during updates. 3. **Ensure fault tolerance from the first deployment:** Use Pod Anti-Affinity and Node Affinity rules to spread pods across nodes or availability zones, preventing a single point of failure. 4. **Implement resource requests and limits:** Define clear CPU and memory requests/limits for each pod to avoid resource starvation, noisy-neighbor issues, and unexpected crashes in production. 5. **Secure by default:** Enforce RBAC policies, enable Pod Security Standards (or PodSecurityPolicy if still in use), and restrict root access. Secrets should be stored securely using tools like Kubernetes Secrets or external vaults. 6. **Centralize logging and monitoring:** Use tools like Prometheus + Grafana, ELK/EFK stacks, or OpenTelemetry to gain visibility into cluster health, performance bottlenecks, and anomalies. Centralized logging simplifies debugging and enhances uptime. ## **Part 3: Performance & Cost Optimization** ### **Q5. What are the most common performance issues encountered with Kubernetes systems, and how can they be tackled effectively?** Before diving into the performance issues themselves, we must take a step back and understand the reasons behind them. They stem from the steep learning curve Kubernetes has, and while dealing with the complexities of the system itself and keeping the costs in check, teams often don’t provision enough resources, or even if they do, not the right kind and services needed. Coming to the performance issues themselves, here are the following: 1. **CPU Memory Throttling:** A result of incorrectly defined CPU and memory request limits. So, when the system scales or load spikes, it leads to performance degradation since the operating system kills the process with something known as Out Of Memory Kill. 2. **Pod Scheduling Issues:** CrashLoopBackOff, which causes frequent container crashes, ImagePullBackOff, Unschedulable Pods, Liveness and Readiness probe errors are some of the errors that occur as a result of misconfigurations. 3. **Networking Bottlenecks:** Container Network Interface misconfigurations or incorrect implementations frequently result in communication bottlenecks between the client and server. 4. **Horizontal Pod Autoscaler Misconfiguration:** When autoscaling thresholds are poorly set or based on the wrong metrics, it can either cause under-scaling, leading to downtime, or over-scaling, leading to unnecessary cloud costs. 5. **Storage Inefficiencies:** If we take the example of a K8 cluster hosted on AWS, EBS volumes can quickly run out. Since Kubernetes storage is not persistent by default, in practice, it stores persistent data—both build files and logs—in cloud provider services. But log files, crash dumps, temporary container files, and image layers can bloat storage, and you end up paying for inefficient storage. However, by using Container Storage Interface, StatefulSets, Persistent Volume, and Persistent Volume Claim, you would have better control over the data you want in persistent storage. 6. **Observability and Monitoring Gaps:** Without proper logging, tracing, and metric collection, DevOps teams often miss the early signals of performance degradation. This lack of visibility makes debugging and remediation extremely difficult in distributed K8 environments. ### **Q6. Performance optimization often sounds expensive. Does improving Kubernetes performance always lead to increased costs? How can organizations strike a balance between cost control and performance requirements?** No, not always. Most performance issues aren’t about throwing more money at the problem; they’re about wrong setups. A lot of the time, you get better results by fixing configs instead of provisioning extra nodes. * The most common culprit is CPU/memory requests and limits set wrong, leading to throttling or wasted capacity. * Autoscalers left with default thresholds cause over-scaling during short spikes. * Idle pods and unused namespaces burn resources silently. * Overprovisioned persistent volumes that nobody checks end up becoming hidden costs. The balance comes when you set up automation that scales **only when demand is real** and shuts things down aggressively when not in use. Kubernetes already gives you those levers—you just have to configure them properly. ## **Part 4: Tooling & Automation for Kubernetes Management** ### **Q7. What tools would you recommend for effective Kubernetes management? Is manual management ever a better option?** Manual management is fine for learning or testing. For production? It’s a trap. At scale, kubectl is firefighting, not management. You might get away with it on a dev cluster, but when you’re running dozens of nodes and hundreds of pods, you’ll spend your day chasing YAML and crashes instead of running workloads. The right approach is to layer your setup with tools that give visibility, automation, and guardrails: * **GitOps/CD:** ArgoCD or Flux lets you treat your cluster like code. Every deployment is version-controlled, auditable, and repeatable. No more “works on my machine” excuses, and no more manually applying YAML that accidentally takes prod down. * **Monitoring:** Prometheus + Grafana are the go-to. Prometheus scrapes metrics from your cluster, while Grafana gives you dashboards that show CPU, memory, pod health, and node status at a glance. Without this, you’ll only know your system’s down when your users start yelling. * **Cost tracking:** Tools like Kubecost or * **Logging & tracing:** ELK Stack, Loki, or OpenTelemetry give you the ability to track what’s happening inside your containers and across distributed services. When a pod crashes at 3 a.m., logs are the only thing between you and a clueless war room. * **Cluster navigation:** Lens or K9s make debugging less painful. Instead of squinting at endless _**kubectl get pods**_ commands, you get a clean view of pods, nodes, and namespaces. It speeds up troubleshooting massively. So is manual management ever better? Only if you’re experimenting, spinning up a quick proof-of-concept, or teaching a junior engineer what Kubernetes feels like. But once real traffic hits, once downtime means real money, **automation + tooling is the only sane way to run Kubernetes.** ## **Part 5: The Long-Term Future of Kubernetes** ### **Q8. Kubernetes is being widely adopted in 2025, but many technologies eventually fade. What do you think the long-term future looks like for Kubernetes?** Kubernetes isn’t going anywhere. The adoption curve has crossed the point of no return. Too many enterprises, ISVs, and SaaS vendors have standardized on it. Entire ecosystems — monitoring, CI/CD, security, networking — have been built with Kubernetes as the assumed baseline. What will change is how much of Kubernetes you actually touch as an engineer: * **Managed K8s (EKS, GKE, AKS):** These already remove ~70% of the operational overhead. You don’t worry about the control plane or patching masters — the cloud provider does it. Engineers only focus on workloads, scaling, and cost. * **Higher-level abstractions:** Platforms like OpenShift, Rancher, or internal PaaS products hide most of the cluster details. To a developer, deploying looks like “git push” or a simple CLI command, while Kubernetes hums invisibly in the background. * **Commoditization:** Just like Linux, Kubernetes will stop being the cool headline tech. It’ll become boring infrastructure — the backbone everything else runs on. You don’t think about Linux when deploying software, and the same will happen with Kubernetes. * **Standardization:** The Kubernetes API has become the de facto interface for container orchestration. Expect it to be the stable “language” for workloads, with the ecosystem building tooling around it rather than reinventing alternatives. * **Ecosystem maturity:** More tooling for policy enforcement (OPA/Gatekeeper), cost control (OpenCost, Tuner), and security scanning will integrate natively. Running Kubernetes won’t feel like stitching 10 tools together anymore. So, the long-term picture is that Kubernetes will feel invisible. You won’t obsess over pods, nodes, and YAML the way we do today. But behind the scenes, it will remain the backbone of cloud-native workloads — the control fabric that keeps containers running everywhere. Kubernetes won’t fade. It’ll stop being “new” and instead settle into the stack permanently, the same way Linux or TCP/IP did. ## **Part 6: Partner vs In-House Expertise** ### **Q9. For organizations facing challenges with Kubernetes, would you recommend relying on a partner-led support model or building strong in-house expertise to address issues?** Both have their place — it depends on where you are in your Kubernetes journey. * **Partner-led support:** Ideal for the early stages. Partners bring experience from multiple deployments, helping you avoid rookie mistakes, accelerate cluster setup, configure networking correctly, implement RBAC, and establish monitoring and alerting best practices. They also help set up CI/CD pipelines, logging/tracing, and automated scaling — all while maintaining cost efficiency. * **In-house team:** Essential for long-term success. Once clusters scale, day-2 operations become complex — patching nodes, managing cluster upgrades, optimizing resource usage, handling multi-cluster networking, and troubleshooting incidents. You can’t outsource every scaling challenge, CI/CD change, or performance bottleneck. Having engineers deeply familiar with your workloads ensures faster response, better cost control, and security compliance. * **Hybrid model:** The most practical approach. Start with a partner to accelerate setup, train your engineers alongside them, gradually transfer knowledge, and eventually allow your team to take full ownership. * **Critical workloads:** Security, auto-scaling decisions, cost optimization, and disaster recovery should always ultimately sit with your in-house team. Bottom line is that**** partners help you get started fast and avoid pitfalls, but real Kubernetes maturity comes when your engineers are battle-tested — capable of handling scaling, optimization, and operational challenges on their own. ## **To Sum Up** If you are deploying software on the cloud in 2025, it is essential to containerize and orchestrate it to ensure high availability and robust performance, even in the face of rapidly changing workloads. This is particularly critical for SaaS providers and ISVs, whose software powers many business-critical applications. Out of all containerization tools and technologies, Kubernetes stands out for its open-source nature, rich ecosystem of tools, seamless integration with To get started with Kubernetes deployment effectively, it is recommended to leverage ## **CloudKeeper Simplifies Kubernetes for You** CloudKeeper’s Kubernetes expertise covers all the bases you need to run, scale, and optimize Kubernetes systems on your cloud. Our team of Kubernetes experts will guide you end-to-end with optimization, intelligent monitoring, visibility, and the setup of observability & governance systems, ensuring maximum performance without incurring exorbitant cloud costs—ultimately maximizing your cloud ROI. Here’s CloudKeeper’s 3-step Kubernetes Optimization Framework: 1. **Audit Your Kubernetes Footprint:** We take read-only access to your K8 system and analyze setups, versions, scaling, and workloads to identify optimization opportunities. 2. **Tuning for Performance & Efficiency: **Based on our assessment, we provide data-driven recommendations and implement best practices that optimize cost while boosting performance, reliability, and security. 3. **Measure Results & Refine:** After implementing strategies, we continuously monitor the impact and provide ongoing recommendations to ensure your Kubernetes environment performs at its best. Talk to a Kubernetes expert today! Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 15 15 Table of Contents In recent years, However, GCP still holds the third spot in terms of cloud market share. AWS benefits from a mature ecosystem that covers almost every use case—ranging from performance optimization and As GCP adoption continues, so will the challenges common to all cloud infrastructures—bill shocks, runaway costs, and unoptimized cloud spend—yet the resources for addressing these issues in GCP remain limited. And that’s precisely why, in this edition of Ask the Cloud Expert, we’ll explore the lesser-discussed aspects of ## **Today’s Expert:** Puneet Malhotra is a Senior Manager at CloudKeeper, responsible for all of CloudKeeper’s GCP clients as well as So, let’s get started! ### **Q1. Despite incentive campaigns and promotions, why is GCP adoption still relatively low compared to AWS?** There are quite a few reasons and a combination of factors due to which Google Cloud Platform’s (GCP) acceptance, while rising, is still behind AWS and Azure. The situation is fairly complicated. **a) Fear of Pulling Out of GCP:** Google has a history of shutting down several major projects — such as Google Reader, Google Hangouts, Google App Engine Standard for Python 2, Google Stadia, and Firebase Dynamic Links. This created uncertainty for enterprises. Companies like Snap and Evernote had to re-architect parts of their stack when Google deprecated certain APIs or products. This fear was further exacerbated in January 2024 when GCP announced the removal of cloud egress fees. While seen as a positive move, it also triggered apprehension that Google might again shift strategies abruptly. **b) Lack of SES Equivalent and Missing Latency-Based DNS:** AWS offers Simple Email Service (SES), a highly scalable email sending and receiving service used for transactional emails, notifications, and marketing campaigns. GCP lacks a native equivalent, leaving developers to rely on third-party integrations for this critical workload. Similarly, GCP does not yet have a latency-based DNS routing service **c) Late to the Game:** By the time GCP seriously picked up pace against competitors, most large enterprises had already locked in their workloads with AWS or Azure. This “first-mover advantage” gap meant that Google had to fight harder to win enterprise trust. **d) Perception of Enterprise Readiness:** For a long time, GCP was perceived as more developer/startup-focused, especially strong in data analytics (BigQuery, ML, However, GCP has worked on these concerns and has carried out many steps to boost consumer confidence, such as **a) Renewed Focus on GCP:** Google has significantly increased its investment and focus on Google Cloud Platform. **b) AI & ML Innovation:** Introduction of Tensor Processing Units (TPUs) — custom hardware designed specifically for AI and ML workloads. Aggressively competing with AWS and Vertex AI platform enables end-to-end ML model training and deployment at a lower cost than AWS SageMaker, while delivering comparable performance. **c) Customer-Centric Investments:** * Free training engagements. * Proactive technical and non-technical support. * Dedicated account managers for enterprises. #### **Market Outlook (2025)** By 2025, most earlier concerns will have been largely addressed, with GCP being widely adopted both as a primary cloud infrastructure and in hybrid settings alongside AWS and Azure. ### **Q2. What are the common causes of GCP cloud cost runaways for organizations?** The most common causes aren't usually one big mistake, but a combination of unchecked automation, **a) Unmonitored Autoscaling:** This is the #1 runaway trigger. Autoscaling is amazing until a misconfigured policy or a code bug creates an infinite loop, spinning up thousands of preemptible VMs or instances that you don't notice until the bill arrives. You need to follow the recommended **b) Orphaned and Idle Resources:** * **Unattached Persistent Disks:** Storage for deleted VMs that you're still paying for. * **Idle VMs:** Development or test instances left running 24/7 primarily due to fear of infrastructure crashing in case it is turned off, because no one knows what it does. * **Old Snapshots & Images:** Forgotten backups that accumulate storage costs over months. **c) Lack of Commitment Discounts:** Without **d) Over-Provisioning ("Right-Sizing" Failure):** Developers often overestimate needs, provisioning 8-CPU machines for workloads that barely use 2. You pay for the entire oversized instance, 24/7. **e) Poor Resource Hierarchy & Tagging:** If you can't tell which project, team, or product is generating a cost, you can't hold anyone accountable. A flat structure with no labels or tags makes cost allocation and shutdown protocols impossible. **f) Spike in Data Processing or Egress:** A sudden, large data analytics job (e.g., a misconfigured The root cause of most of these is a lack of ### **Q3. What role can AI and automation tools play in GCP cost optimization?** AI and Automation are instrumental if you’re looking to optimize your GCP setup. Especially considering the size of infrastructure in the context of services and instances, a cloud engineer can't be at the dashboard observing the GCP cloud round the clock. Primarily, there are three use cases where AI-enabled automation tools have taken over: 1. **Right-sizing of Compute Engine resources:** It is not feasible to always be correct and accurately choose the best-suited VM type for the workload, but AI tools automatically do that for you, 2. **Autoscaling:** Spinning up and down cloud resources by assessing and predicting demand ensures maximum utilization of your resources when there is workload, and turning them off when not needed—thus saving cost while not impacting performance. 3. **Spot VM provisioning automation:** This has largely been taken over by AI and automation tools since it is not possible for a human to select and provision a Spot VM within seconds of availability. This use case is one of the most prevalent in CloudKeeper Lens is one of the few tools in the market that empowers users with the ability to We’ve perfected these offerings after continuous feedback from customers, and they continue to deliver tangible value. ### **Q4. How important is ongoing optimization for organizations seeking to reduce their GCP cloud bill, and what is the best approach for implementing it?** The best approach to ongoing optimization is a two-layered strategy: 1. **Foundational Optimization:** Start by aligning your infrastructure with 2. **Automation and AI-driven Tools:** Use automation to handle day-to-day adjustments. Tools like Google’s own Recommender and Active Assist can right-size instances, automate autoscaling, and provision Spot VMs more effectively than manual intervention. These ensure continuous optimization without requiring engineers to monitor dashboards around the clock. By combining ### **Q5. Are there any discount programs or special pricing plans that Google offers to its GCP customers?** Yes, Google offers many discount plans that are driven by key factors such as the duration of commitment, spend on particular services and instances, as well as similar such contracts: Sustained Use Discounts and Committed Use Discounts are the two discount programs GCP offers. However, before you enter into these pricing models, there are considerations you need to make: **a)Committed Use Discounts:** In exchange for making either a spend-based commitment or a resource-usage-based commitment, you get up to **55% off for most resources** like machine types or GPUs, and up to**70% off for memory-optimized machine types**. There are two variants of Google’s CUD. Those are: * **Resource-based Commitment Usage Discount:** As the name suggests, you get discounted pricing — **up to about 55%** (or up to 70% for memory-optimized machines) — on Compute Engine resources, but only for a predetermined geography. Also, the discount applies throughout the billing account * **Spend-based Committed Use Discounts:** This is analogous to AWS Savings Plans. Spend-based discount requires you to commit to a minimum dollar amount spent on GCP resources. It’s best if you have a steady and predictable workload. After the commitment period, regular on-demand pricing applies. Discounts for spend-based CUDs range from roughly 28% for a 1-year commitment to 46% for a 3-year commitment **Drawbacks of Committed Use Discounts** 1. **Lock-in:** CUDs are generally for a period of 1 year to 3 years, and for maximum discount, you typically make upfront or committed payments. Thus, if there is a reduction in workload, you may end up paying significantly more than the savings you received—defeating the purpose of the discount. **b) Sustained Use Discounts:** Sustained Use Discounts are applied automatically to your billing account at the end of the billing cycle—the more a particular resource is used during a month, the higher the discount. The maximum discount is up to 30% depending on the machine type. It is essential that you first gauge your workload, then go in for these discount plans. **c) Discounted Pricing Agreements for Startups and Enterprises:** Similar to These are the top discount programs and pricing models through which customers can save on their cloud spend instead of spending multiple times more by provisioning instances on demand. ### **Q6. For an organization just beginning its GCP cost optimization journey, what quick-win strategies or action plans would you recommend?** For an organization just starting, I’d recommend a mix of immediate quick wins and a foundational strategy: **Quick Wins in first 48 Hours:** 1. **Enable Recommender API:** Turn on and review the Idle VM Recommender and Right-Sizing Recommender in the console. It gives you instant, actionable shutdown and downsizing suggestions. 2. **Create Budget Alerts:** Set up Google Cloud billing alerts at 50%, 90%, and 100% of your forecasted budget to prevent surprise bills. 3. **Delete Unattached Disks:** These are pure waste. Run a quick query in the console to find and delete them. 4. **Review Sustained Use Discounts:** Check your report to see which discounts are being applied automatically. This identifies your steady-state workloads for future commitments. However, these were quick wins. For ongoing optimization efforts, it is necessary to make corrections at a foundational level—specifically, by sorting the architecture of your GCP infrastructure. And that foundation can be established by aligning your GCP setup with Google’s Cloud Architecture Framework (formerly called the Well-Architected Framework). The Cloud Architecture Framework provides a comprehensive set of recommendations along with actionable steps to implement them, with the end goal of optimizing performance, security, reliability, and cost efficiency in Google Cloud. Reorganizing your Google Cloud is essential for long-term cost reduction. Since it forms the foundation, all other cost optimization gains remain temporary without it. The Architecture Framework review document helps cloud architects, developers, and admins design robust architectures and simplify the administration of Google Cloud resources. ### **Q7. What are the top strategies for reducing GCP costs?** A lower GCP spend is what every organization strives for. However, it’s essential not to overstep and cut costs on resources you actually need. Think of cost optimization as maximizing ROI per dollar spent on cloud, rather than simply “cutting down cloud spend.” Here are some tried-and-tested strategies to follow for managing your GCP bill: **1. Use Spot VMs for non-critical workloads** Compared to the Additionally, creating instance groups of Spot VMs increases your chances of securing the required machines for your workload. **2. Rightsize your VMs** Rightsizing is one of the most critical steps in optimizing cloud spend, but it requires careful planning. Rushing this process can result in excessive downsizing, leading to performance bottlenecks and application crashes. **Key considerations when rightsizing VMs include:** * Match workload to resources: Define CPU count, memory allocation, storage size, and network bandwidth based on workload needs. For example, a high-performance analytics workload may require more memory and compute, whereas a web server may need lighter resources. * Avoid unnecessary premium SSDs: SSD storage is significantly more expensive than HDDs. Use premium SSDs only when workloads require fast or frequent data transfers. **3. Enforce a standardized tagging policy** Establish a clear, organization-wide tagging policy for all GCP resources (e.g., by project, environment, or department). **4. Leverage GCP recommendations** Like other cloud providers, GCP regularly publishes recommendations, best practices, and updates on new instance types or services. Staying on top of these ensures you adopt the latest cost-saving measures and configurations. 5. **Use Autoscaling:** Rather than having instances at maximum capacity all the time, use autoscaling to scale according to actual traffic. GCP's load balancers maintain performance while helping with cost savings—another two key pillars of GCP Optimization. By implementing these strategies, you can achieve sustainable cost reductions on your GCP infrastructure while ensuring performance and reliability remain intact. ### **Q8. What are the common mistakes organizations make when starting their GCP cost optimization journey?** The biggest mistakes stem from a reactive, overly aggressive mindset that alienates engineers and misses the bigger picture. 1. **Focusing Only on Unit Cost:** Slashing spend without context. For example, forcing a service to use a smaller machine type that then crashes under load, costing more in lost revenue than it saved. 2. **Treating It as a One-Time Project:** Thinking of cost optimization as a "cleanup" task you do once. It's an ongoing cultural practice (FinOps) that needs continuous monitoring and adjustment. 3. **Ignoring Commitment-Based Discounts:** Staying on pure on-demand pricing for predictable workloads is the most common and expensive mistake. It's like refusing to use a subscription for a service you use daily. 4. **"Set and Forget"** Policies: Creating autoscaling rules or budget alerts and never reviewing them. Usage patterns change, and your policies need to evolve with them. **Not Tagging Resources from Day One:** Launching resources without labels or tags makes it impossible to answer the question, "Who owns this cost?" This single failure cripples accountability. The core mistake is prioritizing cost-cutting over cost intelligence. The goal isn't just to reduce the bill; it's to understand why the bill is what it is and spend smarter. ### **Q9. What are the key cost metrics every GCP user should track to manage and save costs effectively?** You can't manage what you don't measure. These metrics move you from guessing to knowing. 1. **Total Cost (Monthly & YTD):** Your absolute baseline. Track it in the Billing Reports to understand overall trends and the impact of your changes. 2. **Cost per Project or Product:** Use labels to break down your bill. This tells you which parts of the business are driving spend and enables accountability. 3. **Committed Use Discount (CUD) Coverage:** The percentage of your eligible compute spend covered by commitments. A low percentage (<50%) means you're leaving significant savings on the table. 4. **Idle Resource Cost:** The amount spent on resources that are powered on but doing no work (e.g., VMs with <5% CPU utilization). This is pure, uncontroversial waste. 5. **Data Egress Costs:** Often a hidden killer. Monitor Track these in Google Cloud's Billing Reports and set up Budget Alerts on them to catch anomalies before they become catastrophes. ## **To Sum Up** Optimizing a GCP infrastructure can be more challenging than optimizing with other cloud providers, such as AWS, mainly due to the smaller number of resources, fewer third-party optimization service providers, and the overall lack of awareness of the GCP ecosystem. However, the fundamentals remain the same: right-sizing, visibility, and the use of discount plans. While these fundamentals are consistent across the cloud ecosystem, it is essential to have nuanced, hands-on knowledge of GCP and its ecosystem to get the most out of any optimization effort. ## **Make the Most of Your GCP Infrastructure with CloudKeeper** CloudKeeper is your end-to-end solutions partner for maximizing your ROI in GCP. We bring multiple competencies and partner programs, along with 60+ highly skilled and certified practitioners and consultants who will guide you through every step of your Google Cloud journey. These are the Google Cloud services CloudKeeper offers: * **End-to-End GCP Consulting:** Our team provides strategic guidance and actionable insights to help you achieve your business objectives with a scalable GCP infrastructure setup. * **Deployment and Migration Assistance:** Shifting from another provider to GCP? Our team will help you efficiently deploy and migrate your workloads with minimal disruption while ensuring maximum performance. * **Comprehensive Wellness Reviews:** We thoroughly evaluate your current setup, identify areas for improvement, and provide recommendations to enhance efficiency, security, and cost optimization. * **Best-in-class GCP visibility tool that offers all-rounded insights:** CloudKeeper Lens is one of the few tools in the industry that provides comprehensive visibility into your GCP infrastructure. It delivers resource-level cost visibility and a unified view of multiple accounts—all without requiring access to your GCP account! Get in touch with our GCP experts today! Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents Cloud optimization is too often reduced to catchy marketing slogans: “50% cost cuts,” “instant waste elimination,” or “one-click tuning.” In reality, it’s a nuanced practice that balances spending, performance, reliability, and growth. Whether you’re a CFO bracing for a surprise invoice, an engineering manager troubleshooting performance spikes, or a product owner juggling feature delivery with budget limits, you know cloud optimization isn’t a one-size-fits-all checkbox. In this expert-led conversation, we cut through the noise to reveal ## **About today’s expert -** Leading this conversation is Praneet Chandra, who brings a unique perspective to cloud optimization - combining deep technical expertise with real-world experience scaling SaaS companies from startup to IPO. With over 14 years of hands-on experience building high-growth SaaS platforms, Praneet has navigated the cloud optimization challenges. At CloudKeeper, Praneet applies this experience to help organizations optimize not just for cost, but for sustainable growth. ## **Part 1: What Cloud Optimization Really Means** **Q 1: Everyone talks about "cloud optimization," but what does it actually mean beyond just cutting costs?** This is exactly the right question to start with. I see too many organizations treating cloud optimization like it's just about finding the cheapest option - and that's where they go wrong. True cloud optimization is about finding the sweet spot between four critical dimensions: cost, performance, availability, and scalability. Think of it like tuning a race car. You don't just want the cheapest engine; you want the right balance of power, reliability, and efficiency for your specific race. For example, we worked with a SaaS company that was so focused on cost-cutting that they downsized their database instances. Sure, they saved 40% on their monthly bill, but their application response times doubled, leading to customer churn that cost them far more than they saved. **Q 2: Can't I just implement a cloud optimization tool and call it done?** I wish it were that simple! This is probably the biggest misconception we encounter. Here's what actually happens: A tool might tell you that you have 20 idle EC2 instances, but it won't tell you that 15 of them are critical for your quarterly load testing, and 5 are genuinely wasteful. Without a business context, you might terminate the wrong ones and break your testing pipeline. We've seen companies spend six figures on optimization tools, only to see minimal results because they lacked the expertise to interpret and act on the data meaningfully. That's why our approach at CloudKeeper blends the best of both worlds. Tools like When something unusual pops up, you don't get bombarded with generic alerts. Instead, our team reviews it first and only reaches out when there's something genuinely worth your attention. **Q 3. How should I think about optimization vs. innovation?** Carve capacity: reserve a predictable % of budget/time for innovation while continually improving efficiency in production. Optimization should enable more experiments, not stifle them. ## **Part 2: The Hidden Costs of Poor Cloud Usage** **Q 4: What are the real costs of inefficient cloud usage that most companies miss?** Beyond the obvious overspend, which averages 32% of cloud budgets according to recent studies, there are three * **Opportunity Cost:** Every dollar wasted on idle resources is a dollar not invested in innovation. We had a client spending $200K annually on unused development environments. That money could have funded two additional engineering hires. * **Technical Debt:** Poor cloud practices compound over time. Untagged resources, inconsistent architectures, and ad-hoc provisioning create a mess that becomes exponentially more expensive to clean up later. * **Team Productivity:** Engineers spending hours troubleshooting performance issues caused by undersized resources, or finance teams scrambling to explain unexpected bills - these are real costs that don't show up on your cloud invoice. **Q 5: Should a startup worry about cloud optimization at this stage?** This is a dangerous myth. Early-stage companies often think they'll "optimize later when they're bigger," but that's like saying you'll learn to drive properly after you buy a Ferrari. We've seen startups burn through Series A funding 40% faster due to poor cloud practices. The habits you build early become your foundation. A startup we worked with was spending $50K monthly on cloud - turns out 60% was waste from abandoned experiments and over-provisioned resources. Start with basic hygiene: tagging, rightsizing, and **Q 6: Why do “zombie” resources keep appearing after cleanups?** Lack of ownership, missing automation to delete temporary test or demo environments, manual experiments left running, and gaps in tagging/reporting. Fix by combining policy-based lifecycle rules, ownership tags, and periodic automated sweeps. ## **Part 3: Optimization in Action – What Effective Strategies Look Like** **Q 7: What does effective cloud optimization actually look like in practice?** This is how a plan for **1. Weeks 1–2: Discovery & Quick Wins** * Pinpoint idle or oversized resources to unlock immediate * Automate on/off schedules for non-production environments, slashing those costs. * **2. Weeks 3–8: Strategic Optimization** * Move steady workloads to Reserved Instances for predictable discounts. * Enable * Streamline storage by tiering data and enforcing lifecycle policies. **3. Ongoing: Cultural Integration** * Roll out cost-by-team and cost-by-project * Set up alerting and approval workflows to * Make cost awareness part of every sprint - so every engineer thinks about cloud costs. This approach balances speed, strategy, and sustainability - delivering quick wins while building a culture where optimization is second nature. **Q 8: How do you balance cost optimization with performance requirements?** This is where the "optimization" in cloud optimization really matters. It's not about finding the cheapest option - it's about finding the most efficient one. We use a methodology called "Performance-Cost Profiling." For each workload, we map the relationship between resource allocation and business impact. For example, a client's The key is understanding your performance requirements at a granular level, not just applying blanket upgrades or downgrades. ## **Part 4: Real-World Learnings from SaaS/ISV Teams** **Q 9: What unique cloud optimization challenges do SaaS companies face?** For SaaS companies, cloud costs have a direct impact on unit economics - but many teams don’t have a clear view of spending at the customer or feature level. Without that On top of that, SaaS teams have to juggle the challenge of running shared infrastructure efficiently while keeping tenants isolated, ensuring consistent performance, and managing seasonal or variable usage without paying for extra capacity all the time. **Common SaaS Optimization Patterns:** **-** **Multi-tenancy Optimization:** Rightsizing shared resources while maintaining isolation **- Customer Cost Attribution:** Understanding true cost-per-customer, not just revenue-per-customer **- Feature-Based Costing:** Mapping cloud spend to product features to inform pricing decisions **- Seasonal Scaling:** Many SaaS apps have predictable usage patterns that can be optimized Quick tip: prioritize getting accurate cost telemetry (tenant, feature, environment) - it’s the single best lever for effective, business-aligned optimization. **Q 10: How do ISVs handle cloud optimization differently from other businesses?** One ISV client was spending 40% of revenue on cloud infrastructure. The issue wasn't just efficiency - they hadn't architected for cost-effective scaling. We helped them: **1. Implement Usage-Based Scaling:** Instead of always-on resources, they moved to event-driven architectures **2. Optimize Data Transfer:** Reduced cross-region traffic by 70% through better data locality **3. Right-Size for Customer Tiers:** Different service levels for different customer segments **The result:** Cloud costs dropped to 22% of revenue while improving service reliability. **Q 11. Can you walk us through a cloud optimization success story where CloudKeeper Tuner has helped?** Absolutely. We worked with a leading fintech platform, MobikWik, that was spending heavily on AWS but struggling with visibility across its multi-account setup. Despite having internal tools, they couldn't get a unified view of optimization opportunities. Within days of onboarding CloudKeeper Tuner, Tuner identified about 26% optimization scope in their EC2 environment- flagging underutilized instances that could be rightsized without any service disruption. For RDS, we surfaced over 11% monthly savings potential by recommending smarter instance types and reservation strategies. Overall, they unlocked 7-10% monthly savings across their entire AWS environment. But more importantly, every recommendation was backed by precise data, so their teams could act with confidence. You can read more ## **Final Takeaways** **Q 12: What should companies focus on first if they're starting their optimization journey?** Start with visibility and governance, not cost-cutting. Here's the priority order: **Get Visibility** - Implement proper tagging and cost allocation - Set up monitoring and alerting for unusual spend - Identify your top cost drivers **Quick Wins** - Eliminate obvious waste (idle resources, over-provisioned instances) - Implement scheduling for non-production environments - Right-size based on actual usage data **Strategic Optimization** - Move to appropriate pricing models (Reserved Instances, Savings Plans) - Implement auto-scaling and automated resource management - Build cost awareness into development processes - Run monthly FinOps reviews, rotate owners for continuous improvement, and publish wins internally. **Q 13: How do you know if your optimization efforts are actually working?** Metrics matter, but the right metrics. Don't just track total spend, track efficiency metrics: - Cost per business unit (per customer, per transaction, per feature) - Resource utilization rates (aim for 70-80% on production workloads) - Waste percentage (should be under 15% for mature organizations) - Cost predictability (variance from budget should decrease over time) We track these monthly for our clients, and successful optimization shows improvement across all dimensions, not just raw cost reduction. ## **The Simple Checklist for Cloud Optimization** * Do we have owner tags for all resources? * Are non-prod environments auto-stopped outside business hours? * Do we track cost per product/tenant? * Are storage lifecycles applied? * Is there a monthly FinOps review with engineering + product? * Are we measuring the velocity impact of optimization changes? The Ready to start optimizing? Let's have a conversation about your specific cloud challenges. Whether you're dealing with runaway costs, performance issues, or just want to build better cloud practices, we can help you create a sustainable optimization strategy. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 13 13 Table of Contents AWS continues to dominate the market as the biggest cloud infrastructure provider, taking the lion’s share of the market at 30%. However, having AWS as your cloud infrastructure can quickly turn out to be a costly affair, and numbers prove it too. Cloud computing, more commonly associated with AWS, accounts for around 32% of a company’s IT budget, which is a significant portion of its capital expenditures (capex). As workloads scale, it is not feasible to provision all compute instances on demand; since However, it’s not all a rosy picture. There are several caveats and nuances to consider regarding both AWS Reserved Instances and AWS Savings Plans. By the end of this article, you will be empowered with real-world knowledge to know ## **Featured Expert:** Aman Khandelwal is a Senior DevOps Engineer at CloudKeeper, well-versed in the technical aspects of DevOps and experienced in managing enterprise-scale production AWS infrastructure across diverse workloads. He also possesses a strong theoretical understanding of FinOps principles. By combining deep technical expertise with FinOps knowledge, Aman helps maximize performance while reducing cloud wastage, ultimately driving higher ROI. So, let’s get started. ## **Part 1: Understanding the Current Landscape of RIs and Savings Plans** **Q1. What is the state of AWS Reserved Instances in 2025? Is it true that Reserved Instance discounts are being phased out in favor of AWS Savings Plans?** Reserved Instances are not being phased out in 2025. However, AWS has clearly positioned Savings Plans as the superior and more flexible discount model for the vast majority of use cases. While AWS RIs remain available for purchase, their strategic importance has diminished significantly in favor of the simplicity and flexibility of AWS Savings Plans. AWS RIs are still available, but not promoted: You can still buy Standard and Convertible RIs for a 1 or 3-year term. However, AWS's console, sales teams, and recommendations now almost universally steer customers toward AWS Savings Plans. For specific use cases, AWS RIs can still be marginally better for predictable, static workloads where you are certain you will need a specific instance type in a In essence, AWS is not doing away with RIs, but they are not actively pitching them to customers. For nearly all customers, Savings Plans are now the default, recommended choice because they provide the same level of discount without the operational overhead and risk of being locked into specific instance types. **Q2. What are AWS Savings Plans, and how are they different from AWS Reserved Instances?** AWS Savings Plans are flexible pricing models that allow you to commit to a specific hourly spend (measured in USD/hour) on AWS compute usage for a 1- or 3-year term. In return, you receive significant discounts—up to 72%—compared to on-demand pricing. Unlike Reserved Instances, which require committing to a specific The key difference is flexibility. Reserved Instances lock you into particular configurations and capacity reservations, whereas AWS Savings Plans only lock in your spend commitment. This means that with Savings Plans, you can change instance types, switch regions, or even move workloads between ## **Part 2: Discounts, Pricing Models & Commitments** **Q3. What factors determine AWS Reserved Instances discounts, and which configurations receive the maximum discounts?** AWS Reserved Instance discounts aren't a flat rate; they are a complex algorithm designed to reward commitment and behaviors that benefit AWS's capacity planning. The maximum discount is a product of your willingness to accept the most restrictive terms. Here are the key factors that determine the discount percentage: **a) Commitment Term:** This is the biggest lever. * **1-Year Term:** Lower discount. * **3-Year Term:** This provides the highest possible discount. You are locking in with AWS for a longer period, and they reward that with significantly lower rates. **b) Payment Option:** This affects your upfront cost and the discount rate itself, but it impacts your cash flow. * **No Upfront:** You pay nothing initially and are billed a discounted hourly rate each month. The total cost is the highest. * **Partial Upfront:** You pay a portion of the cost upfront and a lower hourly rate. This offers a more effective discount than No Upfront. * **All Upfront:** You pay the entire cost of the term at once. This provides the highest effective discount because AWS gets all its money immediately. **c) Instance Flexibility:** This is a trade-off between discount and flexibility. * **Standard RIs:** These are locked to a specific instance type (e.g., m5.2xlarge), AZ, and OS. They receive the maximum discount but carry the highest risk if your needs change. * **Convertible RIs:** These can be exchanged for different instance types or families later, but only in the same geographic region. They offer fewer discounts than Standard RIs because you are paying for the flexibility to change your mind. * **Region and Instance Type:** Discounts may vary slightly by region due to local market conditions, supply, and demand. Newer, in-demand instance generations (e.g., **d) Scope:** * **Regional RIs:** Apply to an instance in any Availability Zone within a region. They offer a slightly lower discount than Zonal RIs but provide flexibility during outages. * **Zonal RIs:** Apply to a specific The absolute maximum discount is achieved by combining the most restrictive options: A 3-Year, All Upfront, Standard Reserved Instance, scoped to a specific Availability Zone. This configuration gives AWS exactly what it wants: maximum upfront cash, a long-term commitment, and a guarantee of how and where it will utilize its capacity. You are accepting all the risk of your infrastructure needs changing in exchange for the lowest possible rate. **Important Caveat:** While this gets the highest discount, it also carries the highest risk. Most modern organizations prioritize flexibility over maximizing every last percentage point of discount, which is why Savings Plans (which offer significant discounts with much greater flexibility) have become the default recommendation for most use cases. **Q4. What are the shortfalls of AWS Reserved Instances?** AWS Reserved Instances (RIs) are a powerful tool for savings, but they come with significant drawbacks that have led many organizations to shift towards Savings Plans. Their primary shortfalls are a lack of flexibility and high management overhead. These are the key shortfalls of AWS RIs: * **Inflexibility and Risk of Waste:** This is the biggest flaw. AWS RIs are locked to a specific instance type, size, Availability Zone, and OS. If your application changes and you no longer need that specific resource, the AWS RI becomes useless, and you are stuck paying for it. This often leads to "AWS RI waste," where companies are forced to run outdated workloads just to utilize commitments. * **High Management Overhead:** AWS Reserved Instances are not "set and forget." They require * **Limited Scope:** Traditional AWS RIs primarily only apply to EC2, RDS, and a few other compute services. They do not cover modern, flexible services like AWS Fargate or Lambda, leaving a growing portion of your bill ineligible for discounts. * **Complex Capacity Planning:** You are effectively playing a guessing game with your future infrastructure needs. If you under-purchase, you leave savings on the table. If you over-purchase or guess wrong, you are financially penalized. This is incredibly difficult for dynamic or fast-changing environments. * **Upfront Financial Commitment:** The payment options (All Upfront, Partial Upfront) require significant capital expenditure (CapEx), which can strain budgets and limit financial flexibility compared to the pure operational expense (OpEx) model of pay-as-you-go. To sum up, AWS Reserved Instances require you to trade flexibility for savings. In a modern cloud environment where agility is paramount, this is often a poor trade-off. This is precisely why AWS introduced Savings Plans, which provide similar discounts but automatically apply to your dynamic usage, effectively solving the core shortfalls of the AWS RI model. **Q5. In which use cases do you not recommend Savings Plans to your customers?** While Savings Plans are the most flexible and recommended discount instrument for the vast majority of workloads, they are not a universal solution. I typically advise against them, in a few specific scenarios where their value diminishes or the commitment becomes a liability. Here are the key use cases where Savings Plans are not a good fit: * **Unpredictable or Short-Term Workloads:** For a project with a defined end date (e.g., less than 6 months) or a workload for which you cannot establish a reliable hourly commitment, pay-as-you-go pricing avoids lock-in. Examples include one-time data processing jobs or short-term R&D projects. * **Workloads Planned for Immediate Modernization:** If you are actively planning to re-architect and migrate a significant portion of your compute away from EC2 or Fargate (e.g., to containers on EKS or a serverless architecture using Lambda), a Savings Plan commitment could become stranded. It's better to complete the migration first and then commit based on the new architecture. * **Organizations with Cash Flow Constraints:** The upfront payment options (especially All Upfront), while offering the highest discount, require a significant capital expenditure (CapEx). Companies that need to preserve cash and strictly operate on an operational expense (OpEx) model may find the pay-as-you-go model easier to manage, even if it's more expensive hourly. * **Legacy Environments Slated for Decommissioning:** If you have a large, steady-state workload running on old instance types (e.g., M3, C3) that is scheduled to be fully shut down within the next 12 months, a 1-year commitment might not break even before the shutdown is complete. In these cases, the flexibility and lack of commitment in On-Demand or Spot Instances outweigh the potential savings of a Savings Plan. The core principle is: if you cannot confidently predict your baseline compute usage for the next year, you should not commit to it. **Q6. What are the pricing models of AWS Reserved Instances and AWS Savings Plans, and how are discounts impacted by the type of payment made?** The pricing models for both RIs and Savings Plans are fundamentally about trading upfront financial commitment for a lower effective hourly rate. The golden rule is: the more upfront capital you provide AWS, the higher your effective discount will be. AWS Reserved Instances (RIs) Pricing Models RIs offer three payment options that directly impact your discount and cash flow: **a) All Upfront:** * **Model:** You pay the entire cost of the reservation term (1 or 3 years) in one single, upfront payment. * **Discount Impact:** This option provides the highest effective discount (up to ~72% for a 3-year Standard RI). AWS rewards you most for providing all the capital immediately. **b) Partial Upfront:** * **Model:** You pay a portion of the total cost upfront and are billed a significantly discounted hourly rate for the instance for the duration of the term. * **Discount Impact:** Offers a lower discount than All Upfront but a higher discount than No Upfront. It balances upfront cost with ongoing savings. **c) No Upfront:** * **Model:** You make no upfront payment and are simply billed a discounted hourly rate for the instance over the term. * **Discount Impact:** Provides the lowest effective discount of the three options. It preserves cash flow but is the most expensive way to utilize an RI over the long term. **AWS Savings Plans Pricing Models** Savings Plans mirror the RI payment options but apply them to a dollar-hour commitment instead of a specific instance: **a) All Upfront:** * **Model:** You pay for your entire commitment (e.g., $10/hour for 3 years) in one payment. * **Discount Impact:** Provides the highest effective discount for the commitment. **b) Partial Upfront:** * **Model:** You pay a portion of the commitment upfront and a discounted hourly rate for the remaining balance. * **Discount Impact:** Offers a middle-ground discount, better than No Upfront but less than All Upfront. **c) No Upfront:** * **Model:** You make no upfront payment and are billed at the discounted Savings Plans hourly rate for your usage. * **Discount Impact:** Provides the lowest effective discount but requires no initial capital. ## **Part 3: Application & Flexibility of Savings Plans** **Q7. Once a Savings Plan is purchased, how is it applied to your AWS setup?** AWS automatically applies Savings Plans to your eligible usage, with no manual assignment required. It works on an hourly basis in a specific priority order: * **Automatic Application:** Each hour, AWS identifies your eligible compute usage (EC2, Fargate, Lambda) across your entire organization. * **Discount Application:** It first applies any Reserved Instance discounts you have. Then, it applies your Savings Plan commitment to the remaining On-Demand usage that matches the plan's family and region. * **Priority by Discount:** Usage is covered starting with the resources with the highest On-Demand rates first, ensuring you maximize your savings. * **Beyond the Commitment:** Any usage that exceeds your Savings Plan commitment or doesn't match its terms is billed at the standard On-Demand rate. You don't need to assign it to specific instances; AWS handles it seamlessly in the background. **Q8. Both AWS Reserved Instances and Savings Plans are commitments. If someone no longer needs that capacity after purchase, is there any way to get a refund?** No, you cannot get a cash refund. AWS does not offer refunds for canceled commitments. However, you do have options to minimize further loss, though they come with restrictions: **a) Reserved Instances (RIs):** Sell on the AWS Marketplace: If you have a Standard RI that you no longer need, you can try to sell it on the AWS Reserved Instance Marketplace to another customer. This is often difficult, and you will likely sell it at a loss. * **Modify:** You can change the Availability Zone, scope (Regional vs. Zonal), or network platform of a Standard RI. * **Exchange:** Convertible RIs can be exchanged for a different Convertible RI with a new attribute configuration (e.g., a different instance type or family). The new RI must have an equal or greater value, and the term resets. **b) Savings Plans:** * **No Marketplace:** There is no marketplace to sell Savings Plans. * **Limited Flexibility:** If you change your mind within the first month—before the billing cycle—you can cancel the Savings Plan entirely. But the savings will also be lost, and your bill will revert to standard On-Demand rates. The bottom line: Only commit to what you are very confident you will use. There is no easy "undo" button. ## **Part 4: Automation & Optimization of AWS Commitments** **Q9. Is there a way for automation tools to handle AWS Reserved Instances?** Yes, absolutely. In fact, for any organization of significant size, using automation is essential to manage the complexity and risk of AWS RIs. These tools handle the entire lifecycle: **a) Recommendation:** Analyze historical usage to recommend the optimal AWS RI type, instance family, term, and quantity to purchase to maximize coverage and savings. **b) Procurement:** Automate the actual buying process based on those recommendations. **c) Management & Optimization:** Continuously monitor your environment to: * Ensure * Identify opportunities to modify or exchange underutilized RIs. * Track expiration dates and recommend renewals. **d) Waste Prevention:** Alert you to AWS RIs that are going unused so you can take action (e.g., sell or exchange them) before the commitment is wasted. Our tool CloudKeeper Auto is the only solution you need to manage AWS RIs and Savings. From auto-provisioning to shutting down idle instances to right-sizing, CloudKeeper Auto is a comprehensive ## **To Sum Up** For an organization that’s entering into cloud space with AWS, eventually, slightly scaling up from AWS to production workload scale, you would find yourselves opting for one or the other—Savings Plan or RI Plan. In 2025, AWS is actively pitching Savings Plans while AWS RIs are still available. Both have their utilities, but it’s essential to first have a clear understanding and Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents ## **From Repetitive Tasks to Automated Workflows** In recent years, artificial intelligence has changed the way we approach work. It’s taken a lot of the heavy lifting off our plates and shown how much more effective people can be when they’re not bogged down by the routine. Yet, in many organizations, teams still lose time to the same old problem: repetitive, low-value tasks. These are the things that don’t require much skill or creativity but still eat away at productivity. Automation platforms are stepping in to fix that. By handling the mundane, they let people focus on projects that actually need their expertise. Looking ahead in 2025, one platform in particular is catching the attention of technical teams: n8n. Unlike traditional players such as Make or Zapier, n8n is ## **What is n8n?** ### **Architecture & Core Capabilities** #### **1. Visual Workflow Builder** * Build automations with an intuitive drag-and-drop editor that shows your workflow as you create it. * Get real-time visibility into data flowing through each node, making it easy to debug inputs, outputs, and execution steps. #### **2. Blend No-Code with Custom Code** * Build workflows quickly with visual nodes, while still having the option to drop in custom JavaScript or Python for complex logic. * Extend capabilities with npm or Python libraries, or even import cURL requests directly into your flows for faster API integration. #### **3. 400+ Integrations available across services** * Connect instantly with 400+ pre-built integrations (growing), covering everything from Google Sheets and Slack to databases, CRMs, and AI tools. * Use the HTTP Request node to hook into any API, plus community-built nodes for specialized workflows. * Extend further with n8n’s MCP Server endpoints, making it easy to plug in custom tools or services. #### **4. AI-enabled Advanced Systems** * Leverage built-in AI nodes for summarization, Q&A, chat, and content generation. * Chain nodes together to build multi-step AI agents, complete with custom tools. * Option to self-host models (e.g., Ollama) for tighter control over data privacy. #### **5. Extras (Error handling, retries, and versioning)** * Define dedicated error workflows that kick in automatically when something fails — sending alerts, logging issues, or running fallback logic without manual babysitting. * Configure smart retries on nodes to recover from transient errors, and keep JSON exports as backups so you can roll back changes if a new tweak breaks the flow. ### **Self-Hosting n8n with Docker: Quick Setup** Running n8n locally is pretty straightforward with Docker. For quick tests or small deployments, a single Docker container works fine. For production, Docker Compose or a proper server setup is recommended. Read more #### **Installation Steps** 1. Create a persistent volume for your data: `docker volume create n8n_data` 2. Start n8n with Docker: `docker run -it --rm --name n8n -p 5678:5678 \ -v n8n_data:/home/node/.n8n docker.n8n.io/n8nio/n8n ` 3. Once it's running, open `localhost:5678` in your browser. On first launch, you can either create an account or skip directly to the editor. Congrats — n8n is up and running! From here, you can start building workflows from the dashboard. For production setups, check out environment variables ### **A Developer’s Perspective** What really caught me off guard (in a very nice way) is how naturally and easily JavaScript fits into n8n. Instead of learning a new scripting language or weird syntax for these crazy automations and overhead, I can use plain JS right inside node inputs. For example, when I get a chunky HTTP response, I don’t have to overthink it — I just JSON.stringify or any custom toJSON the part I need and drop it into Google Sheets or something else. Simple, clean, and no extra overhead. When things get more complex and out of the box, I switch to a Code node. This feels so much like home — I can throw in a console.log and actually see the output in Chrome DevTools very clearly while testing a workflow. It’s a small touch, but incredibly useful when debugging your stuff Another real kicker, though, is external npm support. On self-hosted setups, I can pull in npm packages directly in my Code nodes. That’s something you just don’t get with tools like Zapier or Make. This alone puts n8n closer to platforms, where code isn’t treated as a second-class citizen. And yes, Python is supported too. It runs on Pyodide (transpiled into WebAssembly, executed via Node.js), which is wild when you think about it. The only limitation is performance — you can’t sprinkle Python everywhere due to overhead, so most lightweight tasks are still easier in JS. Personally, I’m fine with that since JS is already embroidered into n8n’s DNA. You can read more about code in n8n ### **Pricing Plans (might change, check****)** * **Community Edition:** Free, open-source version (self-hosted) * **Starter Plan:** €20/month (2,500 executions, 5 active workflows) * **Pro Plan:** €50/month (10,000 executions, 15 active workflows) * **Enterprise Plan:** Custom pricing with unlimited executions ## **When to Automate (and When Not To) with n8n** Automation is powerful, but not every process should run fully on autopilot. With n8n — especially now with AI in the mix, also ### **1 . Speed with Safety** Automation speeds things up, but when workflows hit edge cases, human checks can prevent big delays. n8n makes it easy to combine fast automation with manual approvals where needed. ### **2. Saving Engineer Time** Fully autonomous systems can cause bigger headaches if they break. With n8n, hybrid workflows reduce firefighting by letting humans step in only when exceptions occur. ### **3. Consistency Where It Matters** Automation keeps routine processes predictable. But for tasks with unique scenarios, adding AI or manual steps in n8n ensures the right kind of consistency — not blind repetition. ### **4. Repeatability + Flexibility** Rigid automations often don’t scale. n8n lets you design workflows that adapt to different contexts, making them reusable without being fragile. ### **5. Partial Automation Wins** The best balance is often hybrid. Automate data collection or policy updates in n8n, but keep risky final steps under human review. The game-changer? With AI now engraved into n8n so effortlessly and perfectly, you can automate complex, variable logic that was impossible just a few years ago. That means fewer limits — and more freedom to focus on work that matters. ## **Why More Organizations Are Choosing n8n** Organizations across industries are turning to n8n for several strong reasons that go beyond simple automation. 1. **Data Sovereignty** Maintain complete control over where your data is stored, processed, and managed — ensuring compliance and security on your own terms. 2. **Freedom to Customize** Easily modify, extend, and tailor the platform to meet unique business requirements, instead of being locked into rigid workflows. 3. **Cost Efficiency** Reduce automation expenses dramatically when compared with proprietary platforms, without sacrificing performance or flexibility. 4. **Future-Ready Architecture** Built on an open architecture, n8n can evolve alongside changing business needs, making it a long-term solution rather than a temporary fix. 5. **Integration Without Limits** Seamlessly connect virtually any application — even those without built-in or native integrations — to create end-to-end automated workflows. ### **Example Workflow** Auto-Reply to Customer Inquiries with AI-generated First Responses (n8n), Automate first-response emails so your inbox doesn’t drown you. 1. **IMAP Email (Trigger)** **a)** Watches your support inbox for new messages. **b)** Connect mailbox; keep it simple 2. **Set / Extract** **a)** Grabs just the subject and body to pass forward. **b)** subject = {{$json["subject"]}} · body = {{$json["text"] || $json["html"]}} 3. **OpenAI/ AI Agent (Chat Completions)** **a)** Drafts a clear, polite reply in the customer’s language. **b)** Prompt gist: “You’re a concise support agent. Subject: {{subject}} Body: {{body}}. Keep under 150 words; ask up to 2 clarifying questions if needed.” 4. **Gmail / SMTP** **a)** Sends the generated reply back to the sender. **b)** To: {{$json["from"]["email"]}} · Subject: Re: {{$json["subject"]}} · Body: LLM output Read more about N8N nodes, integrations, and their behavior **Pro Tip:** Add an IF node to gate by keywords (refund, billing, urgent) or VIP domains; log all replies to Google Sheets (timestamp, from, subject, snippet). **Super Pro Tip (advanced, for later):** Add RAG (Retrieval Augmented Generation) so replies use your internal docs/FAQs. Retrieve top-k snippets from a vector DB (Pinecone/Weaviate/Supabase) after Extract → include as context in the OpenAI prompt; if no match, ask for missing info. You can read more about RAG ### **Explore more Recipes** * If you are a **data scientist** , auto-track model performance, flag drift or bias, and get concise AI summaries of anomalies with suggested checks. * If you are in **/SRE** , auto-triage alerts, enrich with logs/metrics, validate safe actions, and post clean incident updates to your channels. * If you are a **product/eng lead** , turn merged PRs and commits into polished release notes and customer-facing changelogs, organized and shipped where your team works. * Suppose you are on the **Marketing/Content team. In that case** , auto-generate campaign briefs from customer data, repurpose long-form content into social snippets, and AI-review draft blogs for tone, grammar, and SEO before a quick human sign-off — then publish and promote across your channels. ## **Head-to-Head: n8n, Make, Zapier** ## **What Comes Next in Automation** Automation is moving beyond simple workflows into agentic ecosystems — systems where automations talk to each other, adapt, and get stronger the more you connect. With n8n, this evolution happens naturally: a single trigger-action flow can grow into a network of agents that share context, refine themselves, and multiply value. That’s the network effect applied to automation. As this shift happens, your role changes too. You’re not just a “workflow builder” anymore — you’re the architect of an adaptive system. With n8n’s open design and first-class code support, you decide when humans step in, how agents interact, and where new automations can unlock the most impact. And here’s the twist: the smarter your workflows get, the more human your work becomes. Instead of grinding through repetitive tasks, you’re steering, applying judgment, and designing feedback loops that keep the whole system resilient. ## **In Summary** With n8n, the repetitive stuff takes care of itself — updating spreadsheets, sending emails, summarizing calls, chasing follow-ups, not even this much. You can now execute complex workflows, code, and logic, and more, in a new, cleaner, modular way. That leaves you free to focus on strategy, creativity, and direction. This isn’t just about saving time; it’s about multiplying output with less effort. And it’s already happening. If you’re not experimenting with n8n, you’re already behind. Start small. Automate one thing, then. Let your setup scale as your needs grow. Sure, sometimes agents or nodes fail — and you’ll fix them. But that beats spending hours on tasks that should run themselves. Because brittle systems create busy people. Flexible systems — the kind you build in n8n — create space. The future of work isn’t about replacing people. It’s about working smarter. The tools are here. n8n is one of them. If you're not automating yet, you're working too hard. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Pratik brings together AWS cloud expertise and AI-driven approaches to enhance systems and operational resilience. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Optimizing costs while maintaining performance in the dynamic world of cloud computing is a perpetual challenge for businesses leveraging AWS infrastructure. Among the array of AWS cost savings strategies available, effectively managing AWS Reserved Instances (RIs) is a powerful way to achieve significant savings. However, manual reserved instance management can be cumbersome and time-consuming. Enter automation – the key to unlocking the full potential of AWS reserved instance management. Read along as we talk about the ## **Challenges of AWS Reserved Instance Management** * ### **Inaccurate Planning and Purchasing** Inaccurate planning and purchasing can significantly affect an organization's cloud cost optimization efforts. Firstly, it can lead to overprovisioning, where resources are procured in excess of actual requirements, resulting in wasted spending. Conversely, underestimating resource needs can lead to underutilization, where purchased resources remain idle or underused, still incurring costs. Suboptimal resource allocation may occur, with certain workloads not assigned to the most cost-effective resource types or pricing models. This inefficiency can result in higher-than-necessary costs. Additionally, inaccurate planning makes budget control challenging, as unexpected costs can lead to budget overruns and financial strain. Moreover, it hampers the organization's ability to forecast future cloud spending accurately, hindering long-term budgeting and strategic decision-making. * ### **Uncertainty in Purchase Decisions** Uncertainty in Additionally, organizations may face challenges from a limited understanding of AWS RI offerings and how they align with their specific workload requirements. This lack of clarity can lead to indecision and delays in RI purchases. Consequently, organizations may miss out on fully leveraging the cost advantages and potential savings that RIs offer. * ### **Operational Overhead while Managing RIs** Procuring RIs involves careful planning to Activities like procurement, adjustment, and liquidation of reservations demand meticulous coordination and supervision, making the process of tracking and updating RIs time-consuming and resource-intensive. Despite the AWS cost savings and flexibility offered by ## **How Can Automation Help Effectively Manage AWS Reserved Instances?** * ### **Streamlining RI Identification & Matching** Automated reserved instance management streamlines the process of AWS RI identification and matching. Powered by AI engines, they autonomously analyze workload patterns to identify the most appropriate RIs for These solutions eliminate manual analysis and decision-making by leveraging historical usage data and machine-learning algorithms. They can detect workload changes, forecast resource requirements, and accurately match RIs to instances. This automation significantly enhances RI identification and matching efficiency, saving organizations valuable time and resources. * ### **Maximizing AWS RI Utilization** These platforms empower organizations to make informed decisions, optimize RI usage, and realize substantial AWS cost savings. However, many platforms rely exclusively on the AWS RI marketplace for RI transactions, restricting their capabilities to EC2 instances and limiting the scope of seamless reserved instance management for organizations. * ### **AWS Cost Savings and Operational Efficiency** Automated systems offer significant AWS cost savings and operational efficiency, among their primary benefits. Organizations can guarantee efficient RI utilization and achieve * ### **Reduction in Human Error** Automation drastically minimizes the risk of human error inherent in manual reserved instance management. Through leveraging advanced AI capabilities, organizations can eradicate the guesswork and subjectivity inherent in RI identification and matching. The system autonomously analyzes workload patterns, compares them with historical data, and makes data-driven decisions to optimize RI allocations. ## **Specific Functionalities of Automated Reserved Instance Management Tools** * ### **Automated AWS RI Purchasing and Renewal Recommendations** Utilizing historical usage data and predictive analytics, automated reserved instance management tools recommend the most cost-effective RI purchases and renewals based on workload patterns and future demand projections. * ### **Real-time RI Utilization Monitoring and Alerts** Continuous monitoring of RI utilization allows teams to identify underutilized instances and take proactive measures to optimize resource allocation. Automated alerts notify stakeholders of potential AWS cost-saving opportunities or instances of suboptimal utilization. * ### **Automated RI Rightsizing and Optimization** Automated reserved instance management tools identify opportunities for rightsizing and optimization by analyzing usage patterns and performance metrics. They recommend adjusting RI attributes such as instance type, size, and term duration to match workload requirements more accurately. ## **Introducing CloudKeeper Auto: Zero-touch, AI-based platform for AWS Reserved Instance management** At CloudKeeper, we understand the importance of maximizing AWS cost savings and operational efficiency in the cloud. That's why we've developed CloudKeeper Auto – a comprehensive solution for automating AWS CloudKeeper Auto ensures that organizations get the maximum savings on their AWS usage. Its AI-powered automation capabilities and guaranteed buyback of unused RIs ensure AWS cost savings and financial security. Unlock the full potential of your AWS Reserved Instances with CloudKeeper Auto and experience the power of automagically savings. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 AWS Reserved Instances Buying Guide: Common Pitfalls and Essential Considerations Your strategy guide to making informed AWS Reserved Instance (RI) purchases. Know the common mistakes and prioritize essential considerations for maximizing cost-efficiency. By Sushil Chandra 04 Oct, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents Audit logs in ## **Problem Statement** One of our clients needed better visibility into their BigQuery usage, which was a major cost driver. Instead of going through a tedious manual setup, we built an automated solution that collects audit logs for BigQuery across the organization and sends them to a centralized BigQuery dataset in our project. ## **Why Centralize Audit Logging** Centralized logs in BigQuery provide a unified source across projects: * Enable faster SQL queries * Simplify compliance checks and power dashboards that detect trends and anomalies - without manual data aggregation. ## **Challenges of Manual Configuration** As enticing as this sounds, manually enabling GCP audit logs involves multiple steps—adjusting IAM settings, enabling APIs, creating datasets, setting up log sinks, and assigning sink permissions. So obviously, this process is slow, error-prone, and hard to scale across multiple projects or clients. But here is the full proof solution! ## **Solution: Automated Audit Logs Enablement** To streamline this, we developed a Python script that: * Enables audit logging for BigQuery Analytics Hub at the org level. * Creates the BigQuery dataset if it doesn't exist. * Sets up a log sink with filters specific to BigQuery. * Outputs the sink’s writer identity so we can assign it write access. * Outputs the sink writer identity so it can be granted BigQuery write access. ## **Setup Instructions** Before running the script, make sure to install the required Python packages: **Download the Script** You can download the full automation script from my GitHub repository: **Configuration** After downloading the script, open the audit_log_to_bigquery.py file from the repository and update the following variables at the top of the script with your specific project and organization details: ## **Running the Script** We then execute the script using: **The script:** * Enables audit logs for the Analytics Hub API. * Creates the dataset if missing. * Sets up or updates the log sink. * Prints the sink's writer identity. Finally, we have manually granted the **roles/bigquery.dataEditor** role to this identity so that it can write logs to our BigQuery Dataset. ## **How can you make this solution work for your use case?** This setup isn't limited to BigQuery. By updating the sink’s filter, we can collect logs from other services **(e.g., resource.type="gcs_bucket")** or combine multiple filters for broader visibility. It’s reusable across different clients or environments. Allowing audits across various important services and their visualization. ## **Conclusion** Automating audit log collection has helped us simplify monitoring, ensure compliance, and deliver real-time insights into BigQuery usage to our real client base. But most of all, it ensured best practices are not just idealistic approaches, but realistic rituals! For more information on Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Kanishka specializes in Google Cloud Platform (GCP) and architecting automation solutions that simplify, scale, and secure cloud workloads. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * * * * * * I am looking for blogs on Automation Cloud Cost Management AWS EDP AWS Services Cloud Cost Analytics Cloud Cost Optimization DevOps FinOps Strategy RI Management Kubernetes Generative AI Explained: Concepts, Tools & Important Use Cases A clear, practical guide to Generative AI covering core concepts, future trends, leading tools, and real-world industry applications. By Team CloudKeeper 20 Nov, 2025 Automate Beyond Limits with n8n: Your Open-Source Automation Powerhouse This blog will help you gain a working understanding of automating with n8n through a practical example and a comparison with Make and Zapier. By Pratik Singh 04 Nov, 2025 5 Common Mistakes to Avoid in AWS Auto Scaling Groups AWS Auto Scaling Groups (ASG) adjust EC2 capacity automatically, maintaining your infrastructure effectively. Learn here the 5 common mistakes you should avoid. By Rachana Kumari, Aditya Sinha 31 Aug, 2023 How to Maximize Cloud Cost Efficiency by Utilizing Automation and Scripting? Automation and scripting can be powerful tools for optimizing cloud costs. This blog post will show you how to use these techniques to significantly reduce your cloud bill and improve resource utilization. By Satyam Negi 25 Aug, 2023 Cost Optimization with AWS Auto Scaling: Architectural Best Practices and Strategies Guide to AWS Auto Scaling to maximize cost-effectiveness. Learn architectural best practices and strategies to maximize resources, improve output, and reduce costs. By Arpit Shah 11 Aug, 2023 How to save money on AWS using EC2 Auto Scaling Groups Features? Discover strategies to effectively save money using EC2 Auto Scaling Groups. Explore strategies to optimize EC2 expenses and achieve significant savings while maintaining performance and scalability. By Team CloudKeeper 11 Aug, 2023 How to Automate AWS Resource Optimization with DevOps Tools? Learn how to Streamline AWS Resource Optimization Using DevOps Tools. Discover efficient strategies to enhance performance, reduce costs, and boost productivity. By Atishay Jain 09 Aug, 2023 AWS EC2 Cost Optimization: Right-Sizing and Instance Selection Tips Discover how right-sizing and instance selection can be an effective AWS cloud cost-reduction strategy for your system. By Ajay Jha 21 Jul, 2023 Managing AWS Reserved Instances with Automation and DevOps Tools Learn how to resolve the practical challenges in AWS Reserved Instance Management with the help of Automation and DevOps Tools. By Aanchal Sharma 14 Jun, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents In today's digital age, businesses worldwide are riding the wave of cloud technology, with Amazon Web Services (AWS) leading the charge. The magic of AWS lies not just in its power to fuel innovation, speed, and scalability. It's also in its promise of freedom from the constraints of long-term commitments, be it data-center hardware or software architecture choices. It also helps companies to free up their resources, which could be focused on new innovations and pushing their boundaries. However, there is a growing concern among businesses regarding cloud cost optimization. When companies are operating at scale, the cost of the cloud could result in a staggeringly high infrastructure bill, pushing executive leadership across organizations to even think of drastic measures like complete repatriation to on-premise data centers. ## **The Price of Freedom and Flexibility** Typically, the narrative of ‘cloud is great’ runs on the superpower of flexibility. With cloud service providers like AWS, the principal benefits that businesses expect to derive are on-demand capacity, access to new geographies, and We have taken the liberty to fondly name this the **'AWS Flexibility Tax'.** When businesses scale, this additional price tag on ‘freedom’ to spin up resources as and when needed could eat into the total revenues and even be translated into unlocked market capitalization. Even with committed-spend programs, it is not easy to tackle this challenge unless a company achieves 100% accuracy on their future usage predictions with the cloud FinOps tools. In a recent study, most companies reported that they exceeded their committed spend, switching them over to buying resources on-demand, incurring additional expenses and burning a hole in their pockets. ## **The Silver Lining** With all these Here's the silver lining: you can dodge this Flexibility Tax, continue to reap the full benefits of AWS, and you can do it all with a bit of help from your friend - CloudKeeper. CloudKeeper offers a comprehensive suite of AWS FinOps & Cost Optimization solutions tailored to meet the unique needs of different customer segments. With CloudKeeper by your side, be rest assured that cloud cost will remain a first-class metric of business performance, and you will achieve most, if not all, of your The top 3 benefits that CloudKeeper provides are: * ### **RI like pricing on compute resources** While Reserved Instances cost significantly less than On-Demand Instances, it is often a trade-off between flexibility and cost. In exchange for reduced costs, organizations must agree to large-volume and long-term commitments. The most compelling benefit of CloudKeeper is that you get RI-like pricing on compute resources without getting into any long-term commitments of any kind. CloudKeeper does the heavy lifting associated with making RI commitments so that you can continue to use all your compute resources with 100% flexibility without any lock-in. Also, CloudKeeper provides a 100% buy-back guarantee in case of any unused commitments. * ### **Advanced Analytics, Reports & Recommendations around Cost optimization** With their proprietary AWS Cost Analytics Platform, CloudKeeper gives you access to real-time, * ### **FinOps Consulting & Support** Backed by a team of 300+ AWS Certified Cloud Experts, CloudKeeper offers you end-to-end cloud FinOps support to optimize your entire infrastructure. This includes periodic reviews of your architectural designs, consulting and guidance for adopting new services or at the occurrence of any outages/incidents, business reviews, 24x7 support, and anything and everything that would help you deliver better AWS cost reduction. ## **The Power of Collaborations** With a Cloud FinOps Partner like In essence, cloud is the perfect choice for innovation, agility, and business expansion. Expert FinOps solution providers like CloudKeeper can help you navigate the cloud cost maze easily without compromising on performance and flexibility. They assist you in effectively managing your cloud infrastructure while helping you tackle the burdensome 'AWS Flexibility Tax,' by bringing in optimization, optimization, and more optimization! Achieve all your cloud cost optimization goals with CloudKeeper by your side. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Organizations use different architectural models (Serverless, Microservices, and Monolithic) to deploy their workloads on the cloud and implement the auto-scaling feature along with it, anticipating significant cloud cost savings. But auto-scaling by itself is an ‘overrated’ functionality and doesn’t result in effective cloud cost reduction, unless done right. Allow us to share a customer story that reinforces this notion and sheds light on the importance of proper implementation. For this particular customer, we were planning to initiate a Savings Plan for AWS cost reduction and before purchasing it, we wanted to understand how their hourly spending varied throughout the day, weeks, and months. AWS savings plan recommendations provide excellent insights based on the different configurations available, payment options, and data set duration (7, 30, or 60 days), but we wanted to have a better understanding of their AWS stack and then make the decision on how much USD/Hour commitment should we make. This was quite difficult for us because of multiple reasons like lesser traffic on the platform, and additional cloud cost savings threads like downgrading instance types, and moving them to the latest generation. Before getting into further detail, let us provide more context about the workloads running on the customer’s AWS setup. They have both monolithic (Magento stack) applications and microservices (React, Springboot, Django) deployed in AWS and aggressively use both on-demand and spot instances in the production environment. To make sure that we were committing the right dollar value for the AWS savings plan, we wanted to review our EC2 capacity needs throughout the day, to better Below is the screenshot of the Grafana dashboard with the initial data: In addition to that, we also added the flexibility to choose from multiple auto-scaling groups using a drop-down. This visualization plots the graph for on-demand, spot, and total EC2 count for that auto-scaling group. After analyzing the data for 1 week, we were surprised to see that even after using multiple auto-scaling groups, the number of servers remains consistent throughout the period of 1 week resulting in no significant * In a few of the auto-scaling groups, there were no scale-down policies attached, because of which, the servers were not turning off during the lean hours. * In a few of the auto-scaling groups, ineffective scaling policies were implemented i.e. auto-scaling was implemented on the high CPU, but workloads were more memory intensive. * One of the legacy (Magento stack) workloads were used to run the majority of the EC2 instances in the auto-scaling group. But we were not leveraging scaling policies because the initial uptime of the servers with code sync was very long. And we used to play safe here by Do these findings feel relatable? They might. So, we ended up optimizing the above-mentioned inefficiencies to enhance the AWS cost reduction results, by adopting target tracking scaling policies (request) for most of the workloads. For legacy workloads we initially started using scheduled scaling to immediately reap cloud cost savings. And in the longer run, we started using AWS auto-scaling group warm-up pools to reduce the boot-up times. Below is the screenshot of the same dashboard after making the relevant changes, which helped us to turn off around 25-30 servers during the lean hours. We could also address and resolve all the existing issues related to auto-scaling. Hence, it is important to implement auto scaling the right way, which would not only make your workload more scalable but also ensure you take true advantage of the public cloud and achieve substantial cloud cost savings. Additionally, we would also like to encourage you to stay up to date on the latest features launched by AWS to make your workloads more efficient. As and when you scale your cloud environment, implementing auto-scaling might get even more confusing. An experienced cloud FinOps partner like CloudKeeper could help you tackle this challenge and guide you through the best practices. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Generative AI Explained: Concepts, Tools & Important Use Cases A clear, practical guide to Generative AI covering core concepts, future trends, leading tools, and real-world industry applications. By Team CloudKeeper 20 Nov, 2025 Automate Beyond Limits with n8n: Your Open-Source Automation Powerhouse This blog will help you gain a working understanding of automating with n8n through a practical example and a comparison with Make and Zapier. By Pratik Singh 04 Nov, 2025 5 Common Mistakes to Avoid in AWS Auto Scaling Groups AWS Auto Scaling Groups (ASG) adjust EC2 capacity automatically, maintaining your infrastructure effectively. Learn here the 5 common mistakes you should avoid. By Rachana Kumari, Aditya Sinha 31 Aug, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Buckle up, cloud dwellers, because the AWS Reserved Instance (RI) landscape is taking a turn! If you own Discounted RIs, you might have received an email from AWS which looked something like this - _“ AWS does not permit the resale of RIs obtained through a discount program (per AWS Service Terms 5.5)._ _We are extending a compliance period to give customers time to move their RI’s to come into compliance with AWS Service Terms._ _During this time, the customer may list any RIs (even if the RIs received a discount) purchased before 1-Oct-2023, on the Amazon EC2 Reserved Instance Marketplace for sale through 15-Jan-2024._ _However, the compliance window will close, and after 15-Jan-2024, customers may no longer have any listings and/or sales of RIs purchased via a discount program on Amazon EC2 Reserved Instance Marketplace.”_ **So What Does This Mean?** **AWS has announced an RI Resale Ban and will not permit the resale of Reserved Instances obtained through a discount program,** from Jan 15th, 2024. However, if you possess discounted RIs purchased before 1st Oct 2023, you can still list them on the AWS RI Marketplace till Jan 15th, 2024. While this might initially be met with some skepticism or disappointment, it's crucial to assess the implications and understand how it may or may not affect your ## **Understanding Discounted RIs: A Deep Dive** Before we delve into the "why" behind the ban, let's clarify what constitutes a "discounted RI." These are Standard RIs with an additional customer-specific discount applied above and beyond the standard discount rate. **Volume Discounts:** Awarded for committing to a significant amount of RI usage upfront, these discounts incentivize bulk commitment and resource planning. Discounts begin at 5% of nominal AWS RI pricing and are proportional to the volume of commitments. **Private Pricing:** Negotiated directly with AWS, these agreements offer tailor-made discounts based on specific usage patterns and commitments. When a customer with an additional discount assigned to their account purchases an RI, it gets converted to a discounted RI and lives in their account. This RI could be transferred to other customers via the RI marketplace, until recently. ## **Why AWS Announced a Reselling Ban?** Even though the RI Resale ban might seem like a drastic change, this restriction already existed in Section 5.5 of the AWS Terms of Services for a while now. It is now being strictly enforced for the following reasons: **Abuse of Discounts:** The resale market created an avenue for discounted RIs to fall into the hands of users who wouldn't have qualified for them directly. This potentially skewed resource allocation undermined the intended purpose of discounts and even created unfair advantages for some users. **RI Contagion:** Imagine a domino effect where a single discounted RI gets resold multiple times, each time diluting the original commitment and value. This "contagion" could destabilize **Exploiting EDP Commitments:** Some customers were using volume discounts to acquire RIs and then reselling them to offset their AWS EDP Commitment Shortfall Obligation. This essentially allowed them to escape the consequences of underutilizing resources, impacting the fairness of the These concerns have been a wake-up call for AWS to curb unfair practices in RI transactions. That’s why they began implementing RI transfer limits and have now introduced a complete RI Resale ban on the transfer of Discounted RIs. ## **The Future of Reserved Instances** While the landscape is shifting for Discounted RIs, users of Standard RIs and Convertible RIs stand unaffected. This new AWS ban does not impact their plans to purchase them directly from AWS or to trade the Standard RIs on the AWS Reserved Instance Marketplace. This might cause an increased emphasis on strategic RI planning and utilization, that helps ## **Impact on CloudKeeper and our Customers** While multiple FinOps vendors had their entire business models built on top of Standard Reservation arbitrage, CloudKeeper customers do not have to deal with the complexity of managing Reservation / AWS Savings Plan commitments and they continue to enjoy the savings with ZERO impact from this RI resale ban. How, you may ask. CloudKeeper has always helped its customers escape the complexities of long-term reservations by offering This diverse range of savings strategies and our dedication to transparent FinOps practices sets us apart and ensures rock-solid performance for our valued partners. ## **The Takeaway: Adapting to Change with Smarter Cloud Investments** While this reselling announcement may seem unexpected, it's a move toward more transparent and consistent AWS RI pricing policies. By adapting your AWS Reserved Instance strategy and optimizing your AWS infrastructure with If you need any assistance or clarifications regarding these this AWS ban, feel free to _(Full disclosure: This article represents CloudKeeper's analysis and opinions regarding new AWS regulations. It does not incorporate official Amazon statements or claim to speak on their behalf.)_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 AWS Reserved Instances Buying Guide: Common Pitfalls and Essential Considerations Your strategy guide to making informed AWS Reserved Instance (RI) purchases. Know the common mistakes and prioritize essential considerations for maximizing cost-efficiency. By Sushil Chandra 04 Oct, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents With the increasing use of cloud computing across the world, many companies that rely on it are adopting cloud cost awareness and optimization strategies to understand and manage the charges associated with their usage of different services. In this blog post, we are going to share the best practices pertaining to ## **Significance of Cloud Cost Awareness** Amazon Web Services (AWS) is extremely attractive when it comes to on-demand availability of services and the ability to deploy resources at the click of a button. And, because the ## **Most common questions asked during this process are** * Have we launched new services or workloads? * Have we scaled up a workload? * Was there any architectural change in the infrastructure? * Did someone launch new workloads for testing & forgot to hit pause? Besides, AWS provides a plethora of options to choose from and in case you accidentally choose a service for the wrong use-case you might end up spending more. Therefore, understanding different cost levers for any service will help you build a robust & To ## **Building your ecosystem of Cloud Cost Awareness** It is important to build a step-by-step plan to build an ecosystem which keeps all stakeholders aware of the costs being incurred. This plan serves as a tangible representation of the process, as well as a template for budgeting and management of costs. Some of the fundamentals that should be covered in this plan are as follows- 1. **Build an accountable chargeback mechanism:** In this phase, first ensure that you have identified and implemented a tagging strategy that adds a business context to your usage. The tagging function allows you to define keys and values which can be used to categorize, filter, and sort resources. You can tag your resources based on Application Name, Environments, Owner, Project and Cost-Center. In case you have different requirements (or) use-cases feel free to add (or) modify your tags. It might take upto 48 to 72 hours to reflect tag related data in the cost dashboard, however, soon you will find yourself spending less time in digging to understand your costs and more time in making informed decisions to control your costs based on the rich data you will receive from your tag reports. 2. **Provide a mechanism to your engineering teams to drill down into the cost:** You should provide some mechanism to the different teams which permits them to review the cost related to their resources & drill down themselves. For example,if there is a team who works on the search functionality of your front-end website, then they should have a breakdown of cost on the basis of different environments, different components & different AWS services consumed by their application. 3. **Ability to implement cost deviation alerts:** * This is a principal piece in the cost optimization exercise because this can help you identify the bugs/cost anomalies within days instead of in month end bills. The teams should be able to set up alerts based on the specific thresholds, cost deviations by a certain percentage. * Having these alerts integrated into your slack channels can further improve visibility and response times from your engineers. * AWS cost anomaly detection is a native tool that detects anomalies at a lower granularity and spend patterns and can roll-out individual alerts, daily or weekly summary. 4. **Ad-hoc measures:** Post completion of the above phases, it is time you enforce additional processes to keep everyone answerable for their workloads costs * Schedule monthly sync-ups with all the stakeholders & discuss cost trends for the last few weeks. Discuss any reasons for sudden increase/decrease in cost. Organizations that successfully manage their AWS spends usually have a clear expectation that everyone is responsible for costs. Just like any other operational metric performance, such as security, for example, each team should be required to meet cost objectives when building systems. * The common mistake that teams generally make on the AWS cloud is that they launch workloads for testing purposes and then forget about them. This results in cost in-efficiencies and is the common reason for the cost increase. Habitually, engineering teams rely on the CPU & memory utilization metrics to identify the zombie resources. This might help in most of the cases, but you need some additional metrics to further improve your findings some of which are listed below: ### ## **Conclusion** After completing all the four steps, you will have a good mechanism to identify any cost anomalies and act on them in a timely manner. This system will help you gauge cost on different parameters & help you build cost aware teams. Cost optimization is an on-going process & should be made part of your existing DevOps processes. Additionally, to make AWS cost more meaningful, customers map their AWS cost with different business metrics like orders per month, traffic served per month, transactions per month. Dividing these metrics with total AWS cost, gives them visibility into per transaction cost & helps them to compare their spendings against industry standards. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents ## **Introduction** Network Address Translation (NAT) is a crucial component in AWS environments, enabling instances in private subnets to connect to the internet or other AWS services while preventing unauthorized inbound connections. When implementing NAT in AWS/VPC, you have two options: 1. **NAT Instance:** An EC2 instance placed in the public subnet. 2. **NAT Gateway:** A managed service provided by AWS. Choosing the right solution depends on several factors, like availability, maintenance, or cost. You can refer to a detailed comparison This article will dive deep into NAT Gateway, exploring its pricing model, monitoring techniques, and strategies for cloud cost optimization. ## **Understanding NAT Gateway Pricing** NAT Gateway pricing is based on three primary factors: **1. Hourly Charge:** A fixed rate charged for each hour the NAT Gateway is provisioned and available. **2. Data Processing Charge:** Applied for each gigabyte processed through the NAT Gateway, regardless of the traffic's source or destination. **3. Data Transfer Charge:** Applied for People sometimes assume Processing charge and Data transfer charge are the same, but they are not. Data transfer charges are standard charges that AWS levies on inter-AZ, inter-region, or out to public network traffic. Data processing charges are NAT Gateway-specific charges. Let's examine two pricing scenarios to better understand these charges. **Scenario 1: Same Availability Zone** * EC2 instance in a private subnet * NAT Gateway in the same availability zone * 100 files of 1GB sent to an S3 bucket in the same region daily **Monthly charges (Mumbai region):** * NAT Gateway Hourly: $0.056 per hour * 24 hours * 30 days = $40.32. * Data Processing: $0.056 per GB * 100 GB * 30 days = $168. * Data Transfer: $0.1093 per GB * 100 GB * 30 days = $327.9 **Total: $536.22/month** **AWS Cost Optimization Tip:** Use a Gateway Type VPC endpoint for S3/DynamoDB traffic to reduce charges by 100%, in this case $208.32 savings. If you have high traffic volume in services apart from S3 or DynamoDB, consider using Interface endpoints which can save up to 80% of cost. **Scenario 2: Cross-AZ and Internet Traffic** * EC2 instances in a private subnet * NAT Gateway in a different availability zone * 500GB of data sent to an external server daily **Monthly charges (Mumbai region):** * NAT Gateway Hourly: $0.056 per hour * 24 hours * 30 days = $40.32. * Data Processing: $0.056 per GB * 500 GB * 30 days = $840. * Data Transfer (Cross-AZ): $0.01 per GB * 500 GB * 30 days = $150. * Data Transfer (To Internet): $0.1093 per GB * 500 GB * 30 days = $1,639.5. **Total: $2,669.82/month** **Cost Optimization Tip:** 1. Place NAT Gateway and EC2 instances in the same Availability Zone to avoid cross-AZ charges. (Savings = $150). 2. For high-traffic instances communicating with non-AWS resources, consider using an Internet Gateway instead of NAT Gateway if network security can be handled by security groups. (Savings = $840). 3. Or, Consider setting up PrivateLink connection using Gateway load balancing with External service (Savings = Up To 90%). ## **Analyzing NAT Gateway with CloudWatch** Amazon CloudWatch is a powerful cloud cost analysis and observability tool that provides near real-time metrics for NAT Gateway monitoring. Key metrics related to data processing include: **1. BytesInFromSource:** The number of bytes received by the NAT gateway from clients in your VPC. **2. BytesOutToDestination:** The number of bytes sent out through the NAT gateway to the destination. **3. BytesInFromDestination:** The number of bytes received by the NAT gateway from the destination. **4. BytesOutToSource:** The number of bytes sent through the NAT gateway to the clients in your VPC. These metrics help identify traffic patterns and potential issues. In normal operation: * BytesInFromSource ≈ BytesOutToDestination * BytesInFromDestination ≈ BytesOutToSource If the value for BytesOutToDestination is less than the value for BytesInFromSource or the value for BytesOutToSource is less than the value for BytesInFromDestination, there may be data loss during NAT gateway processing, or traffic being actively blocked by the NAT gateway. **AWS Cost Optimization Tip:** If all four CloudWatch metrics show zero activity for the past month, consider removing the NAT Gateway as it's likely unused. Verify this aligns with expected usage patterns before decommissioning. **Monitoring - Setting up CloudWatch Alarms:** You can ## **Analyzing NAT Gateway Logs with Amazon Athena** While CloudWatch metrics provide overall usage data, deeper insights into traffic patterns require analysis of NAT Gateway logs. These logs are part of VPC flow logs, which can be published to CloudWatch Logs or Amazon S3. For in-depth cloud cost analysis, we'll focus on using Amazon Athena to query logs stored in S3. How to understand and set up VPC flow logs can be found **Key Queries for NAT Gateway Analysis** The following queries are based on the architecture shown in Figure 3. Make sure to adjust the IP addresses and CIDR ranges if your setup differs. **Top Outgoing Traffic (EC2 to Internet):** SELECT s.sourceaddress as EC2_ip, s.destinationaddress as nat_gateway_ip, d.destinationaddress as external_server_ip, SUM(s.numbytes)/1000000000 as total_GB FROM "vpc_flow_logs" s JOIN "vpc_flow_logs" d ON s.destinationaddress = d.sourceaddress AND s.numpackets = d.numpackets AND s.numbytes = d.numbytes AND s.starttime = d.starttime AND s.endtime = d.endtime WHERE s.interfaceid = 'eni-{natgateway1}' AND s.date BETWEEN '2024-09-01' AND '2024-09-16' AND s.destinationaddress = '10.20.4.83' -- NAT Gateway IP from Figure 3 AND s.sourceaddress LIKE '10.30.%' -- Private subnet CIDR from Figure 3 AND d.destinationaddress NOT LIKE '10.%' -- External IPs GROUP BY s.sourceaddress, s.destinationaddress, d.destinationaddress ORDER BY total_GB DESC LIMIT 10; This query identifies EC2 instances in the private subnet (10.30.x.x) sending the most traffic to the internet through the NAT Gateway (10.20.4.83). **Top incoming traffic (Internet to EC2 via NAT Gateway):** This query identifies external sources sending the most traffic to your EC2 instances in the private subnet (10.30.x.x) through the NAT Gateway (10.20.4.83). SELECT s.sourceaddress as external_server_ip, s.destinationaddress as nat_gateway_ip, d.destinationaddress as EC2_ip, SUM(s.numbytes)/1000000000 as total_GB FROM "vpc_flow_logs" s JOIN "vpc_flow_logs" d ON s.destinationaddress = d.sourceaddress AND s.numpackets = d.numpackets AND s.numbytes = d.numbytes AND s.starttime = d.starttime AND s.endtime = d.endtime WHERE s.interfaceid = 'eni-{natgateway1}' AND s.date BETWEEN '2024-09-01' AND '2024-09-16' AND s.destinationaddress = '10.20.4.83' -- NAT Gateway IP from Figure 3 AND s.sourceaddress NOT LIKE '10.%' -- External IPs AND d.destinationaddress LIKE '10.30.%' -- Private subnet CIDR from Figure 3 GROUP BY s.sourceaddress, s.destinationaddress, d.destinationaddress ORDER BY total_GB DESC LIMIT 10; **Interpreting Results** * High outgoing traffic from specific EC2 instances might indicate data-intensive operations or potential data exfiltration. * Unexpected incoming traffic from external sources could reveal misconfigurations or security issues. * Patterns in traffic can guide decisions on resource placement within the VPC or the need for dedicated connections. ## **Conclusion** Analyzing NAT Gateway logs and metrics is crucial for understanding traffic patterns and implementing cloud cost optimization strategies. By following these steps, you can: 1. Identify high-traffic instances. 2. 3. Consider alternatives like VPC endpoints or Internet Gateways where appropriate. 4. Set up alerts to catch unexpected spikes in usage. Regular monitoring and cloud cost analysis will help you Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Director - Product Ronak has over 11 years of experience in building AI/ML and data products and scaling engineering teams at various startups. He was part of the early teams at Cogoport, Jugnoo, and Peak AI. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents Amazon Web Services (AWS) CloudFormation StackSets are a useful tool for deploying infrastructure at a reasonable price. It can help in aws cost management by enabling you to set up and operate CloudFormation stacks across different accounts and regions using a single template. With just a few clicks, you can provide a group of AWS resources across many accounts and regions using a tool called AWS CloudFormation StackSets. A StackSet is a grouping of AWS CloudFormation stacks that may be used to add, modify, or remove stacks across many accounts and regions using a single CloudFormation template, facilitating Here is an example of a CloudFormation StackSet template that deploys an EC2 instance across multiple accounts and regions: In this example, the CloudFormation StackSet creates an EC2 instance with the specified instance type, key pair, and AMI ID in the us-east-1 and us-west-2 regions of the `111111111111` and `222222222222` AWS accounts. The AutoDeployment section enables automatic deployment of updates to the stack instances, and the PermissionModel is set to SELF_ MANAGED to allow stack instances to be managed by the account owners. Here are some strategies for cloud cost control with CloudFormation StackSets: * **Deployment of AWS infrastructure:** You may implement aws cost management by deploying standardized infrastructure using CloudFormation StackSets across many accounts and regions. You can save time and effort managing your infrastructure by adopting standardized infrastructure, which also makes sure that your resources are uniform and compliant. For instance, you can provide standard instance types, storage settings, and network setups that satisfy the needs of your application and do away with extraneous variants that could result in resource waste and increased expenses. * **Cloud Spend Optimization using Tagging:** The ability to centrally manage your infrastructure resources with CloudFormation StackSets can help you optimize how you use them. To guarantee that your resources are being used effectively, for instance, you can use StackSets to enforce resource tagging standards, which can help you spot and get rid of any unnecessary resources. * **Cost Monitoring:** You may * **Utilize Spot Instances:** StackSets enables you to distribute Spot Instances across numerous accounts and regions, which can help you in cloud spend optimization by utilizing unused EC2 capacity. You can bid on unutilized EC2 capacity using Spot Instances and get up to a 90% discount off the On-Demand cost. Your infrastructure expenditures can be decreased by using StackSets to deploy Spot Instances to particular accounts and locations where they are most advantageous. * **Apply Cloud Cost Control Policies Across Several Accounts and Regions:** StackSets allows you to apply * **Automate AWS Resource Provisioning:** Reduce the time and effort needed to manage your infrastructure by * **Quick Deployment:** You can deploy infrastructure resources more quickly with CloudFormation StackSets than with conventional techniques, which can help you shorten your time to market and increase your agility. You may respond to shifting business needs and consumer demands more swiftly by hastening the deployment of infrastructure resources. In general, CloudFormation StackSets are an effective tool for deploying infrastructure at a reasonable price. By utilizing its features, you could perform aws cost management, use resources more efficiently, and increase the agility and dependability of your infrastructure. Understand the cloud cost levers better and receive infrastructure design guidance from AWS Certified Cloud Experts with CloudKeeper. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents ## ## **Introduction to CloudFront** Amazon CloudFront is a global content delivery network (CDN) that makes it easy to deliver websites, videos, apps, and APIs securely and at high speeds with low latency. You can use the AWS CloudFront service to reduce latency by delivering data through 400+ globally dispersed Points of Presence (PoPs) and improve security with traffic encryption, access controls, and resiliency against DDoS attacks. In addition to performance and security, CloudFront services can be used to cost optimize your AWS infrastructure in various ways. In this post, we’ll cover numerous AWS CloudFront features and best practices that can help optimize costs for some commonly deployed architectures. ## **Use CloudFront for everything – including dynamic content** Suppose you serve dynamic content via web applications or APIs hosted directly from an Elastic Load Balancer (ELB) Amazon Elastic Compute Cloud (Amazon EC2) instances, or Amazon Elastic Container Service (Amazon ECS)/Amazon Elastic Kubernetes Service (Amazon EKS) container cluster to end users on the Internet. Instead of serving the requested content directly from these resources, you can route this traffic via AWS CloudFront, configured to pass-through the content without caching it at the edge locations. This approach lets you utilize CloudFront’s Free Tier, which offers 1 TB of data transfer out to the internet, and 10 million HTTP or HTTPS requests free each month, thereby reducing your Data Transfer Out (DTO) costs. If you are using a third-party CDN while hosting your applications on AWS, you should be aware that this can be an anti-pattern from a cost perspective of data transfer. Let’s understand why – assume that you’re running a commonly-deployed web application behind Application Load Balancers (ALB) on AWS and using a different CDN instead of CloudFront. Now assume that your application is serving 10 TB of data to your users per month. If you use AWS CloudFront services as your CDN, then you’ll pay a data-transfer cost for only 9 TB because CloudFront Free Tier will cover the first 1 TB every month. Additionally, there is no data transfer cost for the data that is transferred between your origin servers on AWS, such as ALB, AWS Elastic Beanstalk, Amazon Simple Storage Service (Amazon S3), to the edge locations. However, if you use a different CDN, you’ll pay data transfer costs for 10 TB to them as per their pricing plans, as well as incur an additional data transfer cost to AWS for your data that is transferred out from your origin servers on AWS to the edge locations of the other CDN. ## **Restrict serving content to unwanted regions using CloudFront geographic restriction** Unwanted and malicious traffic can result in additional load on your resources, consume bandwidth, and increase your AWS costs. Restricting unwanted traffic at the edge before it hits your other resources can help you save on costs. For example, suppose you don’t want traffic from specific countries to hit your applications. In that case, you can use the CloudFront geographic restrictions feature to restrict access to all of the files associated with a CloudFront distribution at the country level. This can reduce the amount of traffic that your origin servers must process. Therefore, you can scale down your origin resources appropriately, resulting in cost savings. ## **Use CloudFront price classes as a metric for edge location strategy** AWS CloudFront has edge locations all over the world. The cost for each edge location varies, and thus the price varies depending on which edge location serves the requests. Price classes let you reduce your delivery prices by excluding CloudFront’s more expensive edge locations from your CloudFront distribution. Therefore, configuring the AWS CloudFront pricing class basis of application user geographies helps Figure 2: CloudFront price class options ## **Implement controls to reduce the cost of CloudFront logging** You may want to 1. Specify what percentage of requests you want to log 2. Choose to log only specific log fields 3. Enable real-time logs only for specific CloudFront caching behaviors You can configure all of this on the CloudFront logs settings as shown in the following image. Figure 3: CloudFront logging ## **Optimize cache hit ratio for non-AWS Origins** CloudFront services are often used as a content distribution layer for applications hosted outside of AWS. In these cases, optimizing the cache hit ratio can help save origin request submission costs. Cache hit ratio is the percentage of total requests that are served from the content cached at the edge locations. Take advantage of CloudFront’s customizable cache policies to improve the cache hit ratio by controlling the cache key. The cache key is the unique identifier for every object in the cache, and it determines whether a viewer request results in a cache hit. A cache hit occurs when a viewer request generates the same cache key as a prior request, and the object for that cache key is in the edge location’s cache and valid. One way to improve your cache hit ratio is to include only the minimum necessary values in the cache key. Optimize your cache hit ratio by Figure 4: CloudFront cache key settings ## **Effectively utilize AWS CloudFront compressed data caching capabilities** AWS CloudFront natively supports requesting and caching objects compressed in the GZIP or Brotli compression formats. CloudFront serves the compressed objects when the viewer’s web browsers or other clients support them and indicate their support for compressed objects with the Accept-Encoding HTTP header. Object compression helps Figure 5: CloudFront compressed data cache ## **Optimize CloudFront caching strategy to reduce cache invalidations** If you must remove a file from AWS CloudFront edge caches before it expires, then you can invalidate the file from edge caches. You’re charged for invalidation requests beyond the first 1,000 paths requested for invalidation each month. Therefore, it’s important to know some general best practices to save costs on invalidation. We recommend that you control caching using the Figure 6: CloudFront TTL options If you need to remove a file from CloudFront edge caches before it expires, you can use file versioning to serve a different version of the file with a different name. This allows you to control which file a request returns, even if the user has a version cached locally or behind a corporate caching proxy. If you invalidate the file, the user may continue to see the old version until it expires from those caches. Versioning is a less expensive option, as you only have to pay for CloudFront to transfer new versions of your files to edge locations in the case of non-AWS origins, without having to pay for invalidating files. ## **Optimize Lambda@Edge execution costs by rightsizing AWS Lambda runtime** The cost of running Lambda@Edge for your workload is determined by three factors: the number of executions, the duration of execution of the AWS Lambda function, and the memory usage (combined as Gb/s). Your choice of Lambda runtime has a direct impact on the cost. Generally, compiled languages run code more quickly than interpreted languages, but they can take longer to initialize. For small functions with simple functionality, often an interpreted language is better suited for the fastest total execution time, and thus the ## **Conclusion** This blog explains some best practices that can help you optimize your costs for some commonly deployed architectures on AWS by leveraging _With_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents AWS CloudWatch is an Amazon Web Services tool that collects, stores, and monitors data and metrics from various AWS resources and applications in real-time. AWS CloudWatch can help you detect and diagnose issues, troubleshoot problems, and optimize system performance. It provides users with dashboards, alarms, and metrics to visualize and ## **AWS CloudWatch Pricing Breakdown** ### **1. AWS CloudWatch Metrics:** AWS CloudWatch charges for the number of custom metrics that are collected and stored, as well as the frequency of data points. The first 10,000 custom metrics are free each month. After that, the pricing starts at $0.30 per month per metric for up to 100,000 metrics, and then decreases as the number of metrics increases. The pricing is based on the highest number of custom metrics used in a month. AWS also offers a feature called "Detailed Monitoring" for EC2 instances and RDS databases, which provides more frequent metric data (one minute intervals) for an additional cost. For ### **2. AWS CloudWatch Logs:** AWS CloudWatch Logs charges for the amount of data ingested, stored, and analyzed. Data ingested refers to the amount of log data that is sent to AWS CloudWatch Logs, while data stored refers to the amount of log data that is stored in AWS CloudWatch Logs. Data analyzed refers to the amount of log data that is scanned for patterns, insights, or anomalies using features like CloudWatch Contributor Insights. For data ingested, the price is $0.50 per GB ingested. For data stored, the price is $0.03 per GB per month. For data analyzed with CloudWatch Contributor Insights, the price is $0.30 per GB of data analyzed. In addition to these charges, there are additional costs for using AWS CloudWatch Logs features like real-time log processing with Lambda, and data transfer costs when data is accessed from a different AWS region. ### **3. Alarms:** AWS CloudWatch charges for the number of alarms created and the number of times they are evaluated each month. The first 10,000 alarm evaluations each month are free. After that, the cost is $0.10 per alarm per month. Alarms can be set up to monitor metrics and logs, and can trigger actions like sending notifications, running Lambda functions, or ### **4. CloudWatch Events:** AWS CloudWatch Events is a service that enables you to respond to system events with automated actions. The pricing for AWS CloudWatch Events is based on the number of events ingested, as well as the number of rules and targets used. The first 1 million events ingested each month are free, and after that, the cost is $1.00 per million events. There is also a charge for rules and targets, which is $1.00 per rule per month and $0.10 per target per month. ### **5. CloudWatch Contributor Insights:** AWS CloudWatch Contributor Insights is a feature that helps you identify trends, patterns, and outliers in your log data. The pricing for Contributor Insights is based on the amount of data analyzed, and starts at $0.30 per GB of data analyzed. There are no charges for using the Contributor Insights feature itself. ### **6. CloudWatch Synthetics:** AWS CloudWatch Synthetics is a service that enables you to monitor application endpoints, workflows, and APIs. The pricing for CloudWatch Synthetics is based on the number of canaries (tests) that are created, as well as the frequency of tests. The first 100 canary runs each month are free, and after that, the cost is $0.0012 per canary run. There is also a charge for running tests in specific AWS regions. ## **Best Practices for AWS CloudWatch Metrics Cost Management** ### **1. Choose Metrics wisely** The first step in managing AWS CloudWatch Metrics costs is to choose which Metrics to collect. Collecting Metrics for every AWS resource and service can quickly become expensive, especially if you are using high-resolution monitoring. To optimize AWS CloudWatch Metrics costs, choose Metrics selectively, for critical resources or during specific periods when more granular insights are needed. You can also use AWS CloudWatch Metrics filters to aggregate and analyze only the metrics that are relevant to your use case, reducing the amount of data ingested and stored in AWS CloudWatch. ### **2. Use high-resolution monitoring selectively** By default, AWS CloudWatch Metrics are collected every 5 minutes, but you can enable high-resolution monitoring to collect Metrics at one-minute intervals. High-resolution monitoring can provide more granular insights into system performance but comes at a higher cost. To optimize AWS CloudWatch Metrics costs, consider enabling high-resolution monitoring selectively, for critical resources or during specific periods when more granular insights are needed. You can also use AWS CloudWatch Metrics filters to aggregate and analyze only the Metrics that are relevant to your use case, reducing the amount of data ingested and stored in AWS CloudWatch. ### **3. Set up Metric Filters** Metric Filters allow you to extract Metric data from your log data. This allows you to create custom Metrics, which can provide more specific and relevant insights into your system performance. Using Metric Filters can also reduce the amount of data ingested and stored in AWS CloudWatch by only collecting the Metrics that are relevant to your use case. To optimize AWS CloudWatch Metrics costs, set up metric filters selectively, for critical resources or during specific periods when more granular insights are needed. You can also use Metric Filters to extract only the Metrics that are relevant to your use case, reducing the amount of data ingested and stored in CloudWatch. ### **4. Use AWS CloudWatch Alarms selectively** AWS CloudWatch Alarms allow you to monitor and respond to changes in system performance and resource utilization. Alarms can trigger automated actions, such as sending notifications or scaling resources. However, alarms can also be a significant cost driver if not used selectively. To optimize AWS CloudWatch Alarms costs, create Alarms selectively, for critical resources or during specific periods when more proactive monitoring is needed. You can also adjust Alarm thresholds and evaluation periods to reduce false positives and optimize alarm actions. ## **Best Practices for AWS CloudWatch Data Storage Cost Management** ### **1. Choose the right data retention period** The first step in managing AWS CloudWatch Data Storage costs is to choose the right data retention period for your Logs, Metrics, and Traces. Data retention refers to how long your data is stored in CloudWatch before it is automatically deleted. To optimize AWS CloudWatch Data Storage costs, choose the data retention period carefully, based on your compliance and regulatory requirements, as well as your business needs. For example, you may need to retain Logs data for a longer period for auditing purposes, but Metrics data may not need to be retained for more than a few weeks. ### **2. Use log data lifecycle policies** AWS CloudWatch Logs data can be managed using log data lifecycle policies. These policies allow you to automate the deletion of Logs data based on age or size. For example, you can configure a policy to delete Logs data that is older than 30 days or larger than 10 GB. To optimize AWS CloudWatch Data Storage costs, use log data lifecycle policies to automate the deletion of Logs data that is no longer needed. This can help reduce storage costs and ensure that you are only storing the Logs data that is relevant to your use case. ### **3. Use metric data expiration** AWS CloudWatch Metrics data can be configured to expire automatically after a specified period. This allows you to automatically delete Metrics data that is no longer needed, reducing storage costs. To optimize AWS CloudWatch Data Storage costs, use metric data expiration to automatically delete Metrics data that is no longer needed. This can help reduce storage costs and ensure that you are only storing the Metrics data that is relevant to your use case. ### **4. Use data archiving** AWS CloudWatch Logs data can be archived to To optimize AWS CloudWatch Data Storage costs, use data archiving selectively, for Logs data that needs to be retained for compliance or auditing purposes. Archiving Logs data to ### **5. Use CloudWatch Contributor Insights selectively** Contributor Insights analyzes log data to identify patterns, trends, and outliers. However, this feature can also be a significant cost driver for AWS CloudWatch if not used selectively. To optimize AWS CloudWatch Data Storage costs, use AWS CloudWatch Contributor Insights selectively, for Logs data that needs to be analyzed in detail. You can also adjust Contributor Insights filters to reduce the amount of log data analyzed and ## **Best Practices for CloudWatch Logs Cost Management** ### **1. Choose the right log group structure** One of the most critical factors in managing AWS CloudWatch Logs costs is the log group structure. A log group is a collection of log streams that share the same retention policy, and the structure of log groups can significantly impact your costs. To optimize AWS CloudWatch Logs costs, choose the right log group structure based on your logging requirements. Consider using a hierarchical structure that separates logs by application, environment, and component. This will make it easier to manage your logs and ensure that you are only storing the logs that are relevant to your use case. ### **2. Choose the right log retention policy** AWS CloudWatch Logs data retention policy refers to how long the log data is stored in CloudWatch before it is automatically deleted. Choosing the right retention policy can help you avoid unnecessary expenses. To optimize AWS CloudWatch Logs costs, choose the right log retention policy based on your compliance and regulatory requirements, as well as your business needs. For example, you may need to retain logs data for a longer period for auditing purposes, but some logs may not need to be retained for more than a few weeks. ### **3. Use log data compression** AWS CloudWatch Logs data can be compressed to reduce storage costs. Compression reduces the size of the log data, which can significantly reduce storage costs. To optimize AWS CloudWatch Logs costs, use log data compression to reduce the size of your logs data. This can help reduce storage costs and ensure that you are not paying for unnecessary storage. ### **4. Use CloudWatch Logs Insights selectively** AWS CloudWatch Logs Insights allows you to analyze your logs data using queries. However, this feature can also be a significant cost driver if not used selectively. To optimize AWS CloudWatch Logs costs, use AWS CloudWatch Logs Insights selectively, for logs data that needs to be analyzed in detail. You can also adjust Insights filters to reduce the amount of log data analyzed and optimize the cost per GB of data analyzed. ## **Conclusion** In conclusion, optimizing costs for AWS CloudWatch Logs and AWS CloudWatch Metrics requires a combination of careful planning, best practices, and ongoing monitoring. It is important to choose the right log group structure and retention policy, use data lifecycle policies and compression, and selectively use AWS CloudWatch Logs Insights to reduce costs. Additionally, using tools like CloudWatch Metric Filters, alarms, and dashboards can help you proactively monitor and manage your metrics and logs data, ensuring that you are only storing and analyzing the data that is relevant to your use case. By following these strategies, you can _If you are looking for a trusted partner in your journey of_ _and maximize the value of your cloud investments,__now and see how_ _can help._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents In the ever-evolving world of cloud computing, managing costs efficiently is a critical concern for organizations leveraging Amazon Web Services (AWS). AWS offers a plethora of tools and features to help organizations allocate and optimize their costs. Among the essential practices for effective AWS cloud cost management, strategic tagging stands out. In this blog, we will delve into the intricate details of tagging's importance for AWS cost allocation and optimization. We will explore comprehensive best practices for AWS tagging, different tagging strategies for cost allocation, and strategies for cost optimization in AWS through effective tagging. ## **What is AWS Cost Allocation?** Cost allocation in AWS refers to the process of attributing costs to specific resources or cost centers within an AWS infrastructure. It provides insights into the distribution of expenses across different services, allowing organizations to gain a deeper understanding of their cost drivers and optimize their resource utilization accordingly. ## **What is AWS Cost Optimization?** ## **What answers right tagging can provide you?** 1. Direction where AWS budgeting is going 2. Analysis of resource usage for forecasting purpose 3. Find hidden areas of cost to eliminate unused resources 4. Chargeback - Relate utilization & expenses to business units, departments and projects 5. To analyse resources that require updating 6. Security and compliance related tags can help in assessment of overall security and also providing a framework for who is authorized/unauthorized to work on resources. Eg. How many servers are of old operating system, How many services are being monitored? 7. To identify the most expensive feature of product 8. The most expensive project in organization vs its worth 9. Which area the customers are more interested into 10. Per customer cost of the product ## **Here are some of the best practices** **1. Establishing Tagging Standards** * Identify the right tags for your resources keeping in mind the purpose why you want to include the specific tag key * Discuss within your cross functional teams and come up with standard tags * Standardise the number of tags, their naming convention. Avoid duplications and inconsistencies * Publish the tagging standards in the organization so that people are aware * Tag resources to satisfy all criteria 1. **Name** eg. prod---app1 2. **Project** eg. project-a, project-b 3. **BusinessUnit** eg. engineering, finance, analytics 4. **ServiceTier** eg. web, database, cache 5. **Application** eg. nginx, paymentservice, login, dashboard 6. **Schedule** eg. 24x7, 6 am - 9 pm UTC 7. **Environment** eg. dev/qa/prod 8. **BackupRetention** eg. 365, 12 (with standard time unit) 9. **Backup** eg. True/False 10. **Compliance** eg. true/false (if doesn’t meet any of the security standards or can be broken further to ComplianceDataAtRestEnabled, ComplianceTerminationProtectionEnabled, ComplianceHasSecurityAgentInstalled) 11. **CostCentre** eg. team:finance, team:engineering, team:digitalMarketing, team:module-A 12. **IsMonitored** eg. true/false 13. **Expiry** eg. 30-07-2024 14. **Owner** eg. team-platform-engineering@company.com 15. **ManagedBy** eg. terraform, cloudformation, awscli, toolname **2. Automation for Tagging** Leveraging automation tools and services simplifies and streamlines the process of applying tags to resources. AWS provides services like AWS CloudFormation, AWS Config Rules, AWS Lambda, Resource Groups, Tag Editors, AWS CLI etc which enable organizations to automate tagging workflows. Automation ensures accurate and timely application of tags, reducing human error and saving time. This needs to be ensured that any automation tool being used is well aware of standard tags to be configured. **3. Tagging Policy and Governance** Formulating tagging policies and guidelines is essential for enforcing compliance and consistency throughout the AWS cloud cost management practices. These policies define the required tags for different resource types and specify the consequences of non-compliance. By establishing clear policies and permissions, organizations can ensure that all resources are appropriately tagged, adhering to tagging standards and facilitating effective cost allocation. The practices should ensure: * Restrict who can access a resource * Receive notifications automatically when tags are not proper or missing * Avoid alert fatigue by limiting the number of alerts * As per need basis, review, revise, and realign tagging best practices * Put deny policies in launching the resources if they are not compliant **Let's take a look at various tagging strategies and how they align with tags grouping** ## **Cost Optimization Reporting and Analysis** You can use AWS Cost Explorer and detailed billing reports to break down AWS costs by tags. Tags can include business or technical dimensions, allowing you to associate costs with different aspects such as cost centers, projects, applications, environments, or compliance programs. Leveraging AWS Cost Explorer and Cost and Usage Reports, organizations can You can refer AWS standard tagging guidelines ## **Conclusion** Effective tagging strategies play a crucial role in AWS cost allocation and optimization. By following best practices such as establishing consistent tagging standards, leveraging automation for tagging, and implementing tagging policies and governance, organizations can Resource-based tagging, cost center-based tagging, environment-based tagging, and project-based tagging facilitate precise cost allocation and provide valuable insights for decision-making. Usage-based tagging, expiration-based tagging, right-sizing with tagging, and cost optimization reporting help identify and address cost optimization opportunities. By adopting these strategies, organizations can achieve better cost efficiency, maximize the value of their AWS investments, and drive overall financial success. CloudKeeper _helps you scale your AWS infrastructure and cloud applications, while delivering_ _on your entire AWS bills up to 25%. Sounds too good to be true?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents AWS is the most popular cloud platform utilized by users all around the world for its wide range of services that can help businesses of all sizes achieve their goals. However, like any other cloud platform, AWS can be costly if not used efficiently. In this article, we will delve into most effective AWS cost optimization strategies that can help you maximize your AWS experience while saving money. ## **Optimize Application Architecture** Optimizing your application architecture is a critical component of cost optimization on AWS. Even if you implement all the other best practices for cost optimization, if your application architecture is not designed for efficiency, you will incur unnecessary costs. A poorly optimized application architecture can lead to inefficient resource usage, which in turn can lead to higher costs. * Implement a microservices architecture for efficient resource usage (e.g., ECS, EKS). * Utilize caching to reduce compute costs (e.g., CloudFront, Redis). * Optimize data storage & use data compression and encryption techniques to reduce storage costs ( Amazon S3, Amazon EBS, and Amazon Glacier etc.) * Use serverless computing as per the application requirements. * A well-architected resource utilization is a key ## **AWS Pricing Calculator** AWS Pricing Calculator is a tool that can help you estimate the cost of your AWS usage and optimize your costs. Below are some of the most effective AWS cost optimization techniques: * **Estimate costs for new applications:** Before you deploy on AWS, you can use the AWS Pricing Calculator to estimate the costs. This will help you choose the most affordable instance types and storage options and ensure that you stay within your budget. * **Compare costs across regions:** The AWS Pricing Calculator allows you to compare costs across different regions. This will help you choose the most economical region for your application, based on factors such as data transfer costs, instance costs, and storage costs. ## **AWS Cost Explorer** AWS Cost Explorer is a highly effective tool that can help you ## **Choose the Right Instance Family and Types** One of the simplest methods for optimizing AWS costs is to choose the right instance for your application. * If your application requires a lot of CPU power, you should opt for an instance type with a high CPU count, such as the C5 or M5 instances. * If your application needs a lot of memory, you should opt for an instance type with a high memory capacity, such as the R5 or X1 instances. * If you have a application that requires high compute resources but doesn't require high network or memory resources, you may want to consider using Graviton2 ARM-based instances, which offer a lower cost per unit of compute compared to traditional x86-based instances. ## **Key Points for Right Instance Selection** * ****Architecture compatibility:**** It is important to ensure that the instance family and type you choose are compatible with the architecture of your application and operating system. Some instance families and types may not be compatible with certain applications or operating systems. * **Future scalability:** You should consider the future scalability of your application when selecting an instance family and type. For instance, if you anticipate that your application will grow significantly in the future, you may want to choose an instance family and type that can be easily scaled up or down based on demand. * **Availability:** Additionally, it is important to take into account the accessibility of the instance family and type you choose. Some instance families and types may have limited availability in certain regions or availability zones. Let's say you choose Amazon Linux 2 OS instead of Ubuntu, but your application requires WebP support and the library you require is’t compatible. It's important to note that while Amazon Linux 2 does support WebP, some instance families and types may not be compatible with certain applications or operating systems. Therefore, it's important to ensure that the instance family and type you choose are compatible with the architecture of your application and operating system requirements. ## **Scheduling** ## **Utilize Reserved Instances** Reserved Instances (RIs) are a way to save money on your AWS costs by committing to use a specific instance type for a period of time, typically one or three years. RIs offer significant discounts compared to on-demand pricing, and This can save up to 75% on your instance costs. However, it’s important to ## **Auto Scaling** Auto Scaling is a function that automatically modifies the number of instances in your AWS environment based on demand. By using Auto Scaling, you can ensure that you have enough instances to handle peak traffic periods, while also minimizing costs during periods of low traffic. This can help you save money by utilizing only the necessary resources at the required time. ## **Optimize Storage** AWS offers various storage options with different pricing models and performance characteristics. Selecting the appropriate storage solution for your application can significantly reduce storage costs. Consider the following: * Use lifecycle policies to remove unnecessary object versions and reduce storage costs. * ## **AWS Cost Optimization Tools** AWS offers a range of cost management tools, such as AWS Budgets, AWS Trusted Advisor, and AWS Cost Anomaly Detection. These tools can help you monitor your costs, identify cost-saving opportunities, and optimize your spending. By using these tools, you can stay on top of your AWS costs and ensure that you are receiving the most benefits for your money. ## **Avoid Unused Resources** Avoiding unused resources is another important strategy for saving AWS costs. It's easy to launch resources in AWS, but it's important to periodically review your environment and identify any resources that are no longer needed. This could include instances, volumes, snapshots, or any other AWS resources that are not being actively used. By identifying and terminating these unused resources, you can avoid paying for unnecessary compute, ## **Conclusion** Building AWS cost optimization strategies is an ongoing process that requires constant monitoring and adjustment. By following these recommended methods, you can minimize your AWS costs and optimize your spending, maximizing the platform's benefits while optimizing its utilization. Remember to choose the right instance types, use AWS Cost Explorer, utilize Reserved Instances, use Auto Scaling, optimize storage, and use AWS Cost Management Tools. By doing so, you can achieve cost savings while still meeting your business needs. _For real-time insights, AWS cost optimization recommendations, and a granular view of your cloud spend patterns and cost usage, we offer CloudKeeper Lens, our proprietary_ _With a few clicks of easy onboarding, the platform provides businesses with resource level cost visibility into their billing, RI/Savings plan utilization, EC2 & S3, and data transfer spends. Book a demo to see the platform in action._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Cloud computing has revolutionized how businesses oversee their infrastructure, with AWS emerging as a top option for its flexibility, scalability, and extensive service offerings. Yet, alongside these benefits arise challenges in cloud cost management. Organizations looking to enhance their AWS expenditures must ## **What is AWS Cost Management?** AWS Cost Management includes a range of tools, strategies, and methodologies aimed at assisting organizations in monitoring, managing, and enhancing their cloud expenditures. AWS offers an extensive array of services that enable companies to ## **Importance of AWS Cost Management** Without proactive cost management, expenses in the cloud can escalate rapidly. Unmonitored instances, excessive resource allocations, and unused assets can lead to considerable charges. Efficient AWS Cost Management guarantees that: 1. Resources are fine-tuned for both performance and cost efficiency. 2. Budgets are followed, preventing unforeseen expenses. 3. Unnecessary spending is minimized, resulting in long-term savings. 4. Early detection of anomalies through vigilant cost monitoring allows for prompt action. As cloud expenditures become one of the largest budget categories for numerous organizations, AWS Cost Management is essential for maintaining predictable and manageable costs. ## **How Does AWS Cost Management Work?** AWS offers a collection of tools and dashboards within the AWS Management Console, making it easier to monitor and handle cloud expenditures. This service compiles cost-related information, categorizes it by usage type, and provides insights through various reports and cost allocation methods. **AWS Cost Management works on:** 1. Gathering and organizing information regarding resource usage and their corresponding costs. 2. Evaluating usage patterns to pinpoint areas of high spending. 3. Delivering suggestions for resource optimization, such as 4. Sending alerts for unusual cost activities and budget thresholds, ensuring users are informed of discrepancies in real-time. With AWS Cost Management, businesses can monitor expenses in detail, establish limits, and gain practical insights, which are crucial for minimizing costs and enhancing resource efficiency. ## **Best Practices for AWS Cost Management** AWS Cost Management can serve as an effective tool when utilized properly. Here are some recommended practices to maintain cost control and enhance resource utilization: **Resource Tagging** **Resource Usage Optimization** Reducing instance sizes, adjusting underused resources, and taking advantage of spot instances or reserved instances whenever feasible can greatly lower expenses. The Right-Sizing Recommendations feature assists in pinpointing areas where resources can be utilized more effectively. **Regular Audits** Conducting regular cost audits helps in identifying any idle or orphaned resources that may be accruing charges. Audits also confirm that all resources are still necessary and being utilized efficiently. **Establishing Budgets and Alerts** AWS Budgets allows users to set limits on costs and usage, along with alerts when specific thresholds are reached. This functionality helps to avoid unforeseen charges by proactively managing costs. **Utilizing Reserved Instances and Savings Plans** For workloads that are predictable, Reserved Instances and AWS Savings Plans offer considerable discounts compared to on-demand pricing. Planning resources in advance can lead to significant cost reductions. Adopting these best practices enables organizations to keep their cloud expenses in check and avoid unnecessary costs. ## **Free AWS Cost Management Tools in Action** AWS provides a variety of cost management tools, many of which are free to use, allowing organizations to track and optimize their cloud expenses. **AWS Cost Management Console and Billing Console** The AWS Cost Management Console and Billing Console serve as a unified hub for all cost management resources, enabling organizations to oversee costs, establish budgets, and receive recommendations for cost optimization. The Billing Console offers access to billing statements and payment details. **AWS Cost Explorer** AWS Cost Explorer enables users to visualize, comprehend, and manage AWS expenditures and usage trends over time. It presents in-depth insights into spending behaviors, including detailed breakdowns by service, region, or tags. **AWS Cost Anomaly Detection** AWS Cost Anomaly Detection employs machine learning to identify unexpected spending in AWS, alerting users when abnormal activity is noticed. By **AWS Budgets** AWS Budgets allows users to create tailored cost and usage budgets and receive notifications when actual or anticipated costs surpass specified limits. This tool is vital for managing expenses within set boundaries and preventing budget overspend. **AWS Savings Plans** AWS Savings Plans provide flexible pricing options that offer discounts in exchange for commitments of one or three years. These plans can adjust to fluctuating usage demands across services like EC2, Lambda, and Fargate, presenting an easy way to lower costs. **AWS Right-Sizing Recommendations** AWS Right-Sizing Recommendations delivers suggestions for These tools empower organizations to monitor and manage AWS expenses, streamline resources, and plan their spending more effectively. ## **AWS Cost Management FAQs** Q: How can I track and oversee AWS expenses across different accounts? A: AWS facilitates consolidated billing, allowing you to view and manage expenses across various accounts through a single billing dashboard. You can also opt for third-party Q: What is the optimal method for daily cost monitoring? A: AWS Budgets can send alerts daily, and AWS Cost Anomaly Detection can alert you to any unexpected charges, aiding in close cost monitoring. Q: Is it possible to stop AWS resources from going beyond budget limits? A: Although AWS cannot automatically terminate resources when budgets are surpassed, you can create budgets with alerts to inform you of potential overruns. Q: What distinguishes AWS Savings Plans from Reserved Instances? A: Savings Plans offer greater flexibility, covering services such as EC2, Lambda, and Fargate, while Reserved Instances are limited to specific EC2 instances and availability zones. Here’s a detailed guide on Q: How frequently should I assess my AWS costs? A: Monthly evaluations are typical, but more regular reviews (e.g., weekly) are recommended for organizations with high expenditures or rapid growth. ## **Maximizing Savings and Availing Additional Perks with CloudKeeper** While AWS provides a range of cost management tools, achieving maximum savings necessitates strategic planning and ongoing monitoring. CloudKeeper, an AWS premier partner offers sophisticated solutions that extend beyond simple cost tracking. Here’s how CloudKeeper enhances value: **24/7 Cloud Assistance** CloudKeeper delivers continuous **Assured Savings on Costs** CloudKeeper is dedicated to lowering expenses, and **Improved Visibility of Cloud Expenses** CloudKeeper provides thorough insight into your cloud environment's costs, enabling you to make informed decisions. Through in-depth reports and analytics, you’ll discover patterns in spending and cost factors, simplifying the identification of optimization possibilities. By partnering with CloudKeeper for AWS Cloud Cost Management, you can optimize cloud operations for both efficiency and cost-effectiveness, ensuring they meet your financial and infrastructure goals. ## **Conclusion** Efficient management of AWS costs is essential for organizations aiming to maximize their cloud expenditure. By utilizing appropriate strategies, tools, and partnerships like CloudKeeper, businesses can greatly lessen avoidable costs while still ensuring peak performance. Adopting these approaches allows companies to manage expenses, avoid exceeding budgets, and confirm that their AWS resources are utilized in the most economical way possible. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Amazon Web Services (AWS) is a powerful cloud computing platform that provides a wide range of services to help businesses scale their operations. While AWS offers many advantages, the cost of using these services can quickly add up if not managed properly. One AWS cost optimization best practice is utilizing multi-region and multi-availability zone deployments. As more businesses migrate to the cloud, In this blog post, we'll dive into how multi-region and multi-availability zone deployments can help with ## **What are Multi-Region and Multi-Region High Availability Zone Deployments?** Multi-region deployments involve distributing your application across different regions, while multi-availability zone deployments distribute your application across different availability zones within a region. This allows for increased fault tolerance, high availability, and reduced latency. ### **Multi-Region Deployment** A region is a physical location where AWS has multiple data centers, called Availability Zones (AZs). Deploying your application in multiple regions provides redundancy, ensuring that your application remains available even if one region goes down. Additionally, AWS offers different pricing for its services in different regions. By deploying your application in a region with lower pricing, you can significantly reduce costs. However, there are some potential drawbacks to multi-region deployments, such as increased complexity and additional data transfer costs. ### **Multi-Region High Availability Zone Deployments** An availability zone is an isolated data center within a region. Deploying your application across multiple availability zones within a region provides redundancy, ensuring that your application remains available even if one availability zone goes down. Additionally, AWS offers reduced pricing for data transfer between high availability and disaster recovery AWS zones. By taking advantage of this reduced pricing, you can significantly reduce costs. However, there are some potential drawbacks to multi-availability zone deployments, such as increased complexity and additional data storage costs. ## **Cost Optimization with Multi-Region Deployments** One of the biggest advantages of multi-region deployments is cost optimization. AWS offers different pricing for its services in different regions, so by deploying your application in a region with lower pricing, you can significantly reduce costs. * For example, if your application has a significant amount of data transfer between different regions, you may want to consider deploying your application in a region where data transfer costs are lower. * Similarly, if your application relies heavily on specific AWS services, you may want to consider deploying your application in a region where those services are priced lower. Additionally, deploying your application in multiple regions provides redundancy, ensuring that your application remains available even if one region goes down. This can minimize downtime and reduce the impact of outages on your business. ## **Cost Optimization with Multi-Availability Zone Deployments** Multi-availability zone In a multi-availability zone deployment, you'll need to store data across multiple availability zones. This can result in additional data storage costs, as well as increased complexity when managing data across multiple zones. However, the reduced pricing for data transfer between availability zones can help offset these additional costs. ## **Tips for Effective Cost Management** While multi-region and multi-availability zone deployments can help optimize costs, effective cost management requires careful planning and monitoring. Some To effectively optimize costs with multi-region and multi-availability zone deployments, there are several AWS cost optimization best practices you should follow: 1. **Conduct a cost analysis** : Before deploying your application, conduct a cost analysis to identify the most cost-effective region and availability zones for your application. This analysis should take into account factors such as data transfer costs, infrastructure costs, and energy costs. 2. **Use AWS Cost Explorer** : AWS Cost Explorer is a powerful tool that can help you analyze and optimize your AWS costs. Use it to identify areas where you can reduce costs, such as by using reserved instances or by optimizing your data storage. 3. **Use Auto Scaling** : 4. **Use AWS Trusted Advisor** : AWS Trusted Advisor is a service that provides 5. **Use CloudFormation** : AWS CloudFormation allows you to automate the deployment of your application. By automating the deployment process, you can reduce costs by reducing the time and effort required to deploy your application. 6. **Monitor your costs** : Regularly monitor your AWS costs to identify areas where you can reduce costs. Use tools such as AWS Cost Explorer and AWS Trusted Advisor to help you monitor your costs. ## **Conclusion** Multi-region and multi-availability zone deployments are powerful tools for optimizing AWS costs, providing increased availability, fault tolerance, and reduced latency. By taking advantage of AWS's regional pricing differences and reduced pricing for data transfer between availability zones, businesses can significantly reduce their AWS costs while improving application performance and reliability. However, effective cost management requires careful planning and monitoring, along with the implementation of cost optimization tools and best practices. _Optimize your AWS Costs and achieve enhanced cloud cost savings with_ _by your side. With contractually guaranteed savings, free access to AWS cost analytics platform, and recommendations from certified AWS experts, CloudKeeper can help reduce your overall AWS bills by up to 25%.__today._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 11 11 Table of Contents AWS (Amazon Web Services) is a well-known player in the current cloud computing market, providing a wide range of services to meet various organizational needs. It continues to lead the way in the cloud infrastructure business, having emerged as an early pioneer. According to the Synergy Research Group in the fourth quarter of 2023, Amazon's market share in the global market for cloud infrastructure was 31%, the highest among its competitors. Although using AWS can significantly enhance performance, scalability, and flexibility, cost optimization is an area that must be closely monitored. Effective cost control optimizes the return on investment from your AWS while also ensuring financial sustainability. There are numerous actions you can do to optimize the infrastructure hosting your apps to be as economical as possible, regardless of whether you are already on the cloud or you moved to AWS only recently. Are you, for instance, using the appropriate instances for the workload of your application? Suppose you have several instances constantly running with 10% CPU utilization. Would it be possible to employ smaller instances or push more work onto those instances? We'll dive into the nuances of AWS cost optimization in this in-depth guide, covering tactics, best practices, and crucial resources to assist you in successfully navigating the cloud cost optimization landscape. ## **Understanding AWS cost optimization** To navigate AWS cost optimization, a careful **AWS Billing Fundamentals** Understanding AWS billing is essential for effective cloud cost management. AWS charges are influenced by various factors, including service usage, data transfer, and pricing plans. **Pricing Models** Five pricing tiers are offered by AWS, which can assist you in budgeting and cost optimization for various use cases. When organizing your AWS project, you can make use of one or more of these models. **On-Demand** Paying by the hour or the second, AWS offers on-demand pricing for EC2 compute instances. You can spin up instances using this pricing model without having to pay for anything upfront. When necessary, you can swiftly end these instances and get reimbursed for the resources you utilize. This option offers a high degree of scalability and flexibility, making it perfect for erratic workloads or for new AWS users evaluating the environment. On-demand instances, however, come at a higher cost and can add up quickly. **Spot Instances** Because AWS Spot Instances are available at up to 90% less than the on-demand price, they can help you drastically cut your spending on computing resources. The biggest possible AWS cost savings are available with this arrangement, particularly if you need to scale quickly. Spot instances can be difficult to use, nevertheless, for workloads that are fault-sensitive. AWS reserves the right to terminate a spot instance whenever it is not using the compute capacity. Before your instance is terminated, you are given a two-minute warning. **Reserved Instances** **Savings Plan** Similar to RIs, AWS Savings Plans provide a substantial reduction in exchange for a longer commitment to use AWS services. Savings Plans, on the other hand, allow you to commit to spending on an hourly basis. A discount rate is then applied and deducted from your on-demand usage. Savings Plans, in contrast to RIs, are aggregated across resources, allowing you to take advantage of several AWS cost savings throughout your AWS account. **Dedicated Hosts** Dedicated Hosts are real servers that you can rent through AWS. With the entire server to yourself, this solution is regarded as extremely dependable and safe. Administrative work is eliminated when you rent a dedicated host. The hardware is maintained and cleaned by AWS. Dedicated hosts are costly and mostly fall within the budget of businesses. ## **5 AWS Design Principles** **1. Measure overall efficiency:** Assess overall effectiveness by taking a look at the workload's business output and the delivery expenses. Make use of this data to comprehend the benefits that come from raising production, enhancing functionality, and cutting costs. **2. Stop spending money on undifferentiated heavy lifting:** AWS handles the hard lifting of data center operations, such as racking, stacking, and powering servers, so stop wasting money on indifferent heavy lifting. Additionally, by using managed services, it eliminates the operational load of maintaining operating systems and applications. This frees you up to concentrate on business initiatives and customers rather than IT infrastructure. **3. Adopt cloud financial management:** You must make an investment in **4. Take up a model of consumption:** You just pay for the computer resources you use, and you may adjust how much you use based on your company's needs. For instance, throughout the workweek, development and test environments are usually only utilized for eight hours per day. When not in use, you can discontinue these resources to potentially save 75% on costs (40 hours against 168 hours). **5. Analyze and attribute spending:** The cloud facilitates transparent attribution of IT expenditures to revenue streams and specific workload owners by making it simpler to precisely identify the cost and utilization of workloads. This offers workload owners the chance to maximize their resources and cut expenses while also assisting in the measurement of return on investment (ROI). ## **5 Major Cost Drivers in AWS- What Makes it so Expensive?** The cloud on AWS offers more than 200 services. Because cloud resources are dynamic, managing their costs can be challenging and unpredictable. These are the primary reasons behind AWS waste and excessive costs: **1. Underutilization of resources:** Underutilization of compute instances on services such as Amazon EC2 means that you are paying for instances that you do not really need. Even if they are not being used, unused load balancers, EBS volumes, snapshots, and other resources are still costing money. **2. Inefficient pricing model:** Spot instances and reserved instances, which can offer AWS cost optimization of 50–90%, are not utilized when they are appropriate. Savings Plans, which might reduce computing costs by agreeing to a minimum total expenditure on AWS, are not used. For example, you scale up too much (adding duplicate resources) as demand increases when auto-scaling is not done or is not appropriate. **3. Not optimizing EC2:** For many businesses, EC2 (Elastic Compute Cloud) instances account for a sizable amount of their AWS expenses. Choosing the right instance types, utilizing reserved instances for predictable workloads, adopting auto-scaling, and leveraging spot instances for non-critical tasks are some strategies for **4. Storage expenses:** Storage expenses cover a range of AWS services, including Glacier, EBS (Elastic Block Store), and Amazon S3. Storage costs can be considerably decreased by putting data lifecycle policies into place, optimizing storage classes based on access frequency, and taking advantage of object storage efficiency. **5. Data Transfer costs:** With several cost drivers in the AWS ecosystem, it becomes easier to leverage tools that can help you keep a lot of these costs in check and prompt for timely action. Let’s take a look at these below- ## **AWS Cost Management Tools** AWS provides a range of cost management tools to assist customers in properly tracking, evaluating, and optimizing their cloud expenditures. AWS Budgets, AWS Cost Explorer, **AWS Cost Explorer** You may monitor AWS service costs, consumption, and return on investment (ROI) using the Cost Explorer interface. The interface can assist you in projecting your future expenses by displaying statistics for the previous 13 months. You may further evaluate your AWS expenditures and pinpoint specific areas for improvement by using the UI to generate customized views. You may also get data using your current analytics tools thanks to the API that the AWS Cost Explorer offers. **AWS Budgets** You may create and enforce budgets for every AWS service with the aid of AWS Budgets. The Simple Notification Service (SNS) may send you emails or messages when budgets are met or exceeded. A budget might be linked to specific data points, such as data usage or the quantity of occurrences, or it can be defined as an overall cost budget. The tool offers dashboard views that show how each service is used in relation to its budget, akin to those produced by the Cost Explorer. **AWS Trusted Advisor** It is an automated tool that offers advice on best practices for using Amazon services. Cost optimization is one of the five topics that Trusted Advisor looks into. The tool provides automatic optimization recommendations, such as managing lease expiration and optimizing reserved instances; finding underutilized EC2 instances and EBS volumes; identifying load balancers that are idle at the moment, unused elastic IPs, unused Amazon RDS databases, and any other resource that is underutilized and may be terminated to reduce costs. **AWS Pricing Calculator** You may calculate the cost of use cases on AWS with the help of the AWS Pricing Calculator. It enables you to create monthly cost projections for every region that a given service supports. Prior to developing a solution, you can model it, examine the cost points and estimate computations, and identify instance types and contract terms that satisfy your needs. This can assist you in planning your AWS expenses and consumption, making well-informed decisions, and estimating the costs associated with launching a new collection of instances and services. **Amazon CloudWatch** You can create alarms using Amazon CloudWatch based on metrics that are recorded for Amazon services. For ## **9 Best Practices for AWS Cost Optimization** Here are a few crucial best practices that will help you reduce your AWS costs. Learn how to manage the complexity of cloud expenditures and get more out of your AWS investments by exploring areas like resource allocation and end-to-end cost optimization solutions like CloudKeeper. **1. Right Size Resources:** By matching instance sizes and kinds to workload requirements, you can ensure optimal resource allocation, avoid under- or over-provisioning, and maximize both performance and cost efficiency. **2. Utilize Auto-Scaling:** **3. Leverage Spot Instances:** Benefit from AWS Spot Instances, which provide extra capacity at a fraction of the cost of on-demand instances. These instances are perfect for applications with flexible deadlines and non-critical requirements, allowing you to cut expenses without sacrificing performance. **4. Embrace Serverless Architectures:** **5. Utilize Reserved Instances:** Commit to reserve capacity for predictable workload, benefiting from discounted prices compared to on-demand instances over a one or three-year period. This will also provide cost stability and savings for long-term commitments. **6. Tag your Resources:** By **7. Continuously Monitor and Analyze Costs:** Utilize cost management tools such as **8. Utilize Managed Services:** Utilize AWS managed services to cut total cost of ownership (TCO), offload administrative work, and simplify operations. These services include Amazon RDS, Amazon S3, and Amazon DynamoDB. This will free up organizational resources to concentrate on essential business goals. **9. Optimize with CloudKeeper:** Enhance cost optimization efforts with CloudKeeper, a comprehensive cost optimization solution offering instant & guaranteed cloud savings on cloud. ## **Optimize your Cloud Costs Effortlessly with CloudKeeper** In conclusion, CloudKeeper is an expert, offering comprehensive With CloudKeeper, you can effortlessly optimize your cloud costs and maximize ROI. Our 100+ certified experts ensure that your cloud remains optimized and future-proof. Focus on growing your business while we handle your cloud's holistic optimization needs. _This blog was recently featured in FinOps Weekly, a leading newsletter for FinOps and Cloud Cost Optimization updates. You can explore the full coverage_ _._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Chief Operating Officer Aman spearheads business operations, strategic execution, and cross-functional alignment to drive sustainable growth. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents Amazon Web Services (AWS) is one of the most popular cloud service providers. However, it can be expensive to run workloads on AWS if you don't optimize your usage. One way to ## **Understanding the variations of RIs** AWS offers three variations of Reserved Instances: * Standard RIs * Convertible RIs * Scheduled RIs Standard RIs are the most common type of AWS Reserved Instances, offering the highest discount rates but locking you into a specific instance type, region, and operating system. Scheduled RIs allow you to reserve instances for specific time periods. Convertible RIs offer greater flexibility than Standard RIs, allowing you to modify your reservations as your usage patterns change. ## **Advantages & Limitations of Convertible RIs over Standard RIs** Convertible RIs offer several advantages over Standard RIs. For example, Convertible RIs allow you to change the instance type, region, or operating system of your reservations. This flexibility is especially useful if you are unsure about your future usage patterns or if you want to try out new instance types. Convertible RIs also offer higher discounts than Standard RIs if you commit to a longer term, up to a maximum of three years. However, Convertible RIs also have some limitations. They are more expensive than Standard RIs if you commit to a shorter term. Convertible RIs also offer lower discounts than Standard RIs if you commit to a shorter term or if you need to change your reservations frequently. ## **How to leverage the Convertible functionality of RIs?** To leverage the Convertible functionality of Reserved Instances, you need to understand your usage patterns and future needs. **Usage patterns:** How much do you expect to use AWS resources in the future? Will your usage increase or decrease? **Instance types:** Which **Regions:** Which regions do you expect to use? Are you willing to switch regions in the future? **Operating systems:** Which operating systems are suitable for your workloads? Are you willing to switch operating systems in the future? Once you have identified your AWS RI utilization patterns and future needs, you can purchase Convertible RIs with the appropriate term length, instance type, region, and operating system. You can then modify your reservations as your needs change. ## **Examples of savings achieved in different scenarios** Let's look at some examples of AWS savings achieved by using Convertible RIs in different scenarios: **Scenario 1:** **Scenario 2:** You expect to use AWS resources for the next three years, and you are sure about your instance type and region needs. You purchase Standard RIs with a three-year term and a 50% upfront payment. You save 60% compared to On-Demand instances. **Scenario 3:** You expect to use AWS resources for the next two years, but you are unsure about your instance type and region needs. You purchase Convertible RIs with a two-year term and a 50% upfront payment. You change your instance type and region after one year. You save 30% compared to On-Demand instances. Therefore, utilizing AWS Reserved Instances is an effective strategy to _Did you know that you can now get on-demand EC2 resources at 3-year RI pricing with a buy back-back guarantee of unused RIs without any commitment or additional cost? Check out_ _, an AI-based platform for AWS RI management.__today to accelerator your cloud cost optimization journey and achieve big savings._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Cost reduction is not a one-off project. It is a continuous operational rhythm that aligns engineering, finance, and architecture around a shared view of cloud economics. Many organizations treat cost optimization as a cleanup exercise after a high bill arrives — only to see early savings fade within 4–6 months because the behaviors driving waste remain unchanged. In 2026, the goal should be different: establish a repeatable, cost-aware operating model that prevents regression, embeds accountability, and integrates optimization into normal engineering workflows. This roadmap outlines a strategic 90-day plan to achieve that. ## Guiding Principles for the First 90 Days Before diving into specific activities, anchor your effort in four strategic principles: ### Visibility before enforcement You cannot expect teams to optimize what they cannot see. Make spend transparent at the service and workload level early. ### Ownership at the service and team level Clarify responsibility through tagging, cost allocation, and direct accountability. Shared dashboards are good — but ownership drives action. ### Progress in weekly rhythms, not quarterly reviews Cost doesn’t respond to audits — it responds to habits. Frequent, small reviews create institutional momentum. ### Leadership sets direction; engineering drives execution Optimization should feel like improving software quality, not reducing budgets. Engineers should see efficiency as part of delivery excellence. ## Phase 1 (Weeks 1–2): Establish Transparency & Shared Understanding **Objective** : Ensure everyone sees the same picture of cloud spend. Successful cost programs start with a shared foundation of visibility and language. **Key Actions** * Publish cloud spending dashboards by service, team, and environment. * Categorize resources into business value buckets: — Customer-facing services — Internal platforms — Development and experimentation environments * Identify the top 10 workloads with the highest cost impact. * Create a shared terminology for cost conversations (e.g., utilization, idle, rightsizing, data egress). **Outcome to Aim For:** Teams understand where spend is happening and why. **Sign of Success:** People begin to ask cost-related questions unprompted — an early sign of engagement. ## Phase 2 (Weeks 3–6): Assign Ownership & Begin No-Regret Optimizations **Objective** : Connect cost to the people who design, deploy, and operate workloads. This stage shifts cost awareness from visibility to accountability and begins early optimization that’s safe, reversible, and high-impact. **Key Actions:** * Assign service-level cost accountability to owning teams (not individuals). * Bake simple cost reviews into existing sprint or release rituals — avoid extra meetings. * Begin no-regret optimization actions, such as: -Shutting down clearly idle resources -Consolidating non-production environments -Applying lifecycle policies to storage -Rightsizing obvious over-provisioned compute and databases * Identify cost opportunities for: -Instance family modernization (e.g., Graviton or AMD) -Spot-backed compute for suitable workloads -Kubernetes autoscaling and pod tuning **Outcome to Aim For:** Teams feel responsible and supported — not policed. **Sign of Success:** Teams begin proposing optimizations on their own, rather than waiting for direction. ## Phase 3 (Weeks 7–12): Standardize Governance & Set Scaling Rhythm **Objective** : Make cost efficiency systematic and self-sustaining. This phase introduces lightweight governance, reinforces accountability, and embeds cost consideration into architectural decisions. **Key Actions** : * Implement light governance guardrails, not rigid policy controls: -Tagging standards applied at resource creation time -Default retention policies for snapshots and storage -Single-AZ defaults for non-critical environments * Begin monthly workload review cycles with engineering leads. * Align compute savings commitments to observed usage, not forecasts alone. * Evaluate architecture adjustments only when: -Patterns of usage are stable -Business value justifies deeper fixes **Outcome to Aim For** : Cost efficiency becomes a stable behavior, not a short campaign. **Sign of Success** : Cost decisions begin occurring at design time, not just after deployment. ## Database Savings Plans — New Strategic Lever in 2026 In re:Invent 2025 AWS announced the Database Savings Plans, expanding the existing Savings Plans model beyond compute to cover a broad range of managed database services. This is a major addition to the cost optimization toolkit. **What Database Savings Plans Are:** * A flexible pricing commitment where you commit to a consistent hourly spend for a 1-year term. * Discounts apply automatically to eligible database usage, including: -Amazon RDS (all supported engines) -Amazon Aurora (including Serverless v2) -DynamoDB -ElastiCache (supported configurations) -DocumentDB, Neptune, Keyspaces, Timestream, DMS (Eligibility and exact coverage vary by service type.) **Why This Matters for 2026?** Databases are often the second-largest cost center after compute. Traditional Reserved Instances or commitments had limitations: tied to specific instance types, engines, and regions. Database Savings Plans break many of those constraints, automatically applying discounted rates to eligible usage based on a simple hourly commitment — allowing flexibility across instance types, engines, and deployments. **Savings Potential** * Up to ~35% savings on serverless database usage * ~12–20% savings on provisions across various database services These are meaningful, and importantly, predictable contributions to your optimization plan. **How to Use It Within Your 90-Day Plan?** Include Database Savings Plans in your Phase 2 and Phase 3 optimization reviews: * Evaluate current database usage curves * Model commitment levels using AWS Cost Explorer Savings Plans recommendations * Include database commitment strategy in your monthly cadence ## Rinse & Repeat: The Continuous Cost Reduction Loop At the end of the first 90 days, don’t start a new project. Instead, repeat the same cycle every quarter. Cloud environments evolve constantly: * Workloads change. * Growth patterns shift. * Teams reorganize. * New services are launched. * Business priorities adapt. A cyclical rhythm locks cost reduction into everyday operations. | **Month** | **Focus** | **Why It Works** | | --- | --- | --- | | **Month 1** | Refresh visibility & cost attribution | Keeps accountability current | | **Month 2** | No-regret waste cleanup & rightsizing | Maintains hygiene with minimal friction | | **Month 3** | Architecture-level evaluation of high-impact workloads | Aligns optimization to evolving patterns | This “rhythm over reaction” approach sustains efficiency without overwhelming teams. ## Strategic Outcomes by the End of 90 Days After the first quarter of disciplined effort, your organization should be able to: Identify what drives cloud spend — not just dashboards, but drivers * Know who owns each portion of the cost * Maintain regular optimization cadences * Avoid re-accumulation of waste * Make forward-looking cost-aware architectural decisions This is maturity, not austerity. The purpose is to make cloud cost optimization a normal operating activity, not a periodic scramble. ## Summary The most effective AWS cost optimization strategy in 2026 focuses on visibility, ownership, and repeatable review rhythms, not one-time savings. Tag services for accountability, remove no-regret waste, right-size compute and databases based on real utilization, adopt flexible pricing strategies like Savings Plans (including the new Database Savings Plans), and establish quarterly cost optimization cycles. When cost reduction becomes part of your team’s operating rhythm — rather than a reactive audit — sustainable savings follow naturally. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Did you know? As per a Gartner study, end-user spending on cloud services is projected to grow from $595.7 billion in 2024 to a staggering $723.4 billion in 2025—a 21.5% increase. Cloud has enabled businesses to operate better, offering scalability, flexibility, and cost efficiency. It enables organizations to deploy applications faster, adapt to changing market demands, and innovate without the constraints of traditional IT infrastructure. However, despite these advantages, many organizations struggle with effective AWS cost reduction, where the sheer variety of services and pricing models can be overwhelming. Mismanagement often leads to spiraling expenses and wasted resources, overshadowing the potential savings and efficiencies that cloud computing promises. To truly maximize ## **Common Myths and Realities About AWS Cost Reduction** ### **Myth 1: AWS is inherently expensive** **Reality:** AWS provides a variety of **Explanation:** * On-Demand Pricing: Pay-as-you-go model ideal for unpredictable workloads. * Reserved Instances (RIs): Commit to long-term use and receive significant discounts. * Spot Instances: Leverage unused capacity for non-critical workloads at highly discounted rates. * Savings Plans: Combine flexibility and savings by committing to consistent usage levels. Here are ### **Myth 2: Auto-scaling always enables AWS cost reduction** Reality: Auto-scaling optimizes resource usage but may lead to cost overruns if not configured properly. **Explanation:** * Auto-scaling adjusts resource capacity to match demand. However, improper thresholds or misaligned configurations can lead to over-provisioning. * Set realistic thresholds based on historical traffic data. * Regularly review scaling policies to align with business needs. * Combine auto-scaling with Spot Instances for further savings. Here’s a ### **Myth 3: Migrating to AWS automatically reduces costs** **Reality:** Cloud Cost savings require strategic planning and optimization post-migration. **Explanation:** * Simply migrating workloads without proper optimization may lead to inefficiencies, such as over-provisioned resources or underutilized services. * Conduct a detailed cost analysis before migration. * Right-size instances and use Reserved Instances or Savings Plans for predictable workloads. * Continuously monitor and optimize cloud usage post-migration. For effective cloud cost management and to optimize your AWS spending, it's essential to delve into a comprehensive " ### **Myth 4: Cost optimization is a one-time activity** **Reality:** AWS cost optimization is an ongoing process that requires regular review and adjustments. **Explanation:** * Cloud environments evolve rapidly, and workloads, pricing models, and services change over time. Without continuous monitoring, inefficiencies can creep in. * Schedule periodic reviews of resource utilization. * Train teams on AWS cost reduction and * Leverage * Use Reserved Instances and Savings Plans for long-term cloud cost savings. * Set up cost anomaly detection with AWS Budgets and CloudWatch to catch surprises early. * Gain a ### **Myth 5: Moving to serverless automatically ensures AWS cost reduction** **Reality:** Serverless computing can lead to cost overruns if not implemented and monitored effectively. **Explanation:** Serverless services like AWS Lambda charge based on execution time and requests, which can add up quickly with high volumes or inefficient code. * Inefficient function design, excessive retries, or unoptimized memory allocation can increase costs. * Monitor invocation patterns and optimize function execution times to avoid unnecessary expenses. * Use * Combine serverless with cost management best practices, like setting alerts for unexpected spikes in usage. * Serverless is powerful, but it requires careful planning and monitoring. By optimizing function design and usage, you can unlock its cost-saving potential without surprises. Explore our Serverless Cost Optimization Guide to learn actionable tips and strategies to maximize serverless efficiency while managing expenses. ### **Myth 6: You only pay for what you use** **Reality:** You pay for what you provision, whether you use it or not! In the cloud, costs aren’t just about what you use—they’re about what you set aside. You’re billed for the resources you allocate, whether you fully utilize them or not. That difference between what you planned for and what you actually use can lead to spike in your cloud bills. Learn more in detail ## **Actionable Tips for Effective AWS Cost Reduction** Effective AWS cost reduction requires a multi-faceted approach. Begin by monitoring and analyzing spending using CloudKeeper Lens to uncover spending trends and inefficiencies. And some more useful tips that you can implement: * Tag resources effectively to track costs by department, project, or environment, making it easier to identify and address areas of overspending. * For predictable workloads, leveraging Reserved Instances and Savings Plans can result in substantial discounts. * Evaluate your usage patterns regularly to determine the appropriate level of commitment and maximize savings. * Optimizing storage costs is another critical step. Implement S3 lifecycle policies to automatically transition infrequently accessed data to lower-cost storage classes and delete unused snapshots or clean up orphaned volumes to avoid unnecessary charges * For flexible workloads such as batch jobs or CI/CD pipelines, adopting Spot Instances can significantly reduce costs. Use tools like EC2 Auto Scaling and Spot Fleet to efficiently manage these instances without compromising performance. * Rightsizing is a key practice to ensure resources are utilized effectively. Regularly assess resource utilization and adjust instance sizes based on current needs, leveraging AWS’s Compute Optimizer to identify underutilized resources. * Finally, implement governance tools such as AWS Budgets and AWS Cost Anomaly Detection to monitor and control costs proactively. Establish clear governance policies to prevent resource sprawl and maintain an efficient cloud environment. By debunking myths and following these strategies, businesses can unlock real cost savings on AWS and achieve sustainable cloud efficiency. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Chief Operating Officer Aman spearheads business operations, strategic execution, and cross-functional alignment to drive sustainable growth. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents At every AWS re:Invent, the cloud giant announces a host of new services and features, from AI/ML tools to new compute and storage options. While many of these updates generate excitement, some stand out for their immediate impact on cloud cost management and operational efficiency. One such For businesses running workloads across Aurora, RDS, DynamoDB, DocumentDB, Neptune, and other AWS-managed databases, this plan promises a simpler, more flexible way to reduce costs while maintaining the freedom to adjust workloads as your needs evolve. It’s one of the **most welcome announcements for teams looking to optimize database** spend without getting locked into rigid AWS Reserved Instances or struggling with complex billing. If you’ve been managing multiple database engines, planning migrations, or modernizing your stack, Database Savings Plans are designed to make life easier and budgets more predictable. ## **What are AWS database savings plans?** AWS Database Savings Plans are essentially a **flexible commitment to spend a fixed amount per hour over a 1-year term**. In return, AWS gives you discounted rates on your eligible database usage. **The savings can be up to 35%, especially for serverless offerings** , with modest but still useful discounts on provisioned instances. Unlike * Switch between instance families (for example, Aurora db.r7g to db.r8g) * Modernize from Amazon RDS for Oracle to Aurora PostgreSQL or DynamoDB * Move workloads between AWS regions (say EU (Ireland) to US (Ohio)) All without losing your discount. Any usage beyond your committed spend is billed at **on-demand rates** , so you only pay full price when you exceed the commitment. ## **Which services are covered under AWS Database Savings Plans?** **Database Savings Plans cover a broad range of database services, including:** * Amazon Aurora (including Serverless v2) * Amazon RDS (all supported engines) * Amazon DynamoDB (on-demand and provisioned) * Amazon ElastiCache for Valkey instances and serverless * Amazon DocumentDB (including serverless) * Amazon Neptune (including serverless) * Amazon Keyspaces * Amazon Timestream * AWS Database Migration Service (DMS) Previously, each of these services either had its own reservation options or none at all. Now, a **single commitment instrument** can cover a lot of your database usage, making management simpler. ## **How do the savings work in AWS Database Savings Plans?** The headline “**up to 35% savings** ” usually applies to **serverless deployments** , such as Aurora Serverless v2, DocumentDB Serverless, Neptune Serverless, and ElastiCache Serverless. For **provisioned instances** , discounts are generally lower: * Aurora, RDS, DocumentDB, Neptune → around 20% * DynamoDB and Keyspaces on-demand throughput → up to 18% * DynamoDB and Keyspaces provisioned capacity → up to 12% So while the maximum figure makes for a nice headline, for many traditional workloads, the savings are modest but consistent and predictable. ## **Why are AWS Database Savings Plans a welcome feature?** AWS customers have been asking for flexible, cross-service cost-saving options. AWS Database Savings Plans bring several improvements: * **Broader coverage:** one plan for multiple database types * **Flexibility:** spend-based commitment rather than instance-based * **Support for serverless:** discounted rates even for variable workloads * **Regional mobility:** shift workloads between AWS regions without losing your discount * **Migration-friendly:** switch engines or instance families as part of modernization efforts For businesses running **AI, analytics, or** ## **How to purchase and monitor AWS Database Savings Plans?** AWS provides multiple ways to evaluate and purchase Database Savings Plans: **Savings Plans Recommendations** – generates suggestions based on your recent usage. It calculates the hourly commitment that would maximize savings. **Purchase Analyzer** – lets you model different commitment levels, see coverage, utilization, and cost impact before you buy. You can complete purchases via the **coverage and utilization reports** in the ## **What are the benefits of AWS Database Savings Plans?** 1. **Fungibility across engines and regions** – your $/hour commitment automatically applies to eligible usage, whether it’s Aurora, DynamoDB, or DocumentDB. You don’t need to buy multiple RIs to cover changes. 2. **Covers serverless and instance-based databases** – flexibility to run workloads in whichever deployment type suits your application, while still enjoying cost benefits. 3. **Predictable cost for spiky workloads** – even on-demand DynamoDB workloads can now benefit from a committed spend, bringing more predictable budgeting to variable usage patterns. 4. **Simplifies modernization** – switching engines or instance families no longer requires separate reservations or planning for new RIs. In short, it brings **simplicity, predictability, and cross-service coverage** , which was much needed in the AWS ecosystem. ## **Do AWS Database Savings Plans support older database generations?** While Database Savings Plans sound like a neat, flexible way to save on RDS, Aurora, and ElastiCache, there’s a big practical limitation that customers notice almost immediately - they don’t cover most of the instance types that people are actually running today. ### **RDS & Aurora** The plan only applies to the latest-generation instance families, starting from the M7 and R7 series. If you’re on db.m7 or db.r7, great - you can enjoy the savings. But the reality is different for most teams. A large share of production workloads still run on earlier generations like m5, r5, r6g, and even the popular burstable families t3 and t4g. None of these qualify for the Database Savings Plan. So unless you modernise to the newer families, you’re basically back to the old playbook: Reserved Instances or on-demand pricing. In other words, the savings kick in only if you’re already modern, or willing to migrate. ### **ElastiCache** There’s a similar story here. The Savings Plan only covers Valkey, the Redis-compatible OSS engine. If your workloads use the standard Redis or Memcached, you can’t apply Database Savings Plans at all - your only option is Reserved Nodes. Given Redis’ massive adoption, this feels like a big gap for many teams. ## **What are the other limitations of Database Savings Plans?** * **Discounts aren’t always higher than AWS RIs** – provisioned workloads often get lower discounts than traditional AWS Reserved Instances. * **Commitment term limitations** – currently only 1-year, no-upfront options are available. This keeps things simple but limits discount depth compared to 3-year RIs. * **More moving parts** – if you operate older RDS instances alongside modern Aurora clusters, you may still need RIs for older workloads and AWS Database Savings Plans for newer ones. This adds some complexity to cost management. Basically, AWS Database Savings Plans are a powerful tool, but not a silver bullet. They work best for recent generation instances, serverless workloads, and workloads that can flexibly adopt supported engines. ## **Practical takeaways on AWS Database Savings Plans** * Use AWS Database Savings Plans for **modern workloads** and serverless databases. * Combine with AWS **RIs for legacy workloads** if you have older instances that aren’t eligible. * Start with the **AWS recommendations or Purchase Analyzer** to pick the right commitment level. * Monitor **coverage and utilization** regularly to avoid overspending or underusing the commitment. * Plan For businesses looking to manage costs while maintaining operational flexibility,**this hybrid approach** will likely be standard for the next few years. ## **Conclusion** AWS Database Savings Plans are one of the most useful announcements from re:Invent 2025. They combine flexibility, cross-service coverage, and predictable They are especially valuable for teams running Aurora, serverless databases, and DynamoDB/Keyspaces workloads, but they are not a blanket replacement for all AWS Reserved Instances. The best approach for most organizations will be a hybrid strategy: RIs for legacy workloads, AWS Database Savings Plans for modernized and serverless deployments, and a clear roadmap for modernization to maximize cost efficiency. If you’ve been juggling multiple database engines, planning migrations, or experimenting with serverless workloads, Database Savings Plans offer a welcome, flexible tool to make **To explore more key announcements and insights, make sure to check out our latest blog on** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents AWS EC2 (Elastic Compute Cloud) is a popular service that provides scalable computing capacity in the cloud. However, EC2 costs can quickly add up, especially if instances are overprovisioned or underutilized. In this article, we will discuss two important tips for optimizing EC2 costs: right-sizing and instance selection. When it comes to * **Right-sizing instances:** One of the most common mistakes people make is choosing instances that are larger than what they need. To avoid this, regularly monitor your EC2 instances and look for underutilized resources. AWS provides various tools, such as CloudWatch and AWS Trusted Advisor, to help you monitor your instances and identify opportunities for optimization. Once you've identified underutilized instances, you can either downsize them or consider * **Use the appropriate instance type:** Choosing the right instance type is crucial in ensuring that you only pay for what you need. AWS offers a wide range of instance types with varying performance capabilities and prices. * **Use Spot instances:** AWS Spot instances allow you to bid on unused EC2 capacity, which can result in AWS cost reduction. Spot instances are ideal for workloads that are flexible and can handle interruptions. You can set up Auto Scaling groups to use Spot instances, which will automatically launch and terminate instances based on demand and the spot price. * **Use Reserved Instances:** If you have steady-state workloads, using Reserved Instances can help you save up to 75% of your EC2 costs compared to On-Demand pricing. Reserved Instances require an upfront payment for a specified term and provide a discount on the hourly charge for the instance. * **Use Savings Plans:** AWS Savings Plans offer flexibility and AWS cost reduction of up to 72% compared to On-Demand pricing. Savings Plans provide savings on your EC2 usage in exchange for committing to a specific usage amount over a one- or three-year term. In summary, by right-sizing your instances, using the appropriate instance type, and leveraging AWS Spot instances, Reserved Instances, and Savings Plans, you can significantly ## **Right Sizing Using Performance Data** Right-sizing involves selecting an EC2 instance size that matches the performance requirements of your workload. This is an important because overprovisioning instances can lead to unnecessary costs, while under-provisioning instances can result in poor performance. Hence, cloud cost management of AWS instnaces is necessary. To right-size an EC2 instance, you should analyze performance data such as CPU utilization, memory usage, and disk I/O. AWS provides a number of tools for monitoring performance data, including CloudWatch and the EC2 Instance Status Checks. By analyzing this data, you can identify instances that are overprovisioned or underutilized and adjust their size accordingly. For example, if your performance data shows that your CPU utilization is consistently below 50%, you may be able to reduce AWS costs by downsizing your instance to a smaller size. Conversely, if your performance data shows that your memory usage is consistently above 90%, you may need to upscale your instance to a larger size. ## **Right Sizing Based on Usage Needs** Another way to right-size your EC2 instances is to base your instance selection on your usage needs. AWS provides a wide range of EC2 instance types, each optimized for different use cases. By selecting the right instance type for your workload, you can ensure that you are only paying for the resources you need. For example, if your workload involves a lot of network traffic, you may want to select an instance type with high network performance, such as the C5 or M5 instance type. Conversely, if your workload involves a lot of processing power, you may want to select an instance type with high CPU performance, such as the C4 or M4 instance types. In addition to instance type selection, you should also consider other factors such as instance pricing models (on-demand, reserved, or spot instances) and availability zones. By taking a holistic approach to instance selection, you can ensure that you are getting the most value for your EC2 costs. In conclusion, right-sizing and instance selection are important tips for optimizing EC2 costs. By analyzing performance data and selecting the right instance types based on your usage needs, you can ensure that you are only paying for the resources you need. AWS provides a number of tools and resources to help you optimize your EC2 costs, and by taking advantage of these tools, you can maximize the value of your EC2 investment. ## **Right Sizing by Turning Off Idle Instances** Another way to right-size your EC2 instances is to turn off idle instances. Idle instances are instances that are running but not actively being used, and they can contribute to unnecessary AWS billing costs. By turning off idle instances, you can save on EC2 costs without affecting your workload performance. AWS provides several tools and services that can help you identify and turn off idle instances. For example, you can use AWS CloudWatch alarms to detect idle instances and trigger automated actions to turn them off. You can also use AWS Auto Scaling to automatically ## **Right Sizing by selecting the Right Instance Family** Selecting the right instance family is another important factor in right-sizing your EC2 instances. Each EC2 instance family is optimized for different use cases, and by selecting the right family, you can ensure that you are getting the most value for your AWS costs. For example, if your workload involves a lot of compute-intensive tasks, you may want to select an instance family with high CPU performance, such as the C5 or M5 instance families. On the other hand, if your workload involves a lot of memory-intensive tasks, you may want to select an instance family with high memory performance, such as the R5 or X1 instance families. Selecting the right instance family is an important step in * General Purpose (e.g., M5): These instances are a good choice for a wide range of workloads that require a balance of CPU, memory, and network performance. They are a good choice for general-purpose applications, such as web servers, small to medium-sized databases, and development and test environments. * Compute-Optimized (e.g., C5): These instances are designed for compute-intensive workloads that require high-performance processors. They are a good choice for applications that require high CPU performance, such as batch processing, scientific modeling, and gaming. * Memory-Optimized (e.g., R5): These instances are designed for workloads that require high memory-to-CPU ratios, such as memory-intensive databases, in-memory analytics, and real-time big data processing. * Storage-Optimized (e.g., I3): These instances are designed for workloads that require high disk throughput and low-latency SSD storage, such as large-scale transactional databases, data warehousing, and big data processing. * GPU-Optimized (e.g., P3): These instances are designed for workloads that require powerful NVIDIA GPUs for graphics and general-purpose computing, such as machine learning, high-performance computing, and scientific simulations. * FPGA-Optimized (e.g., F1): These instances are designed for workloads that require customizable hardware acceleration for specific applications, such as genomics, financial modeling, and video encoding. * Arm-Based (e.g., A1): These instances are based on AWS-designed Graviton processors for power efficiency and offer a cost-effective alternative to x86-based instances. They are a good choice for workloads that can benefit from their efficient use of resources and lower AWS costs, such as web servers, containerized microservices, and development and test environments. * Graviton (e.g., M6g): These instances are also based on AWS-designed Graviton processors and offer up to 40% better price-to-performance than comparable x86-based instances. They are a good choice for workloads that require a balance of CPU and memory performance, such as web servers, application servers, and small to medium-sized databases. Overall, selecting the right instance family is crucial in AWS cost optimization and achieving the desired performance for your workload. It is important to evaluate your workload requirements and choose the instance family that best matches those requirements, for it is an effective AWS cost reduction strategies. ## **Right Size Your Database Instances** In addition to right-sizing your EC2 instances, it's also important to right-size your database . Databases can be a significant source of AWS billing costs, and opting for an intelligent cloud cost management strategy of database instances can lead to significant cloud cost savings. To right-size your database instances, you should analyze performance data such as CPU utilization, memory usage, and disk I/O. You can also use AWS tools such as Amazon RDS Performance Insights to gain insights into your database performance and identify opportunities for optimization. In addition to performance analysis, you should also consider database instance types and pricing models. AWS provides several different database instance types optimized for different use cases, and selecting the right type can help with In conclusion, right-sizing your EC2 instances is an important step in implementing _CloudKeeper helps you cost-optimize your entire cloud infrastructure and provides instant and guaranteed savings of up to 25% on your AWS bills.__, to learn more._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents When working with AWS, we may want to track **launches**. By default, both manual launches and **RunInstances** API event in CloudTrail. But in real-world use cases, we often want**alerts only for manually created (standalone) AWS EC2 instances** , not for instances spawned automatically by ASGs. We can achieve this using **CloudTrail** + **EventBridge** + **SNS**. ## **Why Do We Need This?** * **Cost control** – Standalone AWS EC2s may be created for testing or troubleshooting and forgotten, leading to unnecessary spend. * **Security** – Manually launched instances may not follow standard security hardening or tagging policies. * **Governance** – Many organizations want resources to be created only via approved pipelines (Terraform, * **Visibility** – Alerts help ops/FinOps teams track who created instances and why, ensuring better accountability. * **Noise reduction** – By excluding ## **How the Events Look in CloudTrail** Whenever an AWS EC2 instance is launched, CloudTrail records a **RunInstances** event. When the instance is created by ASG, then we have the below userAgent value. This difference in **userAgent** lets us filter out ASG events. ## Create an SNS Topic for Notifications * Go to **Amazon SNS → Topics → Create topic** **a)** Type: Standard **b)** Name: **EC2CreationAlerts** * Create a **subscription** of Email. * Confirm the subscription by clicking on confirm subscription on the email you received. ## Create an EventBridge Rule * Create a rule with the name EC2CreationAlerts-rule. * Click on Custom Pattern(Json Editor) and paste the pattern below. * While creating the EventBridge rule, set the **Target** to the SNS topic **EC2CreationAlerts**. * Click on Next, Review, and create the rule. ## Test the Setup ### **_StandAlone EC2 :_** * Launch an EC2 instance manually from the AWS Console. * Standalone AWS EC2 gets created. * You should **have received an email** via the Amazon SNS topic. ### **_EC2 Created by ASG Test :_** * Create an ASG and set the desired capacity to 2. * 2 ASG EC2s are getting created, and we will not get any alerts for both of them via the SNS topic **Note:** If you prefer a **custom message format** over raw event JSON via email, you can create a Lambda function and attach it to EventBridge according to your requirements. Please ensure that ## **Conclusion** With this setup, we get By combining **CloudTrail** , **EventBridge** , and **Amazon SNS (or AWS Lambda for custom messages)** , we build a lightweight yet powerful guardrail that keeps your AWS environment clean, secure, and cost-efficient. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Rohit is passionate about designing and implementing scalable, secure, and efficient DevOps solutions including automation pipelines, cloud architectures, and infrastructure as code. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents In 2006, when Amazon Web Services (AWS) came, it revolutionized everything with the concept of on-demand cloud computing. At the core of this revolution was Amazon EC2 Instances—a cloud service that enabled businesses to launch virtual machines on demand, scale up or down as needed, and pay only for what they use. This was a savior for many businesses as earlier they had to buy expensive servers, find where to put them, and try to predict how much computing power they would need in the future. It was complicated, costly, and time-intensive. Fast forward to today, as per research, the AWS customer base has grown to 4.19 million customers in 2025. AWS EC2 Instance is the most popular, widely used, and among the top Amazon Web Services (AWS) services, which usually holds a major component in the AWS cloud bill. But the catch is—while EC2 makes cloud computing easier, it’s also one of the biggest cost drivers of your AWS bill. From powering everyday workloads to hosting services like EKS, ECS, and Auto Scaling, AWS EC2 Instance is a necessity, but managing them can be a challenge. In this blog, we will discuss everything about AWS EC2 Instances, its key features, types of AWS EC2 Instances, AWS EC2 Pricing, and ## **What are AWS EC2 Instances?** AWS EC2 is a cloud computing service that offers businesses highly scalable and elastic virtual machines known as AWS EC2 instances. You can easily deploy AWS EC2 instances and manage them using the AWS Management Console, CLI, or SDKs. The AWS EC2 instances can be customized with multiple CPU, memory, storage, and networking configurations to suit a variety of cloud workloads as per business needs, ranging from simple web hosting to complex machine learning. ## **Key Features of AWS EC2 Instances** * **Scalability** : Whether you have a business with fluctuating demand or need to scale rapidly during a product launch, AWS EC2 instances are of great help as they can be scaled up or down as per the workload demands. * **Variety of Instance Types:** There is a wide range of AWS EC2 instances and configurations. You are free to choose from different instance families optimized for compute, memory, storage, and GPU performance. * **Flexible Pricing Models:** AWS EC2 instances offer a pay-as-you-go pricing model, making it a cost-effective option for businesses. There are various AWS EC2 pricing options based on usage patterns considering factors like the type of instance, usage duration, and optimization features, etc. * **Security:** AWS EC2 instances support VPC, IAM roles, and security groups for enhanced cloud protection. * **Custom AMIs:** You can also create and deploy custom Amazon Machine Images (AMIs) for rapid instance provisioning. * **Auto Scaling & Load Balancing: **Maintain application performance and availability with auto-scaling groups and Elastic Load Balancing (ELB). Here’s a guide to learn more about ## **AWS EC2 Instance Types** AWS EC2 instances come in various types, each designed for specific workloads. Let’s understand in detail about each of them. ### **1. General Purpose Instances** This is ideal for applications with balanced compute, memory, and networking needs. Example: **M8g:** Powered by AWS Graviton4 processors, offering enhanced price performance. **M7i:** Features Intel processors, suitable for general-purpose applications. **T4g:** Provides burstable performance with AWS Graviton2 processors. **Use Cases:** Web servers, small databases, development environments. ### **2. Compute-Optimized Instances** These AWS EC2 Instance types are best for compute-heavy applications requiring high processing power. **Example:** **C7g:** Utilizes AWS Graviton3 processors for improved compute performance. **C6i:** Based on Intel processors, ideal for compute-bound applications. **Use Cases:** High-performance computing (HPC), batch processing, game servers. ### **3. Memory-Optimized Instances** This is ideal for applications requiring high RAM for faster data processing. **Example:** **R6g:** Equipped with AWS Graviton2 processors, offering high memory capacity. **X2idn:** Provides high memory and storage for large datasets. **Use Cases:** High-performance databases, data mining, and in-memory databases like SAP HANA. ### **4. Storage-Optimized Instances** These instances are designed for workloads that require high sequential read and write access to large datasets on local storage. Example: **I4i:** Offers high-speed, low-latency NVMe storage. **D3:** Provides high disk throughput and storage capacity. **Use Cases:** Big data processing, data warehouses, log processing. ### **5. Accelerated Computing Instances** Best for machine learning, gaming, and high-performance graphics rendering. **Example:** **P4:** Features NVIDIA GPUs for advanced machine learning workloads. **G5:** Equipped with NVIDIA A10G Tensor Core GPUs for graphics-intensive applications. **Use Cases:** AI/ML training, deep learning, video transcoding, speech recognition. ### **6. High-Performance Computing (HPC) Optimized Instances** This is specifically designed for complex simulations, scientific modeling, and other HPC workloads that require extremely high compute performance and network throughput. **Examples:** **Hpc6id:** Offers high memory bandwidth and network performance for HPC applications. **Use Cases:** Computational chemistry, genomics, seismic analysis, and Financial modeling. AWS EC2 instances also come with powerful features to deploy, manage, and scale workloads. These features include: * **Burstable Performance Instances:** provide a baseline level of CPU performance with the ability to burst above the baseline. * **Multiple Storage Options:** We can choose between various storage options based on requirements. * **EBS-Optimized Instances:** The main purpose here is to provide dedicated bandwidth for high-performance EBS volumes, reducing latency and improving storage efficiency. * **Cluster Networking:** This helps with high-speed, low-latency communication for HPC and data-heavy workloads. * **Intel Processor Features:** Supports AES encryption, AVX acceleration, Turbo Boost, and AI-optimized Deep Learning Boost. ### **A Quick Snapshot of AWS EC2 Instance Types** ## **AWS EC2 Pricing Models** There are several AWS EC2 pricing options to help users optimize costs based on their usage patterns: **1. On-Demand Instances** **How it Works:** This On-demand AWS EC2 Pricing works on a pay-per-second or per-hour basis with no long-term commitments. **Best For:** Short-term, unpredictable workloads requiring flexibility. **Pros:** No upfront cost, easy to scale up/down. **Cons:** Higher cost compared to other pricing models. **2. Reserved Instances (RI)** **How it Works:** You can commit to a 1- or 3-year term for significant **Best For:** Steady-state workloads with predictable usage. **Pros:** Up to 75% savings compared to On-Demand pricing. **Cons:** Requires long-term commitment. **3. Savings Plans** **How it Works:** This is a flexible AWS EC2 pricing model offering discounts in exchange for a usage commitment. **Best For:** Businesses with a predictable spending pattern but require instance flexibility. **Pros:** It works across multiple instance types and regions. **Cons:** Requires upfront commitment. **4. Spot Instances** **How it Works:** It uses spare AWS capacity at a fraction of the On-Demand price. **Best For:** Batch processing, AI/ML training, fault-tolerant applications. **Pros:** One can get up to 90% cost savings. **Cons:** Instances can be interrupted by AWS with short notice. **5. Dedicated Hosts** **How it Works:** Rent an entire physical server for your exclusive use. **Best For:** Compliance-heavy workloads requiring dedicated hardware. **Pros:** Bring-your-own-license (BYOL) for software. **Cons:** Higher cost. **6. AWS Free Tier** **How it Works:** It offers 750 hours of free usage for t2.micro or t3.micro instances per month for 12 months. **Best For:** Learning AWS, testing applications. **Pros:** No cost for beginners. **Cons:** Limited to specific instance types. **Amazon EC2 Cost Components** While estimating costs, we must consider several key factors that impact AWS EC2 pricing. Some of these factors are: * **Clock Hours of Server Time** – Charges apply from instance launch until termination, including allocated Elastic IP addresses. * **Instance Type** – Costs vary based on CPU, memory, networking, and storage configurations. * **Number of Instances** – Pricing depends on how many instances are running at a given time. * **Load Balancing** – Elastic Load Balancing distributes traffic and incurs charges based on usage hours. * **Detailed Monitoring** – Basic monitoring is free, but detailed insights via CloudWatch come at a fixed monthly cost. * **Elastic IP Addresses** – One Elastic IP per running instance is free; additional IPs may have costs. * **Licensing** – Pay-as-you-go AWS licenses or bring-your-own-license options impact total costs. ## **AWS EC2 Best Practices** Let us now learn about some common best practices to optimize your AWS EC2 Instances: **Pick the Right AWS EC2 Instance Type** – This is the most important step that ensures how smartly and efficiently you will be able to avail of the AWS EC2 Service. Choose an instance that fits your workload to avoid paying for unused resources. **Right-Size Your Instances** – Continuously evaluate instance utilization to ensure you're not paying for unused capacity or compromising performance. Adjust instance types and sizes based on real usage data to strike the perfect balance between cost-efficiency and workload performance. Here’s a detailed guide on **Use Auto Scaling** – Make optimum use of your AWS EC2 instances by scaling up when demand rises and scaling down when it drops to optimize performance and costs. Learn more about **Enable Spot Fleets** – It’s a good idea to mix On-Demand and Spot Instances to save money without sacrificing availability. **Monitor with CloudKeeper Lens** – Keep an eye on performance and get comprehensive **Tag Your Resources** – Use **Take Advantage of Savings Plans & RIs** – Commit to long-term usage and enjoy significant discounts. **Optimize with CloudKeeper Tuner** – An Automated ## **AWS EC2 Instances FAQS** ### **1. What is AWS EC2 used for?** The AWS EC2 Instances are used to provide resizable and scalable computing power in the cloud. It has various use cases. For example, businesses use AWS EC2 for web hosting, big data processing, application deployment, machine learning, and more. It offers flexibility, cost efficiency, and seamless integration with other AWS services, making it ideal for various workloads. ### **2. Can I upgrade or downgrade my AWS EC2 instance?** Yes, you can change the instance type by stopping the instance and modifying its instance type in the AWS Console. ### **3. How do I ensure my AWS EC2 instances are secure?** Use security groups, IAM roles, and encrypted EBS volumes, and enable AWS Shield for DDoS protection. ### **4. Does AWS provide free EC2 instances?** Yes, AWS offers 750 hours of free t2.micro or t3.micro instances per month for new users under the Free Tier. ### **4. What happens if my Spot Instance is interrupted?** AWS provides a two-minute warning before terminating the instance. You can use Spot Fleet to maintain availability. ### **5. What is the difference between AWS EC2 Reserved Instances and Savings Plans?** Reserved Instances are tied to specific instance types, while Savings Plans provide broader flexibility across instance families and regions. Learn more about ### **6. How many AWS EC2 instances can be launched at the same time?** By default, AWS allows up to 20 On-Demand AWS EC2 instances per Region for new accounts, but this limit can vary based on instance type. You can request a quota increase via AWS Support if needed. ### **7. How many EC2 instances can be created per region?** By default, AWS has a limit of 20 AWS EC2 instances per region. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents As cloud computing professionals, cost optimization is critical for any organization using cloud services. AWS Fargate is a serverless compute engine for containers that make it easy to run containers on Amazon Elastic Container Service (ECS). It eliminates the need to manage servers or clusters, making it easier to focus on application development. In this article, you will learn how to master AWS Fargate cost optimization by providing tips for right-sizing and task scheduling with ECS Fargate. ## **Introduction to AWS Fargate and ECS Fargate** AWS Fargate is a serverless compute engine for containers that allows you to run your containerized applications without worrying about the underlying infrastructure. It is a fully managed service that eliminates the need to manage servers or clusters, making it easier to focus on application development. With AWS Fargate, you only AWS ECS Fargate is a service that allows you to run containers on Fargate. It is a fully managed service that supports ## **Understanding ECS Fargate pricing** To understand ECS Fargate pricing, you need to know the AWS Fargate Pricing for the resources you use. Fargate charges you based on the vCPU and memory resources you allocate to your tasks. You can choose to allocate either vCPU or memory resources, or both, depending on your application's requirements. ECS Fargate pricing is based on the number of vCPU and memory resources you allocate to your tasks. The Fargate pricing is per second, and you only pay for the resources you use. For example, if you allocate two vCPU and 4GB of memory to your task and run it for one hour, you will be charged for two vCPU and 4GB of memory for that hour. ### **The AWS Fargate pricing is typically based on the following factors** **Task or container resources:** Fargate pricing is based on the vCPU (virtual CPU) and memory resources allocated to your tasks or containers. You pay per vCPU per hour and per GB of memory per hour. **Task duration:** You are billed for the hour the time your tasks or containers are running, rounded up to the nearest second. If you stop or terminate a task, you will only be billed for the time it was actually running. **Networking:** Additional charges may apply for data transfer in and out of your containers, depending on the ### **An Example of Fargate On-demand Charges** Suppose you have an application consisting of two containerized microservices, Service A and Service B. Service A requires 1 vCPU and 2 GB of memory. At the same time, Service B needs 2 vCPUs and 4 GB of memory. Both services run continuously for 24 hours. Here's how the Fargate pricing calculation would work for (US EAST Ohio) Service A: (1 vCPU * $0.04048 per vCPU per hour) + (2 GB * $0.004445 per GB per hour) = $0.0894 per hour Service B: (2 vCPUs * $0.04048 per vCPU per hour) + (4 GB * $0.004445 per GB per hour) = $0.1788 per hour Assuming both services run for 24 hours: Service A cost: $0.0894 per hour * 24 hours = $2.1456 Service B cost: $0.1788 per hour * 24 hours = $4.2912 In this example, the total cost for running both services on Fargate for 24 hours would be $6.4368. ## **Fargate Spot Pricing and How to Use It** Fargate spot pricing allows you to run your Fargate tasks at a lower cost by leveraging spare capacity in the AWS infrastructure. Fargate spot pricing can save you up to 70% on Fargate costs, making it an attractive option for cost-conscious organizations. To use Fargate spot pricing, you need to specify that you want to use spot instances when you create your task definition. When you launch your task, Fargate will try to allocate spot instances first before falling back to on-demand instances. Fargate will automatically terminate your task if the spot instances become unavailable. It's important to remember that Spot instance prices fluctuate based on supply and demand in the Spot Market. Prices can change frequently, and there may be instances where Spot prices exceed the on-demand prices during periods of high demand. However, using Spot instances judiciously can still result in substantial ### **AWS ECS Fargate Spot Pricing is suitable for the following use cases** * Batch Processing: Non-time-sensitive tasks like data analytics, log processing, and image rendering. * CI/CD Pipelines: Parallelized stages of the pipeline that can tolerate occasional interruptions. * Web Applications with Variable Traffic: Fluctuating traffic patterns, utilizing Fargate Spot during low-traffic periods. * Dev/Test Environments: Temporary environments for development and testing purposes. * Stateless Microservices: Independent, stateless components in a microservices architecture. * ECS Containers with Redundancy: Redundant instances for high availability. * By leveraging Fargate Spot instances, you can reduce costs while maintaining the required capacity for these workloads. ### **Example of ECS Fargate Spot Charges** Here's how the pricing calculation would work for (US EAST Ohio) Service A: (1 vCPU * $0.01247334 per vCPU per hour) + (2 GB * $0.00136966 per GB per hour) = $0.01521266 per hour Service B: (2 vCPUs * $0.01247334 per vCPU per hour) + (4 GB * $0.00136966 per GB per hour) = $0.03042532 per hour Assuming both services run for 24 hours: Service A cost: $0.01521266 per hour * 24 hours = $0.36510384 Service B cost: $0.03042532 per hour * 24 hours = $0.73020768 In this example, the total cost for running both services on Fargate for 24 hours would be $1.09531152. ## **Right-sizing your Fargate tasks for cost optimization** Right-sizing your AWS ECS Services and Fargate tasks is an important step in optimizing your Fargate costs. By right-sizing your tasks, you can ensure that you are not over-provisioning resources and paying for unused resources. To right-size your Fargate tasks, you need to ### **Setting up Amazon CloudWatch to monitor CPU and memory usage of an ECS Fargate task** Once your task is running, you can view its CPU and ### **Task scheduling strategies for cost optimization** Task scheduling is another important factor in optimizing your Fargate costs. By scheduling your tasks efficiently, you can ensure that you are not wasting resources and paying for unused resources. One strategy for task scheduling is to use spot instances for tasks that are not time-sensitive or critical. This can help you save costs by leveraging the lower spot prices. Another strategy is to use task placement strategies to optimize resource utilization. You can use task placement strategies to ensure that your tasks are placed on instances with available resources like ECS Containers and to balance the workload across instances. ## **Strategies for optimizing Fargate task scheduling** Optimizing AWS ECS Fargate task scheduling is crucial to ensure that your workload runs efficiently and cost-effectively. Here are some strategies for optimizing AWS ECS Fargate task scheduling: **Examples of how you can use scheduling strategies in ECS Fargate** 1. Spread: Spread evenly distributes tasks across instances to achieve high availability and fault tolerance. It ensures that tasks are spread across different availability zones, reducing the impact of failures. 2. Binpack: This strategy maximizes resource utilization by packing tasks onto instances based on available resources. It aims to minimize the number of instances required to run tasks, reducing costs. 3. Random: This strategy randomly places tasks on instances, in this case, AWS ECS Services, which can be useful for load balancing and distributing workloads across the infrastructure. This constraint ensures that tasks are scheduled on any available instance in the cluster. The "random" strategy can be useful when you don't have any specific placement constraints and want to distribute tasks across available instances in a non-deterministic way. ## **Task Prioritization in ECS Fargate** Suppose you have two tasks running in ECS Fargate - Task A and Task B. Both tasks are critical, but Task A needs to be prioritized over Task B. To prioritize Task A, you can assign a higher priority value to it than Task B. In ECS Fargate, task priority ranges from 1 to 1000, where 1 is the lowest priority, and 1000 is the highest priority. You can set the priority value for Task A to 1000 and Task B to 500. This will ensure that ECS Fargate prioritizes Task A over Task B, and if resources are scarce, Task A will get the resources it needs first. To set the priority value, you can add the "priority" parameter to the run-task command or specify it in the task definition. Here is an example of how you can specify task priority in a task definition JSON: In this example, Task A has a priority of 1000, while Task B has a priority of 500. This ensures that ECS Fargate prioritizes Task A over Task B when allocating resources. ## **ECS Fargate Autoscaling for Cost Optimization** ECS Fargate autoscaling allows you to automatically scale your Fargate tasks based on demand. Autoscaling can help you save costs by To use ECS Fargate autoscaling, you need to define scaling policies that specify how many tasks to launch or terminate based on specific conditions. You can use CloudWatch alarms to trigger scaling actions based on metrics such as CPU utilization, memory utilization, or application load. ### **How to set up Autoscaling?** To In the ECS console, click on the "Clusters" tab and select your cluster. Click on the "Auto Scaling" tab and then click on "Create Scaling Policy". Choose the scaling policy type, such as "Target Tracking Scaling", and configure your scaling policy. ### **Configure your target tracking scaling policy** For example, you can set a target for average CPU utilization of your tasks. To do this, choose "ECSServiceAverageCPUUtilization" as the target metric and set the target value, for example, 70%. This means that the scaling policy will increase or decrease the desired number of tasks to maintain an average CPU utilization of 70%. For example, you can set a target for average memory utilization of your tasks. To do this, choose "ECSServiceAverageMemoryUtilization" as the target metric and set the target value, for example, 80%. This means that the scaling policy will increase or decrease the desired number of tasks to maintain an average memory utilization of 80%. ## **Fargate vs EC2: Which is more cost-effective?** Fargate and EC2 are both options for running containers on AWS, but which one is more cost-effective? The answer depends on your specific requirements and workload. Fargate is more cost-effective for workloads with variable demand or unpredictable workloads. Fargate eliminates the need to manage servers or clusters and allows you to pay for the resources you use. EC2 is more cost-effective for workloads with predictable demand or steady-state workloads. EC2 gives you more control over the underlying infrastructure and allows you to optimize costs by choosing the right instance types and sizes. ### **Best Practices for AWS Fargate Cost Optimization** Here are some best practices for AWS Fargate cost optimization: * Analyze your application's resource utilization and adjust your task definitions accordingly. * Use Fargate spot pricing to save costs on non-critical workloads. * Use task placement strategies to optimize resource utilization. * Use autoscaling to automatically scale your tasks based on demand. ## **Conclusion** This article walks you through some best practices to master AWS Fargate cost optimization by providing tips for right-sizing and task scheduling with ECS Fargate. By following these tips and using the right tools, you can optimize your Fargate costs and save money for your organization. These practices apply to a wide range of AWS Services. Even if you are running a serverless framework, Fargate optimization tips will help you reduce costs. Remember to analyze your application's resource utilization, use Fargate spot pricing, and use autoscaling to scale your tasks based on demand. With these best practices, you can master cost optimization with AWS Fargate. _CloudKeeper helps you in_ _of your entire AWS Infrastructure, spanning a wide range of AWS Services including AWS ECS, AWS EC2, Fargate, and much more. And the best part, the savings are contractually guaranteed! Want to know more?__._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * * * * * * I am looking for blogs on Automation Cloud Cost Management AWS EDP AWS Services Cloud Cost Analytics Cloud Cost Optimization DevOps FinOps Strategy RI Management Kubernetes The Complete Guide to AWS PPA Contract Negotiation for Growing Enterprises A practical guide to AWS PPA or EDP negotiations, covering commitments, discounts, flexibility, risks, and best practices to help growing enterprises secure better pricing and long-term cloud value. By Team CloudKeeper 19 Dec, 2025 Ask the Cloud Expert: A Deep Dive Q&A on AWS PPA In this Q&A, CloudKeeper’s AWS PPA expert Aman Dixit shares real-world insights to help clients navigate PPAs and make smarter, cost-effective decisions. By Team CloudKeeper 04 Sep, 2025 Introducing the AWS EDP Tracker in CloudKeeper Lens AWS EDP Tracker is a real-time interactive dashboard that gives you end-to-end visibility to monitor, forecast, and optimize your EDP spend throughout its term. By Harsh Agarwal 05 May, 2025 From Good to Great: Supercharge Your AWS EDP Plan with a Partner Learn how partnering with the right AWS EDP partner can simplify the complexities of AWS EDP, helping you secure great benefits at lower commitments & cost. By Team CloudKeeper 17 May, 2024 An Essential Guide to AWS EDP to Bag High Discounts The AWS Enterprise Discount Program (AWS EDP) is an enterprise-level cloud program with substantial benefits on their AWS cloud spending. By Team CloudKeeper 02 Feb, 2024 Considerations for AWS EDP: Lightning Theatre Session at AWS re:Invent 2023 Understand the key considerations for AWS EDP explained by Aman Aggarwal at Lightning Theatre Session - AWS re:Invent 2023. By Team CloudKeeper 15 Dec, 2023 How to Maximize the Value of your Cloud Investment with the AWS Enterprise Discount Program? Learn how CloudKeeper has been delivering maximum value to its AWS EDP customers for more than a decade now, with instant and guaranteed savings. By Sakshi Srivastava 10 Mar, 2023 Crafting a Long-Term Cloud FinOps Strategy with AWS EDP Understand how the AWS Enterprise Discount Program offers you unlock big AWS savings and how a cloud FinOps partner could help you make the most of it. By Team CloudKeeper 10 Mar, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Amazon Web Services (AWS) offers the managed database service known as Amazon RDS (Relational Database Service). Users can set up, run, and scale a relational database in the cloud with this cloud-based service without worrying about the supporting infrastructure. The prominent relational database engines Amazon Aurora, MySQL, PostgreSQL, MariaDB, Oracle, and Microsoft SQL Server are all available as options with Amazon RDS. Users can concentrate on their applications because Amazon RDS automates repetitive administration activities including database setup, patching, backup, and recovery. Through its Multi-AZ deployment option, which replicates data to a standby instance in a different availability zone, Amazon RDS offers high availability and durability for databases. Additionally, it gives users access to automated backups, point-in-time recovery, and snapshots, while helping in RDS cost optimization. AWS RDS makes it simpler to set up, run, and scale a relational database in the cloud. As with any cloud service, cost optimization is crucial to prevent overspending. For DevOps and DBAs, the following are some techniques for AWS RDS cost optimisation: * **Make use of reserved instances:** With AWS reserved instances, you can commit for a period of one or three years in exchange for a reduction in the hourly usage fee. Here is an example of achieving Here is the comparison of On-Demand vs Reserved Instances cost for an RDS instance of type›r5.2xlarge: * **Select the appropriate instance type:** There are numerous instance kinds available with different CPU, memory, and storage capacities through AWS RDS. Select a type of instance that satisfies your performance needs while not being over-provisioned. For example, if you use a db.t3.micro instance instead of a db.m5.large instance for a low-traffic database, you can save around 50% in costs and ensure RDS cost optimization. * **Make smart use of Multi-AZ deployment:** High availability and durability are provided for your database by multi-AZ deployment. Nevertheless, it has a price because you're essentially running two instances at once. Instead of using Multi-AZ deployment for all instances, think about using it exclusively for databases that need high availability. * **Using Amazon EC2 instead of Amazon RDS for lower environments:** Here is an illustration of how using Using the above prices, here's the cost breakdown over one year: * **Use autoscaling:** The number of RDS instances in your fleet can be * **Use Amazon Aurora rather than conventional RDS:** A highly scalable, highly available, and highly performant relational database that is compatible with MySQL and PostgreSQL is called Amazon Aurora. While offering better performance, it's frequently more affordable than conventional RDS instances. * **RDS cost analysis with AWS Cost Explorer:** You may * **Smartly choose the database Region:** As of May 2023, the following table compares the hourly On-Demand costs for a db.r5.large instance using the MySQL database engine across several AWS regions: Find out if migrating your database instances to a region is worthwhile. However, this won't significantly affect the cost (aside from the fact that you are using the Sao Paulo region). * **Stop/Start RDS Instances:** The cost of the database instance varies according to how long it is running. When not in use or after business hours, you can terminate your testing instances. The console can be used to accomplish this. Alternatively, you could programmatically stop (and restart) the database instances at specific times each day. Consider the scenario where you only use a few database instances during regular business hours. Keep in mind that you will still be charged for the storage and snapshots utilized even when your database is not active. A database can also be halted for a period of up to 7 days. AWS will automatically launch it after this time period. * **Removing manual snapshots:** Manual snapshots created by Amazon RDS are user-initiated backups. AWS doesn't remove them unless you ask for it. Therefore, if you don't specifically remove them, they will be rendered useless. The snapshot will remain even if the database is deleted. Also keep in mind that AWS will bill you at the Backup Storage rate. Reviewing older photos and deleting any that are no longer needed is a good practice. Also, keep in mind that having automatic backups is simpler. They will always be current because AWS will delete any old automatic backups that go beyond your retention window. Storage backups (and snapshots) are further kept redundantly across AZs in S3. This is a highly recommended * **Wisely choosing the DB engine:** As of May 2023, the following table compares the hourly On-Demand prices for several database engines on RDS for the db.r5.large instance type in the US East (N. Virginia) region: A database engine change is not an easy operation. Not just the database, but the data also needs to be updated. You must ensure that the code using it is likewise changeable. And it must be used properly by your staff. Having said that, it's vital to remember that this kind of database technology will significantly affect your prices. If you can update the database's technology, you could prevent the licensing fees. * **Keep an eye on and modify your database consumption:** To improve performance and cut costs, keep an eye on your database consumption and change the size of your instance, storage, and other options. Utilize tools like AWS CloudWatch and Amazon RDS Enhanced Monitoring to track the performance of your database and spot any places where efficiency can be increased. Also make sure to use instance types like EC2 reserved instances, AWS convertible reserved instances and more * **Use Amazon RDS Performance Insights to optimize performance:** You can use a tool called Amazon RDS Performance Insights to analyze and troubleshoot the performance of your RDS instances. Use it to find areas where performance can be improved and costs can be decreased. DevOps and DBAs could ensure that they're getting the most out of their RDS servers while minimizing costs, by putting these AWS RDS cost optimization tactics into practice. _Streamline your_ _exercise by partnering with a Cloud FinOps expert. CloudKeeper helps you optimize your entire AWS landscape including EC2, RDS, CloudFront and multiple other services, with guaranteed cost savings of up to 25%.__to learn more!_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Scaling your business with the power of cloud computing is not always smooth sailing. You need a robust and comprehensive cloud support system to ensure you resolve all the complexities and technical challenges without impacting the user experience. This blog delves into various levels of cloud support plans offered by Amazon Web Services and how you can avail of their most comprehensive plan, By complexities and challenges, we mean unexpected downtimes, security vulnerabilities, cost overruns, compliance issues, and anything else that could quickly escalate without the right support. Cloud support personnel are your first line of defense here, saving you from disruptions that could cost your business time and money. Whether it’s a sudden spike in user traffic that could overwhelm your resources or a security breach that needs immediate attention, having skilled professionals on hand could make all the difference. Cloud providers themselves understand these requirements and thus offer a range of support plans tailored to different needs. **AWS itself has four different levels of support plans** , supporting companies right from basic billing support to complex architectural recommendations. **1. AWS Developer Support:** The basic level of support, ideal for individuals experimenting or testing in AWS. It provides access to AWS Trusted Advisor, basic technical support during business hours, and **2. AWS Business Support:** The minimum recommended tier for production workloads. The technical support coverage and response times are better than developer support but do not include designated account managers and priority assistance. Both these support tiers also lack any architectural guidance. **3. AWS Enterprise Support:** The highest tier of support, offering comprehensive support with a dedicated Technical Account Manager (TAM), 24*7 access to senior cloud support engineers, and extensive architectural reviews. This plan is designed for mission-critical workloads and requires a significant investment which is why the AWS Enterprise Support pricing is a barrier for many organizations. **4. AWS Enterprise On-ramp Support:** Businesses that need comprehensive support features but do not have the budget to commit to AWS Enterprise support could opt for this support tier. It almost all supports features from the Enterprise tier, with a few exclusions in the availability of a dedicated TAM and custom architecture reviews. ## **What is AWS Enterprise Support?** Specifically tailored for organizations, especially enterprises, that need Businesses that sign up for AWS Enterprise Support benefit from 24*7 access to support engineers and a dedicated account manager who acts as their point of contact with the AWS support services. This ensures immediate assistance, proactive monitoring, and periodic reviews to ensure the cloud operations are not impacted. Going beyond traditional helpdesk services, the AWS Enterprise Support program offers the following benefits: **Proactive Monitoring and Health Checks:** Continuous monitoring of your AWS environment to find solutions to potential issues early. **Capacity Planning:** Expert advice on optimizing resources to meet your needs efficiently, like planning for a business event. **Security and Compliance:** Making necessary updates to your AWS setup to meet security and regulatory requirements. **Architecture and Migration Support:** Assistance with system improvements and **Access to AWS Experts:** Direct access to experienced AWS professionals for technical advice. With this top-tier support, AWS enables businesses to achieve enhanced cloud performance, optimized costs, and strengthened security. AWS reports that enterprises leveraging AWS Enterprise Support see an average cost savings of over 15%, compared to those on other support tiers with similar AWS spend. Additionally, organizations benefit from early access to the latest tools, technologies, and innovations within AWS, empowering them to stay ahead of the curve and fully optimize their cloud environment. ## **Core Features of AWS Enterprise Support** The range of support services offered by the AWS premium support tiers is substantially bigger compared to the basic plans. Let’s explore some of the most important features of the AWS Enterprise Support program. **Access to the AWS Support Services Team** You get direct access to AWS support engineers who help resolve a wide range of technical issues. They help with troubleshooting, configuration errors, performance issues, or any service-related challenges. With AWS Enterprise Support, you also get priority attention, with guaranteed response times depending on the urgency of the issue. Critical production outages can receive responses in as little as 15 minutes. This structured escalation ensures that high-priority issues are handled promptly to minimize downtime. **24*7 Technical Support** One of the highly desired benefits of AWS Enterprise Support is the round-the-clock access to AWS engineers. You can ensure that technical assistance is always available, whether it’s troubleshooting issues or answering service-related questions. Businesses get 24*7 access to cloud support engineers via phone, web, and chat. You also get an unlimited quota for cases. **AWS Service Guidance** With this feature, you get expert advice on **Designated Technical Account Manager** Businesses get a designated Technical Account Manager (TAM) who acts as a bridge between you and AWS, ensuring you get to leverage the AWS support services to the maximum. An AWS and Cloud expert, the TAM offers proactive support for your AWS setup by monitoring your infrastructure, offering personalized recommendations for improvements, and assisting in cloud cost management. They also assist you with your AWS support services tickets ensuring smooth and efficient resolution of technical issues. AWS also provides a designated Solution Architect as part of your cloud support team, who **TAM-Assisted Case Escalation** In critical situations, your Technical Account Manager assists in escalating support cases to ensure they receive top priority from AWS engineers. This service is designed for high-severity issues, to ensure minimal disruption to your operations. TAMs work with the AWS support services team to optimize the communication and timeline for case resolutions. **Architecture Reviews** With AWS Enterprise Support, you get regular assessments of your architecture to ensure it aligns with the best practices for performance, scalability, and security. This helps optimize your workloads, ensuring that your architecture is robust and cost-effective. **Business Reviews** Experts from the AWS support services team conduct regular business reviews to assess your cloud usage, identify areas for improvement, and align your cloud strategy with your business objectives. By aligning AWS solutions with your business objectives, they ensure you’re continuously gaining the most value from your AWS investments while driving innovation. **Application Guidance** With top-tier cloud support, AWS goes one level up and provides support for specific application workloads, fine-tuning them to run efficiently on the cloud. The guidance covers best practices for deployment, configuration, and scaling on AWS infrastructure. **Infrastructure Event Management** This includes proactive support for major infrastructure events such as large-scale migrations, product launches, or business campaigns that could have peak traffic periods. This service includes detailed planning and technical assistance to ensure smooth operations. AWS experts collaborate closely with your technical team to mitigate risks and ensure success. **AWS Trusted Advisor Priority** **Programmatic Case Management with AWS Support API** This feature helps you create, monitor and manage support tickets through automated means, by integrating AWS Support API with existing workflows. It helps streamline repetitive tasks such as updating case statuses, escalating issues, or retrieving historical case information, to improve efficiency. **Training and Workshops** AWS Enterprise Support offers 500 free training credits and access to workshops. Additional credits are available at a 30% discount. These resources help your team build cloud expertise and stay current with AWS best practices, enhancing your skills and ensuring effective use of AWS services. AWS Enterprise Support also has certain features like access to AWS re: Private, AWS Managed Services, and AWS Countdown Premium, which are available at an additional fee. ## **Comparison of AWS Support Services Plans** Although there is some overlap in standard support features, the higher-tier plans offer a significantly broader range of services compared to the basic plans. Here's a detailed comparison of all AWS support tiers: ## **AWS Enterprise Support Pricing** AWS Enterprise Support uses a tiered pricing model, with the cost being the greater of a fixed fee or a percentage of your AWS usage charges, although it has a minimum monthly fee of $15,000. Beyond this, the pricing structure is as follows: 10% of the first $150,000 of monthly AWS charges 7% of charges from $150,000 to $500,000 5% of charges from $500,000 to $1 million 3% of charges exceeding $1 million. **Example:** If your monthly AWS charges total $700,000, your support cost would be calculated as: 10% of $150,000 = $15,000 7% of $350,000 ($500,000 - $150,000) = $24,500 5% of $200,000 ($700,000 - $500,000) = $10,000 Total support cost = $15,000 + $24,500 + $10,000 = $49,500 Thus, you would pay $49,500 per month for AWS Enterprise Support. As you would have noticed, the AWS Enterprise Support pricing is substantial and is most suitable for large organizations with significant AWS usage and complex environments. ## **AWS Enterprise Support at a Fraction of the Cost** Many organizations stand to benefit from the comprehensive range of features offered by AWS Enterprise Support, especially the availability of a dedicated Technical Account Manager (TAM) and priority assistance. However, they could be limited by budget constraints. To address this, AWS offers a workaround through the AWS Partner-Led Enterprise Support Program, allowing organizations to access the same level of support at a significantly lower cost. ## **Who Provides AWS Partner-Led Enterprise Support?** AWS partners who are part of the AWS Solution Provider Program can offer Partner-Led Enterprise Support to their customers. These partners undergo ## **AWS Partner-Led Enterprise Support Program by CloudKeeper** CloudKeeper, an AWS Premier Consulting Partner, offers the Partner-Led Enterprise Support model, delivering all the benefits of AWS Enterprise Support at a custom discounted pricing. Through CloudKeeper, businesses can access high-quality cloud support services, with added flexibility and cost savings that make it easier for organizations with tighter budgets to benefit from AWS’s premium offerings. Here’s a snapshot of how ## **Advantages of Partner-Led Support** While Partner-Led Enterprise Support closely mirrors AWS Enterprise Support, it also provides several unique benefits: **Cost Savings:** Partner-led Support generally comes at a lower cost than AWS Enterprise Support, making it accessible for organizations with tighter budgets. **Flexible Pricing:** Partners offer customized pricing models based on the business's specific cloud support needs, allowing for better cost management. **Lower Costs for Partner Programs:** Customers who sign up for programs like the **Personalized Service:** With a focus on customer relationships, Partner-led Support often includes tailored advice and solutions specifically aligned with the business’s unique requirements. **Extended Expertise:** Partners bring additional expertise in cloud-native technologies and DevOps, which can be beneficial for more specialized cloud support needs. _We’d recommend_ _to learn about Partner-led Enterprise Support in detail._ ## **Conclusion** Cloud support is important for all kinds of businesses and while hyperscalers themselves offer support plans, cost considerations can limit access to AWS premium support services like AWS Enterprise Support. With programs like the AWS Partner-Led Enterprise Support programs, organizations can now access nearly all the benefits of AWS’s top-tier support at a fraction of the cost. Working with an expert cloud support partner helps organizations access a comprehensive range of services personalized to their specific needs. Additionally, experienced partners like CloudKeeper also offer a host of extended services like DevOps Support, Workload Modernization, and Cloud Cost Optimization, with no additional costs, making it a really attractive choice. With a robust cloud support framework to streamline your operations, you can make the most of your cloud infrastructure efficiently while not compromising on innovation and your business goals. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents A data warehouse is a type of data management system that is designed to enable and support business intelligence activities, especially analytics. Data warehouses are solely intended to perform queries and analysis and often contain large amounts of historical data. Data warehousing plays a crucial role in modern businesses, enabling efficient analysis and decision-making processes. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. However, optimizing costs while maintaining performance is essential to maximize the benefits of Redshift. There are a number of best practices you can follow to ensure you’re getting the best value with Amazon Redshift. There are many different best practices available for AWS Redshift cost optimization, but in this blog, we will explore some of them, which are popular in the industry, and will help you make the most of your Amazon data warehouse services investment. ## **Best practices to manage Amazon data warehouse for cost optimization** ### **Sizing Considerations** Cost optimization starts with Amazon Redshift RA3 nodes with managed storage enable you to optimize your AWS data warehouse by scaling and paying for compute and managed storage independently. With RA3, you choose the number of nodes based on your performance requirements and pay only for the managed storage that you use. There’s a recommendation engine built into the console to help you make the proper selection. Previous generation nodes include DC2 (Compute intensive), and DS2 (Storage Intensive). Reserved instances (RI) (also called reserved nodes in the Amazon Redshift console) can provide up to 75% savings vs on-demand pricing. ### **Use Auto WLM (Workload Management)** Auto WLM enables dynamic workload management by automatically allocating resources based on workload priorities. Assigning appropriate WLM queue and concurrency settings allows you to optimize resource allocation, ensuring critical workloads receive sufficient resources while lower-priority workloads run more cost-effectively. Continuously monitor and fine-tune your WLM configuration to strike the right balance between performance and cost efficiency. ### **Trusted Advisor** The Trusted Advisor application (available under management and governance) runs automated checks against your Amazon Redshift resources in your account to notify you about Redshift cost optimization opportunities. Checks include the following: * Checks usage to provide recommendations about when to purchase reserved nodes to help reduce costs. **Recommended action in this case:** Evaluate and identify clusters that will benefit from purchasing reserved nodes. Moving from on-demand will result in between 60-75% cost savings. * Checks for clusters that appear to be underutilized (< 5% average CPU utilization for 99% of last 7 days). **Recommended action in this case:** Shutting down the cluster and taking a final snapshot or downsizing will save costs./li> ### **Data Partitioning** Partitioning your data based on relevant criteria, such as time or key ranges, can significantly improve query performance and reduce costs. Partition pruning allows Redshift to skip irrelevant data blocks during query execution, reducing the amount of data scanned and improving query performance. By organizing your data into smaller, more manageable partitions, you can minimize the resources required for queries and lower costs. ### **Cost Explorer** AWS Cost Explorer helps you visualize, understand, and * **Budgets:** Amazon Redshift customers can create budgets based on usage type (paid snapshots, node hours, and data scanned in TB), or usage type groups (Amazon Redshift running hours) and schedule automated alerts. * **Cost and Usage Reports:** Amazon Redshift cost and usage reports include usage by an account and AWS Identity and Access Management (IAM) users in hourly or daily line items, as well as tags for cost allocation. We can integrate it with AWS Redshift. * **Reservations:** Provides recommendations on ### **Scheduled Pause and Resume** Leverage the scheduled pause and resume feature in AWS Redshift to further optimize costs. If your Redshift cluster is not required during specific time periods, schedule it to pause automatically and resume it when you need this. Pausing the cluster suspends compute resources and saves costs. ### **Compressing Amazon S3 file objects loaded by COPY** The _COPY_ command integrates with the massively parallel processing (MPP) architecture in Amazon Redshift to read and load data in parallel from Amazon S3. Leveraging compression for Amazon S3 file objects loaded by the _COPY_ command in Redshift offers significant cost optimization benefits. It reduces storage costs, improves data loading and query performance, minimizes data transfer expenses, enhances resource utilization, and provides flexibility in choosing compression algorithms. By using this feature, you can maximize the efficiency and cost-effectiveness of your AWS data warehouse solution. ### **Amazon Redshift Spectrum** By using this feature of Amazon Redshift Spectrum you can store data in open file formats in your Amazon S3. An analyst that already works with Redshift will benefit most from Redshift Spectrum because it can quickly access data in the cluster and extend out to infrequently accessed, external tables in S3. It's also better suited for fast, complex queries on multiple data sets. Using this feature offers us benefit in the following way: AWS recommends that a customer compresses its data or stores it in column-oriented form to save money. Those costs do not include Redshift cluster and S3 storage fees. ### **Improved Query Performance** Compressed data in Redshift can lead to better query performance. When compressed data is stored, it takes up less disk space, allowing more data to reside in memory. This increased data locality improves query execution times by reducing the amount of disk I/O required to access the data. Ultimately it will save us money. ### **Concurrency Scaling** While resizing your cluster is fit for known workloads, for spiky workloads you should consider using the concurrency scaling feature. Concurrency scaling is a cost-effective way to pay only for additional capacity during large workload spikes, as opposed to adding persistent nodes in the cluster that will incur extra costs during downtime. Each cluster earns up to one hour of free concurrency scaling credits per day, which is sufficient capacity for almost all workload types. For the small chance you go over your allotted free credits, you simply pay a per-second on-demand rate for the usage that exceeds those credits. To implement the concurrency scaling, the user will route queries to concurrency scaling clusters by enabling a workload manager (WLM) queue as a concurrency scaling queue. These are some of the popular Redshift optimization techniques to achieve cost optimization while using AWS Redshift Service, you can explore other best practices as well. ## **Conclusion** As we have seen some of the _While you are absorbing the above-mentioned ways for redshift optimization techniques, a_ _can help you benchmark your infrastructure against the best practices and design principles created by AWS. Cloudkeeper funds your AWS WARs with a focus on the six recommended pillars: operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability. A_ _can accelerate your savings by manifolds._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents As we move into 2025, AWS re:Invent continues to be a beacon for cloud innovation, showcasing groundbreaking advancements that will shape the future of technology. Here's a glimpse into what trends and technologies are set to dominate the ## **1. Generative AI at Scale** Generative AI remains a central focus, with AWS unveiling enhancements to its Bedrock service. Over 100 foundation models, multimodal AI integration, and intelligent tools for efficient deployments were highlighted. These developments are designed to make generative AI adoption cost-effective and scalable, especially for applications in healthcare, finance, and media. Notable announcements include the Nova AI model suite: **Nova Micro:** A low-latency, cost-efficient, text-only model. **Nova Lite:** Designed for multimodal AI applications, supporting text, image, and video processing. **Nova Pro:** A versatile multimodal model suitable for general use. **Nova Premier:** Advanced reasoning capabilities for solving complex problems. **Nova Canvas:** Professional-grade image generation tools. **Nova Reel:** Simplified high-quality video creation. These innovations aim to make generative AI accessible and transformative for businesses across all sectors. SageMaker also received significant updates, including automated workflows for model training and deployment. These advancements empower organizations to leverage cloud-based AI infrastructure without the complexity of managing extensive resources. ## **2. Hybrid Cloud and Quantum Computing** Hybrid cloud continues to gain traction as enterprises seek flexible, scalable solutions. The integration of Nvidia CUDA-Q with AWS Braket showcases how quantum and classical computing can work in tandem to solve complex problems. This hybrid model is expected to drive innovation in fields like cryptography, materials science, and financial modelling. AWS further demonstrated its infrastructure prowess with the introduction of **Trn2 UltraServers** , delivering 83.2 petaflops of computing power. EC2 Trn2 Instances, powered by Trainium2, offer 30–40% better price performance, making it easier for businesses to run large-scale AI workloads efficiently. ## **3. Cloud-Driven Robotics and Simulation** AWS is pushing the boundaries of robotics development with platforms like Nvidia's Isaac Sim. These tools, hosted on AWS, allow for the creation of synthetic data and simulation environments, enabling developers to train robotic systems more efficiently. Such advancements reduce the time and cost associated with physical prototyping. AI/ML innovations also include **Bedrock Agents** , which enable seamless multi-agent collaboration, and **Bedrock Model Distillation** , delivering models that are five times faster and 75% cheaper. These advancements make AI-driven simulations and collaborative robotics development more accessible to enterprises. ## **4. Developer-Centric Innovations** The **Amazon Q Developer** is transforming software development by automating tasks like documentation, code reviews, and unit testing. These tools, embedded into IDEs and platforms like GitLab, boost developer productivity and streamline workflows. For businesses, Amazon QuickSight now integrates with **Amazon Q** , unifying business data for smarter decision-making. Its ability to expand data index capabilities with ISVs enhances the accessibility and utility of cloud-stored data, further cementing the role of AWS in enterprise cloud strategies. ## **5. Sustainability in Cloud Infrastructure** AWS is leading sustainability efforts with innovations like liquid-cooled data centres designed to support high-performance workloads. These centres optimize energy use, meeting the increasing demand for resource-intensive AI applications while minimizing environmental impact. Such initiatives align with global efforts to create greener cloud solutions. ## **6. Customer-Centric Cloud Experiences** Enhanced tools like Amazon Connect, now integrated with generative AI features, are helping businesses deliver superior customer experiences. These capabilities are already driving cost reductions and efficiency gains in global enterprises. AWS also highlighted its work with **DynamoDB Global Tables** and **Aurora DSQL** , offering scalable, distributed databases that ensure availability and performance for organizations with a global footprint. ## **7. Edge Computing and Distributed Cloud** The growing importance of edge computing was evident with AWS Outposts and Local Zones. These solutions bring cloud capabilities closer to where data is generated, reducing latency and enabling real-time processing. Industries like manufacturing, retail, and IoT applications stand to benefit significantly from this distributed cloud approach. ## **8. Industry-Specific Cloud Applications** AWS's focus on vertical-specific solutions was evident with the rollout of tailored applications for manufacturing, healthcare, and logistics. For example, cloud-based platforms are optimizing supply chains, enhancing customer experiences, and enabling advanced analytics in real time. These innovations demonstrate the versatility of cloud computing in addressing diverse business needs. ## **Looking Ahead to 2025** AWS re:Invent 2024 has once again demonstrated why it is the premier event for cloud innovation. The advancements in generative AI, hybrid cloud models, quantum computing, and sustainable infrastructure showcase the immense potential of cloud computing in 2025 and beyond. These innovations are set to redefine industries, enabling businesses to harness the full power of the cloud for growth and efficiency. Team CloudKeeper at AWS re-Invent 2024 CloudKeeper was proud to be part of this transformative event. As a trusted partner for Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents ## **AI Takes Center Stage** The opening keynotes set a clear direction: **AI agents, not just assistants** , are the next major shift in cloud computing. AWS CEO Matt Garman framed this shift as moving beyond chat interfaces to autonomous systems that execute workflows independently — a theme that resonated throughout the week. ### **Top Announcements** * **Amazon Nova 2 family:** New models like **Nova 2 Sonic** for speech-to-speech experiences, **Nova 2 Lite** for cost-effective reasoning, and **Nova 2 Omni** for multimodal AI. * **Nova Forge:** A major leap in enterprise AI — build custom foundation models using AWS checkpoints and your own data. * **Nova Act:** AI agents that automate browser workflows with high reliability. * **Bedrock AgentCore:** Production-ready controls, memory, and quality evaluations for enterprise agentization. * **S3 Vectors GA:** Scalable vector search hitting billions of vectors with fast latencies and up to **90% lower cost** vs specialized DBs. * **Multicloud preview with AWS Interconnect:** Secure private links to other clouds such as GCP. These innovations weren’t surface-level demos — they were _practical tools_ executives and engineers can apply immediately to build, automate, and scale. ## **Infrastructure & Compute Evolutions** AWS also doubled down on performance and cost-efficiency: * **Graviton5:** AWS’s most powerful CPU yet, offering significantly better compute for databases, analytics, and high-performance workloads. * **Trainium3 UltraServers:** Powerful new AI silicon enabling faster training and inference at lower unit cost. * **Lambda Durable Functions & Managed Instances:** Let cloud teams build long-running workflows without paying for idle time — a big win for serverless efficiency. Behind the scenes, talks emphasized that _performance and cost control still matter as much as AI innovation._ Throughout re:Invent there were deep dives into cloud governance, observability, and optimization best practices. ## **Cloud Cost Conversations — Latte on Cloud Costs Live at re:Invent** One of CloudKeeper’s highlights was _taking “_ _” live_ from the re:Invent floor. These on-camera discussions with , Senior Manager, Cloud Cost Optimization, AWS and Founding Account Executive, OpenOps. The experts brought practical strategies from CloudKeeper’s team to a broader audience — and resonated with builders struggling with runaway bills. We covered: * **Cost visibility across AI workloads** * **Rightsizing compute with Graviton & Trainium silicon** * **Finance + DevOps alignment for predictable billing** The coffee-cup chats turned out to be a perfect setting for honest, tactical conversations that _developers and finance partners both loved._ ## **Sessions, Community & the Overall Vibe** Outside keynotes and product news, the energy was unmistakable: * Crowded breakout rooms on AI engineering best practices * Multi-cloud resilience talks amid broader enterprise concerns * Security sessions on new IAM innovations like _IAM Outbound Identity Federation_ and Policy Autopilot tools that help reduce risk while scaling development velocity. And of course, re:Play and hallway conversations reminded us why re:Invent isn’t just about tech — it’s about _people, community, and the shared commitment to innovate._ ## **Final Thoughts** AWS re:Invent 2025 wasn’t about _the next shiny thing._ It was about _making innovation practical and operationalizable._ Whether your team is building AI applications, optimizing cloud spend, or tightening security at scale, there was something here to elevate your strategy. CloudKeeper returned with learnings, relationships, and content that will fuel insights for months to come — starting with the episodes we recorded live for you. Stay tuned for the upcoming episodes of the special edition of Latte on Cloud Costs, recorded at re:Invent 2025! Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Chief Revenue Officer - North America Ryan brings over a decade of leadership experience in building high-performing teams & driving revenue growth. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents In the last decade, the cloud revolution has empowered businesses of all sizes to leverage the power of Amazon Web Services (AWS) to help scale and grow. Cloud computing has grown into a vast ecosystem of technologies, products, and services giving rise to a multi-billion dollar economy growing exponentially each year, where many cloud providers compete for an ever-expanding cloud market share. The popularity of the Cloud is primarily because of its unique benefits and the major economic value it presents. Many recent reports show that cloud services offer a number of advantages over traditional on-premises infrastructure, including superior scalability, resilience, and cost management. However, as customers, ## **Who is an AWS Reseller?** An AWS reseller is a third-party company authorized by AWS to sell its cloud services. Resellers purchase AWS services in bulk at discounted rates and then resell them to customers. They usually bundle AWS offerings with additional services such as a cost visibility platform, consulting, support, and managed services, so the final bundle seems very lucrative to the end users. The target segment for AWS resellers typically are businesses looking for more personalized and tailored cloud solutions. ## **Choosing the Right Purchasing Method for AWS Services** To ## **Direct Purchases** In a direct purchase, businesses buy AWS services directly from Amazon Web Services without any intermediaries. In direct purchase, there is a higher control of a company over the cloud infrastructure. While large enterprises can enjoy a range of benefits from direct purchase, small and medium-sized enterprises (SMEs) and digital-native businesses (DNBs) can find it challenging to go for direct purchase. ## **Benefits of Buying AWS Directly** **Full Control and Flexibility:** Direct purchasing enables you to have greater control over your AWS resources. There is also direct access to all the functionalities and benefits of AWS without any reseller in between. **Direct Access to AWS Support:** There is direct contact between you and AWS support which eliminates any middleman whenever there is any issue, thus expediting troubleshooting and resolution. **Cloud cost-saving potential:** Directly purchasing resources from AWS could save you the additional mark-up that resellers could add for their services. Large companies with considerable AWS expenditures can negotiate directly with AWS to secure discounts or create tailored enterprise agreements. **Access to all AWS Programs:** Purchasing directly from AWS gives you access to all programs offered by AWS, including free tiers, credits for startups, training resources, etc. ## **Drawbacks of Buying AWS Directly** **Complexity:** For a small company, managing an AWS account without any reseller assistance can be challenging because of the expertise needed for the management. **Limited Support Access:** Free AWS support has limitations and companies need to subscribe to a premium plan like AWS Enterprise support for more advanced support options. This can add to the overall costs and not be a feasible option for SMEs **Hidden Costs:** Although direct billing saves you reseller markups, unforeseen costs can occur because of accidental resource overprovisioning or inefficient configurations if proper cost optimization practices are not followed. ## **Purchasing through an AWS Reseller** As mentioned earlier, a reseller is an AWS Partner. Resellers purchase AWS services in bulk at discounted rates and then resell them to customers usually bundled with other services like support etc. Purchasing AWS resources through a reseller ensures that there is a significant amount of handholding as far as cloud implementation is concerned. Let us look at the advantages and disadvantages of reseller purchases. ## **Benefits of Buying AWS Through a Reseller** **Cost Savings:** The biggest advantage that resellers offer is discounts because of bulk purchasing and negotiated rates, which can significantly benefit especially small businesses that do not have access to volume-based discounts. These discounts might otherwise go untapped if you directly purchase with AWS. It is however important to note that, buying through a reseller doesn’t automatically guarantee the best rates. You should compare the rates with direct purchases on a case-to-case basis. **Expertise & Guidance:** For businesses that lack in-house AWS expertise or are new to AWS cloud, AWS resellers can assist in **Industry-Specific Knowledge:** Many AWS resellers focus on specific industries, such as healthcare, finance, or retail. They offer tailored advice and services that address the unique needs and challenges of your industry. **Simplified Cloud Cost Management:** Resellers typically offer managed AWS services, account setup, resource management, and daily operations. This allows your internal team to concentrate on core business activities. **Enhanced Support and value-added services:** Companies can enjoy the added advantage of dedicated and personalized support with the reseller support teams at no extra cost. This is a higher level of support compared to the basic AWS support that comes with direct buying. Also, there are certain value-added services that resellers offer like **Simplified Billing Management:** AWS Resellers alleviate the complexities of AWS billing by consolidating multiple accounts, services, and usage data into a single, understandable format. **Strategic Guidance:** AWS Resellers can aid in developing a long-term cloud strategy aligned with your business goals. They access cloud partner network resources, programs, and incentives to further support and meet your specific business goals. ## **Drawbacks of Buying AWS Through a Reseller** **Dependency on the reseller and less control:** When working with a reseller, you might have to give up some control over your AWS account. The billing has to be done through a reseller. **Difficult to switch resellers:** Switching to another reseller or even to direct purchase would become difficult if a particular reseller has managed your AWS configurations. **Markup for their services:** Although in principle, resellers are supposed to offer your discounts, there is a possibility of markup fees for their additional support and services which could inflate your cloud bill. The choice between buying AWS directly or through a reseller depends on your needs. If you are a large enterprise with a strong internal cloud team and can access volume-based pricing for AWS services, going direct could be a feasible option. However, for savings on those who can't access volume-based pricing, lack cloud expertise, or need extra support, an AWS reseller can be invaluable. Partnering with an AWS reseller can significantly offer better cost savings, personalized support, consulting, etc. Use the APN network to find a reseller that matches your requirements and helps you reach your cloud goals. ## **Evaluating Reseller capabilities** One of the most reliable sources of finding a reseller is through the Amazon Partner Network(APN). It is a directory of vetted and qualified partners endorsed by AWS. All partners are categorized based on tiers (Standard, Select, Advanced, Premier) depending on their expertise, experience, and commitment to AWS. AWS also offers a partner finder tool that can ease your reseller discovery process. Besides APN, you can consider several factors for choosing the right reseller with the right set of capabilities. Some of them are - the expertise and experience of the reseller, the range of service offerings, pricing, communication and transparency, and their success stories. ## **Why You Should Choose AWS Billing with CloudKeeper?** CloudKeeper AZ is a ## **The value proposition of CloudKeeper AZ** **Enjoy savings, visibility, and expert support - all in one place at no cost or commitment!** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Chief Growth & Marketing Officer Naman is a seasoned GTM leader with deep expertise in technology sales, marketing, & strategic planning. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents ## **What are AWS Reserved Instances?** AWS Reserved Instances is a billing discount that offers significant cost savings to businesses that commit to a certain level of usage. For organizations with stable and predictable workloads, AWS Elastic Cloud Compute (EC2) instances can be reserved in advance, making By opting for AWS Reserved Instances, you'll effectively reduce your expenses. However, it's essential to remember that ### **Following are the types of AWS RIs** * **Standard RIs:** Ideal for steady-state usage, they offer the highest discounts (up to 72% off On-Demand). * **Convertible RIs:** Offer a discount (up to 54% off On-Demand) and the option to change the attributes of the Reserved Instance if the exchange creates an equivalent or greater Reserved Instance. For steady-state operation, Convertible RIs are best suited. It is possible to schedule RI launches within the time limits you specify. Depending on the capacity reservation, there can be a predictable recurring schedule within a fraction of a day, week, or month. ## **The Essential considerations while purchasing AWS Reserved Instances** **Purchases of AWS Reserved Instances are infrequent:** * The key point to remember is that when you make a reservation purchase, you commit to paying for every hour of the RI term regardless of whether the AWS RIs are used or not. * Whenever you purchase Reserved Instances in bulk once a year, your AWS RI needs may change over the course of that year due to changes to your infrastructure. * It has been recommended to follow the iterative Reserved Instances approach rather than ### **Excessive purchases of AWS RIs:** AWS offers Reserved Instances with three payment options: All Upfront, Partial Upfront, and No Upfront over 1 or 3-year terms. Depending on the amount paid upfront and the term length, discounts are greater. Calculate your specific reservation needs instead of just buying the RI with the greatest discount on a 3-year term. ### **Insufficient purchasing of AWS RIs:** We sometimes buy too few Reserved Instances (RIs) to be on the safer side and not overspend. We want to get just enough computing power, but this cautious approach can lead to running out of computing resources. When an organization makes this mistake, it can face various problems, and fixing it often means spending more money. ### **Extending the purchase period:** You need to review the contract you signed three years ago if it doesn't properly reflect your business needs today. With ### **Failure to manage changes and inaccurate calculations:** Effectively planning and managing your AWS Cloud infrastructure is crucial for maximizing its benefits. CloudKeeper offers a comprehensive solution that provides insights and takes action to help you better manage your expenses and AWS Reserved Instances. ### **Right-sizing Without Simulation:** A ### **Improper AWS RIs requirements:** The use of incorrect calculation methods by businesses when determining their reservation needs can lead to missed possibilities or unnecessary RI purchases. It is common for businesses to determine their needs based on the overall consumption rate of their Using the incorrect approach to determine RI needs would result in the over-purchase of reservations. For example - If three instances ran during a given timeframe, but each for 30% of that timeframe. In the scenario of all three instances running at mutually exclusive times, and a single instance can operate 90% of the time, it could be a reasonable suggestion to purchase just one reservation in this scenario. By using CloudKeeper Auto's Reserved Instance Planner, you can calculate hourly instance counts for each type of instance per OS and availability zone, which is the most efficient method for making RI purchase decisions. _Do you want to switch to a smarter_ _, and receive benefits like zero-touch RI Management, the flexibility of on-demand for all your Amazon EC2 resources, buy-back guarantee for unused reserved instances,__and much more, at no cost from your pocket? If your answer is yes, then_ _is precisely what you're looking for.__today._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents Cloud computing has revolutionized the way businesses operate in the digital age, providing a flexible and scalable way to manage infrastructure needs. However, it's essential to keep cloud cost optimization at the forefront, which is where AWS Reserved Instances (RI) come in. With the potential for significant savings, RI can be a powerful tool for organizations of all sizes. But to truly maximize those savings, it's crucial to follow cloud FinOps (Financial Operations) principles. By understanding your usage patterns, committing to RIs for the long term, utilizing RI exchanges, and following RI purchase recommendations, you can optimize your AWS RI purchases and ensure that you're getting the most value for your money. In this article, we'll explore these FinOps principles in more detail and show you how to set AWS cost optimization into motion, with the help of Reserved Instances. ## **What are AWS Reserved Instances (RI) and how do they save you money?** AWS Reserved Instances (RI) are contractual agreements that allow customers to reserve cloud capacity for a fixed period of time. By committing to using this capacity for the reserved period, customers receive a significant discount on the hourly rate compared to On-Demand instances. This makes RIs an ideal cloud FinOps tactic for businesses that require predictable workloads and need to optimize their cloud spending. This also helps in ## **The basics of FinOps principles and why they're important for optimizing RI purchases** FinOps is a powerful methodology that combines financial management, technical operations, and cloud technology expertise to maximize the value and efficiency of cloud investments. It provides you with the ability to When it comes to AWS RI purchases, ## **How to analyze usage patterns to determine the best RI offerings for your needs?** Analyzing usage patterns is a critical step in determining which AWS RI offerings are most appropriate for your business needs. * Collecting and analyzing usage data from your AWS account provides insights into instance performance and usage patterns. * Identifying consistent and stable workloads that can benefit from AWS RIs can help you optimize your RI usage. * You can leverage various tools and metrics for cloud cost tracking and * AWS Cost Explorer provides an intuitive interface for analyzing usage patterns, identifying opportunities to modify term length or instance size, and forecasting usage and cost trends. * AWS Trusted Advisor can help you * Following these technical best practices enables businesses to make informed decisions and achieve efficient AWS cost optimization. ## **How to sell RIs and unlock additional cost savings?** Selling unused or underutilized RIs can help you unlock additional cost savings and optimize your cloud infrastructure investments. AWS Marketplace can be used to sell your Reserved Instances. * The AWS Marketplace allows listing RIs for sale, for customers seeking to purchase them. * The Reserved Instance Marketplace provides a platform to list RIs for sale, set terms of sale, and negotiate with potential buyers. * Selling unused or underutilized RIs through these tools and programs can help businesses achieve better value for their cloud spending. * This approach can also enable other customers to purchase cost-effective RI options. * Recovering some of the upfront costs associated with purchasing RIs is possible through selling unused RIs. Reserved Instances offer valuable opportunities for cloud cost optimization when utilized for workloads and even if they remain unused. Incorporating Reserved Instances can be a highly _Now you can_ _and unlock superior savings with CloudKeeper Auto. And with our results-based pricing model, you only pay when you achieve AWS savings._ _Want to know more?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents You optimized your architecture. You right-sized your instances. You even turned off dev environments on weekends. And your AWS bill still made you flinch. The problem might not be what you're running. It might be how you're paying for it. Pricing model selection is the most underrated lever in AWS gives you three ways to cut compute costs significantly: the AWS Savings Plan, Reserved Instances, and Spot Instances. Each saves you anywhere from 40% to 90% versus On-Demand. But they are built for very different workloads, and picking the wrong one is just as expensive as picking none at all. ## **The Core Trade-Off Across All Three** * **AWS Savings Plan:** Commit to a spend amount, get flexibility in return * **Reserved Instances (RIs):** Commit to a specific resource, get the deepest discount * **Spot Instances:** Accept interruption risk, pay the lowest price on AWS The right answer depends on your workload's predictability, your team's operational maturity, and how much your infrastructure is likely to evolve. ## **Head-to-Head Comparison: Find Your Fit Fast** **Quick read:** _Not sure where to start? The AWS Savings Plan covers the most ground with the least overhead. Use Reserved Instances to go deeper on specific stable resources and push everything interruptible to Spot._ ## **AWS Savings Plan: The Smart Default** An **AWS Savings Plan** commits you to a minimum hourly spend on AWS compute over 1 or 3 years, in exchange for discounts up to 66% (Compute Plans) or 72% (EC2 Instance Plans) off On-Demand rates. The key advantage: AWS applies the discount automatically to your most expensive eligible usage. No manual matching, no inventory tracking. That simplicity makes it the go-to starting point for most **Best fit:** Teams that move fast, run mixed EC2 and serverless workloads, or want to simplify reserved instance management without tracking individual RI inventory. **Honest trade-off:** Slightly lower ceiling than the deepest RI discounts. If you have a perfectly stable workload and the discipline to manage it, RIs go further. ## **Reserved Instances: Maximum Savings, Maximum Commitment** Reserved Instances deliver discounts up to 72% off On-Demand, but require committing to specific instance configurations. This is not a model for teams that change their minds often. Regional RIs apply flexibly across a family within a region. Zonal RIs lock to a specific Availability Zone but come with a capacity guarantee, which matters when supply is constrained. **Best fit:** Steady-state workloads like RDS databases, ElastiCache clusters, or persistent application servers where the instance type will not change over the commitment term. **The hidden cost:** Poor reserved instance management is where organisations quietly bleed money. Utilisation below 80%, unmonitored expirations silently flipping back to On-Demand pricing, and mismatched Convertible vs Standard RIs can erode every dollar saved. Someone on your team needs to own this continuously, not just at purchase time. ## **Spot Instances: Radical Savings for Fault-Tolerant Workloads** Spot gives you access to unused AWS capacity at up to 90% off On-Demand. The catch: AWS can reclaim it with a two-minute warning. **Best fit:** Stateless, interruptible workloads including EMR jobs, ML training runs, rendering pipelines, and CI/CD runners. Containerised workloads on EKS or ECS handle interruptions especially well. **Never use Spot for:** Databases, stateful services, or any customer-facing application that cannot tolerate sudden node loss. **The one rule:** Diversify across multiple instance families and Availability Zones. When one pool is reclaimed, your workload keeps running in another. ## **The Winning Strategy: Layer All Three** The most cost-efficient AWS environments do not pick one model. They layer all three: Cover your baseline with an AWS Savings Plan, lock in specific long-lived resources like RDS with Reserved Instances, and route all interruptible workloads to Spot. This layered approach typically delivers 50 to 65% overall savings versus a pure On-Demand footprint. ## **Where to Start This Week** Open AWS Cost Explorer and pull your last 30 days of On-Demand spend. Flat, consistent usage patterns are your RI or Savings Plan candidates. Batch and non-production workloads are your Spot candidates. You do not need to do everything at once. Committing even 30% of your baseline compute to an AWS Savings Plan produces real savings within the first billing cycle. Cloud cost optimisation is not about finding one perfect pricing model. It is about matching the right tool to every layer of your stack. That is a decision you can make today. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * * * * * * I am looking for blogs on Automation Cloud Cost Management AWS EDP AWS Services Cloud Cost Analytics Cloud Cost Optimization DevOps FinOps Strategy RI Management Kubernetes AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 How We Strengthened Application Security with AWS WAF Learn how to secure web apps using AWS WAF with rate limiting, custom rules, and layered controls to reduce abuse and ensure reliable performance. By Aryan Kulshrestha 09 Apr, 2026 Migrating Workloads to AWS Graviton2 Instances A comprehensive guide to migrating workloads to Graviton2-based instances from legacy systems, with best practices across business and technical aspects. By Jatin Srivastava 24 Mar, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 Migrating Amazon RDS MySQL 8.0.35 to Amazon Aurora MySQL: What You Need to Know A practical step-by-step guide to migrating Amazon RDS MySQL 8.0.35 to Aurora MySQL, covering compatibility checks, migration methods, and performance and cost impact. By Pranav Bhardwaj 17 Mar, 2026 Securing Amazon QuickSight: Private URL Access, SSO Enforcement, and Regional Considerations This blog explains how to secure Amazon QuickSight using VPC endpoints, IP restrictions, and SSO, while addressing home-region limitations and enterprise access control. By Anjali Jain 12 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 12 12 Table of Contents A Well Architected Framework Review is a structured, expert-led process designed to assess and enhance the performance, security, and cost-efficiency of cloud infrastructures. This blog delves into the phased implementation of the AWS Well Architected Review Process, why a customized approach is crucial for different business needs, and how partnering with an expert Well Architected Partner can help you achieve optimal cloud performance and cost savings. One of the major reasons why businesses choose AWS as their cloud partner is its However, managing such a broad array of services within a complex cloud infrastructure could take time and effort. Without a carefully designed architecture, businesses may face inefficiencies, such as underutilized resources, wasted volumes, and unnecessary costs. Optimizing this infrastructure from scratch could use up a lot of time and resources, which could be focused elsewhere to drive your business growth. That’s why AWS offers the AWS Well Architected Framework, a blueprint of sorts, that could help you benchmark various aspects of your cloud architecture with global benchmarks and standards for building and managing cloud environments. Based on their vast experience of working with organizations across the world, the framework sets forth key concepts, design principles, and best practices that ensure your cloud architecture is robust and cost-efficient. The AWS Well Architected Review (WAR) leverages this framework to systematically analyze and optimize your cloud setup, ensuring it meets these high standards. While the terms **AWS Well Architected Review** and **AWS Well Architected Framework** are sometimes used interchangeably, it’s important to note that the framework sets the standards, while the AWS Well Architected Review Process refines your infrastructure to align with these benchmarks. ## **The pillars of AWS Well Architected Framework** The AWS WAR Framework is created based on six foundational pillars that influence different facets of any cloud infrastructure. * **Operational Excellence** - Defining operational standards, monitoring workloads, and enabling continuous improvement. * **Security** - Protecting customer and business data, controlling access privileges, and managing security events. * **Reliability** - Addressing resource availability, disaster recovery, and managing service disruptions. * **Performance Efficiency** - Streamlining resource selection, rightsizing, and performance monitoring. * **Cost Optimization** - Tracking cloud costs, eliminating waste, and optimizing spend while the business scales. * **Sustainability** - Designing the cloud architecture for environmentally conscious resource management. Each of these pillars further consists of various design principles and best practices, that serve as guidelines for achieving the highest standards on various functional aspects. The core purpose of this framework is to find any areas of improvement in your infrastructure, critical issues that should be addressed as well as ### **Who performs the AWS Well Architected Reviews?** Although the framework has been formulated by AWS, they themselves do not typically perform hands-on Well Architected Reviews. A certified AWS partner usually does this, called an AWS Well Architected Partner which is an organization that possesses the necessary understanding and expertise to evaluate and optimize your cloud infrastructure. They work collaboratively with your team to identify areas for improvement, optimize your architecture, and ensure that it meets the highest standards for security, performance, and cost-efficiency. Alternatively, you could also ## **Understanding the AWS Well Architected Review Process** The ## **Phase 1 - Prepare** The Prepare Phase begins a few weeks before the infrastructure review date and involves several activities that ensure a smooth and effective analysis. **Defining a Workload:** Identifying the specific workload you want to review. The term ‘workload’ in this context means a set of technology, people, and processes that deliver business value, like a customer-facing website. **Defining a Core Team:** Teaming up **Deciding on the Pillars:** Determining which of the six AWS Well Architected Framework pillars (Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, Sustainability) will be reviewed, since there may be instances where you need to focus on specific pillars only. It is also advisable to follow the review of the pillars in the same order as defined in the AWS Well Architected Framework (listed above). **Deciding on Session’s Type:** Mutually deciding upon the comfortable format for the review session, such as a full-day meeting or multiple shorter sessions, and whether the review will be conducted live or asynchronously. **Collecting Necessary Data:** Gathering all relevant architecture documentation and data, including diagrams and AWS Trusted Advisor checks, to support the review process. ## **Phase 2 - Review** The actual AWS Well Architected Review Process begins during this phase. Here the focus is on **Identifying Risks:** After careful evaluation of the architecture, the experts generate a report on your cloud architecture to categorize and understand **High-Risk Issues (HRIs), Medium-Risk issues (MRIs), and Low-Risk Issues (LRIs)** , based on their impact on the business. **Prioritizing Risks:** Evaluating the potential severity and impact of each risk and considering its potential business consequences, the experts engage with key stakeholders to prioritize the risks. **Determining Prescriptive Solutions:** The AWS Well Architected Partner will then work with teams to develop appropriate solutions for the identified risks. This phase involves researching, discussing, and understanding the complexity of each solution. ## Phase 3 - Improve This phase involves creating and executing a plan to address the identified risks and optimize the cloud architecture for better cost efficiency and performance. **Creating Improvement Plan:** Developing a plan to address HRIs, MRIs, and LRIs based on their priority. This plan will have the actions outlined, ownerships assigned, and timelines set for implementation. **Implementing the Changes:** This step involves the final implementation of the changes and optimizations suggested in the AWS Well Architected Review Process. You can use tools like the Eisenhower matrix to prioritize improvements based on their impact and complexity. Improvements are made starting with high-priority, low-effort items and moving through the list systematically. **Continuous Monitoring:** The Well Architected Reviews also need continuous tracking and monitoring of the resolutions implemented and make adjustments as needed. This helps to dynamically improve the workload's architecture to better support business needs and adapt to changes over time. Structuring the AWS Well Architected Review Process into these phases ensures a systematic approach to optimizing cloud architecture, Another important query is the time needed to go through these phases. The timelines can vary significantly based on factors such as the architecture in question, the specific pillars under review, and the complexity of the challenges. While exact durations can differ, AWS recommends a general timeframe of 90 to 180 days for a comprehensive review and effective implementation. ## **Maximizing AWS WAR benefits with a tailored approach** The AWS Well Architected Review Process offers a comprehensive methodology to understand, troubleshoot, and optimize your cloud infrastructure. However, applying this framework across diverse businesses—each with varying sizes, architectural complexities, and specific needs—requires a customized strategy that would address their specific needs. A one-size-fits-all approach without deeply diving into a customer’s specific objectives, maturity level, pain points, and capabilities will not deliver the desired enhancements. The resulting recommendations offered after the AWS Well Architected Review Process could also be too generic and businesses could waste a lot of time and resources in trying to implement them, only to understand that it’s ineffective. That’s why expert AWS Well Architected Partners, like Here are some of the enhancements offered by an AWS WAR Partner. **Customer-centric Engagement Model** Comprehensive architecture consultations are conducted to fully understand your unique infrastructure, its gaps, and your desired outcomes before jumping into the AWS WAR. This foundation analysis allows for an action plan that aligns with your specific needs and objectives. **Pre and Post-WAR Essential** Detailed discussions are done with the stakeholders before and after the review process, often scheduled for 90 minutes. This ensures the review is focused on the areas that matter most to you and that the steps outlined are both relevant and feasible for your organization. **Automated Reviews** An automated assessment process is employed using advanced scripting, that thoroughly evaluates your cloud infrastructure. The result is a streamlined AWS WAR process that reduces time and effort by fivefold, saving both resources and money. **Custom Recommendations** By understanding your unique challenges, capabilities, and goals, personalized suggestions are made to fine-tune your cloud architecture. This ensures that your time and resources are invested in an effective AWS Well Architected Review Process and the changes deliver maximum impact. **Short, Medium, and Long-Term Strategies** A precise action plan is provided, detailing exactly what needs to be done in a phased approach, for successful implementation of the resolutions of High-Risk Issues (HRIs), Medium-Risk Issues (MRIs), and Low-Risk Issues (LRIs) according to their urgency and impact. **End-to-End Support** Having an action plan is not enough and real progress happens when those plans are put into action. The partner offers Thus, by combining the fundamentals of AWS Well Architected Review Framework with the customized approach by an experienced partner, businesses can seamlessly optimize their cloud infrastructure and achieve cost and performance efficiency. ## **Conclusion** The AWS Well Architected Review is a powerful framework that helps assess and enhance cloud infrastructures, optimizing operational excellence, security, reliability, performance efficiency, and cost optimization. The true value of AWS WAR lies not just in identifying areas for improvement but in implementing the recommendations. A well-structured framework without effective execution would not deliver tangible results. In Well Architected Reviews, a customized approach is essential since different businesses have their unique challenges, maturity levels, and business goals. This is where an expert AWS Well Architected Partner comes into the picture, who helps in tailoring the process to your environment and provides continuous end-to-end support. With an expert partner like CloudKeeper, businesses will be able to seamlessly integrate the AWS Well Architected Review Process into their strategy, optimizing infrastructure, enhancing performance, and achieving significant cost savings. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Cloud cost management is a crucial aspect of any organization's cloud strategy. In this article, we will discuss two cost-saving options offered by AWS - AWS Savings Plans and Each plan is optimal for specific purposes, let's get into the details: ## **What Are AWS Savings Plans?** Customers can now save upto 72% on Amazon EC2 and AWS Fargate costs by committing to a consistent amount of compute usage for one to three years. This is Amazon's new flexible pricing model. The AWS savings plan is applied to Amazon compute usage regardless of the Amazon EC2 instance family, size, os, tenancy, or region. This also applies to AWS Glacier. In exchange for the commitment to use a certain amount of compute power (measured in $/hour) over a period of one or three years, the Savings Plan offers significant The ### **AWS provides two types of Savings Plans:** #### **1. Compute Savings Plans :** It provides the most flexibility and helps to reduce your costs by up to 66%, these plans are automatically applicable whether you use EC2 instances, regardless of their family size, AZ, Region, operating system, or tenancy. They also apply if you use Fargate and Lambda instances. For Example, By using Compute Savings Plans, you have the flexibility to switch from M5 to C4 instances, relocate a workload from EU (Ireland) to Europe (London), or transfer a workload from Amazon EC2 to Fargate or Lambda without any hassle and still benefit from the Savings Plans pricing automatically. #### **2. EC2 Instance Savings Plans :** It offers savings of up to 72%, whether it is a selected instance family, AZ, size, operating system, or tenancy in that region, you will be automatically able to optimize cloud cost on that instance family. If you switch from c5.xlarge running Windows to c5.2xlarge running Linux, the Savings Plans pricing will automatically apply. Source: https://docs.aws.amazon.com/ ## **What Are AWS Reserved Instances?** Whenever you Instances reserved for your organization are not dedicated instances. On-Demand Instances are discounted when you use them. A billing discount is only available if the On-Demand Instances you purchased match certain attributes of your Reserved Instances. Due to the fact that you pay for the entire term of a Reserved Instance, regardless of how much you utilize it, your _Source: https://docs.aws.amazon.com/_ ### **AWS Reserved Instances Pricing Options** Reserved Instances provide three payment options: #### **No Upfront:** In this EC2 Reserved Instances pricing option, no upfront payment is required. You are billed a discounted hourly rate for every hour within the term, regardless of whether the Reserved Instance is being used. No Upfront Reserved Instances are based on a contractual obligation to pay monthly for the entire term of the reservation. #### **Partial Upfront:** Reserved Instances are a way to reduce the cost of EC2 instances by committing to a one- or three-year term of usage in exchange for a lower hourly rate compared to On-Demand pricing. With partial upfront payment, you pay a portion of the total upfront cost of the EC2 Reserved Instance at the time of purchase, and the remainder is paid over the course of the RI term in smaller, recurring payments. For example, if you purchase a one-year Reserved Instance for an EC2 instance with a total upfront cost of $1,000 and choose the partial upfront payment option, you might pay $500 upfront and the remaining $500 over the course of the year in smaller, recurring payments. This Reserved Instance pricing option can help reduce the upfront costs of Reserved Instances while still providing cloud cost savings over On-Demand pricing. #### **All Upfront:** With the all-upfront payment option in the EC2 Reserved Instances pricing option, you pay the entire upfront cost of the Reserved Instance at the time of purchase, and you don't have to pay any additional fees or recurring payments for the remainder of the RI term. _Did you know that CloudKeeper Auto, an AI-based_ _platform can help you get on-demand EC2 resources at 3-year RI pricing?_ **Here’s a comparison table of AWS Savings Plans Vs. Reserved Instances based on different parameters that will help pick out the right one for your use case:** Here are some links to AWS documentation that provide more information on Savings Plans and Reserved Instances: * AWS Savings Plans: * Understanding Savings Plans: * AWS Reserved Instances: * Understanding Reserved Instances: Additionally, AWS offers a Savings Plans Purchase API that you can use to automate Savings Plans purchases and management.Here is a link to the API documentation: * AWS Savings Plans Purchase API: By understanding the differences and considering the specific requirements of your organization, you can make an informed decision on which option is best suited for your use case. _If you are looking for a trusted_ _in your journey of cloud cost optimization and maximize the value of your cloud investments,__and see how CloudKeeper can help._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents In today's dynamic business landscape, ## **Understanding Azure Reservations** An Azure reservation entails committing to utilize a specific virtual machine (VM) at a fixed capacity, measured in dollars per hour, for a duration of either one or three years, in return for discounts of up to 72% off the standard rate. Opting for Windows virtual machines can yield cloud cost savings of up to 80%. Furthermore, by combining an Azure reservation with an Azure Hybrid Benefit plan, you can save up to 80% off the pay-as-you-go rate (standard rate). The extent of savings achievable with Azure reservations hinges on various factors, such as the region, VM type, commitment term, payment option, operating system, etc. One of the key advantages of Azure Reservations is cost predictability. By locking in discounted rates for reserved resources, organizations can ## **Exploring Azure Savings Plans** To keep parity with AWS offerings and provide customers with a straightforward and flexible way to save on compute services, Azure Savings Plans were released in late 2022. With Savings Plans, Microsoft customers commit to spending a fixed hourly amount for one or three years and can save up to 65% compared to pay-as-you-go pricing. Savings Plans maximize flexibility by allowing customers to apply their commitment across multiple services, including virtual machines, Azure SQL Database, Azure Cosmos DB, and more. These options enable businesses to achieve long-term cloud cost savings while retaining the ability to scale their usage based on fluctuating demands. Organizations commit to a specific amount of usage (measured in dollars per hour) over a one- or three-year term. In return, they receive discounted rates on their Azure bills, with savings applied automatically to all eligible usage within the commitment scope. ## **Key Differences and Considerations** When comparing Azure Reservations and Savings Plans, several key differences and considerations come into play: * Resource Specificity: Azure Reservations require organizations to commit to specific resource types and configurations, while Savings Plans offer discounts on a broader range of usage, providing greater flexibility and coverage. * Payment Flexibility: Azure Reservations offer payment flexibility with options for upfront or monthly payments, whereas Savings Plans require upfront commitments but provide automatic discounts on all eligible usage. * Usage Patterns: Azure Reservations are ideal for predictable workloads with consistent usage patterns, while Savings Plans are better suited for dynamic workloads with fluctuating usage levels. * Scope of Coverage: Azure Reservations apply discounts to specific instances or resources within a predefined scope. Savings Plans provide discounts on all eligible usage within the commitment scope, offering broader coverage and potential savings. ## **Choosing the Right Option for Your Organization** The right cloud cost-saving option depends on various factors, including your organization's workload characteristics, budgetary constraints, and long-term cloud strategy. To make an informed decision, consider the following steps: * Evaluate Workload Patterns: * Assess Cost Savings Potential: Calculate the potential cloud cost savings offered by Azure Reservations and Savings Plans based on your organization's usage patterns and projected workload. * Consider Flexibility and Coverage: Evaluate the flexibility and coverage provided by each option, considering your organization's need for resource-specific commitments or broader discounts on all eligible usage. * Optimize for Long-Term Benefits: Look beyond immediate cloud cost savings and consider the long-term benefits of each option in terms of scalability, agility, and By carefully weighing these factors and considerations, you can choose the cost-saving option that best aligns with your organization's goals and requirements, enabling you to ## **Conclusion** In conclusion, Azure Reservations and Savings Plans offer distinct approaches to Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents As we welcome 2024 with a bunch of fresh hopes, dreams, and some ambitious New Year resolutions, it felt like the perfect time to take a little trip down memory lane and peek at how 2023 shaped our journey. So, here's a look at the key highlights of what happened at CloudKeeper in 2023. ## **Igniting CloudKeeper 2.0 with Jaw-Dropping Launches** Early into the year 2023, we kicked off our CloudKeeper 2.0 strategy by launching an We also rolled out our Mascot and made a grand entrance through videos and social media posts. He's a superhero battling cloud-cost villains, ensuring peace and cloud savings in the world – just like we strive to do. In April 2023, we launched our YouTube handle with Last year also marked the birth of one of our flagship solutions, CloudKeeper Auto. It's an And guess what? CloudKeeper Auto made its We've also officially set foot in the Azure territory, broadening our horizons. We've kicked off Well-Architected Reviews and FinOps Consulting for Microsoft Azure too. We believe in spreading love and cloud savings across cloud platforms! But wait, there's more – we've introduced ## **Forging Powerful Alliances Along the Way** In 2023, we forged powerful alliances that took our Cloud FinOps game to new heights. We became a **CEO, Deepak Mittal, even joined the Board of Directors** – talk about a power move! In addition to being an AWS Premier Partner, we also earned the AWS Graviton Service Delivery Partnership. This achievement showcased our excellence in cloud services, helping our customers ## **Jet-Setting and Throwing FinOps Fiesta Worldwide** 2023 was all about spreading the FinOps love globally. We hosted events like the AWS Unconventional Hacks Webinar series and participated in major events such as ## **Bragging Rights: Awards and Milestones** CloudKeeper bagged a slew of awards and hit service-specific milestones in 2023, keeping us motivated to deliver top-notch Cloud FinOps solutions and massive savings to our customers. Some of these milestones include - And here are the Industry Awards and Accolades that made our year shine: **As a whole, 2023 has been eventful, challenging, and exciting for us. We hope for an even brighter and better year ahead.** **Happy New Year. Cheers to 2024!** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents Did you know that How can businesses identify and address the gap between cloud expenditure and its impact on business outcomes? A ## **Cloud cost allocation** Cloud cost allocation is, as the name suggests, the process of allocating cloud spending to various departments, teams, business units, or individuals. Here is how the FinOps Foundation defines cloud cost allocation - _“ Cost Allocation is a process of identifying, categorizing, and assigning the costs of cloud computing resources to specific users, departments, projects, or any other relevant grouping within an organization through the use of structural hierarchies, tags, and labels available from cloud service providers or third party tooling platforms.”_ Cloud cost allocation enables businesses to understand better where their budget is being spent and thus make better budgeting decisions. Cloud cost allocation establishes accountability among teams using cloud resources and it offers visibility into which team is using your cloud budget. ## **Benefits of cloud cost allocation** Cloud cost allocation offers you the following benefits. **1. Better accountability:** It holds specific people or teams responsible for cloud resource usage and associated costs so that teams make conscious decisions while making spending decisions. **2. Financial transparency:** Cost allocation clarifies which sources, teams, or departments are generating the cloud costs, and thus improves the financial transparency in an organization. **3. Cost optimization:** Cloud cost allocation plays a key role in cloud cost optimization. By identifying cloud spending sources, companies can easily **4. Resource optimization:** Cloud cost allocation also helps to identify underutilized resources, which can then be reallocated to areas with higher demand to increase overall cloud utility. ## **Cloud cost allocation tags** Cost allocation tags are digital labels or metadata that can be assigned to any cloud resource. Once assigned, you can track the tagged resources using cloud cost platforms such as AWS Cost Explorer and other reporting tools. It thus enables you to understand the cost of cloud services in a detailed and granular manner. Each tag is comprised of a key and a unique value and serves as a unique identifier for all tagged resources which could be applications, teams, cost centers, etc. Source: ## **How to implement cloud cost allocation tags** Let us take the case of AWS to understand how cloud cost allocation can be implemented in your company. AWS provides two types of tags - **AWS-generated tags** and**user-generated tags.** Users have no control over the AWS-generated tags and can apply and compute these tags when they create a new AWS resource that is supported. However, you can customize the user-generated tags to organize resource consumption. These user-generated tags can be created with the AWS tag editor. Once you tag your resources such as EC2 or S3 instances, you must activate the tags in the Billing and Cost Management console. Once activated, AWS generates a cloud cost allocation report that displays your usage and costs. The cost allocation report is a CSV file of your usage and costs, according to your chosen format. You can then break down costs by tags and attribute AWS costs accurately across various dimensions like project, team, or customer. You can apply tags that represent business categories (such as cost centers, application names, or owners) to organize your costs across multiple services. The cost allocation report aggregates all of your AWS costs for each billing period. The report includes both tagged and untagged resources, hence organizing the costs becomes easy. For instance, if you tag resources with an application name, you can track the total cost of a single application that runs on those resources. Here is how the break-up looks on AWS with columns for each tag created. At the end of the billing cycle, you can easily reconcile costs in this report with tagged and untagged resources with the total charges on the bills for the exact period. Source: ## **Cloud cost allocation best practices** Cloud providers recommend certain best practices when allocating costs and tagging. They are discussed below. **1. Comprehensive tagging framework:** Implement a **2. Consistency in tagging:** This is the most important practice to follow while creating cost allocation tags. Consistency in tagging across teams, departments, and environments is key to creating accurate cost allocation reports. **3. Avoid untagged resources:** Use as many tags as possible for an accurate picture - having untagged resources can provide a skewed view of your cost analytics reports. **4. Proactive Tagging:** Ensure that tags are created as soon as the resources are created or put to use so that cost and usage data is captured early in the cycle. This will avoid any untagged instances and hence inaccuracies in reports. ## **Challenges of Cloud Cost Allocation** There are several challenges with cloud cost allocation that act as deterrents to effective tagging and allocation. Some of them are: **1. Complicated and time-consuming:** Creating an effective tagging strategy is extremely complicated and time-consuming. A minor error in tagging can cause erroneous cloud allocation reports thus impacting your cloud cost analytics. Also, scaling a team or an organization adds to the complexity of creating cloud tags as the number of resources increases. **2. Challenges with standardization and organizational change:** Inconsistencies can occur if a team member leaves or changes his or her role within the organization. The same is the case with a company getting acquired by another company, rendering all previous tags useless. If a team member tags a resource in lower-case without realizing that the tag had already been created in upper-case by a previous member, it can result in duplicate tags and thus result in inaccurate data for the entire billing cycle. Thus it is a challenge for organizations to maintain consistency in tagging amidst changes in teams. **3. Manual process:** Analysis of cost allocation reports is a manual process and making sense of the hundreds of rows of data can be very difficult without the help of a third-party tool or platform. **4. Undefined resources:** Resources such as business support, bandwidth, etc. cannot be assigned any tags, thus it is virtually impossible to assign such costs to the right cost center. This can create inaccurate cost allocation reports. ## **How can CloudKeeper help?** As an Moreover, one of the key building blocks of an effective cloud cost optimization strategy is addressing the issue of cloud cost visibility. Better visibility into your organization’s cloud spending and more granular cost and usage reporting can provide actionable insights into where you are spending the most money and opportunities for cloud cost optimization. **CloudKeeper Lens** is CloudKeeper’s proprietary Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents ## **Act I: The Setup — When Speed Meets Surprise** BigQuery is the stage where data teams perform their boldest experiments. With a single query, petabytes of information bend into charts, dashboards, and insights in seconds. It feels limitless until the invoice arrives. What looked like an elegant analysis can reveal itself as a runaway cost event. A dashboard refreshes every hour without filters. A developer casually runs SELECT * across terabytes. Or an entire historical dataset is scanned to answer a question about yesterday. Each of these decisions is invisible at first, but painfully clear when the bill lands. This tension is what makes BigQuery fascinating: its brilliance lies in scale, but scale without discipline is expensive. Organizations don’t just need speed; they need control. They need a way to navigate the vast library of their data without wandering every aisle, to fly their analytical aircraft with pre-flight checks, to measure twice and cut once. Such is the degree of speed and simplicity in using it that cloud engineers often But speed without visibility is still a gamble. Queries may return results instantly, yet the cost and usage patterns often remain hidden. It’s like racing with a clear road ahead but no dashboard you can steer, and you can’t see fuel, performance, or strain on the engine. What teams need are instruments that reveal not just results, but the economics and behavior behind them: who is querying, how much data is scanned, where inefficiencies creep in. The moment costs and performance become visible side by side, a new realm of insight opens, one where surprises turn into strategy, and that’s exactly where this story is headed. In the sections that follow, we’ll look at **seven practices** that separate cost chaos from cost clarity. Think of them not as a checklist, but as a journey of architectural maturity. Each practice adds a layer of foresight, governance, and efficiency. Together, they transform BigQuery from a cost wildcard into a predictable, finely tuned part of your data strategy. ## **Act II: The Journey — Seven Practices for Cost Clarity** ### **1. Partition Large Tables (Aisles in the Data Warehouse)** **Challenge:** Without partitioning, every query is forced to scan the entire dataset like rifling through every drawer in a filing cabinet to find one sheet of paper. **Strategy:** Partition tables by ingestion date, timestamp, or another logical key. _Think of it as constructing aisles in a warehouse: instead of walking through every corner, queries can head directly to the right aisle and scan only what matters._ **Payoff:** Partitioning often cuts scanned data by orders of magnitude, reducing costs while accelerating performance. ### **2. Cluster Tables (Sorting Before the Search)** **Challenge:** Even within a partition, queries may still slog through irrelevant rows. A filter like “California customers in January” can still trigger a wide scan. **Strategy:** Clustering sorts data inside partitions by frequently queried columns (region, product ID, etc.). It’s like pre-sorting mail by zip code before delivery for faster and cheaper than opening every envelope. **Payoff:** When combined with partitioning, clustering ensures BigQuery skips massive chunks of data. Queries become more precise, costs drop, and dashboards load faster. ### **3. Avoid SELECT * (Order Only What You’ll Eat)** **Challenge:**_**SELECT ***_ looks harmless, but BigQuery charges for every column scanned, even if you don’t use them. It’s the equivalent of ordering every dish on the menu when you only plan to eat one entrée. **Strategy:** Always specify columns explicitly, or use _**SELECT * EXCEPT**_ when flexibility is needed. This ensures your queries touch only what’s relevant. **Payoff:** Eliminating **SELECT *** reduces both cost and query time. For large enterprises, this small shift often produces some of the biggest savings. ### **4. The LIMIT Illusion (Trimming Doesn’t Mean Saving)** **Challenge:** Analysts often assume that adding _**LIMIT 100**_ reduces cost. In reality, BigQuery still scans the full dataset before trimming output. It’s like paying movers to carry every box out of the house just to keep one. **Strategy:** Recognize that LIMIT is a display tool, not a cost-control mechanism. To meaningfully reduce costs, pair LIMIT with partition filters, clustering, or column selection. **Payoff:** Teams stop leaning on false cost controls and instead adopt patterns that genuinely cut spend. ### **5. Dry-Run Queries (The Pre-Flight Checklist)** **Challenge:** Without foresight, queries run blind. A small mistake can trigger scans of billions of rows before anyone realizes. **Strategy** : Use the BigQuery query validator or _**--dry_run**_ flag. Dry runs estimate the exact number of bytes before execution. It’s a pilot’s pre-flight checklist: no engines start until fuel, hydraulics, and weather checks are complete. **Payoff:** Expensive mistakes never take off. Teams refine queries confidently, knowing costs before committing. _Sidebar note:_ CLI dry-run example with estimated bytes scanned. ### **6. Budgets & Alerts Dashboard Lights for Spend ** **Challenge:** Too often, costs are discovered when the invoice arrives far too late to act. **Strategy:** Configure budgets and alerts in Cloud Billing and use the **Payoff:** Finance and engineering teams gain shared visibility. Surprises vanish, replaced by predictable cost governance and proactive adjustments. ### **7. Long-Term Storage Moving Records to the Archive** **Challenge:** Cold, rarely accessed data quietly inflates storage bills, taking up premium space. **Strategy:** After 90 days of no modification, BigQuery automatically halves storage costs. Beyond that, export archival data to Cloud Storage Coldline or Archive. It’s like moving old records out of prime downtown office space into a secure, low-cost warehouse. **Payoff:** You maintain accessibility for compliance and history, but at a fraction of the cost. _Visual note:_ Lifecycle diagram “Hot data → 90 days → long-term pricing → archive.” ## **Act III The Resolution: From Chaos to Control** BigQuery is powerful. It can compress hours of analysis into seconds. It can turn petabytes of data into a single answer. But power without visibility leaves teams exposed. You can tune queries, partition tables, and set alerts, yet still be left wondering: **Where** did the cost really come from? **Who** is driving it? **What's** wasteful and what’s efficient? That’s why we at CloudKeeper built the **BigQuery Lens** , an advanced dashboard that’s part of the Snapshot of CloudKeeper's BigQuery Lens BigQuery Lens by CloudKeeper takes something complex, the economics of BigQuery, and makes it simple, elegant, and clear. For the first time, you can see cost and performance side by side, at the level where it matters: the query. With BigQuery Lens, every job tells its story. You see which teams and projects are driving spend, which queries deliver value, and which are silently wasting resources. You discover cache savings you didn’t know you had. You uncover queries that scan terabytes to return only a handful of rows. You don’t just see the numbers, you see the patterns. Snapshot of CloudKeeper's BigQuery Lens And because BigQuery Lens was designed for both engineers and finance, it becomes a shared language. Data teams learn how their choices affect cost. Finance teams see spending they can trust and explain. Leaders gain clarity at a glance. This is not just another dashboard. It is a Lens that brings the hidden world of BigQuery into focus. With best practices guiding behavior, and BigQuery Lens illuminating the results, organizations move from uncertainty to control, from surprise to strategy. Google BigQuery unlocked Data, **CloudKeeper’s BigQuery Lens** unlocks Understanding. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Abul specializes in Cloud Cost Optimization, FinOps practices, and GCP data solutions, combining technical expertise with strategic insight to drive efficiency and innovation. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents Whenever we hear the word “Instant Savings” or “Instant Success”, our mind gets triggered with a sense of excitement. But as the saying goes, all great things take time, instant wins can give us temporary results but they might not be sustainable in the long run. In cloud computing, cloud cost optimization is a critical component of maintaining profitability in business. The rising cloud cost can have a great impact on your gross margin and bottom line. Therefore, to achieve sustained success we need to move from the mindset of “quick fixes" to "building lasting value" in And interestingly, we are already moving towards a paradigm shift in the cloud cost optimization approach. The research suggests that businesses are shifting their focus towards sustained cost efficiencies. _A_ _highlighted that “The growing maturity of cloud adoption has shifted the focus from immediate cloud cost savings to sustained cloud cost optimization through a structured methodology for continuous monitoring, analysis, and adjustment of cloud costs, ensuring long-term efficiency."_ ## **The Limitations of Instant Savings In Cloud Cost Optimization** While the strategies for instant savings might be beneficial in certain scenarios, the instant cloud cost savings approach has limitations such as: **Short-Term Focus:** The immediate cloud cost savings strategies prioritize short-term gains without considering long-term implications. They majorly focus on a reactive approach rather than a proactive approach. For example for occasional use, the pay-as-you-go model might seem to be a good choice for **Lack of Scalability:** The immediate cloud cost savings strategies might not be helpful in scaling your business efficiently to accommodate future growth. For example: Avoiding scalability needs and implementing temporary solutions to mitigate high traffic volume during peak periods of business can lead to performance degradation and service outages. Also, reducing instance sizes to save cost may result in bad performance over time hampering user experience. **Missed Opportunities:** The constant focus on instant cloud cost savings opportunities may make you miss bigger wins. For example, if you solely focus on reducing server costs, you might tend to overlook opportunities to Moreover, the mindset of immediate cloud cost savings restricts you from investing in new technologies, tools, and services such as The immediate cloud cost saving is more focused on cloud cost reduction. However, ## **Why is a Sustained Cloud Cost Optimization Approach Crucial for Long-Term Cost Efficiency?** **Continuous Cloud Cost Optimization:** Long-term cloud cost savings practices involve continuous cloud cost monitoring, analysis, and adjustment, ensuring ongoing efficiency and control over performance. **Adaptability to Change:** This sustained approach enables businesses to respond to evolving requirements and **Cultivating Accountability:** It fosters a culture of accountability and transparency in cloud spending decisions. **Maximizing Returns:** By prioritizing long-term value, businesses can achieve greater cost efficiency and maximize returns on cloud investments. **Strategic-Decision Making:** Unlike immediate cloud cost savings a sustained approach encourages a data-driven mindset to make decisions. This strategic decision-making fosters continuous improvement and cost control over the long term. **Future-Proofing:** Businesses are constantly evolving, and cloud needs will inevitably change. The long-term cloud cost optimization approach focuses on building a flexible and adaptable framework. This allows you to adjust your strategy as your requirements evolve, ensuring your cloud environment remains cost-effective in the long run. ## **Cloud FinOps: A way to adopt sustained cloud cost optimization approach** We have heard this multiple times now that we need to ### **1. Cost Awareness and Culture** * **Establishing a strong FinOps Culture** Establishing a strong FinOps Culture sets a foundation for sustainable cloud cost optimization. _“FinOps is an evolving cross-functional management discipline with a set of methodologies that enables organizations to get maximum business value by bringing together people, processes, and tools to manage and optimize cloud costs across a business. ”_ The FinOps market is valued at $5.5 billion and is projected to grow at a robust 34.8% CAGR from 2023-2025. Moreover, 63% of global organizations allocate more than 7% of their total cloud spend to FinOps. It is evident from these statistics that enterprises consider cloud FinOps to be crucial in cloud cost reduction and optimizing cloud spending across all departments and teams. **Let's see how your business transforms after establishing a FinOps culture:** * **Collaboration: The core essence of FinOps** **** The success of cloud cost optimization heavily relies on collaboration between different teams and departments within an organization. In FinOps, cross-functional teams including finance, technology, product, and business teams work together to prioritize innovation and efficiency with cloud resources. This helps in breaking down departmental silos, getting a unified view, and focusing on shared FinOps goals, Finops best practices, * **A centralized team for FinOps** The basic idea of FinOps is simple: everyone works together to manage cloud spending. While members of the centralized FinOps team collaborate to accomplish cloud cost optimization goals, individual teams are equally accountable for their role in adhering to established standards and practices. The centralized team defines the FinOps best practices, while individual teams monitor their usage and participate in shared accountability. * **Ownership and Accountability** In FinOps, the accountability of cloud usage and cloud cost is more than just a task. It's about understanding and being responsible for your actions in the cloud and how it impacts the financial performance of the business. FinOps Principles suggest decentralizing the decision-making around cost-effective architecture, resource usage, and optimization. In order to make the roles and responsibilities of everyone involved in cloud cost decisions and accountability clear, the "Responsibility Assignment Matrix" (RACI matrix) can be used. * **Real-time data access** FinOps relies on real-time data to make proactive decisions about cloud spending. The faster you can access, understand, and act on this information, the more efficient and cost-effective your cloud operation becomes. **Dashboards:** Real-time **Alerts:** Automatic notifications highlight unusual spending patterns or potential cloud cost savings opportunities, enabling timely action. * **Decision Making-based on Business Value** The well-known Iron Triangle model, representing quality, speed, and cost, highlights the balancing act businesses face. FinOps as a part of your cloud cost optimization strategy helps you adopt a balanced approach instead of only a cost-focused approach. Let us understand it by a simple example. A product team adds a new cloud service for better performance of the solution, but this eventually ends up costing a lot to the business, making it an ineffective decision. However, if we imagine the same scenario in a company that has a collaborative FinOps culture, an informed decision would have been made after discussions with other stakeholders that balance both performance and cost. In order to understand the true value of your cloud, clear metrics need to be defined to track progress toward cloud cost optimization goals. Also, it is important to move beyond immediate metrics and embrace a broader perspective. This includes measuring the Internal Rate of Return (IRR) of the project. Moreover, setting Cloud Unit Costs is essential to further operationalize this approach. * Regularly assess unit costs for all cloud services and resources. * Track unit cost changes and align them with shifts in business metrics. * Ensure each unit cost is directly linked to specific business outcomes. The research suggests that as the market matures, FinOps metrics are expected to evolve. Future metrics may encompass engineering costs, relevant cost data availability, business value alignment with costs, and enhanced cost visibility granularity. ### **2. Resource Management and Leveraging Cost Opportunities :** * **Right-sizing:** Regularly assess your cloud resource usage and adjust them (like virtual machines) to match actual demand. Don't overprovision – find the "just right" size for your needs. * **Automation:** * **Strategic Use of Pricing Models:** Explore different cloud pricing options. Utilize reserved instances for predictable workloads and spot instances for flexible workloads to find the most cost-effective solutions. ### **3. Cloud Governance and Continuous Improvement:** * **Cloud Governance:** Establish * **Promote best practice sharing:** Establish mechanisms for sharing FinOps best practices and lessons learned across teams. This fosters a culture of continuous learning and improvement. * **Invest in knowledge:** Provide training sessions, workshops, and resources on FinOps principles and FinOps best practices. Equip your team with the knowledge and skills needed to make informed decisions about cloud spending and resource utilization. ## **Partnering up with a Cloud FinOps Partner:** Cloud FinOps requires specific expertise and skill sets in the domain. A potential and wise alternative could be partnering with a As long as you leverage the cloud services, your journey of cloud cost optimization will persist. The above-mentioned strategies will act like a guiding beacon through your ongoing pursuit to ensure sustained cloud cost efficiency. _CloudKeeper would love to partner with you and make your cloud cost optimization journey more effortless.__today!_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents Amazon Aurora DSQL (Distributed SQL) introduces a modern approach to relational databases by leveraging a distributed SQL architecture. This design delivers scalability, availability, and robust support for distributed transactions. However, adopting Aurora DSQL requires more than just excitement—it’s essential to understand its inner workings and evaluate whether your workload patterns align with its capabilities. In this post, we’ll unpack how Aurora DSQL functions, explore the data patterns it’s best suited for, and provide insights to help you assess whether it’s the right fit for your use cases. Also, you should explore the ## **How Aurora DSQL Works** Aurora DSQL’s power lies in its disaggregated architecture. Unlike traditional monolithic databases, it divides core functions into independent, scalable services. Each component can expand as needed, while cloud networking—with its high bandwidth and speed—keeps everything working seamlessly together. This approach strikes a balance between performance, scalability, and consistency, while enabling distributed transactions across nodes. ## Architecture Amazon Aurora DSQL consists of the following elements: The operation when reading and writing is as follows. Let’s look at each element. ### **1. The Query Processor (QP)** Each database can have any number of these. Just keep scaling. The PostgreSQL-compatible SQL engine Firecracker runs on a lightweight Firecracker-based virtual machine. QPs are scalable and dynamically increase or decrease according to client demand. Each transaction runs on a separate QP and is connected to the Storage in a logical interface. All read queries are run in the snapshot isolation and refer to the data state at the start. Changes are saved locally until commits, even during write operations, and a distributed integrity check occurs only when committing. ### **2. Adjudicator** It is a lightweight component that detects collisions during transaction commits. With an OCC-based architecture, Adjudicator does not hold a lock to an execution transaction, but determines a collision with a validation just before the commit. This Adjudicator is close to stateless and can be reconfigured from the committed transaction logs, making it easy to restart when a failover occurs. ### **3. The Journal** Record this at the time of the transaction commit. At this point, the transaction is permanently and atomically committed, and then the Storage shard applies the Journal to reflect the final state. This approach achieves efficient durability and availability without complex distributed consensus protocols such as 2PC (two-phase commit) and Paxos/Raft. ### **4. Storage layer** Manage data with multiple Storage shards and replicas via the Distributed Journal . MVCC provides a data view at any point in time, and QPs can access Storage with a linear logical interface. In addition, the storage layer reduces the number of network reciprocating times by pushing down some processing, such as filtering and aggregation, to the requests received from QPs. Single-region configuration The single-region configuration consists of distributed storage across three AZs, a group of scalable QPs, Journal, and Adjudicator. The write transaction is committed to the distributed transaction log, and the data is synchronously reflected in the storage replica across 3 AZs. This replica is efficiently distributed throughout the storage fleet to maximize database performance. In addition, the system has a built-in automatic failover function that automatically switches to a healthy resource in the event of a component or AZ failure. The failed replica is then repaired asynchronously, and as soon as the restoration is complete, it is re-embedded into the quorum and made available as part of the cluster. This process ensures high availability and reliability. ### **Multi-Region Configuration** In a multi-region configuration, we provide resiliency and connectivity, as well as in a single-region configuration, while leveraging 2 region endpoints to further increase availability. The endpoints of these linked clusters act as a single logical database, allowing simultaneous read-write operations while maintaining strong data integrity. This mechanism allows applications to flexibly choose their connection destination according to their geographic location, performance requirements, and fault-tolerant needs, providing consistent data whenever they read. When you create a multi-region cluster, Amazon Aurora DSQL also adds clusters to another region specified and links them. With this link, all committed changes are replicated to other linked regions. This makes it possible to read and write strongly from any cluster. ## **Is Aurora DSQL the Right Choice?** Aurora DSQL is an excellent solution for modern distributed applications—especially those requiring high concurrency, global reach, read-heavy workloads, or partitionable writes. At the same time, it comes with trade-offs such as retries for optimistic locking and query timeouts that demand careful application design. By aligning your workload patterns with Aurora DSQL’s strengths, you can unlock unmatched scalability, performance, and resilience compared to traditional relational databases. For the right workloads, it represents a major step forward in database architecture. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Cloud Engineer Rishabh is a result-driven engineer with expertise in AWS cloud infrastructure, cost optimisation, and secure solution design. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 2 2 Table of Contents ## **Problem Statement** When building sandbox or proof-of-concept (POC) labs in AWS, isolation and governance quickly become necessary. Creating a handful of accounts manually in the AWS Management Console is manageable, but provisioning 20, 50, or 200 accounts is tedious, error-prone, and inefficient. Challenges include: * Automating account creation at scale * Managing access dynamically for users * Keeping costs under control while ensuring security and compliance ## **Solution Overview** By combining **AWS Control Tower** for governance with **Account Factory for Terraform (AFT)** for automation, you can: * Deploy a multi-account landing zone with centralized governance * Automate the provisioning of hundreds of sandbox/demo accounts * Manage user access flexibly using * Automate cost cleanup using AWS Nuke ## **Architecture Overview** ### **1.Control Tower Landing Zone** * Audit Account → for compliance checks (restricted, no direct login). * Log Archive Account → centralized logs (CloudTrail, * Sandbox OU → dedicated for lab/demo accounts. ### **2.Account Provisioning** * Small scale: Account Factory console. * Large scale: AFT with Terraform definitions. ### **3.Access Management** * Group-based access: one group with AdminAccess across all accounts. * Dynamic assignment: allocate sandbox accounts to users on-demand. ### **4.Cost Management** * Cleanup automation with AWS Nuke on a scheduled basis. ## **Scalable Automation with AFT** Instead of creating accounts manually: * Define accounts as Terraform resources. * Generate requests from a CSV or database if provisioning hundreds of accounts. * Unlike console-based creation, AFT does not require assigning users at creation. * You can build an **account pool** first and assign users later using the _create-account-assignment_ API. ## **Automated Cleanup with AWS Nuke** Creating 200 sandbox accounts means there’s always a **risk of resource sprawl** and **rising costs**. The solution is to use AWS Nuke for periodic cleanup. ### **How It Works** * **EventBridge Rule** → Triggers cleanup (nightly or weekly). * **Function** → Spins up an * * **AWS Nuke** → Deletes all resources in the child account. ## **AWS Nuke Configuration Example** A minimal _nuke-config.yml_ : ### **Considerations for Cleanup** * Always test in non-production accounts first. * Exclude mandatory roles like _OrganizationAccountAccessRole_. * Run on a schedule that balances **availability for labs** (e.g., nightly, weekly, or monthly). * Monitor via * Keep the cleanup automation in the **management account** for central control. ### **Cost Considerations** * Centralize logs in the log archive account to avoid duplication. * Use shorter retention periods for CloudWatch logs and export to S3 if needed. * Enforce cleanup schedules with AWS Nuke to minimize idle costs. * Apply guardrails with Control Tower to enforce security/compliance automatically. ### **Results** With this setup, you achieve a governed, scalable, and cost-efficient lab environment: * Isolated accounts for users or groups * Automated provisioning with Terraform (AFT) * Flexible access management with Identity Center * Automated cleanup and cost control with AWS Nuke This provides the agility of quick sandbox environments while maintaining control and keeping costs predictable. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Aryaman is a DevOps Engineer who is passionate about software and problem-solving. He has a keen interest in DevOps practices, cloud technologies, and building efficient, scalable solutions. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents APIs usually do not break because business logic is wrong. They break when the edge behavior is inconsistent: one service enforces auth, another skips it, a third has no rate limit, and every team implements policy differently. Kong helps you standardize this entire edge layer. It can start as a reverse proxy and evolve into a complete API platform for routing, authentication, authorization, traffic control, observability, and governance. This blog explains how to use Kong as a full-fledged API gateway in a general-purpose setup, with architecture patterns, runnable examples, and a migration path. ## **What is Kong?** Kong is a high-performance, open-source API gateway built on NGINX. It sits between clients and backend services and enforces policies without requiring code changes in each service. Kong is plugin-driven. That plugin model is the reason it scales from simple routing to enterprise-grade API governance. ## **Core Concepts You Must Know** Kong has four foundational building blocks: * **Service:** Your upstream backend endpoint (for example, https://api.example.com). * **Route:** The matching rule that maps incoming traffic to a service (path, method, host, headers). * **Plugin:** Middleware policy applied globally, per service, per route, or per consumer. * **Consumer:** A client identity (application, partner, or user) that can have credentials and individual limits. Think of it this way: the route decides where traffic goes; plugin decides how traffic is allowed and shaped. ## **Why Kong as a Full-Fledged Gateway** A proxy only forwards traffic. A full-fledged gateway enforces platform-wide behavior: * Unified authentication and authorization * Per-client throttling and quota control * Security headers and request normalization * Centralized logs, metrics, and tracing context * Safer rollout and governance across environments ## **Reference Architecture** Control plane handles configuration. Data plane handles live traffic. This separation improves safety and scalability. ## **Getting Kong Running with Docker** You need a database and Kong container. The following setup uses PostgreSQL. ### **Step 1: Start PostgreSQL** ### **Step 2: Bootstrap Kong database migrations** ### **Step 3: Start Kong** **** Ports to remember: * **8000:** Proxy traffic (client requests) * **8001:** Admin API (configuration endpoint) **Quick health check:** ## **Create Your First Service and Route** * **Register a service** * **Create a route for that service** Now requests to localhost:8000/v1 are proxied to ## **Add Essential Gateway Plugins** ### **1) API Key Authentication** Enable key-auth on service: Create a consumer: Issue an API key: **Result:** requests without apikey header return 401 Unauthorized. ### **2) Rate Limiting** **** This caps traffic at 100 requests/minute per default keying strategy. ### **3) CORS** **** ## **Verify End-to-End Behavior** * Without API key (expect 401): * With API key (expect a successful upstream response): ## **Detailed Use Cases and Patterns** ### **Pattern A: Public Partner APIs** * Use OIDC/JWT or key-auth based on partner integration maturity. * Apply strict per-consumer limits and clear error contracts. * Add request/response logging with sensitive field masking. ### **Pattern B: Internal Microservices** * Use service identity (JWT) and relaxed but bounded limits. * Add correlation IDs at gateway to unify tracing across services. ### **Pattern C: Browser Frontend APIs** * Standardize CORS policies at the gateway, not per backend. * Enforce origin allowlists and credential behavior consistently. ## **Before vs After Migration Snapshot** ### **Before:** * Every service owns edge logic (auth, limits, headers). * Security behavior differs by team and release cycle. * Onboarding a new API requires repeated boilerplate. ### **After:** * Kong owns edge policy and traffic governance. * Services focus on business logic only. * New APIs reuse standard route and plugin templates. ## **Operational Best Practices** * Never expose the Admin API publicly. Bind it to localhost/private network and protect it with network controls. * Use decK for configuration as code (export, review, version, deploy). * Use Redis-backed rate limiting in distributed deployments so counters stay consistent across nodes. * Keep plugin templates by API category (public, internal, admin). * Add CI checks for route conflicts, missing auth, and policy regressions. ## **Conclusion** Kong becomes a full-fledged API gateway when you use it as a policy platform, not only as a router. Start with service and route mapping, then layer authentication, consumer identity, and rate controls. Add observability and config-as-code early. With that model, API delivery becomes faster, safer, and easier to operate at scale. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Prerana is a tech enthusiast with a passion for building scalable and reliable cloud systems. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents Our data pipelines used to run on **Jenkins** , a tool we originally chose for CI/CD automation in **dynamic, fault-tolerant, and large-scale data workflows**. As our data volume and tenant base grew, limitations started to surface. ## **Challenges we faced** * **Static Workflow Management:** Jenkins supports static pipelines, but adding or changing workflows requires **manual scripting** , slowing down iteration and increasing the risk of errors. * **Lack of Fault Tolerance:** Failures often require manual recovery, causing downtime and risking data consistency. * **Scalability Issues:** Scaling to large datasets and complex workflows creates performance bottlenecks. * **Limited Monitoring:** Native Jenkins lacks real-time * **Centralized Control:** Teams depend on Jenkins admins to update workflows, reducing agility and slowing innovation. ## **Why We Needed a New Approach** We identified the need for a modern **orchestration** system designed to: * Dynamically create workflows (DAGs). * Recover gracefully from failures. * Scale with data and tenants. * Provide real-time observability. * Empower teams to self-serve, without bottlenecking on central admins. ## **Our Solution Strategy** We identified **Apache Airflow** as the right fit for orchestration and built a **custom orchestration framework** on top of it, guided by principles of **modularity, reuse, and user-friendliness**. Instead of fully replacing Jenkins, we positioned both tools where they deliver the most value: * **Jenkins** → continues managing CI/CD workflows. * **Apache Airflow** → orchestrates scheduling, retries, and monitoring. * * **MongoDB** → stores pipeline metadata with version history for rollback. * **Jinja** → powers SQL templating to embed runtime logic and reduce duplication. * **React + Spring Boo** t → provides a UI for visual, self-service pipeline creation. ## **How the New System Works** Our new orchestration platform is designed to balance **user-friendliness** for pipeline creators with **robust orchestration** under the hood. Here’s how it works end-to-end: ### **1. User Interface for Pipelines** * Users interact with a simple UI to create **Concrete Tasks, View Tasks, Parameter Templates, and Pipelines**. * Each component is stored in **MongoDB** , ensuring persistence and version control. * **Reusable tasks** and parameter templates make building pipelines fast and consistent. * Every pipeline version is tracked, enabling **rollbacks** to previous configurations when needed. ### **2. Integration with Apache Airflow** * Once pipelines are defined in MongoDB, configurations are**synchronized with Apache Airflow**. * Airflow orchestrates execution: handling **dependencies, scheduling, retries, and tracking**. * To support this dynamic execution, we developed three internal systems (distributed as wheel packages) integrated into the Airflow runtime: **a) Sync Engine** → pulls pipeline/task definitions from MongoDB into Airflow. **b) Concrete Task Executor** → executes Python-based tasks with appropriate parameters. **c) Dynamic View Engine** → renders SQL-based tasks at runtime using Jinja templates. ### **3. Task Execution with AWS Fargate** * For resource-intensive or long-running tasks, Airflow delegates execution to **AWS Fargate**. * Tasks run in **serverless, isolated containers** , ensuring scalability and preventing Airflow workers from being overloaded. ### **4. Security, Reliability & Maintainability** * **Retries & Fault Tolerance:** Failed tasks automatically retry, reducing manual intervention. * **RBAC:** Role-Based Access Control enforces secure and permissioned access. In AWS, RBAC can be enforced with * **Observability:** Airflow’s monitoring, logging, and alerting give teams real-time visibility into pipeline health and execution. ## **Impact & Results** * **30% Faster Development** – Reusable templates reduced onboarding time and sped up pipeline creation. * **< 5% Manual Intervention** – Automatic retries improved fault tolerance and reduced recovery overhead. * **Elastic Execution** – AWS Fargate enabled scalable, multi-tenant task processing. * **Improved Observability** – * **Team Autonomy** – Self-service pipeline creation reduced central dependencies. ## **Final Takeaways** Moving from Jenkins-only pipelines to an Airflow-based orchestration framework allowed us to balance scalability, resilience, and usability. The journey reinforced a key principle: the right abstractions and tools enable teams to move faster, with confidence. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Director - Engineering Vishu Tyagi brings deep technical leadership in software development and team management. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents ## **Problem Statement** Managing multiple AWS accounts across * No ability to scope alerts to only the relevant customer accounts. * Customers may receive irrelevant or noisy notifications. * Lack of clear separation between different customers’ events. To solve this, we needed a system that could: * Collect AWS Health events from only the relevant customer accounts. * Work seamlessly across all AWS regions. * Route events to a central monitoring location. * Deliver professional, branded email alerts instead of raw JSON. * Be automated, scalable, and easily repeatable through CloudFormation. ## **The Solution** We designed a serverless, cross-account pipeline using EventBridge, * **Customer accounts:** EventBridge rules in each required region capture **aws.health** events and forward them cross-account. * **Central account:** Hosts a custom EventBridge bus (Health-bus) that receives all forwarded events. * **EventBridge rules:** On the central bus, rules trigger a Lambda function for every incoming event. * **Lambda + SES** : The Lambda parses and formats the Health event and uses Amazon SES to send it as a clean HTML email to customer stakeholders. This ensures each customer receives only their own alerts, in a form that’s easy to read and act upon. ## **Architecture Overview** The architecture is built from three components: ### **1. Customer accounts** * EventBridge rules in every region where AWS Health events should be monitored. * Rules forward events securely to the central custom bus. ### **2. Central account** * A dedicated EventBridge bus to aggregate events. * Rules attached to this bus to trigger the Lambda function. ### **3. Lambda and SES** * Lambda extracts details such as service, region, account ID, description, and timestamps. * It builds an HTML email and delivers it using Amazon SES. * Because AWS Health is regional, forwarding rules must be deployed in each region the customer wants covered. ## **Deployment with CloudFormation** To make the solution repeatable, we created two CloudFormation templates: ### **1. Customer Forwarder Template** * Deployed in each customer account and region. * Creates a rule named **ForwardAllHealthEvents** to forward all AWS Health events to the central bus. Customer Forwarder Template **2. Central Aggregator Template** * Deployed once in the central monitoring account. * Creates the custom event bus. * Sets up a rule to invoke the Lambda function. * Deploys the Lambda code from S3. * Leaves SES setup (sender/recipient verification, sandbox exit) as a manual step. Central Aggregator TemplateEvent Bus created ## **The Email Experience** Instead of raw JSON, customers receive structured HTML emails with: * Service and category (issue, scheduled change, or notification). * Region and account ID. * Event time in UTC. * A clear description. * A direct link to the AWS Health Dashboard. ## **Cost Considerations** * EventBridge → $1 per million events on a custom bus. * Lambda → $0.20 per million invocations (lightweight usage costs almost nothing). * SES → $0.10 per 1,000 emails, with 62,000 free emails per month when sent from For most customers, the monthly cost is only a few dollars. ## **Results** With this setup in place, we achieved: * Real-time AWS Health alerts across accounts and regions. * Clean separation of events per customer within a shared AWS Organization. * Branded, customer-friendly email notifications. * Automated, repeatable If your teams are struggling with fragmented AWS Health alerts, this approach provides a proven, low-cost way to centralize and streamline communication. Start small with a single account and region, then expand as needed — the design scales effortlessly. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 2 2 Table of Contents A monitoring account is a central AWS account that can view and interact with observability data generated from source accounts. A source account is an individual AWS account that generates observability data for the resources that reside in it. Source accounts share their observability data with the monitoring account. The shared observability data can include the following types of telemetry: 1. Metrics in Amazon CloudWatch. You can choose to share the metrics from all namespaces with the monitoring account, or filter to a subset of namespaces. 2. Log groups in Amazon CloudWatch Logs. You can choose to share all log groups with the monitoring account or filter to a subset of log groups. 3. Traces in AWS X-Ray, etc. The following high-level steps show you how to set up Amazon CloudWatch cross-account observability. ## **Step 1: Configure Monitoring Account** Log in to the Monitoring Account. Go to CloudWatch > Settings. Under Monitoring Account Configuration, click Configure. ## **Step 2: Define Data and Source Accounts** In the Select Data section, choose the types of data you wish to collect (logs, metrics, etc.). Enter the list of **Source Account IDs** (comma-separated) and select the account name under **Account Label**. Click Configure. ## **Step 3: Resources to Link Accounts** After configuration, you'll land on a settings screen again. Now, click on **Resources to Link Accounts** , then click on **Any Account** and **Copy URL** to link source accounts. ## **Step 4: Link Source Accounts** Open a new browser/incognito window and log into the source account (child account). Paste the **copied URL from Step 3** into a new window. This displays a screen with pre-populated parameters. You’ll be prompted to confirm what data to share - verify and hit "Link". ## **What to Expect** After successful configuration, logs and metrics start flowing from the source to the monitoring account. It may take up to 45 minutes for data to appear, so allow some buffer time before verification. Checkout our other guide sharing Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Siddharth is passionate about taming cloud chaos and building calm, efficient infrastructures. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents The FinOps market has grown at a compound annual growth rate of 35.2% since 2019. Future growth is expected to outpace the IT market for several years. Many companies report to IDC that they are still overspending on their public cloud. As IT budgets tighten, wasted cloud spending eats up future investments. As the market growth suggests, enterprises are increasingly turning to FinOps practices and tools to gain control of their cloud costs. Choosing the right vendor to help implement and mature your FinOps practice can be challenging. As our A reliable partner will provide your company with many vital FinOps capabilities. A partner can assist with Below is a checklist of things to consider when comparing FinOps partners for this strategic area: **Training and certifications:** Confirm the partner’s consultants have individual certifications, such as **Architecture, customization, and flexibility:** Architecting your FinOps solution and services to your specific needs is vital. There is no one-size-fits-all solution. The dynamic nature of the public cloud means the FinOps vendor needs to see the bigger picture, understand your desired business outcomes, and engineer a flexible solution to meet those requirements. **Customer references:** Check a partner's track record and customer testimonials. An established FinOps partner should be able to demonstrate **Multicloud platform experience:** Ensure the FinOps partner has expertise with your specific cloud platforms (e.g., AWS, Azure, and Google Cloud). The partner must be familiar with the nuances of your platform(s) to provide the best optimization strategies. **Automation tooling and AI technology:** Assess cutting-edge technologies, the FinOps partner created in-house, that may increase your FinOps team’s business value. These tools often leverage AI to find anomalies faster and quickly customize business dashboards. Automation is vital to driving the implementation of cloud optimization recommendations and realizing savings for your company. **Industry experience:** The partner should have a general understanding of your industry and unique use cases. FinOps processes and personas may vary from industry to industry. Compliance and regulations may require consideration for **Regulatory compliance and security:** The FinOps partner should know your company's security requirements to ensure recommendations do not cause compliance issues or vulnerabilities. **Reporting and forecasting:** An experienced FinOps partner recognizes the importance of cloud forecasting and the processes of continual improvement related to cloud spending. Working to provide best practices and streamlined processes to create and update your forecast multiple times per year is often high on the list of CFOs for the FinOps team. **Easy-to-understand pricing structure:** Public cloud management is complex, so understanding your partner's fee structure should not be difficult. A transparent pricing model for one-time projects and ongoing services will keep your company and partner aligned. **Partnership:** FinOps is often a journey, not a transactional short-term engagement. Does your potential partner view the engagement as a long-term collaboration? The partner should have experience in providing training and skills transfer for FinOps processes. This will ensure your team is self-sufficient in the long term. **Growth and scalability:** Can your potential FinOps partner's services and capabilities scale and grow with your business? Your partner should adapt and adjust to your ever-changing business requirements over time. Do they have references for successful projects with companies your size or larger? **Communication and reporting:** Collaboration and communication are critical for a FinOps team. Setting up customized reports that track **Commitment-based pricing discounts:** Some partners offer access to unique marketplaces of reserved instances and other pricing options besides optimizing your cloud resources via the cloud cost tool. These longer-term savings can add business value to standard FinOps cost optimizations. Another element a **Figure: FinOps Team Sizes for 2023: G2000 Enterprises** (Source: After reviewing the checklist of critical FinOps factors, companies can identify a solid match with prospective FinOps partners and move to the next step. Assigning a weighting to factors that deliver the most business value to your company is expected and can help with the selection. You can then identify areas of improvement with people, processes, and tools/technology that your FinOps partner can assist you with first. ## **Conclusion** The importance of Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents Did you know as per a survey by Everest Group a staggering 67% of organizations worldwide are grappling with cloud costs that exceed their expectations? Moreover, 82% of these organizations are inefficiently using their cloud resources, with at least 10% of these volumes going down the drain. That’s billions of dollars going down the drain due to inadequate cloud cost optimization practices. This problem is exacerbated by the complexity of managing hybrid and multi-cloud infrastructures, as well as a Tapping into this demand, the landscape of FinOps vendors has evolved significantly, offering a wide array of solutions. These range from niche tools that focus on a few specific cloud services, to end-to-end cloud cost optimization platforms and FinOps consulting, that take care of your entire cloud infrastructure. Let's explore the diverse range of vendor options and help you identify the best fit for your business needs. ## **A Broad Classification** Cloud FinOps service providers can be classified broadly into five categories, based on the type of services provided and their level of assistance. These categories also impact different phases of the FinOps lifecycle. ### **Resellers** Cloud Resellers, wielding the power of their industry expertise and strategic partnerships with major cloud providers offer organizations a compelling path to reduced cloud costs. At the core of the advantage offered by resellers is their knack for harnessing economies of scale, enabling them to secure bulk purchase discounts from major cloud providers like AWS, Azure, and GCP, resulting in Unlike the standard pay-as-you-go models, resellers provide flexible payment options that can be customized to fit an organization's financial schedule, including subscriptions, upfront commitments, or tailored invoicing, enhancing budget compatibility. In addition, Resellers might also offer value-added services like expertise in cloud billing management, FinOps consulting, cloud migration support, and round-the-clock technical help. ### **RI/SP Management Providers** Reserved Instances (RIs) and Savings Plans (SPs) stand as In an innovative leap forward, many RI/SP management providers now incorporate AI-based solutions, with some harnessing the capabilities of Generative AI, to elevate their service offerings. These advanced technologies enable even more refined analysis and optimization, predicting usage trends and identifying savings opportunities with unprecedented accuracy. RI/SP Management providers could help you secure the most cost-effective cloud infrastructure configurations and maximum cloud cost savings. ### **Consulting and Managed Service Providers** Consulting and Managed Service Providers (MSPs) are indispensable allies for businesses aiming to navigate the complexities of cloud FinOps. These experts possess a wealth of knowledge and tools, ensuring that organizations can fully leverage their cloud investments for maximum efficiency and cost savings. One notable service that some MSPs offer is Key offerings by Consulting and MSPs include: * **Resource Optimization:** Continuous monitoring and fine-tuning of cloud resources to match your operational requirements perfectly. * **Cost Management:** Implementation of strategies and tools designed to keep cloud expenses within budget, identifying savings and avoiding wasteful spending. * **Security Enhancement:** Proactive FinOps consulting that shores up cloud defenses, identifying and mitigating potential security threats. * **Performance Optimization:** Adjustments and recommendations to ensure your cloud infrastructure performs optimally, supporting a seamless user experience. ### **Visibility and Recommendations Providers** Achieving clarity on resource utilization and spending is akin to finding your way through a fog. Visibility and recommendations providers act as navigators, offering critical insights into your cloud expenditure, resource allocation, chargebacks, and tagging practices. Their expertise unveils hidden inefficiencies and provides actionable advice to streamline cloud FinOps operations and reduce waste. Key benefits these providers offer include: * **Granular Spend Analysis:** Detailed breakdowns of spending by resource, department, or project to identify overspending or underutilization. * **Allocation Transparency:** Insights into how resources are distributed, ensuring equitable cost sharing. * **Chargeback Clarity:** Simplified understanding of cost attribution across departments or projects. * **Rightsizing Recommendations:** Advice on adjusting resource configurations for optimal cost-efficiency. * **Tagging Strategies:** Guidance and FinOps consulting on effective tagging for improved cost tracking and optimization. Working with Cloud Cost Visibility solutions not only cuts down on unnecessary expenditures but also enhances informed decision-making with a comprehensive ### **End-to-End FinOps Service Providers** These providers stand out as one-stop solution providers offering a comprehensive array of services that cover FinOps consulting, Reserved Instance (RI)/Savings Plan (SP) management, and extensive visibility into your cloud spending. Their holistic strategy transcends the limitations of piecemeal solutions, positioning them as a centralized beacon for cloud cost optimization, embodying several critical benefits: * **Unified Strategy:** They eliminate the complexity of dealing with multiple vendors, offering a single, streamlined platform for all cloud FinOps activities, simplifying operations, and enhancing efficiency. * **Comprehensive Insights:** With a broad analysis of your cloud expenditure and usage, these providers uncover in-depth optimization opportunities across your entire cloud landscape. * **Effortless Integration:** Their solutions integrate smoothly with your existing cloud setups, ensuring that enhancements are implemented without disrupting your operations. These End-to-end FinOps services include: * **Consulting and Strategy:** Providing tailored FinOps Consulting services to craft and deploy a Cloud FinOps strategy that aligns with your business objectives and cloud infrastructure. MSP services contribute by offering strategic guidance on overall cloud management and integration with Cloud FinOps strategies. * **RI/SP Optimization:** Leveraging expertise in the adept management of Reserved Instances and Savings Plans, ensuring optimal utilization to maximize cost savings. * **Visibility and Analytics:** Offering sophisticated reporting tools that furnish detailed insights into cloud spending patterns, resource allocation, and optimization opportunities. * **Automated Optimization:** Harnessing the power of An End-to-End FinOps Service Provider can transform your cloud FinOps journey from a fragmented struggle into a unified and streamlined campaign. ## **Impact on the FinOps Lifecycle** Optimizing cloud costs isn't a one-time feat; it's a continuous journey through the cloud FinOps lifecycle. Different service providers specialize in distinct stages, empowering you to navigate this journey with expert guidance. The below image summarizes their impact on the different phases of the lifecycle. An end-to-end provider could help you set sail along this journey, With an End-to-End FinOps provider by your side, you achieve holistic Cloud FinOps consulting support, comprehensive visibility, and resource optimization. ( ## **CloudKeeper: One-Stop Solution for Everything FinOps** Now you know why an End-to-End Cloud FinOps Provider would be the right choice to go about, for all types of cloud cost optimization needs. Among the wide range of service providers in the landscape, there are only a handful that offer comprehensive FinOps services and CloudKeeper stands tall among them. With over 12 years of cloud expertise, CloudKeeper is a distinguished player in the FinOps landscape, holding the status of an AWS Premier Partner, Microsoft Azure Solutions Partner, and Premier Partner with the FinOps Foundation. This rich experience and strategic partnerships underscore CloudKeeper's position as a leading provider of cloud cost optimization. **The solutions offered by CloudKeeper include -** Additionally, CloudKeeper offers **Did we mention the pricing?** Well, it might sound too good to be true, but almost all solutions offered by CloudKeeper require **zero costs, zero efforts, and zero commitments** from your side. CloudKeeper Auto is the only exception and there too, the solution follows results-based pricing, priced at only a small percentage of the savings achieved via the solution. It’s a win-win situation. In short, with just a simple onboarding process, CloudKeeper helps you with rate, usage, and process optimization, effortlessly. ## **Conclusion** In the complex realm of cloud cost optimization, the journey may seem daunting, but with diverse cloud FinOps solution providers ready to guide you, it becomes a manageable expedition. These providers specialize in distinct phases, offering crucial support throughout the process. Cloud cost visibility providers act as beacons, shedding light on spending patterns for informed decision-making. FinOps consulting and managed service providers play the role of seasoned navigators, optimizing your cloud environment for peak efficiency. Resellers and RI/SP management providers ensure smooth operations and cost-effective resource utilization. The choice of the right partner depends on your specific needs and your position in the FinOps lifecycle. Amidst these providers, CloudKeeper emerges as a standout with support over each and every step of your FinOps Journey, with guaranteed savings, effortless optimization, and zero cost or commitments. Embark confidently with a reliable companion, witnessing a reduction in your cloud costs and the soaring heights of your return on investment. _We know, partnering with a FinOps vendor requires much more understanding of the market and in-depth analysis. Let us help you break down the FinOps Vendor Market with a comprehensive analysis done by Everest Group.___ _Would you like to know more about CloudKeeper?__with one of our experts._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents For **how to create resources** ’ - it’s ‘**how to track, audit, and govern them continuously** ’. As cloud environments grow, This is where the **Google Cloud Asset API** plays a foundational role. ## **What is Google Cloud Asset API?** Cloud Asset API is a read-only inventory and analysis service that gives you a unified view of all your Google Cloud resources across: * Organizations * Folders * Projects Cloud Asset API provides a centralized and authoritative view of a Google Cloud environment by continuously aggregating metadata from individual services into a single, consistent interface. It captures both the current state and historical changes of resources across By remaining strictly read-only, the API serves as a reliable source of truth for audits, governance, automation, and operational analysis, enabling teams to reason about their cloud environments with accuracy and confidence. ## **Building Blocks of Cloud Asset API** 1. **Asset Inventory:** Cloud Asset API maintains a centralized inventory by aggregating metadata from across GCP services into a single, consistent model. Each asset captures identity, configuration details, labels, and IAM policies where applicable. This allows teams to discover and understand their entire cloud footprint at an organization level without manually querying individual services or projects. 2. **Asset Search:** The asset search capability allows teams to query resources across projects, folders, or entire organizations using filters like resource type, location, and labels. Cloud Asset API queries can be executed from multiple entry points, including the gcloud CLI, Google Cloud Console (Cloud Asset Inventory), and programmatically via REST or client libraries. For deeper analysis and reporting, asset data can also be exported to BigQuery, where teams can run SQL queries across their entire cloud estate. This flexibility allows engineers, security teams, and governance tools to access the same asset data in ways that best fit their workflows. 3. **Asset Feeds (Change Detection):** Asset feeds deliver near real-time notifications whenever resources are created, modified, or deleted. These events are published to Pub/Sub, enabling automated workflows such as compliance checks, alerting, or remediation. This is especially valuable in fast-moving environments where frequent changes make manual tracking unreliable. 4. **Asset Export:** Cloud Asset API supports exporting asset data to Cloud Storage or ## **Getting Started with Cloud Asset API** **Step 1:** Enable the API: In the Google Cloud Console, navigate to "APIs & Services" and enable the "Cloud Asset API." **Step 2:** Assign Permission: Assign roles/cloudasset.viewer to a user or service account for read-only access to asset metadata and history. **Step 3:** Quick CLI Tutorial: Search all Compute Engine instances in a project: 1. **gcloud asset search-all-resources \** **--scope=projects/ck-gcp-poc \** **--asset-types=compute.googleapis.com/Instance** 2. Export assets to Cloud Storage: **gcloud asset export \** **--project=YOUR_PROJECT_ID \** **--output-path=gs://YOUR_BUCKET_NAME/assets.json** ## **Driving Security, Compliance, and Visibility Across Roles** One of the strengths of Cloud Asset API is that it does not belong to a single team. The same source of truth can be used differently by DevOps, security, data, and platform teams-each solving distinct problems while relying on the same underlying visibility. * **DevOps Engineering: Enforcing Infrastructure Standards Automatically** **How it operates:** The Cloud Asset API generates change events whenever new infrastructure is added to GCP. Serverless automation that verifies whether newly produced resources adhere to organisational standards—like required labels, network location, or security metadata—can be triggered by these events. For instance, an automatic check determines if ownership and security labels are present when a new Compute Engine instance is created. The system applies them right away or notifies the relevant team if they are absent. **Why it matters:** Manual reviews and recurring audits are no longer necessary for DevOps teams. Even when infrastructure is built via various pipelines or the console, standards are consistently followed. **Impact:** Without slowing down deployments or introducing human checkpoints, infrastructure consistency increases. * **Security Engineering: IAM Visibility Across the Organisation** **How it operates:** IAM policies from several projects, folders, and the company are combined into a single, queryable inventory via the Cloud Asset API. To find dangerous access patterns like external identities, cross-project permissions, or unduly broad responsibilities, security teams examine this data. **Why it matters:** One of the most frequent reasons for security problems is IAM sprawl. Risky permissions frequently go overlooked in the absence of centralised visibility. Checkout the **Impact** : Security teams may confidently apply least-privilege rules and proactively limit excessive access. * **Data & Analytics Teams: Governing Access to Sensitive Data** **How it operates:** BigQuery datasets and Cloud Storage bucket asset metadata are routinely exported to BigQuery. To make sure that sensitive datasets are not accessible to the public and that access policies comply with internal and legal requirements, data teams conduct cloud governance queries for improved business efficiency. When a dataset's permissions change while experimenting or working together, the problem is found early on, before it becomes a violation of compliance. **Why it matters:** Manual permission tracking becomes unfeasible as data environments expand. Sensitive data protection requires visibility into access setups. **Impact:** Stronger adherence to privacy and compliance rules and a decreased chance of data leaks. * **Platform Engineering: Governance at Scale** **How it operates:** Platform teams track infrastructure trends across hundreds of projects using the Cloud Asset API. They monitor unsupported services, configuration drift introduced outside of authorised workflows, and deviations from permitted architectures. Platform engineers use visibility and automated correction to help teams get back into compliance rather than obstructing teams up front. **Why it matters:** While free constraints lead to anarchy, rigid controls hinder innovation. A balanced governance approach is made possible via the Cloud Asset API. **Impact:** Maintaining self-service infrastructure and developer autonomy while maintaining consistent platform standards. ## Common Misconceptions About Cloud Asset API 1. **It's merely a tool for inventory:** The Cloud Asset API is not limited to listing resources. It allows for automation, incident analysis, and audits by tracking changes over time. 2. **Infrastructure-as-Code already covers this:** The Cloud Asset API displays the actual state, including manual or out-of-band modifications. 3. **Only security teams may use it:** Asset data is essential for compliance, governance, and troubleshooting for DevOps, platform, data, and incident response teams. 4. **It's difficult to use:** Asset feeds and exports operate automatically and smoothly interact with native GCP services once they are configured. ## **Pricing Overview** All use of Cloud Asset Inventory is free of charge. However, you are responsible for any costs associated with storing data that Cloud Asset Inventory produces, such as any data written to buckets in Cloud Storage. ## **Best Practices** * Use asset feeds for change detection, not polling, to capture near real-time updates without unnecessary API calls. * Export asset data to BigQuery for historical analysis, audits, and incident investigations instead of relying on point-in-time queries. * Grant least-privilege IAM roles, such as roles/cloudasset.viewer, and avoid using broad project owner roles for inventory access. * Combine asset data with labels and tags to enable meaningful filtering, ownership tracking, and policy enforcement. * Treat Cloud Asset API as a source of truth, validating Infrastructure-as-Code deployments against the actual runtime state. * Automate remediation carefully, ensuring feeds trigger validation logic before applying configuration changes. ## **Summary** Cloud environments don’t fail because teams move too fast; rather, they fail because visibility doesn’t keep up with change. A central source of visibility is provided by the Cloud Asset API, which displays what is there, how it changes, and who has access. It becomes an essential tool for large-scale cloud operations, whether you are enforcing compliance, securing IAM, safeguarding data, or handling incidents. Cloud Asset API transforms the management, governance, and security of GCP environments when viewed as a shared control plane rather than merely another API. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Priyanshi specializes in cloud cost optimisation, FinOps, and GCP, with a DevOps-driven approach to automating workflows and designing scalable systems that improve efficiency and business impact. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Pod In-Place Resizing is a This feature is particularly helpful for managing unpredictable workloads, ## **Key Concepts** * **Desired Resources:** A container’s ‘spec.containers[*].resources’ represent the container's required resources and are changeable in terms of CPU and RAM. * **Actual Resources:** The ‘status.containerStatuses[*].resources’ resources that are currently set up for a running container are reflected in this field. It shows the resources allotted for containers that have not yet started or have been restarted. * **Triggering a Resize:** By changing the desired requests and restrictions in the Pod's specification, you can request a resizing. Usually, kubectl patch, kubectl apply, or kubectl edit are used to target the resize subresource of the Pod. The Kubelet will try to resize the container if the assigned resources do not match the intended resources. The scheduler makes scheduling decisions based on the maximum of a container's allocated requests, intended requests, and actual requests from the status if a node includes pods with a pending or incomplete resizing. ## **Pod resize status** To reflect the status of a resize request, the Kubelet modifies the Pod's status conditions: * **type:** PodResizePending: The request cannot be fulfilled right away by the Kubelet. The reason is explained in the message field. **-- > reason: **Infeasible: The current node cannot accommodate the required resizing (for instance, by asking for more resources than the node has). **-- > reason:** Postponed: Although the requested resizing is not now possible, it may become achievable in the future (for instance, if another pod is eliminated). The resizing will be attempted again by the Kubelet. * **type:** PodResizeInProgress: Although the resizing and resource allocation have been approved by the Kubelet, the modifications are still being implemented. This is typically quick, but depending on the resource type and runtime behavior, it may take longer. The message field reports any faults that occur during actuation. ## **How kubelet retries Deferred resizes** The kubelet will periodically try the resize again if the requested resize is deferred, such as when another pod is eliminated or scaled down. If several resizes are postponed, they are retried in accordance with the following priority: * The resize request will be retried first for pods with a higher Priority (based on PriorityClass). * The resizing of guaranteed pods will be attempted before the resizing of burstable pods if two pods have the same priority. * Pods that have been in the Deferred state for a longer period of time will be given priority if everything else remains the same. Even if a higher-priority resize is postponed once again, all pending resizes will still be attempted, even if the higher-priority resize is designated as pending. ## **Container resize Policy:** We can control whether a container should be restarted or not when we resize the memory limits or the CPU limits, and request it by setting it in the resizePolicy in the Container specification, thus giving us the fine grained control based on the resource type Default container resizePolicy Example setup: Created a pod with a yaml file having a limit for CPU as 700m and memory as 200 Milliseconds Command to increase the limit and request of cpu Output: The CPU limit and request are increased to 800m To increase the limit of the memory, use the command Output: In the screenshot below, we can see that the memory has been increased to 300 Mi ## **Errors and Caveats** There are significant restrictions and warnings associated with Pod In-Place Resizing. In-place scaling is not fully supported by all workloads, Kubernetes versions, or container runtimes. Memory reductions are especially limited because if the program is unable to safely release memory, container termination may result from memory reduction. Although CPU scaling is more adaptable in general, how well it works relies on how the application uses CPU resources. Furthermore, during resizing operations, some workloads can still encounter temporary throttling or OOM(Out of Memory) occurrences. There are also operational considerations: resource changes may be subject to node capacity constraints, admission controllers, and policy enforcement. In-place resizing does not eliminate the need for proper capacity planning, monitoring, and testing. Applications should be designed to handle dynamic resource changes gracefully, and teams should validate resize behavior in non-production environments before relying on it at scale. ## **Conclusion** By enabling CPU and memory requests or limitations to be changed without restarting active pods, Pod In-Place Resizing significantly improves Kubernetes resource management. For stateful, long-running, and latency-sensitive applications, this functionality increases reliability, minimizes needless restarts, and maintains application state. It allows platform teams more freedom to respond to resource demands in real time while maintaining continuous application availability. In-place resizing improves overall cluster usage and allows for more accurate resource tweaking from an operational perspective. Without depending exclusively on pod recreation, autoscaling, or redeployments, teams can quickly address under- or over-provisioned workloads, cut waste, and enhance performance consistency. It creates a more flexible and responsive resource management approach when used with autoscaling technologies like HPA or VPA. In summary, while Pod In-Place Resizing is not a silver bullet, it is a powerful addition to the Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Priyansh Pathak is a tech enthusiast focused on automation, cloud-native platforms, and Kubernetes on AWS, with hands-on experience in Python-based automation and evaluating modern DevOps tooling t FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents So, you've probably heard this catchy phrase floating around in the cloud computing universe: **"You pay for what you use."** Sounds pretty straightforward, right? It conjures up visions of a perfectly fair and straightforward billing system where you're only charged for the computing power, storage, or other cloud services that you actively chow down on like a buffet at an all-you-can-eat restaurant. But, spoiler alert: it's not quite that simple. In reality, it's more like **"You pay for what you provision."** In this blog, we're going to dive headfirst into this cloud conundrum and unravel the mystery behind the cloud invoice, with a few examples to really drive the point home. ## **The Myth vs. The Reality** **Myth:** _You are only charged for the resources that you actively use._ This whole "pay for what you use" deal gives you the warm fuzzies, making you think that cloud billing is as precise as a surgeon's scalpel, billing you dollar for dollar based on your actual consumption of resources. It's like going to the grocery store and only paying for the groceries you ate, which implies a direct correlation between usage and cost. **Reality:** _You are billed for the resources you have provisioned, whether you use it or not!_ In the cloud, it's more like you pay for what you thought you might use. You see, you're not billed just for what you munch on; you're billed for the resources you've reserved or allocated, whether you're feasting on them or not. Yep, that gap between what you provision and what you actually use? That's where those sneaky unnecessary costs creep in, like those surprise charges on your phone bill. ## **Some Examples to Chew On** **EC2 Instances in AWS:** **Myth:** _You might think you're paying for the CPU cycles or data transfer you actually use._ Okay, picture this. You've got yourself an **Reality:**_You're billed for the entire instance as long as it’s running, not just the CPU and bandwidth you consume._ You're on the hook for the entire instance as long as it's running, whether you're chewing up its full capabilities or just nibbling on the edges. Order a big, beefy instance but only use a fraction of its muscle? Cloud billing solutions make sure you're still footing the bill for the whole shebang. If you provision a high-capacity instance but only use a fraction of its capabilities, you still pay for the whole thing. ### **Azure SQL Databases:** **Myth:** _You pay based on the queries you run._ Now, over in Azure land, you might think you're getting billed based on the number of queries you're throwing at your database. **Reality:** _Nope, not quite._ The Azure cloud billing services will hit you up for the DTUs (Database Transaction Units) or vCores you've reserved, whether you're running a database marathon or just doing a leisurely stroll through some data. Unused capacity? Well, that's basically wasted money right there. ### **Google Cloud Storage:** **Myth:** _You pay for the storage you actively use._ In Google's corner, you might assume you're only coughing up dough for the storage you're actively using. **Reality:** _You pay for the storage you've provisioned, whether or not you're using all of it!_ You're paying for the storage you've provisioned, whether your data's living it up or just hanging out in the corner, sipping a virtual cocktail. Even if you're only using half of that 100GB you provisioned, guess what? Google storage billing will ensure you pay for what you order in! ### **Kubernetes Clusters:** **Myth:**_You pay based on the pods you run._ Lastly, let's talk about those Kubernetes clusters, the cool kids on the cloud block. The myth would have you believe that you're paying based on the number of pods you're running. **Reality:**_You pay for the worker nodes you've set up, regardless of how many pods are running on them._ Cloud billing management for Kubernetes is not that simple. You're on the hook for the worker nodes you've set up, regardless of how many pods are crashing the party. For example, in ## **Bridging the Gap** So, how do you bridge this gap between what you thought you'd eat and what you actually devoured? Here are a few tips to help you navigate the cloud cost maze: **Rightsizing Your Services:** Regularly take a peek at the size and type of instances you've provisioned. Maybe you don't need that 64-core monster when a 16-core would do just fine. **Auto-Scaling:** Embrace the **Idle Resource Cleanup:** Don't let those resources sit around like forgotten leftovers in your fridge. Regularly clean up or downsize unused or underutilized resources that's not pulling its weight so that cloud billing services go easy on you. So, there you have it, folks. The saying "you pay for what you use" in the cloud is more like a catchy jingle than a solid truth. The real deal is more like "you pay for what you provision—whether you use it or not." Knowing this difference can help businesses make informed decisions and optimize their cloud costs effectively. And with tools like Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 15 15 Table of Contents Popular cloud infrastructure providers like AWS, If your workloads involve delivering services over the internet, chances are cloud infrastructure is already a key part of your system. That’s why it’s all the more important for you to stay updated on the top cloud computing trends for 2026. After conducting exhaustive research and validating it with top cloud experts at CloudKeeper, we’ve compiled a list of the top cloud computing trends for 2026, thus saving you the effort of scouring multiple sources and piecing together the information yourself! ## **1. The Complete Shift of AI Workloads to the Cloud** Cloud computing trends for 2026 predict that you’d hardly find any organization running their AI workloads—such as For most workloads, the ### **Training and Deploying AI Models Seamlessly on Cloud** Since 2023–2024, cloud computing trends have been such that most tech-driven companies have been investing significant time and resources in AI and ML to streamline operations, automate repetitive processes, and reduce business costs. Each organization has unique needs: Cloud computing trends show that some organizations use AI to optimize their sales development (SDR) pipelines, while others leverage it for business forecasting. That’s where model training becomes critical. Instead of relying on pre-trained, generic models, many companies now train custom ML models tailored to their data and objectives. ## **2. Cloud Bills Are Bound to Rise in 2026** For most companies, especially digital-native businesses (DNBs), cloud bills will start to make a considerably more noticeable dent in their OPEX. As a result, the need for While issues like unoptimized architecture, improper right-sizing of resources, and incorrect billing models have always been relevant, the cloud computing trends with respect to key cost drivers in 2026 are as follows: * **Rising energy prices:** This is a factor that is often overlooked when discussing cloud computing trends, but rising power costs are just as significant a factor as anything else. According to the U.S. Energy Information Administration, global energy demand has been growing by around 2.6% annually, while residential growth has remained at around 0.7%. As a result, power bills — especially for data centers — have surged. * **Cost runaways due to lack of expertise:** Cloud providers, to keep up with the cloud computing trends, are frequently releasing new services. Services are growing fast, but when engineering expertise doesn’t keep up, cost overruns happen. As a result, the demand for * **Rising hardware costs:** Cloud computing trends predict that GPU costs will continue to rise. Industrial GPUs, which generally run AI/ML tasks such as training transformer models, image recognition, and real-time inference, cost around $10,000–$30,000 per GPU. ## **3. FinOps Will Emerge as the Standard for Cloud Cost Management** In 2026, ## **4. The Growing Focus on Sustainable Cloud Computing** To cater to the rising demand for cloud resources, the expansion of cloud capacity by increasing the number and size of data centers shouldn’t come as a surprise to anyone. The increased — or increasing — capacity is one of a few cloud computing trends that has started to take its toll on the ecology of the areas where they are set up. The primary resource a data center impacts is the groundwater of that area, followed by energy emissions, and lastly, the generation of e-waste. Some examples are: 1. **Virginia, USA:** Almost 25% of the state’s total electricity is hogged up by data centers. And it’s not just the big corporations footing the bill — cloud computing trends suggest that residents of Virginia are expected to see their electricity costs double by 2039 due to the demand from data centers. 2. **Mesa, Arizona, USA:** From a purely monetary perspective, the rise of data centers in the middle of deserts is one of the few cloud computing trends the community could get behind — but instead, locals are far from pleased. A notorious example is the Apple data center approved in Mesa, which is estimated to consume up to 1.25 million gallons of water every single day. As a result, saying that people are concerned about the environmental impact of data centers would be an understatement — and definitely not paranoia. ### **What is GreenOps?** GreenOps is a framework that blends technology with business processes to optimize cloud efficiency while minimizing environmental impact. Call it a miracle or an awakening, but cloud computing trends show that organizations are beginning to realize that working with data can also harm the environment. As the popular saying goes, “Data is the new oil” — so it’s not far-fetched to say it pollutes too. When put to action, GreenOps includes all the actions an organization takes to reduce the ecological footprint of its cloud usage. It focuses on creating strategies that advance sustainability while supporting core business goals, such as: * Reducing resource waste * Transitioning to renewable energy sources * Fostering a company-wide culture of environmental responsibility ## **5) DevSecOps Will Redefine Cloud Security** DevSecOps combines development, security, and operations right from the very beginning. Companies are having a rude awakening — realizing that lax digital infrastructure security actually hurts the bottom line, and isn’t just something for engineers to worry about. It’s one of the few cloud computing trends bringing security efforts into the spotlight, rather than keeping them as a behind-the-scenes act. From code commits all the way to release, when security becomes a shared responsibility, vulnerabilities are caught early — not after production. It’s a welcome shift that both users and companies would heartily embrace. With automation and security testing built into CI/CD pipelines, teams get the best of both worlds: faster releases and stronger protection. ### **Embedding Security at Every Stage of Cloud Development** Code security starts with automated code scanning tools that detect vulnerabilities before deployment. The goal is simple — secure by default. When security checks happen automatically, teams can focus on building, knowing their code meets security standards every single time. ### **Emerging Tools and Practices Accelerating DevSecOps Adoption** Tools like AWS Security Hub, Azure Defender, and Google Cloud Security Command Center are helping automate much of this process. In cloud computing trends for 2026, you’ll often see these paired with Aqua or Prisma Cloud, providing complete situational awareness of your cloud environment. Alongside these, the rise of policy-as-code and runtime monitoring has made DevSecOps a practical solution. ## **6. Multicloud Deployments Will Become the New Normal** If you have even an elementary understanding of cloud computing trends, you’ll know there’s no “silver bullet” cloud provider. But that service diversity is still needed. What do you do in that case? This was a question organizations once struggled with — until the answer emerged: multi-cloud deployment, which is now set to become the new norm. Make no mistake, it’s still a challenge to “Resilience and redundancy” are the two Rs that attract companies to a multi-cloud setup. If one provider faces downtime or changes its pricing, your business doesn’t take the hit — you’ve got backup options. ### **The Rise of Hybrid Cloud (Native + Public Integrations)** Hybrid setups are a highlight of cloud computing trends for 2026 — where on-premises (native) systems work hand in hand with public clouds — and are becoming more popular. It gives companies the best of both worlds: the control of local infrastructure and the flexibility of the cloud. Many industries, especially finance and healthcare, are using hybrid models to balance compliance and scalability. Sensitive workloads stay on-prem, while compute-heavy operations move to the cloud. This mix keeps costs in check while maintaining agility. ## **7. Cloud-Native Software Development Will Lead the Way** Going by what This shift allows for faster scaling, easier updates, and reduced downtime. With tools like **Docker** , and **AWS Lambda** , developers can now build and deploy features independently. ### Cloud-Native Tools Expected to Dominate in 2026 Some of the most in-demand tools will include **Kubernetes, Argo CD, Istio, Terraform** , and **AWS Copilot**. These tools make automation, scaling, and continuous deployment smoother than ever. Cloud-native is going to be the new normal for how modern software is built. ## **8. Edge Computing Is Set to Take Off** Sending all that data to distant cloud servers for processing causes delays and higher costs. That’s where Edge Computing steps in — bringing the computation closer to where the data is created, for faster and more efficient processing. This means faster response times, reduced latency, and lower bandwidth usage. Industries like logistics, manufacturing, and healthcare are already adopting edge setups to make real-time decisions without waiting on cloud latency. ### **Real-Time Data Processing Closer to the Source** Edge devices powered by AI chips and lightweight models are allowing organizations to handle time-sensitive operations instantly. For example, predictive maintenance in factories or smart traffic management in cities now happens at the edge — not in distant data centers. ## **To Sum Up** Looking at the cloud computing trends, it’s clear that 2026 is set to be a defining year for cloud computing. With AI now finding its way into nearly every aspect of cloud , we’re going to see major shifts in how cloud systems operate and evolve. However, this rapid growth brings its own set of concerns — rising cloud costs, increasing environmental impact, and ever-growing security challenges. Beyond advanced CI/CD pipelines and complex Machine Learning models, artificial intelligence is now playing a key role in something every cloud user cares about — reducing cloud spend. That’s where our tools, CloudKeeper Tuner and CloudKeeper Commit, come into the picture. Here’s how these AI-powered platforms help keep your cloud costs in check: * **CloudKeeper Tuner:** * **CloudKeeper Commit:** As always, innovation comes hand in hand with challenges. The real question is — will the cost of these advancements outweigh their benefits, or will we find smarter, more sustainable ways to keep innovating? Only time will tell. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Chief Operating Officer Aman spearheads business operations, strategic execution, and cross-functional alignment to drive sustainable growth. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents As we move toward the year 2024, the cloud technology landscape continues to grow faster than ever. Worldwide end-user spending on public cloud services is forecast to grow 20.4% to a total of $678.8 billion in 2024, up from $563.6 billion in 2023, according to the latest With cloud computing maturing and becoming more and more pervasive, new and emerging technologies are driving the evolution and transformation of the cloud landscape. These technologies enable new capabilities, applications, and business models that leverage the power of the cloud. In this blog, we shall briefly explore some of the key cloud computing technology trends and predictions for 2024 and why they are important for customers, industry verticals, and cloud service providers. These trends encompass advancements in key themes such as artificial intelligence, edge computing, multi-cloud and hybrid cloud strategies, cloud security concerns, and resource optimization & cloud cost efficiency. ## **Evolution of Significant Cloud Computing Trends** ## **AI-Infused Cloud Services** AI integration within cloud platforms becomes more ubiquitous, unlocking intelligent functionalities, predictive analytics, and automated decision-making. As we move closer to 2024, the integration of AI within cloud services is expected to evolve in the below-mentioned areas: ### **1. Automated Data Preparation** This technology harnesses machine learning algorithms and AI-driven processes to automate the cleaning, integration, and organization of diverse datasets. By automating repetitive tasks and eliminating manual errors, it accelerates data processing, ensuring improved accuracy and consistency in analyses. ### **2. Intuitive Query and Visualization** This technology will enable users to interact seamlessly with complex datasets through natural language queries and intuitive visualization interfaces. Leveraging AI and augmented analytics, it translates complex data into easily digestible visual representations and facilitates quick decision-making and a deeper understanding of trends, patterns, and correlations within data. ### **3. Augmented Collaboration and Insights Sharing** These advanced services leverage AI-driven capabilities to enhance collaboration by facilitating real-time information exchange, predictive analytics, and intelligent decision-making. ## **Cloud FinOps Evolution** The ### **1. Real-Time Cloud Cost Visibility and Granular Insights** These tools provide real-time cloud cost tracking, ### **2. Automation for Continuous Optimization** Smart automation capabilities optimize resource utilization, automatically scaling instances, ### **3. Integration with DevOps and Cross-Functional Collaboration** This integration fosters a culture of cost-awareness among engineering teams, promoting collaboration between finance, operations, and development. The method facilitates cross-functional collaboration, allowing stakeholders to align cloud costs with business objectives effectively. ## **Edge Computing Dominance** The dominance of edge computing is poised to significantly reshape the technological landscape as we approach 2024. Here’s an in-depth look at how edge computing is set to dominate: ### **1. AI and Edge Integration** The fusion of artificial intelligence (AI) with edge devices and networks marks a significant progression in technological integration. Leveraging AI algorithms in edge computing proclaims a new era of distributed intelligence, unlocking novel possibilities for decentralized, intelligent decision-making at the edge of networks. ### **2. Edge-as-a-Service (EaaS)** EaaS eliminates the need for substantial upfront infrastructure investments, enabling businesses to tap into the potential of edge computing without bearing the burdens of deploying and managing dedicated edge infrastructure. By embracing EaaS models, organizations gain flexibility, scalability, and agility in deploying edge applications. ## **Quantum Computing Integration** Quantum computing marks its inception into cloud services, offering immense potential for complex problem-solving and revolutionizing computational capabilities. This integration brings forth a multitude of advancements and transformative impacts, such as: ### **1. Enhanced Computational Capabilities** The integration of quantum computing within cloud services heralds a groundbreaking era of enhanced computational capabilities poised to redefine the realms of computing as we know them. This transformative union facilitates the execution of sophisticated simulations, enables rapid optimization of complex processes, and revolutionizes cryptography applications by bolstering security through more robust encryption methods. ### **2. Industry-Specific Applications** The advent of quantum cloud services heralds a transformative wave across diverse industries, promising a paradigm shift in how optimization, data analysis, and problem-solving are approached in specialized domains. This innovative technology holds immense promise for sectors such as finance, healthcare, logistics, and materials science. ## **Multi-Cloud Orchestration** Multi-Cloud Orchestration refers to the strategic management and coordination of various cloud services and resources across multiple cloud providers. This approach offers the following advantages and capabilities: ### **1. Mitigation of Risk** Mitigating risks through multi-cloud strategies involves diversifying an organization's cloud infrastructure across multiple service providers. This approach offers several advantages, notably reducing the vulnerability to potential outages, security threats, or compliance issues that might affect a single cloud provider. ### **2. Scalability and Resource Allocation** The utilization of multiple clouds for orchestrating workloads presents a compelling solution for achieving dynamic scalability and ### **3. Innovation and Future-Proofing** The adoption of multi-cloud orchestration serves as a catalyst for fostering innovation and future-proofing strategies within organizations. Embracing a multi-cloud approach empowers enterprises to cultivate an innovative culture by exploring and integrating new technologies and services available across diverse cloud ecosystems. ## **Potential Challenges and Opportunities** While the prospects are promising, the challenges mentioned below might persist: ### **Security and Data Privacy Concerns** Heightened focus on robust security measures and data privacy regulations amid rising cyber threats and regulatory compliance. 1. #### **Privacy Regulations and Compliance Challenges** Stringent data privacy regulations like GDPR, CCPA, and evolving regional laws necessitate strict compliance measures. Organizations grapple with the complexities of ensuring data sovereignty, lawful processing, and consent management across diverse jurisdictions. 2. #### **Vulnerabilities in Cloud-Native Technologies** Cloud-native technologies, including containers and serverless architectures, introduce unique security challenges. Inadequate patch management, insecure APIs, and shared responsibility models create avenues for exploitation. ### **Skill Gap and Talent Acquisition** The need for skilled professionals adept at managing and optimizing complex cloud environments presents an opportunity for upskilling and talent acquisition. 1. #### **Shortage of Specialized Skills** With Gartner stating that some 91 percent of organizations have not yet reached a “transformational” level of maturity in data and information, the need to drive improved decision-making is just one reason why the number of jobs requiring data science skills is expected to grow 27.9% by 2026. 2. #### **Hybrid and Multi-Cloud Expertise** Competency in orchestrating workloads across multiple platforms is essential but lacks availability. According to the ## **The Road Ahead** While the future of cloud computing appears promising, challenges persist. Issues around data sovereignty, vendor lock-in, and managing multi-cloud complexities will necessitate strategic planning and robust governance frameworks. However, these challenges present opportunities for innovation, CloudKeeper, as a sophisticated multi- In conclusion, 2024 promises an ever-evolving cloud computing landscape characterized by transformative technologies, enhanced security measures, and unprecedented opportunities for businesses. While challenges persist, innovative solutions pave the way for efficient cloud cost management, enhanced governance, and continued innovation in the realm of cloud computing. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * * * * * * I am looking for blogs on Automation Cloud Cost Management AWS EDP AWS Services Cloud Cost Analytics Cloud Cost Optimization DevOps FinOps Strategy RI Management Kubernetes GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 Solving the Blind Spot in GCP Billing with Browser Automation A comprehensive guide to solving the lack of visibility in GCP Commitment-Based Discount reports from the BigQuery billing export, using custom Python automation scripts and Selenium. By Manav Mittal 19 Aug, 2025 AI Cost Optimization Strategies: How to Cut Costs Without Slowing Innovation Explore practical strategies to optimize AI workloads in the cloud, reduce costs, and boost performance through automation, right-sizing, and smarter resource use. By Aman Aggarwal 24 Jul, 2025 Centralized Monitoring in AWS cloud using Amazon CloudWatch A simple step-by-step guide to configure AWS CloudWatch for centralized monitoring across accounts using logs, metrics, and AWS X-Ray. By Siddharth Sharma 10 Jul, 2025 GCP Cost Monitoring: 10 Tips to Avoid the Cloud Bill Shock Struggling with unexpected GCP bills? Learn 10 expert tips to monitor and optimize your Google Cloud costs, prevent overages, and maximize savings effectively. By Team CloudKeeper 12 Mar, 2025 Unlocking the Power of EKS Cost Tracking Learn how CloudKeeper's EKS cost tracking dashboard offers granular insights for EKS cost optimization, enabling cloud cost reduction and data-driven decisions. By Harsh Agarwal 25 Sep, 2024 Hourly Dashboards in CloudKeeper Lens Explore Hourly Dashboard, a new feature of CloudKeeper Lens to track AWS spend by each hour of the day. Gain cost control, monitor, optimize, and save with precise, hourly data insights. By Harsh Agarwal 26 Aug, 2024 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents In recent years, cloud computing has become the solution of choice for businesses of all sizes, promising greater flexibility, scalability, and cost efficiency. However, there are some misconceptions about cloud costs that can lead to unexpected expenses and budget overruns. This article addresses and debunks these misconceptions and provides insight on how to overcome them to effectively optimize cloud costs. ## **Cloud is always cheaper than on-premises infrastructure** One of the most common misconceptions is that moving to the cloud automatically guarantees cost savings. The cloud offers the following potential cost advantages, but the actual cost savings depend on many factors, for example, lower initial investment and operating costs. These include workload characteristics, usage patterns, data transfer costs, and the level of optimization implemented. It is crucial to perform a thorough cloud cost analytics exercise and compare the total cost of ownership, to make an informed decision. ## **Cloud providers will automatically optimize costs for you** Cloud providers offer a range of tools and services to help optimize cloud costs, but the responsibility for cost optimization ultimately lies with the user. Cloud providers may offer recommendations and suggestions based on usage patterns, but it's essential for businesses to actively monitor their resources, and right-size instances, **1. Utilize automation and orchestration:** Automation plays a crucial role in optimizing costs. By automating routine tasks, businesses can reduce manual errors, optimize resource provisioning, and ensure that resources are only active when needed. Utilize tools like auto-scaling, auto-start/stop schedules, and infrastructure-as-code to dynamically adjust resources based on demand, thereby helping **2. Implement tagging and resource grouping:** Cloud providers allow you to assign tags to resources, enabling you to categorize and track costs based on different dimensions such as departments, projects, or applications. By using tags effectively, you can gain granular visibility into resource costs and allocate expenses accurately, allowing for **3. Leverage cost analysis and monitoring tools:** Cloud providers offer cost analysis and monitoring tools that provide detailed insights into resource consumption and associated costs. Utilize these tools to identify cost trends, spot anomalies, and gain a better understanding of the factors driving your cloud costs. This information can help you make informed decisions regarding resource allocation and identify areas for cost optimization. **4. Take advantage of spot instances and reserved instances:** Cloud providers offer pricing options like spot instances (unused capacity available at a significantly reduced cost) and reserved instances (prepaid instances for a specific term at a discounted rate). By leveraging these options intelligently, you can significantly reduce costs, especially for non-critical workloads or long-term commitments. **5. Consider multi-cloud or hybrid cloud strategies:** It's worth exploring multi-cloud or hybrid cloud strategies to optimize costs further. By distributing workloads across multiple cloud providers or combining on-premises infrastructure with cloud resources, businesses can take advantage of competitive pricing, leverage specific service offerings, and maintain cost efficiency. **6. Continuously evaluate and optimize resource utilization:** Regularly review your resource usage patterns to identify underutilized instances or idle resources. Right-size your instances by selecting the appropriate instance types and sizes based on workload requirements. By optimizing resource utilization, you can minimize costs while ensuring optimal performance. **7. Engage with cloud provider support and cost optimization programs:** Cloud providers often offer support and cost optimization programs to assist businesses in optimizing their cloud costs. Take advantage of these resources, consult with their experts, and participate in cost optimization initiatives to stay updated on best practices and leverage provider-specific cloud spend optimization tools. ## **All cloud services are priced the same across providers** Cloud services are not priced uniformly across different providers. Each provider has its own pricing model, instance types, and additional service charges, so it's important to compare costs between providers for effective cloud infrastructure management. Additionally, pricing structures can be complex, with various factors such as data transfer, storage, data processing, and additional services affecting the overall cost. Before choosing a cloud provider, it's important to understand pricing models, research pricing calculators, and consider your workload's specific needs. **1. Diverse pricing models:** Cloud providers offer different pricing models, such as pay-as-you-go, spot instances, reserved instances, and committed use discounts. These models vary in terms of commitment levels, payment structures, and flexibility. Understanding the pricing models of different providers is essential to determine which one aligns best with your workload and cloud spend optimization goals. **2. Varied instance types and sizes:** Cloud providers offer a wide range of instance types with varying specifications and performance capabilities. Each provider may have its own unique instance types, such as general-purpose, memory-optimized, or GPU-based instances. The pricing for these instances can differ significantly, and **3. Additional service charges:** Cloud providers often offer additional services beyond basic computing and storage, such as database services, content delivery networks, machine learning services, and analytics tools. These services typically have their own pricing structures, which can vary between providers. It's important to consider the costs associated with these additional services when comparing pricing across providers. **4. Data transfer costs:** Transferring data into and out of the cloud can incur additional charges. Cloud providers may have different pricing tiers for data transfer within their networks and between different regions. The volume of data transferred and the distance between regions can impact the overall cost. Analyzing data transfer patterns and **5. Storage costs:** Cloud providers charge for storing data in their infrastructure, and the pricing can differ based on the storage type (e.g., object storage, block storage, archival storage) and the volume of data stored. Some providers offer tiered pricing based on storage usage levels, while others may have different pricing tiers for different storage classes. Evaluating your storage requirements and understanding the pricing variations is important to determine the most cost-effective option. **6. Data processing and other service-specific costs:** Depending on the type of workload and the services utilized, cloud providers may charge for data processing, API requests, load balancing, monitoring, and other service-specific features. These costs can vary between providers, and understanding the pricing structure for these additional services is an important aspect of **7. Research and utilize pricing calculators:** Cloud providers typically provide pricing calculators or cost estimation tools that allow you to input your workload specifications and get an estimate of the associated costs. Utilize these tools to compare costs across providers, considering the various factors mentioned above. These calculators can help you make an informed decision by providing a comprehensive view of the expected expenses. ## **Cloud costs are static and predictable** Cloud costs can fluctuate based on factors such as resource usage, demand spikes, and pricing model changes. Workloads with unpredictable or highly variable usage patterns can lead to unexpected cost spikes. It is important to regularly monitor usage and costs, leverage automation and autoscaling capabilities, and implement effective cloud spend optimization strategies to ensure costs are predictable and within budget. ## **Cloud services are always billed accurately** Cloud providers strive to maintain accurate billing practices, but errors can still occur. Improperly terminated instances, improperly configured autoscaling rules, or improper resource allocation can lead to high costs. Businesses should regularly check their bills, monitor resource usage, and adopt cloud infrastructure management tools that provide detailed insight into resource consumption. By proactively managing and validating billing information, organizations can quickly identify and resolve billing discrepancies **1. Accurate billing:** While cloud providers strive for accurate billing practices, errors can still occur due to various factors. Regularly checking your bills helps ensure that you are being charged correctly for the resources and services you are utilizing. **2. Identifying improperly terminated instances:** Improperly terminated instances, whether due to technical issues or human error, can continue to accrue charges unnecessarily. Monitoring your resource usage and checking your bills allows you to identify any instances that have not been properly terminated and take appropriate action. **3. Managing autoscaling:** Autoscaling is a valuable feature that automatically adjusts resource allocation based on demand. However, improperly configured autoscaling rules can lead to unnecessary resource usage and increased costs. Monitoring resource usage and analyzing billing information can help identify any autoscaling issues and optimize cloud costs. **4. Resource allocation:** Ensuring proper resource allocation is crucial for cloud spend optimization. Checking your bills and monitoring resource usage allows you to identify over or under-utilized resources and make necessary adjustments to optimize resource allocation, thereby avoiding unnecessary costs. **5. Cost variations:** Cloud providers may have different pricing for their services based on the geographical location of the data centres or regions. Prices can vary based on factors such as infrastructure costs, local regulations, energy costs, and market demand. **6. Regional price variations:** Pricing variations can occur between different regions within a cloud provider's network. Some regions may have higher or lower prices compared to others, depending on factors like local competition, demand, and infrastructure availability. These factors must be accounted for in cloud cost analytics. **7. Data transfer costs:** Data transfer between regions or data centers may incur additional charges. Cloud providers often charge for both incoming and outgoing data transfer, and costs can vary based on the distance between the locations. **8. Cost savings:** Cloud providers offer reservation options, such as Reserved Instances (RIs) or Savings Plans, which allow users to commit to using specific resources over a certain period. Reservations offer discounted rates compared to on-demand pricing, resulting in significant cost savings over time. **9. Upfront payments:** Reservations typically involve upfront payments, where users pay a lump sum or a partial upfront amount to secure the discounted rates. The upfront payment contributes to the overall cost savings but requires an initial financial commitment. **10. No upfront options** : Some cloud providers offer "no upfront" reservation options, where users can still benefit from discounted rates without making any upfront payments. Instead, the discounted pricing is distributed over the duration of the reservation term. **11. Term commitments:** Reservations come with term commitments, ranging from one to three years, depending on the cloud provider and the specific reservation type. Users commit to using the reserved resources for the duration of the term to avail of the discounted rates. ## **Conclusion:** Cloud computing undoubtedly offers significant benefits, but cloud spend optimization requires careful consideration and proactive action. By dispelling common misconceptions about cloud costs and implementing effective cost optimization strategies, organizations can maximize the potential of the cloud while controlling budgets. Regular monitoring, right-sizing, cloud cost analytics, leveraging cost-saving mechanisms, cross-vendor price comparisons, and bill verification are key steps to a successful, cost-effective cloud journey. _When it comes to_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Top 10 Best Cloud Cost Management Tools in 2026 (Ranked by G2 Users) This blog walks you through the top 10 Cloud Cost Management tools featured in the G2 Winter 2026 Grid® Report, highlighting their strengths and limitations to help you choose the right FinOps platform. By Naman Jain 18 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents According to a Nowadays, one of the most important goals for a CXO-level stakeholder is cloud cost management. An ample amount of time & energy is spent in first migrating workloads to the cloud and then maintaining the uncertainty of costs. If focus is placed on improving the processes & strategies of managing cloud costs, a huge part of the revenue can be maintained and further, grown to the next target. That’s where CloudKeeper comes in. Over the course of a decade and more, we have honed our skill set and come up with 3 automated & AI-based platforms to simplify cost management, cost allocation, chargeback, anomaly detection & much more! In this blog, we will explore the importance of cloud cost management, compare it with cloud cost optimization, offer tips on multi-cloud management, and introduce automated platforms to optimize costs. Let’s get started! ## **Why is Cloud Cost Management so important for businesses?** With the convenience and flexibility that cloud platforms offer, there is a growing need to keep track of cloud-related expenses. Managing these costs effectively is crucial for maximizing the value of cloud investments. As businesses increasingly migrate their operations to the cloud, understanding and managing cloud expenses becomes essential for financial efficiency and operational success. Here’s why cloud cost management matters: **1. Cost Control:** Without proper oversight, cloud spending can spiral out of control due to factors like over-provisioning, idle resources, or unexpected usage spikes. Proper cloud cost management ensures that cloud resources align with actual needs, avoiding wasteful spending. **2. Financial Visibility:** By cloud costs monitoring, businesses can gain real-time insights into how resources are being used and allocate budgets accordingly. This clear cloud cost visibility clubbed with real-time dashboards helps in making data-driven decisions that can boost profitability. **3. Improved Forecasting:** Effective cloud cost management tools enable **4. Competitive Advantage:** Organizations that manage their cloud costs well are better positioned to invest savings into innovation and other core activities, giving them a competitive edge. ## **Cloud Cost Management vs. Cloud Cost Optimization** While cloud cost management focuses on controlling and monitoring expenses, cloud cost optimization takes a step further by proactively finding ways to reduce costs without compromising on performance. Here’s how they differ: **Cloud Cost Management:** This is about keeping track of what you’re spending and ensuring that expenses stay within the set budget. It involves monitoring usage patterns, creating detailed reports, and assigning costs to various departments. This also offers insights into where and how money is being spent on cloud resources. **Cloud Cost Optimization:** Optimization goes beyond just monitoring. It uses the insights from cloud cost management to maximize business value at the lowest possible cost. It involves taking actionable steps to reduce costs, such as rightsizing instances, eliminating idle resources, and Both are essential for ensuring that businesses not only stay within their cloud budgets but also maximize their return on investment (ROI) in cloud services. ## **Cloud cost management across multiple cloud platforms** Managing costs across multiple cloud platforms can be challenging. Here’s how you can simplify multi-cloud cost management: **1. Unified Dashboards:** Use a cloud cost management tool that aggregates data from all cloud providers into a single dashboard. This provides a holistic view of expenses and avoids data silos **2. Set Governance Policies:** **3. Centralized Billing:** Implement a centralized billing system that consolidates cloud costs from different providers, helping to monitor and compare expenses effectively **4. Cross-Platform Automation:** Automate tasks like resource provisioning, scaling, and shutdown across different cloud environments to optimize costs **5. Interoperability Considerations:** Choose tools that support the interoperability of cloud services to minimize vendor lock-in and ensure flexibility in switching between providers Learn more about picking the right kind of multi-cloud management tools ## **Cloud Cost Management Best Practices** There are multiple best practices that are referred to, quite frequently, including rightsizing resources, leveraging reserved & spot Instances, daily monitoring and tagging of resources, and more. Here are some of them explained: ### **1. Enable Cost Cost Monitoring & Tracking** Organize resources by applying tags or labels (e.g., by project, department, environment) to track cloud costs by categories. This provides a clear view of where resources are allocated and helps manage budgets. We should also leverage tools like Tag Editors to efficiently automate the process of tagging. Tools like AWS Config Rules or Azure Policy can enforce tag compliance, alerting teams when resources are missing tags. Here are some tagging standards one must keep in mind for better cloud cost management: * Identify the right tags for your resources, focusing on the specific purpose for each tag (e.g., project, department). Collaborate with cross-functional teams to define standard tags. * Ensure consistency by standardizing tag names, avoiding duplicates, and preventing inconsistencies. * Share and publish the tagging standards across the organization to keep everyone aligned. We should prepare internal documentation or wikis, ensuring everyone follows the same conventions. * Apply tags to meet all necessary tracking criteria, giving you better visibility into cloud usage and costs. Learn more about the ### **2. Set Budgets and Spending Limits** Define budgets for teams, applications, or services, and monitor them regularly. Configure automated alerts to notify you when cloud spending approaches or exceeds budget thresholds. This allows for early action before unexpected costs accumulate. For instance, you could set a budget of $10,000/month for a department and automatically receive alerts if the budget crosses 80%. This gives teams a chance to investigate and correct course before incurring more costs. You can use tools like AWS Budgets or Google Cloud’s Billing Alerts to track costs against predefined budgets and configure alerts for early warnings. You can also sign up with ### **3. Right-Size Resources** Review and adjust the allocation of resources to avoid over-provisioning or underutilization. For example, if a production database is only using 50% of allocated CPU, downgrade it to a smaller instance type. This simple action could save thousands annually. ### **4. Utilize Cost-Efficient Pricing Models** If workloads are predictable, consider reserved instances, savings plans, or commitment-based pricing to lower costs compared to on-demand pricing. AWS offers up to 72% discounts for Reserved Instances with one- or three-year commitments, which is ideal for steady-state applications. For flexible workloads, consider spot instances (AWS) or preemptible VMs (Google Cloud) that offer deep discounts for non-critical applications. ### **5. Automate and Enforce Cost Policies** Set up automation to shut down unused resources (e.g., non-production environments during off-hours). Use governance tools to enforce cost-saving policies, such as limiting the provisioning of expensive resources or enforcing the use of low-cost storage tiers. We can use tools like AWS Lambda or Azure Automation to automatically shut down idle resources during non-working hours. Implement policies in AWS Control Tower or Azure Policy to enforce the cost-saving rule. These practices help in better cloud cost management by preventing overspending, optimizing usage, and providing insights into cloud expenditures. While all of them work well when implemented with careful consideration, to get the maximum advantage out of cloud cost management, automation & AI needs to be incorporated. Here’s how CloudKeeper offers certain platforms to help you achieve your cost optimization goals faster than usual. ## **Keep Your Cloud Cost Management on the Right Track With CloudKeeper** **CloudKeeper Lens: Efficient cost allocation, chargeback, tagging, and anomaly detection** This platform focuses on making cloud spend more intelligent through optimized tagging, anomaly detection, and chargeback strategies. By getting complete visibility and building smarter processes, businesses can gain deep insights into resource utilization and identify inefficiencies in real time. Learn more about CloudKeeper Lens for **CloudKeeper Auto: Zero-Touch, AI-based AWS reservation management** CloudKeeper Auto enables zero-touch, AI-driven platforms empowering businesses to automate **CloudKeeper Tuner: An Automated AWS Usage Optimization & Recommendation Platform** An The goal is continuous improvement and better business outcomes with less manual effort. ## **Conclusion** Cloud cost management is not just about saving money; it’s about making smarter, data-driven decisions to ensure long-term success. By implementing the right strategies and tools, businesses can unlock significant value from their cloud investments while staying within budget. Whether you're just starting out or are already a cloud-first organization, optimizing your cloud costs should be a top priority for sustainable growth. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * * * * * * I am looking for blogs on Automation Cloud Cost Management AWS EDP AWS Services Cloud Cost Analytics Cloud Cost Optimization DevOps FinOps Strategy RI Management Kubernetes From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 How 400+ Global Teams Are Solving Cloud Cost Issues & Scaling Efficiently? This blog distills real cloud cost problems, visibility gaps, overprovisioning, storage creep, and AI/Kubernetes sprawl and shows how ownership and CloudKeeper expertise drive lasting savings. By Team CloudKeeper 08 Jun, 2026 Vega Cloud Receivership: What It Means for FinOps and Cloud Cost Optimization in 2026 Vega Cloud’s entry into receivership has raised FinOps concerns, with the cloud cost management firm reportedly restructuring after financial challenges, including unpaid AWS dues. By Team CloudKeeper 29 Jan, 2026 Top Agentic AI Trends to Watch in 2026: How AI Agents Are Redefining Enterprise Automation This blog explores Top Agentic AI Trends to Watch in 2026 and how AI Agents Are Redefining Enterprise Automation. By Team CloudKeeper 27 Jan, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 A complete guide to Multi-Cloud Management This blog explores the rise of multi-cloud adoption, the challenges enterprises face, and how a modern multi-cloud management platform turns complexity into a strategic advantage. By Team CloudKeeper 31 Dec, 2025 Monitoring AWS Costs and Resource Utilization with Amazon SNS A comprehensive, step-by-step tutorial on controlling cloud costs using Amazon SNS for AWS monitoring and actionable cost optimization. By Naveen 23 Dec, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents As companies expand their digital functions, the significance of efficient cloud cost management has become more critical than ever. By 2025, the cloud environment is anticipated to become increasingly dynamic, shaped by technological innovations, a rising demand for transparency, and the necessity for sustainability. This blog delves into the ## **Shifting Dynamics in Cloud Cost Management** ### **1. The Rise of AI and ML in Cloud Operations** Artificial intelligence (AI) and machine learning (ML) are transforming cloud management. These technologies examine large quantities of cloud usage data to identify inefficiencies and forecast opportunities for cost savings. By 2025, tools for AWS has recently launched AI-powered tools that offer insights into cost irregularities, helping users detect and address issues before they worsen. Businesses using similar tools have reported savings of as much as 30%. ### **2. The Growing Complexity of Cloud Environments** The ### **3. Rising Demand for Cost Transparency and Accountability** According to a report by FinOps Foundation, ### **4. Increasing Focus on Sustainability and Energy Efficiency** Sustainability is now essential rather than optional. Cloud service providers are implementing energy-efficient methods to lessen their environmental impact, and businesses are emphasizing green cloud options to align with their sustainability objectives. By the year 2025, energy efficiency will become a vital factor in managing cloud costs. Google Cloud’s carbon-conscious computing system organizes workloads to be processed in areas where carbon intensity is at its lowest, leading to reductions in costs and emissions. Organizations utilizing such systems experience considerable Organizations should try engaging with cloud service providers that focus on renewable energy and employ energy-efficient data centers. They can also enhance workload efficiency by scheduling non-urgent tasks during off-peak times to lower energy expenses. ## **How to Adapt to the Changing Landscape?** Adapting to these trends requires a proactive approach. Organizations need to bridge the gap between understanding the dynamics of the cloud ecosystem and implementing practical solutions to meet evolving demands. Here’s how you can effectively adapt: ### **1. Adopt AI-Driven Optimization** AI and machine learning have transitioned from emerging technologies to indispensable tools for managing costs. Utilize AI to: * Anticipate future expenses based on past trends. * Spot idle or underused resources. * Automate scaling to correspond with real-time demand. **Action Step:** Investigate AI-driven solutions designed for your cloud infrastructure. Consider platforms like ### **2. Streamline Multi-Cloud Management** To effectively manage the intricacies of multi-cloud and hybrid-cloud environments: * Utilize platforms that combine cost information from various providers. * Standardize resource tagging and naming conventions. * Regularly review your cloud architecture to remove duplications. **Action Step:** Consider investing in a comprehensive ### **3. Foster a Culture of Cost Accountability** Optimizing costs should be a collective responsibility. Create an accountability culture by: * Educating teams about the financial consequences of cloud usage. * Assigning specific cost ownership for each resource. * Employing chargeback or showback models to encourage responsible consumption. **Action Step:** Organize recurring training sessions related to ### **4. Emphasize Sustainability** Sync cloud operations with sustainability ambitions by: * Selecting providers committed to renewable energy initiatives. * Tracking and reporting the carbon footprint of your cloud activities. * Optimizing workloads to lessen energy use. **Action Step:** Utilize sustainability calculators offered by cloud providers, such as AWS’s Customer Carbon Footprint Tool, to gauge and enhance your environmental impact by scheduling non-essential tasks during off-peak hours to lower energy expenses. ## **The Road Ahead** As the cloud environment continues to change, strategies for managing costs must evolve to keep up with technological progress, growing complexity, and the need for sustainability. Tools from third-party providers, such as CloudKeeper, are essential for managing this complexity by offering advanced analytics, enhanced savings, and extensive support. Companies that take a proactive approach by utilizing AI-driven solutions, streamlining multi-cloud cost management, focusing on transparency, and embracing sustainable methods will not only manage costs more effectively but also secure a competitive advantage. By applying the strategies discussed above, organizations can successfully navigate the changing landscape of cloud cost management and set themselves up for long-term achievement. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Discussions on cutting cloud costs are everywhere, from the internet to top tech conferences. It is not only the executives from finance or DevOps who are pondering over the issue, but In a unique survey, _Discussions about budgets increased by 17.4% and cost optimization discussions rose by 21.4% in Q4 2023 compared to the previous quarter, as CEOs considered the costs of borrowing money and servicing their debts among relatively high interest rates. As these and other operational expenses start to weigh on the bottom line, many enterprises try optimizing costs, with cloud-related optimization as an example focus area. In response to this trend, AWS announced its Cloud Cost Optimization Hub at AWS re:Invent 2023, which aims to help customers optimize their cloud spending._ ” This suggests that CEOs are becoming more aware of this critical factor that spikes the business cost and hence, are actively involved in exploring the ways of cloud cost optimization. Image source: In this blog, we explore the changing dynamics of the ## **FinOps Adoption for Cloud Cost Optimization: Senior Leaders Taking the Control** As economic uncertainties rise globally, CEOs and board members are increasingly focused on optimizing costs across all sectors. Cloud-related expenses have gained prominence, with unmanaged bills potentially causing financial strain. As per a recent survey by the Everest group, 46% of organizations struggle to define comprehensive cloud unit economics, hindering clear measurement of cloud cost's impact on business value. FinOps has become a widely recognized approach in the business world, as it promises to empower organizations with cloud cost ownership across all levels and Cloud FinOps practices facilitate the adoption of a well-structured collaborative framework that bridges IT, finance, and business units. It helps businesses establish clear cost ownership, set realistic budgets, and align cloud costs with business value. This cross-functional collaboration ensures that cloud expenses are not just controlled but strategically aligned with organizational goals. _**Senior leadership, including SVPs, VPs, Directors, CIOs, and CTOs, actively participates in FinOps decisions (12% representation from business and management leaders), underscoring its strategic importance.**_ Figure: Taken from ## **Drivers of Business Leader Engagement in Cloud FinOps** Earlier, we mentioned that ‘economic uncertainties’ is one of the major factors pushing shareholders and businesses to focus more on cloud cost reduction. However, other drivers have led to this shift in responsibilities. * **Rising Costs:** Underutilized resources, inefficient configurations, and a lack of cloud cost visibility contribute to wasted spending, thus escalating uncontrolled cloud bills. With increasing pressure on budgets, board members are * **Focus on ROI:** Shareholders and board members are becoming increasingly concerned with getting a good return on their investment (ROI) from all technology initiatives, including using cloud computing. Their main question is whether cloud adoption provides benefits beyond just saving money. They want to know if controlling cloud costs can also maximize the value, they get from their cloud investment by * **Data-Driven Decision Making:** A well-informed business decision should always be backed up with real-time data points. The availability of detailed cloud cost data empowers boards to understand the pretext of cloud expenses, allowing them to make appropriate budgeting decisions. The use of various sophisticated cloud cost visibility tools like CloudKeeper Lens that provide * **Sustainability Concerns:** Environmental, Social, and Governance (ESG) considerations are gaining traction in boardrooms. Cloud cost optimization can contribute to sustainability goals by reducing the energy consumption associated with underutilized resources. This encourages board members to actively learn about optimizing cloud usage and show their commitment to managing resources responsibly. ## **Finding Their Place: Business Leaders in the FinOps Landscape** The The Image content source: So, where and how do business leaders fit with their roles, in this FinOps Framework? Here is how: ## **Embrace FinOps for Cloud Cost Optimization & more** Cloud cost optimization has become a top priority in boardrooms, with business leaders taking an active role in driving optimization efforts. Thanks to FinOps adoption, leadership now has a deeper understanding of cloud operations and associated costs, enabling them to develop Ready to unlock the full potential of FinOps in your organization? Our team of cloud FinOps experts is here to guide you every step of the way. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 16 16 Table of Contents Still, think cloud cost optimization is just a technical matter? Well, not anymore. As cloud adoption has accelerated, so have cloud expenses, often reaching a point where these rising costs become a key concern at the executive level. Leaders have now realized that their bottom line could take a significant hit without proactive cloud cost management. As a result, ## **What is Cloud Cost Optimization?** Cloud cost optimization is a proactive and strategic process that goes beyond simply cutting costs. It’s about getting maximum value from cloud investments through a mix of smart allocation, strategic planning, and resource management. Here’s what cloud cost optimization typically involves: * **Right-sizing resources:** Avoid overspending by adjusting the scale of resources to fit exactly what’s needed. Identifying and fixing inefficiencies: Finding areas where resources aren’t being fully utilized and making changes to save costs. * **Eliminating waste:** Just like turning off the lights when you leave a room, shutting down idle resources can save significant costs. * **Using discounts and savings programs:** Cloud providers offer discounts and programs that can provide substantial savings with a bit of planning. * **Achieving visibility with cost management and visibility tools:** Using Each application or workload in a cloud environment has its own unique demands, and these demands change as the application evolves. A big part of cloud cost optimization is understanding these requirements—balancing performance thresholds with cost efficiency to ensure resources meet organizational needs without unnecessary expense. Cloud cost optimization isn’t a one-and-done deal; it’s a continuous process, of adapting to the ever-shifting landscape of cloud pricing and service options. It’s about keeping cloud investments efficient and aligned with your business’s needs, so you’re not just saving money—you’re making your cloud work smarter for you. ## **Why is cloud cost optimization important?** Cloud cost optimization offers multifaceted benefits that impact both financial and performance aspects as well as the long-term and short-term goals of your business. ### **Achieve Detailed Cloud Cost Visibility** Having granular visibility on cloud cost is the first and foremost important step towards cloud cost optimization. Without this, tracking exact cloud spend across teams, services, or applications is challenging. The process of cloud cost optimization offers the granular insight needed to see precisely where your funds go, enabling clearer budgeting, **Actionable Advice:** Leverage **A Glimpse of CloudKeeper Lens** ### **Eliminate Unnecessary Expenditures** For many businesses, costs can spiral when resources are over-provisioned, underused, or left running after projects wrap. Effective cloud cost optimization helps identify these idle resources and eliminate redundancies, ensuring your cloud environment operates leanly without sacrificing performance. ### **Increase Profit Margins** For digital native companies, keeping cloud costs lean directly impacts gross margins, freeing up capital for growth initiatives like product innovation or expansion. With optimized cloud spend, companies gain a significant advantage—lowering operational expenses while maintaining scalability and resilience. ### **Promote a Cost-Efficient Culture** Cloud cost optimization promotes a cost-conscious approach to development, with engineers and teams aware of real-time cost impacts. For example, if any company is rapidly expanding its engineering team, unmonitored cloud usage can lead to runaway costs. By fostering cost awareness, teams are more likely to make smart choices that align with budget goals, avoid waste, and keep spending under control as new features and infrastructure are added. ### **Align Spending with Business Priorities** With cloud cost optimization, resources are allocated precisely where they bring value. By associating costs with specific teams, projects, or products, optimization ensures that investments align with strategic priorities, allowing for more dynamic, data-driven business scaling. ## **What are the Practical Challenges in Cloud Cost Optimization?** Some may think that cloud cost optimization seems simple enough—just reduce waste. But once you deep dive, and get hands-on with it you realize a few common challenges can make it harder than expected to keep those costs down. ### **Complex Billing Structures** Cloud providers like AWS, Azure, and GCP have intricate pricing models with various tiers, discounts, and usage-based fees that can be overwhelming to understand. Let’s take the example of a media company For example, a media company planning for a big live-streaming event might end up with unexpected costs due to unpredictable data transfer and scaling charges. Trying to anticipate every cost component and manage them effectively can feel like ### **Limited Visibility Across Teams** In larger organizations, different teams might launch cloud resources on their own, often without letting others know. Imagine a product team launches a new feature without informing the finance team. Costs start piling up, but no one notices until it’s too late. ### **Cloud Waste - A global challenge** Cloud waste, in simple terms, means the cloud resources that remain unused or underused. Research suggests that ### **Constantly Changing Cloud Options** Cloud platforms regularly release new services and pricing options, making it hard for companies to keep up. Keeping up with these changes can be an ongoing challenge. Learn in detail about the ## **Cloud Cost Optimization Best Practices** Now we have understood the benefits and challenges of cloud cost optimization, let’s discuss in detail ### **1. Understand Your Cloud Bill** It's important to go beyond just the total amount when reviewing your cloud bill. **Actionable Advice:** Partnering with a cloud cost optimization expert like CloudKeeper can simplify the process of analyzing your usage patterns and managing your expenses. This collaboration not only provides you with greater clarity but also offers personalized recommendations that can significantly improve your cloud efficiency. ### **2. Define key FinOps KPIs and metrics** Understanding how costs relate to your business goals is crucial. Focusing on For example, if your startup is focused on rapid customer growth, knowing the cost per feature can help determine which features are worth building. * Effective cloud cost per resource * Percentage of money saved on Reservations, Savings Plans, or Committed Use Discounts against the total cost of cloud resources * Cloud usage pattern on weekdays vs weekend * Percentage change in the cost of cloud resources over time (%) * Mean Time to Recovery (MTTR) * Percentage of infrastructure running on demand * Reverted cloud deployments * Meeting SLAs and uptime goals * Cloud optimization ratio * Cloud cost per user **Top 5 Cloud Cost Optimization Metrics (Source:****)** Always ensure to Keep the KPIs SMART (Specific, Measurable, Achievable, Relevant, and Time-Based). Frequent review and update the KPIs as your business evolves. The cloud cost optimization needs may change over time, so ensure your KPIs remain relevant and aligned with current priorities. We’ll discuss more on the changing trends in metrics in the later section. ### **3. Define Budgets for Cloud Usage** Managing cloud costs effectively starts with clear budgets for each project. Instead of picking a random number, encourage open discussions between engineering teams, product managers, and executives. This helps everyone understand the specific cost needs tied to each product or feature. For instance, if a project is part of a free trial plan versus an enterprise solution, the cost structure may vary, impacting budget requirements. A monthly cloud budget, tailored to your organization’s goals, is essential to stay on track with your spending and optimize cloud costs. For example, if you're running AWS, you can set budget alerts to notify you when spending approaches the limit. This proactive approach helps in cloud cost optimization & managing cloud resources without unexpected cost spikes. ### **4. Align budgets with business goals** Ensure that everyone understands their budgets and how they relate to overall business objectives. For instance, an engineering team might have different cost requirements for a new product versus a feature upgrade. By having open discussions with leadership, teams can align their spending with broader company goals. For example, if a company aims to enhance its user experience, the engineering team can prioritize features that align with this goal, knowing the associated costs. ### **5. Remove Unused and Idle Resources** One simple way to lower cloud costs is to regularly check for and delete unused and idle resources. For example, temporary servers and attached storage often stay active after tasks are done, adding unnecessary costs. Services like Also, review resources with low usage, like servers running at only 10% capacity, and either resize them or combine workloads. Instead of keeping idle resources "just in case," use auto-scaling and load balancing to scale up only when needed, saving money by paying only for active use. ### **6. Provide Relevant Data to the Right People** Get the right data, at the right time, for the right people. Everyone in the team needs different data, so tailor the information you share. Engineers may need detailed breakdowns of resource usage, while finance might focus on overall spending projections. By providing the right insights to the right teams, you empower them to make informed decisions. ### **7. Enable Real-Time Analytics for Immediate Action** With real-time cloud cost monitoring, you can see if a cost spike is temporary or ongoing. Imagine identifying an unexpected compute cost increase right as it happens—this lets you intervene promptly, minimizing unnecessary spending and potentially reallocating resources to where they generate better returns. ### **8. Rightsize Your Cloud Resources** Regularly review and adjust your cloud resources to fit your needs. This could involve scaling down over-provisioned servers or optimizing storage options. For instance, a company that frequently launches new features might find they need more compute power during peak times but can scale back during quieter periods. **Actionable Advice:** Leverage heatmaps to understand peak usage times and periods of underutilization. This helps you make informed decisions about establishing start and stop times to save and reduce cloud costs. **Daily Breakup Heatmap - CloudKeeper Lens** ### **9. Optimize Costs Throughout Development** Often, cost considerations come into play only after a product launch. Instead, think about cloud cost optimization at every stage of the software development lifecycle. During planning, teams can justify budgets based on historical data, while in deployment, they can quickly identify unexpected spending. Integrating cost data into design and build phases helps teams make informed architecture decisions. Monitoring costs throughout ensures that every engineering choice aligns with your financial goals. ### **10. Centralize Monitoring for a unified view** Managing data across various cloud dashboards can complicate decision-making. Instead, bring critical information into a single platform as a unified source of truth. This centralized view gives teams full visibility into costs, making it easy to focus on specific resources and better cloud cost optimization. ### **11. Embrace Cloud-Native Designs** When ## **Emerging Trends & Innovation in Cloud Cost Optimization** **Source:** As per the Everest Reports, the next set of innovation areas within FinOps is expected to be embedded automation, provision of support for hybrid cloud environments, as well as cost linkages with business value. Here’s a rundown of some of the major emerging trends and innovations in cloud cost optimization. ### **Greater Use of Automation** ### **FinOps as a Business Enabler Beyond Cloud Cost Savings** FinOps is evolving from a cost-cutting tool into a broader business enabler. By providing insights into resource usage and cost distribution, it helps companies make data-driven decisions that enhance overall efficiency and business agility, ultimately supporting cloud cost optimization goals, business growth and innovation. ### **More M &As and Investor Interest ** With the rising value of cloud cost optimization, there’s growing interest from investors and increased mergers and acquisitions (M&As) in the space. Companies offering cloud cost optimization solutions are seeing strong investment, driving more innovation and expansion in this field. ### **Growth of Internal FinOps Teams** Organizations are building and expanding their internal FinOps teams to keep up with the complexity of cloud cost optimization & scaling cloud environments. By adding specialized roles and resources, companies are better equipped to handle the growing demands of cost and resource management. ### **More Multi-Cloud and Hybrid-Cloud Vendors** As ### **AI-driven cloud cloud optimization** It is emerging as a major trend, with many organizations recognizing its significant potential. AI tools offer advanced solutions for real-time cost monitoring, automated resource allocation, and predictive analytics, allowing businesses to manage cloud expenses more effectively. ### **Rising Demand for End-to-End Cloud Cost Optimization Service Providers** The Everest Group survey found that - The current automation-led FinOps tools are falling short of expectations, prompting a demand for a more holistic approach from Cloud FinOps providers. The growing trend toward end-to-end cloud FinOps Service Providers is driven by the need for a holistic approach to cloud cost optimization. Furthermore, end-to-end Cloud Providers address this demand by offering a complete suite of services that cover every aspect of FinOps, from consultation to implementation. Understand in detail ### **Evolving Cloud Cost Optimization Metrics** Over 70% of organizations rely on the dated metric of tracking cloud cost per application. This approach overlooks crucial aspects like overprovisioned resources and continuous wastage. As the market matures, the cloud cost optimization metrics are expected to evolve. Future metrics may encompass engineering costs, relevant cost data availability, business value alignment with costs, and enhanced cost visibility granularity. ### **FinOps for Carbon Footprint Optimization** FinOps, initially focused on managing cloud expenses, is now also helping companies reduce their environmental impact. Tracking and optimizing cloud resources not only cuts costs but also lowers carbon emissions, making FinOps a key player in sustainability. ## **Understanding Cloud Cost Optimization Vendor Landscape** The * **Resellers:** Resellers help organizations cut down on cloud costs by offering discounted pricing, flexible payment options, and efficient billing management through value-added services. * **RI/SP Management Providers:** These providers enhance resource coverage through Reserved Instances (RIs) and Savings Plans (SPs), embedding automation to streamline and manage reservations. * **Consulting and Managed Service Providers (MSPs):** MSPs assist in cloud optimization by performing well-architected reviews and overseeing ongoing operations, helping to align usage with cost-effective practices and keep expenditures in check. * **Visibility and Recommendations Providers:** Visibility providers offer insights into cloud spending patterns, allocation, chargebacks, right-sizing, and tagging, providing actionable recommendations to reduce waste and optimize resources. * **End-to-End Cloud Cost Optimization Solution & Services Providers: **These providers offer comprehensive cost optimization solutions that span all aspects of cloud management, from visibility and analytics to automated cost-saving actions, enabling full-spectrum support for cloud cost control. **CloudKeeper is a prime example in this space.** **CloudKeeper: An end-to-end Cloud cost Optimization Partner** Each vendor type plays a unique role in helping organizations control cloud costs. Selecting the right mix based on specific needs can lead to efficient, sustainable cloud management and savings. As we discussed above, the research supports a growing trend of organizations prioritizing end-to-end cloud cost optimization partners. CloudKeeper stands out as an ideal choice, delivering an integrated solution through a powerful combination of advanced cloud cost platforms and hands-on optimization services, making it a top recommendation for organizations looking to maximize cloud value and long-term savings. ## **Effortless Cloud Cost Optimization With CloudKeeper** CloudKeeper is a comprehensive and certified CloudKeeper’s offerings are tailored to meet the unique needs of different customer segments and bring highly skilled and experienced cloud professionals to help you at every stage of the cloud cost optimization growth journey. **CloudKeeper AZ:** Guaranteed reduction on the entire bill with access to volume-based pricing and hassle-free management of RIs & Savings Plans, without any commitments. **CloudKeeper Auto:** Zero-touch, AI-based automated system for Reserved Instances (RI) and Savings Plans management offering RI & Savings Plans pricing for on-demand instances and a buy-back guarantee of unused RIs & SPs. **CloudKeeper EDP+:** Maximizes your AWS EDP benefits with additional discounts, lower annual commitments, and discounted prices on AWS Support. **CloudKeeper Lens:** A cloud cost visibility & analytics platform that provides insights to track, analyze, and optimize your cloud usage. **CloudKeeper Tuner:** An Automated AWS Usage Optimization & Recommendation Platform that optimizes the performance of your workloads on 50+ AWS services thereby reducing the cost of your infrastructure without compromising on performance. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Chief Operating Officer Aman spearheads business operations, strategic execution, and cross-functional alignment to drive sustainable growth. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 12 12 Table of Contents Imagine a scenario where your cloud expenses are not a burden but a strategic asset, where every dollar spent fuels innovation and growth. Cloud cost optimization is the key to unlocking this reality, transforming cloud spending from a source of anxiety into a driver of long-term business success. As organizations increasingly embrace the cloud for its agility, scalability, and cost-efficiency, they find themselves facing a paradox: while the cloud offers immense potential for savings, it also harbors hidden costs that can quickly spiral out of control if left unmonitored. Moreover, research reveals that a whopping 32% of cloud spend gets wasted by organizations. Together, let’s dive into detail about cloud cost optimization, the strategies, and best practices to get really good at managing cloud costs. ## **What is Cloud Cost Optimization?** Cloud cost optimization is an ongoing and strategic process to manage and control the expenses of cloud computing services while maintaining optimal performance and efficiency. This intricate process goes beyond mere At its core, cloud cost optimization involves: * Right-sizing your cloud computing resources. * Identifying inefficiencies and optimizing resource allocation. * Eliminating waste/unnecessary cloud expenditure. * Leveraging discounts provided by cloud providers to acquire more resources cost-effectively. * Gaining better cloud visibility with the help of cloud cost management tools. There's a common misconception that merely reducing cloud expenses equals optimization. In reality, the ultimate objective of cloud cost optimization is to utilize resources efficiently, striking a balance between cost, performance, security, and availability. This, in turn, supports funding for growth-oriented initiatives for organizations, like rolling out improved feature updates. ## **Why is cloud cost optimization a non-negotiable for your business?** Did you know that cloud cost optimization is the top cloud initiative for the seventh year running? **The multifaceted benefits of Cloud Cost Optimization** ### **Financial Benefits of Cloud Cost Optimization** **Cloud Cost Reduction** Cost optimization in the cloud acts as a guiding light for organizations, offering strategies such as #### **Cloud Budget Predictability** Cloud cost optimization empowers better budget planning by providing a deep **A screenshot from CloudKeeper Lens** #### **Cost Governance and Accountability** Cloud cost governance and accountability are crucial parts of cloud cost optimization. This enables creating a structure, defining budgets and allocation policies, employing cost management tools, assigning cost ownership, and efficient management, monitoring, and transparency of cloud expenses. #### **Cost-Conscious Culture** Cloud cost optimization involves fostering an organizational mindset where every team member, from developers to operations, is aware of and considers the financial implications of their decisions. In a cost-conscious culture, everyone collaboratively works towards optimizing expenses and ensuring financial sustainability. _**Actionable Advice:** Empower your team with the knowledge and skills necessary for making cost-effective decisions. Provide training on cloud pricing models, __._ ### **Performance Benefits of Cloud Cost Optimization** **Optimum Cloud Resource Utilization** Cloud cost optimization makes sure you use cloud resources just right by adjusting them to match what you actually need. The strategies like automation and load balancing help distribute resources efficiently as the workload changes. #### **Data-driven Decision Making** Cloud cost optimization thrives on data-driven insights. By Picture a scenario where a business had to decide whether to invest in scaling up infrastructure or optimizing existing cloud resources. Cloud cost optimization data guides them to make the right decision. #### **Scalability and Flexibility** Cloud cost optimization contributes significantly to scalability and flexibility by allowing businesses to align their resource allocation with actual demand, thereby enhancing operational efficiency and cloud cost-effectiveness. Imagine an e-commerce giant like Amazon, whose online sales surge during the holiday season. Their cloud infrastructure, the backbone of their operations, must scale up rapidly to accommodate the influx of customers. However, maintaining that peak capacity throughout the year leads to exorbitant costs. Through cloud cost optimization they can dynamically scale up their resources to handle the increased demand, ensuring smooth operations and customer satisfaction. Importantly, during less busy times, they can scale down to avoid overpaying for resources they don't need, demonstrating the flexibility and cost-efficiency that cloud cost optimization provides. #### **Better Cloud Performance** Inefficient resource allocation often leads to slow application performance. Through cloud cost optimization, the business not only saved costs but also improved the overall user experience, enhancing customer satisfaction. #### **Competitive Advantage** Cloud cost optimization provides a competitive advantage by directing funds strategically toward innovation, customer experience, or other growth areas. Let’s take the example of two businesses in the same industry—one investing in cloud cost optimization and the other overspending on unused resources. The former had the financial flexibility to invest in new technologies and customer-focused initiatives, gaining a competitive edge in the market. ## **Cloud Cost Optimization Best Practices** Below are some must-do cloud cost optimization best practices that every organization should prioritize: ### **1. Gain insights into your cloud usage** The foundation of cloud cost optimization lies in gaining a comprehensive understanding of an organization's usage patterns and seasonal fluctuations. It also makes forecasting cloud spend optimization becomes a more manageable task. An effective strategy involves ### **2. Comprehend your cloud bill** Make sure you understand your cloud bill beyond just the total amount. Effective cloud cost optimization necessitates a deeper understanding of the bill's components and overall cloud pricing structure. This helps you figure out where your money is going and make informed decisions to reduce cloud costs effectively. _**Actionable Advice:** Joining forces with a __eases the task of understanding your usage patterns and managing your bill. This collaboration not only brings peace of mind but also unlocks tailored benefits like personalized recommendations, enhancing your overall cloud efficiency._ ### **3. Right-Size your cloud resources** Right-sizing refers to tailoring your cloud computing resources to match the workload requirements, ensuring that you have neither too little nor too much capacity. By right-sizing, organizations can optimize performance, enhance reliability, reduce overhead costs, and improve the overall end-user experience. **Below are some proactive strategies for right-sizing:** **a. Performance Monitoring:** Implementing robust performance monitoring tools and techniques allows businesses to gain real-time insights into their computing infrastructure. By analyzing usage patterns, peak loads, and resource demands, organizations can proactively identify bottlenecks and make informed decisions about rightsizing. **b. Capacity Planning:** Businesses must go beyond mere reactive resource management and engage in proactive capacity planning. By forecasting future demands, businesses can efficiently align their **c. Automated Resource Scaling:** Leveraging automation, businesses can dynamically scale their resources based on actual demand. This proactive approach enables efficient utilization of resources during peak periods while scaling down during periods of lower demand, leading to cloud cost savings and improved performance. **d. Load Balancing:** Distributing workloads across multiple resources can help optimize utilization and prevent overutilization of specific resources. This strategy enhances performance, prevents downtime, and ensures high availability, making rightsizing more effective. **e. Continuous Evaluation and Optimization:** Rightsizing is not a one-time process; it requires ongoing evaluation and optimization. By regularly assessing their computing resources against actual requirements, organizations can remain agile and responsive to changing business needs. _**Actionable Advice:** Leverage heatmaps to understand peak usage times and periods of underutilization. This helps you make informed decisions about establishing start and stop times to save and reduce cloud costs._ **A screenshot from CloudKeeper Lens** ### **4. Monitor and Correct cloud cost anomalies** Establishing a strong monitoring system that goes beyond conventional dashboards and manual analytics is crucial for effective cloud cost optimization. Cloud cost optimization tools can further enhance an organization's ability to detect and act on cloud cost anomalies. Once anomalies are detected, the next crucial step is correcting them promptly. Additionally, implementing automated cost control measures, such as setting spending limits, budgets and alters, tagging or utilizing instance scheduling, can help prevent future anomalies from occurring. ### **5. Identify Unused and Unattached Cloud Resources** As cloud systems get bigger and more complicated, there's a higher chance of having resources that are not being used, unattached, or just sitting idle. Implementing best practices such as regular resource audits, ### **6. Focus on Cloud Storage Optimization** Cloud storage offers a variety of options, each tailored to specific data types and usage patterns. _**Actionable Advice:** Schedule regular storage audits to identify and remove outdated or unused data, including obsolete backups, or old data that no longer serve any business purpose. _ ### **7. Limit Data Transfer charges** ### **8. Opt for Reserved Instances and Spot Instances** Reserved Instances offer businesses the opportunity to maximize cost savings by providing significant discounts on computing resources compared to on-demand Instances. This makes Reserved Instances an ideal choice for workloads with consistent demand or steady-state applications. On the other hand, Spot Instances offers an innovative way to dramatically cut cloud computing costs by allowing organizations to bid on surplus EC2 capacity. While Spot Instances may not provide guaranteed availability, they offer significant discounts of up to 90% compared to On-Demand Instances. _Actionable Advice: If you would like to enjoy the flexibility of on-demand EC2 & RDS instances at AWS Reserved Instances pricing, all without any commitments or lock-ins explore _ _._ ### **9. Opt for Enterprise Discounts** By opting for an enterprise discount for example AWS Enterprise Discount Program, businesses can achieve substantial cost optimization. These discounts typically offer tiered pricing models or volume discounts, enabling organizations to _**Actionable Advice:** You can unlock the maximum potential of AWS EDP by availing additional discounts, lower annual commitments, and discounted prices on AWS support only with __._ ## **Let’s optimize tomorrow's cloud costs today** As we conclude, let's remember cloud cost optimization is not a mere checklist; it's a mindset, a personalized journey for each company. Just as a skilled chess player carefully evaluates and strategizes their every move, cloud cost optimization demands a similar approach. It's about making informed decisions that align with your organization's goals, not just about cutting costs blindly. It's a collective responsibility, involving not just IT but the entire organization. Embracing the cloud cost optimization best practices, keep playing the game wisely, make strategic moves, and see your cloud journey be both efficient and cost-effective. Happy cloud cost optimization! ## **Would you like an extended team to take up your burden of Cloud Cost Optimization at zero cost?** Well, it is the real deal! Imagine saving not just money but time, resources, and energy too. This is where CloudKeeper comes in. Trusted by 300+ global businesses CloudKeeper, is a multi-cloud cost optimization partner that provides you with **the complete package to ace your cloud cost optimization journey at no cost from your pocket.** _**Intrigued to discover more?**__**today!**_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents A 2022 research by Flexera involving over 750 global cloud decision-makers has revealed that an estimated 32% of cloud spend is wasted by organizations on average. That’s more than a third of your cloud investments going down the drain. Alarming, isn’t it? No wonder we witnessed a 75% increase in Cloud FinOps initiatives across organizations globally. ( Most of the time, in-house cloud personnel could handle cloud FinOps tasks only as a part of another, larger job function. So, a dedicated FinOps partner becomes a smarter choice for organizations. But, with a broad spectrum of FinOps solutions out there in the market, which one should organizations trust with the responsibility of governing and optimizing their cloud infrastructure? If you are at a similar crossroads, this blog might help you gain a better understanding of the vendor segments and make an informed decision that suits your needs. The Cloud FinOps lifecycle involves three phases - Inform, Optimize and Operate. This blog classifies the FinOps vendor landscape based on their alignment with one or more of these phases. To read more on further classifications, check out this **Fig: Cloud FinOps Vendors’ Landscape** ## **Cost Analytics Platforms** Cost optimization initiatives need readily-available information on resource utilization, cost breakdowns, usage forecasts and so on. This helps identify provisioning issues, manage idle resources and ensure cost-effective cloud operations. FinOps vendors who address this real-time cloud infrastructure visibility are the Cost Analytics Platforms or Cloud Financial Management (CFM) Solutions. Catering to the **Inform phase** of the FinOps lifecycle, CFMs provide a reporting mechanism on cloud usage, spend patterns, budget coverage and even discounts and chargebacks. Most vendors also provide security and data privacy-related insights, lending an additional support to the customer business functions. However, please note that these platforms might need access permissions into the customer’s cloud setup or the cloud provider accounts. CFMs provide **detailed and elaborate cost insights** , helping organizations in identifying costly virtual machines, zombie/idle resources, and even data transfer costs. Additionally, with the help of various **cost thresholds or percentage deviation alerts** , organizations can keep track of their cloud budgets and commitments and prevent the costs from spiraling out of control. They also help in allocating cloud spend and resources across the organization by leveraging **AI-based resource tagging tools**. These tools, based on a custom tagging strategy, bring better cost visibility and ownership across business units, accounts, etc. **Cloudability, Densify and CloudHealth** are some of the vendors who fall into this category. ## **Savings / RI Management Tools** As the organizations scale up their user base, changes in their cloud usage volumes could become quite dramatic from time to time, leading to large gaps in cloud resource provisioning. Mending these gaps with On-demand instances, however, is a surefire way to have cloud cost overruns and a deeper dent in cloud budgets. Commitment-based discounts like AWS Reserved Instances, and Savings Plans, can help manage this to some extent. But without proper resource planning, forecasting and rightsizing in place, organizations are still left with under-provisioned or over-provisioned reservations. Getting trapped in this vicious cycle of cloud wastage and unbudgeted expenses is a story that most cloud engineers are familiar with. This is where the Savings / Reserved Instances Management Platforms come into play. Mostly driven by **AI-powered Automation Engines** , these vendors help organizations by performing resource provisioning and workload management on their behalf. These platforms use **real-time usage data and predictive analytics to track and forecast application needs**. Based upon this analysis and projections, these tools **buy/sell reservations dynamically** in the AWS Secondary Market, or sometimes within their own customer network, bringing in substantial cloud cost control. Majorly impacting the **Optimize Phase** of the FinOps lifecycle, these platforms usually offer very **high savings potential, in the range of 50% - 60%**. The On-Demand instances provisioned by customers are usually billed as per 1-Year or 3-Year RI pricing. Customers benefit from the vendors’ volume and committed term discounts while maintaining complete flexibility. Vendors under this category mostly support Standard Compute Reservations only, like EC2 instances, with an exception of a few who support Savings Plans, EBS Storage Volumes, etc. But none of the vendors offer guaranteed savings. However, like Cost Analytics Platforms, RI Management tools also require certain access privileges to the customer’s cloud setup. **ProsperOps, Zesty, Spot.io, nOps and Cloudwiry** are some of the vendors that fall into this category. ## **Resellers & Managed Service Providers** At times, organizations require a third party to manage their entire Cloud and IT Infrastructure and end-user systems. By **delegating cloud operations** to an expert cloud partner, companies can focus on improving their business without worrying about extended system downtimes or service interruptions. Driving the **Operate phase** of the FinOps lifecycle, MSPs offer a broad range of cloud optimization services like cost management, budgeting and reporting, expert guidance and architectural reviews, 24x7 support, and so on. This segment also includes **Resellers** , who are able to provide discounts to the customers because of the volume and scale they manage. They mostly do 1-year or 3-year RIs with Cloud platforms and are able to pass on some percentage of savings as guaranteed discounts. MSPs make sure that all the applications, databases and related frameworks get to leverage enough cloud resources for optimal performance, while reinforcing their security and data protection standards. They also provide dashboarding, analytics, right-sizing, and right-costing services to their clients which would help them reduce their overall cloud spending. Most of these vendors possess multiple competencies, like the AWS Well-Architected Review, DevOps, Cloud Migration and more. They can perform **periodic architectural reviews** and help companies enhance their overall cloud strategy, thus, helping organizations in **‘building better’ rather than ‘buying better’**. **Rackspace, Intervision, Bespin Global and NTT Data** are some of the prominent players in the category. ## **A One-Stop End-to-End Cloud FinOps Solution - Too Much To Ask For?** Could we find a FinOps partner who helps **manage reservations and save big** on cloud bills, offers **infrastructure reviews and guidance** and also provides **state-of-the-art cloud analytics** software for in-depth cost insights? While most vendors focus on a specific domain and a niche set of practices, there are a select few who have proven their capabilities and scale in all the three vendor segments. These **Holistic FinOps Service Providers** offer an entire spectrum of FinOps services to their customers across **all the three phases of the FinOps lifecycle**. They offer superior savings in comparison to other vendors, by leveraging exclusive relationships with hyper-scalers, large volume reservations and a vast client base. With a team of certified **CloudKeeper** is a prime example and one of the highest-rated service providers in this space. CloudKeeper has two major offerings, each of which can be mapped to different vendor spaces. **CloudKeeper Auto** is an **Automated Savings / RI Management Platform** that dynamically optimizes AWS Resource Utilization and Workloads. With the help of an AI engine, the platform analyzes the organization’s usage patterns and provisions resources accordingly. It also uses the AWS Secondary Market and the CloudKeeper Client Network for the Buying and Selling of AWS Reservations, thereby offering a **superior savings potential of up to 50% - 60%**. **CloudKeeper AZ** , on the other hand, is a **comprehensive Cloud FinOps Solution** that caters to the entire FinOps Lifecycle by offering Savings, Software and Services. The solution offers **Guaranteed Savings** for its customers on their entire AWS bills, right from Day 1. CloudKeeper is also an AWS Premier Partner and offers **periodic reviews and guidance from AWS Certified Cloud Experts** which could bring about significant improvements to the customer’s cloud infrastructure. CloudKeeper AZ also offers **complimentary access to its proprietary Cloud Cost Analytics** platform, which gives resource-level cloud usage data and actionable cost insights, with no additional permissions or privileges. The platform is also available as a standalone offering from CloudKeeper. ## **Time to Introspect** The FinOps vendor marketplace is currently witnessing a paradigm shift. The vendors are introducing more mature solutions, improving their understanding of unit cost metrics, and leveraging AI and Machine Learning more often. With years of experience in the FinOps industry, they now possess a better knowledge of the cloud cost challenges and could help immensely in redefining It's upon the organization to introspect on their needs and aspirations and choose the right FinOps partner, who will help them accomplish most of their Cloud FinOps goals, maximize their business value and benefit each and every stakeholder involved. We’d love to show you how CloudKeeper makes your Cloud Cost Optimization efforts go that extra mile. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents Congratulations! You’ve successfully built your product on the cloud! Your innovative idea has the potential to disrupt the industry and create a significant impact. Your offerings will undoubtedly solve a critical industry problem and as the demand for your startup rises, your cloud consumption will imminently rise. Among all the hassle, it is easy to lose control of your cloud spending and before you know it, you’ve exhausted your cloud budgets. You were so close to making a huge impact and yet so far, due to improper Cloud FinOps planning and ## **Common Mistakes and Challenges** You need to know the common mistakes startups make & **1. Lack of Monitoring and Optimization:** You must understand that Cloud cost optimization is a continuous process. This means you must closely monitor your cloud consumption using the right metrics to make sure you’re not leaking dollars on unused resources. Regular reporting will create a culture of cloud cost visibility and accountability within your organization and will hence empower you with actionable insights to optimize your cloud usage. **2. Not Using Reserved Instances or Savings Plans:** Cloud providers like AWS, Azure, and GCP offer commitment & saving plans allowing users to book resources for a period of time (usually 1 or 3 years). In exchange for your commitment, the cloud providers offer significant discounts as compared to the on-demand prices which can create a significant impact on your cloud cost savings. If your cloud consumption is high and you foresee that it’ll stay the same in the future, you must look into RI and savings plans offered by your cloud provider. **3. Over or under-commitment of resources:** It is important for you to accurately judge and predict your business operations and match your consumption with commitments. You could also leverage third-party reserved instance management platforms like CloudKeeper Auto which can **4. Ignoring Auto Scaling:** Startups often ignore auto-scaling policies which lead to underutilized resources during low demand and increased costs due to on-demand charges during high demand. **Time-Based Auto Scaling of Instances** **5. Failure to Set Budgets and Alerts:** It’s easy for costs to overrun when you’re in a growth state. Implementing Cloud Cost Optimization strategies like Setting budgets and alerts is important to notify the right stakeholders if you run over your periodic limits. It’ll help you maintain control of your cloud resources and costs alike. **6. Overlooking Data Transfer Costs:** ## **Cloud Cost Optimization Best Practices** **1. Usage Optimization:** You must **2. Data Optimization:** Make sure to appropriately select the storage class based on the access frequency and latency requirements of your data. For example - Standard Storage is ideal for frequently accessed data, such as live website content, mobile and gaming applications, and big data analytics since it offers low-latency and high-throughput performance. On the other hand, Standard S3 Infrequent Access is suitable for infrequently accessed data that can be stored for long periods. Choosing the right class can significantly help you with cloud cost optimization. **3. Spot Instances and Preemptible VMs:** We’ve already talked about how RIs and savings plans can be a great way to save costs on the cloud. Similarly, utilizing **4. Monitoring and Benchmarking:** As discussed earlier, **5. Leverage Cost Management Tools:** There exist numerous provider-specific cloud cost management tools like AWS Cost Explorer, Azure Cost Management, Google Cloud Billing, or third-party cloud cost visibility tools like As a startup, effectively allocating your cloud costs is critical for the smooth functioning of your business. By leveraging resource tagging features, you can create a culture of cloud cost visibility & accountability within your organization from the start. By requesting granular billing data and establishing cross-functional collaboration, you can make better decisions regarding resource budgeting and forecasting as well. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents In today’s fast-paced digital landscape, cloud computing has become a cornerstone of modern IT infrastructure. Amazon Web Services (AWS) is one of the most popular cloud platforms, offering a vast array of services that enable organizations to build, deploy, and scale applications quickly. However, with great power comes great responsibility, particularly when it comes to managing expenses. Without a well-defined strategy, AWS costs can spiral out of control. In this blog, we’ll explore key cloud cost optimization strategies in AWS DevOps and how tools like CloudKeeper can further enhance your cost-saving efforts. ## 1. Right-Sizing Resources One of the most effective ways to optimize costs is by right-sizing your resources. This involves analyzing your current infrastructure with tools such as AWS Cost Explorer and identifying instances that are over-provisioned or underutilized. By resizing instances to better match actual usage, you can significantly reduce costs. ### **How to Implement:** * **Use AWS Trusted Advisor:** It provides * **Leverage Auto Scaling:** Set up Auto Scaling groups to dynamically adjust the number of running instances based on demand. ## 2. Leverage Spot Instances AWS Spot Instances allow you to bid on unused EC2 capacity at a fraction of the regular on-demand price. While Spot Instances can be interrupted by AWS, they are ideal for fault-tolerant workloads that can withstand interruptions, such as batch processing, big data analysis, or stateless applications. ### **How to Implement:** * **Integrate with Auto Scaling:** Use Spot Instances * **Use Spot Fleet:** Create a Spot Fleet to automatically request Spot Instances with the lowest price. ## 3. Implement Savings Plans and Reserved Instances AWS offers ### **How to Implement:** * **Analyze Usage Patterns:** Use AWS Cost Explorer to analyze historical usage and forecast future demand. * **Mix and Match:** Combine Savings Plans with Reserved Instances to cover predictable workloads while using on-demand or Spot Instances for variable demand. ## 4. Optimize Storage Costs Storage can quickly become a significant barrier to cloud cost optimization in AWS if not properly managed. ### **How to Implement:** * **Use S3 Intelligent Tiering:** Automatically move data between two access tiers when access patterns change, optimizing storage costs without impacting performance. * **Archive Data with S3 Glacier:** For long-term storage of infrequently accessed data, use S3 Glacier or S3 Glacier Deep Archive, which offers lower storage costs. ## 5. Monitor and Manage Costs Continuous monitoring and management are crucial for keeping AWS costs under control. By setting up cost alerts and using monitoring tools, you can quickly identify cost anomalies and take corrective actions. ### **How to Implement:** * **Use AWS Cost Explorer and Budgets:** Set up custom cost and usage alerts to stay informed about spending trends. * **Enable AWS CloudWatch:** ## How CloudKeeper Enhances Cloud Cost Optimization While the strategies mentioned above are effective, managing them manually can be time-consuming and prone to error. This is where CloudKeeper comes in as a game-changer for AWS DevOps teams. **CloudKeeper is your comprehensive cloud cost optimization partner** that combines the power of group buying and resource provisioning strategies, unlimited cloud consulting and support, and an enhanced visibility and analytics platform to reduce your cloud cost and help you maximize the value from AWS. ### **Key Benefits of Using CloudKeeper** * **Automated Resource Cleanup:** CloudKeeper * **Customizable Policies:** You can define policies that dictate which resources should be cleaned up and under what conditions, providing you with control and flexibility. * **Enhanced Visibility and Analytics:** CloudKeeper offers * **Unlimited Cloud Consulting and Support:** Cloudkeeper’s team of experts is available to provide ongoing cloud consulting and support, ensuring you make informed decisions that align with your business goals. * **Group Buying and Resource Provisioning:** By leveraging group buying power, CloudKeeper helps you secure better rates for cloud services, further driving down costs while ensuring you have the resources you need. ## Conclusion Adopting these strategies and tools not only helps in reducing costs but also contributes to building a more efficient and resilient cloud infrastructure. Start optimizing today and make the most out of your AWS investment! Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Sushil is a passionate DevOps Expert skilled in configuring and automating CI/CD pipelines. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents As enterprise cloud adoption accelerates, optimizing cloud spending has become a top priority for many organizations. Yet, it’s shocking how much waste is incurred, especially with Reserved Instances (RIs) and other discount programs. AWS offers various ways for cloud cost management, but are you leveraging them effectively? A recent FinOps survey revealed that nearly one-third of cloud investments go to waste, and most organizations exceed their budget by at least 13%. If you are responsible for cloud cost optimization and facing discount program wastage as high as $5,000 per day, it's time to take immediate action. This blog will shed light on the key reasons behind cloud inefficiencies and offer actionable steps to help you regain control of your cloud spend, with a particular focus on addressing Reserved Instance (RI) & Savings Plan wastage. ## Are You Really Losing Money to AWS Cloud Wastage? Here's How to Assess Your Wastage Before diving into cloud cost optimization strategies, it’s important to assess your wastage. This can be done by using AWS’s comprehensive cloud cost management tools, which provide detailed insights into your cloud spending patterns and identify inefficiencies. Here's how you can get started. * ### **Leveraging AWS Cost Explorer & Utilization Report ** AWS Cost Explorer is an essential tool for analyzing your cloud spending. It provides interactive visuals that make it easy to track where your money is going and identify areas of potential wastage, particularly when it comes to Reserved Instances (RIs) and Savings Plans. For example, you can analyze your costs on a month-to-month basis by grouping the data by month and charge type, specifically focusing on charges related to RIs and Savings Plans such as Savings Plan Covered Usage, Savings Plan Recurring Fee, and Recurring Reservation Fee. This method helps you New Cost and Usage report from Once you've identified a cost anomaly in AWS Cost Explorer, you can dive deeper to determine which Reserved Instances (RIs) are contributing the most to the wastage. To do this, use the Utilization Report under the Reservations section of AWS Billing and Console. This report is a critical part of AWS RI management as it provides detailed insights into RI usage, helping you pinpoint underutilized instances that are driving unnecessary costs. **Reservation Utilization Graph from AWS RI Utilization Report under Billing & Cost Management** The graph above illustrates the utilization percentage, with the ideal target being 100%. If there's a sudden drop or decrease, it can be easily spotted in the graph. To further investigate which individual RIs are contributing most to the wastage, refer to the table in the Utilization Report. By sorting the list by Net Savings in descending order, you can quickly identify the RIs where you're losing the most money. **Reservations Utilization Breakdown from AWS RI Utilization Report under Billing & Cost Management** For more detailed information about an RI, click on the Subscription ID to view specifics such as the instance type, effective hourly rate, count, region, and more. This will provide a comprehensive overview, helping you fully understand the source of RI wastage. **Reservations Utilization Breakdown from AWS RI Utilization Report under Billing & Cost Management** Similarly, you can refer to the Utilization Report for Savings Plans to dive deeper into their usage and identify any inefficiencies or wastage. **Savings Plan Utilisation Graph from AWS Savings Plan Report under Billing & Cost Management** * ### **Leveraging AWS Cost and Usage Dashboards (CUDOS) and Cost Intelligence Dashboards** For a more comprehensive and tailored analysis, the **Cudos Executive: RI/SP Summary Dashboard from AWS** By using these tools, you can generate actionable insights that help you spot wastage and identify areas for improvement in real time. ## **Probable reasons you might be losing money on AWS RI/Savings Plan?** If you are experiencing wastage on this scale, the root cause often includes: * **Underutilized RIs and Savings Plans:** Misconfigurations or overcommitment lead to instances sitting idle, causing unnecessary costs. * **Inflexibility of Standard RIs:** Locked into long-term commitments with instances that no longer fit your usage patterns. * **Inability to Leverage Discounts:** High spend regions (exceeding $500K) are ineligible for further RI discounts, pushing organizations toward more flexible but complex pricing models. Without additional discounts, the fixed pricing of RIs might not match your evolving usage patterns, leading to underutilized capacity and wasted costs. ## **Strategies to Reclaim and Optimize Your Cloud Spending** Once wastage has been identified, it’s time to take action. Here are a few strategies you can implement for effective cloud cost optimization: * ### **Collaborate with Your Team to Enhance Resource Utilization** Work closely with your product owners, engineering teams, and FinOps practitioners to identify inefficiencies and develop targeted solutions. Initiatives such as a * ### **Convert Underutilized Convertible RIs** If you have Convertible RIs that aren’t being fully utilized, it’s possible to convert them to instance types or sizes that better match your current usage patterns. AWS allows you to exchange a Convertible RI at any time during the term for another Convertible RI, provided that the new RI: * Has an equal or higher total cost over the remaining term compared to the existing RI. * Belongs to the same scope (either regional or zonal), ensuring that the coverage remains consistent. If the RI for m4.large is underutilized, you can convert it to another instance family with consistent and significant On-Demand usage, enabling better coverage and For more details, visit the AWS documentation * ### **Sell EC2 Standard RIs on the Marketplace** If EC2 Standard RIs are underutilized, consider listing them on the AWS RI Marketplace. Though you won’t be able to list discounted Standard RIs (due to AWS policies), selling your unused capacity can **Reservations Utilization Breakdown from AWS RI Utilization Report under Billing & Cost Management** For instance, if the RIs highlighted in the utilization report are from older generations like r4.large, r5.large and contributing to significant wastage, you can collaborate with your team to list those RIs on the AWS marketplace, if you've already migrated to the latest generation. This can help reduce unnecessary costs and optimize your cloud resources. Note: Amazon Web Services India Private Limited (AWS India) customers can't sell Reserved Instances in the Reserved Instance Marketplace. For more details on selling RIs visit the * ### **Reduce Convertible RI Commitments** You can also minimize waste by adjusting the commitment levels for your Convertible RIs, particularly if your cloud usage fluctuates. By reducing the commitment of your Convertible RIs, you can transition those workloads to be covered by a Compute Savings Plan or EC2 Instance Savings Plan, further aiding in cloud cost optimization. For example, if you had a high commitment to m5.large Convertible RIs but now need to shift to different instance types, you can lower that commitment and let the Savings Plan automatically apply across various instance families and regions. For more details visit the ### **Reach Out to AWS Support for Assistance** AWS offers By implementing proactive cloud cost management strategies—utilizing AWS tools, launching organization-wide initiatives, optimizing RI commitments, and seeking AWS Support when needed—you can significantly reduce daily cloud spend. For enterprises facing major wastage, especially those losing $5K or more per day, adopting these practices is critical. Don’t let your cloud investment slip away—optimize your Reserved Instances, Savings Plans, and overall cloud cost management with CloudKeeper today. Did you know that you can eliminate the hassle of AWS RI management, buy-back guarantee on unused Reserved Instances, access on-demand EC2 resources at three-year RI pricing, and much more - all with no commitment or cost involved? Sounds interesting? Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Product Manager Atiya brings over 5 years of expertise in product management, specializing in Data & Analytics, AI, and Machine Learning. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents When making the shift to Docker orchestration as part of your cloud cost optimization strategy, it's important to be aware of common missteps that can arise. By recognizing and understanding these potential pitfalls, you can take proactive measures to steer clear of them and ensure a successful cloud migration that aligns with your cost optimization goals. Here are some of these mistakes that organizations should be aware of and aim to avoid. **Over-Provisioning Resources:** * One of the key benefits of container orchestration is efficient resource utilization. However, over-provisioning resources (CPU, memory, etc.) for containers can lead to higher costs. * Always monitor resource utilization and adjust container resource requests and limits accordingly, **Lack of Auto-Scaling Policies:** * Failing to set up * **Using Persistent Volumes Inefficiently:** * Utilizing persistent volumes excessively or not reclaiming unused volumes can lead to unnecessary storage costs. * Implement proper data lifecycle management and delete unused volumes. **Not Monitoring Costs:** * Failing to monitor and analyze the costs of container orchestration can result in cost overruns. * Implement cloud cost management tools to track spending and identify areas for optimization. **Ignoring Container Images:** * Large container images with unnecessary dependencies can increase storage costs. * **Complex Network Architectures:** * Overly complex network configurations can lead to difficulties in troubleshooting and inefficiencies. * Keep network configurations simple and well-organized to avoid unnecessary resource consumption. **Overuse of Persistent Storage:** * Relying too heavily on persistent storage for stateless services can lead to increased storage costs. * The use of ephemeral storage or in-memory caching is one of the lesser-known docker best practices to reduce storage costs. **Not Leveraging Spot Instances or Preemptible VMs:** * Some orchestration platforms allow the use of lower-cost spot instances or preemptible VMs. * Spot instances are one of the most used features for AWS cost optimization. Consider using these instances for non-critical workloads that can tolerate interruptions. **Poorly Designed Application Architecture:** * Migrating to container orchestration without * Design applications with microservices principles in mind to take full advantage of containerization benefits and streamline resource scaling. **Ignoring Inactive Containers:** * Leaving inactive containers running can accumulate costs. * Implement container lifecycle policies in your cloud optimization strategy to automatically remove or scale down containers that are no longer needed. **Lack of Tagging and Resource Labeling:** * Without proper tagging and labeling of resources, it becomes challenging to track and allocate costs accurately. * The use of ## **Conclusion:** The process of migrating to Docker orchestration for the purpose of cloud optimization demands a vigilant approach. Recognizing the common mistakes that can occur during this transition is the first step towards sidestepping some of the potential pitfalls. By incorporating this awareness into your strategy, you can navigate the path with confidence, ensuring a successful cloud migration that not only optimizes costs but also fosters operational efficiency and sustainability. _With certified cloud experts, resource-level cost insights, and_ _Witness how we could transform your cloud strategy, with a_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 40 40 Table of Contents Did you know that a This highlights a gap in the maturity of cloud operating models and strategies being put into action. To counter this, ## **Understanding Cloud Cost Savings in Cloud Computing** The potential for cloud cost savings is significant. Some studies suggest that businesses can reduce their cloud spending by 20-30% or more just by applying effective cloud cost optimization practices. There could be various factors impacting your cloud cost savings. Some of the major ones are: * **Cloud Usage Patterns:** Cloud costs can vary depending on how and when services are used. Costs can rise during peak usage if resources aren’t scaled down when demand is lower. The type of workload—whether it needs a lot of computing power, memory, or network bandwidth—also affects cloud savings. * **Cloud Pricing Models:** Cloud providers offer various pricing options, like pay-as-you-go, reserved instances, and spot pricing. It’s important to choose the right pricing model based on your needs and usage, which can make a big difference in your overall costs. * **Cloud Service Models:** The choice of cloud service model—Infrastructure as a Service (IaaS), Platform as a Service (PaaS), or Software as a Service (SaaS)—affects your costs. Each model offers different levels of control and management. * **Resource Management:** You need to be proactive in regularly assessing and adjusting your cloud resources to ensure they meet current needs without excess. Right-sizing, optimizing configurations, removing unused services, and adopting newer, more cost-effective technologies are some of the ways that help in resource optimization, ultimately resulting in cloud savings. This blog deep dives into instant cloud cost savings hacks as well as some proven long-term cloud cost savings strategies. We will explore practical approaches to help you achieve these savings and ensure you get the most value from your cloud investments. ## Cost reduction best practices for instant cloud cost savings (simple fixes) Companies can see immediate cloud savings by implementing some simple fixes. While some optimizations might require significant updates that take time, there are plenty of simple steps you can take today for quick cloud cost savings. Let’s take a look at them. ### **Review Resource Utilization** **1. Analyze Usage:** Use monitoring tools like Amazon CloudWatch, Azure Monitor, or GCP Cloud Monitoring to review the usage of production and non-production resources from the past month. Categorize resources as Idle, Underutilized, or Optimally Utilized. **2. Identify Idle Resources:** Focus on metrics such as CPU and memory utilization, or for specific resources like RDS instances, check database connections. Examples of idle resources include: * EBS volumes attached to stopped instances. * Databases (RDS/RedShift, Azure SQL, Google Cloud SQL) with zero active connections. * Load balancers with fewer than two active servers. * Compute instances (EC2, Azure VMs, Google Compute Engine) with low network utilization ### **Downgrade Underutilized Instances** Often, cloud compute instances run at just 10-20% capacity, which wastes the flexibility of the cloud. For optimal cloud savings, aim to use your resources at least 50-60% of the time. If your instances are consistently underused, consider downgrading them. Here’s how: * **Start Gradually:** If both CPU and memory usage are low, consider switching to a lower configuration. Be cautious—make changes gradually and monitor performance closely. * **Switch Instance Types:** If only one of the CPU and Memory metrics is low, you might switch to a different instance family. * **Combine Workloads:** If downgrading seems risky, try running multiple apps or databases on a single server. Containerization can help with this. ### **Always Use the Latest Generation Instances** For instances running at around 60% or more utilization, it’s wise to use the latest generation available for AWS, Azure & GCP. These instances are generally cheaper. Replacing older instances with newer ones can have a quick and major impact on cloud savings. ### **Continuously Review & Remove Obsolete Snapshots** Snapshots capture a read-only view of your data for backup, but their size grows as the database changes. This leads to increasing storage costs, which can sometimes exceed the cost of compute instances. Regularly review and delete outdated snapshots to avoid unnecessary expenses. Even a 10% data change monthly can double snapshot costs within a year. ### **Avoid data transfer charges** * Always transfer data between EC2 instances in the same availability zone using Private IPs to keep it free. * For GCP also, minimize network egress costs by placing resources (like VMs and databases) in the same region or zone to avoid cross-region data transfer fees. * Compress data at every step—CloudFront, web servers, and when uploading backups to S3. * If you rely heavily on AWS services like S3 and DynamoDB, enable VPC gateway endpoints. This shifts traffic to a private network, eliminating NAT gateway fees and significantly Here's a detailed guide to help you ### **Leverage Time-Based Scaling** Time-based scaling is an easy and effective way to save costs, yet it's often underused. Let’s take the example of an AWS user running 6 C5.4xlarge instances can reduce to 2 during off-peak hours, cutting costs significantly. With hundreds of instances, these savings multiply fast. ## Top 8 Proven Cloud Cost Savings Strategies The recommendations discussed so far offer quick cloud cost reductions. However, for long-term, more significant cloud cost savings, a different approach is needed. These strategies take a bit more effort but lead to continuous, sustained cost savings over time. ### 1. Selecting the right Cloud Pricing Models as per your business needs Cloud providers offer a variety of pricing models to help you in cloud cost savings effectively. However, it's wise to begin with short-term optimizations to quickly address immediate spending before diving into long-term commitments like Reserved Instances or Savings Plans. Each provider offers different pricing models, features, and levels of support, which can significantly affect your overall costs and the value you receive. By thoroughly evaluating your workloads, resource requirements, and potential cloud cost savings, you can select the most suitable provider and plan. Additionally, don't overlook the opportunity to negotiate enterprise discounts with cloud vendors or utilize standard discount options like Reserved Instances or Savings Plans for further cost reductions. **Reserved Instances (RIs)** RIs can save you 50-70% compared to on-demand pricing when you commit to one- or three-year contracts. They work best for workloads with stable usage. Use tools to figure out which instances to reserve for maximum savings, and manage variable workloads with on-demand instances. Similar to AWS Reserved Instances, Azure offers Reserved Virtual Machines (RIs) for long-term commitments. If you have steady workloads that run consistently, you can save up to 72% by committing to a one-year or three-year term. Unlike AWS and Azure, GCP’s commitment isn’t tied to specific instances but instead to the total amount of resources used. GCP Committed Use Contracts allow you to receive significant discounts (up to 57%) for committing to a specific amount of resources (like vCPUs, memory, or GPUs) for a one-year or three-year term. **Savings Plans** Savings Plans are flexible contracts (one or three years) based on your hourly usage. They cover various services and can save you up to 72% on EC2 instances and 64% on SageMaker. These plans are great for workloads that change frequently. **Spot Instances** Spot instances let you tap into unused cloud capacity for discounts of up to 90%. They’re ideal for fault-tolerant tasks like batch processing but can be interrupted with little notice. Tools like Elastigroup can help manage these instances for better availability. **Burstable Instances** Burstable instances are low-cost options that provide steady performance but can "burst" for extra power when needed. They’re great for general workloads with occasional spikes, such as small websites or development environments, and can save up to 15% compared to on-demand prices. Learn more in our blog on ### 2. Choose The Appropriate Region & Instance Family Choosing the right region and instance family can significantly reduce cloud costs and improve cloud cost savings. For example, hosting in North Virginia is often cheaper for services like servers, data transfer, and storage, compared to other regions. While compliance might require specific regions, you can still host non-production workloads in cost-effective areas like North Virginia. ### 3. Set Cloud Budgets and Forecasts Creating a budget cloud cost forecasting, for your cloud expenses is a crucial step in managing costs that eventually leads to better cloud cost savings. As rightly said by Paul Saffo, the goal of forecasting is not to predict the future but to tell you what you need to know to take meaningful action in the present. You can’t measure cloud cost savings without something to compare them against, so start by setting a budget based on your estimated cloud usage. Use this as a baseline to guide your cloud cost savings efforts and track your progress over time. **Actionable Advice:** Leverage **A Glimpse of CloudKeeper Lens** ### 4. Right-size your instances Rightsizing cloud resources is considered one of the most How does it work? * **Analyze your usage** : Figure out how much power your virtual machines are really using. * **Identify waste** : Spot any resources that are underutilized or overprovisioned. * **Adjust your resources** : Make changes to match your workload. * **Optimize performance** : Fine-tune your setup to get the best results. Cloud providers offer tools to monitor CPU, memory, and network usage, helping you set thresholds for when to scale up or down. You can use tools like Google Cloud’s Rightsizing Recommendations, AWS Cost Explorer, and Azure Advisor. Automating this process is key to avoiding both overprovisioning, which wastes money, and underprovisioning, which harms performance. By ### **5. Monitor and Correct Cost Anomalies** Unexpected spikes in your cloud bill can hurt your budget and cloud cost savings if you don’t catch them in time. These surprises often come from issues like poorly set up workloads or mistakes in how services are configured. The key is to spot these problems quickly so you can fix them before they lead to higher costs. _There are many tools available for spotting anomalies in cloud spending, but CloudKeeper combines automation with human-assisted anomaly detection to avoid alert fatigue. We won’t overwhelm our customers with a flood of alerts that might not be important. Instead, we focus on analyzing genuine anomalies and usage trends. Our approach prevents alert fatigue by filtering out irrelevant notifications and highlighting only the significant issues._ **Human-assisted cloud cost anomalies detection** ### 6. Adopt Containers and Serverless Architectures Switching to containers and serverless architectures can help you with cloud savings. Containers let you run multiple applications using the same operating system, which makes resource use more efficient and cuts down on extra costs. On the other hand, Serverless computing (like AWS Lambda) takes cloud cost savings to an even further level by eliminating the need to manage servers altogether. You only pay for the actual compute time you use, meaning no charges for idle capacity. This pay-as-you-go model, combined with efficient resource use, reduces overhead and makes application deployment much more agile, leading to big operational cost savings. ### 7. Achieving 100% Coverage under Reserved Instances/Savings Plan To maximize AWS cost savings, it’s smart to aim for 100% coverage with AWS Reserved Instances (RI) or AWS Savings Plans. While this strategy is a go-to for many, it’s actually best to start with other quick cost-saving steps first before locking in long-term commitments. Many users rely on standard RI utilization reports, but those don’t always tell the full story. To really understand where your savings are coming from and how much you’re spending on On-Demand instances versus Reserved Instances or Savings Plans, you’ll need more detailed insights. Custom reporting is a better way to track how well you’re utilizing your reserved instances and on-demand consumption. For this, a cloud cost visibility platform like CloudKeeper Lens can be of great help. It showcases detailed insights on RI & Savings Plan Utilization and tells you how much of your AWS reserved instances was used every hour of the day. For Azure users, **RI & Savings Plan Utilization Summary on CloudKeeper Lens** **Actionable Advice:** One of the easiest ways to achieve 100% AWS RI Coverage is to automate the process of AWS RI/SP Management by signing up with an AI-based Platform. CloudKeeper Auto is one such platform that makes the ### 8. Foster a Culture of Cloud FinOps Cloud cost optimization isn't just the responsibility of the finance or IT departments; it’s a team effort across the entire organization. Thus, This culture of accountability encourages teams to design with cost efficiency in mind—whether they're building applications, managing data, or setting up backup and disaster recovery processes. It also involves implementing tools to monitor and track cloud costs by project, team, or department, giving everyone a clear picture of their contribution to the overall bill. Regularly sharing cloud cost reports across the organization increases transparency and helps each team understand where they stand, encouraging proactive adjustments and improvising strategies for cloud cost savings. Ultimately, a company-wide commitment to cost efficiency results in smarter decisions, reduces waste, and ensures that cloud resources are being used in a way that maximizes value while minimizing unnecessary expenses. **Actionable Advice:** Cloud FinOps requires specific expertise and skill sets. It is a wise choice to partner with a FinOps Foundation certified ## How Do We Measure Cloud Cost Savings Effectively? We will talk about the two most important concepts that are very crucial for effectively measuring cloud cost savings here - Effective Savings Rate and Cloud Unit Economics. **Effective Savings Rate** Measuring cloud cost savings is essential to ensure you're getting the most out of your cloud investments. Effective Savings Rate (ESR) = 1- {Actual Spends Including Discounts/On Demand Equivalent Spend} _Here, Actual Spend Including Discounts refers to the actual amount the business paid with RIs and Savings Plans, amortizing any upfront charges._ _On-demand equivalent (ODE) Spend refers to the amount a business would have paid if no discounts were applied._ _A higher ESR indicates better cost management and optimization of cloud resources, helping businesses maximize the value of their cloud investment._ **Cloud Unit Economics** Let’s discuss another must-know topic which is Let’s understand it through an example of cost per customer for a B2B SaaS company using a different scenario. _Suppose the company has an Amazon cloud bill of $50,000 for one month, serving 1,000 customers. This means their cost per customer is $50._ _In the following month, their Amazon bill increased by 20%, bringing it to $60,000. However, their customer base only grows by 10%, reaching 1,100 customers. This results in a higher cost per customer of about $54.55._ _In this case, the business is spending $4.55 more per customer on cloud costs compared to the previous month, which isn’t a good sign. Understanding these numbers is crucial to managing cloud expenses effectively and improving cloud cost savings._ Moreover, It’s always a smart move to align costs with business ## **Addressing Common Questions About Cloud Cost Savings** **Q: Does using cloud services always result in cost savings?** While cloud services offer the potential for significant cloud cost savings, it depends on how effectively they are used. Simply migrating to the cloud doesn’t guarantee reduced costs. In fact, if resources are over-provisioned, or if there’s a lack of proper management and optimization, costs can spiral out of control. To achieve real cloud cost savings, it’s important to take steps like choosing the right pricing models (e.g., Reserved Instances or Savings Plans), regularly monitoring usage, rightsizing resources, and implementing cost management strategies as guided in this blog. When done right, cloud services can save you money, but without proper oversight, they can also become a source of unexpected expenses. **Q. How do I avoid cloud waste?** Avoiding cloud waste is all about making sure you're only using what you need and optimizing your resources. Here are a few tips to get you started: * **Turn off idle resources** : If you have instances running that aren’t being used, shut them down! These idle resources can add up to big costs. * **Right-size your resources** : Make sure you're only using the resources you actually need. Avoid overprovisioning, as this can lead to unnecessary costs. * **Optimize storage** : Clean up unused storage and archives that you no longer need. Also, it's a good practice to use tiered storage for data that’s infrequently accessed. * **Monitor Resource Usage** : Continuously monitor resource utilization. Keep track of what's being used, and optimize where needed—whether it’s memory, CPU, or storage. * **Set budgets & alerts**: Regularly monitor your spending. Use cloud cost management tools to set spending limits and get alerts to take proactive actions before things get out of control. **Q. What are common cloud cost pitfalls to avoid?** * **Over-provisioning:** Don’t pay for more resources than you actually need. Right-size your instances * **Leaving unused resources on:** Shut down idle servers or instances to avoid paying for nothing. * **Lack of monitoring:** It's a must to use cloud cost visibility and management tools to monitor and control your cloud expenses. * **Not setting up cost alerts:** It is important to set up cost alerts so that you can be notified when your spending exceeds a certain threshold. * **Ignoring savings opportunities:** Many cloud providers offer discounts for long-term commitments or specific usage patterns. If your workload is predictable, it’s a great way to save money. * **Data transfer costs:** Moving data between regions can get expensive, so plan carefully. * **Not using cloud cost management optimization:** Many cloud users skip out on using the available cloud cost management optimization, but these can help track spending, set alerts, and find areas where you can optimize your usage. Learn more about **Q. How do Reserved Instances or savings plans reduce cloud costs?** Reserved Instances and Savings Plans are two popular strategies used to reduce cloud costs. They work by providing discounted rates for a committed period of usage. **Reserved Instances:** These are instances that you commit to using for a specific term (e.g., 1 or 3 years). In exchange for this commitment, you get a significant discount on the hourly rate. **Savings Plans:** These are a more flexible option that provides a discounted hourly rate for a specified amount of compute usage over a one-year term. You can use your Savings Plan across multiple instance types and regions. Here's how these options can help reduce cloud costs: * **Predictable Costs:** By committing to a specific usage pattern, you can lock in a predictable cost for your cloud resources. * **Significant Discounts:** The discounts offered for Reserved Instances and Savings Plans can be substantial, saving you a significant amount of money. * **Flexibility:** While Reserved Instances offer a fixed commitment, Savings Plans provide more flexibility, allowing you to use your discounted hours across different instance types and regions. Check out **Q: How often should we review and adjust our cloud costs?** ## Effortless Cloud Cost Savings With CloudKeeper CloudKeeper is a comprehensive and certified CloudKeeper’s offerings are tailored to meet the unique needs of different customer segments and bring highly skilled and experienced cloud professionals to help you at every stage of the growth journey. **CloudKeeper AZ:** Guaranteed reduction on the entire bill with access to volume-based pricing and hassle-free management of RIs & Savings Plans, without any commitments. **CloudKeeper Auto:** Zero-touch, AI-based automated system for Reserved Instances (RI) and Savings Plans management offering RI & Savings Plans pricing for on-demand instances and a buy-back guarantee of unused RIs & SPs. **CloudKeeper EDP+:** Maximizes your AWS EDP benefits with additional discounts, lower annual commitments, and discounted prices on AWS Support. **CloudKeeper Lens:** A cloud cost visibility & analytics platform that provides insights to track, analyze, and optimize your cloud usage. **CloudKeeper Tuner:** An Automated AWS Usage Optimization & Recommendation Platform that optimizes the performance of your workloads on 50+ AWS services thereby reducing the cost of your infrastructure without compromising on performance. Discover how CloudKeeper can transform your cloud infrastructure and achieve cloud cost efficiency for you, today! Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Chief Operating Officer Aman spearheads business operations, strategic execution, and cross-functional alignment to drive sustainable growth. FOUND THIS USEFUL? SHARE IT 2 Comments John Snow 2 days ago Your article is great! Thank you for taking the time and effort to share this valuable knowledge. I have learned a lot of new things and will apply them in practice. I hope you will continue to write more good articles like this. 2 days ago allin 2 weeks 4 days ago This guide offers some valuable strategies for managing cloud costs effectively. Smart optimization is all about accuracy and planning — similar to how an online protractor ensures precise measurements. Very helpful resource! 2 weeks 4 days ago Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents The landscape in which a FinOps team must operate is a complex and varied one. FinOps is a holistic approach to delivering accountability and collaboration around an organization's cloud investment. It is also a change management journey that involves a cross-functional team. The FinOps team must navigate internal changes and politics to drive this culture change. However, a company's overall strategy should also include the external landscape and its associated complexities. A company must decide if and how to properly engage FinOps-managed service providers, cloud resellers, consultants, and software providers. These vendors offer many capabilities including FinOps business process services, cloud cost analytics, and reserve instance (RI) optimization. Let's focus on this external landscape and where to leverage each type of vendor for the best business benefit. To understand how a vendor can benefit the FinOps team, an organization must know where they can fit in the Figure 1: FinOps Phases Source: IDC currently tracks 63 individual FinOps vendors, including IDC uses three categories to segment the market: cloud analytics and reporting platforms, cloud resource and pricing optimization tools, and service providers and resellers. 1. **Cloud analytics and reporting platforms:** Software tools in this category are designed to quickly get teams up and running on the Inform phase of FinOps. These tools pull an organization's current spending from the leading hyperscalers and help automate the tagging of cloud resources through AI. 2. **Cloud resource and pricing optimization tools:** Monitoring the demand side of a cloud application and automatically adjusting its resources are part of the FinOps Optimize phase. This stage includes RI optimization, which matches the proper cloud resources with the correct pricing tier. This complex task is typically driven by real-time monitoring of the cloud environment by AI. Many companies attempt to perform this task with spreadsheets, but the myriad of options makes that ineffective. Some tools will offer 3. **Service providers and resellers:** In the Operate phase, a specialized FinOps service provider can help a company control its cloud costs and dramatically mature its FinOps processes. These providers can offer managed services to assist in Finally, there is what IDC calls the "all of the above" option: a combination of cloud dashboard analytics, RI and cloud resource optimization, and ongoing managed cloud services. However, only a few multiple cloud vendors and providers offer this holistic choice. By selecting this approach, companies can compound the benefits of all three FinOps phases (Inform, Optimize, Operate) and ensure their Selecting this last option will increase a company's savings and mature its FinOps processes today while helping to better architect and control future cloud investments. Organizations looking for a comprehensive partner would do well to ask tough questions and demand coverage of all three phases. ## **Finding the Right FinOps Partner** The importance of Cloud FinOps in organizations is on the rise. However, with varying FinOps maturity across organizations, it is essential to find the appropriate partner who can help adopt FinOps and optimize cloud costs. CloudKeeper is a comprehensive AWS Cost Optimization and FinOps solution that offers instant & guaranteed savings of up to 25% on your entire AWS bill at no cost or commitment. The company falls into the “all of the above” category of vendors and offers cloud cost optimization solutions and technology guidance, throughout an organization’s FinOps journey. An AWS Premier Consulting Partner, CloudKeeper has helped 300+ businesses, over 12+ years, to achieve instant and guaranteed cost savings right from Day 1. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents As and when enterprises move towards higher cloud budgets, more resources, and longer-term commitments, the need for a proper Cloud FinOps system becomes crucial. By implementing FinOps, the organization makes sure that ‘cloud cost’ remains one of the top priorities while managing, monitoring, allocating, and forecasting cloud resource usage. To complement these AWS Enterprise Discount Program (EDP) is one among the lot, tailored specifically for organizations who are scaling their businesses over the cloud and require a long-standing partnership with AWS. But there are a handful of requirements to be eligible for EDP. ## **Making the Most Out Of Cloud Investments** The AWS EDP takes into account the predictability and volume commitments of the customer’s cloud usage. AWS analyzes their consumption history and the discounts are used to encourage these users for longer partnerships. Hence, this program is more suitable for organizations that require a long-term commitment, could almost accurately forecast their usage needs, and would have minimal variations from these projections and commitments. EDP applies to a variety of AWS Services and the size of the discount scales in proportion to the committed volume and term length. According to Although seemingly small, Customers who consume services exceeding the committed limit are charged at standard rates and this spending would not be accounted for future term EDP commitments. This overage charge could significantly impact their budgets. Similarly, when the usage falls short of the commitments, they might not receive the discount benefits as expected with the plan. The leftover credits will not result in reduced billings, nor will be rolled over. ## **Choosing the Right Terms and Commitments** By understanding their business requirements and the right kind of AWS services needed, the organization can assemble the right set of volume and term commitments. This way, they could make sure that any deviations from the expected usage commitments are avoided. There are a few more factors that could influence the EDP agreement, which include: - Spend on the AWS Marketplace towards third-party listings - Future spending projections for AWS Services or further cloud transformations - Additional AWS cloud users in immediate association, i.e., a subsidiary - Ability to migrate existing on-premise services to AWS Gathering this information requires an in-depth analysis of the current cloud spending patterns, along with a collaborative effort of the Finance and Engineering teams. Quite evidently, finalizing the right EDP commitment for an organization depends on a thorough understanding of their existing cloud infrastructure and the in-outs of all the AWS offerings they have deployed. There isn’t much information on these commitment terms and discount brackets available in the public domain. This might indicate the flexibility AWS offers in customizing the EDP program according to the needs and cloud resource usage projections of the organization. But again, without any awareness of the intricacies of this program, enterprises might find it difficult to arrive at the right set of commitments that would give them the maximum benefits. ## **Working with a Trusted Cloud Partner** There are many nuances that go into selecting the perfect EDP plan depending on the resource utilization, AWS service types, target platforms, AWS marketplace apps, Savings plans, SLAs, and more. With a trusted cloud partner by their side, organizations can maximize their savings from an EDP package with a minimum commitment. Organizations like With CloudKeeper in particular, AWS EDP programs will result in double the benefits. CloudKeeper has been working with 20+ active AWS EDP customers across various domains. With the in-depth knowledge of the EDP program and the expertise to recommend valuable considerations for requirement planning, CloudKeeper would be able to help realize the best possible commitment-discount tradeoff. Additionally, CloudKeeper offers a one-stop Therefore, in addition to helping organizations grab the best EDP plans at an optimal price, CloudKeeper also helps them to track and manage their progress, thereby ensuring maximum savings from EDP. For any organization opting for an EDP plan, it is important to have diligent planning backed by an in-depth understanding of their existing cloud resources and future requirements, before reaching out to AWS and locking in on any agreement. With an expert FinOps vendor as their ally, they could ensure the right set of commitments and a well-rounded EDP plan, helping them grab the best price, maximum discounts, shorter renewal cycles, and enough flexibility. ## **Related Blog :** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Complete Guide to AWS PPA Contract Negotiation for Growing Enterprises A practical guide to AWS PPA or EDP negotiations, covering commitments, discounts, flexibility, risks, and best practices to help growing enterprises secure better pricing and long-term cloud value. By Team CloudKeeper 19 Dec, 2025 Ask the Cloud Expert: A Deep Dive Q&A on AWS PPA In this Q&A, CloudKeeper’s AWS PPA expert Aman Dixit shares real-world insights to help clients navigate PPAs and make smarter, cost-effective decisions. By Team CloudKeeper 05 Sep, 2025 Introducing the AWS EDP Tracker in CloudKeeper Lens AWS EDP Tracker is a real-time interactive dashboard that gives you end-to-end visibility to monitor, forecast, and optimize your EDP spend throughout its term. By Harsh Agarwal 06 May, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 23 23 Table of Contents Imagine a vibrant Monday morning at your company. The Marketing team is gearing up for their latest campaign launch, a social media offensive, and the cloud resources are humming into action with new collaterals posted to the internet horizons. However, the Finance department is in a whole other vibe. Their inboxes start getting filled with cloud cost alerts from the cloud provider, threshold barriers broken and costs mounting up and traversing well above the benchmarks. There begins the blame game in full swing, teams pointing fingers at each other and engineers caught in the crossfire. What was planned as a well-budgeted, highly anticipated marketing celebration has turned into a financial, technical, and strategic quagmire. While it has a comic tone to it, this is a pressing dilemma faced by almost every business out there in the cloud, which is, the challenge of ## **What is FinOps?** It involves an act of synergy that unites Finance, Engineering, and Business functions, fostering shared accountability within cloud financial management. We can draw similarities of a cloud FinOps process with our favorite superhero movies, like ‘The Avengers’. The cloud FinOps practice is an ensemble of various powers that contribute a larger effect to the business finances. **The Finance Team:** With their arsenal of budgets and fiscal reports, they champion transparency and accountability in cloud expenditure. **The Engineering Team:** Experts in infrastructure and resource stewardship, they fine-tune cloud deployments for peak efficiency and cloud cost optimization. **The Business Team:** Ever poised to meet and exceed business objectives, they steer cloud investments towards the pinnacle of value and return on investment. Cloud FinOps is much more than saving money. It's about making strategic choices concerning ## **Cloud FinOps vs. FinOps** The terms **“FinOps”** and **“Cloud FinOps”** , although used interchangeably, represent slightly distinct concepts. **FinOps:** This is a broader term that means the financial management practices related to any technology environment or ecosystem, and that too, encompassing on-premises, cloud-based and hybrid systems. **Cloud FinOps:** Specifically applies to ## **The benefits of Cloud FinOps** Now you know the fundamentals of FinOps, but you might be thinking - why should this be important to you? What benefits could it possibly bring to you and your business? Let’s see how Cloud FinOps helps you unlock the full potential of your cloud investments. **1. Enhanced Cloud Cost Savings** * Reduction in Cloud Expenditure: One of the most obvious and widely known advantages is the * Minimizing Cloud Wastes: By pinpointing and eliminating underutilized resources, excess storage, and suboptimal configurations, cloud FinOps ensures that every penny spent is completely optimized, contributing to long-term cloud cost savings. * Rightsizing Resources: Organizations can **2. Visibility and Control Aiding Strategic Decisions** * Expense Tracking: Cloud FinOps helps gain enhanced visibility on cloud utilization and resource-level costs, granting the clarity needed to make strategic resource management and optimization decisions. * Budget Forecasting: Better visibility in turn helps with precise budgeting, enabling organizations to anticipate cloud expenditure and mitigate the risk of cost overruns. * Cloud Resource Governance: By implementing governance protocols, cloud FinOps ensures the **3. Boosted Innovations** * Better Time-to-Market: Cloud FinOps streamlines resource management, helping quicker market entries for new products and services. * Enhanced Scalability: Tapping into the scalability of the cloud, FinOps matches available resources to business needs, * Empowered Teams: By enabling informed decision-making, cloud FinOps leads to more streamlined and effective cloud utilization, cultivating a culture of cost consciousness. **4. Amplified Return on Investments** * Business Alignment: Cloud FinOps guarantees that cloud investments are strategically aligned with business goals, prioritizing projects with the highest potential for return on investment. * Minimized Vendor Lock-in: Leaning towards a diversified approach to cloud infrastructure design, cloud FinOps helps diminish dependency on a single vendor. * Future-ready Strategies: With **5. FinOps Culture** As important as the savings, cloud FinOps also instigates a cultural shift within the organization. It dismantles traditional siloes, fostering a synergy between various organizational functions. The ## **The FinOps Foundation** Cloud cost optimization is often a complex affair and the FinOps Foundation stands at the forefront of helping businesses navigate this maze. Launched in 2019 by the Linux Foundation, they help impart cloud FinOps wisdom, best practices, and governance policies among practitioners far and wide, with a mission to make cloud spending smarter and more efficient. The core of the foundation’s mission is a handful of * **The Six Core Principles:** These principles lay the groundwork for FinOps success, championing teamwork, accountability, strategic spending, swift action, strong leadership, and a keen adaptation to the dynamic nature of the cloud. * **The FinOps Lifecycle:** This framework imagines cloud FinOps as a continuous cycle of three phases - **Inform, Optimize, and Operate**. These phases involve, learning from the cost visibility, making strategic adjustments, and fostering a culture of continuous optimization and collaboration. * **The FinOps Maturity Model:** This helps organizations see where they stand in their FinOps journey. Their maturity is assessed in three phases - **Crawl, Walk, and Run** - and offers a way to elevate their game. ## **The State of FinOps Report** Every year, the FinOps Foundation releases an annual report, gathering information about key priorities, industry trends, and the direction of FinOps practices across organizations worldwide. The latest insights from the State of FinOps Report sheds light on the evolving landscape of cloud cost management. * **Demand for FinOps Practitioners:** There’s a * **Evolving Goals:** The focus areas of cloud FinOps strategies are broadening to a more nuanced approach aimed at minimizing cloud waste and maximizing business value. * **Sustainable Practices:** Nearly 50% of the organizations surveyed are planning to sync their FinOps practices with sustainability goals, reflecting a growing commitment to eco-friendly cloud computing. ## ## **The Principles of FinOps** Implementing cloud FinOps in your organization is a continuous process, embracing a * **Foster Team Collaboration:** This principle champions shared responsibility across all stakeholders involved in FinOps decision-making and implementation. This fosters a culture where finance, engineering, and business teams work together towards common goals. * **Cultivate Ownership:** This principle focuses on building accountability for cloud expenditures. With practices like real-time cost allocation, tagging, chargebacks, and showbacks, along with measuring cost per unit, organizations can improve cost management and accountability. * **Data-Driven Decisions:** This value urges organizations to align cloud usage and cost information with business outcomes. This enables informed decisions on * **Timely Reporting:** Accessibility to real-time data ensures that decision-makers can swiftly act, facilitates quick feedback loops, and enables responsive and agile financial management. * **Centralized Leadership:** A dedicated FinOps Team should spearhead the planning, implementation, and optimization of cloud cost optimization practices in the organization. This central leadership ensures consistent monitoring, value delivery, and cloud governance that aligns with the organization’s goals. * **Tapping into the Variable Cost Model:** This principle re-emphasizes the importance of By implementing these cloud FinOps principles, a cloud consumer can unlock a pathway to not only manage cloud expenses more efficiently but also to drive strategic business value from cloud investments. Cloud FinOps is more than just a framework and could be considered a cultural transformation that steers organizations toward a future where cloud financial management is closely integrated to business objectives. ## **The FinOps Lifecycle** The **FinOps Lifecycle** comes into play. It involves three phases. **1. Inform - Establishing Cost Visibility** This phase is all about demystifying cloud expenses. The key action items include: * Deploying tools to capture in-depth cost data. * Analyzing major cost contributors to understand where the budget is being spent. * Establishing benchmarks for monitoring cloud expenses over time. * Creating This phase sets the premise and enables everyone to base their decisions on solid data. **2. Optimize - Transforming Insights to Savings** This phase is where a team equipped with data and insights acts upon them. This includes acts where they: * Adjust cloud resources to match actual needs, avoiding provisioning mismatches. * Explore cost-saving options like RIs or Spot Instances for appropriate requirements. * * Negotiate with the cloud providers for savings or discounts based on existing usage and commitments. **3. Operate - Building a Cost-conscious Culture** This phase ensures cloud FinOps becomes ingrained in your organization’s DNA, with an increased focus on: * * Governance policies for responsible use of cloud resources to avoid wastage. * Keeping a vigilant eye on cloud expenses, always on the lookout for better efficiencies. * Revisiting and tweaking your approach to stay aligned with the business dynamics. Due to its iterative nature, the cloud FinOps lifecycle becomes a closed loop, that invites continuous refinement and adaptation. This flexibility ensures that as your cloud infrastructure evolves, your approach towards managing costs also becomes optimized. ## ## **The FinOps Maturity Model** Another innovative framework introduced by the FinOps Foundation, the maturity model employs a phased approach to cloud FinOps implementation - **Crawl, Walk, and Run.** This model encourages businesses to gradually evolve their Finops capabilities in a way that aligns with their unique needs and scales with their growth. * **Crawl:** At the beginning of their FinOps journey, organizations are in their Crawl phase, where the focus is on laying the groundwork. Minimal reporting tools and basic KPIs are established for insights that help mature the FinOps practice. The primary goal of this stage is to set the stage for more sophisticated optimization strategies, along with * **Walk:** Businesses in the Walk phase have internalized FinOps practices across their teams. These practices are enhanced by technologies like analytics, automation, and refined processes, that cover more of the FinOps requirements. A few edge cases might be identified during cost monitoring, however, the focus remains on addressing the challenges that have the most significant impact on cloud financial health. In this phase, KPIs become more nuanced, reflecting a deeper engagement with cloud cost management and optimization strategies. * **Run:** This phase signifies a mature FinOps practice, where organizations have successfully integrated FinOps principles across all their teams, with a strong emphasis on technology. The focus is on The guiding principle for organizations following the FinOps Maturity Model is to focus on maturing the areas that promise the highest business value. There should not be any haste to evolve through the phases, instead, ensure that the efforts to mature a FinOps capability are aligned with the overall success metrics. In simple terms, the priority should be to mature those capabilities that directly contribute to the financial and operational goals. By adopting this model, companies become equipped to make informed decisions that optimize cloud spend, improve efficiency, and ## ## **The FinOps Personas** In the cloud computing domain, optimizing the entire infrastructure of an organization and achieving proper ROI is akin to conducting an orchestra - everyone must play in sync, with a clear vision and mutual understanding. In essence, cloud FinOps should have diverse roles brought together to fine-tune the cloud’s potential. The key stakeholders behind this symphony include: ### **1. The Executive Suite** **Titles** : CTO, CIO, CFO, Head of Cloud, Head of Engineering **Role** : Executives provide the direction for cloud FinOps initiatives. They ensure alignment with business goals, foster accountability, ensure transparency and help teams ### **2. Leaders of Functional Units** **Titles:** Director of Cloud Optimization, Cloud Analyst, Business Operations Head **Role:** Maximizing the business value of cloud investments by prioritizing cloud resource usage and optimization for daily operations and new launches. They aim to accelerate business growth while ### **3. Engineering and Business Operations** **Titles:** Software Engineer, DevOps Engineer, Cloud Architect, Delivery Manager **Role:** Responsible for building and maintaining cloud infrastructure efficiently. They identify cloud cost-saving opportunities by resource optimization, ### **4. Finance and Procurement** **Titles:** Finance Manager, Analysts, Procurement Specialists **Role:** Gather insights from the cloud FinOps teams to negotiate favorable contracts with cloud providers. They could also work with the engineering teams to find a balance between performance requirements and cost benchmarks, by building guardrails. ### **5. The FinOps Team** **Title:** FinOps Practitioner, Cloud FinOps Expert **Role:** Lead the cultural and operational shift required for successful cloud cost optimization practices. They draft cost management policies, educate the organization on cloud FinOps principles, The magic of FinOps lies in collaboration, where each group plays its part with commitment and understanding. The result is a well-tuned performance that delivers: * **Shared Responsibility:** A collective ownership of the cloud strategy, where everyone plays a part in harmonizing cost, provisioning, and performance. * **Informed Choices:** Decisions are guided by actionable insights, ensuring that each move is a step towards greater efficiency. * **Strategic Alignment:** Cloud resources and investments align in harmony with business objectives, amplifying impact where it matters the most. By encouraging a symphony of efforts across these key roles, organizations can orchestrate a ## **The Challenges in Cloud FinOps** Even with the various cloud FinOps roles mapped out across the stakeholders, there are a host of challenges that persist in cloud FinOps implementation. These obstacles hinder organizations from fully realizing the benefits of cloud cost management and optimization. If we were to list out the top 5 cloud FinOps challenges faced by businesses worldwide, they would include: **Cloud Waste:** Unnecessary cloud resource usage and the corresponding costs, due to exceeded capacities, overprovisioned resources, and underutilized discounted instances remain significant challenges to Finops teams. Without **Lack of Cost Visibility and Granularity:** Without adequate cloud cost visibility, it is difficult to zero in on the cost drivers and optimize spending. Robust cloud cost monitoring and reporting, leveraging advanced tools, is necessary to track and analyze cost data at a granular level. **Complex Cost Allocation and Tagging:** Properly tagging and allocating costs to different departments, projects, or teams remain a challenge due to the lack of transparent, fair cost allocation strategies. Establishing cost centers and **Lack of Collaboration:** Even with multiple teams carrying out their FinOps responsibilities, these teams getting siloed with limited collaboration poses a significant challenge in cloud FinOps. Without cross-functional synergy, there would be a lack of shared understanding of cloud costs, budgetary constraints, complicated spending patterns, and a disconnect in resource provisioning decisions. **Multi-Cloud and Hybrid Cloud Complexities:** Optimizing costs in a These challenges, along with other issues which include a lack of proper FinOps talent, governance, and compliance issues, and resource utilization problems, could create roadblocks to effective cloud FinOps implementation and successful cloud cost optimization. Tackling these hurdles needs concerted efforts from the organization by ## **Cloud FinOps Best Practices** The challenges to FinOps implementation could be mitigated by integrating certain best practices into the cloud FinOps strategy. While some of these practices require the use of certain tools or skills, some might require an entire cultural change. These cloud cost optimization best practices include the following. * **Automated Resource Management:** To handle unnecessary cloud resource usage and the resulting cloud waste, organizations can implement resource monitoring and management tools. Resource management tools of today are laced with automation and AI capabilities, which conduct * **Integrating Cost Visibility Tools:** There are advanced cost management tools in the market that help gain comprehensive visibility into cloud costs, at a granular level. These tools also offer * **Establishing Cost Centers:** Cloud cost centers are an effective way to streamline cost allocation and tagging. By defining standardized cost allocation frameworks, organizations can ensure transparency and fairness in cost distribution across different business units. Leveraging automation tools can further simplify the cost allocation process, by tagging resources based on predefined rules which ensure consistency and accuracy in cost attribution. * **Promoting Cross-Functional Collaboration:** Organizations should establish regular communication channels and forums for cloud FinOps stakeholders to share insights, challenges, and best practices. Conducting training sessions and workshops can educate them on the importance of collaboration in cloud cost management. A rapport between Finance, IT, and Business teams can * **Unified Cost Management Solutions:** Implementing a centralized cloud cost optimization platform is crucial in managing complexities associated with multi-cloud and hybrid cloud environments. These solutions provide a single pane of glass view across multiple cloud environments. Additionally, by upskilling employees for expertise in multi-cloud management, organizations can effectively By embracing these best practices and strengthening the governance and compliance frameworks, organizations can address their cloud FinOps challenges, achieving greater efficiency and cloud cost savings. ## **Working with a Cloud FinOps Partner** While these cloud FinOps frameworks and best practices empower organizations to step ahead and optimize cloud costs, As tempting as the result of huge cloud cost savings, the journey toward cloud cost optimization is not always smooth sailing. That is where a cloud FinOps expert could be onboarded and there are multiple reasons why it is a smart move. ### **Snagging the Right Crew is Tough** Finding and assembling a FinOps team involves excessive scouting for cloud FinOps pros who are technically advanced and also align with the organizational philosophy. Even if you are ready to make that effort, so is everyone else in the market, which makes finding cloud FinOps talent nothing less than hunting treasure. ### **Turbulent Internal Waves** Resistance to change is a very common challenge in almost all organizations and this makes getting FinOps to mesh with your team’s rhythm even more difficult. However, a cloud FinOps expert would be adept at ### **Access to the Finest Tools and Skills** FinOps partners are fully equipped with the latest cloud cost optimization capabilities, tools, and skillsets. This could include in-depth analytics, automation, AI/ML, and comprehensive dashboarding and reporting features. Accessing these individually could be much more expensive. ### **Unlocking Secret Hacks and Hidden Discounts** A cloud FinOps partner is not just an advisor or facilitator, they also know the secret paths to ### **Sailing with the Current** The FinOps domain is like a vast, ever-changing sea and only a dedicated cloud FinOps expert can keep a keen eye on the horizon, and understand new updates, policy changes, vendor transformations, and technology enhancements. With the cloud FinOps partner, businesses could ### **More Savings for Lesser Investments** Building a FinOps discipline from scratch involves a lot of effort, time, resources, and especially, financial backing. Partnering with a cloud FinOps expert on the other hand is often very much economical, and it also helps you skip multiple steps and dive straight into reaping the rewards of cloud cost optimization. ## **Cloud FinOps Tools - Must-have Features** Let’s take a look at the breakdown of the key factors to weigh in when selecting the ideal cloud FinOps solutions for any business. * **In-depth Cost Insights:** It is crucial to have a * **AI and Automation Capabilities:** It is always an advantage to have tools that use the power of AI/ML and Automation to optimize resources, mitigate cloud waste, and optimize cloud costs efficiently. These enhancements could dramatically improve cost-saving efforts. * **Multi-Cloud and Hybrid Cloud Support:** The cloud FinOps partner should be able to * **Proactive Budgeting and Reporting:** Cloud FinOps solutions should empower you to proactively manage your budget with real-time spending alerts and customizable reporting dashboards. This helps immensely when collaborating with multiple teams within the organization. ### **Comprehensive Cloud FinOps Partner** Rather than choosing multiple cloud FinOps solutions for specific capabilities and features, a certain handful of cloud FinOps solutions offer a comprehensive approach to cloud cost optimization. They include all of the features listed above, along with capabilities like Automated RI Management, Smart Recommendations, FinOps Consulting, Architectural Reviews, and more. Working with an all-in-one cloud FinOps provider helps organizations _**Pro Tip:** It’s important to keep up with the latest FinOps industry trends, and understand what your competition is doing right. How about understanding the market demands better based on insights from 450+ businesses worldwide? __for a comprehensive and interesting analysis of the FinOps Vendor Market._ ## ## **How CloudKeeper Becomes the Best Choice?** Now that we've seen the benefits of having a comprehensive cloud FinOps partner, the big question arises: How do you pick the perfect one from the crowded marketplace to embark on your cloud cost optimization journey? That's where CloudKeeper steps in – your go-to partner for cloud FinOps excellence. Here's why CloudKeeper is your perfect companion on the journey to optimizing cloud expenses: ### **Expertise and Partnerships:** CloudKeeper isn't just any cloud FinOps provider – we bring almost a decade and a half of expertise and prestigious partnerships, including AWS Premier Partnership, Microsoft Azure Solutions Partnership, and Premier Partnership with the FinOps Foundation. This extensive experience and industry recognition ensure top-notch solutions and expert guidance for your cloud environment. ### **Tailored Solutions for Every Need:** We recognize that each organization's cloud requirements are unique. CloudKeeper offers a diverse range of solutions to meet these varied needs for both AWS and Azure infrastructures: * **CloudKeeper AZ:** This solution guarantees savings through * **CloudKeeper Auto:** Say goodbye to the hassle of managing Reserved Instances (RIs). CloudKeeper Auto automates RI buying and selling based on your infrastructure needs, offering On-Demand * **CloudKeeper EDP+:** Looking for a * **Unveiling Hidden Costs with CloudKeeper Lens:** CloudKeeper Lens is your gateway to unlocking invaluable insights into cloud costs. This powerful tool offers a granular view of your cloud spending patterns, identifying resource-level costs and variations through a heatmap. Initially offered **Beyond Cost Savings: Expert Cloud FinOps Guidance** CloudKeeper doesn't stop at providing cost optimization tools. We offer **Zero-Hassle, Zero-Risk Approach** At CloudKeeper, we believe in making cloud cost optimization effortless for you. Most of our solutions require zero upfront costs, zero effort from your IT team, and zero commitment from your organization. Our RI Management platform, CloudKeeper Auto, operates on a results-based pricing model, where our fees are a small percentage of the savings you achieve. With CloudKeeper by your side, rest assured to be navigating the cloud cost optimization landscape seamlessly, empowering your organization to unlock the full potential of cloud efficiency and savings. ## ## **The Future of Cloud FinOps** FinOps and Cloud Cost Optimization is a rapidly evolving domain that is becoming a strategic discipline that fosters collaboration along with delivering immense business value. The future of cloud FinOps looks exciting and here are some trends shaping its path ahead: **AI-powered Optimization:** Artificial intelligence will play a prominent role in cloud cost analytics and prediction. * Proactive identification of potential budget overruns. * Pinpointing unauthorized usage, security breaches, and resource waste. * Real-time cost insights by answering queries and offering recommendations. Also, the availability of Generative AI-based capabilities could be used to create realistic “what-if” scenarios in cloud cost optimization. This would enable FinOps teams to understand the potential cost impact of strategies like scaling resources, adopting a new cloud service, or migrating workloads to different cloud providers, and make informed decisions. **Decentralized Cloud Cost Management:** A shift is underway towards empowering individual teams to manage their cloud costs. This fosters a culture of accountability and ownership, leading to more efficient resource utilization. **Unified Cost Visibility and Management:** With the increase in the adoption of multi-cloud and hybrid cloud infrastructures, managing cloud costs become a challenge. Future FinOps solutions will offer **Adopting DevSecFinOps:** The concept of DevSecFinOps shows the importance of including FinOps from the very beginning of the development process, alongside security considerations. This signifies a more holistic approach to cloud resources management. Regular audits, reviews, and security mechanisms will be a part of cloud FinOps strategies. **Sustainability in the Cloud:** Cloud FinOps will play an important role in optimizing cloud resources for energy efficiency, and reducing the environmental footprints. FinOps solutions and tools will be built to measure and optimize cost from a sustainability perspective. Organizations are also increasingly adopting green computing principles in their cloud FinOps practices. The possibilities of ## **Conclusion** The importance of a cloud cost optimization strategy is more critical than ever in today’s digital landscape. By embracing and learning the foundational concepts of cloud FinOps, businesses can easily The shared responsibility model of cloud FinOps principles emphasizes the theme of collaborations and the importance of team synergy in achieving FinOps success. Adding to this mix is the necessity of working hand in hand with trusted cloud FinOps partners, who can With proper cloud FinOps best practices in place, no businesses would ever need to worry about their new launches and innovations eating up their budgets. Cloud cost optimization is an efficient and sustainable way to build a future where executives strategize ambitiously, engineers build without being scared of costs and marketers celebrate their campaigns with no one frowning upon them. _Did you know CloudKeeper offers an end-to-end Well-Architected Review of your cloud infrastructure, completely free of cost?__._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents Cloud is being embraced quickly by organizations. Organizations move from legacy infrastructure and traditional hardware setup to Cloud to reduce total cost of ownership, improve disaster recovery and get multiple other benefits. According to Gartner, end-user spending on public cloud services is predicted to grow at 21.7% from $396 billion in 2021 to $482 billion in 2022. According to Rightscale State of The Cloud Report 2017, more and more companies are adopting a multi-cloud strategy to amplify scale and receive benefits faster from Cloud. This journey to cloud is not a simple one though. An increasing number of organizations are steadily realizing the advantages of partnering with Cloud Managed Service Providers (MSPs) who have expertise in building and managing Cloud Services to support organizations in their journey to cloud transformation. In such instances, Cloud Managed Service Providers can manage your cloud infrastructure-be it multi-tenant or hybrid, and close service gaps, if any. They have expertise in cloud computing, managing cloud security, storage, network operations, application stacks, performance testing, IT health monitoring, reporting, recovery, infrastructure migration, change management and more to ensure continuous delivery pipeline. Migrating to the cloud and maintaining it while ensuring optimal functioning is not an easy task. It entails a thorough understanding of the cloud environment and tools that are available today for optimization of performance. Cloud MSPs can help organizations not only during the migration of their legacy IT to cloud but also beyond that, by providing maintenance services on an ongoing basis. MSPs bring advantages of scale and experience with them. On-boarding an MSP is not an easy task though. Here’s a quick checklist for you to assess cloud MSPs before on-boarding them: * Assess the vendor’s end-to-end capabilities- from planning and migration to maintenance and optimization. * Measure the industry or vertical specific expertise. * Check the Cloud Services or Providers in their support ecosystem. * Assess their best practices, tools, collaboration models. Organizations can afford to become lean by tying up with a Cloud Managed Service Provider. Earlier, organizations had to maintain separate teams for network admin, server admin, storage admin, virtualization admin, and data center operations team. With a Managed Service Provider, enterprises can do away with these separate teams. The Cloud Service Providers look after application deployment, does fine tuning of servers and applications, manages infrastructure-as-a-code, and performs high-value tasks while the in-house Developers can focus on their development work. With Cloud Managed Service Providers on board, organizations do not have to worry about managing complicated devices (such as Firewalls, NetApp Storage), hardware failures and their replacement. The managed services team nowadays follow Agile Methodologies and DevOps best practices using tools such as Puppet, Ansible, Jenkins, etc. and utilizes Chef/ OpsWorks for configuration management. Apart from the above advantages and associated cost advantages, on-boarding a managed service provider for your cloud environment is a smart move. ## **Top 5 reasons to on-board Cloud Managed Service Provider** 1. **Performance Monitoring** Effective Performance Monitoring strategy is a must for preventive maintenance initiatives on the cloud. Since 2010, the cost of downtime has steadily increased by 41 percent. As per a study, data downtime can cost as much as $7900 a minute! Cloud outages are not uncommon. Recently at the beginning of the year, GitLab experienced an 18-hour outage owing to a human error that affected 5000 projects, 5,000 comments, and 700 new user accounts. Facebook, Amazon and many other global giants had witnessed downtime due to human errors, hackers or other technical glitches. Cloud performance monitoring is much more than monitoring disk, VR memory or CPU usage. Cloud MSPs have expertise in proactive monitoring strategy that includes monitoring performance, security, throughput, uptime, capacity, SLAs, KPIs, user metrics, log files and more. End-to-end monitoring of infrastructure is essential to optimize performance, put an alert mechanism in place for detection of issues, reduce downtime, and monitor network traffic and efficient scheduling of maintenance. Cloud Managed Service Partners make effective use of available tools like New Relic for server monitoring, Pingdom for application monitoring, PagerDuty for alerts and more. 2. **Security** In 2016, the cost associated with IT breaches averaged $ 2.5mn per incident. One of the recent incidents being hackers leaking the much-awaited episodes of Game of Thrones. Though fans lapped it up, HBO faced some serious security lag issues. Security breaches not only costs dollars and customers but also brand reputation can go for a complete toss. A comprehensive cloud security management strategy is important to tackle outages, data loss or security threat. More often than not, internal IT resources are not adequately skilled for managing these cloud security threats. Partnering with MSP’s that brings value to the table with the experience they have in managing cloud environment is a smart strategy. The device data security strategy that is specific to the client cloud environment. MSPs are competent at developing, deploying, implementing and managing these security controls. Specialized service providers like Cloud MSPs are ideal partners to tackle the rising number of attacks and threats. 3. **Disaster/Recovery Management** Business Continuity is essential even during massive outages. One of the leading services provided by cloud MSPs is disaster management. These MSPs design data centres and networks that are resilient enough to maintain business continuity even during disasters with minimal downtime, ensuring that your data is secure across all services and applications. 4. **Replica management** Data replication across multiple sites in the cloud has become a go-to strategy to ensure optimal performance in terms of load balancing, response time and availability. Replication can markedly bring down access latency as well as bandwidth consumption as it increases resource availability, brings in consistency and reliability. The advantage associated with replication management is that it is a proactive approach towards tackling system failure. However, replication management is not an easy task and comes with maintenance overhead. It is difficult to execute in-house, hence outsourcing replica management to cloud MSPs can make data management simpler for organizations. Cloud MSPs have the required expertise to handle data replication. Replica management depends on storage requirement, load variance, latency, and the probability of failure and service time. Public Cloud Managed Service Providers ensure data consistency during the replication process, monitors downtime during new replica creation, takes care of replica storage maintenance, decreases latency time, balances workload, minimizes execution time, ensures scalability and availability and fault tolerance. 5. **Compliance** Many organizations need to follow industry specific rules and regulations for their IT initiatives, for privacy, information security and reporting. The Banking/Financial Services industry and healthcare industry, for instance, have complex compliance checklist to follow. Alliance with cloud managed service partners can significantly reduce the burden of compliance from the in-house team. Managed service providers sometimes have a vertical specific expertise and are thorough with industry specific regulations. They can provide the right systems, reports, and processes to ensure regulatory compliance. Cloud Managed Services Companies have numerous other benefits to offer. Their 24X7 help desk comes in handy when it comes to managing untoward circumstances. Nowadays all Cloud MSPs provide around the clock services. These MSPs provide reactive and proactive management of issues that are fixed within the service SLA. Organizations have a host of services to choose from when partnering with a Cloud Managed Service providers- Managed Infrastructure Services, Managed Network Services, Managed Security Services, Managed Data Center services, Managed Mobility Services and Managed Communication Services. Depending on your cloud strategy you can avail any permutation and combination of these services or choose to avail end-to-end Cloud Managed Services. Take advantage of the cloud without taking on the liability of maintaining and managing cloud deployment, by partnering with a Cloud MSP. Cloud MSPs can significantly complement your in-house resources with access to their technical expertise. If you have any other queries on Cloud Managed Service Providers, feel free to comment in the section below. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents From beginning as a business unit and AWS consulting partner under our then-parent company, TO THE NEW, in 2009, to emerging as an industry leader in cloud cost optimization, CloudKeeper has come a long way. What started as an AWS-focused reseller arm soon began evolving into something much larger. We’re now a 350+ strong team and have already 2025 has been one of the most exciting chapters in our story, marked by heavy Gen AI investments, expansion into new geography, major product innovations & advancements, all while strengthening our team. This blog gives you a **wrap-up of our year** and our game plan for the next year. ## **Redefining Innovation with Two Industry-First Product Launches** 2025 was a landmark year for CloudKeeper as we introduced **two first-of-their-kind product innovations** , redefining how enterprises approach cloud cost optimization and FinOps at scale. * ### **The Industry’s First Fully Automated AWS Usage Optimization Platform** Within the very first month of the year, we kicked off with the launch of Delivering 150+ actionable recommendations across 50+ AWS services, Tuner offers the widest coverage in the industry, optimizing nearly 90% of an organization’s AWS bill. It’s the * ### **The Industry’s First All-in-One FinOps Platform Suite** CloudKeeper introduced the Going beyond traditional FinOps tools, it also provides powerful value-adds like GenAI-powered assistance, expert architecture reviews, and 24×7 cloud support, making it the most comprehensive, end-to-end FinOps platform for modern cloud enterprises. Together, these launches marked a decisive shift from fragmented tools to intelligent, outcome-driven cloud financial management, reinforcing CloudKeeper’s position at the forefront of FinOps innovation. ## **Strengthening Generative AI Capabilities with LensGPT & GenAI Launchpad** We launched the **idea to proof of concept up to 10× faster**. This year, we have put a strong focus on deepening our GenAI capabilities with a simple idea in mind - make cloud cost intelligence as easy as having a conversation. With It was a fundamental shift in how teams interact with cloud financial data—bringing clarity, speed, and intelligence right to where decisions are made. We also launched our internal **AI Center of Excellence** backed by a**20-member full-stack team**. The team is focused on applied research - turning AI innovations into real-world use cases that are practical, scalable, and easy for teams to adopt. ## **Our Growing Dream Team** CloudKeeper is now 350+ strong - and counting! 2025 marked a year of strategic talent expansion. Alongside welcoming high-energy graduates, we strengthened A key highlight was the addition of visionary leaders who will shape CloudKeeper’s next phase of growth: Together, this leadership expansion reinforces our focus on scaling globally, building a strong product platform, and creating long-term value for customers and teams alike. ## **North America Momentum** We Led by Currently, **we are serving 150+ North American customers (35% of global customer base)** across tech, retail, healthcare, and financial services, contributing to 42% worldwide revenue share. ## **Deepening GCP Capabilities; Elevating Multi-Cloud Management** In 2025, we strengthened We launched With these capabilities in place, CloudKeeper is fully equipped to support enterprises across every stage of their GCP journey, spanning: * Cloud cost visibility * Cost optimization * Architecture reviews * 24/7 cloud support * GCP migration/modernization and much more…! This makes us one of the strongest multi-cloud management & FinOps partners. ## **Awards & Industry Recognitions** * **Great Place to Work™ Certification:** Earned the prestigious certification, highlighting CloudKeeper’s commitment to a thriving workplace. * **IDC MarketScape:** Recognized as a **Major Player** in the Worldwide FinOps Cloud Cost Optimization Multicloud 2025 Vendor Assessment. * **G2 Cloud Cost Management Leader:** Consistently named **a leader across all seasonal reports.** * **Customer Satisfaction:** Achieved a **100% G2 satisfaction score** , reflecting strong customer trust and impact. * **Everest Group PEAK Matrix® 2025:** Named a **Major Contender** in FinOps Cost Management Products. * **AWS Recognition:** Recognized by AWS for driving the highest-value new launches in 2025. * **Competency:** Officially achieved the Amazon ECS Service Delivery competency. _We’re ending the year on one of our happiest notes yet**- ranked #1 in the G2 Winter Cloud Cost Management Report across 60+ tools,** a testament to our team, innovation, and customer impact._ ## **CloudKeeper’s Flagship Research Report & Cloud Fitness Challenge** We released our **Built on data from 500+ organizations, combined with perspectives from leading FinOps experts** , the report outlined the next era of cloud financial governance. The findings from research highlighted that _97% of teams miss critical savings_ & we've found _six-figure gaps in "fully optimized"_ companies. That insight led to the launch of the **uncover blind spots, even in “fully optimized” environments.** ## **To Sum Up** 2025 was a year of strategic expansion - We entered new markets, strengthened multi-cloud capabilities, grew our leadership team significantly, and continued to innovate across our product suite. 2026 is shaping up to be just as exciting for the cloud ecosystem. CloudKeeper will continue leading the way in cloud management while helping customers operate efficiently and sustainably. Here’s to good times ahead - for our customers and for CloudKeeper. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 11 11 Table of Contents Imagine you run a rideshare company along the likes of Uber and Lyft. The most important question you would ask yourself and your team would be “Are we actually making profits on each ride?”. It's a bit tricky to make sense of, given the costs like fuel, vehicle maintenance, technology licenses, and driver payments against each fare. This is where unit economics swoops in and saves the day by breaking down revenues and costs per unit. Going by the above example, the metrics could be costs and revenue per ride, which can pinpoint exactly how much profit or loss each ride delivers to the company. This further helps the company refine pricing strategies or trim unnecessary costs. As you might have understood, unit economics is the analysis of the profitability of a single unit or transaction within a business, where the unit is any quantifiable item that brings in value. Monitoring unit economics makes it easier to assess the profitability of the business at a granular level and do forecasts like break-even points and gross margin. Unit economics is an important concept applicable across industries, especially for companies venturing into new marketing or scaling their business. In the cloud computing sphere, where costs can swing dramatically in response to demand, the unit economics concept can enhance cloud cost optimization and help companies No wonder the FinOps Foundation has a whole unit economics Working Group dedicated to designing resources and frameworks that help a universal implementation of these concepts. Let’s learn more about cloud unit economics. ## **What exactly is Cloud Unit Economics?** At a fundamental level, cloud or FinOps unit economics is all about getting the most value out of every unit or transaction of the business and every dollar spent in the cloud. It is a cost management strategy that measures and analyzes the marginal spending and revenues associated with cloud-based businesses. By using multiple unit metrics, organizations can forecast, with greater accuracy, the point where their cloud investments would break even and start making money for the business. The strategy involves The profitability of cloud investments in this scenario will be calculated as: ### **Profit per Server Hour = Revenue per Server Hour - Cost per Server Hour** Here: * Revenue per Server Hour represents the income generated from each server hour used. * Cost per Server Hour is the expense incurred for each server hour used. This equation helps a business evaluate the profitability and financial performance in relation to server utilization for a product or service delivered to the customer. ## **Why is Cloud Unit Economics Important?** The variable cost model remains one of the most attractive features and at the same time, one of the main challenges of commercial usage of cloud. While the cloud costs are as dynamic as the weather, linking them to quantifiable units, like per customer or per feature costs, makes it easier to manage from a cloud finops perspective. These metrics allow for data-backed discussions that align engineering, finance, and business units under a common goal: maximizing cloud efficiency and business value for day-to-day operations, new feature releases, scaling up business, and more. Didn’t you notice that despite having a crucial role, cloud unit economics is not listed as one of ## **Cloud Unit Economics in the Non-profit Sector** While most of the Consider a non-profit dedicated to educational outreach. To measure effectiveness, they could adopt a cost-per-educational-session-delivered metric. This approach helps the organization implement FinOps best practices to optimize cloud spending used for hosting virtual classrooms and distributing material. This ensures more funds are available to expand their educational programs. This adaptability across different domains and types of organizations underscores the universality of cloud unit economics and its critical role in any cloud finops strategy. ## **Benefits of Cloud Unit Economics** Cloud unit economics offers one of the most effective ways to make data-driven decisions regarding your cloud investments. The advantages it offers are a multitude which include: * **Clarity on Financial Performance:** It helps management, investors and employees get a clear picture of the company’s financial performance, aiding their strategic decision-making. * **Forecasting Profitability:** By analyzing unit metrics, businesses can predict profitability and identify the factors that affect profit margins, enabling them to make timely optimizations. * **Cost Optimization Planning:** Helps companies determine if their products are architected and priced appropriately, unveiling areas for cloud cost optimization efforts. * **Evaluating Product Potential:** Businesses could use this concept to understand which products and services are most profitable, supporting product roadmap decisions and engineering priorities. * **Promoting Responsible Usage:** It allows for the measurement of end-user behavior impact on cloud costs, be it the employee or the customers. The related metrics will help encourage cost-conscious behavior and optimize resource utilization. * **Improve Cloud FinOps Practices:** Cloud unit economics ## **Common Use Case Scenarios** The cloud unit economics concepts are universal and can be applied across businesses of all types, shapes, and sizes. Here are some sample use case scenarios where you can use it: * A Cybersecurity SaaS company measuring **cost per analyzed security event** to understand cost-to-serve and pricing strategies. * A Municipal Transportation Authority measuring **cost per passenger** for a mobile ticketing application to assess app usage impact on costs. * An E-commerce Platform analyzing **cost per order** to forecast expenses during peak shopping seasons. * A Food Delivery Service evaluates **cost per delivery by time of day** to optimize delivery route efficiency. * A Project Management Software company tracking **cost per active project team** to identify high-cost clients. Though the concept of unit economics is domain-agnostic, the specific metrics used do not follow a one-size-fits-all approach. The metrics that work for you would be a function of what you do, your industry, target market, company size, and the aspects unique to the business. Unit metrics could also vary according to the measurement categories. Here are some examples: Source: The FinOps Foundation ## **Getting Started with Cloud Unit Economics** So, you have a foundational understanding of the concept and you are ready to dive in. Do you go headfirst, do a flip, or land on your back? Let’s break it down. ### **When to Get Started** Think of it as setting up the GPS before hitting the road. You want to figure out your destination and the best route to get there. In this case, the destination is understanding your cloud spending better, and the route involves defining those key metrics. So, when do you start? Right from the get-go! Don't wait until your cloud bill is through the roof to figure out what's going on. The earlier you start, the better prepared you'll be to ### **How to Get Started** Implementing cloud unit economics practices requires a strong unit cost model or in simple terms, the initial set of unit cost metrics. You should seek out help from within your organization from those who are already thinking about this and enlist their support. Don't be afraid to put your ideas out there, even if they're not perfect. Most of the time, the practice starts with the involvement of Sales and Marketing personnel, who can understand the business better from the customer perspective. They can help link cloud spending with metrics such as Customer Acquisition Cost (CAC), Customer Life Time Value (LTV), and Customer Retention Cost (CRC) (which are quite well-known these days, thanks to the Shark Tanks and Dragon’s Dens of the world). * **Defining the First Set of Metrics** When it comes to defining your metrics, there's no one-size-fits-all solution. You should tailor them to your organization's unique needs and workflows. And most probably, there won’t be any single central metric that rules all others. It’s recommended to have metrics that are not static, and that evolve according to business objectives, new insights gained, or any other reason that brings in The metric should be actionable and should have a certain level of correlation between its value and the use of cloud resources. * **Deciding Who Collects the Data** The data collection policies depend on the objectives, culture, and team preferences. It is also a choice between pulling or pushing the data required. Pulling data involves retrieving it when needed, typically user-friendly but may not suit complex metrics. Pushing data entails sending it to a centralized dashboard automatically, which may require technical expertise. Regardless of the method, centralizing metrics for analysis is essential. The crucial step is to begin the process, learning as you go, and sharing cloud finops insights to foster broader adoption of unit cost metrics in cloud operations. It is also important to seek feedback regularly on the practicality and usefulness of the metric from the stakeholder perspective. This is to make sure * **Making Company-Specific Optimizations** Once the metrics are set up and the data collection plan is decided upon, it’s time to level up with any organization-specific adjustments. One of the crucial aspects here is how the responsibilities would be mapped across various cloud FinOps Personas. Here is an image briefly depicting who should own what. Source: The FinOps Foundation Stay flexible, as this isn’t a rigid or unchangeable mapping. Remember, there’s no one right way to do this. Keep at what’s working for your organization and have those lines of communication open. However, it is always advisable to keep the cloud FinOps team at the center, which would be responsible for maintaining the unit metrics repository and ## **Potential Roadblocks and Challenges** Implementing Cloud unit economics practices in an organization might not always be a cakewalk. There are a lot of factors that might work against you while integrating unit economics into cloud cost management. **Knowing What to Measure:** Choosing the right metrics is crucial for accurately assessing cloud spend and resource utilization. For example, opting for a cost-per-GB metric may overlook efficiencies gained through data compression techniques, leading to misleading cost assessments. Collaborating with stakeholders to identify metrics aligned with business value is essential for effective cloud cost optimization. **Defining Financial Inputs:** Organizations must decide whether to incorporate discounts, negotiated rates, shared costs, and other operational expenses into their cost calculations. This necessitates thorough consideration of various factors, such as **The Number of Metrics Required:** Determining the number of metrics required is also a critical challenge. Striking a balance between granularity and simplicity is essential, as too many metrics can overwhelm stakeholders, while too few may provide insufficient insights. Embracing the principle of "good enough" enables organizations to achieve meaningful cost insights without impacting the results of FinOps best practices. Despite the challenges inherent in adopting cloud unit economics, the benefits far outweigh these obstacles. The rewards in terms of cost efficiency and operational excellence make it a worthwhile endeavor for organizations seeking to thrive in the cloud computing landscape. ## **How CloudKeeper Saves You The Effort** As you might now be aware of all the fundamental aspects of cloud unit economics, the best practices, and the challenges that might dampen its implementation, you should also know that there are better ways to get things rolling. With CloudKeeper's comprehensive Cloud FinOps Consulting & Support, you can trust in the implementation of the right unit metrics, tailored to your organization's needs. Backed by 15 years of experience and a dedicated team of 300+ cloud and DevOps experts, CloudKeeper has a proven track record of delivering substantial savings for countless organizations. Through our FinOps Consulting and Support service, we empower businesses with FinOps best practices to gain deeper insights into their cloud infrastructure, optimize key metrics, and maximize returns on cloud investments. ## **Conclusion** While challenges such as measurement clarity and metric selection exist, the benefits of cloud unit economics far outweigh them. Partnering with experienced Cloud FinOps Partners can streamline implementation, offering expertise and support throughout the journey. With the right guidance and strategies in place, organizations can optimize their cloud investments, achieve substantial savings, and enhance their financial performance. _Did you know CloudKeeper offers FinOps Consulting and Support completely free if you sign up for any of our solutions including CloudKeeper AZ and CloudKeeper Auto?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents _G2’s Winter 2023 Grid® Report is here, and CloudKeeper stands strong in the top 3 spots for best cloud cost management solutions worldwide._ **Grid® for Cloud Cost Management Software** (Source: G2 Winter 2023 Grid® Report) **Why does the G2 Grid Report matter?** Every quarter The Grid® is a representation of the finest & leading players in the category, and we’re glad CloudKeeper shines bright as a leader among them. **What makes users love CloudKeeper?** Customer satisfaction has always been a top priority for CloudKeeper. With our customers’ support and feedback, we have grown to a customer base of 250+ global brands while managing 100 Mn+ AWS billing annually. Subsequently, CloudKeeper has been named a leader based on receiving a high customer satisfaction score and having a large market presence. We have been rated #1 in user satisfaction and earned the top 3 spots in multiple parameters like compliance, ease of use, ease of setup, and ease of admin. CloudKeeper guarantees savings of up to 15% on the entire AWS cloud bill without any commitment from the user. We also help our customers with granular insights on their AWS cloud usage and periodic recommendations & optimization guidance by AWS-certified engineers. Some of the most-loved and highest-rated features of CloudKeeper are spend forecasting & optimization, usage monitoring, dashboards, & visualizations. Furthermore, 92% of users have highly recommended CloudKeeper, while 97% of users have rated it 4 stars and more. The satisfaction score given by G2 is based on six major attributes(refer to the below images) and CloudKeeper emerges as a champion among its competitors. CloudKeeper also saw a lot of success in the Mid-Market space, being named #1 for Compliance, Ease of Setup, and Spend Tracking. A few highlights from what customers are saying about CloudKeeper: **“One of the best decisions we made“** - Keshav Murali Head of Engineering **“We are really happy with CloudKeeper for the insight we get using it.“** - Saurabh Pandey Head(IT Infrastructure) **“Using the CloudKeeper solution we were able to save between 7 to 10% on our AWS spend“** - Verified Customer **“We've found the product valuable, both for insights and savings. The service & support is excellent”** - Verified Customer **“Compared to other competition, their reports are more granular, and even the pricing is very lucrative”** - Ashu Gupta CTO **A note of Gratitude** We are, as always, immensely grateful to our customers for choosing CloudKeeper as their cloud savings and growth partner. With the continued support and trust of customers, CloudKeeper can’t wait to set the bar high and serve the best as it gears to level up with some exciting & new features this year. Read the full G2 Grid® Winter 2023 report Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents The G2 Spring 2023 report is here, and CloudKeeper has a reason to celebrate again. ## **Leading the way in cloud cost management** Customers are at the heart of everything we do at CloudKeeper. With over 12 years of rich experience in the AWS cloud and FinOps ecosystem, we have grown over a global customer base of 300+ while delivering savings of over $100 mn on AWS Bills. The love and trust of our customers have made CloudKeeper earn multiple awards including: * Best Support * Easiest to Use * Easiest To Do Business With * Best Usability, Easiest Admin * Easiest Setup These G2 badges serve as a testament to CloudKeeper's hard work and dedication and demonstrate that its solutions are well-received by customers. We have earned a spot in the top 3 rankings for multiple categories like - User Satisfaction, Compliance, Ease of Use, Spend Forecasting and Optimization, and Market Presence. 98% of users have rated 4 or more stars for CloudKeeper, with 91% expressing their willingness to strongly recommend CloudKeeper. The solution also garnered users’ love across mid-market and small business spaces for cloud cost management. It is ranked #1 in the mid-market and #2 in the small business space, showcasing its unwavering commitment to providing a seamless FinOps experience to a wide range of businesses. CloudKeeper showcases its strength in various attributes which are majorly considered to determine the satisfaction score in the G2 report for cloud cost management. The performance of CloudKeeper is illustrated in the accompanying images below. ## **Why should you consider G2 rankings?** The report is based on verified and authentic user reviews, offering an unbiased view of the world's top software companies. G2 employs an algorithm that considers genuine reviews and data collected from various online sources and social media networks to assess products in the cloud cost management category. The Grid® represents the most prominent and leading players in the category, and we are thrilled CloudKeeper stands out as a leader among the competitors, once again. The Vice President & Managing Director of G2 Asia Pacific, Chris Perrine also praised CloudKeeper on these outstanding results in G2's Spring 2023 reports. ## **A note of gratitude for our customers** CloudKeeper expresses heartfelt gratitude to all its valuable customers for trusting them as their growth partners in the journey of cloud cost management. It’s the love and trust of our 300+ customers that drive us to be the best in the FinOps domain. This year marks a new wave of growth and advancement, as we come up with a breakthrough solution The Read the full coverage of CloudKeeper’s feat in the G2 Spring 2023 Report Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents Whenever new resources are created in the cloud, one of the recurring tasks of Each time new resources are added, these scripts must be updated, and error handling must be implemented to account for resources that may be deleted, ensuring the scheduling process remains uninterrupted for other resources. This approach requires scripting expertise and ongoing maintenance, as any team member wanting to schedule a resource must modify the script. To simplify managing cloud infrastructure, AWS offers straightforward solutions for starting and stopping resources using AWS APIs and custom templates, eliminating the need for complex, manually maintained scripts. When it comes to automating infrastructure operations, both ## **AWS EventBridge Scheduler vs. CloudKeeper Tuner Scheduler** **A Deep Dive into Technical Feature Comparison** Here’s a technical breakdown of how CloudKeeper Tuner Scheduler and AWS EventBridge Scheduler differ across key scheduling features. ### **1. Scheduling Features** **CloudKeeper Tuner Scheduler:** Uses a custom template for scheduling, streamlining the process for supported resources. This makes scheduling start/stop actions quick and straightforward, especially for users focused on resource optimization. **AWS EventBridge Scheduler:** Offers two scheduling options: * One-time (one-off) schedules * Recurring schedules using cron or rate expressions This flexibility supports a wide range of automation scenarios, from simple to complex, and enables precise time-based control. ### **2. Retry Mechanism and Failure Handling** **CloudKeeper Tuner Scheduler:** Has a backend retry mechanism. If throttling occurs, retries are visible in the event dashboard. Once the default retry limit is reached, it waits for the next scheduled interval before attempting again. There is no dead-letter queue (DLQ) integration. **AWS EventBridge Scheduler:** Provides advanced delivery controls: * Configurable maximum event age * Retry attempts with delayed retries * Failed events can be moved to dead-letter queues (DLQs) for further analysis or reprocessing. ### **3. Resource Identification** **CloudKeeper Tuner Scheduler:** Automatically fetches resources for start/stop operations. Users don’t need to manually input instance IDs or ARNs, simplifying setup for supported resource types. **AWS EventBridge Scheduler:** Requires explicit resource identifiers (such as instance IDs or ARNs) in the API payload for each scheduled action. ### **4. Supported Operations** **CloudKeeper Tuner Scheduler:** Focused solely on start/stop operations for a select set of AWS resources (e.g., EC2, RDS, ECS). **AWS EventBridge Scheduler:** Supports a much broader range of operations, including: * Running ECS tasks * Invoking Lambda functions * Triggering Step Functions * Sending messages to SQS/SNS * Any API operation can be scheduled, provided the correct resource identifier is supplied. ### **5. Scheduler Setup** **CloudKeeper Tuner Scheduler:** Start/stop operations are configured through a single template, making setup fast and user-friendly for supported actions. **AWS EventBridge Scheduler:** Requires creation of separate schedules for each action (e.g., one for start, one for stop), which can increase setup complexity for resource lifecycle management. ### **6. Batching and State Management** **CloudKeeper Tuner Scheduler:** Maintains the state of resources before and after scheduling, ensuring resources return to their original state after scheduled actions. This is particularly helpful for environments where state consistency is critical. **AWS EventBridge Scheduler:** Some AWS APIs support batch operations (e.g., starting/stopping multiple EC2 instances at once). For Auto Scaling Groups, users must specify desired, max, and min capacities, but the scheduler does not maintain resource state. For ECS, separate schedules are needed per service. ### **7. Grouping** **CloudKeeper Tuner Scheduler:** Does not support grouping of schedules. Each schedule is managed individually. **AWS EventBridge Scheduler:** Supports Scheduler Groups for logical organization (e.g., by environment or application), making it easier to manage large numbers of schedules at scale. ### **8. Flexible Time Window** **CloudKeeper Tuner Scheduler:** Does not support flexible time windows; actions occur at the scheduled time. **AWS EventBridge Scheduler:** Includes a flexible time window feature, allowing scheduled actions to execute within a defined interval (e.g., between 9:00–9:05 PM). This helps spread out actions, reduces throttling, and improves reliability for large-scale operations. Let us understand with an example. ## **Use Case** If we want to start an ASG every weekday at 9 AM using AWS Eventbridge Scheduler: **Step 1: Specify Schedule Details** * **Provide a Name** for this schedule ( Non-ProdASG_Start) * **Description:** Optionally, provide a description like **Increase ASG capacity during business hours.** * **Select Schedule Group:** Each schedule needs to be placed in a schedule group. By default, a schedule is placed in the 'Default' group. You can also create your schedule group. You can only add tags to a schedule group, not a schedule. * **Choose a schedule pattern** * Schedule type: Select "Recurring". * Schedule pattern: Choose "Cron expression". * Cron expression: Enter a cron expression that defines when the scaling action should occur. For example: * 0 9 ? * MON-FRI * — Triggers at 9:00 AM UTC, Monday through Friday. * Time zone: Select your desired time zone, such as Asia/Kolkata. * Set a cron expression, such as cron(0 9 ? * MON-FRI *) for 9 AM on weekdays. **Step 2: Select Target** ● Select the target type as AWS SDK operation ● Choose: Service: EC2 Auto Scaling Action: UpdateAutoScalingGroup Payload: { "AutoScalingGroupName": "ck-dev4-ue1-ecs-asg", "MinSize": 1, "MaxSize": 3, "DesiredCapacity": 1 **Step 3: Setting** ● Configure retry behavior (e.g., 3 retries). ● Add a Dead Letter Queue (DLQ) if needed for failure tracking. ● Create a Role that has access to Update AutoScaling Group. Here, we are using "*" for the resource so that the role can be used to start and stop any Auto Scaling Group. Whenever you want to perform start or stop actions on an ASG, you can use this role to set up the schedule. **Step 4: Review and create** **●** Confirm details and click Create schedule. Schedule created. It will now start your ASG every weekday at 9 AM with Give Configuration ( Maxsize, DesiredCapacity, Minsize) **Note: If you want to stop Same ASG at a specified time, same as stop operation, you need to create a new schedule for the Stop operation. With the below payload** Payload: { "AutoScalingGroupName": "ck-dev4-ue1-ecs-asg", "MinSize": 0, "MaxSize": 0, "DesiredCapacity": 0 } This has a disadvantage for some APIs that do not support operations on bulk resources—such as ASG and ECS tasks. You need to create a separate scheduler for each ASG with its own configuration, which adds more steps and overhead when setting up resource scheduling. ### **Here comes CloudKeeper Tuner Scheduler with a simplified approach** CloudKeeper Tuner Scheduler takes a simplified, user-friendly approach to resource scheduling, eliminating unnecessary complexity and ensuring full transparency in operations. It’s an excellent choice for teams aiming to automate cloud management, cut costs, and retain control—all without dealing with complicated setup processes. Thanks to its smart design, built-in state awareness, and robust retry capabilities, Tuner Scheduler guarantees that your cloud resources are managed efficiently and reliably. Whether you’re overseeing a handful or hundreds of instances, Tuner Scheduler transforms automation into a seamless, “set it and forget it” process. This allows you to concentrate on driving innovation, while your cloud resources are automatically managed in the background. ## **Getting Started is Easy** Scheduling your cloud resources with CloudKeeper Tuner takes just a few steps: Here’s how you can get started in a few easy steps: **1. Log in:** Log into your CloudKeeper Tuner dashboard. **2. Give Scheduler Access:** Give Start and Stop Access to Scheduler **3. Enable Scheduler:** * Enable Scheduler for the Account and add the default configuration (start/ Stop time and days).This will be inherited by all the resources in the account eligible for scheduling. * Head to the scheduler tab and choose the resource type (EC2, RDS, etc.) you want to auto start & stop. * Enable the scheduler for the resource, and you can set the time for start and/or stop operations at the resource level as well. **4. Auto Schedule Your Resources:** Tuner will immediately begin monitoring and executing start and stop actions based on your schedule. **5. Monitor Savings:** Use the dashboard to track the overall scheduling and savings achieved. ## **Scheduling Made Easy with Tuner** **1. Easy and Simple Setup -** Schedule start/stop actions quickly using a single template—no complex scripts or multiple workflows. **2. Auto Resource Detection -** Tuner automatically identifies resources, so you don’t need to enter instance IDs or ARNs manually. This feature is especially valuable for managing large inventories or dynamic environments. **3. Smart Retry Handling -** If an operation fails, Tuner retries the action intelligently. Once the default retry limit is reached, the scheduler waits for the next scheduled cycle, avoiding unnecessary system load. **4. Remembers Resource State -** Tuner keeps track of resource states to avoid unnecessary actions, even if changes happen manually. This is especially useful in environments where manual overrides may occur, as the system ensures predictable behavior without duplicating actions. **5. Optimized for Start/Stop -** Perfect for automating non-production shutdowns, helping you with cloud cost savings easily. **A Glimpse of CloudKeeper Tuner's Scheduler** ## **Conclusion** ● CloudKeeper Tuner Scheduler is purpose-built for ● AWS EventBridge Scheduler is a powerful, general-purpose scheduling engine with advanced features like flexible time windows, DLQ integration, and broad API support. It is best suited for complex automation scenarios, event-driven architectures, and environments requiring fine-grained scheduling control and grouping. ● Choose CloudKeeper Tuner Scheduler for simplicity and cloud cost optimization ● Choose AWS EventBridge Scheduler for advanced, large-scale automation and orchestration. Ready to automate your cloud savings? Try scheduling with Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents As 2024 comes to a close, we reflect on a year that has truly reshaped CloudKeeper. This has been a year of remarkable growth and meaningful impact—for our team, our customers, and our community. From becoming an independent organization to expanding our product offerings and hosting breakthrough events, 2024 has been packed with milestones that have set us on an exciting path forward. Here's a look at the key moments that made this year unforgettable. ## **A New Chapter: Becoming an Independent Organization** One of the key milestones this year was our transformation from a business unit at TO THE NEW, an 8-time GPTW winner, into a fully independent organization. With a growing team of 250+ CKers and counting, we are proud to carry forward this rich legacy while shaping our unique identity. This transformation stands as a testament to the unwavering trust and support of our valued customers. As part of this transformation, we also launched a brand-new website with a sleek, intuitive design. The aim was to enhance the user experience while clearly reflecting our identity as a comprehensive ## **Expanding Horizons with WiseOps Acquisition** One of the most notable milestones of this year was the addition of WiseOps, now known as ## **Growing Stronger Globally** As part of our growth strategy, we’ve also expanded our presence internationally, opening our U.S. office. As we continue to scale, we’re looking forward to expanding our presence in the North American (NAMER) region, strengthening our ability to serve customers. ## **Delivering Measurable Results for our customers: Impacting the Bottom Line** Our favorite moments are always when we truly make a difference for our customers. Here’s what the numbers speak for themselves: These results are why we do what we do—to help businesses thrive by taking control of their cloud costs. ## **Strengthening our multi-cloud capabilities with GCP Partnership** This year, CloudKeeper became an official Google Cloud Partner! In just a short span of 3 months, we welcomed over 10 new GCP customers, solidifying our position as a trusted With the increasing demand for multi-cloud cost optimization partners, CloudKeeper is committed to providing comprehensive solutions across all major cloud providers - AWS, Azure, and GCP. ## **Our Enhanced Suite of Cloud Cost Optimization Services** We expanded our ## **Supercharging our product capabilities to make cost management more effortless** We made our products better, smarter, and more impactful. Here are some exciting updates we rolled out for our CloudKeeper Lens, our visibility platform: * CloudKeeper Lens for Multi-Cloud: We extended our Lens capabilities to support Azure and GCP. * * Buying/ Renewal of Reserved Instances can now be effortlessly performed through Lens. **A Glimpse of Hourly Dashboard in CloudKeeper Lens** ## **Thought Leadership moments that made an impact** **Our first self-hosted physical event:** Our inaugural self-hosted event, AWS EDP Connect, in Bangalore, was a milestone moment for CloudKeeper. It brought together cloud experts, industry leaders, customers, partners, and top analysts for an engaging day of valuable insights and thought-provoking discussions. Through this event, many attendees discovered and got a clear understanding of how to **A noteworthy highlight** : _CloudKeeper EDP+ has emerged as one of the fastest-growing and most favorite solutions among our customers. With its unparalleled benefits over AWS EDP, and offering larger discounts at lower commitments, we’ve seen a significant increase in the number of new CloudKeeper EDP+ customers, this year._ **Launched our podcast series:** We launched " So far, we’ve released three exciting episodes, featuring thought leaders and pioneers in the FinOps and cloud space including Rakesh Pathi, FinOps Lead at Invesco, Cristian Măgherușan-Stanciu, Founder of Leaner Cloud, and Victor Garcia, Founder of FinOps Weekly. Each episode has been an exclusive conversation with Praneet Chandra, Senior Director at CloudKeeper, diving deep into actionable strategies and thought-provoking discussions. We’re thrilled by the response so far and are excited to bring more episodes that inspire, educate, and empower businesses in their cloud cost optimization journey. **An exclusive e-book on FinOps Landscape:** We published an in-depth ## **Acknowledged, Recognized, Inspired** Recognition always feels great, and this year we were honored with some remarkable achievements. ## **A Note of Gratitude and Looking Ahead** **To our customers, partners, and team—thank you** for making this year so special and being a part of our journey! Your unwavering support and trust have been the cornerstone of our success, and we couldn’t have achieved any of this without you. As we step into 2025, we’re more determined than ever to push boundaries and redefine what’s possible in cloud cost optimization while strengthening our relationships with customers and partners. From launching our Cloud Usage Optimisation Platform to enhancing our service capabilities to a whole new level, there are so many things in line and we can’t wait to share them with you. We will be investing heavily in enhancing our product portfolio, with advanced capabilities and integrations. The aim is to solidify our position as the go-to partner in the market that helps customers tackle any challenge in the cloud cost optimization landscape be it rate, usage, or process optimization. We will also expand our reach through strategic partnerships and by leveraging the cloud marketplace to connect with a wider audience. Here’s to creating impact and achieving even more together in 2025! Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Optimizing non-production environments on AWS is a critical task for organizations looking for cloud cost savings, improved performance, and streamline operations. It is important to note, however, that there are some mistakes that can result in unexpected costs and performance problems. In this blog post, we will discuss some of the common mistakes to avoid when optimizing non-production environments on AWS for cost and performance while avoiding potential pitfalls. ## **AWS cost reduction strategies while creating a non-production account** **Use a free tier account:** AWS offers a free tier account that provides access to many of their services for free for 12 months. You can use this account for your non-production environment to save costs. **Choose the right account type:** Choose an account type that best suits your needs. For example, a developer account might be sufficient for your non-production environment, which is less expensive than an enterprise account. **Use AWS organizations:** AWS organizations can help you manage multiple AWS accounts from a single dashboard. You can use this feature to consolidate multiple non-production accounts and implement cloud spend optimization by sharing resources. **Use AWS cost allocation tags:** AWS cost allocation tags can help you track and categorize spending, making it easier to identify areas where you can cut costs. **Implement cost optimization features** : AWS provides several **Use AWS Trusted Advisor:** AWS Trusted Advisor can provide recommendations to optimize your non-production environment, such as identifying unused or underutilized resources, which can help you in cloud cost savings. **Review your non-production environment regularly:** Review your non-production environment regularly with the help of AWS Cost Monitoring Tools to identify opportunities to save costs. For example, you may find that some instances are no longer needed or can be scaled down to a smaller size. ## **What are the Common Mistakes to Avoid in the Cloud Spend Optimization of Non-Production Environments ?** Reducing costs in non-production environments on AWS is a key priority for many organizations, but there are several common mistakes that can be made during the process. Failing to monitor resource usage, not using cloud spend optimization tools, using oversized or underutilized instances, not using reserved instances or savings plans, leaving instances running when not in use, not using tagging, and not considering **Not using AWS Cost Explorer:** AWS Cost Explorer is one of the most extensively used AWS Cost Monitoring tools provided by AWS that allows you to visualize, understand, and manage your AWS costs and usage. It is essential to use this tool to get a clear view of your costs and identify areas where you can save. **Not setting up cost alerts:** AWS allows you to set up cost alerts so that you can be notified when your spending exceeds a certain threshold. Failing to set up these alerts can lead to unexpected and uncontrolled expenses. **Not using reserved instances:** Reserved instances are a way to prepay for your EC2 usage and can result in significant cloud cost savings. Failing to use reserved instances is a common mistake that can lead to unnecessary expenses. **Not using auto-scaling:** **Not using spot instances:** Spot instances are instances that can be purchased at a much lower cost than on-demand instances. They are ideal for non-production environments where uptime is not critical. **Not optimizing storage:** AWS offers several storage options, each with different pricing structures. It is essential to choose the right storage option for your needs to avoid unnecessary expenses. **Not turning off resources:** Failing to turn off resources when they are not in use is a common mistake that can lead to unnecessary expenses. Your AWS cost reduction strategies must include regularly auditing your environment and turning off resources that are not needed. **Not monitoring usage:** Monitoring usage is essential to identify areas where you can save money. Failing to monitor usage can result in unexpected expenses and missed opportunities to save money. Reducing costs in non-production environments on AWS requires careful planning, monitoring, and optimization. Avoiding these common mistakes can help you save money and make the most of your AWS environment. ## **The Benefits of Optimizing Non-Production Environments on AWS** Optimizing non-production environments on AWS provides several benefits. It helps to reduce costs by identifying underutilized or unnecessary resources and Some of the additional benefits include: **Cost Savings:** Non-production environments are used for development, testing, and staging purposes, and they typically do not require the same level of resources as production environments. By optimizing these environments, businesses can reduce their infrastructure costs significantly. **Improved Efficiency:** Cloud spend optimization of non-production environments can improve the efficiency of the development process. Faster deployments and testing cycles can be achieved, which can result in faster time-to-market and improved agility. **Reduced Risk:** Non-production environments are typically used for testing and staging, which means that issues can be identified and fixed before they impact production environments. By optimizing these environments, businesses can reduce the risk of introducing bugs or other issues into production. **Better Resource Utilization:** Optimizing non-production environments is one of the most effective AWS cost-reduction strategies for businesses to ensure that resources are being used efficiently. This can help to avoid waste and ensure that resources are being used for the intended purpose. **Enhanced Collaboration:** Optimizing non-production environments can ## **Conclusion :** Optimizing non-production environments on AWS can lead to significant cost savings for organizations. By following the best practices such as monitoring resource usage, using cost optimization tools, rightsizing instances, and using reserved instances or savings plans, organizations can reduce costs while improving performance and streamlining operations. It is important to regularly review and optimize non-production environments to ensure that they are running efficiently and effectively. By doing so, organizations can achieve the benefits of cloud computing, such as scalability, flexibility, and agility, while also keeping cloud cost savings as a priority. With the right strategies and tools in place, organizations can optimize their non-production environments on AWS and achieve their business goals while staying within budget. _CloudKeeper helps you cost-optimize your entire cloud infrastructure, including non-production and testing environments and provides instant and guaranteed savings of up to 25% on your AWS bills._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 11 11 Table of Contents Managing cloud spending could become harder as your business grows. At some point, many teams look at large-volume discounts like the But these deals are tricky. If you commit too high, you overspend. If you commit too low, you lose savings. Many teams also face pressure to finish negotiations quickly, which increases the chance of mistakes. This guide explains how AWS PPA/EDP work, It is written for CEOs, CFOs, CTOs, and cloud leaders who want clarity and a realistic understanding of how these agreements work. ## **What is AWS EDP and AWS PPA?** AWS Enterprise Discount Program (EDP) and Today, AWS has standardized everything under the “PPA” label. If your previous agreement was called EDP and your current one says PPA, nothing major changed except the naming. Historically: * AWS EDP covered cross-service, organization-wide discounts. * AWS PPA was used mainly for service-specific pricing. Now, AWS simply uses PPA as the umbrella term for all ## **How does AWS PPA work in simple terms?** An AWS Private Pricing Agreement (PPA or Enterprise Discount Program (EDP) is a long-term, high-value commitment you make to AWS in exchange for Once the agreement is active, AWS tracks your usage against the committed spend. If you meet or exceed it, you enjoy the full value of the discount. If your yearly AWS usage doesn’t meet the agreed commitment, a true-up fee is applied to make up the difference. This ensures the commitment is treated as a guaranteed minimum spend and not a target usage. To qualify for an AWS PPA/EDP, organizations must meet specific baseline requirements. These usually include a minimum annual cloud spend in the $500K - $1M+ range and the ability to maintain or increase spend each year. Contract duration also plays a major role - longer terms typically ## **AWS PPA Qualification Criteria** | **Requirement** | **Details** | | --- | --- | | **Minimum Annual Spend** | Usually $500,000–$1,000,000+ in AWS usage. | | **Contract Duration** | Contract Duration 1, 3, or 5-year agreements. | | **Year-over-Year Growth** | Commitments must remain equal or higher each year. | | **Enterprise Support** | Enrollment in AWS Enterprise Support is typically mandatory. | Some benefits of the program may require specific architectural conditions - such as ensuring that both your application and control planes are fully hosted on AWS. Contract timelines are also strict: agreements must be completed by the 20th of a month to begin on the 1st of the next. Additionally, AWS allows a portion of the annual commitment - usually up to 25% - to be met through AWS Marketplace purchases. However, discounts applied by AWS such as standard service-tier discounts or promotional credits - do not count toward your annual commitment. Even if these ## **What Services Are Typically Included in an AWS PPA?** AWS PPA/EDP agreements generally cover the services enterprises rely on most for daily operations, scalability, and innovation. Since these contracts are tied to committed spend, Most enterprise workloads revolve around compute, storage, databases, and networking - making these categories central to any AWS consumption strategy. Security, AI/ML, and management tools also contribute significantly to * **Compute:** EC2, Lambda, Fargate, ECS, EKS * **Storage:** S3, EBS, EFS, FSx * **Databases & Analytics: **RDS, DynamoDB, Redshift, EMR, ElastiCache * **Networking:** VPC, Direct Connect, CloudFront, Transit Gateway * **Security:** IAM, GuardDuty, WAF, Shield * **Machine Learning & AI: **SageMaker, Bedrock, Textract * **Management Tools:** CloudWatch, CloudFormation, Systems Manager ## **What Services Are Not Included in an AWS PPA?** While AWS PPA offers broad coverage, they don’t include everything. Since these agreements are fully customized, exclusions vary by customer, region, and negotiation. Still, several categories are commonly ineligible for discounted or committed spend. Typically excluded from AWS PPA commitments: * AWS Professional Services, including * AWS Training & Certification costs * AWS IQ engagements with third-party experts * AWS Elemental Appliances & Software * Third-party messaging fees (for end-user communication) * AWS Support plans ( * Excess AWS Marketplace spend beyond the allowed threshold (commonly up to 25%) * AWS Credits of any kind, including promotional or enterprise credits _**Important Notes**_ _Since each AWS PPA/EDP is negotiated individually, coverage can shift based on your spend profile and service usage. New or highly specialized services may require specific clarification from your AWS account team. Many enterprises also work with AWS partners to access partner-led PPAs, which may offer more flexible terms and_ _._ ## **When to Start Your AWS PPA Negotiation?** Timing can influence your contract quality. Most enterprises begin negotiations when one of these conditions appears: * You are within 3 to 6 months of your current contract renewal. This gives you enough room for multiple negotiation rounds. Many deals take a few weeks instead of a few days. * Your cloud spend is scaling fast. Growing workloads often change spend patterns. If you cross certain annual spend thresholds, you may qualify for stronger discounts. * You are planning one or more big migrations. Large EC2, data, or ML workloads can shift your projected spend significantly. AWS offers incentives for customers * You need long-term cost predictability. Rapid expansion, new product launches, or entry into new regions are all good reasons to lock in pricing. * You want to align the deal with your financial year. Many finance teams prefer syncing commitments with their FY cycles. * AWS sellers are approaching a quarter or year end. Sales teams work toward targets, so this period sometimes brings more flexibility. The key idea is simple. Start early and give your team enough time to plan, review, model, and negotiate. ## **Key Elements to Negotiate in an AWS PPA** An AWS PPA has many components. Each one affects the final deal. These are the major items to review carefully. **1. Annual or multi-year spend commitment** This is the most **2. Discount structure** Your final discount is influenced by several factors. These include your total committed spend, the length of the contract, the mix of AWS services you use, future migration plans, and expected growth across regions or workloads. Discounts differ from one customer to another and are not publicly published. They are discussed and agreed upon during the negotiation process. **3. Flexibility terms** This section is often overlooked but matters a lot over a multi-year contract. You should ask for **4. Payment schedules** Payment terms can usually be discussed. Options may include annual billing, quarterly payments in some cases, partial prepayment, or spreading payments to ease cash flow. Larger contracts typically allow more flexibility. **5. Credits and migration support** AWS may provide credits to support large migrations, **6. Custom terms for emerging services** If you plan to use ## **Strategies for a Successful AWS PPA Negotiation** Good preparation leads to a better deal. These steps help you enter the **1. Study your historical usage** Look at spend patterns across EC2, S3, RDS, Lambda, and every core service. Check seasonality and business growth. This **2. Forecast your next 1 to 3 years** Use workload plans, migration timelines, and expansion goals to estimate future spend. Talk to your engineering and finance teams. Bring everyone into the forecasting process. **3. Consolidate spend across business units** If you operate multiple accounts or departments, combining them helps you reach higher thresholds and unlock better cloud pricing. **4. Ask for discounts and flexibility** Push for the best possible discount percentage. But look beyond discount numbers. Flexibility on terms, payment, and consumption can have equal value. **5. Expect multiple negotiation rounds** AWS contracts usually need 2 to 4 rounds of discussion. Going slow is better than rushing into a multi-year commitment. **6. Explore competitive options (only as needed)** Most enterprises stay with AWS. But showing that you are **7. Align with quarter deadlines when possible** Quarter ends often bring higher responsiveness from sales teams. The aim is simple. Show that you have done your homework. ## **Role of a Partner in AWS PPA Negotiations** Large enterprises often take help from A strong partner adds value in several ways. **1. Better forecasting accuracy** Partners use tools and past experience from other customers to **2. Clear understanding of discount benchmarks** Partners know what is achievable for customers with similar spend profiles. This helps you set realistic targets during negotiation. **3. Strong knowledge of contract clauses** Many clauses look simple but affect flexibility later. A partner helps you avoid common pitfalls, especially in areas like Marketplace inclusion, region usage, and service coverage. **4. End-to-end support** Planning, modeling, negotiation, review, and closure - a partner covers the full cycle so your team can stay focused on product and engineering. **5. Post-contract optimization** Signing an AWS PPA is not the end of the work. You must consume the commitment properly. A partner helps ensure you stay aligned with the contract and ## **How 50+ Enterprises Saved Millions on AWS PPA With CloudKeeper** Many organizations bring CloudKeeper into the negotiation process to reduce risk and improve outcomes. CloudKeeper has managed more than fifty AWS PPA and EDP contracts and has helped every customer CloudKeeper supports customers with: * **Smarter commitment planning** - Forecasting based on usage trends, workloads, migrations, and growth plans. * **Higher discounts and better terms** - Negotiation backed by real experience across many industries. * **End-to-end guidance** - From modeling to negotiation to final signatures. * **Continuous Support and Success Management** - A team of more than one hundred AWS specialists helps customers * * * ## **FAQs** **1. Is AWS PPA the same as AWS EDP?** Yes. AWS now uses the PPA label for all private pricing contracts. EDP is the older term. The structure and purpose remain the same. **2. How long does it take to negotiate an AWS PPA?** Most deals take a few weeks. Some can take a month or more if forecasting or contract reviews need extra time. **3. Can AWS Marketplace spend count toward my AWS PPA commitment?** Yes, some part of your commitment can include Marketplace purchases. The exact portion varies by agreement and must be confirmed during negotiation. **4. What happens if I under-consume my AWS PPA commitment?** You may lose some savings if your usage does not meet the agreed commitment. A partner can help you plan so this does not happen. **5. Are all AWS services covered in AWS PPA discounts?** Most core services are included in AWS PPA, but some newer or specialized services may not be. Always check service coverage before signing. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Ask the Cloud Expert: A Deep Dive Q&A on AWS PPA In this Q&A, CloudKeeper’s AWS PPA expert Aman Dixit shares real-world insights to help clients navigate PPAs and make smarter, cost-effective decisions. By Team CloudKeeper 05 Sep, 2025 Introducing the AWS EDP Tracker in CloudKeeper Lens AWS EDP Tracker is a real-time interactive dashboard that gives you end-to-end visibility to monitor, forecast, and optimize your EDP spend throughout its term. By Harsh Agarwal 06 May, 2025 From Good to Great: Supercharge Your AWS EDP Plan with a Partner Learn how partnering with the right AWS EDP partner can simplify the complexities of AWS EDP, helping you secure great benefits at lower commitments & cost. By Team CloudKeeper 17 May, 2024 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents ## Introduction to Multi-Cloud Management Enterprises today are adopting a According to Gartner 90% of organizations will adopt a hybrid cloud approach by 2027, highlighting the rapid shift toward distributed cloud models. This rapid adoption is driven by rising AI workloads, the need for resilience, cost pressures, and the strategic desire to avoid vendor lock-in. At the same time, IDC predicts global public cloud spending will exceed $1.35 trillion by 2027, a figure that underscores why companies urgently need a unified approach to A multi-cloud environment allows companies to leverage AWS for compute scale, GCP for analytics and AI efficiency, Azure for enterprise identity, and Kubernetes for workload portability. But these benefits can only be realized when enterprises use a multi cloud management platform capable of integrating operations, automating governance, and offering ## Why Enterprises Are Shifting to Multi-Cloud The move toward multi-cloud is intentional rather than accidental. Enterprises now recognize that no single cloud delivers optimal performance for all workloads. AI training may run most efficiently on GCP TPUs, while real-time transactional workloads may perform best on AWS, and enterprise security frameworks may rely on Azure’s identity ecosystem. A modern The Strategic Drivers Behind Multi-Cloud Adoption are : * Cost Efficiency at Scale - Cloud pricing models vary widely across providers. Without central oversight, cost structures quickly become opaque. A multi-cloud management platform provides a * Built-In Resilience and Uptime - Single-cloud outages no longer meet enterprise uptime expectations. By distributing workloads across providers and managing them through a multi-cloud management platform, organizations reduce risk, ensure continuity, and maintain performance even during regional disruptions. * Freedom from Vendor Lock-In - Companies want the freedom to adopt best-of-breed offerings. A multi-cloud strategy preserves negotiating power and flexibility while the multi cloud management platform ensures that this flexibility does not result in operational chaos. ## What are the Benefits of Multi-Cloud Management The benefits of multi-cloud management extend far beyond choice and flexibility. When supported by a multi-cloud management platform, these advantages translate into measurable financial, operational, and strategic value. * **Cost Optimization** - A multi cloud management platform gives FinOps and engineering teams complete visibility into usage patterns and cost drivers, enabling dynamic optimization of compute, storage, data transfer, and commitments. * **Built-In Resilience** - By spreading workloads across AWS, Azure, and GCP, enterprises eliminate the risk associated with regional outages or provider-specific disruptions. * **Optimized Performance** - Running the right workloads on the right cloud improves speed and efficiency, with consistent monitoring across all environments. * **Unified Governance & Compliance** -Regulatory requirements such as GDPR, HIPAA, and PCI-DSS require consistent controls regardless of cloud provider. Without a multi-cloud management platform, each cloud becomes a separate governance challenge. * **Strategic Flexibility** - As organizations grow through expansion, mergers, AI adoption, or industry-specific digital initiatives, they need a cloud foundation that does not constrain innovation. A modern multi-cloud management platform becomes the enabler of this flexibility. ## Key Features of a Multi-Cloud Management Platform A mature multi-cloud management platform acts as a unified control plane that ties together observability, automation, cost governance, security, and orchestration across AWS, Azure, GCP, Kubernetes, and hybrid infrastructures. * **Unified Visibility Across Clouds** - A multi-cloud management platform aggregates logs, metrics, traces, cost data, security findings, and performance insights into a single, coherent view. This not only improves operational efficiency but dramatically enhances cloud visibility and reduces mean time to resolve incidents. * **Automated FinOps Governance** - Continuously identifies cost inefficiencies, recommends rightsizing, forecasts usage, and optimizes commitments across dynamic pricing models. * **Policy-Based Cloud Governance** - A multi-cloud management platform enforces uniform governance through automated policy controls, compliance frameworks, and drift detection capabilities. * **Centralized Multi-Cloud Security** - Security is foundational. As multi-cloud architectures expand, so does the attack surface. The platform centralizes identity, access, vulnerability scanning, misconfiguration management, and threat detection. It establishes a unified security baseline across environments, * **Infrastructure Automation & Orchestration** - Automates provisioning and remediation using Infrastructure as Code, ensuring predictable deployments across clouds. * **Hybrid & Kubernetes Workload Management** - Support for hybrid and multi-cloud workloads, including Kubernetes multi-cloud clusters, is increasingly important. Enterprises often run containerized applications simultaneously on EKS, GKE, AKS, and on-prem Kubernetes clusters. The platform manages these environments cohesively, delivering consistent lifecycle management across all deployments. * **AI-Driven Cloud Operations** - As AI becomes deeply embedded in cloud operations, the multi-cloud management platform leverages machine learning to optimize autoscaling, detect anomalies, predict resource requirements, and drive autonomous optimization of workloads and cost structures. ## Challenges in Multi-Cloud Management Despite its advantages, multi-cloud comes with inherent challenges that cannot be addressed without a unified platform such as: * **Fragmented Visibility** - Each cloud provider exposes data differently, making it difficult to correlate performance issues, understand cost anomalies, or enforce consistent governance. A modern multi cloud management platform resolves this by offering a single data fabric across all environments. * **Multi-Cloud Skill Gaps** - Skill gaps also hinder multi-cloud success. Engineers who are specialists in AWS may lack deep knowledge of Azure networking or GCP IAM hierarchies. Without unified guardrails and automation, these skill gaps introduce operational risk. A platform reduces this dependency by standardizing workflows and providing consistent automation across clouds. * **Shadow IT Proliferation** - Shadow IT is another growing concern. Teams often deploy workloads without proper governance or tagging, leading to financial and security exposure. Centralized governance through a multi-cloud management platform eliminates unauthorized deployments and enforces compliance automatically. * **Interoperability Complexity** - Interoperability challenges arise because cloud providers use different APIs, services, and architectural approaches. Moving workloads or integrating cross-cloud data becomes complex and costly. The platform abstracts these differences and offers a common orchestration layer. * **Inconsistent Security Posture** - Security inconsistencies also surface in multi-cloud environments. IAM configurations vary widely between AWS, Azure, and GCP, and misalignments often lead to vulnerabilities. A unified platform ensures consistent multi-cloud security and reduces misconfiguration risk. ## **Best Practices for Multi-Cloud Management** Successful multi-cloud implementations are anchored in a strong operating model and a well-designed multi-cloud management platform. * The first best practice is * FinOps should be integrated from the start. Rather than treating cost control as a late-stage reporting activity, enterprises that adopt FinOps early benefit from continuous optimization, real-time cost transparency, and proactive budget enforcement. The multi cloud management platform operationalizes this discipline. * Standardizing policies across providers is equally critical. IAM, network security, encryption, and tagging standards must be uniform across all clouds. The platform ensures compliance through automated rule enforcement and drift detection. * Automation is essential for reducing complexity. From provisioning to remediation, automation ensures predictable outcomes and frees teams from low-value tasks. A multi-cloud management platform orchestrates these processes across AWS, Azure, GCP, Kubernetes, and hybrid systems. * ## Future Trends in Multi-Cloud Management The next wave of cloud innovation will be defined by automation, intelligence, and architectural convergence, each accelerated by the multi-cloud management platform. * * * Edge computing will merge with multi-cloud as organizations deploy low-latency workloads closer to customers. A unified platform will orchestrate application flows across edge nodes, Kubernetes clusters, and hyperscale cloud environments. * Unified security fabrics will standardize multi-cloud security by providing a central policy plane across all infrastructure layers. A multi-cloud management platform will serve as the foundational policy engine for identity, access, encryption, and threat detection. * Industry-specific cloud stacks will grow rapidly. Healthcare, BFSI, insurance, and retail organizations will adopt specialized cloud blueprints tailored to compliance and performance requirements. The platform will manage and govern these vertical solutions. * The rise of supercloud architectures, an emerging model where applications operate seamlessly across cloud providers, will further increase the need for a robust multi-cloud management platform as the control plane for orchestration, data fabric, and governance. ## Conclusion: Why Multi-Cloud Management Is Essential in 2026 and Beyond Multi-cloud is no longer an experimental strategy, it is becoming the default architecture for global enterprises. As organizations scale AI workloads, modernize legacy systems, expand geographically, and face rising regulatory pressures, they require a multi-cloud management platform that unifies governance, improves cloud visibility, automates optimization, enforces security, and delivers continuous cost control. With the right platform, multi-cloud becomes not just a distributed infrastructure model but a powerful competitive advantage. Enterprises that invest in intelligent, AI-driven, enterprise-grade multi-cloud management platforms today will be best positioned to lead in 2026 and beyond. Planning to move to a multi-cloud setup? CloudKeeper offers an enterprise-grade multi-cloud management platform for AWS and GCP delivering real-time cost visibility, automated savings, unified governance, continuous compliance, and AI-driven optimization. Whether you’re modernizing workloads or scaling AI, CloudKeeper gives you a single pane of glass to manage it all. Sign up for a demo and see how CloudKeeper simplifies and optimizes your multi-cloud environment. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents SigNoz is an open-source observability platform that integrates metrics, traces, and logs into a single pane of glass. By leveraging high-performance storage and standardized ingestion, it provides an alternative to traditional SaaS vendors without the constraints of proprietary lock-in. This guide provides a conceptual and structural walkthrough to taking SigNoz from an initial idea to a production-ready deployment. ## **Part 1: Architecture & Data Philosophy** ### **1.1 Understanding the Data Flow** Success with SigNoz begins with understanding how data moves through the system. Unlike traditional monitoring where an app might talk directly to a dashboard, SigNoz uses a decoupled architecture to ensure resilience: * **Telemetry Generation:** The application produces data points (traces, metrics, logs) using standardized protocols. * **The Processing Layer:** A central collector receives this raw data, filters out noise, and ensures it is formatted correctly before storage. * **Storage Engine:** Data is stored in a high-performance database optimized for large-scale analytical queries. * **Visualization Layer:** The user interface queries the storage engine to represent the data visually. ### **1.2 Deployment Strategy** Choosing between Docker and Kubernetes is less about the technical commands and more about the scale of your organization. * **Small-Scale/Testing:** Simplified containers are ideal for local debugging or small, isolated environments where high availability is not a primary concern. * **Production/Enterprise:** Orchestration platforms like Kubernetes are preferred for their ability to handle resource isolation, automatic scaling, and persistence of data across hardware failures. ## **Part 2: Connectivity via Runtime Configuration** The most significant advantage of modern observability is Zero-Code Instrumentation. This allows teams to connect services to SigNoz without modifying the application's source code. ### **2.1 The "Config-Only" Approach** For established services, the connection is established entirely through the runtime environment. By leveraging the service's configuration file, you can "hook" into the application at the startup level. * **Runtime Interception:** By adding specific flags to your service's startup options (such as Java's _**javaagent**_), you allow the observability engine to listen to the application's internal behavior, like database calls or external API requests, automatically. * **Environment Mapping:** By adding destination endpoints and service identifiers to your environment variable list, you define the path the data takes to reach SigNoz. ### **2.2 Standardizing Metadata** For observability to be useful across multiple teams, metadata must be standardized. Every service should share a common language regarding its name, its version, and the environment it lives in. This consistency allows the system to correlate a performance dip in one service with a deployment event in another. ## **Part 3: The Theory of Custom Metrics** Standard monitoring shows you if a server is "up," but custom metrics show you if the business is "functioning." ### **3.1 Understanding Metric Types** To measure your service accurately, you must choose the correct mathematical model for your data: * **Counter:** A counter is a metric that represents a single numerical value that monotonically increases over time. A counter resets to zero when the process restarts. Counters are used to track the number of events that occur in a system. For example, the number of requests received by a server. * **Gauge:** A gauge is a metric that represents a single numerical value that can arbitrarily go up and down. Gauges are typically used for measured values like temperatures or current memory usage. * **Histogram:** A histogram is a metric that represents the distribution of a set of values. Histograms are used to track the distribution of values over time. For example, the response time of a web service. * **Exponential Histogram:** An exponential histogram is a metric that represents the distribution of a set of values on a logarithmic scale. Exponential histograms are used to track the distribution of values that span several orders of magnitude. For example, the latency of a network request. ## **Part 4: Designing Intuitive Dashboards** A dashboard’s value is measured by how quickly an engineer can understand a situation during a crisis. ### **4.1 Hierarchy of Information** Effective dashboards follow a top-down logical flow: 1. **High-Level Health:** The top section should answer, "Is there a problem?" using broad indicators of service availability and error frequency. 2. **Contextual Drill-Down:** The middle section should answer, "Where is the problem?" by breaking down data by service components or geographical regions. 3. **Deep Diagnostics:** The bottom section should provide the granular details required for root-cause analysis, such as specific system resource usage or individual trace IDs. ### 4.2 Visualization Principles The goal of a visualization is to reduce the cognitive load on the observer. * **Trend Over Time:** Use line charts to see patterns, shifts, or sudden spikes that indicate a change in system behavior. * **Comparative Analysis:** Use bar charts or tables when comparing different services to identify outliers or underperforming nodes. * **Color as Communication:** Use color intentionally. For example, consistent use of warning and error colors allows an engineer to scan a dashboard and immediately identify "hot spots" without reading the text. * **Explicit Labeling:** A chart without clearly defined units or axes is open to misinterpretation. Always ensure the scale and the measurement units are explicitly defined. ## **Part 5: Real-World Resilience & FinOps** Observability tools should provide clarity, not overhead. Below are two scenarios for optimizing SigNoz. ### **5.1 Scenario A: Preventing "Observability Deadlock"** If your application process is tightly coupled with the SigNoz agent, a failure in the collector could prevent your app from booting. **The Solution: Non-Blocking Startup** Implement a wrapper script (start.sh) that checks for the collector's availability before attaching the OTel agent: ### **5.2 Scenario B: Cost Management via Custom Metrics** We used SigNoz to detect an AWS API cost spike caused by an aggressive polling tool. By instrumenting the specific API client, we created a "Cost Guardrail" dashboard. ### **Step-by-Step Slack Integration:** 1. **Setup:** Navigate to Settings -> Notification Channels. 2. **Add Slack:** Enter your Webhook URL. 3. **Create Alert:** Set a threshold on your custom aws_api_calls_total metric. 4. **Result:** The team receives a Slack notification the moment a "tuner tool" exceeds 1,000 calls per minute, preventing a surprise bill. ## **Conclusion & Best Practices** **Sample Intentionally:** In high-traffic production environments, use probabilistic sampling to save on storage. **Monitor the Monitor:** Set up external alerts for your SigNoz ClickHouse disk usage. If ClickHouse hits 90% disk, it will go into read-only mode. Config as Code: Store your SigNoz dashboard JSONs and OTel Collector .yaml files in Git. By following this structured approach, your SigNoz setup becomes more than just a tool—it becomes a reliable pillar of your SRE strategy. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Diya Khandelwal is a cloud enthusiast with deep expertise in AWS and a knack for simplifying complex systems. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents Microsoft Azure, one of the largest cloud providers, empowers you to achieve unparalleled performance and innovation while mastering your cloud costs. Its vast network of over 200 data centers fuels blazing-fast computing, industry-leading AI and ML services, and robust security solutions, all wrapped in a framework designed for seamless While Azure grants you access to a universe of possibilities, true success lies in harnessing its potential within a financially sustainable ecosystem. Uncontrolled cloud spending can quickly engulf even the most innovative projects, hindering growth and profitability. This is where effective cloud cost management takes center stage. Here we aim to empower you to take control of your cloud spending, maximizing value and minimizing cloud cost surges. ## **About Azure Cost Optimization** Imagine you're renting a fancy car – you want the power and speed, but nobody likes seeing the gas gauge plummet. Azure cost optimization is like that, but for your cloud resources. It's about finding the sweet spot between getting the most out of Azure's amazing features without breaking the bank. Think of it like this: every unused virtual machine is like a parked car guzzling gas. Every underutilized resource is a fancy gadget gathering dust. And it's not just about saving a few bucks. With an efficient and streamlined Azure cost management plan, you can expect your resources to work smarter, not harder. You're using the right tools for the job, cutting out the waste, and squeezing the most value out of every cloud penny. Plus, it's like giving your IT team superpowers – they can track spending, adjust resources on the fly, and keep your cloud running. Azure cost optimization strategies can be summarized as follows: Image Source: Of course, the best part is that cloud cost optimization isn't a one-time thing. It's like a fitness routine for your cloud – you check in regularly, adjust your settings, and keep things running smoothly. Azure has a whole toolbox of tips and tricks to help you navigate the pricing landscape. ## **Cost-Effective Azure Pricing Models and Solutions offered** The fundamental pricing framework within Azure, known as the pay-as-you-go model, offers users flexibility in resource usage but comes with relatively higher costs. This model allows customers to pay only for the services they consume, making it adaptable to varying workloads and usage patterns. However, due to its on-demand nature, where charges are based on the resources utilized, the pay-as-you-go model may result in increased expenses, particularly for consistently high or unpredictable workloads. ### **1. Azure Reservations** Azure Reservations present an opportunity to reserve Azure resources for one or three years, securing a substantial discount compared to regular pay-as-you-go rates. This model suits predictable workloads with consistent usage over the reservation term. Azure Reservations can yield ### **2. Azure Spot Virtual Machines (Spot VMs)** Azure Spot Virtual Machines operate on an auction-based pricing system, offering considerable discounts compared to standard pay-as-you-go rates. However, there is a caveat: Azure retains the authority to reclaim spot VMs when capacity is required for other customers. These VMs are suitable for workloads that can tolerate intermittent interruptions or downtime. While they are a cost-effective option, caution is advised due to their uncertain availability. ### **3. Azure Hybrid Benefit** Azure Hybrid Benefit is a licensing approach enabling the utilization of existing on-premises Windows Server and SQL Server licenses within Azure. Leveraging these licenses allows for To access Azure Hybrid Benefit, Software Assurance or qualifying subscription licenses are necessary. This model is particularly advantageous for organizations heavily invested in Microsoft software seeking to optimize their investments in a cloud environment. To mitigate potential cost escalations associated with the pay-as-you-go structure, exploring and implementing alternative pricing strategies within Azure becomes imperative. By considering and adopting various cost-effective models available, businesses can effectively manage and optimize their expenditure on cloud resources, aligning more closely with their specific operational requirements and financial strategies. ## **Best practices to ensure long-term Azure cost optimization** Conquering the cloud requires not only technical prowess but also financial acumen. While Azure empowers your projects with unparalleled scalability and performance, mastering its pricing model is crucial for sustainable success. Beyond selecting the most advantageous pricing tier, a strategic approach to Azure cost management unlocks significant savings opportunities. Here, we delve into six potent strategies to optimize your Azure expenditure, ensuring your cloud resources deliver maximum value without exceeding budgetary constraints. ### **1. Granular Visibility through Resource Tagging** Azure cost-related tags offer a powerful solution for demystifying cloud expenses. By attaching these labels to resources, you can precisely map cost drivers to specific users, products, and processes. This granularity unlocks a wealth of insights into resource utilization, recurring spend, budgeting, and cost optimizations. Image source: You can analyze ROI on cloud initiatives, track the impact of budget adjustments, and leverage data-driven recommendations to maximize cost efficiency. ### **2. Optimizing Resource Utilization:** Identifying and shutting down unused resources in Azure is a critical practice in optimizing costs by eliminating unnecessary expenses associated with dormant or underutilized services. Effectively managing these resources involves the identification, evaluation, and subsequent decommissioning or scaling down of such assets. The section on tagging and categorization of resources as outlined above is the fundamental practice to identify unused resources. Leveraging valuable insights from Azure Cost Management & Billing tools is the subsequent step in this process. Once these unused resources are identified, the implementation of automation through ### **3. Reclaiming Unnecessary Resources:** Often, an accumulation of digital debris, such as forgotten virtual machines, orphaned databases, and redundant storage accounts, burdens the cloud bill without providing tangible benefits. For instance, During application development or migration processes, databases might be created for temporary use. However, upon completion, these databases might not be deleted, resulting in orphaned instances that consume storage resources and incur unnecessary costs. Image source: While Azure Advisor offers valuable suggestions and insights, its view might be limited in identifying every dormant or underutilized resource. Manual exploration through the Azure portal's graphical user interface (GUI) becomes necessary for a more thorough examination of all resources deployed within the Azure environment. ### **4. Virtual Machine Autoscaling** Virtual machines, if left statically provisioned, may continue to consume resources regardless of actual utilization. In response to this challenge, Azure's Virtual Machine Autoscaling presents a powerful technique that automatically adjusts the number of VM instances, scaling them up or down as per real-time demand. Consider a cloud-based application catering to global users that might witness variations in usage throughout the day due to different time zones. With VM Autoscaling configured based on these usage patterns, the system can scale up resources during peak hours when the application experiences higher traffic and scale down during quieter periods, optimizing resource utilization and controlling costs. ### **5. Proactive Cost Monitoring** By embracing proactive cost monitoring practices facilitated by Azure Cost Management, organizations gain the ability to make timely budget adjustments, optimize resources, and proactively manage their cloud finances. Facilitated by tools like Azure Cost Management and third-party cloud cost visibility & recommendation tools such as Image source: A company maintaining a monthly budget for its Azure resources can leverage Azure Cost Management to compare actual spending against the allocated budget. Any deviation beyond set thresholds triggers alerts, prompting the finance team to take corrective actions promptly, such as adjusting resource allocation or identifying areas for optimization. ### **6. Spot Virtual Machines (VMs)** Spot Virtual Machines (VMs) in Azure play a significant role in cost optimization by offering highly discounted pricing compared to regular on-demand instances ( Remember, Azure cost optimization is an ongoing endeavor that demands a combination of proactive strategic planning and timely, informed actions. Utilizing the six outlined strategies facilitates the effective management of Azure expenses, achieving a harmonious equilibrium between operational performance and fiscal sustainability. ## **Monitoring and Controlling Azure Spending** As established by Azure, cloud expenditure optimization revolves around three fundamental pillars to ensure effective cost management -visibility, accountability & optimization. The process encompasses a symphony of tools and strategies, orchestrating effective monitoring and control mechanisms. ### **1. Azure Cost Management + Billing: Visibility** Azure Cost Management + Billing is more than just a mere dashboard, evolving into a comprehensive financial intelligence center. It equips you with visibility into your cloud investment, offering: * **Granular Scrutiny:** Delve into granular cost breakdowns by department, project, resource type, and timeframes. Pinpoint anomalies with laser precision and unveil resource usage patterns like an astute financial detective. * **Budgetary Orchestra:** Compose a symphony of custom budgets, enabling meticulous progress tracking against established spending goals. Pre-emptive alerts prevent budgetary discord, ensuring harmonious financial control. * **Allocation Maestro:** Facilitate meticulous cost allocation to specific teams, projects, or departments. This fosters accountability and promotes responsible cloud resource utilization. * **Forecasting Prowess:** Leverage the power of historical data and resource utilization patterns to predict future spending trends. Prepare for peak periods and optimize resource allocation for long-term cost efficiency. ### **2. Resource Policies and Governance: Accountability** Resource policies and governance serve as a fortified budgetary firewall, ensuring that individuals or teams are responsible for their resource usage, promoting a culture of cost consciousness and ownership within the organization. * **Role-Based Control:** Define granular permissions for resource creation, access, and modification. Delegate authority while ensuring only authorized personnel can incur cloud costs. * **Resource Guardrails:** Establish spending and consumption limits for specific resources or resource groups. These guardrails automatically throttle or stop resource provisioning before exceeding pre-defined thresholds. * **Automated Optimization:** Schedule automatic shutdowns or scaling down of unused resources during off-peak hours. Maximize resource utilization while minimizing unnecessary idle costs. ### **3. Cost Alerts and Budgets: Optimizations** Continuous optimization involves employing strategies to enhance resource efficiency, eliminate waste, and optimize spending without compromising performance or functionality. Implementation of budget thresholds and cost alerts empowers us to act as vigilant sentinels and proceed cautiously with cost optimization. * **Threshold Guardians:** Establish customized spending thresholds for specific resources, accounts, or overall budgets. Receive immediate notifications via email, SMS, or even Azure Monitor upon breaching pre-defined limits. * **Proactive Response:** React swiftly to cost spikes by investigating the underlying causes, optimizing resource usage, or implementing temporary resource scaling adjustments. These prompt actions can significantly mitigate potential financial repercussions. * **Customization Choir:** Fine-tune your notification system to receive alerts precisely when needed. Avoid information overload while ensuring you are always aware of significant cost fluctuations. ## **How CloudKeeper helps in Azure cost optimization?** Trusted by over 300 global businesses, **CloudKeeper isn't merely a cost optimization tool: it's your comprehensive FinOps partner**. It serves as your all-in-one solution for Azure cost optimization with: * **:** Our proven strategies and expert guidance on Azure cloud ensure savings right from day one. * **:** Gain an eagle-eye view of your spending across Azure through our intuitive platform, providing comprehensive cloud cost visibility. * **:** From strategy to optimization, our team of certified cloud FinOps specialists guides you at every stage of your Azure cost optimization journey. **Are you ready to unleash the full potential of your Azure cloud?** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Chief Operating Officer Aman spearheads business operations, strategic execution, and cross-functional alignment to drive sustainable growth. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents ## **Introduction** This guide demonstrates how to establish secure, private access from a laptop to resources in an AWS VPC that are protected by a Simple Active Directory (SAD) and Windows Server. The primary path uses **AWS Client VPN** with **Directory Service authentication**. An appendix shows how to achieve the same using **Pritunl**. ### **What you’ll build** * A * **AWS Directory Service – Simple AD** (managed LDAP + DNS) in private subnets. * A**Windows EC2** instance in a private subnet reachable **only over VPN**. * An**AWS Client VPN** endpoint integrated with Simple AD for user authentication. * (Optional) A **Pritunl** VPN server as a self‑hosted alternative. ### **Reference Architecture** ### **Prerequisites** * AWS account with permissions for VPC, * A workstation with an RDP client and (optionally) the AWS CLI. * A single AWS **Region** chosen—keep all resources in that same Region. **Tip:** If you already have a VPC and NAT, you can reuse them. ## **Part A — Network Setup (from scratch)** ### **1. Create a VPC** * CIDR: **10.0.0.0/16.** ### **2. Create subnets** * Public: **10.0.10.0/24**(AZ‑A) * Private‑A: **10.0.1.0/24** (AZ‑A) * Private‑B: **10.0.2.0/24** (AZ‑B) ### **3. Internet Gateway (IGW)** * Create and attach it to the VPC. ### **4. NAT Gateway** * Allocate an Elastic IP. * Create the NAT Gateway in the public subnet. ### **5. Route tables** * Public RT →**add 0.0.0.0/0 → IGW** ; associate the **public subnet**. * Private RT →**add 0.0.0.0/0 → NAT GW** ; associate the**private subnets**. ### **6. Baseline security groups (SGs)** * **sg-windows** (for Windows EC2): allow **RDP 3389 from the Client VPN CIDR**(set later). Allow other internal ports as needed. * **sg-client-vpn-endpoint:** allow inbound from VPN clients (AWS maps this) and outbound to the VPC. **Public vs. private subnets** are defined by routes: public subnets have a default route to an IGW; private subnets do not. ## **Part B — Directory Service (Simple AD)** ### **1. Create Simple AD** * Directory name (example): **corp.local**. * Choose the VPC and **two private subnets** in different AZs. * After creation, record the two **Simple AD DNS IPs** (e.g., **10.0.1.50, 10.0.2.50**). These resolve**corp.local** and host LDAP. ### **2. NACL/RT notes** * Default NACLs (allow/allow) are fine for most cases. * Ensure the private route table has a path to the internet via NAT if Simple AD requires outbound updates. ## **Part C — Windows EC2 (private subnet)** ### **1 . Launch the instance** * AMI: Windows Server. * Subnet: 10.0.1.0/24 (Private‑A). * SG: sg-windows. * No public IP. * Optional IAM role: **AmazonSSMManagedInstanceCore** for Session Manager access. ### **2. Join to Simple AD** * After VPN and DNS are in place, join the instance to **corp.local,** or simply rely on Simple AD for VPN user authentication. With **Simple AD** , AWS operates the domain controllers. Your Windows instance is a **member server** , not a DC. In the windows instance, to join the instance to **corp.local** go to: Control panel -> Network and Internet -> Network and Sharing Center -> ethernet -> properties -> Internet Protocol Version 4(TCP/IPv4) -> properties -> use the following DNS server addresses. Here, add the DNS address of Simple AD. ## **Part D — Certificates for AWS Client VPN** You need a **server certificate** in **ACM** to create the Client VPN endpoint. ### **Option 1 — Self‑signed (EasyRSA)** Generate locally, then import to ACM (in the same Region as the VPN): **# On Linux/macOS** git clone cd easy-rsa/easyrsa3 ./easyrsa init-pki ./easyrsa build-ca nopass ./easyrsa build-server-full server nopass **# Import to ACM** : **# Certificate body** → pki/issued/server.crt **# Private key** → pki/private/server.key **# Certificate chain** → pki/ca.crt For AWS Client VPN, the server certificate does **not** need a public DNS name; a generic CN like **server** is sufficient for console selection. ### **Option 2 — ACM Private CA (recommended for enterprises)** Issue the server certificate from a private CA; it’s already in ACM and easier to manage/rotate. ## **Part E — Create the AWS Client VPN Endpoint** ### **1. Create endpoint** (VPC → Client VPN Endpoints → Create) * **Client IPv4 CIDR** : e.g., **10.250.0.0/22** (must **not** overlap the VPC CIDR). * **Server certificate** : pick the ACM cert you imported/issued. * **Authentication** : user‑based → **Directory Service** → select your **Simple AD**. * **Connection logging** : optional (CloudWatch Logs). * **DNS servers** : enter your **Simple AD DNS IPs** (from Part B). This ensures **corp.local** resolves on clients. * **Security group** : attach **sg-client-vpn-endpoint** (you can refine later). ### **2. Associate a subnet** * On **Associations** → **Associate subnet** → choose any VPC subnet (public is common). This provides a path from the endpoint into the VPC. ### **3. Add routes** a) On **Routes** → **Add route** : * Destination: your VPC CIDR (e.g., **10.0.0.0/16**). * Target: the associated subnet. ### **4. Authorization rules** * Allow access to **10.0.0.0/16** for **all users** or a specific AD group. The endpoint should reach **Available**. If it’s stuck in **pending-associate** , you likely missed the **Associate subnet** step. ## **Part F — Client Setup & Testing** 1. **Download the client configuration** from the endpoint (Client configuration tab). 2. Install the **AWS VPN Client** (or another OpenVPN client) on your laptop. 3. **Import** the configuration and **connect** with your **AD credentials**. ### **Verify** * **ipconfig/ifconfig** : you should receive an IP from **10.250.0.0/22**. * **nslookup corp.local:** should resolve via the Simple AD DNS servers configured on the endpoint. * RDP to the Windows private IP (e.g., **10.0.1.119**). * (Optional) Join a Windows workstation to the **corp.local** domain while connected. ## **Security Groups — Practical Rules** ### **1. Windows EC2** * Inbound: RDP 3389 from the **Client VPN CIDR** (e.g., **10.250.0.0/22**). * Inbound: other ports (DNS/LDAP/etc.) only if required by your apps. * Outbound: allow all, or restrict as policy dictates. ### **2. Client VPN Endpoint** * **Inbound:** from VPN clients (AWS handles mapping to this SG). * **Outbound** : to the VPC CIDR. For tighter security, allow only the exact application ports from the Client VPN CIDR to target instances. ## **Troubleshooting (real‑world)** * **RDP times out** → Check SGs (3389 from Client VPN CIDR), NACLs (allow/allow), Windows Firewall, and that the instance has no dependency on a public egress path. * **VPN connects, but names don’t resolve** → Ensure the endpoint’s**DNS servers are the Simple AD DNS IPs**. On Windows, run**ipconfig /flushdns** after reconnecting. On Linux with systemd‑resolved, the local stub (**127.0.0.53**) may persist until reconnect. * **Certificate not visible when creating the endpoint** → Confirm ACM Region matches the endpoint Region and that you imported the full **cert + key + chain**. * You haven’t associated a subnet yet. * **Windows can’t reach the internet** → Private route table must have **0.0.0.0/0 → NAT GW** for updates, activation, etc. ## **Cost Considerations (ballpark)** * **Client VPN** : hourly per endpoint + per‑connection pricing. * **Simple AD** : hourly pricing (AWS runs two DCs). * * Windows EC2: instance hours + Use Savings Plans/Graviton where possible and shut down test environments when idle. ## **Optional — Pritunl (Self‑Hosted Alternative)** Choose this if you want more control or to avoid Client VPN costs. ### **Configure in the web UI** * Open **https:// ** (allow 443 from your admin IP). * Run **sudo pritunl setup-key** on the server and paste the key. * Create an **Organization** and a **User**. * Create a **Server**(UDP 1194 or TCP 443). Set **DNS Server** = **Simple AD DNS IPs.** * **Add Route:** **10.0.0.0/16** with **NAT enabled** to simplify return traffic. * Attach the Organization to the Server and **Start** the server. * Export the user profile (**.ovpn**) and connect from your laptop. ### **EC2 security group for Pritunl** * **Inbound:** 1194/udp (or your chosen port) from client IP ranges; 443/tcp from admin IPs. * **Outbound:** to the VPC CIDR. For whole‑VPC access, ensure the route covers **10.0.0.0/16** and that target instance SGs allow traffic from the VPN subnet (or from the Pritunl server if NAT is enabled). ## **Quick Validation Checklist** * Client receives IP from the **Client VPN CIDR**. * **nslookup corp.local** resolves via **Simple AD DNS**. * RDP to Windows private IP works while connected; fails when disconnected (desired isolation). * Authorization rules limit access to intended subnets/ports only. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Rohan is a technology enthusiast with expertise in cloud infrastructure, automation, and containerized environments. He is passionate about building secure, scalable, efficient cloud solutions. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents The shiny strip of Las Vegas bore testimony to yet another successful iteration of AWS re:Invent, the grand fest of AWS practitioners, industry leaders, and cloud enthusiasts alike. The 2023 edition was packed with over 50,000 attendees, covering groundbreaking keynote sessions, networking events, and so much more. Generative AI (GenAI) was the highlight among a CloudKeeper was a ## **Lightning Theatre Session by Aman Aggarwal** CloudKeeper’s Business Head, In this session, Aman explained the advantages and disadvantages of an AWS EDP, determining your ideal annual commitment amount and span, how to maximize the benefits of an EDP while retaining flexibility, and using Let us break down Aman’s session in detail below by understanding the nitty-gritty of AWS EDP and CloudKeeper EDP+. It would have been an astounding experience to hear from the man himself, but for those who missed it, here are the details of the session below. ### **CloudKeeper’s Relationship with AWS** Aman commenced his AWS: re:Invent 2023 session by introducing CloudKeeper. CloudKeeper has been an AWS Partner since 2013 and became a premier(highest) tier partner in 2018. AWS has more than 100k partners around the globe, out of which only less than 0.5% belong to the category of premier partners. CloudKeeper is a globally authorized channel reseller and one of the top 5 partners globally for the AWS Well-Architected partner program. ### **AWS Enterprise Discount Program(EDP)** Aman provided an overview of the AWS Enterprise Discount Program (EDP) which is specially designed and aimed to ### **AWS EDP eligibility** The following could be listed as eligibility criteria for AWS EDP: * Customers should have a minimum annual spend of $1 million. * Annual commitment should be the same or greater than the current spend. * Commitment for each subsequent year should be 10-20% higher than the current year’s spend. * AWS Enterprise Support subscription is mandatory for all AWS accounts. * AWS EDP requires a commitment of 1 to 5 years, the higher the better. ### **Key considerations for maximizing AWS EDP benefits** AWS EDP generally hinges on two factors - commitment value and the tenure of the commitment. As expected, the longer one commits to the program, the bigger the discount potential is. If the tenure of engagement and scale of AWS operations is predetermined to a certain extent, it will definitely pay to commit for the longest period possible to get the highest discount. However, the annual commitment must exclude all the AWS EDP benefits including discounts, credits, private pricing etc. This is mostly a point of confusion among many companies. Again, accounts with different Sellers of Record( AWS Singapore, AWS Inc. US, AWS EMEA, etc.) cannot be consolidated under one AWS EDP. What is allowed however is consolidating spends from multiple entities to sign a larger AWS EDP. This consolidation thus leads to higher benefits and improved cost-efficiency. Last, but not the least, ISV purchases via AWS Marketplace can offset up to 25% of the annual AWS EDP commitment. However, it's important to note that the AWS EDP is a firm commitment with no termination for convenience during the specified tenure. ### **Preparing for AWS EDP success** Before embarking on an AWS EDP journey, your cloud architecture and operations model should be optimized for cost savings and cloud efficiency. AWS EDP or not, cloud cost optimization is something that should be at the heart of every cloud-based organization. Committing to an under-optimized cloud system can only hurt your business profitability. Several existing SaaS subscriptions and licenses can also be routed via the AWS Marketplace, which not only enhances your eligibility but also helps with additional discounts. Many organizations also tend to go overboard with their spending projections. Overly conservative or optimistic estimates must be avoided and some buffer must mandatorily be maintained in the actual commitment. Aman emphasizes that realistic expectations are key; striking a balance between conservatism and confidence in commitments is advised. It's recommended to commit slightly lower (around 5-10%) than actual projections to account for uncertainties or unforeseen issues, ensuring a buffer for meeting AWS EDP commitments even in challenging circumstances, There are also additional discount programs that can complement an AWS EDP such as Migration Acceleration Program (MAP), service-specific private pricing, etc. The key to success is to be comprehensive as far as cloud optimization is concerned. ### **Managing commitment shortfalls** Falling short of an AWS EDP commitment is something enterprises face from time to time. At the end of each contract year(not applicable at the end of the final year), any commitment shortfall is charged back, which is generally adjusted as credits in subsequent months to mitigate the impact. As such, companies must set up strict adherence to AWS EDP commitments and take proactive steps to mitigate any shortfalls. Key actions include upfront payment of Reservations or Savings Plan to meet commitments. Additionally, as covered earlier, SaaS payments or even professional services payments can be routed via the AWS Marketplace, making it easier for businesses to meet the compliances. Needless to say, enterprises must proactively communicate and collaborate with the AWS account manager and AWS EDP partner to seek guidance and possible amendments to mitigate the shortfall impact. ### **Collaborative Edge: How Partners Enhance AWS EDP** Partners play a crucial role in enhancing your Enterprise Discount Program (EDP) construct with Amazon in various ways. Firstly, partners bring valuable experience from working on multiple AWS EDP deals, offering insights into best practices and helping align commitment values with your business goals. Considering the complex nature of AWS EDP, a partner like CloudKeeper can help you with a multi-pronged approach to managing the commitments and running a successful and effective Enterprise Discount Program. Key areas where an AWS EDP partner can significantly make an impact are: * Determining the appropriate commitment value. * Ensuring that commitments are aligned with organizational goals and projections. * Providing improved AWS EDP discounts and lower annual commitments. * Providing customized reports/monthly invoices and recommendations for cost optimization. * Invoicing and compliance-related modalities and workflows. * Deliver value-added benefits without additional costs, such as AWS cost optimization suggestions, consulting, professional services, cost audits, reservation management, and access to a cost governance platform. * Enhance cost-efficiency and overall value through supplementary services. ## **CloudKeeper EDP+** As an AWS partner, we have helped over 30 customers in enhancing their AWS Enterprise Discount Program with CloudKeeper EDP+. One of the key highlights of Aman’s session at AWS re:Invent 2023 was that with CloudKeeper EDP+, enterprises can avail of even greater discounts at lower annual commitments. More than qualifying, negotiating for a benefit-driven AWS EDP contract is a tough job. With CloudKeeper EDP+, you can land a winning AWS EDP contract, laden with higher savings at lower commitments. On top of that, you get access to Partner-led Enterprise Support at a much lower cost compared to direct AWS support. With CloudKeeper EDP+, you also get onboarded to our The comprehensive breakdown of AWS EDP, coupled with the unveiling of CloudKeeper EDP+, garnered significant attention, marking the session as a highlight. If you'd like to watch the full session, you can view it To delve deeper into how CloudKeeper EDP+ enhances your AWS EDP, feel free to ## **Related Blog** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Complete Guide to AWS PPA Contract Negotiation for Growing Enterprises A practical guide to AWS PPA or EDP negotiations, covering commitments, discounts, flexibility, risks, and best practices to help growing enterprises secure better pricing and long-term cloud value. By Team CloudKeeper 19 Dec, 2025 Ask the Cloud Expert: A Deep Dive Q&A on AWS PPA In this Q&A, CloudKeeper’s AWS PPA expert Aman Dixit shares real-world insights to help clients navigate PPAs and make smarter, cost-effective decisions. By Team CloudKeeper 05 Sep, 2025 Introducing the AWS EDP Tracker in CloudKeeper Lens AWS EDP Tracker is a real-time interactive dashboard that gives you end-to-end visibility to monitor, forecast, and optimize your EDP spend throughout its term. By Harsh Agarwal 06 May, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 17 17 Table of Contents When cloud computing revolutionized how organizations manage their data and operate daily, much effort was put into technologies and practices that further optimize its usage. Like DevOps, which helped in breaking down silos and enhancing agility in engineering, FinOps, a blend of “Finance” and “DevOps”, evolved to be a cultural transformation bringing together finance, engineering, and business professionals. FinOps solutions focused on enhancing the ROI of cloud investments with effective cloud cost optimization services. When distributed teams work together, it is important to ensure that they speak the same language and are on the same page. But when engineers focus only on performance enhancements and finance teams on cost savings, the discussions become tedious to manage and decisions get caught up in an unending loop. This is a challenge that can’t be tackled with the help of even the best cloud cost management tools. Hence, it becomes vital for organizations to understand the basic concepts of FinOps to foster a mutual understanding between the teams, create a common vocabulary and consistency in cloud cost tracking and reporting terms. This makes sure that smooth product deliveries go hand in hand with cost predictability and financial control. This blog talks about the foundation principles of FinOps and the three iterative cycles of FinOps - Inform, Optimize, and Operate. Your organization could be in multiple phases of this lifecycle, so this blog will help you understand where your business units stand in their FinOps journey. ## **The Basic Principles of FinOps** FinOps is a cultural practice that helps bring financial responsibility to the cloud-based spending model. FinOps is a culture shift where cloud cost tracking is moved to the forefront of everyone's thinking. The foundational principles based on which the concept of FinOps is being practiced are as follows: * Collaboration - Continuous improvement and innovation are needed to optimize the per-resources-per-second-cost and require seamless cooperation of the finance and cloud infrastructure teams. FinOps solutions, by discipline, demand capabilities from these teams to collaborate in order to balance the cloud costs and their derived value. ( on how to introduce a FinOps Culture in your organization) * Value-Driven Decision Making - The broader FinOps concept of enterprise value per business unit influences real-time decisions in managing cloud usage. While immediate cloud cost optimization services offer gains that are attractive, FinOps focuses on maintaining efficiency and flexibility to improve the long-term value of cloud deployments. * Ownership - FinOps aims at cloud cost excellence in an organization. Each stakeholder in the cloud infrastructure of a company should own the responsibility of being held accountable for cloud usage and the associated costs. * Centralized FinOps Management - A cultural shift requires a leading authority for advocacy and goals in order to be successful. A FinOps team should develop principles and practices to enhance cost excellence for an effective operating model that can be adhered to by the organization. * Timely Availability of Insights - In a world of automated deployments and per-second compute resources, monthly or quarterly reports aren't enough. Teams need real-time cloud cost tracking to make the best decisions. The dynamic nature of the cloud demands real-time decision-making to * Advantages of the Variable Cost Model - Cloud-based capacity planning makes it much easier to determine how much capacity to buy and how many resources to use. Instead of assumptions on future requirements, cloud cost management tools recommend making purchase decisions based on actual usage data and scientific projections. ## **The FinOps Lifecycle** **** The **Inform -** This phase involves informing the stakeholders what they are spending on and why. This involves a granular view of cloud spending, allocation, chargebacks, and tagging, analytic insights into spend patterns, and audit frequency, along with recommendations for right-sizing and proper costing. The focus throughout this phase is cloud cost tracking to identify current resource allocation, the performance of the budget, and its future implications. This phase helps in mitigating the challenges of the complex and overwhelming number of choices of Cloud SKUs. By following practices such as benchmarking, businesses could ensure that they are driving ROI while staying within the budget. **Optimize -** Once the cloud stakeholders have been empowered with usage insights, they need to focus on further Cloud Service Providers offer a variety of cloud cost optimization services to assist teams in optimizing their operations. In this phase, organizations work on right-sizing their current compute storage and network resources. Purchases of committed use plans (like Reserved Instances (RI) and Savings Plans) will help them with discounts while maintaining high utilization. Companies must leverage the proprietary cloud resources & volume offered by vendors for discounts and savings. They can also engage third-party vendors for leveraging AI-based FinOps solutions, which can help automate rightsizing, purchase, and sale of reservations and turn off wasteful resources. **Operate -** The third and final phase of the FinOps lifecycle is focused on designing procedures and processes that help achieve the goals set by technology, finance, and business. By continuously evaluating these goals and the metrics, companies can come up with ways to improve their overall performance. They should measure business alignment to these objectives based on speed, quality, and cost. Companies should also identify the latest developments in the discipline of FinOps while taking proactive steps to ensure a competent talent pool in the future. They should also leverage expert assistance and architectural reviews, whenever possible, to ensure more innovative resource provisioning, lesser wastage, maximum cloud coverage, and enhanced performance with the help of the best cloud cost management tools. It is also advisable to build a Cloud Center of Excellence, comprising experts from multiple business functions with cloud experience, who can define the appropriate FinOps governance policies and models. ## **Working with the right FinOps Partner** As mentioned earlier, the individual business units of an organization could be in distinct phases of the lifecycle. Getting through each of these phases requires the application of different technologies and skill sets. Since it might be hard for a single organization to possess all the necessary tools and talented professionals, it is always advisable to get the help of a domain expert. This is where a Cloud FinOps Partner comes into play. Experienced With a comprehensive set of FinOps solutions, CloudKeeper has enabled businesses of all shapes and sizes to achieve maximum ROI with their cloud infrastructure, by ensuring alignment with the basic FinOps principles and successfully navigating the FinOps Lifecycle. Inform Phase - CloudKeeper offers in-depth, resource-level cloud usage insights with Optimize Phase - Organizations can scale their cloud usage according to their business needs without any budget overruns, using Operate Phase - Businesses can have their end-to-end FinOps processes sorted out with Understanding the basic principles of FinOps and the lifecycle will help organizations understand where they stand in terms of their cloud cost optimization initiatives. This will help them in ensuring enhanced performance and productivity, along with better cost management and zero budget overruns, and take the necessary steps to foster a thriving FinOps culture. Partnering with an expert FinOps service provider is the best decision a cloud consumer could make. That’s Cloud FinOps 101. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents IDC recently released its first-ever Market Glance for the FinOps Cloud Transparency presentation. A Market Glance is a visual representation of the landscape of a specific marketplace, showing vendors that provide critical software and services to end customers. This Market Glance examines how software and service providers support enterprise wide FinOps teams in their journey to manage and optimize cloud costs. Enterprise FinOps teams can utilize a Market Glance to create a shortlist of vendors to review and compare when looking for modern tools. The Market Glance has multiple segments within the overall market, with many vendors appearing in more than one segment. This inaugural FinOps Cloud Transparency Market Glance lists vendors who can assist your organization in increasing transparency and providing valuable insights into cloud spending. FinOps is a cross-functional discipline focused on collaboration and IDC organizes FinOps cloud transparency vendors into five segments. Vendors must have recognized and demonstrated capabilities in one or more segments for inclusion in the Market Glance. Many have been around for years, helping hundreds of customers successfully manage their cloud spending. Vendors in multiple categories typically offer a more * **Cloud infrastructure-as-a-service (IaaS) resource optimization:** Many servers are overprovisioned compared to actual workloads, and other servers have been abandoned but are still generating costs. This segment can identify and * **Report and pricing analytics:** Every cloud provider offers various saving plans, reserved instances, spot instances, and other ever-changing pricing options. FinOps teams need a single source of truth with recommendations on the latest pricing tiers. Analytics provide * **Cloud software-as-a-service (SaaS) management:** There are over 25,000 active SaaS providers today. Most enterprises spend more on SaaS than IaaS but need a tool to uncover hidden costs. This segment depends on machine learning (ML) to find and identify opportunities for savings. * **FinOps service providers:** To successfully * **Container optimization:** The fastest-growing area of cloud-native applications involves containers. This requires a new approach to optimizing container-based resources. IDC estimates containers will grow to 6.5 billion worldwide by 2025. Tools are needed to provide better insight and analysis. IDC Market Glance FinOps Cloud Transparency 2Q23 As seen in the Figure, cloud IaaS resource optimization has the most significant number of vendors, followed closely by the reporting and pricing analytics segment, with many vendors appearing in both areas. The complexity of reserved instances and other pricing models of the public cloud providers means enterprises need these analytics and recommendations coupled with proper IaaS resource sizing. The bottom row offers a glimpse into the future with cutting-edge capabilities IDC believes will soon be needed by FinOps teams. SaaS optimization represents a large area of cloud spending that enterprises need insight into today. Containers are a rapidly growing cloud-native approach as many companies modernize their application environments, but the complexity of An essential segment is FinOps service providers. A trusted advisor can help large enterprises start their FinOps journey with best practices and proper tools. For small and medium-sized businesses (SMBs), a strategic vendor can provide ongoing services and continually optimize the cloud environment as companies migrate applications and move towards a digital business model. Navigating the complex and ever-changing world of cloud providers is often a skill that SMBs struggle to recruit or retain. IDC recommends that enterprises utilize this Market Glance to find the best partner for their FinOps teams. Ensuring a partner offers all the capabilities and value-added services your teams need will increase your FinOps maturity. IDC believes a mature FinOps practice is essential to delivering business value in today's economic climate. ## **Finding the Right FinOps Partner** The importance of cloud FinOps in organizations is on the rise. However, with varying FinOps maturity across organizations, it is essential to find the appropriate partner who can help adopt FinOps and optimize cloud costs. CloudKeeper is an AWS cost optimization and FinOps solution that offers savings, software, and services, all bundled into one solution. An AWS Premier Consulting Partner, CloudKeeper has helped 300+ businesses over 12+ years to achieve instant and guaranteed cost savings right from Day 1. Learn more about CloudKeeper Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 14 14 Table of Contents Remember when cloud computing was supposed to solve all our cost problems? Yet here we are, with most of us staring at our cloud bills wondering where exactly all that spending is going. Turns out, we're not alone. The recent State of FinOps 2025 Report by FinOps Foundation, shows that **workload** **optimization and waste reduction are keeping 50% of FinOps practitioners up at night**. Source: State of FinOps 2025 Report (https://data.finops.org/) ## **Shift towards Governance and Automation** But here's what's fascinating: while we're all trying to get a handle on cloud costs, the landscape is shifting beneath our feet. The data in the State of FinOps 2025 Report tells an interesting story. While workload optimization tops today's priority list, there's a clear pivot happening towards governance and automation. It's like watching the FinOps community collectively realize that throwing more spreadsheets at the problem isn't the answer. Source: State of FinOps 2025 Report (data.finops.org) This hits close to home. In my conversations with cloud architects and FinOps leaders, I keep hearing the same thing: _"We know we're wasting money, but finding where and fixing it manually is like trying to find a needle in a digital haystack."_ **, an automated usage optimization platform is already helping organizations tackle these exact challenges**. Think of it as having a tireless Cloud FinOps engineer working 24*7, spotting unused resources, optimizing workloads, and even automatically switching between Spot and On-Demand instances to save costs while keeping the performance optimal. The best part? It's not just about cost-cutting. It's about bringing intelligence and automation to your cloud operations. When I see it automatically shutting down idle resources during off-hours or providing tailored modernization recommendations, I'm reminded that good FinOps isn't about penny-pinching - it's about smart resource usage. **Within 24 hours of implementation (which takes just minutes), teams start seeing real savings - we're talking an average of 10% off AWS bills**. But beyond the numbers, it's about giving teams back their time to focus on innovation rather than cloud cost management. Let’s uncover some more interesting insights from the State of FinOps 2025 Report. ## **The "Cloud+" Era: FinOps beyond the cloud** We've been so focused on cloud costs for so long, that it's easy to forget that technology spending extends way beyond those virtual servers. The State of FinOps 2025 report highlights a really interesting trend: FinOps is growing up. It's moving beyond just the public cloud and embracing a "Cloud+" approach. ### **What does "Cloud+" actually mean?** Essentially, it's about applying the same * **SaaS (Software as a Service):** Think about all those subscriptions: CRM, project management, communication tools. They add up fast, and many companies are now using FinOps to get a handle on them. * **Licensing:** Software licenses, especially for enterprise-grade applications, can be a huge expense. FinOps is helping businesses understand and optimize these costs. * **Private Cloud and Data Centers:** Even if you're not fully in the public cloud, you still have infrastructure costs to manage. FinOps is being used to bring transparency and efficiency to these areas. Source: State of FinOps 2025 Report (data.finops.org) Initially, practitioners are applying foundational FinOps capabilities, such as cost understanding and value quantification, to these new areas. As they gain better visibility and maturity, optimization efforts will follow. ## **Public cloud dominates AI investment** According to the State of FinOps 2025 Report, organizations are **prioritizing AI investments in the public cloud** , with **69% directing funds toward SaaS solutions** and **30% investing in data centers or private cloud**. Source: State of FinOps 2025 Report (data.finops.org) Right now, the top priority in AI cost management is understanding usage and quantifying business value, with a strong emphasis on allocation, data ingestion, reporting, anomaly detection, and forecasting. Optimization isn’t a key focus yet, but as businesses ## **Organizational alignment remains key, but investment in tools gains momentum** Organizational alignment (like leadership buy-in) is still the top factor in achieving FinOps priorities, but its importance has dropped by 9% compared to last year, a positive sign for growth in FinOps adoption growth. Meanwhile, investment in tooling and resources has surged by 20%, with key needs including upskilling, automation, and productivity tools. Source: State of FinOps 2025 Report (data.finops.org) This completely makes sense as leadership support solidifies, the focus must shift toward resourcing and efficiency, especially as FinOps workloads continue to grow. _If your company is still figuring out how to get started with FinOps or scale it with the right tools and resources,_ ## **FinOps Practitioners are taking on More – But at what cost?** The State of FinOps 2025 Report shows, FinOps practitioners are taking on more than ever, increasing focus on nearly 12 capabilities. With workloads growing but resources staying the same, teams are at risk of spreading themselves too thin. With limited time and resources, trying to improve everything at once can dilute focus and reduce overall impact. To be effective, FinOps teams need to prioritize. Instead of stretching themselves across too many areas, they should strategically allocate their efforts to the most valuable opportunities. ## **Cloud Sustainability: Still more talk than action** Cloud sustainability reporting hasn’t changed much over the past year, with only a **1% increase globally**. While **Europe leads the way** —with **53% of organizations tracking cloud carbon emissions (up 18% YoY)** —**North America remains stagnant at 29%**. **But here’s the real takeaway:** cost still rules the decision-making. Only **3% of FinOps teams optimize cloud costs based on carbon impact** , **while 15% focus purely on cost savings**. Despite the rise in ESG initiatives, sustainability efforts are still more about visibility than action. Source: State of FinOps 2025 Report (data.finops.org) ## **FOCUS adoption is growing, but challenges persist** More than half of FinOps practitioners plan to adopt **FOCUS (FinOps Open Cost and Usage Specification)** in the next 12 months, according to the State of FinOps 2025 Report. However, adoption isn’t without hurdles. * **57%** have plans to use FOCUS. * **24%** are still figuring out their approach. * **18%** don’t plan to adopt it at all. The main barriers to adoption include time constraints, skill gaps, and dependency on billing providers. Some organizations are also holding off until more SaaS vendors align with the standard. With the release of FOCUS 1.2, which incorporates SaaS data, adoption is expected to grow. As more providers standardize billing data, cost transparency and FinOps processes will become more efficient. ## **The Final Thoughts** Looking to 2025, the State of FinOps 2025 Report makes one thing clear, FinOps is evolving fast. It's not just limited to public cloud costs anymore. To stay ahead, organizations must: * **Establish Robust Governance** – Build strong frameworks to manage costs effectively. * **Invest in Skills & Automation** – Empower teams with training and advanced tools. * **Tackle AI Cost Challenges** – Prepare for the complexities of AI-driven spending. * **Expand Beyond Cloud** – Develop a holistic strategy for managing all technology costs. At CloudKeeper, we're excited to be part of the FinOps evolution by empowering organizations with the right tools and capabilities to navigate these FinOps challenges with confidence. _We'd love to hear your perspectives on these trends and discuss how we can support your journey!_ **About the State of FinOps 2025 Report by FinOps Foundation** The State of FinOps 2025 Report marks the fifth annual survey conducted within the FinOps Foundation community. This year's**** respondents include large enterprise organizations, with 31% spending over $50 million annually on public cloud, 20% exceeding $100 million per year, and more than 20 companies surpassing $1 billion in cloud expenditures. Additionally, 41% of respondents come from organizations with over 20,000 employees, while 15% represent companies with more than 100,000 employees. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Director Praneet brings over 14 years of experience in building high-growth SaaS companies right from 0$ to IPO. He has held key roles at Udemy, Gainsight, and Deloitte. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * * * * * * I am looking for blogs on Automation Cloud Cost Management AWS EDP AWS Services Cloud Cost Analytics Cloud Cost Optimization DevOps FinOps Strategy RI Management Kubernetes How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. 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By Priyansh Choudhary 05 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents ## ## **What is an EC2 Auto Scaling Group?** An Amazon EC2 Auto Scaling functionality mainly centers around maintaining a specified amount of instances in a group or automatically increasing and decreasing the size of a group according to different aspects, such as application loads or predetermined schedules. ## **How to reduce AWS expenses using AWS EC2 Autoscaling groups?** AWS EC2 Auto Scaling Groups offer various functionalities to **Scaling policies:** You can establish policies to adjust the number of instances in your Auto Scaling Group based on the current demand. This way, you can prevent unnecessary expenses by increasing instances only during peak hours and reducing them during off-peak hours. **Instance types:** AWS EC2 provides different types of instances with varying specifications and prices. You can select the most cost-effective instance type for your workload, thus saving money without compromising performance. **Spot instances** : Bidding on spare EC2 capacity with Spot instances can save up to 90% on your EC2 costs. However, remember that they may not be suitable for all workloads as they can be terminated with little notice. **Scheduled scaling:** You can schedule automatic adjustments to the number of instances in your AWS Auto Scaling Group, e.g., increase during business hours and decrease during weekends or holidays. **Load balancers:** Load balancers distribute traffic across multiple instances, enhancing availability and scalability. By using them, you can also reduce costs by running only necessary instances for handling the current traffic load. Additionally, here are some other **Use instance reservations:** Reserved instances provide significant discounts compared to on-demand instances. By purchasing reserved instances, you can save up to 75% on your EC2 costs. You can also combine instance reservations with Auto Scaling Groups for further savings. **Use smaller instance sizes:** Smaller instance sizes usually cost less than larger ones. By choosing smaller instances, you can **Optimize storage:** EC2 offers different storage options, each with distinct performance and cost characteristics. By selecting the right storage option, you can save money without performance trade-offs. Auto Scaling Groups can also adjust storage capacity based on demand. **Use Amazon CloudWatch:** CloudWatch provides real-time visibility into your EC2 resources, allowing you to optimize underutilized resources and save money. You can also use **Use instance lifecycle:** The instance lifecycle automates the launching and terminating process of instances. By configuring AWS Auto Scaling Groups to launch Spot instances during high demand and terminate them during low demand, you can optimize costs. Overall, AWS EC2 Auto Scaling Groups provide numerous features and _If you are looking for a trusted partner in your journey of_ _and maximizing the value of your cloud investments,__now and see how CloudKeeper can help._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents ## **What is AWS Config?** AWS Config is a powerful service designed to inspect, audit, and evaluate the configuration of AWS resources and plays a key role in helping companies ensure compliance and risk management. However, as with any cloud service, there is a balance between using the full potential of AWS Config and managing the associated costs. AWS Config tracks and compares current and historical configurations of AWS resources, enabling monitoring, compliance auditing, and troubleshooting. ### **Key Features of AWS Config:** * **Resource Inventory:** Provides an inventory of AWS resources and captures their configurations over time. * **Configuration Change History:** Tracks changes made to resources and records the history for audit and analysis purposes. * **Compliance Auditing:** Enables auditing against internal policies and regulatory requirements by setting up Config Rules. * **AWS Config Rules:** These are pre-configured or custom rules that automatically assess the compliance of resources based on defined conditions. ## **AWS Config Pricing** AWS Config is priced based on the number of configuration items recorded, the number of rules evaluated, and the number of API calls made. Learn more about the factors It can deliver configuration items at two frequencies: periodic and continuous. Periodic recording captures configuration data every 24 hours, but only if a change has occurred, making it useful for tasks like operational planning or auditing. Continuous recording captures configuration items whenever a change happens, which is beneficial for meeting security and compliance requirements by tracking all configuration changes in real-time. **Config Rule Evaluations:** **Conformance Pack Evaluations (when a resource is evaluated by a Config rule within a Conformance Pack):** _**Note** - There may be additional costs for S3 storage of snapshots and history files, SNS charges for change notifications, and Lambda charges if you create custom rules._ ## **Cloud Cost Optimization Techniques for AWS Config** ### **Identification of Cost leaks** **CloudKeeper Lens** The majority of AWS Config costs arise due to a lack of visibility. Cloud costs can quickly jump from $5 to $50 if left unnoticed. CloudKeeper Lens, a **CloudWatch and Athena** AWS native services can also be used to improve the visibility of the cost of this service. Amazon Cloudwatch is one of them. Amazon Athena can also be used to query the data and get accurate information of the cost. It enhances visibility into your Config costs and resource changes, helping in troubleshooting the cost anomalies. By using Athena, you can query Config data and generate custom reports, offering insights into which resources are creating Config items and driving expenses. Here is the To retrieve the number of changes for specific resources and configuration items, we can use the COUNT function and group the results by resourceId and configurationItemMD5Hash (or any other unique identifier for the configuration version). This will give you a count of how many configuration changes occurred for each resource. Here’s how you can design the query to get the number of changes for specific resources: **Example Result:** ### **Fixing the leaks** **1. Selectively Record Resources** By default, AWS Config tracks many different types of resources. However, not all resources are equally important to your compliance and **2. Optimize Config Rule Evaluations** As mentioned earlier, AWS Config charges for rule evaluations. Reducing the number of evaluations by tuning rule evaluation frequency and using rule grouping can lead to direct cost savings. Additionally, turning off unused or unnecessary rules is essential to ensure you aren’t paying for evaluations that don’t add value to your compliance goals. **3. Automate Cost Optimization Through Policies** Use AWS Config and AWS Lambda together to automate the shutdown or cleanup of non-compliant or unnecessary resources. For instance, if an instance in a test environment is not tagged correctly, a Lambda function could automatically stop it, thereby reducing unnecessary costs. Automation not only helps with compliance but can also help you avoid the ongoing costs of unused or misconfigured resources. **4. Review Configuration Snapshots Regularly** AWS Config creates snapshots of your resource configurations, which can take up considerable space over time. Regularly reviewing and cleaning up old or unnecessary snapshots can save storage costs. Additionally, consider exporting configuration data to Conclusion AWS Config offers valuable insights into AWS environment compliance and security, but costs can rise quickly. Optimize usage through selective enabling, custom rules, and regular cost reviews. Balance compliance needs with cost efficiency to make AWS Config a powerful yet cost-effective governance tool. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Arpit is a senior DevOps Engineer with over 6 years of experience in the DevOps and SRE field. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents Managing Reserved Instances and Savings Plans with input metrics such as utilization and coverage doesn’t give a complete picture due to its limitations and can often be misleading. One of the most important Cloud FinOps metrics in business to measure true AWS cost savings is the Effective Savings Rate. To understand how much money businesses save on the cloud one must track the Effective Savings Rate or ESR. It is also considered the AWS metric that matters the most as it provides valuable insight into the level of cost-efficiency. Effective Savings Rate gives an understanding of whether there is scope to reduce cloud spending further. ## **What is an Effective Savings Rate?** While investing, the output metric that eventually matters is the Return on Investment. ROI is fundamentally how investment performance is evaluated. The Effective Savings Rate (ESR) measures the **ROI** for all tools and methods specific to (or across) different cloud providers. **ESR is a crucial KPI to measure the actual** Let us understand by an example. Suppose a business initially spends $200,000 per month on cloud resources. By using discount opportunities, the price gets reduced to $190,000. So the ESR per month is 5 percent of the original cloud bill. Effective Savings Rate is a crucial KPI that tracks what we are saving in the cloud compared to what we would be spending if there are no changes made for cloud cost optimization. ## **How to track and measure Effective Savings Rate for businesses?** The Effective Saving Rate, which includes Savings Plans and RIs across EC2, Fargate, and Lambda, can be calculated as follows: **Effective Savings Rate (ESR) = 1- {Actual Spends Including Discounts/On Demand Equivalent Spend}** Here, _Actual Spend Including Discounts_ refers to the actual amount the business paid with RIs and Savings Plans, amortizing any upfront charges. _On-demand equivalent**(ODE**)_ Spend refers to the amount a business would have paid if no discounts were applied. There are two key practices for calculating Effective Savings Rate. * Negotiating discounted pricing with cloud providers. * Leveraging committed-use discount opportunities, such as reserved instances (RIs) which offer resources at a discounted rate in exchange for a fixed period commitment use. ## **Challenges in Measuring Effective Savings Rate** There are several variables and factors that can influence the Effective Savings Rate and hence calculating ESR is not as easy as it seems. A common scenario is that businesses may obtain credits from the cloud provider, which can later be redeemed for free cloud services. If the credits are only available for a limited period, and the ESR calculations are based on them, then the ESR calculation will not be accurate in terms of cloud cost savings. In this case, the ESR calculation will not reflect the cloud cost savings after the credits expire. This may result in overestimating the ROI of your cloud cost optimization efforts. Another challenge in measuring the Effective Savings Rate is that it measures overall cloud cost savings. However, there can be a case where the savings rates for specific cloud services or products vary significantly from each other. The ESR concept is simple but is often more complicated with large savings portfolios of ## **Strategies to Improve Effective Savings Rate** If there are multiple clouds, it must also be known how business spending outcomes and FinOps ROI vary between clouds. This will help in understanding which clouds are costing more than they should. For example, if the overall ESR is twenty percent, and one of the cloud accounts for eighteen percent of the savings, we get an insight that there can be an opportunity to save more on another cloud. Another important way to get ESR insights is to measure the Effective Savings Rate based on business units. Depending on how each department or team uses cloud resources, and how they approach cost-optimization practices and savings, ESR tracking on a per-business unit basis can be helpful. This practice tells which teams are doing best in cloud cost savings and which teams are obstructing cloud cost optimization. Businesses must ensure that they track ESR continuously and over time. Calculating the ESR only once in a few months would not serve the purpose as it will give clarity of fluctuations that occur in between. **Continuous ESR tracking** also explains the impact of a new product or service launch on the business ROI. ## **Conclusion** Effective Savings Rate (ESR) comes out as a crucial metric in evaluating the effectiveness of your cloud cost optimization strategies and investment. By breaking down ESR calculation across different cloud providers, services, and business units businesses can achieve a more precise understanding and identify the room for improvement in cloud cost savings. _If you are looking for a Cloud FinOps partner to help you with_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents As organizations rapidly migrate to cloud-first strategies, traditional perimeter-based security models are proving insufficient in safeguarding distributed environments. Present **Zero Trust Architecture (ZTA)** , a revolutionary methodology that operates on the principle: “**Never trust, always check**.” This blog explores what Zero Trust means, why it's vital in cloud security, and how businesses can effectively adopt it. ## **What is Zero Trust Architecture?** Zero Trust is a cybersecurity framework that **eliminates implicit trust** and continuously validates every user, device, and network component attempting to access resources. Unlike legacy models that assume trust once inside the network perimeter, Zero Trust assumes **breach by default** and enforces strict access controls. ### Key pillars of Zero Trust include: * **Identity Verification:** Every individual's identity must be verified to determine their true identity. * **Least Privilege Access:** Every identity requires permission only. * **Micro-Segmentation:** Network segments are isolated to contain breaches. * **Continuous Monitoring** : Behavior is tracked in real time for anomalies. ## **Why Zero Trust Matters in the Cloud** Cloud platforms, whether public, private, or hybrid, introduce **complex access pathways** , making perimeter security obsolete. In cloud environments: * Employees access data from various devices and locations. * APIs and third-party services introduce new entry points. * Dynamic scaling and multi-tenancy add to the security complexity. A Zero Trust model ensures that **no action or entity is trusted automatically** , even if it’s operating from within the environment. ## **Benefits of Adopting Zero Trust in the Cloud** 1. **Enhanced Data Protection** By implementing 2. **Improved Incident Response** 3. **Regulatory Compliance** Many standards (e.g., NIST, ISO 27001, GDPR) recommend principles aligned with Zero Trust, aiding compliance efforts. 4. **Resilience Against Modern Threats** From ransomware to insider attacks, Zero Trust helps minimize lateral movement and data exfiltration. ## **How to Implement Zero Trust in Your Cloud Strategy** 1. **Start with Identity and Access Management (IAM):** Deploy multi-factor authentication (MFA), enforce strict password policies, and use role-based access controls. 2. **Monitor and Analyze:** Leverage cloud-native security tools (like AWS GuardDuty, Azure Defender) to track access and usage patterns. 3. **Segment Your Network:** Utilize micro-segmentation to isolate workloads, applications, and environments, thereby limiting the impact of a breach. 4. **Automate Security Policies:** Use 5. **Educate and Involve Your Teams:** Security is a team sport. Train employees regularly and establish a culture of accountability. ## **Challenges to Watch Out For** * Legacy System Integration: Some older systems may not support Zero Trust mechanisms natively. * Complexity of Implementation: ZTA can be intricate; starting small and scaling is key. * User Experience: Overly strict controls might hinder productivity. Balance is essential. ## **Final Thoughts** Zero Trust is not a product, but a mindset — and a continuous journey. As cyber threats grow more sophisticated and the cloud becomes the norm, adopting Zero Trust is not just an option, but a Organizations that initiate early security model development and evolution will be better positioned to protect assets, maintain trust, and ensure business continuity in a cloud-dominated world. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Cloud Engineer Abhinav has hands-on experience in infrastructure solutions that support scalability and reliability. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents In a world where every millisecond matters, scaling is less about capacity and more about control. A small disruption at the core of your infrastructure can ripple across operations, delaying transactions, eroding customer trust, and driving up costs. For enterprises, the strength of their messaging and streaming layers often determines how well they can grow under pressure. Two AWS services Amazon Simple Queue Service (SQS) and Amazon Managed Streaming for Apache Kafka (MSK) sit at the heart of this foundation. Together, they form a ## **Strengthening SQS Architecture for Scale** SQS is the load-bearing pillar of many modern workflows. Just like a strong support beam keeps a structure steady under weight, As workloads grow, consistent and deliberate configuration becomes essential. Aligning Choosing between FIFO and Standard queues is like selecting the right support structure for the job. FIFO enforces strict order where every step matters, while Standard queues favor speed and throughput where flexibility is key. These aren’t technical footnotes, they set the tone for system stability, influencing response times, incident frequency, and overall resilience ## **Monitoring for Early Warning Signals** Operational maturity isn’t measured by how fast you fix a problem, but by how early you see it coming. SQS offers a powerful set of monitoring signals that can turn small tremors into early warnings rather than full-blown outages. Netflix is a classic example of this discipline in action. As Netflix has shared in multiple engineering talks and technical blogs, Long polling reduces unnecessary API calls and optimizes cost efficiency, while tuning batch size and concurrency keeps message processing steady even under unpredictable spikes. With the right practices, monitoring stops being a passive dashboard, it becomes a radar that keeps your operations one step ahead. ## **Building Internal Capability** Technology alone doesn’t guarantee resilience. The real strength comes when teams can solve problems on their own. Organizations that train their engineering teams to diagnose and resolve SQS issues like stuck messages, misconfigurations, or visibility resets and respond faster, depend less on external escalations, and control their operational costs more effectively. This internal capability shortens time to resolution and frees up budget and bandwidth for strategic initiatives instead of firefighting, building a stronger ## **MSK Upgrades with Precision** MSK acts as the load-bearing bridge, carrying the weight of real-time data flows. Upgrading it requires careful orchestration to avoid downtime. The most successful teams follow a Before starting the upgrade, teams take a snapshot of the current setup, set clear rollback triggers, and use test topics to check everything in a controlled way. By fine-tuning replication settings and fixing any known issues early, the upgrade runs smoothly. After the rollout, they monitor consumer lag and replication performance to make sure everything stays stable and healthy. This is not theoretical. Uber has publicly shared how ## Governance That Protects Growth Strong architecture needs structure. For CIOs and CTOs, governance means control without friction. For CFOs, it brings financial predictability and reduced exposure to unplanned risk. Governance isn’t a roadblock, it’s the bridge that lets you cross at full speed. ## **Why This Matters Beyond Engineering** Every detail in how SQS and MSK are implemented, monitored, and governed ties directly to business outcomes. Better configurations reduce operational friction. Proactive monitoring prevents incidents. Strong team capability speeds up resolution. Structured upgrades protect revenue during change. Governance minimizes risk and cost surprises. Companies like Netflix, Amazon, Uber, and Slack didn’t scale successfully just because of their products. They did it because their ## **From Foundation to Advantage** SQS and MSK are the power grid of modern enterprises, invisible when they work, unforgettable when they don’t. Strengthening them isn’t a technical upgrade; it’s strategic insurance for growth. For leaders, this is how you scale without cracks, control cost without surprises, and build trust that lasts. A solid foundation doesn’t just carry growth, it amplifies it. ## **Accelerate your SQS and MSK journey with our certified experts!** Whether you’re optimizing message flows, strengthening monitoring, or planning critical Kafka upgrades, our AWS-certified experts help you do it with precision and confidence. We’ve guided enterprises like Franconnect to build resilient, cost-efficient systems with zero downtime and strong operational foundations. Let’s help you streamline your SQS architecture, enhance MSK performance, and implement best practices that ensure scalability, governance, and long-term stability. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Modern organizations increasingly need to In this scenario, a solution was required that allowed two separate organizations to authenticate with their respective Google identity providers (IdPs) while still accessing shared AWS applications through This article explains why this architecture was chosen and provides step-by-step integration guidance for the complete setup. ## **Why Use a Federating IdP in Front of AWS IAM Identity Center?** AWS IAM Identity Center supports only a single external SAML identity provider (IdP). This can become a limitation when multiple independent organizations need to authenticate using their own identity providers. Introducing a federating identity provider in front of IAM Identity Center addresses this challenge by: * **Supporting multiple external IdPs** (for example, separate Google IdPs for different organizations). * **Providing a unified login experience** across organizations. * **Enabling fine-grained user and group mapping** before sending SAML assertions to AWS. * **Presenting a single SAML IdP to IAM Identity Center** simplifies the AWS-side configuration. This approach centralizes authentication logic while preserving each organization’s existing identity system. ## **Target Architecture** Business Unit 1 Entra IdP ─┐ ├──> Keycloak (IdP Broker) ──> IAM Identity Center (SAML) ──> AWS APPS Business Unit 2 Entra IdP ─┘ ## **Prerequisites** Before starting the integration, ensure the following components are in place: * An active AWS IAM Identity Center. * A running federating identity provider (such as Keycloak) with administrative access. * Two separate external identity providers (for example, Google IdPs, Entra), each configured for its respective organization. * Domain and DNS access for the federating IdP, ensuring it is publicly reachable if using a hosted IAM Identity Center deployment. ## **Integration Steps** ### **1. Configure IAM Identity Center to Trust the Federating IdP as a SAML Provider** 1. In AWS IAM Identity Center, navigate to **Settings → Identity Source**. 2. Select**External Identity Provider**. 3. Download the **IAM Identity Center SAML metadata** file. 4. Note the **ACS URL** and **Entity ID** , as these values will be required when configuring the federating IdP. ### **2. Create a SAML Client/Application in the Federating IdP (for AWS)** In the federating identity provider (for example, Keycloak): #### **1. Create or Select a Realm** Create a new realm or select an existing realm dedicated to AWS access. #### **2. Create a New SAML Client** 1. Go to **Clients** under the selected **Realm**. 2. Click **Import Client**. 3. Click **Browse** and upload the **AWS IAM Identity Center SAML metadata** that you downloaded earlier. 4. Click **Save**. #### **3. Configure Client Settings** Update the following fields in the client configuration: * **Valid Redirect URIs:** AWS IAM Identity Center ACS URL Set the following values: * **Base URL:** your_keycloak_login_url/realms/your_realm_name/protocol/saml/clients/amazon-aws * **IDP Initiated SSO URL Name** : amazon-aws After making these changes, click Save to apply the configuration. Learn more about #### **4. Export Keycloak SAML Metadata** Your **IdP metadata file** can be obtained from the **Keycloak Administration Console**. 1. In the Keycloak Administration Console, select Realm Settings from the main navigation sidebar. 2. Go to the General tab. 3. Under the Endpoints section, click the link for SAML 2.0 Identity Provider Metadata. ### **3. Upload Federating IdP Metadata to AWS IAM Identity Center** 1. In **AWS IAM Identity Center** , upload the **Keycloak SAML metadata** exported from the federating IdP. 2. Once uploaded, AWS establishes the **SAML trust relationship** between IAM Identity Center and the federating IdP. ### **4. Add Multiple External Identity Providers in the Federating IdP** Within the federating identity provider: 1. Navigate to **Identity Providers**. 2. Add each external IdP (for example, separate Google IdPs for different organizations). However, there is an important limitation:**Keycloak does not allow creating multiple Google IdPs with different redirect URIs directly from the admin console** , because the console does not expose options to modify the redirect URI configuration for the identity provider. 3. To work around this limitation, the configuration can be performed using the **Keycloak CLI tools or Admin API** , which allow full control over the identity provider settings, including redirect URIs and other parameters. This approach makes it possible to create and manage multiple Google IdP configurations within the same realm. 4. Configure the required details for each IdP, such as: * **Client ID and Client Secret** * **Authorized Redirect URIs** ### **5. Map User Attributes for IAM Identity Center** The federating IdP should send user attributes that the IAM Identity Center can interpret. Common attributes include: * **email** * **givenName** * **groups** (optional but useful for application or permission assignments) * These attributes can typically be configured under **Application → Attribute Mappers.** ### **6. Test the End-to-End Authentication Flow** 1. Access the **AWS IAM Identity Center** user portal. 2. Confirm that authentication redirects to the **federating IdP login page**. 3. Select the appropriate **external identity provider**. 4. Authenticate with the selected IdP. 5. Verify that the user successfully signs in and can view the expected **AWS applications or accounts**. ## **What This Gives Us** * A single AWS integration point (Keycloak). * Flexible federation of multiple organizations. * Consistent access to AWS applications through AWS IAM Identity Center. * Centralized control over authentication behavior and identity mapping. ## **Conclusion** For organizations that must integrate multiple identity providers into AWS, Keycloak offers an elegant and scalable solution. By using Keycloak as a federation layer, we could allow multiple organizations to authenticate using their own IdPs—while keeping a single, clean SAML integration into AWS IAM Identity Center. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents FinOps for Cloud is what a personal trainer is for your fitness goals. The set of practices, policies, and guidelines that FinOps lays out helps organizations get financially fit in cloud usage. While industry experts like A well-functioning Cloud FinOps practice requires the Finance, Engineering, and Business teams to work together to fill the gaps in cost-effective cloud usage and look out for each other. However, there is a concerning statistic that needs to be addressed. Studies by the Here's the deal: engineers are the architects of the cloud. They're the ones making infrastructure decisions, and those choices can have a wild impact on cloud bills. This blog intends to bridge this gap between the FinOps stakeholders. Here are three actionable tips which can help engineers become more cost-savvy about the cloud and be better equipped to ‘take action’. ## **Get Involved with Budgeting** It’s not always you, the engineers, but the organization as a whole. Most organizations use a top-down approach for setting budgets, where the finance team creates a rather immovable budget for the year and everyone else should follow on. But obviously, engineers like you have to prioritize aspects like customer experience, performance benchmarks, and the infrastructure needed to support an application. This might force you to spin up new resources and exceed utilization limits, thus overspending on the budget. Thus, it's always a tug of war between contradicting priorities, with finance emphasizing The right way to tackle this is to rethink the budgeting approach to a “participatory” model. Cloud budgeting should happen with the finance, engineering, and business leaders all on the same page. To get a better picture of the technical requirements, the finance team could seek wisdom from the engineers regarding the following queries * The kind of architecture, tools, and services they are planning to implement * What portion of the infrastructure would the hyperscaler manage versus what the company would be responsible for? * How will discounts like Reserved Instances help in overall cloud cost reduction and And anything else that you can think of. Participatory budgeting might feel like a bit much in the beginning. But it will surely get better and be seamless, as and when the FinOps practices mature. ## **Reframe your KPIs** Of all the different employee performance metrics to assess an engineer, cost is often the least used. But this can become a game changer in terms of promoting the practice of ‘cost avoidance’ and ‘cloud cost optimization’ among engineers. A cost-based KPI is indeed a cultural shift for engineers that will drive you toward - * **Ownership** - You will have a deeper understanding of the cost of cloud resources and the need to manage them responsibly. This will encourage you to make informed decisions regarding * **Accountability** - Who needs to be more accountable for cloud costs than the people who use it firsthand? Being accountable will make you more conscious about your choices and lead to better cost control. But, there’s a catch. For successful implementation of the cost-based KPI for desired results, engineers must be provided with real-time cloud cost data with the right level of granularity. Interestingly, upstream cost data, the cloud bill insights after deployment, seems to be driving better action rather than cost forecasts. ## **Get Trained on Cloud Tools** The key aspect in creating cost-aware cloud professionals is to make sure the engineers are knowledgeable of the various cloud cost optimization practices. This is the step that will keep the cloud governance practices up and running like a well-oiled machine. With a well-thought-out training plan on cloud cost optimization, your organizations could accelerate the learning curve for cloud cost intelligence. This could help you acquire the necessary skills for - * **Enhanced cost visibility** - Expertise in leveraging various tools like the AWS Cost Explorer to * **Choosing the right instance types** - Ability to research and find the right computing power needed at the most cost-effective pricing, rather than getting lost in the huge selection of instances. This would also help in choosing the most affordable regions, availability zones, processor types, and more. * **Tagging and cost allocation** - Integrating a tagging policy into the deployment process, thereby enhancing usage tracking, monitoring, resource identification, and even system functionality. * **Better knowledge of cloud tools** - Understanding of various cloud optimization tools offered by the Hyperscalers. For example, AWS offers tools like AWS Cost Explorer for cost analysis, Many more advantages could be attributed to educating engineers on cost-optimized cloud usage. Your companies could also use approaches like ‘gamification’ to increase engagement, where friendly competition drives enthusiasm for learning and improvement. We have only pondered over a few basic, but must-have strategies that can help engineers like you become better at identifying and minimizing cloud costs. With enough research and discussions with the right stakeholders, businesses can formulate a more customized approach to accomplish their cloud cost optimization goals. ## **Working with a FinOps Partner** Incorporating these seemingly straightforward strategies, like that of participatory budgeting, into your organization may appear challenging due to the necessary cultural and governance shifts. This is precisely where the expertise of a FinOps partner comes into play. With an experienced FinOps partner by your side, you can rest assured that they will ensure a smooth transition from your existing business culture towards one that is more cost-aware. FinOps partners like CloudKeeper has already been helping 300+ businesses across the world in reducing their cloud costs by more than 20% on average. Moreover, CloudKeeper offers solutions that deliver By synergizing the efforts of the FinOps partner and your engineering team, you would achieve cloud cost reduction above and beyond your cost optimization goals, unlocking substantial savings and efficiency gains. _How about booking an absolutely Free Demo of CloudKeeper and understanding how we can help you transform your Cloud FinOps journey?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents ## Introduction The Azure Key Vault Provider for Secrets Store CSI Driver facilitates the seamless integration of an Azure Key Vault as a secure secret store with an Azure Kubernetes Service (AKS) cluster through the utilization of Container Storage Interface (CSI) volumes. This guide demonstrates how to implement and use the Azure Key Vault Provider for Secrets Store CSI Driver in AKS clusters. It covers integration steps, benefits, and best practices for secure secret management, including setup, configuration, and ## How it works The diagram below illustrates how Secrets Store CSI volume works: Just like Kubernetes secrets, upon the initialization and restart of a pod, the Secrets Store CSI driver interacts with the external Secrets Store through gRPC to fetch the secret content specified in the SecretProviderClass custom resource. This content is then mounted within the pod as a `tmpfs` volume, and the secret data is written into that volume. When a pod is deleted, the corresponding volume is cleaned up and deleted. ## Features While Kubernetes secrets provide a basic mechanism for storing such data, they may not offer the robust security measures required for certain scenarios. Secrets Store CSI Driver’s notable features make it a preferred choice for organizations seeking a robust and flexible secret management solution: 1. Mounts secrets, keys, and certificates to a pod using a CSI volume. Secrets are directly mounted in the pod’s volume so secrets cannot be accessed directly outside the pod. 2. Kubernetes secrets are not secure. Secrets Store CSI Driver uses external secret stores to store the secrets which are more secure. 3. Secrets Store CSI Driver does not store secrets in etcd and supports CSI inline volumes. 4. Supports mounting multiple secrets store objects as a single volume. 5. Supports pod portability with the SecretProviderClass CRD. 6. Supports Windows containers. 7. Syncs with Kubernetes secrets. 8. Supports autorotation of mounted contents and synced Kubernetes secrets. 9. Create an AKS cluster with Azure Key Vault Provider for Secrets Store CSI Driver support ## Solution approach Implementing the Azure Key Vault Provider for Secrets Store CSI Driver involves a strategic approach to ensure secure and effective deployment within your AKS cluster. Follow these steps for a successful setup: * Install the driver and providers in either the kube-system namespace or a dedicated namespace. The driver is deployed as a DaemonSet and requires permissions to mount kubelet hostPath volumes and access pod service account tokens. It should be handled as a privileged component, and regular cluster users should not have the authority to deploy or modify it. * The above point can be ignored if you are installing the CSI driver by enabling azure-keyvault-secrets-provider as add-ons (which we’ll be using in this blog); the AKS handles this on its own. **Prerequisites:** * Check that your version of the Azure CLI is 2.30.0 or later. If it's an earlier version, install the * If you're restricting Ingress to the cluster, make sure ports 9808 and 8095 are open. **Steps:** 1. Create an Azure resource group using the [az group create] command. 2. Create an AKS cluster with Azure Key Vault Provider for Secrets Store CSI Driver capability using the az aks create command and enable the azure-keyvault-secrets-provider add-on. If you are using Azure Portal then the option to enable secret store CSI driver can be found in the `Advanced` options. Upgrade an existing AKS cluster with Azure Key Vault Provider for Secrets Store CSI Driver support: Upgrade an existing AKS cluster with Azure Key Vault Provider for Secrets Store CSI Driver capability using the az aks enable-addons command and enable the azure-keyvault-secrets-provider add-on. The add-on creates a user-assigned managed identity you can use to authenticate to your Azure key vault. If you are using Azure Portal, the same addon can be enabled in Setting -> Cluster configurations. **3. Verify the Azure Key Vault Provider for Secrets Store CSI Driver installation:** Verify the installation is finished using the kubectl get pods command, which lists all pods with the secrets-store-csi-driver and secrets-store-provider-azure labels in the kube-system namespace. **4. Create or use an existing Azure key vault:** Create an Azure key vault using the az keyvault create command. The name of the key vault must be globally unique. Your Azure key vault can store keys, secrets, and certificates. In this example, the **az keyvault secret set** command is used to set a plain-text secret called secretName. You can also create the Key Vault and Key vault secret using Azure portal. **Note:** Azure role-based access control (Azure RBAC) should be configured for the key vault. RBAC can be found in **Access Configuration** settings while creating the key vault. **5. Provide an identity to access the Azure Key Vault Provider for Secrets Store CSI Driver:** Access with a user-assigned managed identity- Find the Client ID of the managed identity created by azure-keyvault-secrets-provider addon. Use the following command to find the same- The same can be found through Azure portal in managed identities. The name of the managed identity has a syntax: **azurekeyvaultsecretsprovider- ** Create a role assignment that grants the identity permission to access the key vault secrets, access keys, and certificates using the az role assignment create command. **6. Create a SecretProviderClass:** You can use the following YAML to create a SecretProviderClass- apiVersion: secrets-store.csi.x-k8s.io/v1 kind: SecretProviderClass metadata: name: azure-kv-spc spec: provider: azure secretObjects: - data: - key: username objectName: secretName secretName: mysecret type: Opaque parameters: usePodIdentity: "false" useVMManagedIdentity: "true" userAssignedIdentityID: keyvaultName: objects: - | array: - | objectName: secretName objectType: secret objectVersion: "" tenantId: **Note:** a) No need to create k8s secret object separately. It will be created automatically when you create a pod with CSI driver volume. b) The secretObjects block in the above YAML is optional and is only needed if you need to synchronize mounted content with a Kubernetes secret. You will still get the key vault object mounted to the pod if you do not use this block. **7. Set an environment variable to reference Kubernetes secrets:** Use the following YAML to reference your newly created Kubernetes secret by setting an environment variable in your pod: kind: Pod apiVersion: v1 metadata: name: nginx-csi spec: containers: - name: nginx image: nginx volumeMounts: - name: secrets-store mountPath: "/mnt/secrets-store" readOnly: true env: - name: SECRET_USERNAME valueFrom: secretKeyRef: name: mysecret key: username volumes: - name: secrets-store csi: driver: secrets-store.csi.k8s.io readOnly: true volumeAttributes: secretProviderClass: "azure-kv-spc" **8. Validate the secrets:** a) Show secrets held in the secrets store using the following command. b) Display a secret in the store using the following command. This example command shows the test secret secretName. **9. Enable and disable autorotation:** When the Azure Key Vault Provider for the Secrets Store CSI Driver is enabled, it periodically updates the mounted secrets within your pods and the corresponding Kubernetes secrets defined in the secretObjects field of your SecretProviderClass. This update process is initiated based on the rotation poll interval that you have configured. By default, the rotation poll interval is set to two minutes. When a secret updates in an external secrets store after initial pod deployment, the Kubernetes Secret and the pod mount periodically updates. **a) Mount the Kubernetes Secret as a volume:** Use the autorotation and Sync K8s secrets features of Secrets Store CSI Driver. The application needs to watch for changes from the mounted Kubernetes Secret volume. When the CSI Driver updates the Kubernetes Secret, the corresponding volume contents automatically update as well. **b)Application reads the data from the container’s filesystem:** Use the rotation feature of Secrets Store CSI Driver. The application needs to watch for the file change from the volume mounted by the CSI driver. **c)Use the Kubernetes Secret for an environment variable:** Restart the pod to get the latest secret as an environment variable. Use a tool such as _Enable auto-rotation on a new AKS cluster:_ __ _Enable auto-rotation on an existing AKS cluster:_ __ _Specify a custom rotation interval:_ __ _Disable auto-rotation:_ To disable autorotation, you first need to disable the add-on **azure-keyvault-secrets-provider**. Then, you can re-enable the add-on without the enable-secret-rotation parameter. You can see the automatic change in value of the secretName after the autorotation interval. But the same change won’t be reflected in the environment variable that is using this ‘secretName’ value. To reflect the change in this case you need to restart the pod. ## Additional Examples The following example illustrates the usage of multiple secrets from Azure Key Vault in a single SecretProviderClass YAML file: secretProviderClass.yaml- apiVersion: secrets-store.csi.x-k8s.io/v1 kind: SecretProviderClass metadata: name: azure-kv-spc spec: provider: azure secretObjects: - secretName: bucketsecret type: Opaque data: - key: DB-USER objectName: DB-USER - key: DB-PASSWORD objectName: DB-PASSWORD - key: DATABASE-HOST objectName: DATABASE-HOST - key: DATABASE-PORT objectName: DATABASE-PORT - key: DATABASE-NAME objectName: DATABASE-NAME parameters: usePodIdentity: "false" useVMManagedIdentity: "true" userAssignedIdentityID: keyvaultName: objects: | array: - | objectName: DB-USER objectType: secret objectVersion: "" - | objectName: DB-PASSWORD objectType: secret objectVersion: "" - | objectName: DATABASE-HOST objectType: secret objectVersion: "" - | objectName: DATABASE-PORT objectType: secret objectVersion: "" - | objectName: DATABASE-NAME objectType: secret objectVersion: "" tenantId: **pod.yaml-** kind: Pod apiVersion: v1 metadata: name: nginx-csi spec: containers: - name: nginx image: nginx volumeMounts: - name: secrets-store mountPath: "/mnt/secrets-store" readOnly: true env: - name: DB_USER valueFrom: secretKeyRef: name: bucketsecret key: DB-USER - name: DB-PASSWORD valueFrom: secretKeyRef: name: bucketsecret key: DB-PASSWORD - name: DATABASE-HOST valueFrom: secretKeyRef: name: bucketsecret key: DATABASE-HOST - name: DATABASE-PORT valueFrom: secretKeyRef: name: bucketsecret key: DATABASE-PORT - name: DATABASE-NAME valueFrom: secretKeyRef: name: bucketsecret key: DATABASE-NAME volumes: - name: secrets-store csi: driver: secrets-store.csi.k8s.io readOnly: true volumeAttributes: secretProviderClass: "azure-kv-spc" ## Limitations a) Enable Secret autorotation feature has been released in v0.0.15+ and is not available in release v0.0.14 and earlier of Secrets Store CSI Driver. b) Secrets not rotated when using subPath volume mount. volumeMounts: - mountPath: /app/spapi/settings.ini name: app-config subPath: settings.ini ... volumes: - csi: driver: secrets-store.csi.k8s.io readOnly: true volumeAttributes: secretProviderClass: app-config name: app-config For more details refer to https://secrets-store-csi-driver.sigs.k8s.io/known-limitations.html ## Conclusion This guide provided a comprehensive walkthrough for implementing the Azure Key Vault Provider for Secrets Store CSI Driver in AKS clusters. It covered integration, benefits, and best practices for secure secret management, empowering users to enhance their Kubernetes application security and efficiently leverage Azure Key Vault. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Jatin is a DevOps Engineer with expertise and multiple certifications in Azure and AWS. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents In today’s always-on world, reducing downtime is crucial. Disaster recovery (DR) strategies enable businesses to quickly recover from outages and maintain service availability. Amazon Route 53 is a highly available and scalable Domain Name System (DNS) service that plays a key role in DR by routing traffic between on-premises infrastructure and AWS Cloud resources. This blog looks at how to use Route 53 failover routing policies to create ## **Understanding Disaster Recovery and Route 53** Disaster recovery involves restoring operations after unexpected failures caused by hardware problems, natural disasters, or cyberattacks. AWS offers several DR strategies, ranging from simple backups to multi-site active/active deployments. Amazon Route 53 provides resilience by giving DNS-level control over traffic distribution. Its features, like health checks and failover routing, can detect outages and redirect clients to healthy endpoints, ensuring minimal downtime. **Key DR methods supported by Route 53 include:** * **Pilot Light:** Keep a minimal version of your environment in AWS and scale up during a disaster. * **Warm Standby:** Maintain a scaled-down, yet fully functional, copy of your production system in AWS. * **Multi-Site (Active/Active):** Run workloads in both on-premises and AWS at the same time. ### **Route 53 Failover Routing Policy** The failover routing policy directs traffic to a primary resource under normal conditions and to a secondary resource during an outage. **How It Works** 1. **Define Primary and Secondary Endpoints:** The primary could be an on-premises web server, while the secondary might be an A 2. **Configure Health Checks:** Route 53 continuously monitors the health of your primary endpoint using HTTP/HTTPS or TCP checks. 3. **Automatic Failover:** If health checks fail, traffic automatically routes to the secondary endpoint until the primary recovers. This policy helps organizations blend existing infrastructure with AWS resources, ensuring high availability. For instance, it would lead to ## **Designing a Hybrid Disaster Recovery Architecture** A hybrid DR plan uses both on-premises and AWS resources, which lowers costs and enhances resilience. **Key Components** * **Primary Infrastructure:** Your existing on-premises servers or data center. * **Secondary Infrastructure:** AWS-hosted services like EC2, Application Load Balancer, or * **Route 53 Health Checks:** Monitor endpoint availability using * **DNS Records:** Configure failover routing records for each application. **Steps to Implement** 1. Assess Your Workloads: Identify critical applications that need failover. 2. Provision Secondary Resources: Deploy equivalent infrastructure in AWS (e.g., AWS EC2 behind an Elastic Load Balancer). 3. Set Up Route 53 Hosted Zones: Create DNS records with failover routing. 4. Configure Health Checks: Monitor the primary site’s availability. 5. Test Failover Scenarios: Simulate outages to confirm seamless redirection. ## **Best Practices for DR with Route 53** * **Use Multiple Health Checks:** Combine endpoint and * **Leverage Latency or Geolocation Routing:** For global users, pair failover with latency-based routing for the best performance. * **Enable DNSSEC:** Enhance DNS security by protecting against spoofing. * **Regular Testing:** Schedule failover drills to ensure readiness. * **Automate Recovery:** Use ## **Advantages of Using Route 53 for DR** * **High Availability:** Globally distributed DNS servers lower the risk of single points of failure. * **Cost-Efficiency:** Pay only for the resources you need in standby. * Seamless Integration: Works well with other AWS services like CloudWatch, * **Scalability:** Easily handle large-scale traffic redirection. By combining Amazon Route 53 failover routing with a hybrid architecture, organizations can create a strong disaster recovery solution that protects both on-premises and cloud workloads. Whether using a pilot light, warm standby, or multi-site strategy, Route 53 supports automated, reliable failover with minimal complexity. Investing in a solid DR plan ensures business continuity, protects against data loss, and maintains customer trust, all backed by the flexibility of AWS and Route 53. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Jatin is an AWS-certified SysOps Administrator Associate with extensive expertise in AWS cloud services and a broad spectrum of DevOps tools. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents In today’s cloud-native world, database availability is absolutely critical. Amazon Aurora, being a high-performance and fully managed relational database, is designed with fault tolerance in mind. But like with most things in tech, the way you configure it can make a huge difference when things go sideways. In this post, I’ll walk you through a real incident from a production environment that we recently handled. It’s a good example of how things can still go wrong despite having a seemingly resilient setup—and what you can do to avoid similar issues. ## **The Scenario: Unexpected Downtime Despite Redundancy** One of our customers was running an Aurora cluster with the standard setup—**one Writer and one Reader instance**. To manage database connections efficiently, they were using RDS Proxy with a read-only endpoint. On paper, this sounds pretty solid: * A separate Reader handles read traffic. * RDS Proxy manages database connections efficiently. However, the Reader instance experienced a host-level failure. At this point, RDS Proxy, which was wired to the read-only endpoint, just waited for the Reader to come back. **What didn’t happen?** * Proxy didn’t reroute traffic to the Writer, even though it was still healthy and available. * As a result, read queries started failing, application performance tanked, and users experienced ten minutes of downtime for read-only queries. ## **Digging Into the Root Cause** When we looked deeper, here’s what we found: * The Reader became unreachable due to a host issue. * Aurora kicked off its automatic recovery, which involved replacing the host and rebooting. * Read queries started failing with the error: _ERROR 9501 (HY000): Timed-out waiting to acquire database connection._ * Since there were no other Readers, and RDS Proxy does not redirect read-only queries to the Writer, the read-only queries timed out. Now, this might feel counterintuitive, but according to the AWS documentation, this is expected behavior. ## **What We Learned: Tips for Better Availability** If you’re using Aurora with RDS Proxy, there are a few things you should definitely consider to avoid this kind of scenario. **Option 1: Improve RDS Proxy Configuration** **1. Always Have More Than One Reader** * RDS Proxy’s read-only endpoint depends on at least one Reader being available. * If there’s only one Reader instance and it goes down, the read queries will time out waiting for the Reader to come back. * **Solution** : Always add a second Reader, which could be of a smaller configuration to optimize costs. **2. Set Failover Priorities Wisely** * Aurora allows you to assign failover tiers to Writer and Reader instances. * Don’t keep all instances at the same priority level. * **Tip** : Keep the Writer at a higher priority and Readers at different lower tiers to give the system more flexibility during recovery. **Option 2: Remove RDS Proxy and Use Cluster Endpoints** Instead of relying on RDS Proxy, use Aurora cluster endpoints directly. * Cluster endpoints handle failover dynamically, unlike instance endpoints, which are tied to specific instances. * Implement connection pooling at the application level to manage database connections efficiently. * This avoids the dependency on RDS Proxy and reduces unnecessary waiting time in case of failovers. **Wrapping Up** At the end of the day, Aurora gives you a solid foundation, but it’s up to us to build a setup that’s actually resilient. Just adding one more Reader and adjusting failover priorities could have prevented the downtime in this case. These might sound like small tweaks, but in production, they can make the difference between smooth failover and frustrated users. Also, remember: * RDS Proxy is powerful, but it has its own behaviors. * Make sure you understand how its endpoints work—especially in failover scenarios. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Himanshu is a Senior DevOps Engineer with hands-on experience in cloud infrastructure, automation, and implementing modern DevOps best practices. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents An organization's dependence on cloud services, particularly as a key element of its expansion strategy, has become evident more than ever before. While cloud services facilitate rapid and efficient scaling, the associated costs escalate as the organization grows. Regardless of the company's scale, cloud management is crucial to avoid squandering finances and resources on underutilized cloud assets. One solution offered by AWS for organizations with growing cloud spends is their Enterprise Discount Program (EDP). ## **What is AWS Enterprise Discount Program (AWS EDP)?** The AWS Enterprise Discount Program (AWS EDP) is a cost-saving initiative tailored for organizations with substantial cloud usage. The ## **Eligibility for AWS EDP** Organizations depicting a minimum annual spend of USD 1 Million towards their AWS usage become eligible for an AWS enterprise discount program. They must also commit to a term in the range of 1 to 5 years and each subsequent year should reflect a higher commitment than the previous year. The AWS EDP facilitates sustainable scaling in return for a prolonged commitment from clients, typically ranging from 1 to 5 years. The clients who commit more for a longer time get higher discounts in AWS EDP. So, three 1 year terms are less viable than a single 3-year commitment. Let us understand with an example. From Table 1 and Table 2, we can see that the value of services consumed is the same in both cases but in Table 1, the client has to pay the difference for the underspend and buy additional services for the overspent. This overspent will be charged according to the on-demand pricing model which is relatively expensive. For organizations who foresee significant growth in their AWS usage over the next 1-5 years and are certain about growing business needs, AWS EDP would be the way to go for them. ## **Benefits of participating in AWS EDP** Participating in the **1. Discounted Rates:** One of the primary advantages is the potential for cloud cost savings through the application of discounted rates. It provides a structured framework for organizations to receive significant cost savings on their AWS usage fees. Based on the customer's total annual commitment and their growth commitment over time, AWS EDP allows organizations to optimize their cost savings according to their specific usage patterns and growth trajectories. **2. Long-Term Commitment Incentives:** AWS EDP is the program that encourages long-term commitments from customers, typically ranging from 1 to 5 years. Due to the commitment, higher discount rates are rewarded, incentivizing the organizations to engage in sustained partnerships with AWS. **3. Predicted Budgeting:** Participants of EDP Amazon web services help organizations budget and plan for their cloud expenses over an extended period of time due to a more predictable pricing structure. You know exactly how much you'll be spending on AWS for the duration of the agreement, making **4. Strategic Partnership with AWS:** By participating in AWS EDP, there is an enhanced collaboration, support and close partnership between the organization and AWS. Being an AWS EDP partner, the organizations demonstrate a strategic and long term commitment to AWS which unlocks additional benefits and resources. **5. Versatile Applicability:** The discounts provided through the AWS EDP are applicable to a diverse range of AWS services. This flexibility allows organizations to utilize various cloud solutions while still ## **The right partner can help maximize your benefits from EDP** An AWS EDP partner can help **1. Consultation for Optimized Commitments:** Alignment of commitments with organizational goals is the top priority and an ideal AWS EDP partner can help you with that. Furthermore it is essential to determine the right commitment value. **2. Enhanced Discounts and Commitment Flexibility:** An AWS EDP partner can help negotiate better discounts and also lower the annual commitment. **3. Tailored Reporting and Monthly Insights:** An enterprise discount doesn’t necessarily close doors for further optimization. Partners can help provide customized usage reports along with recommendations for further cost optimization. **4. Efficient Invoicing and Multi-entity Support:** AWS EDP Partners can help facilitate invoicing from foreign entities, split invoices across different organizational entities, enable invoices in different currencies, and ensure compliance in financial reporting. **5. Value Added Benefits:** They deliver additional value added benefits without any additional cost, including Cloud AWS EDP partners have expertise in AWS and EDP collaboration and offer significant support during contract discussions, negotiating advantageous terms, and enhancing the contract for increased cost efficiency. EDP partners can additionally offer training and assistance to cloud engineers, enabling them to efficiently harness AWS services after joining the EDP. This support aims to expedite their setup process with minimal exertion and expenses. ## **Secure Maximum discounts on EDP with CloudKeeper EDP+** **** There are a large number of **offers a number of benefits right from the contracting stage, providing intelligent and effective contract negotiations which lead to higher discounts and lower annual commitments.** Furthermore CloudKeeper EDP+ provides a partner led Enterprise Support at a lower cost, It also provides a host of value added services such as free access to CloudKeeper Lens, the cloud cost visibility and recommendations platform, providing daily, weekly and monthly cost breakups, alerts through emails and Slack, and resource level break up. Additionally, CloudKeeper also provides FinOps audit and consulting services, _CloudKeeper is a one-stop solution for all your_ _needs and guarantees instant cloud savings. Want to learn more?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Complete Guide to AWS PPA Contract Negotiation for Growing Enterprises A practical guide to AWS PPA or EDP negotiations, covering commitments, discounts, flexibility, risks, and best practices to help growing enterprises secure better pricing and long-term cloud value. By Team CloudKeeper 19 Dec, 2025 Ask the Cloud Expert: A Deep Dive Q&A on AWS PPA In this Q&A, CloudKeeper’s AWS PPA expert Aman Dixit shares real-world insights to help clients navigate PPAs and make smarter, cost-effective decisions. By Team CloudKeeper 05 Sep, 2025 Introducing the AWS EDP Tracker in CloudKeeper Lens AWS EDP Tracker is a real-time interactive dashboard that gives you end-to-end visibility to monitor, forecast, and optimize your EDP spend throughout its term. By Harsh Agarwal 06 May, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Cloud computing is one of the biggest disruptors in today’s technological era. Because of its myriad financial and operational benefits, enterprises are now flocking to leverage the advantages of the cloud. However, with the benefits of the cloud come its associated costs. As a result, it is not uncommon for enterprises to encounter large cloud bills, which are complicated to manage. In today’s topic, we dive into **cloud budgeting and cloud cost forecasting** - both key elements in your cloud FinOps strategy, that will help you manage cloud cost overruns and deal with budget shocks in your journey. ## **What is cloud budgeting?** Cloud budgeting involves estimating, allocating, and controlling the financial resources dedicated to cloud services. It is a financial plan that estimates how much money you will spend on cloud computing over a fixed period. Cloud budgeting is always a proactive approach that aims to manage cloud expenditures by setting up cost thresholds, managing cost overruns, cost allocation, etc., and ensuring that your costs align with your overall business objectives. ## **How does cloud budgeting work?** The first step towards effective cloud budgeting starts with a clear understanding of the company’s cloud usage patterns and requirements. It includes identifying the necessary resources, estimating their costs, and A critical element of budgeting also involves ## **Why is accurate forecasting important in Cloud FinOps?** _“The goal of forecasting is not to predict the future but to tell you what you need to know to take meaningful action in the present.” - Paul Saffo_ __ Accurate cloud cost forecasting is important in a company’s cloud journey for several reasons. **1. Cost management:** With accurate cloud cost forecasting, enterprises can predict their cloud costs more precisely, thus budget allocation becomes more efficient, and cost spikes can be avoided. **2. Resource optimization:** Cloud cost forecasting allows organizations to optimize resource utilization and allocation by **3. Performance optimization:** Accurate cloud cost forecasting enables organizations to anticipate changes in workload demand and performance requirements. This allows them to proactively adjust resources and configurations to maintain optimal performance levels and ensure a positive user experience. **4. Risk management:** Accurate forecasting helps organizations ## **Common challenges in cloud cost forecasting** **1. Poor cloud visibility:** Poor cloud cost visibility can set you back in your forecasting efforts. Cloud bills are generally very complex and challenging to understand. Even with a cloud bill at hand, it is very difficult to gauge how much money you spent on a product, feature, team, or service. Unless you truly understand what drives your cloud costs, it is not easy to make a forecast on your budgets. **2. Challenges with cloud tagging:** Cloud tagging is assigning meta-data or labels to cloud resources for easy identification. Cloud tagging can help you track usage, performance, etc, hence setting up a strong foundation for correct forecasting. However, the challenges with cloud tagging are many. There are challenges with a **3. Multi-cloud adds to the complexity:** **4. Alignment between finance and engineering:** The priorities of both the finance and engineering teams are poles apart. Finance’s objective is to maximize the cloud ROI. Engineering’s is to improve functionality, speed, availability, and security. Finance would find it seemingly difficult to invest in a feature that does not improve profitability. Similarly, engineering cannot make architectural decisions that can lead to better cost management. This misalignment makes budgeting and forecasting very challenging. **5. The variety makes it challenging:** Figuratively speaking, cloud comes in different shapes, sizes, and types. Cloud service providers like AWS offer numerous cloud services. The number of choices in a simple thing like instance type can also be quite overwhelming. With so many offerings, forecasting how much cloud resource you will need, and of what type is next to impossible. ## **Different types of cloud cost forecasting** Forecasting is of different types corresponding to different FinOps maturity phases. **1. Simple forecasting:** In simple cloud cost forecasting, you assume that your spending for the next period will be the same as the current period. It is also called “naive forecasting”. Accuracy with simple forecasting is very low since businesses are always evolving and so are their costs. **2. Trend-based forecasting:** It uses historic cloud spend to predict the future. Trend forecasting generally picks up the trend of growth from a past period and assumes the growth will be similar in the future. For a company growing at a steady rate, trend-based cloud cost forecasting offers a pretty accurate forecast concerning cloud spending. **3. Driver-based forecasting:** Driver-based forecasting utilizes the business KPIs to predict future demand. The forecast reflects what the business is planning, whether this is a release of a new product, a promotion that is expected to increase demand, etc. This forecasting requires working closely with business stakeholders, and hence the accuracy of this method is a little tricky to achieve. **4. Net new workloads forecasting:** Net new workloads forecasting is based on new pipelines or workloads that an organization might be planning. There are different models for new workload forecasting - based on existing applications, publicly available forecasting calculators, third-party data sources, etc. ## **Strategies to improve accuracy in cloud cost forecasting** **1. Monitor cloud spending regularly:** Cloud budgets need to be monitored closely and regularly to keep track of unnecessary costs, idle resources, etc. Cloud cost monitoring tools can be of great help in making the tracking process seamless. **2. Understand your cloud bill:** Make use of native tools like AWS cost explorer, cost and usage report, etc. to nail your cloud bill. Cloud costs are operational expenses and keep on fluctuating based on resource usage and demand. So, **3. Get everyone on board:** Accurate cloud cost forecasting requires that everyone - finance, developers, system operators, DevOps specialists, SecOps, and other stakeholders who affect cloud costs be on board to discuss, deliberate, and join hands for budgeting. **4. Play around with your last budget:** One of the easiest ways to land close to an accurate cloud cost forecast is to add or subtract a certain percentage from your last budget. Whether to add or subtract, you can decide based on your business plans. If there is no substantial change, you can stick to your last budget which would be a good forecast in itself. **5. Set a trial budget based on experience:** If you have set budgets and costs on-premise, you should have no difficulty in setting up a trial budget. Then refining and reviewing it should get you to the level of accuracy you aim for. If you want more granular insights, you can consult an expert or get hold of a **6. Review and iterate:** Cloud forecasting is not a one-time process but a continuous improvement process. Your business will evolve, along with your budgeting requirements. The key step is to track your changes as far as cloud costs are concerned and adapt your budget accordingly. You should then stick to your budget to avoid cost overruns. ## **How CloudKeeper can help?** Being able to accurately forecast cloud costs is a critical pillar in your cloud cost optimization journey. However, cloud cost forecasting is easier said than done. In order to set yourself up for success, begin your journey with small, achievable goals that can be built on over time as you mature, continually improving as you go. CloudKeeper’s __ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents Cloud migration can be a paradigm shift for organizations, enabling scalability, agility, and cost optimization. Yet, due to a lack of proper planning, they risk facing hurdles, unplanned expenditures and workflow interruptions. That’s where CloudKeeper comes in—an end-to-end cloud optimization partner with a 10-step cloud migration strategy that helps ensure a smooth transition. So let’s look at the roadmap and see how ## **1. Assessment** The first step in this process is a comprehensive review of your current IT systems. Our experts at CloudKeeper will analyze your applications, workloads, and dependencies to define relevant **How CloudKeeper helps:** * We perform a deep evaluation of your on-prem and cloud-based workloads. * Offers a cost analysis that showcases potential cloud cost savings. * Pinpoint risks and develop a plan to migrate that aligns with your specific needs. ## **2. Planning** After the assessment is complete, the next step is to create a comprehensive cloud migration plan for your cloud migration. This involves choosing an appropriate cloud service model (IaaS, PaaS or SaaS), defining a timeframe for cloud migration, and **How CloudKeeper helps:** * We create a tailored cloud migration plan according to your business needs. * Ensures the least downtime by implementing phased cloud migration. * Rank applications in terms of complexity and business impact. ## **3. Rehost** Rehosting, or “Lift and Shift” is a way of migrating the applications to the cloud with modifications. This is among the fastest and cheapest methods that companies use to cloud-enable services that they want to provide immediately. **How CloudKeeper helps:** * Offers tools to automate cloud migration. * It provides compatibility with the cloud infrastructure. * Reduces interruptions to your operations. ## **4. Re-platform** Re-platforming requires only minor changes to applications to utilize the features of cloud-native architectures, resulting in improved scalability and performance while avoiding the pitfalls of complete redevelopment. **How CloudKeeper helps:** * Optimizes apps for cloud-native services (managed DBs, containers, etc). * Increased scalability while lowering infrastructure expenses. * Keep cloud security best practices in mind. ## **5. Repurchase** Repurchase in cloud migration means replacing an existing application with a commercial SaaS product. Instead of migrating or modifying the current app, you "repurchase" the functionality from a third-party cloud-native solution. Example: Moving from a self-hosted CRM system to Salesforce or HubSpot. **How CloudKeeper helps:** * We evaluate current licensing modeling and offer cost-effective options. * Enables a shift to software solutions in the cloud. * Businesses experience little to no disruption. ## **6. Refactor** Refactoring refers to reconfiguring applications to take full advantage of cloud-native capabilities, resulting in long-term savings and efficiency. **How CloudKeeper helps:** * Assist in the redesign of applications for serverless computing, microservices, and containerization. * Enhances application resiliency, scalability, and maintainability. * Enforces compliance to cloud security and compliance standards. ## **7. Retain** This strategy means keeping certain applications or parts of your IT infrastructure on-premises, instead of migrating them to the cloud. This could be because: * The application is already performing well and doesn’t benefit from cloud migration. * It’s a legacy system with compliance or regulatory requirements. * It requires a major rework that isn't justified right now. * There may be some workloads, for example, security, compliance, or latency-sensitive workloads, that may be better suited for on-premises. * You plan to revisit the decision later as part of a phased migration. **How CloudKeeper helps:** * Regulates applications that need to remain on-prem. * It's designed to make sure hybrid cloud strategies are applied in a cost-effective way. * Offers integrating tips for on-prem/cloud environmental conditions. ## **8. Retire** Some of the applications eventually become irrelevant or obsolete. This means retiring these applications to eliminate unnecessary costs and simplify IT operations. **How CloudKeeper helps:** * It spots deprecated applications that should do not contribute anymore. * It also helps consolidate and thus optimize IT infrastructure. * Lowers licensing costs and operational overhead. ## **9. Training** Cloud migration must be followed by upskilling all employees. Training prepares teams to maintain the new cloud environment successfully. **How CloudKeeper helps:** * Hones in on hands-on training for IT teams and end-users. * Teaches teams security best practices and management of the cloud. * Provides resources for continued learning for skill advancement. ## **10. 24*7 Cloud Support** Once cloud migration is complete, post-migration support is key for maintaining cloud performance, ensuring cost efficiency, and resolving unexpected hurdles. **How CloudKeeper helps:** * Delivers 24*7 * Perform constant monitoring and cloud spending optimization. * Provides high availability and performance of cloud applications. By following this structured 10-step approach, businesses can achieve a smooth, efficient, and cost-effective cloud migration. Each step ensures minimal disruption while maximizing the benefits of cloud computing, paving the way for long-term success. ## **FAQs on Cloud Migration** ### **1. What is cloud migration?** The process of transferring data, apps, and digital assets from on-premises infrastructure to a cloud computing environment is known as cloud migration. ### **2. Why should businesses migrate to the cloud?** Companies move to the cloud in order to increase operational efficiency, scalability, cost savings, and security. ### **3. What challenges can arise during cloud migration?** Downtime, data loss, security threats, unforeseen expenses, and compatibility problems are typical difficulties. ### **4. How long does cloud migration take?** There are different factors that decide how long the cloud migration process can take. This includes the complexity of the program, the amount of data, and the migration approach selected. ### **5. How can CloudKeeper assist in cloud migration?** To guarantee a smooth transfer, CloudKeeper offers end-to-end migration help, which includes evaluation, planning, execution, and post-migration optimization. ### **6. What are the cost implications of cloud migration?** By removing hardware expenditures, cutting maintenance costs, and strategically managing cloud spending, cloud migration can result in cloud cost savings. However, it's important to note that achieving continuous ### **7. Is cloud migration secure?** Cloud migration is secure if done properly. To safeguard sensitive data, CloudKeeper makes sure that encryption, access controls, and security best practices are followed. ### **8. What is the best cloud migration strategy for my business?** Your budget, current infrastructure, and business objectives will determine the optimal course of action. CloudKeeper can help adapt the strategy to your needs. ## **Your cloud journey starts here** Cloud migration requires re-architecting and optimizing IT infrastructure for increased cost agility and efficiency. While there is a proper method to approach the process, though, it can be more complicated than it seems. Businesses can make sure that risks are controlled and value is maximized during their cloud migration by using CloudKeeper's 10-step cloud migration plan. During the planning, evaluation, migration, and support stages, CloudKeeper provides a smooth, safe, and optimized cloud experience. With a good partner, organizations can easily attain cloud excellence, regardless of whether they’re prepared to migrate or want to improve their cloud strategy. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents In **Amazon Web Services (AWS)** and **Oracle Cloud Infrastructure (OCI)**. To enable secure communication between workloads running across these platforms, a Site-to-Site VPN is one of the most reliable and cost-effective solutions. This blog walks through a complete implementation of an AWS ↔ OCI Site-to-Site VPN using static routing and IPSec (IKEv1). By the end of this guide, AWS VPC and OCI VCN will be connected through a private, encrypted tunnel, allowing seamless network communication. ## **Objective of This Setup** The primary goals of this configuration are: * Establish a**secure private connection** between AWS and OCI * Enable **bi-directional communication** between AWS * Use **static routing** for predictable and controlled traffic flow * Ensure **IPSec tunnel compatibility** between AWS and OCI ## **Network Architecture Overview** Before starting the configuration, define the network boundaries clearly. **Static routing** is used in this setup, meaning all network prefixes are manually defined on both sides. This approach is simple and effective when network ranges are well-known and do not change frequently. ### **AWS Configuration** On the AWS side, the VPN architecture consists of: * A **Virtual Private Gateway (VGW)** attached to the VPC * A **Customer Gateway (CGW)** representing the OCI VPN endpoint * A **Site-to-Site VPN connection** between AWS and OCI #### **1. Creating a Virtual Private Gateway (VGW)** A **Virtual Private Gateway** acts as the AWS-managed VPN endpoint that connects your VPC to external networks such as OCI. **Steps:** * Navigate to * Select Virtual Private Gateways * Click Create Virtual Private Gateway * Provide a name: **aws-vgw** * Create the gateway #### **2. Attaching the VGW to the VPC** The VGW must be attached to the target VPC to enable VPN traffic flow. **Steps:** * Select the created VGW * Choose Actions → Attach to VPC * Select the VPC:**10.0.0.0/16** * Attach This step logically associates the VPN gateway with the AWS VPC. #### **3. Creating a Customer Gateway (CGW)** A **Customer Gateway** represents the remote VPN device, in this case, the OCI IPSec tunnel public ip. Since OCI tunnel public IP addresses are available only after tunnel creation, a **temporary placeholder IP** is used initially. **Steps:** * Go to VPC → Customer Gateways * Click Create Customer Gateway * Name: **oci-cgw** * Routing: **Static** * IP Address: Temporary public IP (placeholder). The actual OCI IPSec tunnel public IP will be updated later. AWS requires a public IP address as per the documentation. * Create AWS does not allow modification of a Customer Gateway IP address later, which is why a new CGW will be created once the actual OCI tunnel IP is available. #### **4. Creating the Site-to-Site VPN Connection** This step establishes the actual IPSec VPN connection between AWS and OCI. **Steps:** * Navigate to **VPC → Site-to-Site VPN Connections** * Click **Create VPN Connection** * Name: **aws-oci-vpn** * Target Gateway Type: **Virtual Private Gateway** * Virtual Private Gateway: **aws-vgw** * Customer Gateway: **oci-cgw** * Routing Options: **Static** **Static Route Prefix:** **10.20.0.0/16** - This CIDR represents the OCI VCN network reachable from AWS. ##### **Pre-Shared Key Considerations** AWS automatically generates pre-shared keys containing special characters. However, **OCI does not support special characters in pre-shared keys**. **Important constraints:** * Allowed characters: **A–Z, a–z, 0–9** * Special characters (. - _) are not supported Example of a compatible pre-shared key: **psd43mdk620djn** This key must be identical on both the AWS and OCI sides #### **5. AWS Tunnel Parameters (Reference)** Download the AWS VPN configuration and note the parameters for Tunnel-1. These settings must match exactly on the OCI side. **IKE Phase 1** * IKE Version: IKEv1 * Encryption: AES-128-CBC * Authentication: SHA1 * Diffie-Hellman Group: Group 2 * Lifetime: 28800 seconds **IPSec Phase 2** * Protocol: ESP * Encryption: AES-128-CBC * Authentication: HMAC-SHA1-96 * PFS: Group 2 * Lifetime: 3600 seconds #### 6. Updating AWS Route Tables To route traffic destined for OCI through the VPN, update the AWS subnet route tables. ##### **OCI Configuration** * On the OCI side, the equivalent components are: * Dynamic Routing Gateway (DRG) * Customer-Premises Equipment (CPE) * IPSec Connection #### **7. Creating a Dynamic Routing Gateway (DRG)** A **DRG** in OCI functions similarly to an AWS VGW. Steps: * OCI Console → Networking * Dynamic Routing Gateways → Create * Name: **oci-drg** #### **8. Attaching the DRG to the VCN** * Open the created DRG * Create a **VCN Attachment** * Select VCN: **10.20.0.0/16** #### **9. Creating Customer-Premises Equipment (CPE)** CPE represents the AWS VPN endpoint from OCI’s perspective. Steps: * Networking → Customer-Premises Equipment * Name:**aws-cpe** * IP Address: AWS VPN tunnel outside IP * Vendor: **Other** #### **10. Creating the IPSec Connection** This establishes the OCI side of the VPN tunnel. Basic Configuration * Name: **oci-aws-vpn** * CPE: **aws-cpe** * DRG: **oci-drg** * Routing Type: Static * Static Route CIDR: **10.0.0.0/16** Tunnel Configuration and Phase Settings * Pre-Shared Key: Same as AWS * IKE Version: IKEv1 * Inside Tunnel IPs: From AWS VPN configuration Phase 1 * Encryption: AES-128-CBC * Authentication: SHA1 * Diffie-Hellman Group: 2 * Lifetime: 28800 seconds Phase 2 * Encryption: AES-128-CBC * Authentication: HMAC-SHA1-128 * (OCI does not support HMAC-SHA1-96) * PFS: Group 2 Lifetime: 3600 seconds #### **11. Updating OCI Route Tables** Update the OCI VCN subnet route tables to forward AWS traffic via DRG. ##### **Updating the AWS Customer Gateway (Final Step)** Once the OCI tunnel public IP is available: 1. Create a new Customer Gateway in AWS * Name: **oci-cgw-active** * IP Address: OCI IPSec tunnel public IP 2. Modify the existing Site-to-Site VPN connection 3. Associate it with the new Customer Gateway 4. Save changes ## **Validating the VPN Connection (End-to-End Testing)** After completing the AWS ↔ OCI Site-to-Site VPN configuration, it is critical to validate connectivity at the application and network level. The most reliable way to test this setup is by deploying compute instances on both sides and verifying private IP communication over the VPN tunnel. Test Scenario Overview For validation, we will: * Launch an * Launch a Compute instance in OCI * Use private IP addresses only * Test ICMP (ping) and SSH connectivity between both instances This confirms: * VPN tunnel is UP * Routing is correct on both sides * Security rules allow traffic * Traffic is flowing through the IPSec tunnel, not the public internet ### **Step 1: Launch Test Instances** AWS Side (EC2) * Launch an EC2 instance in the AWS VPC (10.0.0.0/16) * Place the instance in a subnet associated with the VPN route table * Assign only a private IP (public IP is optional and not required for VPN testing) * Use Amazon Linux / Ubuntu Example: AWS EC2 Private IP: **10.0.1.10** OCI Side (Compute Instance) * Launch a Compute instance in the OCI VCN (10.20.0.0/16) * Place it in a subnet whose route table points to the DRG * Assign a private IP Example: OCI Instance Private IP: 10.20.1.10 ### **Step 2: Update Security Groups and Security Lists** By default, cloud firewalls block cross-network traffic. To allow VPN traffic, security rules must be updated on both AWS and OCI sides. #### AWS Security Group Configuration Update the EC2 Security Group attached to the AWS instance. Inbound Rules: Outbound Rules: * Allow all traffic (default is usually sufficient) This allows ping and SSH requests from OCI to AWS. #### OCI Security List / Network Security Group Update the Security List or NSG associated with the OCI subnet or instance. Ingress Rules: Egress Rules: * Allow traffic to **10.0.0.0/16** This allows AWS-originated traffic to reach OCI instances. ### **Step 3: Verify Route Tables** Before testing connectivity, double-check routing on both sides. AWS Route Table Ensure the subnet route table contains: OCI Route Table Ensure the subnet route table contains: If routes are missing or incorrect, traffic will not traverse the VPN tunnel. ### Step 4: Test ICMP Connectivity (Ping) **From AWS EC2 → OCI Instance** Login to the AWS EC2 instance and run: **ping 10.20.1.10** Expected result: * Successful ICMP replies * Low latency * No packet loss From OCI Instance → AWS EC2 Login to the OCI instance and run: **ping 10.0.1.10** If ping works in both directions, it confirms: * VPN tunnel is active * Routing is symmetric * Firewalls allow ICMP traffic ## Conclusion An AWS to OCI Site-to-Site VPN using static routing provides a secure and reliable multi-cloud connectivity solution. With correctly aligned tunnel parameters, routing, and security configurations, encrypted communication is established over private IP addresses. Successful validation using private IP ping confirms that the VPN tunnel is operational and traffic is flowing correctly between AWS and OCI with minimal operational overhead. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Pritam possesses strong expertise in AWS, CI/CD, and Infrastructure as Code. He focuses on designing scalable, automated cloud environments and enhancing overall system performance. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents When deploying large language models (LLMs) in real-world workflows, systematic evaluation is essential—especially for mission-critical tasks like automating personalized sales outreach. At CloudKeeper, our goal was to help Sales Development Representatives (SDRs) draft hyper-personalized emails using contact and company data, driving productivity gains and higher engagement rates. Here’s how we approached **model evaluation on Amazon Bedrock** , from model selection through hands-on assessment and result interpretation. ## **Why Model Evaluation Matters for SDR Workflows** Personalized outreach at scale is a nuanced challenge for generative AI. SDRs need emails that are not only grammatically correct but also tailored, context-aware, and responsible. Picking the right model—and **proving its performance** on your unique task—is the difference between busywork and real business impact. For example, **Amazon Nova** creates extremely long emails, **Claude 3.5 Haiku** is more straightforward and follows instructions precisely, while **Llama 3.3-70b** writes catchy subject lines that boost open rates. ## **1. Model Selection on Amazon Bedrock** **Scope:** We focused on text-generation models available within Amazon Bedrock, filtering for those suitable for real-time, context-heavy email writing. **Initial Candidates Included: ai21**.jamba-1-5-mini-v1:0, **amazon**.nova-micro-v1:0, **cohere**.command-r-v1:0, **mistral** -small-2402-v1:0, **anthropic**.claude-3-5-haiku-20241022-v1:0, **llama3.3** -70b-instruct-v1 _Note:_ Access to advanced models such as Claude 3.5 and Llama 3-70B is limited to the playground or requires purchasing throughput. **Best Practice:** Start broad—benchmark all feasible models on your specific use case before narrowing the field. Don’t assume “bigger” is better; smaller models may be faster and more cost-effective if they meet your quality bar. ## **2. Amazon Bedrock Evaluation Workflows** Bedrock offers three robust evaluation pathways: **a. Automatic Model Evaluation Jobs** * **What:** Fast, repeatable model benchmarking using datasets (either custom or built-in) to assess basic task performance. * **When:** Early-stage filtering or regression tests after model updates. **b. Human-in-the-Loop Evaluation Jobs** * **What:** Involve in-house reviewers or external experts to score and comment on outputs. * **When:** For nuanced tasks, or when subjective human judgment is needed. **c. Judge-Model Evaluation Jobs** _**(Our Choice)**_ * **What:** Use a separate LLM (“judge model”) to evaluate model responses, assigning both a score and an explanatory rationale. * **Why we picked it:** We leveraged **Claude 3.7 Sonnet** as our judge model, valuing its strong reasoning, speed, and consistency over manual reviews. **RAG-Specific Evaluation** Bedrock’s LLM-based judge workflows extend to Retrieval-Augmented Generation (RAG), letting you evaluate not just LLM responses but also the **relevance of retrieved content** from knowledge bases or external data sources. **Best Practice:** Automate what you can, but periodically validate with human reviews—especially for high-stakes or evolving tasks. ## **3. Setup Steps: Data, Metrics, and Storage** **a. Dataset Preparation** * **Format:** Store custom prompts (and, optionally, ground truths) in **JSONL files.** * **Location:** Upload these files to an S3 bucket accessible by Bedrock. **Structure Example:** {"input": "Write a personalized email to Jane Doe at Acme Corp about our cloud savings platform.", "referenceResponse": "Hi Jane, I noticed Acme Corp recently expanded its AWS footprint..."} **b. Metric Configuration** * **Quality:** Bedrock provides built-in scoring for relevance, fluency, and completeness. * **Responsible AI:** Out-of-the-box checks for toxicity, bias, etc. * **Custom Metrics:** Define additional measures (e.g., personalization, factual accuracy) as needed. **c. Evaluation Output** **Storage:** Results (including scores and judge model explanations) are saved back to S3 and available in the Bedrock console. **Best Practice:** Align your evaluation dataset closely with real-world SDR prompts. Always include expected responses if possible; this helps both human and LLM judges evaluate meaningfully. ## **4. Interpreting Results and Using Bedrock’s Visualization Tools** After jobs run: * **Scores** are normalized between 0 and 1, enabling easy comparison. Source: AWS * **Judge Explanations** provide context for each score, highlighting strengths and areas for improvement. * **Visualization:** The Bedrock console displays: 1. Job-over-job comparison charts. 2. Metric breakdowns (by prompt, by category). Source: AWS **Best Practice:** Use visualizations to identify patterns—are certain prompt types consistently underperforming? Are some models excelling at personalization but lacking in factual accuracy? Iterate your evaluation dataset and metrics to surface these insights. ## **Key Takeaways & References** * **Systematic evaluation** is critical for responsible, effective LLM deployment—especially in customer-facing roles like SDRs. * **Amazon Bedrock** streamlines this process with multiple evaluation workflows, seamless S3 integration, and robust visualization. * **Judge-model evaluation** (using a strong LLM like Claude 3.7 Sonnet) provides both quantitative and qualitative insight at scale. * **Actionable outputs** —normalized scores, judge rationales, and clear visualizations—empower teams to choose the best model for their needs. **Further Reading:** * * * **Deploying LLMs for high-stakes, real-world tasks demands more than intuition—let Amazon Bedrock’s evaluation tooling be your guide to consistent, measurable, and scalable success.** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Shivam is passionate about building GenAI applications and cloud solutions. He specializes in AWS cloud computing and Python, with a keen interest in emerging AI technologies. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 18 18 Table of Contents It's 2026, and AI is no longer the novelty it was 10 years ago. From copilots embedded in everyday software to LLM-powered search, chat, code, design, and analytics tools, artificial intelligence has been effectively democratized. Unlike traditional AI systems that respond to prompts, Agentic systems can plan, decide, act, and iterate toward goals autonomously. However, we’ve barely scratched the surface. This blog explores Agentic AI in detail. It is a practical, end-to-end guide to Agentic AI—what it is, how it works, where it's being used today, and what it means for the future of software, automation, and ## **The Evolution of AI: From Traditional AI to GenAI to Agentic AI** ### **a) Traditional AI** Traditional AI—also called narrow AI or weak AI—dominated from the 1950s through the early 2020s. These systems excelled at single, well-defined tasks within rigid parameters. Some applications of traditional AI systems are: * **Netflix's recommendation engine:** It drove 80% of content watched on the platform by 2016. * **Email services (Common example being Gmail):** Spam filters achieved 99.9% accuracy in detecting unwanted emails using Bayesian classification, yet couldn't identify phishing attacks using novel techniques. The architecture relied on rule-based systems, decision trees, and supervised machine learning. Engineers manually coded if-then logic or trained models on labeled datasets for specific tasks. ### **b) Generative AI** OpenAI's GPT-3 launched in 2020 with 175 billion parameters. It could generate human-like text on virtually any topic. DALL·E created images from text descriptions. ChatGPT, released in 2022, became the fastest-growing consumer application in history. * Writing essays * Generating code * Composing music * Designing graphics But the Achilles’ heel for GenAI was that it couldn’t take action. The working of GenAI remained reactive—it would wait for you to enter a prompt, generate a response, and then the cycle continued. The key highlight was that it improved if you gave a positive or negative response. ### **c) Agentic AI** 2025 was the “great coming” of Agentic AI. AI agents moved from theory to production infrastructure. The definition shifted from academic concepts of systems that perceive, reason, and act to practical descriptions of large language models capable of using software tools and taking autonomous action. The only major hiccup in “true artificial intelligence” was that it couldn’t act, and with Agentic Artificial Intelligence, that is what was solved. Agentic AI, unlike previous systems, can act on what it generates. Some of the common use cases of Agentic AI are: * **Calling APIs:** Agents can autonomously trigger APIs to fetch data, execute actions, or update systems without human intervention. * **Using external tools:** Agents can operate software tools such as browsers, databases, code editors, and SaaS platforms to complete real-world tasks. * **Coordinating across different systems (e.g., cloud and software applications) :** Agents can move information and actions across multiple systems to complete end-to-end workflows. * **Completing tasks independently** : Agents can plan, execute, verify, and finish multi-step tasks without continuous human guidance. * **Maintaining context over long periods:** Agents can remember past interactions, goals, and decisions across sessions and long-running workflows. What we’re witnessing is the fourth major evolution in AI–human interaction: from rigid rule-following systems to autonomous agents that can reason, adapt, and take action across complex workflows. ## **Why Agentic AI Is Gaining Attention Now** It’s 2026 now, and in the years leading up to this point, there have been several key developments in Agentic AI that have shaped what it is today. These can broadly be split into two themes: ### **a) New AI tools were being created:** The Model Context Protocol (MCP) from Anthropic, released in late 2024, allowed developers to connect large language models to external tools in a standardized way. DeepSeek-R1’s release in January disrupted assumptions about who could build high-performing LLMs. Chinese tech companies rapidly expanded the open-model ecosystem. Google introduced Agent2Agent. Agentic browsers appeared—Perplexity’s Comet, Browser Company’s Dia, and OpenAI’s GPT Atlas. These tools reframed the browser as an active participant rather than a passive interface. ### **b) Tools began showing real value, and more innovation and investment followed:** Enterprises started seeing tangible results. Google Cloud’s 2025 survey, conducted across 3,466 senior leaders, confirmed that Agentic AI was no longer experimental. Companies deploying agents reported measurable productivity gains and cloud cost savings. As has been the case with AI, today’s “star of the tech show,” Agentic AI, has developed incrementally rather than overnight. ## **What Is Agentic AI?** Let's cut through the hype. Agentic AI refers to AI systems that act autonomously to achieve defined goals. They don't just generate responses—they take action. They don't wait for constant human input—they pursue objectives independently. These systems combine LLMs with external tools, memory, planning capabilities, and feedback loops. They can break down complex goals into manageable tasks. Execute those tasks using appropriate tools. Observe outcomes. Adjust their approach. Iterate until the goal is achieved. Think of it this way: Generative AI is like having a smart consultant while Agentic AI is like having an employee who actually does the work. The key difference? Agency. ## **What Does "Agency" in Agentic AI Stand For?** Agency means autonomy with purpose. Traditional AI and GenAI are reactive. meaning they respond to inputs. Agentic AI, however, is proactive, which means it initiates actions based on goals, not prompts. **Agency involves several components:** * **Autonomy:** The ability to operate without constant human supervision. An agent receives a high-level objective and figures out how to achieve it. * **Goal-oriented behavior:** Everything an agent does serves a defined purpose. It's not executing random actions—it's working toward specific outcomes. * **Decision-making:** Agents evaluate options and choose paths forward. When one approach fails, they try alternatives. * **Tool usage:** Agents can call APIs, query databases, browse the web, execute code, send emails, and update records. They interact with the digital world. * **Adaptability** : Environments change, and Agents adjust. They don't blindly follow fixed scripts—they respond to new information and obstacles. Agency transforms AI from an assistant into an actor. That's the revolution. ## **Beyond Chat-Based Interactions: How Agentic Systems Interact With You** Chatbots wait for you to type a question. Copilots suggest completions as you work. Agents? They take over entire workflows. Here are two of the most impacted areas, which have the market on the edge of its seat, with everyday interactions being handled by Agentic systems: 1. **Customer Service:** An agentic customer service system autonomously processes your refund, updates your account, verifies the transaction, sends a confirmation, schedules a follow-up, and escalates complex issues to humans only when necessary. 2. **Software Development:** An AI agent writes entire features, tests them, debugs failures, documents changes, and deploys to production—all from a high-level description of what you need. Agentic AI closes the loop that previous generations left open. It no longer hands off instructions to humans—it carries them out end to end. The interaction model has shifted from conversation to collaboration. Instead of prompting, you’re delegating. ## **Progression from Chatbots to Autonomous Agents: What Does That Look Like?** The evolution happened in stages. ### **Stage 1: Rule-Based Chatbots** "Press 1 for billing. Press 2 for support." These systems followed decision trees and delivered clear ROI by deflecting simple support tickets. But throw a curveball at them, which was a question they don’t know, and you’d see the system break down immediately. ### **Stage 2: Conversational AI** Natural language understanding improved significantly, and chatbots started handling much more complex interactions. Most common examples of conversational AI systems are Siri and Alexa. ### **Stage 3: Generative AI** LLMs like GPT-3 and ChatGPT generated human-quality responses. They could explain concepts, write code, and analyze documents. Conversational depth increased dramatically. ### **Stage 4: Agentic AI** The real evolution with Agentic AI is the independence it has gained to solve problems end-to-end. What Agentic AI is now empowered to do is: * Use external tools. * Maintain memory across sessions. * Adapt new approaches when encountering problems. Example: Party planning. A chatbot can suggest recipes. An agent, on the other hand, checks your calendar, emails friends to coordinate dates, orders groceries through an API, creates a Spotify playlist based on guest preferences, and sends calendar invitations. It executes the entire project. That’s the shift from read-only to read-write. From suggesting to doing. **Why Chatbots and Copilots Were Limited** No memory beyond the conversation: Each session started fresh. Context disappeared the moment you closed the chat window. * **No tool access:** They couldn't take actions in other systems. Want to check inventory? The chatbot can't query your database. Want to send an email? It can't access your mail server. * **No planning:** Chatbots responded to immediate inputs. They couldn't break down complex tasks into steps and execute them sequentially. * **No persistence:** If a task required multiple steps across hours or days, chatbots couldn't handle it. They operated in single turns. * **Limited reasoning:** Early chatbots, especially those from the 1970s, struggled with the logical reasoning chains required for complex problem-solving. Copilots improved on some of these. GitHub Copilot suggests code. It's useful. But it doesn't architect the system, write tests, deploy to production, and monitor for errors. You still do the heavy lifting. Agents remove these constraints. They access tools, remember, plan, execute, and persist until goals are achieved. ## **How Agentic Systems Shift from Responding to Executing** Traditional AI follows a simple pattern: Input → Process → Output. Agentic AI operates in loops: Perceive → Reason → Act → Observe → Adjust → Repeat. Let's break that down. 1. **Perceive:** The agent gathers information from its environment. This might be reading an email, checking a database, monitoring system logs, or analyzing user behavior. 2. **Reason:** The agent interprets what it perceives. What does this information mean? What are the implications? What actions might address the situation? 3. **Act:** The agent executes actions. Call an API. Update a record. Generate a document. Send a notification. Whatever the situation requires. 4. **Observe:** The agent monitors outcomes. Did the action succeed? What changed? Are there side effects? 5. **Adjust:** Based on observations, the agent modifies its approach. If something failed, it tries an alternative. If it worked, it proceeds to the next step. 6. **Repeat:** The cycle continues until the goal is achieved or the agent determines the goal is unachievable. This feedback loop enables agents to handle dynamic environments and complex, multi-step tasks that would defeat reactive systems. ## **Prompts vs Objectives: A Fundamental Change** Prompting and objective-setting might look similar on the surface, but they’re really not. A prompt is a very specific instruction, like: “Write a product description for noise-canceling headphones.” An objective, on the other hand, is a goal: “Increase headphone sales by 20% this quarter.” When you work with prompts, you’re telling the AI exactly what to do. You’re still thinking, planning the steps, and deciding the direction. The AI is mostly just executing what you asked for. With objectives, the dynamic changes completely. You tell the AI what outcome you want, and it figures out how. It might research competitor pricing, analyze customer reviews, generate multiple product descriptions, run A/B tests, identify the best-performing version, and then deploy it across your marketing channels. Same outcome on paper. Completely different process underneath. This is where planning comes in. Objectives require agents to actually think in terms of steps: breaking a big goal into smaller tasks, prioritizing them, executing them in the right order, handling dependencies, and even dealing with things when they fail or don’t go as expected. And that’s really the core difference. Assistants need instructions, whereas Agents need objectives. ## **How Does Agentic AI Work?** The mechanics involve several interconnected components. ### **Understanding Objectives** First, the agent must comprehend what you're asking for. This goes beyond parsing language. The agent needs to understand intent, context, constraints, and success criteria. "Book the cheapest flight" is different from "Book a direct flight leaving after 2 PM." The agent must extract these nuances. LLMs handle this through their training on vast text corpora. They've learned how humans express goals, how to interpret ambiguous requests, and how to ask clarifying questions when needed. ### **Planning and Task Decomposition** Once an objective is clear, the agent breaks it into manageable steps. Say your objective is "Analyze Q4 sales performance and identify improvement opportunities." The agent might decompose this into: 1. Query the sales database for Q4 data 2. Calculate key metrics (revenue, growth rate, conversion rate) 3. Compare against Q3 and previous Q4 4. Identify top-performing and underperforming products 5. Analyze regional variations 6. Correlate with marketing spend 7. Generate visualizations 8. Draft executive summary 9. Compile the final report Task decomposition requires understanding dependencies. You can't analyze data before retrieving it. You can't generate visualizations before calculating metrics. Agentic systems use planning algorithms—some inspired by classical AI planning, others using LLM reasoning—to create execution plans. ### **Taking Actions and Observing Outcomes** With a plan established, the agent executes. This is where tool usage becomes critical. An agent needs access to databases, APIs, code execution environments, email systems, document editors, and whatever else the task requires. The After each action, the agent observes outcomes. Did the database query succeed? What data was returned? Are there errors? How does this affect the plan? Observation informs the next action. If a query returned no data, the agent might try alternative date ranges or data sources. If an API call failed, it might retry with different parameters or switch to a backup service. ### **Feedback Loops and Iteration** Agents don't follow rigid scripts. They adapt based on what happens. If the initial plan isn't working, they revise it. If they discover new information midway through, they incorporate it. If they hit a dead end, they backtrack and try alternatives. This iterative process is what makes agents robust. Static workflows break when encountering unexpected conditions. Agents adjust. Reinforcement learning principles often guide this adaptation. Actions that move toward the goal are reinforced. Actions that don't are deprioritized. Some advanced agents even learn from deployment. They analyze which strategies worked in past situations and apply those patterns to new problems. This on-the-job learning allows agents to improve over time without explicit retraining. ## **Real-World Examples of Agentic AI** Theory is one thing. Practice is another. Here's where agentic AI is actually being deployed in 2026. **Software Development** AI coding agents like Devin from Cognition Labs and enhanced versions of GitHub Copilot now write, test, and deploy code autonomously. The agents handle boilerplate, while humans focus on system design and complex logic. **Customer Service** Companies like Salesforce deployed Agentforce in 2025, handling customer inquiries from end to end. The system researches issues, implements fixes, updates records, and follows up—without human intervention except in edge cases. **Financial Services** Credit analysis agents evaluate loan applications by pulling data from dozens of sources, applying complex scoring models, and generating approval recommendations—all in minutes rather than days. **Healthcare** Diagnostic support agents analyze patient histories, lab results, imaging studies, and medical literature to suggest differential diagnoses and recommend tests. They don't replace physicians but augment clinical decision-making. **Cloud Operations** This is where things get particularly interesting for Infrastructure agents monitor cloud resources continuously. They detect idle instances, identify oversized resources, recommend ## **Benefits and Challenges of Agentic AI** ### **Benefits** 1. **Massive productivity gains :** Agents handle routine work that consumes human hours. One supply chain company reported that agentic optimization saved $47,000 monthly by automatically adjusting logistics in response to real-time conditions. 24/7 operation. Agents don't sleep. They monitor, analyze, and act around the clock. Problems get addressed immediately, not during business hours. 2. **Scalability:** One agent can handle workloads that would require an entire team. Deploy that agent across your organization, and the impact multiplies. 3. **Consistency:** Humans have good days and bad days, whereas agents perform consistently. They follow policies exactly and don't cut corners when tired. 4. **Speed:** Agents execute in seconds or minutes what would take humans hours or days. Analysis that required days of manual work now completes while you grab coffee. 5. **Cost reduction:** Automating 60-90% of routine tasks translates directly to lower operational costs. The ROI is measurable and significant. ### **Challenges** 1. **Security risks:** Chinese hackers used Anthropic's Claude AI tool to break into 30 companies and government agencies last year. Agents with broad system access become attractive attack vectors. Prompt injection attacks can manipulate agents into unauthorized actions. An agent with database access could be tricked into deleting records or exfiltrating data. 2. **Accountability questions:** When an agent makes a mistake, who's responsible? The developer? The deploying organization? The AI provider? Legal frameworks haven't caught up to autonomous AI systems. 3. **Hallucinations and errors:** LLMs sometimes generate plausible-sounding but incorrect information. When those hallucinations drive actions, problems compound quickly. 4. **Lack of transparency:** Understanding why an agent chose a particular action can be difficult. This "black box" problem makes debugging and auditing challenging. 5. **Over-automation concerns:** Not every task should be automated. Some require human judgment, ethical reasoning, or creative thinking that agents can't replicate. 6. **Trust erosion:** One spectacular agent failure can undermine confidence in the entire system. Early deployments need careful oversight and graceful failure modes. The key is thoughtful deployment. Here’s how you should proceed : 1. Start with low-risk tasks. 2. Monitor carefully. 3. Build in guardrails. 4. Maintain human oversight for high-stakes decisions and 5. Gradually expand the scope as confidence grows. ## **Comparison: Traditional AI vs GenAI vs Agentic AI** ## **Role of Agentic AI in Cloud Cost Optimization** Agentic AI represents a shift from reactive cost control to autonomous cloud cost optimization. Instead of just flagging issues, these systems can analyze, decide, and act - optimizing spend, performance, and governance across the cloud. 1. **Autonomous Anomaly Detection** Agentic AI monitors spending patterns across thousands of resources, 2. **Intelligent Resource Rightsizing** Agents analyze actual usage patterns across CPU, memory, and network to recommend optimal instance types, then execute changes during maintenance windows with automatic rollback if needed. 3. **Automated Waste Elimination** Agents identify and eliminate zombie resources—idle instances, unattached volumes, outdated snapshots—automatically flagging, notifying owners, and deleting after grace periods to recover thousands monthly. 4. **Cloud FinOps** Agentic AI automates 5. **Cost Management** Agents 6. **Performance Optimization** Agentic systems 7. **Cloud Visibility** Agents provide natural language access to cloud costs—practitioners ask "Why did the spend spike?" and receive context-rich answers with visualizations, eliminating dashboard complexity and enabling cross-team collaboration. ## **The Future of Agentic AI** Where does this go from here? 1. **Multi-agent collaboration becomes standard:** Instead of one agent handling everything, specialized agents work together. A research agent gathers data. An analysis agent processes it and so on. This mirrors human teams—division of labor with coordination. 2. **Agents develop long-term memory:** Current systems have limited context windows, whereas future agents will maintain comprehensive memory across months or years. They'll learn from past interactions and continuously improve. 3. **Physical-world integration expands:** We're already seeing robots with agentic capabilities in warehouses. This extends to manufacturing, construction, agriculture, and service industries. 4. **Personalization deepens:** Agents will adapt to individual working styles, preferences, and goals. Your agent will operate differently from your colleague's, even when handling similar tasks. 5. **Regulatory frameworks emerge:** Governments will establish rules for agent accountability, transparency, and safety. Compliance requirements will shape how agents are built and deployed. 6. **Education transforms:** Teaching agents will adapt to each student's learning style, pace, and interests. Education becomes truly personalized at scale. 7. **Enterprise adoption accelerates:** By 2028, Gartner predicts 33% of enterprise software will include agentic AI, up from less than 1% in 2024, making it a competitive necessity. The organizations moving now are building the muscle and governance frameworks while there's time to learn. Those waiting will spend years catching up. ## **LensGPT: Agentic AI Meets Cloud Optimization** Everything we've discussed—the planning, the tool usage, the autonomous execution—applies directly to CloudKeeper recognized this opportunity early. Instead of making you navigate dashboards, export CSVs, and manually analyze spending patterns, we built LensGPT: It's conversational cloud FinOps. No SQL queries. No complex filters. No dashboard archaeology. Just ask questions in natural language and get complete answers. Just like you chat with a colleague and get answers the way you would from a seasoned FinOps consultant. The platform goes beyond simple cost reporting: 1. **Real-time anomaly detection:** LensGPT monitors spending continuously. Unusual patterns trigger immediate analysis and alerts. You discover issues before they become expensive problems. 2. **Automated optimization:** It identifies idle resources, rightsizing opportunities, and reservation purchases. Then it implements approved changes automatically during maintenance windows. 3. **Architecture-aware recommendations:** Unlike tools that only see billing data, LensGPT understands your infrastructure. It knows how services connect, which resources are critical, and what changes are safe to implement. 4. **Multi-cloud intelligence:** Managing AWS and GCP together? LensGPT provides unified visibility and optimization across both platforms. 5. **Role-based insights:** CFOs get financial summaries. Engineers get technical recommendations. FinOps teams get actionable optimization lists. Everyone sees the information they need in a language they understand. Learn more at cloudkeeper.com/cloudkeeper-lensgpt ## **Conclusion** Agentic AI is going to be the next big thing, potentially even eclipsing the dot-com revolution of the 90s in terms of its unprecedented boost in productivity, reach, and accessibility. But unlike the fearmongering that goes around—that Agentic AI will replace humans in terms of their dexterity, creativity, and uniqueness—that narrative is largely a marketing gimmick pushed by those who have billions invested in it. In reality, Agentic AI is a tool that augments human effort and makes individuals far more productive, not obsolete. For organizations, the coming decade will belong to those that master human–agent collaboration to boost productivity, ship products faster and with fewer bugs, Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 Solving the Blind Spot in GCP Billing with Browser Automation A comprehensive guide to solving the lack of visibility in GCP Commitment-Based Discount reports from the BigQuery billing export, using custom Python automation scripts and Selenium. By Manav Mittal 20 Aug, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents Today’s world is cloud-driven and businesses are leveraging the power of cloud to innovate while maintaining security, efficiency, and cost control. However, as cloud environments grow more complex how can you be sure that your infrastructure is not only built right but also performing at its peak? That's where AWS comes in with its Well-Architected Framework, an architectural blueprint created by seasoned AWS specialists that states the key concepts, design principles, and architectural best practices for designing and running workloads in the AWS ecosystem. _**As defined by AWS, The Well-Architected Framework is a collection of best practices that allow customers to evaluate and improve their cloud workloads' design, implementation, and operations.**_ An The AWS Well-Architected Framework Pillars are built upon six key areas: * Operational Excellence * Security * Reliability * Performance Efficiency * Cost Optimization * Sustainability ## **What is AWS Well-Architected Review (AWS WAR)?** AWS Well-Architected Review (AWS WAR) is a systematic process of assessing your infrastructure against the defined best practices and identifying areas of improvement, any critical issues, or optimization opportunities. But simply following the framework isn't always enough and might not lead you to your desired solution. Thus having the right AWS Well-Architected Partner makes all the difference. Here's a blog to read in-depth about ## **Who is an AWS Well-Architected Partner?** An AWS Well-Architected Partner is a certified consulting partner recognized by AWS for their expertise in While selecting an AWS Well-Architected Partner, you must ensure that they have a deep understanding of AWS Well-Architected best practices and know how to apply them effectively based on your specific organization’s maturity level, objectives, and capabilities. ## **Limitations of the Traditional AWS WAR Method** Many AWS Well-Architected Partners still follow the traditional review method. AWS Well-Architected Review(AWS WAR) is quite an extensive process, and each pillar consists of a set of assessment questions. AWS has established standard AWS Well-Architected best practices for each of those assessment questions, however, its implementation comes with certain limitations. * ### **Lengthy Questionnaires** Traditional AWS WARs rely on extensive questionnaires which can overwhelm your team. These are often time-consuming, resource-draining, and cost-ineffective. Moreover, the questions may lack relevance to the specific needs and purpose for which you are conducting AWS WAR. * ### **One-Size-Fits-All Approach** Traditional AWS WAR doesn’t take the company’s specific maturity, objectives, or capabilities into account. Whether it's a startup seeking rapid cost reduction or an established enterprise looking for long-term cost optimization, in traditional AWS WARs, everyone gets the same assessment questions. This approach can lead to more questions than answers. * ### **Generic Recommendations** Because the traditional AWS WAR is one-size-fits-all, the recommendations are usually too broad and may not offer practical, specific steps for the specific challenge that your team can act on. Implementing these broad recommendations without a clear direction can lead to wasted resources and missed opportunities for meaningful improvement. * ### **Lack of implementation support** The lack of hands-on implementation support makes it even harder to turn recommendations into action leaving you to figure out the next steps on your own. Thus, achieving optimal cloud performance can feel like a distant goal. And also we know that businesses don't have this much time to sort through broad recommendations. ## **How does CloudKeeper help as your AWS Well-Architected Partner?** As an AWS Certified Well-Architected Partner, CloudKeeper recognizes that every cloud environment has its own unique challenges. We understand that no two organizations have the same level of maturity or capabilities. Many of our customers also shared their feedback that traditional AWS Well-Architected Reviews often overlook customers’ specifics and commence without a deep understanding of pain points and capabilities, resulting in generic recommendations that fail to deliver tangible value. To tackle these challenges head-on, **CloudKeeper, exclusively came up with a smarter approach to AWS Well-Architected Reviews** that addresses all the limitations of traditional AWS WAR —and it’s all at no cost to you! As an AWS Well-Architected Partner, we never let our customers go through the long and cumbersome process, instead, our entire AWS WAR process is customized for each company. ### How does CloudKeeper stand out as an AWS Well-Architected Partner? We start our AWS WAR process with “you (our customer)” in mind. CloudKeeper follows a customer-centric engagement model. Before diving into the AWS Well-Architected Review, we conduct thorough consultations to understand your unique infrastructure and its gaps, your capabilities, and your desired outcomes from the review. Additionally, the foundation analysis helps us to tailor our recommendations and action plan based on your capabilities and maturity level. **Pre-WAR Essential:** A 90-minute detailed discussion for a deep understanding of your infrastructure and goals. **Post-WAR Essential:** A 90-minute detailed discussion to finalize actionable recommendations based on your maturity level. Here’s how we are countering every challenge of Traditional AWS WAR: * **Automated Architectural Review** Forget those long, tedious questionnaires. As an AWS Well-Architected Partner, we use advanced automation to assess your cloud infrastructure, making the process quicker and more relevant to your specific needs. This streamlined approach cuts down the time and effort needed by up to 5x, focusing on what truly matters to you. * **Custom recommendations for your cloud environment** We don’t do one-size-fits-all. Our recommendations are crafted just for you, thanks to our detailed post-WAR conversation. As an AWS Well-Architected Partner, we understand your environment inside and out, so our advice is always on point and actionable, helping you see real improvements in your cloud performance. * **Actionable Plans with Clear Milestones** Traditional reviews often stop at basic recommendations. Not us. We provide a clear action plan divided into short, medium, and long-term strategies. Our AWS Well-Architected Reviews break it down into actionable steps for the next 30, 60, and 90 days, so you know exactly what to do and when. * **Comprehensive Cloud Optimization Support** As your AWS Well-Architected Partner, we’re with you every step of the way, helping you implement changes and achieve cloud efficiency. Our certified experts provide ongoing support, making sure you get the most out of your cloud investment and see results faster. **Here’s a comparative table highlighting the clear advantage** **CloudKeeper AWS WAR vs. Traditional AWS WAR** ## **Steps for CloudKeeper’s AWS Well-Architected Review Process:** ## **Our Value Proposition as Your AWS Well-Architected Partner** As your AWS Well-Architected Partner, we go beyond basic assessment & recommendation and help you drive real cloud optimization with actionable strategies and tangible results. Here’s how we make a difference: * **Identify Critical Issues & Challenges** We dive into your cloud environment to find issues impacting performance, * **Tracking & Remediation of Top Pain Points** We focus on resolving critical issues first, helping you improve cloud performance and save up to 10% within the first 90 days. * **Adoption & Integration of New AWS Services** As your AWS Well-Architected Partner, we guide you in integrating the latest AWS services, keeping your infrastructure efficient and up-to-date. * **Expert Consulting for Overall Cloud Optimization** Our team provides expert advice to * **Proactive Outreach for Cost Optimization** We continuously monitor your environment for * **Human-Assisted Anomaly Detection to avoid Alert Fatigue** We know too many alerts can be overwhelming. That’s why we filter out unnecessary notifications and highlight only the significant issues. * **Custom Monthly Cost Analysis Reports** Each month, we send you detailed reports that break down your costs, trends, and other key insights, making it easier for you to take action. ## **CloudKeeper’s Proven Capabilities as an AWS Well-Architected Partner** An AWS Premier Partner, with 15+ years of cloud expertise, CloudKeeper stands out as one of the most experienced AWS Well-Architected Partners. CloudKeeper was ranked in the ### **Our AWS WAR Success Story** Within a week of partnering with CloudKeeper, as an AWS Well-Architected Partner,**Prodigal reduced their monthly AWS costs by 25%** and resolved many operational issues through the automated AWS Well-Architected Review & Implementation support. ## **How to choose your AWS Well-Architected Partner: A Quick Checklist** Next time when you go for an AWS Well-Architected Review, ensure your partner checks yes to the below questions. * Do they take the time to understand current state & company specifics(needs, challenges, desired outcomes, maturity level)? * Is their process simple, efficient, and streamlined? * Are their recommendations customized to your needs? * Do they provide a clear action plan on how to improve your infra? * Will they guide you on the implementation of the action plan? * Are they certified AWS Well-Architected Partners and have enough experience? Remember, AWS Well-Architected Review is always a smart investment and instrumental in guiding you toward an optimized cloud infrastructure on all six AWS WAR pillars. But don’t settle for a one-size-fits-all approach. CloudKeeper’s customized AWS Well-Architected Reviews and hands-on support help you not only save costs but also achieve peak performance and lasting value—all without any upfront expense. **Claim your****with CloudKeeper today!** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Traditionally every managed services team consisted of different team members with different skill sets, performing multiple roles for e.g. * **DC Ops/Administrators:** Responsible for providing Hands & Eye Support in data centers for Server/Storage etc. * **Network Admins:** Responsible for installing and managing Network Devices like Routers, Switches, Firewalls, cabling, etc. * **Monitoring Team:** Responsible for monitoring various monitoring tools and generated alarms and escalate to different teams based on alarm types. * Manage other aspects like the physical security of data centers, cooling systems, etc. However, as Cloud Service providers came into the market a massive shift started happening from Hosted/On-premise datacenter more simpler and agile way of working and managing the infrastructure. Teams started embracing the speed at which the Servers and other infrastructure components were deployed in Cloud. Engineering teams did not have to wait for 2-3 months to get the new hardware in place to launch a new application. However, as the traditional roles were eliminated, people had to re-skill as they no longer had to manage Hardware devices like Physical Servers, Storage, Backup tapes, networking devices, etc. Due to this shift, teams re-skilled and learned new services provided by Cloud Services providers. Which in turn, facilitated rapid deployment, automated configuration management, scaling of infrastructure based on demand and load, etc. With the new skills, the team is more focused on higher productivity work which facilitates businesses in increasing agility as well as embracing new age methodology like Agile, DevOps, etc. In the traditional data center, there were separate teams which were taking care of Physical servers and devices while a different team is taking care of virtual server provisioning, etc. Another benefit that organizations get by embracing However, in Cloud, capacity could be increased with a click of a button, hence, instead of waiting for new servers to be deployed for 2-3 months, this can now be done within 5-10 minutes and once it is not required it can be decommissioned which helps to keep the operational cost down. Moving to the cloud has enabled Managed services team to manage the complete infrastructure as code instead of doing everything manually, which was done earlier while operating in an on-premise/hosted environment. This has enabled teams to automate complete infrastructure deployments & management, which allows developers to work in close collaboration with infrastructure teams as it has enabled them to effectively utilize the available capacity without the need of over-provisioning resources. ## **Evolution of Managed Services** Managed services teams have come a long way from Managed Infrastructure services organizations are now However, in Cloud, it is now managed services team which does the installation, configuration, fine tuning of applications & servers so that Developers can focus on the development instead of worrying about how the server or application has to be installed or configured. ## **Comparison of MS teams in different environments** ## **Benefits of moving to Cloud Managed Services** * Organizations no longer need Datacenter Operations Team to be physically available at the site. * No need to worry about various compliances, which needs to be managed in a data center environment. For, e.g., physical safety/security, etc. * No need to install/manage physical devices. * No need to have specialized skills like Storage Admin, Network Admin, etc. * Cloud managed services team can quickly install pre-built AMI’s that saves on execution time. * No hand & eye support needed in Cloud. * Complication of managing different devices are eliminated, for, e.g., Fortigate/Cisco * Firewalls, Checkpoint Firewalls, NetApp Storage, etc. * No need to wait for months for the new hardware to provide additional capacity on a temporary or permanent basis. * Reduced capital investment as you don’t have to pay for a temporary spike in required capacity. * Don’t have to worry about Hardware failures and hardware replacement as it is managed by Cloud Provider (AWS, Azure) in the background. * New age tools specifically made available on Cloud facilitates quicker adoption of DevOps best practices (Puppet, Ansible, Jenkins, etc.) * Leverage services like Chef, OpsWorks for configuration management. * Easy migration and manageability of application from On-premise to Cloud and vice versa. * Cost savings on human resources required to manage a data center (on-premise/hosted) compared to management of servers running in Cloud. * High availability and SLA’s offered by Cloud Service Providers take the burden off the businesses to worry about infrastructure availability. * Cloud Managed Services team are now skilled to carry out higher value tasks instead of focusing on just provisioning a physical server and cabling of connected equipment’s etc. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents In a series of interview sessions at AWS re:Invent, CloudKeeper engaged FinOps leaders in a thought-provoking dialogue, exploring the intricacies of FinOps, and cost management challenges & solutions. Our team asked some of the most widely discussed topics to experts from organizations such as ISG, Everest Group, Capgemini, Merck, TP ICAP, Slickdeals, and others, unearthing ## **Meet the FinOps leaders who shared insights with CloudKeeper at AWS re:Invent-** * * * * * * * * * * * * **,** Senior Manager, Software Engineering at Archer Integrated Risk Management. Joe heads the software engineering department and works with Archer’s AWS reps to understand new feature capabilities and areas of improving cost efficiencies. * **,** VP of Engineering at DigitalReef. Rafael oversees the work of three primary full-stack development teams. ## **A recap of their valuable perspectives on FinOps strategies and cost management challenges-** The collective perspective on FinOps was unanimous – it's not solely about cost-cutting but a strategic approach to making money by optimizing cloud resources. The leaders emphasized that FinOps acts as a crucial bridge between technology and finance, emphasizing the necessity of integrating cost considerations into architectural decisions. The aftermath of widespread cloud adoption during the pandemic highlighted current struggles in managing and optimizing costs effectively. Among the myriad challenges discussed, RDS emerged as a central concern, with leaders expressing surprise at its substantial costs. The commitment to consumption gaps on AWS and the need to align commitments with actual usage was underscored. Leaders stressed the importance of robust cost control, crafting tailored solutions, and leveraging reserved instances to effectively address these challenges. When delving into cost optimization hacks, the conversation touched upon the cultural shift required within organizations. Treating cost as a key performance indicator and benchmarking against on-premises costs were highlighted as crucial practices. The recommendation included regular sessions to uncover low-hanging fruits for optimization, fostering a culture of continuous cost scrutiny. As the cloud continues to reshape the business landscape, the insights shared by FinOps leaders, representing a diverse array of companies, shed light on the evolving nature of cloud financial operations. ## **Conclusion** As the cloud continues to reshape the business landscape, the insights shared by FinOps leaders shed light on the evolving nature of cloud financial operations. From the strategic importance of FinOps to the challenges posed by specific services like RDS, the interview provides a comprehensive overview of the current state of cloud cost management. CloudKeeper, with its innovative solutions, has piqued the interest of FinOps leaders, signifying a potential shift in how enterprises approach cloud financial operations. For a deeper dive into the conversation and to glean further insights, we invite you to watch the complete video interview. Discover firsthand the perspectives, suggestions, and expert opinions that can guide your organization in navigating the intricacies of FinOps in the ever-evolving cloud landscape. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents The FinOps Framework is a living document, or more aptly, a roadmap for organizations to manage their cloud costs effectively, along with making the most out of their cloud investments. This framework evolves through the collective experience and insights of a community including technical experts and thought leaders, dedicated to refining cloud financial management practices. This guide is constantly being updated, with the 2024 changes released a few weeks ago. And yes, this is a big deal for all FinOps practitioners since they reflect the latest trends and best practices in cloud cost optimization. ## **What is in the FinOps Framework?** Think of it as a toolbox full of strategies for team collaboration, smart budgeting, and making data-driven decisions. It covers everything from With the 2024 updates, the FinOps Foundation has added even more tools to this ‘box’, especially for navigating newer challenges like cloud sustainability and integrating with other IT management areas. This means FinOps practitioners now have a more robust guide to help their organizations thrive in their turbulent journey through the cloud. ## **Why the Framework is Changing?** The motivation to update the framework came from the FinOps community itself, which has grown by leaps and bounds. More people across the globe now manage cloud budgets for their organizations, which means there is a Frequently used terms like “cloud cost optimization” and “cloud financial management” no longer capture the full scope of today’s challenges and opportunities. The framework aligns with a broader spectrum now, including emerging areas like cloud sustainability, **IT Asset Management (ITAM), IT Financial Management (ITFM),** and**IT Service Management (ITSM).** The 2024 revision of the FinOps Framework is a milestone that reflects these shifts. It aims to capture this collective wisdom, making the framework an essential playbook for the evolving demands of the cloud landscape. ## **What are the 2024 changes to the FinOps Framework?** These new updates signify a pivotal movement in the evolution of Cloud Financial Management practices. These changes are driven by the insights and experiences of the Technical Advisory Committee of the FinOps Foundation, and the larger Cloud FinOps community. ### **Refined Definition and Scope** One of the central updates is the refined definition of FinOps, which reflects ### **Revised Personas and Allied Roles** The personas within the FinOps Framework have undergone restructuring and now they align better with the updated cloud management needs. Core Personas, who directly engage in FinOps practices, have been streamlined and simplified to emphasize Additionally, there are Allied Personas, which are roles that are not directly involved in FinOps practices. They might be coordinating with other FinOps practitioners and might be working with intersecting disciplines. The new update has added a few more Allied Personas to encompass both the Source: The FinOps Foundation ### **Domain Updates - Shifting Focus to Business Outcomes** The FinOps domains have been updated for an outcome-driven approach, emphasizing the business objectives that the organization aims to achieve. The major changes include merging some domains to streamline focus areas and renaming these domains to better align with the desired outcomes. The new domains represent the four fundamental Source: The FinOps Foundation ### **Capability Updates - Capturing New Challenges** FinOps capabilities are the building blocks of actionable tasks and activities, which are required to meet the challenges of the FinOps practice. These help various FinOps Personas in aligning technology decisions with business objectives. New capabilities, such as Licensing & SaaS, and Architecting for Cloud, have been introduced to address the emerging challenges in cloud infrastructure design and management. This also encompasses the advancements in cloud technology. Additionally, existing capabilities have been refined and merged to reduce overlaps and to provide a more cohesive framework for FinOps practitioners. However, certain Source: The FinOps Foundation ## **Conclusion** There has been an active involvement of the FinOps community in shaping the framework’s evolution. Their contributions in terms of insights, experience, and feedback have played a vital role in guiding these updates, ensuring that the FinOps Framework remains relevant, comprehensive, and responsive to the emerging needs of FinOps practitioners. The 2024 update to the FinOps Framework ensures that it continues to stand as a trusted resource, empowering various stakeholders to optimize cloud resources, derive value, and _Did you know that CloudKeeper is a Premier Partner at the FinOps Foundation? We ensure all our FinOps practices are updated and optimized in tandem with the new FinOps Framework._ _Get your entire cloud infrastructure audited by us, completely for free!_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 2 2 Table of Contents For a decade, cloud cost management has meant one thing: open a dashboard. Log in, filter, pivot, export. The problem was never the dashboard; it's that almost no one opens it until the bill is already too high. Meanwhile, the way we work has changed. Engineers, platform teams, and FinOps practitioners now spend their day inside AI assistants - Claude, ChatGPT, Cursor, and Claude Code. That's where the questions get asked. It's not where the cost answers live. Today, we close that gap. **LensGPT - the AI cost analyst already used across CloudKeeper’s 400+ customers is now available as an MCP server.** Connect it to Claude Desktop, Claude Code, Cursor, ChatGPT, or Kiro, and ask about your cloud spend the way you’d ask a teammate: _“What did we spend on EC2 last month, and how does it compare to the month before?”_ You get an answer grounded in your real billing data, not a guess - without leaving the tool you’re already in. RI coverage, Savings Plan utilization, cost breakdowns, the right dashboard - all conversational. ## **Conversational Cloud Intelligence, built for trust.** The hard part of putting an LLM near your cost data isn’t access. It’s trust. LensGPT is built for it: every number maps to a real query against your data - if the data isn’t there, it says so, it never estimates. Your data stays scoped to your account, and it’s strictly read-only. It analyzes spend; it can’t touch your environment. If you’re already a CloudKeeper customer, you can turn this on today This is the start of a larger shift. Cost intelligence shouldn’t be a place you go. It should be ambient - in the conversation, then in the workflow, and eventually acting on what it finds, not just reporting it. The dashboard isn’t going away. But it no longer has to be where FinOps begins. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Director - Product Ronak has over 11 years of experience in building AI/ML and data products and scaling engineering teams at various startups. He was part of the early teams at Cogoport, Jugnoo, and Peak AI. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 10 Costly BigQuery Mistakes Engineers Make (And How to Avoid Them) A comprehensive guide to the top 10 BigQuery mistakes that cause cloud cost runaways and how to optimize queries, storage, and usage. By Team CloudKeeper 12 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents If you're reading this, chances are you've felt the shock of an unexpectedly high AI bill. You're not alone. Organizations worldwide are discovering that AI costs can spiral out of control faster than anyone expected. Enterprise Here's the reality: 62% of organizations report cloud mistakes costing them over $25,000 monthly, while 72% of IT and financial leaders say Generative AI spending has become completely unmanageable. We're talking about startups watching their bills explode from $10,000 to $100,000 in just three months. The problem isn't just the numbers- it's that AI works differently than traditional software. Instead of predictable monthly licenses, you're paying for every token processed, every conversation handled, and every piece of content generated. It's like switching from a monthly gym membership to paying per step on the treadmill. This is where FinOps for AI comes in. It's not just about cutting costs - it's about finding the sweet spot between scaling your AI capabilities, maintaining speed and performance, and keeping your CFO happy. ## **What is FinOps for AI?** FinOps for AI means bringing together finance, engineering, and business teams to gain visibility into AI-related cloud costs, ### **FinOps Scope Expansion Beyond Traditional Cloud Services** ## **The Scale vs. Speed vs. Spend Triangle: Managing Competing Priorities** Organizations implementing FinOps for AI must navigate three competing priorities simultaneously: Scale Demands: Meeting growing user adoption, expanding AI capabilities across business units, and handling increased data volumes without service degradation. Speed Requirements: Delivering rapid responses for real-time applications, accelerating time-to-market for AI features, and maintaining competitive performance benchmarks. Spend Constraints: Controlling operational costs, maximizing return on AI investments, and maintaining budget predictability amid variable usage patterns. Organizations that explicitly manage this three-way balance typically achieve better overall outcomes than those focusing exclusively on either technical or financial metrics. ## **Why Generative AI Costs Are Different (And Why That Matters)** **The Token Economy: Small Units, Big Bills** Let's talk tokens. Think of them as the fuel that powers AI models. When you type "What's the weather like?" you're not just using four words - you're consuming about 7-8 tokens, each adding to your bill. And here's the kicker: GPT-4 can cost up to 10 times more than smaller models for the same task. It gets more complex. You're charged for both input tokens (your questions) and output tokens (the AI's responses). Longer conversations? More tokens. Complex prompts? Even more tokens. Before you know it, you're looking at bills that make traditional software licensing seem quaint. * **Token economics** — Cost is often charged per 1k tokens. Multiply tokens-per-call by call volume and you quickly see the effect. Optimizations: shorter prompts, prompt engineering, response-length limits, and semantic caching. * **Model inference vs. training/fine-tuning** — Fine-tuning and training use lots of GPU-hours; inference at scale uses many smaller calls but can still dominate costs. Track both separately. * **Compute type** — * **Data storage & retention** — Logs, training datasets, and intermediate artifacts multiply storage bills; many organizations over-retain. * **Networking & cross-region egress **— Multi-cloud or multi-region topologies may add egress costs. ## **The Hidden Gen AI Costs Nobody Talks About** Beyond those obvious API calls, there are other costs lurking in the shadows: * **Experimentation Expenses:** Unlike traditional software, where you build once and deploy, AI requires constant testing, tweaking, and comparing different models. * **Data Preparation:** Getting your data ready for AI often costs as much as running the AI itself. We're talking about cleaning, formatting, and preparing massive datasets—all of which require serious computing power. * **Storage That Multiplies:** Every AI output, training dataset, and model version needs storage. 50% of organizations cite excessive data retention as their biggest inefficiency. * **Monitoring and Observability:** Real-time monitoring of AI model performance, accuracy, and usage patterns requires additional infrastructure and tooling investments that scale with deployment complexity. So the actual problem for Generative AI cost problem isn’t just “**we spent too much** ”. It’s that Gen AI multiplies cost vectors and outpaces legacy finance controls - which weren’t built for token meters or GPU spot pools. ## **The FinOps Solution: From Chaos to Control in Three Steps** **1. Crawl: Know What You’re Spending** Start by making costs visible. * Who’s running which models? * How many tokens and compute hours are we using? * Which workloads are the biggest money drains? * **2. Walk: Automate Smart Controls** With clarity in place, add smart guardrails: * **Budget Alerts:** Notify teams when they approach monthly or daily limits. * **Rightsizing:** Automatically suggest smaller models or fewer GPUs when usage is low. * **Spot and Reserved Instances:** Use discounted capacity for non-urgent training jobs. * **Prompt Optimization:** Refine prompts to get concise outputs, cutting token costs. At this stage, teams often see another major drop in spending without losing performance. **3. Run: Turn Cost Management Into a Growth Engine** Here, FinOps for Generative AI becomes proactive: * **Predictive Scaling:** Anticipate demand surges—scale up before traffic spikes, scale down when idle. * **Model Routing:** Send simple queries to cheaper models, complex tasks to premium ones. * **Integrated ML Pipelines:** Embed cost checks into your CI/CD so every new model automatically respects budgets. * **Business Alignment:** Tie AI spend to actual revenue or customer metrics—optimize for cost-per-result, not just cost-per-token. Leaders at this stage trim AI bills, freeing up budget to invest in new features. ## **Simple Strategies That Deliver Big Wins** **Smart Model Selection: The 80/20 of AI Optimization** Don’t always reach for the biggest, costliest model. Match model size to task complexity. Small models handle classifications and Q&A cheaply. Medium model nails summaries and code. And, save the heavyweights for high-value creative or multimodal jobs. **Improve Your Prompts** Well-crafted prompts can dramatically improve performance without expensive model upgrades. Reports from platforms like Prompts.ai show enterprises can cut AI expenses by 20-40% with smarter prompt routing and optimization. **Use Spot Instances** For non-mission-critical jobs (like training experiments), spot or preemptible VMs can slash compute costs by up to 60%. **Compress and Tier Data** Compress datasets before training, and move old data to cheaper archival storage. That alone can shave off 30–40% of your storage expenses. **Sandbox budgets & Automate Idle-Resource Shutdown** Provide data scientists with fixed experiment budgets and Turn off GPUs and nodes when they aren’t actively running jobs. Even leaving compute idle for a few hours each week adds up. **Semantic caching & deduplication** Cache the outputs of expensive calls (summaries, FAQ answers, short conversations). Use hashing of prompt+context to detect duplicates. Caching reduces token spend and improves latency. **AI-aware autoscaling & compute optimization** Autoscale based on inference queue depth or request backlog (not CPU alone). Use spot instances or preemptible VMs for non-urgent training; schedule heavy jobs off-peak. Here are a few strategies: **1. Automated Scaling Strategies:** * * Real-time demand response that adjusts resources based on current queue depth and request patterns. * Scheduled scaling for predictable workload variations (e.g., business hours, batch processing windows). * Cross-region optimization that shifts workloads to regions with better pricing or availability. **2. Token Usage Optimization:** Companies implementing systematic token optimization typically reduce consumption with minimal impact on response quality. Strategies include: * Prompt compression techniques that maintain meaning while reducing token count. * Response length controls to prevent unnecessarily verbose outputs. * Context window management to optimize the balance between context and cost. **Integration with MLOps Pipelines** Advanced organizations integrate cost optimization directly into their machine learning operations, ensuring that every model deployment, training run, and inference pipeline includes cost considerations alongside performance metrics. ## **Model Sizing Strategy Framework** ## **Real-World Case Studies and Results** **Netflix: AI-Driven Cost Optimization** Netflix uses FinOps to optimize its AI-driven recommendation system. The streaming giant combines model efficiency improvements with **Spotify: Auto-Scaling Innovation** Spotify uses **.** **Global Financial Services Transformation** A major financial services firm implemented machine learning algorithms that automatically identified and eliminated 23% of cloud waste while ensuring compliance with industry regulations. ## **Essential Metrics and KPIs for tracking AI FinOps Success:** **Cost Efficiency Metrics:** * Overall AI spend reduction percentages. * Unit economics improvements (cost per prediction, per model run). * Elimination of waste identified by optimization systems. **Optimization Accuracy:** Prediction accuracy vs. actual resource needs. Impact of optimizations on both cost and performance. Time-to-value acceleration for optimization implementations. **Business Alignment Indicators:** * How effectively does AI resource allocation support business objectives? * Ability to adjust to changing business priorities. * Automation effectiveness percentages for optimization actions. **Regular Cross-Functional Reviews:** * Weekly operational reviews focusing on cost trends and optimization opportunities. * Monthly strategic sessions aligning AI investments with business priorities. * Quarterly planning cycles incorporating both technical roadmaps and financial projections. * Real-time dashboard access providing visibility into both technical metrics and cost implications. ## **Cross-Functional Collaboration for AI Success** Effective AI FinOps requires bridging significant knowledge and perspective gaps between finance and engineering teams. Key strategies include: * **Shared Metrics:** Establishing common KPIs that matter to both technical and financial stakeholders. * **Regular Reviews:** Weekly or bi-weekly cross-functional meetings to review AI spending and performance. * **Automated Reporting:** Real-time dashboards showing both technical metrics and cost implications. * **Joint Accountability:** Shared responsibility for both AI performance and cost outcomes. ## **Quick Checklist for FinOps Generative AI action items** * Instrument and tag calls * Build per-model cost dashboard * Apply model tiering rules * Implement semantic cache * Add autoscaling based on AI-specific signals * Enforce sandbox budgets for experiments * Integrate cost checks in MLOps pipelines ## **Future Outlook: Automated FinOps for AI Becoming Standard Practice** IDC Predicts by 2027, 75% of organizations will combine Generative AI with FinOps processes. The future belongs to organizations that get ahead of this curve. **What's coming:** * * Integrated MLOps where cost considerations are built into every deployment. * Predictive management that prevents cost issues before they happen. * Business value optimization that balances cost with revenue impact. As highlighted in FinOps X 2025, leading cloud providers are already onto next-generation AI-Powered Cost Management tools. AWS Q for Cost Optimization, Azure AI Foundry Agent Service, and Gemini-powered FinOps Hub 2.0 all demonstrate LLM copilots that can explain spending anomalies, automatically tag resources, and even terminate idle GPUs in near-real time. Sustainability integration is also emerging. Oracle Cloud now shows CO₂ emissions alongside dollars, indicating environmental impact will join cost and performance as optimization criteria. **Mastering the AI Cost Management Challenge** FinOps for AI isn't just about controlling costs—it's about unlocking sustainable AI growth. Organizations that master this balance don't just save money; they create competitive advantages through smarter resource allocation and better return on AI investments. The organizations winning with AI aren't necessarily those with the biggest budgets - they're the ones who've learned to balance scale, speed, and spend effectively. The time for action is now. As AI adoption accelerates and costs continue rising, organizations that implement comprehensive FinOps for AI strategies today will be best positioned to scale their AI capabilities efficiently, maintain competitive performance, and ## **Ready to turn your Generative AI vision into something real — without the surprise bills?** That’s exactly what the Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Enterprises tell IDC they are rapidly adopting FinOps, with over 61% recently reporting they have active FinOps teams and processes in place today. To be candid here, I was expecting a much lower uptake for this relatively new practice. I dutifully rewrote the question to validate my assumption using a FinOps Foundation-supplied definition for clarity. I requested that IDC’s survey data team resubmit the question to another group of 800+ enterprises. Sure enough, the data came back with statistically the same high adoption rate. With “data” as our middle name (literally) at IDC, I humbly accept that enterprises are embracing FinOps faster than expected. And that's a good thing! In speaking with a sampling of these enterprises and other IDC clients, it is clear that many companies are in the early stages of maturity in their FinOps journey. FinOps is not just a technology tool. It is a collaborative process with cross-functional team members holding each other accountable. The aspirational goal is to improve cloud spending transparency by continually improving agreed-upon business and financial metrics. For many organizations, it is a culture change for cloud spending and investment. An excellent resource for FinOps definitions and best practices can be found at the Determining where your company is on its FinOps journey is the first step. Business-focused metrics are essential in maturing FinOps processes and critical to holding team members accountable. Every FinOps team should define and agree on at least the following five general areas of metrics. Adding critical metrics in each of these areas will help you to grow your FinOps Maturity. 1. **Accountability:** Identifying who is responsible for approving, architecting, monitoring, managing, and provisioning cloud resources is fundamental to FinOps. Cloud Enablement Percentage is one metric to define who is accountable for cloud costs and associated resources. To calculate this metric, take the percentage of cloud resources provisioned and managed by business units compared to those centrally managed by IT. Set a goal to move this percentage of cloud resources higher quarterly or annually, with steps to move the needle managed by business units towards this goal. 2. **Measurement and realization metric:** Cloud Spend Percentage Allocated to Business Owner is different from cloud enablement because it focuses on cloud costs that are correctly tagged and allocated to the line-of-business owner. Cloud expenses are often left to IT to budget and pay for each month, with some companies using a “show back” only model. Moving actual costs into the line of business that requested the cloud resource helps ensure accountability and focus on projects with business alignment and the highest return on investment. It must be stated the importance of proper tagging to achieve this metric. The tags must be correctly set up on new cloud resources and maintained to avoid finger-pointing and losing faith in the allocation process. Automation can help teams keep tagging accurately. FinOps teams should strive to continually raise the bar to move entirely to business-allocated cloud costs. 3. **Cost optimization:** A way to measure cost optimization is for FinOps teams to calculate the percentage of implemented cloud optimization recommendations. Typically, FinOps teams meet monthly to review the reports and analytics from their cloud cost transparency tool. Tracking what was successfully implemented each month is essential to driving cost improvements. The tool can help identify abandoned servers, over-provisioned cloud resources, and opportunities related to hyperscaler pricing tiers. Each month a FinOps team member should be assigned to implement these recommendations. A mature FinOps practice will have a high percentage of optimization recommendations implemented each month, and the savings realized will be reported to the whole team. 4. **Planning and forecasting:** One of the most important tasks for FinOps is to create and forecast future cloud spending. Accurate quarterly and annual cloud spending is essential for proper planning and budgeting for new and existing investments. Teams should publish quarterly and yearly enterprise-wide forecasts and compare those to consolidated cloud spending. The variance percentage should also be shared with all participants. By assigning a team member to analyze forecast variance, FinOps teams can improve their accuracy over time and build trust in cloud future cloud projects. 5. **Tools and accelerators:** The people and processes of FinOps are often the biggest challenges to implementing a mature practice in an organization. However, the cloud costs tool is the single critical source of truth for the team. Tracking and publishing the ongoing and cumulative successes in cloud savings and resource optimization will build momentum and engagement around the FinOps team. In addition, FinOps automation is a capability of numerous tools today. Automation can assist in many ways, such as tracking the above metrics and helping with resource tagging. Take charge of your FinOps adoption and maturity by implementing one of the more impactful metrics in each category. Kick off the training wheels and kickstart high-performing FinOps. I'd love to hear the most impactful metrics used by your FinOps teams, so feel free to share your comments below or email me. ## **Finding the Right FinOps Partner** The Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * * * * * * I am looking for blogs on Automation Cloud Cost Management AWS EDP AWS Services Cloud Cost Analytics Cloud Cost Optimization DevOps FinOps Strategy RI Management Kubernetes FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 10 Costly BigQuery Mistakes Engineers Make (And How to Avoid Them) A comprehensive guide to the top 10 BigQuery mistakes that cause cloud cost runaways and how to optimize queries, storage, and usage. By Team CloudKeeper 12 May, 2026 GCP Pricing Demystified: A Comprehensive Cost Guide A simplified yet comprehensive guide to GCP pricing, covering everything you need to make informed and cost-efficient GCP decisions. By Team CloudKeeper 08 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Top 10 Best Cloud Cost Management Tools in 2026 (Ranked by G2 Users) This blog walks you through the top 10 Cloud Cost Management tools featured in the G2 Winter 2026 Grid® Report, highlighting their strengths and limitations to help you choose the right FinOps platform. By Naman Jain 18 Mar, 2026 State of FinOps 2026 Report: Key Trends, Insights, and What Comes Next This blog analyzes the State of FinOps 2026 Report, highlighting key trends, insights, and what they mean for cloud ecosystems and technology decision-makers. By Team CloudKeeper 13 Mar, 2026 From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents Let's be real. When you first dive into the cloud, it's easy to get lost. It feels like walking into a massive hardware store, being handed a pile of parts, and being told, "Build a house. Oh, and it has to be cheap and secure." The same feeling applies when you need to deploy a classic 3-tier application—a frontend, some backend logic, and a database. So, how do you do it on ## **The Architecture: A Visual Guide** Before we get into the nitty-gritty, let's look at the big picture. This is the architecture we're building—lean, scalable, and secure. It's a real, working reference architecture from Google Cloud that perfectly illustrates the philosophy behind a modern cloud deployment. As you'll see from the diagram, the secret is a serverless, managed-first approach. Let's break down the services that make this possible. ## **Tier 1: The Frontend - Going Serverless for the Win** Your frontend is the face of your application. It’s what users see and touch. The old way involved running a number of VMs with a web server on each, but that required a lot of manual work and wasted money. The smart, cost-effective, and low-maintenance way is Cloud Run. You just package your web app into a container—whether it’s built with React, Vue, or just plain HTML—and let Cloud Run handle the rest. It scales down to zero instances when no one's using it (hello, zero cost!), and then scales out automatically when a million users hit your site. You literally only pay for the time your code is actually running. For detailed information, see the For all your static stuff—images, CSS, JavaScript files—we'll use **Cloud Storage**. It's incredibly cheap, massively scalable, and integrates perfectly with Cloud Run. You can even set up a simple Content Delivery Network (CDN) to ensure your content is delivered lightning-fast to users worldwide. Learn more in the ## **Tier 2: The Backend - All the Logic, None of the Headaches** This is where your business logic lives, handling API calls and talking to the database. This is another perfect candidate for serverless. Once again, **Cloud Run** is our hero. Your API can live in its own container, completely separate from the frontend. This decoupling makes it a breeze to manage and scale independently. Now for the important part: security. You absolutely do not want your backend API exposed to the public internet. Instead, we'll use a **Serverless VPC Access** **connector** , allowing your backend service to securely and privately communicate with the database, keeping your data locked down. For a deeper dive, refer to the official ## **Tier 3: The Database - Let GCP Do the Work** The database is the heart of your application. You could run a VM and install a database on it, but let's be honest, managing backups, patches, and replication is a full-time job. Instead, let GCP do all the heavy lifting with **Cloud SQL**. It’s a fully managed relational database service that supports MySQL, PostgreSQL, and SQL Server. You get high availability, automated backups, and effortless scaling. While it might seem pricier upfront, when you factor in all the engineering hours you save from not having to be a DBA, the total cost of ownership is far lower. Refer to the for more information. And for the most sensitive stuff—your database passwords and API keys—don’t ever hardcode them. Use **Secret Manager**. This service securely stores and manages all your sensitive data, and your application can retrieve it at runtime. It's an easy way to level up your security posture. Learn how to use it in the ## **The Final Word on Security and Cost** This architecture isn't just about services; it's about a mindset. By embracing a serverless-first approach, you're building a solution that is inherently more secure and cost-effective. * **Security:** You've got a minimal attack surface because you're not managing VMs. Your services talk to each other over a private network. And you're handling secrets the right way. * **Cost:** This is the magic part. Pay-per-use on Cloud Run means your bill directly reflects your user traffic. You're not paying for idle servers. You can start small and scale up only when your business demands it. In short, deploying a 3-tier app on GCP isn't a complex puzzle. It's a strategic design process. By leveraging these powerful, managed services, you build a foundation that is not only robust and secure but also scales with your needs—all without requiring a massive budget. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Lead Rahul is a seasoned DevOps professional with hands-on experience in building, automating, and scaling cloud infrastructure. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents When businesses mature on cloud adoption, what started as simple infrastructure migration evolve into distributed, containerised, multi-project, multi-team environments. Gaining better visibility through efficient In the case of Google Cloud users, most organisations begin with GCP Cost Explorer and native billing tools. It is the logical first step for GCP cost monitoring. It provides structured access to billing data, service-level breakdowns, and budget tracking. For many teams, this works well in the initial stages. But then your infrastructure grows. You've got Seeing your spending is one thing. Actually controlling it is different. ## What GCP Cost Explorer does well? Let's give credit where it's due - GCP Cost Explorer handles the basics. You can analyze spend across services and projects, It's a solid starting point for smaller setups or teams just getting their feet wet. The problem is, it's mostly backward-looking. You're analyzing what already happened. And as your environment gets more complex, the questions you need to answer get way more specific: * What's actually causing that cost spike? Like, the specific resource? * Which of our GKE clusters is sitting there underutilized? * Why is Team X creating resources without proper tags? * What workloads are quietly eating up the budget every hour? * Are we actually using those commitments we bought, or are they about to expire? * How much are we really saving from CUDs, SUDs, spot instances, and credits? GCP Cost Explorer wasn't built to answer these questions easily. That's not a knock on it - it's just not designed for that level of detail. ## Why does hourly visibility actually matter? This is where I know what you're thinking - do we really need to check costs every hour? Well, not exactly. But here's what changes: when your engineers can see cost impacts within hours instead of days, they make different decisions. That database someone spun up for testing at 2 PM? They'll shut it down before leaving instead of letting it run all weekend. It's behavioral, really. Real-time feedback creates accountability in a way that monthly bills just don't. ## Resource-level breakdown GCP Cost Explorer shows you service-level costs. CloudKeeper Lens shows you every instance, volume, bucket, and resource for an in-depth You also get bucket-level breakdowns for Cloud Storage. This might sound overly detailed, but if you're running data-heavy workloads, storage costs can creep up without anyone noticing. Being able to pinpoint which buckets are the culprits makes a huge difference. Instead of "Cloud Storage is expensive," you get "these three specific buckets are costing us $X per month, and here's why." ## Comprehensive dashboards Native tools give you cost reports. CloudKeeper Lens gives you dashboards designed for people who actually need to use them. You get breakdowns across services, SKUs, resource families, compute, storage, networking - plus custom tags and groups. There's unified visibility at both the org level (for leadership) and project level (for individual teams). These aren't just for finance folks preparing budget reviews. Cloud architects can use them to model unit costs, analyze regional differences, and It bridges the gap between "Here's what we spent" and "Here's why we spent it, and what we should do about it." ## The daily cost digest One practical improvement: Major spending changes, anomalies, commitment utilization shifts - all summarized without you having to remember to check the console. It sounds simple, but it makes cost awareness part of your daily routine instead of a monthly fire drill. ## Smarter cost alerts Budget alerts exist in GCP Cost Explorer, but they can be... noisy. You get a lot of alerts, many of which turn out to be nothing. Lens adds anomaly detection, predictive forecasting, and spike alerts. But here's the kicker: there's a human-assisted layer. Cloud experts review anomalies and recommendations before they hit your inbox. This cuts down on false positives dramatically. If you're already drowning in alerts from your monitoring stack, you need to focus on cloud cost signals that actually matter. ## Making Sense of Commitments and Savings Commitment management is tricky. You want to commit enough to get discounts, but not so much that you're paying for capacity you don't use. CloudKeeper Lens tracks both CUDs and SUDs with detailed utilization trends. It flags underutilized commitments, warns about upcoming expirations, and - this is important - Not just "you're using commitments," but "here's your exact savings from CUDs, SUDs, spot instances, and credits." That level of clarity doesn't exist in native GCP tools or any other tool available in the market. ## Optimization Built In Here's where things get interesting. Lens doesn't just show you costs - it also tells you how to reduce them. Rightsizing recommendations, idle resource detection, underutilized GKE clusters, storage class transitions, network egress optimization. All surfaced automatically within the same interface you're using to monitor costs. You don't need to export data to another tool, run analyses, and come back with recommendations. The recommendations are already there. Monitoring and optimization become the same workflow. Want custom reports in GCP Cost Explorer? For custom reports in GCP Cost Explorer you're probably exporting to BigQuery and writing queries. Lens lets you generate custom reports with one click. Projects, services, SKUs, resource types, tag groups - whatever cuts you need. No external pipelines required. FinOps teams get clearer ## Tag Compliance Tagging feels like busywork until you realize your cost allocation is completely wrong because nobody tagged their resources properly. Lens highlights untagged and non-compliant resources along with their costs. It's a governance layer that enables GCP Cost Explorer gives you project-level breakdowns, but it won't tell you which team forgot to tag half their infrastructure. ## Multi-project visibility If you're running multiple GCP projects (and most enterprises are), you need consolidated views. Lens gives you an org-wide dashboard plus detailed project-level breakdowns. Role-based access means teams only see their own project data, while leadership gets the full picture. No more manually aggregating reports from different environments or building custom dashboards just to see everything in one place. ## Quick Comparison Overview ## Fast, secure onboarding From an architectural standpoint, implementation simplicity matters. CloudKeeper Lens requires only billing account read access. There are no agents to deploy, no infrastructure modifications, and no operational access to workloads. The onboarding process is straightforward: * Login to your Google Cloud account * Provide billing account read access * Receive Lens credentials Within minutes, teams gain access to resource-level For organisations concerned about security exposure or operational disruption, this low-friction model is a strong advantage. ## From mere cost visibility to Cloud Cost Intelligence GCP Cost Explorer remains a reliable starting point for However, with a mature and complicated infrastructure in place, teams require more than retrospective dashboards. They need hourly visibility, deep resource-level insights, unified organisational dashboards, structured custom reporting, proactive daily cost digests, and more, preferably with a human in the loop for expert That is the evolution from basic cloud cost monitoring to intelligent * * * ## Frequently Asked Questions **Q1. Is GCP Cost Explorer enough for enterprise-level cloud cost governance?** GCP Cost Explorer is good for basic cloud cost monitoring. But for enterprise-level governance, teams need deeper visibility, better alerts, and stronger cloud cost optimization. It manages foundational needs, but advanced environments usually require more control and intelligence. **Q2. When should I move beyond GCP’s native cost tools?** You should move beyond GCP cost explorer when your cloud setup becomes complex. If you manage multiple projects, GKE clusters, or large CUD commitments, basic cloud cost monitoring may not be enough. Advanced cloud cost optimization tools help prevent spikes and improve cost control. **Q3. Does CloudKeeper Lens replace GCP Cost Explorer or work alongside it?** CloudKeeper Lens works alongside GCP cost explorer. GCP cost monitoring continues as usual, while Lens adds deeper visibility, optimization insights, and governance controls. It enhances native tools rather than replacing them. **Q4. Can GCP Cost Explorer manage committed use discounts effectively?** GCP cost explorer shows basic CUD and SUD data. However, it does not provide deep tracking or strong cloud cost optimization insights. For better commitment utilization and savings visibility, more advanced GCP cost monitoring tools are often required. **Q5. How does CloudKeeper Lens align cloud spending with business KPIs?** CloudKeeper Lens improves cloud cost monitoring by linking spend to projects, teams, and resources. With detailed reports and unit cost views, it supports better cloud cost optimization and helps align GCP costs with real business goals. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 Solving the Blind Spot in GCP Billing with Browser Automation A comprehensive guide to solving the lack of visibility in GCP Commitment-Based Discount reports from the BigQuery billing export, using custom Python automation scripts and Selenium. By Manav Mittal 20 Aug, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents ## **Why is GCP Cost Monitoring important?** GCP offers cutting-edge tools for cloud computing, but without adversative monitoring features, businesses risk recurring instances of "bill shocks." Managing the cloud bill as much as performance optimization is important. GCP cost monitoring can greatly enhance companies' cloud cost visibility, control, and optimization. ## **How does GCP cost work?** Google Cloud Platform (GCP) uses a pay-as-you-go scheme, and in turn, companies are charged based on actual resource consumption. The charges are further determined by variables such as: * **Compute resources:** These include VMs, Kubernetes clusters, and serverless functions. * **Storage & databases:** Charges accrue for being utilized in respect of Persistent Disks, Cloud SQL, or BigQuery. * **Networking:** This includes data transfer, bandwidth consumption, and load balancing. * **APIs and Services:** Charges incurred using a service (such as using Google AI Services, BigQuery, or Cloud Functions). Since GCP costs are chargeable per usage, these costs can very quickly go out of control if services are not monitored, resources are left idle, or configurations are inefficient. ## **10 ways to curb your GCP "Bill Shock"** Here are ten best practices to help you ### **1. Use Google Cloud Billing Reports and Dashboards** Google Cloud Billing Reports is a widely used GCP cost monitoring tool that provides insight into cost trends, anomalies, and detailed usage breakdowns. You should configure alerts for any uncommon spending patterns so that unexpected spikes can be avoided. Here’s a guide to learn more about ### **2. Set Up Budgets and Alerts** Establish spending limits and real-time alerts through the GCP console. Notifications will be sent whenever usage approaches a pre-defined threshold. This will enable proactive cost control. ### **3. Optimize Costs with Committed Use Discounts (CUDs)** For predictable workloads, CUDs provide a means to guarantee lower rates against on-demand pricing—by as much as 55%. ### **4. Ensure the Right Sizing of Compute Instances** Avoid over-provisioning virtual machines by choosing the right CPU, memory, and storage configuration. GCP cost monitoring tools can further help identify the under-utilized instances for better optimization. ### **5. Identify and Remove Idle Resources** These would include VM instances, disks, and Kubernetes clusters not in use, all of which incur storage costs; therefore, unnecessary costs arise when not regularly checked for idle or orphaned resources. ### **6. Optimize Storage Cost** Move rare access files to cheaper storage, such as Nearline, Coldline, or Archive. Enable Object Lifecycle Management to automate this transition. ### **7. Keep an eye on Networking Costs** This is one of the most important aspects of GCP cost monitoring. Data transfer costs can explode if internal versus external traffic flows are not optimized, so it is wise to consider the usage of Cloud CDN and cut down on unnecessary egress fees. ### **8. Enable Cost Attribution via Tags and Labels** Tagging resources by teams, projects, and environments will enable the tracking of costs by departments or workloads. ### **9. Gain Advanced Cloud Cost Visibility Via CloudKeeper Lens** ### **10. Scale and Schedule Automation** To avoid unnecessary expenditure during off-hours, shut down the VMs via a schedule. Also, auto-scale Kubernetes and Compute Engine resources based on demand with auto-scaling policies. ## **GCP Cost Monitoring - Frequently Asked Questions** ### **Q1: How do I set up GCP cost alerts?** You can create cost alerts in the Google Cloud Billing Console by setting up budgets with email notifications when spending exceeds thresholds. You can also take the help of the CloudKeeper Lens which provides human-assisted cost anomaly detection to avoid alert fatigue. ### **Q2: What are some cost-saving techniques for GCP compute?** Use Committed Use Discounts (CUDs) for predictable workloads, and right-size instances, and automate your VM shutdowns when not needed. ### **Q3: How does CloudKeeper Lens help in GCP cost monitoring?** CloudKeeper Lens provides a comprehensive and unified dashboard for your entire spending on Google Cloud. It offers end-to-end resource-level cost visibility, personalized reporting, cost-saving recommendations, and a detailed breakdown of your cloud spending to make smarter, data-driven decisions. ### **Q4: How do I control transfer costs on GCP?** Control data transfer costs in GCP by minimizing inter-region transfer, using Cloud CDN for caching, and prioritizing internal traffic. ### **Q5: Why is it important to label resources in GCP?** Labels and tags help allocate costs to specific teams or projects, which facilitates tracking of their spend and optimization of the associated budgets. ## **Final Thoughts** By implementing these GCP cost monitoring and Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents Cloud computing costs are set to surpass traditional IT spending, according to research by Gartner. As organizations continue to embrace the cloud, the challenge of managing cloud expenses effectively has come to the forefront. Studies suggest that 32% of cloud budgets are wasted, 75% of organizations report rising cloud waste, and nearly half (49%) of cloud-based businesses struggle to control costs. These figures highlight why This blog dives into the top strategies that help in GCP cost optimization while maintaining peak performance. While GCP brings a host of unique advantages, its pricing model—like the pay-as-you-go approach common across cloud providers—requires thoughtful planning and vigilant oversight to effectively manage costs and maintain performance. Fortunately, there are a variety of features, tools, and strategies available to help businesses in Google Cloud cost optimization empowering them to maximize their ROI, which we’ll explore in detail in this blog. ## **Understanding GCP Pricing** Before diving into GCP cost optimization strategies, it’s crucial to ### **Pay-As-You-Go** The pay-as-you-go pricing model provides flexibility by charging users only for the resources they use. It is particularly suitable for businesses with fluctuating or unpredictable workloads, as it allows for easy scaling of resources without long-term commitments. However, this flexibility often comes with higher hourly rates compared to other pricing models. ### **Long-Term Commitments** Google Cloud offers significant discounts for users willing to commit to using services for extended periods, typically 1 or 3 years. This pricing model, referred to as Committed Use Discounts, helps in cloud cost optimization by saving businesses up to 70% on Compute Engine expenses. The trade-off is reduced flexibility, as organizations must commit to a fixed price and usage level for the duration of the agreement. ### **Free Tier** The GCP free tier is ideal for individuals and businesses exploring Google Cloud’s offerings or those with minimal usage requirements. It includes access to 24 predefined services, with certain resources always free within usage limits. Users also receive $300 in free credits to try out paid services. ### **Key Cost Drivers in GCP** Beyond its flexible pricing models, GCP costs are influenced by core service categories such as compute, storage, and networking. * **Compute:** Charges based on VM runtime, with discounts for sustained use or preemptible VMs. * **Storage:** Costs depend on data volume, operations, and retrieval fees, especially for archival storage. * **Networking:** Ingress is free, but egress costs vary by region and traffic type. * **Cloud SQL:** Charges depend on instance type, CPU and memory usage, storage, and networking, with costs varying by region and active runtime for shared-core instances. * **Google Cloud Functions:** Pricing is based on function execution duration, invocation frequency, and allocated resources, ensuring cost alignment with specific usage. To better predict and manage expenses, GCP provides a Pricing Calculator, helping users estimate costs based on their unique requirements. Mastering these basics is the first step toward optimizing your GCP investment effectively. ## **Challenges in GCP Cost Optimization** There are several challenges organizations face that can make cloud cost optimization complex and difficult. * **Inefficient Resource Utilization:** Underutilized services and cloud waste often lead to unnecessary expenses. Compute services like GCP's Compute Engine are costly, and without * **Rising Storage Costs:** Storage resources, particularly block storage, are a significant contributor to rising GCP costs. Overprovisioning, driven by the desire to avoid performance issues, often leads to paying for unused storage, exacerbating inefficiency. * **Complex Billing Structure:** GCP’s complex pricing model, which includes varied costs for ingress, egress, and usage-based discounts, makes cloud cost optimization difficult. Fluctuating usage patterns further complicate accurate billing predictions. * **Overprovisioning of Resources:** Many organizations tend to overprovision compute and storage resources to ensure system performance. However, this results in wasted resources and inflated bills as they pay for capacity they don’t use. * **Lack of Efficient Optimization Tools:** GCP’s native tools can fall short in streamlining resource optimization, often requiring manual interventions or third-party solutions. This increases the burden on teams and ## **10 Best Practices to Reduce Your Google Cloud Costs** Now you know the major challenges that could impact your GCP budgets and cause cost overruns. Let’s explore some GCP cost optimization strategies. These strategies, ranging from simple housekeeping tasks to advanced techniques like leveraging discounts and preemptible VMs, can help you fine-tune your infrastructure, reduce waste, and make the most of your cloud investments. ### **Gain Visibility into Cloud Costs** ### **Remove Unattached Block-Level Storage Discs** When you terminate a VM, ensure that any unattached block-level storage discs are also deleted. These discs can continue accruing charges even when no longer associated with an active VM. Regular audits of your resources can help you identify and eliminate these unnecessary costs. ### **Get Rid of Unused IP Addresses** Google charges for external static IP addresses that are not in use. Make it a routine to monitor your environment for unused IPs and remove them. This small practice can prevent unexpected charges and boost your cloud cost optimization efforts. ### **Schedule Non-Production Virtual Machines** ### **Leverage Committed Use Discounts (CUDs)** Committed Use Discounts (CUDs) offer significant savings for businesses with predictable workloads. By committing to a 1-3 year term, organizations can reduce cloud spending by up to 57%. It’s a smart move for those who can forecast their cloud usage with confidence. ### **Optimize VM Selection for Cost Efficiency** Choosing the right VM type can significantly enhance cloud cost optimization. Use Preemptible VMs for fault-tolerant workloads like big data processing and CI/CD pipelines to save up to 80%. Additionally, leverage Custom Machine Types to align instance sizes with workload needs, avoiding overprovisioning and reducing cloud costs significantly. ### **Implement Object Lifecycle Management for Storage** Google Cloud Storage offers various storage tiers, and not all data requires high-performance access. Use object lifecycle management to automatically move older or less frequently accessed data to lower-cost storage tiers, ensuring you only pay for the performance you need. ### **Take Advantage of Sustained Use Discounts (SUDs)** If your workloads consistently use Google Cloud resources, you can benefit from Sustained Use Discounts (SUDs). These discounts are automatically applied based on how long you use specific services, enabling ### **Clean Up Unused Resources** It’s easy to accumulate unused resources in your cloud environment. Regularly cleaning up unused instances, IP addresses, or storage buckets helps eliminate waste and reduce your overall cloud expenditure. Setting up automatic clean-up procedures is a proactive approach towards Google Cloud cost optimization. ### **Work with a Cloud Cost Optimization Partner** While implementing cost-saving strategies internally is important, working with a cloud cost optimization partner could help you achieve far better results. Working with experts like CloudKeeper can help you identify hidden costs, streamline your cloud resources, and By following these strategies and best practices, businesses can see significant reductions in their Google Cloud costs while maintaining performance and scalability. ## **Conclusion** Google Cloud Platform (GCP) is a standout choice in the cloud industry, holding about 10% of the market share and offering unmatched strengths in data analytics, machine learning, and containerization with Kubernetes. Its capabilities around fast data transfers and low latency make it a go-to option for businesses needing real-time data processing or latency-sensitive applications. With seamless integration into tools like Google Workspace and support for multi-cloud setups, GCP provides the flexibility and reliability modern enterprises demand. That said, keeping costs under control is just as important. By adopting the GCP cost optimization strategies outlined in this blog—like rightsizing virtual machines, leveraging Committed Use Discounts, and optimizing storage—companies can significantly reduce cloud spending. Also, cloud cost optimization doesn’t have to be overwhelming. With GCP’s robust capabilities and a strategic approach to cost efficiency, businesses can not only save money but also reinvest those savings into innovation—unlocking the full potential of their cloud journey. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 12 12 Table of Contents When you run workloads on Google Cloud, one of the most important decisions you'll make is choosing the right virtual machine (VM) instance. That choice directly affects how well your application performs, how easily it scales, and how much it ends up costing you. This blog is all about GCP Compute Engine types of instances - the building blocks of your cloud infrastructure. Whether you're spinning up a web server, running an analytics job, or training a machine learning model, picking the right VM type is critical. A mismatch can lead to sluggish performance, wasted resources, or bills that spiral out of control. And this isn’t just theory - cloud waste is a growing issue. Studies show that organizations are projected to waste around $44.5 billion in 2025 due to unused or overprovisioned cloud resources. Kubernetes clusters alone waste about 37% of what they’re allocated. That’s why engineers, CTOs, and even CFOs are paying more attention to GCP instance selection. The good news? GCP offers a wide variety of VM types through Compute Engine - general-purpose, memory-optimized, compute-optimized, and even custom machines - giving you plenty of flexibility to match your workloads and supporting In the sections ahead, we’ll break down GCP instance selection across various GCP machine families, compare them for real-world use cases, and guide you on how to choose the one that delivers the best mix of performance, scalability, and cost savings. ## **What is Google Cloud Compute Engine?** Google Compute Engine (GCE) is the foundation of virtual machines on Google Cloud. As an Infrastructure-as-a-Service (IaaS) offering, it gives users full control over VM provisioning and GCP instance selection - letting you choose exactly how much CPU, memory, and storage your workloads need. Whether you're hosting a website, processing big data, or running high-performance simulations, compute engine offers the flexibility and power to match. You can choose from a range of predefined GCP machine families, or build custom VMs tailored to your unique requirements. This level of customization helps avoid overprovisioning, which means One of GCE’s biggest strengths is scalability. You can spin up instances when demand spikes and shut them down when you don’t need them, helping you stay efficient. Plus, with features like global load balancing, live migration, and deep integration with other GCP instances and services like BigQuery, Cloud Storage, and Vertex AI, Compute Engine becomes the central piece of your cloud architecture. In short, GCE gives you the raw compute power of a physical server, with the flexibility and agility of the cloud - making it an ideal choice for businesses looking to scale smarter and spend wiser. ## **What are the various GCP Instance Types?** Choosing the right VM instance type is crucial for balancing performance, scalability, and cost. GCP Compute Engine offers a wide array of GCP machine families tailored to different use cases - from general-purpose applications to memory-hungry databases or compute-heavy workloads. ### **Understanding GCP Machine Families and Series** Before diving into specifics, it’s essential to grasp GCP’s classification system: * **Machine Family:** Broad categories like general-purpose, compute-optimized, memory-optimized, or accelerator-optimized. * **Series:** Generations within each family, like E2, N2, or C2D, offering different performance, pricing, and hardware platforms. * **Machine Type:** Specific combinations of vCPU, memory, and optional features (like GPU or SSD) that define each VM configuration. Now let’s understand the VMs based on their specific use-cases. ### **General-Purpose VM Instances** General-purpose GCP instances offer a balanced blend of compute, memory, and networking resources. They're best suited for common workloads such as web servers, small to medium databases, development environments, and business applications that don’t have extreme CPU or memory demands. **Key Series:** * E2 / E2 Shared-Core: Cost-effective VMs with burstable performance. Ideal for dev/test workloads; note that sustained-use discounts aren’t applicable. * N2 / N2D / N4: Performance-focused with flexible configurations. Choose between Intel (N2, N4) or AMD (N2D) based on your workload needs. * Tau T2D / T2A: High-throughput, fixed-shape instances powered by AMD Milan (T2D) or ARM (T2A). The smarter GCP instance selection for scale-out microservices and web hosting, with leading price-to-performance ratios. * C3 / C3D / C4: While labeled compute-optimized, these newer generation VMs can also serve general-purpose needs, offering performance, advanced networking, and the latest CPUs. ### **Compute-Optimized VM Instances** Compute-optimized instances are GCP instances tailored for high-performance tasks that require intensive CPU processing like scientific computing, game servers, and latency-sensitive microservices. **Key Series:** * C2: Intel Cascade Lake CPUs, designed for workloads needing high single-thread performance. * C2D: AMD Milan-based VMs with larger memory and cache - these GCP machine families are ideal for simulations, media processing, and compute-bound tasks. * H3: Next-gen compute instances supporting PCIe Gen5 and CXL, optimized for low-latency, high-throughput applications. ### **Memory-Optimized VM Instances** These GCP compute engine types are engineered for memory-heavy workloads such as large-scale databases, SAP HANA, in-memory analytics, and enterprise caching. **Key Series:** * M1 / M2 / M3 / M4: High memory-to-vCPU ratio GCP instances, scaling up to 12 TB RAM (M4). Best fit for mission-critical applications needing extreme memory capacity. * X4: Supports even higher core and memory limits for advanced SAP HANA and memory-bound analytics. ### **Accelerator-Optimized VM Instances** GCP instance selection for workloads requiring GPUs or TPUs, such as AI/ML training, inference, data modeling, and graphics rendering, will require accelerator-optimized instances. These GCP machine families are purpose-built for parallel processing at scale. **Key Series:** * A2: Powered by NVIDIA A100 GPUs and Intel Cascade Lake CPUs, available in fixed shapes. Ideal for deep learning and model training. * A3 / A4: Next-gen GPU instances for highly parallelized workloads like LLMs, GenAI, and advanced inference (A4 in preview). * G2: Equipped with NVIDIA L4 GPUs for high-efficiency inference and media workloads. * TPU VMs: Built on Google’s custom Tensor Processing Units. These GCP instances are perfect for TensorFlow-based AI training and massive inference jobs. ### Here is a summary of the various instance families, the major instance types, machine types, and use cases ## **How to choose the right GCP Compute Engine type for your needs?** Choosing the right GCP instance helps ensure your application performs well while staying within budget. Here are the key points to consider: ### **Understand your workload** Different workloads demand different configurations. Compute-heavy workloads like simulations, online gaming, or rendering tasks perform best on compute-optimized GCP machine families such as C2, C2D, or H3. If you're running in-memory databases, real-time analytics, or applications like SAP HANA, memory-optimized machines such as M2, M3, or M4 are better suited. ### **Leverage custom machine types** If your workload doesn’t align with predefined configurations, GCP allows you to create custom VMs. You can select specific combinations of vCPUs and memory, helping you with GCP cost optimization by avoiding overprovisioning. This flexibility is especially useful for unique applications that don’t fit neatly into standard instance types. ### **Plan for scalability** If your application usage fluctuates, plan for how it will scale. Vertical scaling involves increasing CPU or memory on a single GCP instance, while horizontal scaling adds more instances across your infrastructure. For many businesses, autoscaling policies are an effective way to scale automatically while keeping costs under control. ### **Check regional availability** Not all GCP compute engine types, GPUs, or storage options are available in every GCP region. Choosing a region closer to your end users helps reduce latency and can improve application performance. It also lowers costs related to cross-region data transfer. ### **Evaluate network and storage performance** Some workloads require high network throughput or low-latency access to data. GCP machine families like C3 and A4 offer high-speed networking, which is useful for distributed systems and machine learning tasks. You can also pair VMs with high-performance storage like Hyperdisk or Titanium SSDs to reduce bottlenecks. ### **Watch for hidden costs** Consider factors like Selecting the right Compute Engine VM involves more than picking the cheapest option. It’s about finding the right balance of performance, flexibility, and cost for your specific use case. Running tests before making long-term commitments can help with effective GCP cost optimization. ## **What are the cost considerations for GCP Compute Engine?** GCP instances offer flexible pricing options, but careful planning is key to avoiding unexpected costs. Here’s how to approach it: ### **Choose the right machine family** Your instance choice has a major impact on cost. Start by aligning the GCP machine families with your workload: * General-purpose **(E2, N2):** Ideal for everyday workloads, development, and web hosting. E2 is the most affordable but comes with limited features. N2 offers more performance and is a good next step if E2 isn’t enough. * Memory-optimized **(M2, M3, M4)** : Designed for workloads like in-memory databases or analytics that need large memory allocations. These are more expensive, but offer the best value per GB of memory. * Compute-optimized**(C2, C2D)** : Built for high CPU performance. These tend to be the smarter GCP instance selection decisions when the applications are CPU-heavy and demand consistent speed. These are costlier and not ideal for general tasks. * Accelerator-optimized **(A2, A3)** : Include GPUs or TPUs, perfect for machine learning or video processing. These are premium GCP instances and should be used only when needed. ### **Understand pricing models** GCP offers several pricing models to suit different needs: * Pay-as-you-go: Charges are based on actual usage. There are no commitments, and billing is per second after the first 60 seconds. * Committed Use Discounts (CUDs): Get up to 57% savings when you commit to using specific GCP machine families for 1 or 3 years. Great for predictable workloads. * Spot VMs: Offer big savings, but can be stopped at any time. Best for non-critical tasks like batch processing or CI/CD. * Sustained Use Discounts: Automatically applied when VMs run for a large portion of the month. ### **Other ways to save** Small adjustments can lead to big cost savings: * Use instance schedulers to shut down idle VMs. This is effective for most instances, except E2 shared-core machines that rely on burst credits. * If E2 is not enough, N2 is a budget-friendly upgrade with more flexibility. * For apps that are memory-heavy but don’t need much CPU, replacing general-purpose VMs with smaller memory-optimized ones could be a better choice in terms of GCP cost optimization. ### **Be aware of hidden costs** Costs can add up beyond just the VM price due to multiple reasons. * Moving data between regions or outside of GCP incurs egress fees. * Using GPUs or certain licensed software (like SAP-certified VMs) can increase your bill. * Some discounts don’t apply to all GCP instance types, so double-check before relying on them. ### **Estimate and monitor proactively** * Use the GCP pricing calculator to estimate your total cost before you launch. * Set up budget alerts and monitor usage in real time to stay in control. GCP cost optimization isn’t just about choosing the cheapest VM. It’s about matching the right resources to your workload, selecting the best pricing model, and keeping an eye on usage. Planning well today can prevent future cloud costs from being surprising. ## **Use Case Examples for Choosing the Right GCE VMs** Every workload is different - and so is the virtual machine (VM) that best supports it. Google Compute Engine (GCE) offers a wide range of instance types to match various use cases. Here are five practical examples: * **Web Applications and Development Environments** For basic apps, dev/test setups, or internal tools, general-purpose VMs like E2 or N2 offer cost-efficient performance. These VMs provide a good balance of CPU and memory, ideal for predictable, moderate workloads. * **High-Performance Computing (HPC)** If you're running simulations, scientific computing, or rendering tasks, compute-optimized VMs like C2, C2D, or H3 are the right fit. These machines offer high CPU speeds, large core counts, and fast networking for CPU-intensive operations. * **Machine Learning and AI** ML model training, deep learning, or large inference workloads benefit from accelerator-optimized instances like A2, A3, or G2. These GCP machine families come with powerful NVIDIA GPUs, NVLink support, and high throughput for parallel processing. * **Large-Scale Databases and Analytics** Memory-optimized VMs such as M2, M3, or X4 are well-suited for in-memory databases like SAP HANA, OLAP workloads, or real-time analytics. These offer large memory capacity, high memory bandwidth, and advanced storage options. * **Storage-Intensive Workloads** If your workload relies heavily on disk I/O, like data warehousing, big data processing, or streaming, then storage-optimized instances like D3 or Z3 are ideal. These VMs provide high local SSD throughput and large disk sizes for read/write-heavy tasks. ## **Strategic Selection is Cost-Smart Selection** Choosing the right GCP Compute Engine types (VM) is a technical as well as financial decision. Each instance family in Google Cloud is optimized for specific use cases, and aligning your workload with the right one prevents resource waste and unexpected bills. What happens if you mismatch workloads with the instance types? A low-traffic web server doesn’t need the high compute power of a compute-optimized machine. On the flip side, memory-heavy workloads will struggle on general-purpose VMs. Poor choice of GCP instances can lead to either poor performance or wasted spend. So, how should you select the right instance types? Understand whether your app is CPU-intensive, memory-heavy, or balanced. Then choose a VM family built for that profile. Google Cloud’s range of VM instance types makes this matching easier. This strategic approach helps you scale more efficiently and take advantage of Google Cloud’s pricing models - whether it’s sustained use discounts, committed use discounts, or spot VMs for flexible jobs, thereby Is testing different VM types before committing worthwhile? Yes, experimenting with different instance types can help you uncover the most efficient fit for your workload. Many teams find that even a small change in GCP instance selection leads to noticeable savings and better performance. With options like custom machine types and autoscaling, you can fine-tune your setup for the right balance of power and cost-efficiency. ## **FAQs** * **How can I know which VM type is right for my application?** It depends on your workload. Evaluate CPU, memory, storage, and networking needs. For best results, benchmark your application using custom or predefined machine types before committing. * * * * **Are spot VMs reliable for production use?** Spot VMs offer significant cost savings but can be terminated at any time. They are not suitable for critical workloads but are great for batch processing, CI/CD, and test environments. * * * * **Can I combine different instance types in my setup?** Yes. Many workloads benefit from a mix of VM types - for example, memory-optimized instances for databases and general-purpose ones for app servers. * * * * **What tools can I use to estimate VM pricing?** Google Cloud provides a Pricing Calculator to estimate costs based on region, machine type, and usage. Tools like CloudKeeper can offer additional insights and cost-saving recommendations. * * * * **How do I monitor and control GCP VM costs in real-time?** Use Google Cloud Billing, Cost Table Reports, and tools like Cloud Monitoring and * * * * **Can I use the same VM type across dev, test, and production environments?** You can, but it’s better to use smaller, cost-effective instances in dev/test and scale up only in production where performance is critical. * * * * **What’s the difference between Committed Use Discounts (CUD) and Sustained Use Discounts (SUD)?** CUDs require a 1- or 3-year commitment to specific resources in exchange for up to 57% savings. SUDs are automatic discounts applied when eligible VMs run for a significant portion of the month—no commitment needed. * * * * **Which VM instances should I use for GenAI or AI/ML workloads on Google Cloud?** Accelerator-optimized VMs like A2, A3, or G2 are best for machine learning, deep learning, and large-scale inference workloads. They feature powerful NVIDIA GPUs, NVLink, and high network throughput - ideal for training large language models, foundation models, or running high-performance AI and ML workloads efficiently on Google Cloud. ## **Make Smarter Choices for Your Google Cloud Setup with CloudKeeper** Optimizing your cloud setup starts with the right decisions - from selecting the best-fit GCP instance types to As a trusted Google Cloud Resell and Service Partner since 2019, CloudKeeper brings deep expertise to help you scale smarter. Our team of certified Google Cloud experts works closely with businesses to modernize their infrastructure, drive innovation, and deliver savings through smarter GCP cost optimization. With 15+ years of experience and 400+ successful cloud transformations, we combine strategic insights with hands-on support to help you understand your requirements, align them with the right GCP machine families, optimize your entire GCP setup and unlock more value from Google Cloud. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 12 12 Table of Contents However, choosing the most appropriate pricing model for a given use case is easier said than done. With multiple pricing models, discount programs, and tiered structures available, the possible combinations can quickly run into the hundreds when used together. That’s what this guide aims to simplify. Instead of offering a one-size-fits-all template, it equips you with the knowledge to choose the right pricing model for your specific service and workload requirements. By the end, you’ll have a clear understanding of GCP pricing models, how to pair them with the right services, and which discounts to use to keep your cloud spend optimized. ## **Why Understanding****Matters** Different GCP pricing models and mechanisms, when applied to the right services, help optimize costs without compromising performance or efficiency. For instance, if a workload is predictable and long-running, you’d opt for Conversely, for short-duration workloads, committing to a longer duration of 1 or 3 years won’t make sense, since their utility doesn't justify the commitment. This ability to pair a service with the right pricing model for maximum efficiency comes from having a solid understanding of GCP pricing models, which we’ll discuss later in the blog. ## **How GCP Pricing Works** When provisioning any service within your GCP infrastructure, you’re likely to expect that you’ll be paying exactly what Google has listed as the price. For example, running an e2-standard-4 In fact, there isn’t a single standard price when you choose a GCP service. Instead, the base price and your final cost depend on multiple factors and are determined based on the following: ### **Resource-based vs usage-based pricing** Resource-based and usage-based pricing are commonly seen in GCP Compute Engine instances. In resource-based pricing, you are charged for individual components of a machine, such as vCPU, RAM, and storage, rather than the entire instance bundle. Discounts like Committed Use Discounts and Sustained Use Discounts apply directly to these resources based on usage patterns. In resource-based pricing, billing happens based on how much of each resource is consumed. For example, if a VM uses 4 vCPUs and 16 GB RAM, you are billed for those exact resources instead of a predefined machine package. Whereas in usage-based pricing, you pay based on the duration and extent of usage of a resource. Similar to on-demand pricing, compute is billed per second (with a minimum of 60 seconds), storage is billed based on the amount of data stored (per GB per month), and network usage is billed based on data transfer (ingress/egress). ### **Difference between Resource-based and Usage-based Pricing:** ### Billing accounts and project hierarchy Every GCP resource sits inside a project, and every project is linked to a billing account. The billing account is where charges accumulate and where you set budgets and payment methods. A single billing account can cover multiple projects, which is useful for organizations that separate environments like production, staging, and development into different projects but want unified billing visibility. Understanding this hierarchy is important for cost allocation because charges in GCP are tracked at the project level, and without a clear project structure, attributing costs to the right team or product becomes difficult. ### **Region-based GCP pricing variations** When you look up the same GCP VM or storage class across two different regions, say us-central1 (Iowa) and asia-southeast1 (Singapore), you'll find the pricing to be different, even for the same service. The difference comes down to operational factors such as: * Data center costs, * Power costs, * Labour cost * Infrastructure overhead, All these vary from region to region. Some regions are also newer or carry higher reliability infrastructure, which is reflected in the price. Here's the n2-standard-4 (4 vCPUs, 16 GB RAM) on-demand pricing across three regions to illustrate the contrast: One thing to bear in mind: if you later decide to move data out of one region to another, there are ### **Currency and tax considerations** GCP bills are generated in USD, which means every customer paying in a local currency is subject to exchange rate fluctuations. GCP does provide some protection here: exchange rates are locked at the beginning of each month, and for select currencies, GCP limits the month-to-month rate change to a maximum of 2%, giving customers a degree of predictability even in volatile currency environments. GCP collects applicable taxes (VAT, GST, etc.) based on your billing address, but your organization remains responsible for tax compliance reporting. Therefore, teams need to factor in applicable local taxes when budgeting for the cloud. ## **What are the GCP Pricing Models** Depending on your workload type, commitment level, and usage patterns, there are multiple GCP pricing models to choose from, each with a different cost-to-flexibility trade-off. Here are the different GCP pricing models available: ### **On-Demand Pricing** On-demand pricing is the default GCP pricing model. You pay for compute, storage, or services as you use them, with no upfront commitment. It's the most flexible option and works well for unpredictable or short-lived workloads. The trade-off is **cost** : on-demand rates are the highest of all GCP pricing models. For teams running consistent workloads without a defined plan, opting for on-demand pricing results in a bill that's much higher than it would be with a commitment-based discount plan. ### **Committed Use Discounts (CUDs)** By committing to a specific resource configuration for 1 or 3 years, you get up to 57% off on general-purpose machine types and up to 70% off on memory-optimized instances compared to on-demand pricing. CUDs are ideal GCP discounts for steady and predictable workloads. The commitment is to spend, instead of a specific instance, which gives teams some flexibility to shift across machine types while retaining the GCP discount. ### **Sustained Use Discounts (SUDs)** Sustained Use Discounts are GCP discounts that apply automatically. When a resource, such as a Virtual Machine, runs for more than 25% of a billing month, GCP monitoring begins applying incremental discounts. The discounts can be up to 30% off the on-demand rate. SUDs are available for most N-series and custom machine types and cannot be combined with CUDs on the same resource. ### **Spot and Preemptible VMs** Spot VMs offer the highest GCP discounts available, up to 91% off the on-demand rate. The trade-off is availability: GCP can reclaim these instances at any time when capacity is needed elsewhere. Preemptible VMs work on a similar model with a maximum lifetime of 24 hours. Both are well-suited for batch jobs, data pipelines, CI/CD runs, and any fault-tolerant workload that can handle interruptions. ### **Custom Machine Types** Custom machine types let you specify the exact number of vCPUs and memory you need, rather than choosing from predefined instance configurations. This directly affects GCP pricing because you're not paying for resources you don't use. A workload that requires 6 vCPUs and 20 GB of RAM no longer needs to be rounded up to the nearest predefined type. Custom configurations are subject to the same GCP discounts as standard machine types. ## **What are GCP Pricing Tiers** The costs you incur while using GCP services depend heavily on factors such as your total usage volume. This is often structured through pricing tiers or specific thresholds. For example, if your usage of a service is below a threshold, such as the first 240,000 vCPU-seconds per month for Cloud Run services, then the Free Tier will apply, and you would pay a lower rate (or nothing at all) Conversely, for the same instance type, such as an n1-standard-1 VM on Compute Engine, if your usage goes above these initial thresholds, you would pay more as you transition into standard paid tiers. ### **Understanding GCP Pricing Tiers** GCP offers pricing tiers, wherein pricing may vary based on usage thresholds, time duration, or a combination of both: * Free usage up to a defined limit (e.g., limited GB, requests, or compute time) * Free for a specific time duration (e.g., 12-month free tier) * Tiered pricing based on increasing usage levels The most common example is the GCP free trial: ### **Internet Egress Pricing (Example)** GCP follows a tiered pricing model for internet egress: ### **Regional Pricing Tiers** GCP pricing also varies by region, categorized into Tier 1 and Tier 2 regions: * Tier 1 regions generally offer lower costs due to scale and infrastructure maturity * Tier 2 regions are priced higher due to factors like data center costs, power, and local demand * The same workload can cost more or less, depending on the region selected ## **GCP Pricing: Service-based Breakdown** GCP pricing is highly variable across different offerings. In fact, it is so variable that GCP discounts apply differently based on the tier, usage, and volume you’ve provisioned. All this goes to show that the list price of a resource is merely an indication, while the final cost depends on several factors. Out of these, we’ve discussed service-based GCP pricing in this section. ### **GCP Compute Engine Pricing** Typically, it's the largest driver of GCP spend. Key pricing points: * **e2-standard-4 (4 vCPUs, 16 GB RAM):** $97.84/month on-demand in us-central1 * **n2-standard-4 (4 vCPUs, 16 GB RAM):** $141.79/month on-demand in us-central1 * Spot VMs of the same type can reduce costs by up to 91% SUDs apply automatically for instances running more than 25% of the month ## **Pricing** There are three components to GKE pricing: **Node pools:** Committed Use Discounts (CUDs) and Sustained Use Discounts (SUDs) apply to the underlying VMs **Autoscaling:** Automatically adjusts the number of nodes based on workload demand, which helps to maintain performance without overprovisioning **Autoscaler costs:** While the autoscaler itself doesn’t incur a separate charge, the cost depends on the underlying Compute Engine resources.GKE adds a cluster management fee of $0.10 per cluster per hour, which is separate from node costs. Google Compute Engine offers similar performance capabilities to Google Kubernetes Engine; however, its setup and pricing differ. You can check out a ### **Cloud Functions and Cloud Run:** Both Cloud Functions and Cloud Run use usage-based GCP pricing: ### **Google Cloud Storage Pricing:** Google Cloud Storage follows a consumption-based pricing model, in which the cost is based solely on the storage capacity of the selected type. A key point to note for storage is that network ingress and egress are calculated outside storage, with ingress generally free and egress chargeable. Therefore, when billing, egress charges show up separately, even though they are associated with the same storage bucket. ### **Big Data & Analytics Pricing:** Big data and analytics offer great utility for a variety of use cases, such as real-time analytics and business intelligence reporting, for which Google offers dedicated services like Pricing models for all these do not follow a single standard rate, since the factors influencing pricing differ across services, with the base pricing model and consumption patterns being the key differences. Here’s how GCP pricing across Big Data and Analytics services works: #### **BigQuery on-demand vs flat-rate reservations:** **** * **Data ingestion:** Data ingestion is free when loading data into BigQuery using batch loads, but streaming inserts are charged per GB of data ingested * **Storage:** Storage in BigQuery is billed separately based on the amount of data stored per month. Long-term storage is 50% cheaper ($0.01/GB vs $0.02/GB in US regions). The 90-day clock resets on any modification (INSERT, UPDATE, DELETE, MERGE). #### **Databases** * **Cloud SQL:** Priced by instance type, storage, and egress. A db-n1-standard-1 in us-central1 runs at approximately $50/month before storage costs. * **Cloud Spanner:** ~$0.90 per node per hour for multi-region configurations; designed for globally distributed workloads where consistency is non-negotiable. * **Firestore:** $0.06 per 100,000 document writes, $0.06 per 100,000 reads, $0.02 per 100,000 deletes, plus $0.18/GB per month for storage. * Backups, I/O operations, and storage all carry separate charges across database services. #### **Networking** GCP pricing for networking follows a clear rule: ingress is free, egress is not. ### **AI/ML services** * **Vertex AI pricing:** * An NVIDIA A100 GPU on a training job runs at approximately $3.67/hour. * Model hosting vs Training: Model hosting is charged per node hour for deployed endpoints. CUDs apply to Vertex AI but offer lower discounts than compute-optimized instances, typically 20-40% off. ## **Billing, Invoicing, and** GCP provides a native set of tools for cost visibility: * **Cloud Billing reports:** Through Cloud Billing reports, teams can see separate project- and service-based cost breakdowns. * **Budget Alerts:** For a set spend or while crossing a threshold, for example, $1,000 or 80% of the budget, you can configure Google Budget Alerts, which can alert you on channels such as email, Pub/Sub, or webhooks. * **Billing Export to BigQuery:** BigQuery, being a data analytics service, allows you to export the raw billing report to it, and you can track the bill in detail. ## **Common Cost Traps and Hidden Charges** Several GCP pricing line items catch teams off guard, and most of them live outside compute. **Egress** is the most common trap. Inter-region transfers, cross-zone VM traffic at $0.01/GB, and internet egress all add up fast at volume. **Idle resources** continue to generate GCP charges even when stopped. Attached persistent disks and reserved static IP addresses keep billing regardless of VM state. **Early deletion from cold storage tiers.** Removing an object from Coldline before 90 days or Archive before 365 days triggers an early deletion fee equivalent to the remaining minimum duration. **Cloud NAT data processing** at $0.045/GB applies to both directions of traffic. GKE clusters pulling container images through Cloud NAT at scale can generate significant charges entirely separate from egress. **BigQuery SELECT * queries.** Scanning full tables instead of specific columns is one of the fastest ways to generate unexpected GCP costs in analytics workloads. GCP monitoring of these specific SKUs through the billing export to BigQuery is the most reliable way to surface them before they compound. You can learn more about ## **Forecasting, Budgeting, and Financial Planning** Getting GCP pricing under control requires building a forecasting and budgeting practice around how your organization actually uses GCP. * **Start with the billing export to BigQuery:** It's free to enable and gives you a complete, queryable record of every cost by service, project, region, and SKU. * **Set budget alerts at multiple thresholds:** 50%, 80%, and 100% are some examples of potential intervals you can set. GCP monitoring at these intervals gives teams time to investigate before a bill shock incident. * **Run a 30-day GCP monitoring analysis:** Before committing to a discount program, you should first gauge your usage because simply committing to a spend and then underutilizing that resource makes the discount counterproductive, and you could end up spending more than the reduced costs that come with CUD. * **Layer your GCP discounts.** Use resource-based CUDs for your most stable, long-running workloads. Use Flexible CUDs for workloads that shift across machine families or regions. ## **To Sum Up** GCP pricing is tricky to navigate, but essential to understand for GCP monitoring needs to be maintained continuously, as it provides real-time visibility into your infrastructure and helps determine whether the pricing model you’ve chosen is actually the right fit for the use case. Need GCP experts? Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents The Google Cloud Platform is currently the third largest cloud provider, and it is on track for continued growth. The report suggests that in 2024, Google Cloud's market share has grown to 28% among the top 10 cloud providers and reached 11% of the global cloud market. Furthermore, Deutsche Bank analysts also affirm that Google’s cloud business is growing impressively, predicting that Google’s cloud revenue could reach $38 billion by 2025. As your business grows and you scale on the Google Cloud Platform, managing it can get tricky. You might need to add more services and resources, which can make things complicated. That's why it's important to have a good GCP cost management system in place to manage your cloud environment. In this blog, we'll talk about the essential GCP tools for ## **What is Google Cloud Cost Optimization?** Google Cloud Cost Optimization is a continuous practice of identifying and eliminating unnecessary cloud spending while also ensuring that your applications perform optimally. This involves a combination of proactive measures and ## **The native Google Cloud Cost Optimization Tools** Google Cloud offers a suite of useful tools to help you with your cloud cost optimization objectives. Let’s discuss the top native GCP tools: ## **1. Google Cloud Billing Reports** The GCP tool provides detailed reports on your spending which allows you to pinpoint cost drivers, identify unexpected spikes, and understand where your money is actually going. It’s a great GCP tool to provide answers to questions such as: * Where is the majority of my Google cloud spending occurring? * Which GCP services are the biggest cost drivers? * Are there any unexpected cost spikes? * Are we spending more or less than the last billing period? **Features of Google Cloud Billing Reports:** * Granular cost breakdowns by service, region, and project. * Customizable reports to analyze spending trends and identify anomalies. * Get forecasted spending based on historical usage patterns. Image Source: ## **2. Google Cloud Pricing Calculator** As a cost or ROI continuous business, before you launch a new project or scale existing workloads, you would usually like to get an idea of how much a specific deployment costs. Or maybe what are the pricing options for different services and configurations? This GCP tool provides great help in estimating the cost of various GCP services based on your specific business/ project needs. You can experiment with various configurations, compare pricing plans, and choose the best-suited plan for your business. This proactive approach saves you from unexpected charges by planning in advance, and your projects do not exceed their budgets. **Features of Google Cloud Pricing Calculator:** * Allows you to estimate costs for Compute Engine, Cloud Storage, BigQuery, and other GCP services. * Helps with budgeting and cost forecasting. * Also helps to choose the best storage locations. Thus, organizations using BigQuery can significantly benefit from this GCP tool. ## **3. Google Cloud Recommender** This GCP Tool works like your personal cloud optimization advisor. It analyzes your GCP usage patterns and provides personalized recommendations for improving resource utilization, rightsizing instances, optimizing storage, and more. These recommendations are based on Google Cloud Platform's best practices. **Features of Google Cloud Recommender:** * It identifies underutilized resources and rightsizing options. * It provides tailored recommendations based on your specific usage patterns. * It can be integrated with Google Cloud FinOps Hub to provide better cloud cost-saving recommendations. Image Source: ## **4. Google Cloud Cost Table** The Google Cost Table presents an overview of Stock Keeping Unit (SKU) pricing for Google Cloud services in a concise format. You can compare cloud spending across tiers and configurations using this GCP tool, as it shows the cost in a tabular format. Additionally, you can quickly identify trends, spot anomalies, and gain valuable insights into your overall cloud consumption. You can identify cost outliers, such as unusually expensive projects, and understand the total cost distribution in your organization. **Features of Google Cloud Cost Table:** * Each view displays SKUs and prices specific to the selected Cloud Billing account: 1- A list displaying SKU prices only for the SKUs that have incurred usage. 2- A list displaying prices for all Google Cloud and Google Maps Platform services SKUs. * The report view is customizable and downloadable to CSV for offline analysis. Image Source: ## **5. Google Cloud Committed Use Discounts (CUD) Analysis Report** This GCP tool helps you optimize one of your most crucial resources: Compute Engine instances. It analyzes the CPU and memory utilization of your Google Compute Engine instances, identifying underutilized or overprovisioned resources and giving you an idea if you are fully utilizing the commitments or not. This report enables you to avoid paying for resources that are not being fully utilized, leading to substantial cost savings over time. **Features of Google Cloud CUD Analysis Report:** * It helps analyze the effectiveness of Compute Engine instance utilization. * It helps you avoid paying for resources that are not being fully utilized. ## **6. Google Cloud Operations Suite** Google Cloud Operations Suite is specially designed to help businesses monitor, troubleshoot, and improve the performance of their applications running on Google Cloud. **Features of Cloud Operations Suite:** * **Cloud Monitoring:** You can monitor and visualize performance metrics for primary services including Compute Engine and Kubernetes Engine (GKE) and receive insights on application and resource health in the cloud. * **Cloud Logging:** It collects and stores application and infrastructure logs. You can troubleshoot issues, analyze application behavior, and ensure security and compliance. * **Cloud Trace:** Analyzes application request flows to pinpoint where latencies and performance bottlenecks occur. * **Cloud Debugger:** Allows cloud developers to inspect and debug applications in real-time without impacting performance. Further, it can quickly identify and resolve code-level issues. * **Cloud Profiler:** It constantly monitors application performance to recognize where there is excessive CPU or memory usage, and through this, you can optimize resource use and make applications more efficient. ## **7. GCP Cloud Console** The GCP Cloud Console acts as your central hub of GCP Cost Management. It provides: * **Centralized Management:** You can access and manage all your GCP services from a single console. * **Customizable Dashboard:** Monitor your GCP resources and applications by creating a personalized dashboard with key performance indicators (KPIs) and widgets. * **Resource Management:** This helps you easily create, modify, and delete resources across different GCP services. * **Identity and Access Management (IAM):** Control access to your resources by assigning roles and permissions to users and service accounts. **Features of GCP Cloud Console:** * **Budget Alerts:** Create custom budgets with alerts for cost threshold breaches. * **Detailed Cost Breakdowns:** Analyze expenditures by project, service, or SKU. * **Billing Data Export:** Export billing data to BigQuery for advanced analytics and reporting. While the GCP Cloud Console provides visibility and control, please note that it lacks advanced GCP cost optimization features like automated recommendations and forecasting capabilities. ## **A Quick Snapshot of the GCP Tools** ## **GCP Cost Optimization with CloudKeeper** The native GCP tools are helpful in your GCP cost management journey. However, these GCP tools are standard for all and also have limitations for businesses with complex needs. The native native GCP tools might not always provide the level of granularity, automation, or integration required by some businesses. If you are looking for specialized solutions and platforms with deeper insights and tailored GCP cost optimization strategies, we can help. CloudKeeper is a certified * **CloudKeeper Lens:** A comprehensive Google cloud monitoring platform that provides granular visibility into cloud costs with resource-level breakdowns and tailored recommendations. * **CloudKeeper AZ:** An end-to-end GCP cost optimization solution that offers guaranteed savings, a cloud cost visibility platform, and 24/7 cloud support. * **Google Cloud Architecture Framework Review:** Benchmark your infrastructure against the best practices and design principles created by cloud and FinOps experts. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents ## **Introduction** Enterprises don’t suffer from missing information; they struggle with turning insight into immediate control, yet overspending continues. Industry research highlights the scale of the issue. Gartner estimates that organizations can overspend on cloud infrastructure by as much as 70% without disciplined optimization practices, while the FinOps Foundation reports that nearly 28% of cloud spend is wasted due to idle or misconfigured resources. These findings point to a deeper gap in how AI is beginning to reshape ## **Evolution of AI in FinOps: From Dashboards to Actionable Intelligence** AI in FinOps has evolved in clear stages, each improving insight but not execution. The first phase focused on dashboards and reporting. Organizations gained better transparency into cloud spending and stronger governance, but optimization required manual analysis and coordination across teams. Machine learning then introduced forecasting and anomaly detection. Enterprises could predict overruns and spot inefficiencies earlier, improving financial planning. Still, cost corrections depended on human intervention. While cost intelligence has improved significantly, real-time execution has not, and that is exactly where Agentic AI will make the difference. ## **Generative AI in FinOps Today** Generative AI has already transformed several FinOps workflows. **1. Faster Cost Analysis and Reporting** Modern FinOps teams use AI to convert billing data into actionable insights, enabling: * Automated reporting workflows * Improved financial transparency * Faster executive decision-making **2. Improved Forecasting and Budget Planning** Generative AI analyzes historical usage trends to **3. Advanced Anomaly Detection** AI models can detect unusual cost spikes by monitoring real-time consumption patterns and highlighting misconfigured infrastructure or inefficient resource allocation. **4. The Execution Gap** Despite these advantages, Generative AI remains advisory. FinOps teams still coordinate with engineering teams to implement optimization recommendations. This delay often reduces the financial impact of cost-saving opportunities. ## **Why 2026 Marks a Turning Point for AI in Cloud Cost Management** Several industry trends are driving the transition toward Agentic AI in FinOps * Rising Multi-Cloud Complexity - Enterprises increasingly operate across * AI Workloads Are Increasing Cost Volatility - AI-driven applications are introducing new cost challenges. IDC reports that over 84% of AI infrastructure investments are now cloud-based, significantly increasing spending variability and optimization complexity. * Automation Is Becoming an Enterprise Imperative - McKinsey research indicates organizations implementing AI-powered automation achieve 20–30% efficiency improvements. These gains are accelerating enterprise adoption of autonomous operational models, including cloud cost optimization. ## **How Agentic AI Advances Beyond Generative AI in Cloud FinOps** Agentic AI introduces autonomous intelligence into Cloud FinOps by combining monitoring, decision-making, and execution. **1. Autonomous Cloud Cost Optimization-** Agentic AI continuously evaluates infrastructure performance and automatically implements optimization strategies such as: * Rightsizing compute instances * Eliminating idle workloads * Adjusting storage configurations * Enforcing budget governance policies These capabilities enable continuous cloud optimization strategies. By shifting from reactive cost management to proactive, autonomous optimization, organizations build a self-regulating cloud environment. The result is sustained savings, improved performance, stronger compliance, and reduced operational overhead, all without increasing manual effort from FinOps or engineering teams. **2. Proactive Execution Instead of Reactive Alerts -** Traditional FinOps tools rely on alert-based responses. Agentic AI strengthens automated FinOps governance frameworks by initiating optimization actions immediately, reducing cost leakage. **3. Multi-Agent Collaboration Across FinOps Workflows -** A * Monitoring agents track infrastructure performance * Financial agents manage forecasting and budget alignment * Governance agents enforce compliance policies This collaborative architecture enables seamless coordination across finance, engineering, and operations teams. ## **Key Trends in Agentic AI for FinOps** Agentic AI is more than an upgrade in analytics. It brings autonomous intelligence into cloud cost management, enabling systems to move beyond recommendations and take action. As enterprises look to strengthen 1. **Real-Time Cost Visibility with Automated Remediation** - Enterprises increasingly require real-time monitoring combined with automated remediation to eliminate inefficiencies instantly. 2. **Context-Aware Optimization** - Agentic AI evaluates workload dependencies and business priorities before implementing cost optimization actions, ensuring performance stability. 3. **Integration with Automation Ecosystems** - Agentic AI integrates with: * CI/CD pipelines * Infrastructure-as-Code platforms * Enterprise cloud infrastructure automation strategies ## **Benefits for FinOps Teams** In simple terms, Agentic AI helps FinOps teams move from reviewing costs to actively controlling them. Instead of spending time analyzing reports and coordinating fixes, teams can rely on intelligent systems to monitor usage, prevent waste, and optimize spending continuously. This leads to clear operational and financial gains. * Increased Productivity - Automation reduces manual analysis tasks, allowing teams to focus on strategic governance. * Faster Optimization Cycles - Autonomous execution ensures cost savings are captured in real time. * Stronger Financial Accountability - Continuous monitoring improves budget compliance and financial transparency. * Expanded FinOps Scope - FinOps Foundation research indicates that 65% of organizations now include SaaS cost management and FinOps is expanding into enterprise-wide cost governance. ## **Challenges and Considerations** While Agentic AI offers clear advantages for Cloud FinOps, adoption requires careful planning. Autonomous systems can improve efficiency, but they must operate within defined boundaries. Enterprises need the right governance, skills, and data foundation to ensure AI-driven optimization delivers consistent and reliable outcomes. * Governance of Autonomous AI Actions - Enterprises must define guardrails that ensure AI-driven optimization aligns with compliance and performance objectives. * Workforce Transformation - FinOps professionals must evolve from cost analysts into AI supervisors responsible for monitoring agent behavior. * Data Quality and Integration - Reliable optimization depends on consistent billing and usage data across multi-cloud environments. ## **Preparing for Agentic AI in Your FinOps Strategy** 1. Integrate Agentic AI with Generative AI Workflows - Organizations should begin by leveraging reporting automation and forecasting intelligence before introducing autonomous optimization. This approach supports sustainable AI-driven FinOps transformation frameworks. 2. Establish Governance and Risk Policies - Clear policies and audit mechanisms help maintain control over AI-driven decisions. 3. Choosing the Right Tools and Platforms – LensGPT - Selecting a robust Agentic AI platform is critical to successful adoption. LensGPT combines ## **Agentic AI as the Future of Intelligent FinOps** Cloud investments continue to grow, increasing financial governance complexity. Generative AI has improved cost intelligence, but Agentic AI is redefining how enterprises execute optimization strategies. By enabling: * Autonomous decision-making * Real-time remediation * Multi-agent collaboration Agentic AI is transforming Cloud FinOps into a self-optimizing discipline. Organizations that adopt this approach will gain stronger cost control, improved operational agility, and sustained cloud ROI. As cloud environments grow more complex, autonomous financial governance will become essential for maintaining efficiency and competitive advantage. ## **Frequently Asked Questions** * Q1. What is Agentic AI in FinOps? Agentic AI refers to autonomous AI systems that monitor, analyze, and optimize cloud spending while executing optimization strategies without manual intervention. * Q2. How is Agentic AI different from Generative AI? Generative AI provides cost insights and recommendations, while Agentic AI can execute optimization decisions independently. * Q3. Why is Agentic AI important for Cloud FinOps? It enables continuous optimization, reduces manual workload, and strengthens financial governance across multi-cloud environments. * Q4. How can enterprises adopt Agentic AI? Organizations can begin by integrating Generative AI workflows with autonomous optimization platforms and establishing governance frameworks. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 How 400+ Global Teams Are Solving Cloud Cost Issues & Scaling Efficiently? This blog distills real cloud cost problems, visibility gaps, overprovisioning, storage creep, and AI/Kubernetes sprawl and shows how ownership and CloudKeeper expertise drive lasting savings. By Team CloudKeeper * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 11 11 Table of Contents Creating images, full-length videos, and complete software applications — all through natural, conversational interaction with a digital interface — that’s what Generative AI does. UI/UX designers use it, content creators — both writers and video producers — rely on it, and companies apply it to develop software. These are just a few of its many applications and use cases. So exponential has been the growth of AI that there’s now an industry-level discourse on cost-optimisation strategies for AI workloads running on the cloud. This alone speaks volumes about how widespread the adoption is! If you’ve been on the internet at any point in the last two to three years, chances are you’ve encountered content that wasn’t created by a human but generated by an AI model. Generative AI is the “next big thing” in the technology ecosystem. Hence, you must be up to speed on the key aspects of it. By the end of this blog, you’ll have a solid understanding of the core concepts powering GenAI, current industry trends, key tools built on generative AI, its major industrial applications, and more. ## **What is Generative AI?** Generative AI, also known as Generative Artificial Intelligence, is a technology that enables users to generate a variety of content — such as videos, text, images, sounds, and code snippets — simply by entering instructions into a software interface in a natural, conversational tone. These inputs, in GenAI terminology, are known as “prompts.” Under the hood, these Generative AI systems are initially trained on massive datasets that often contain billions of data points. Once these models are released to the public, their underlying algorithms continue to improve through user interactions and feedback. Sounds just like humans? Well, it’s a tech that’s somewhat close. When a user provides feedback to the model, it learns to either produce more outputs similar to what the user liked or, if the feedback is negative, avoid generating similar outputs the next time. ## **Are Generative AI and AI the Same?** They’re somewhat similar, but it would be wrong to use these two terms interchangeably. This is because GenAI is a subfield or specialisation within the broader and more encompassing domain of Artificial Intelligence. Confusion is common, but Artificial Intelligence, apart from Generative AI, also includes several other major sub-domains such as Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Computer Vision (CV), and Robotics. Each of these subfields focuses on a distinct capability of intelligent systems: * **Machine Learning (ML):** Enables systems to learn and improve from experience without explicit programming automatically. The global ML market is projected to exceed USD 200 billion by 2030, driven by enterprise adoption and automation. * **Deep Learning (DL):** A subset of ML using neural networks with multiple layers to model complex data patterns, widely used in speech recognition and image classification. Models like GPT, BERT, and DALL·E are built on deep learning architectures. * **Natural Language Processing (NLP):** Powers chatbots, voice assistants, and translation tools by enabling machines to understand and generate human language. The NLP market alone is expected to reach USD 80 billion by 2030. * **Computer Vision (CV):** Enables machines to interpret and process visual data from the world — key to applications like facial recognition, autonomous vehicles, and medical imaging. * **Robotics:** Integrates AI with mechanical design and automation, driving advancements in manufacturing, healthcare, and even space exploration. Generative AI, therefore, represents just one — albeit highly transformative — branch within this vast and rapidly evolving ecosystem of Artificial Intelligence. ## **Evolution of Generative AI** Contrary to popular belief, GenAI technology wasn’t invented in the early 2020s. In fact, the groundwork for Generative AI had begun around 2014. That year is often marked as the beginning of modern Generative AI because it was when Generative Adversarial Networks (GANs) architecture developed by Ian Goodfellow and his colleagues at the University of Montreal, were introduced. GANs were the first algorithms to generate somewhat realistic images by pitting two neural networks — a generator and a discriminator — against each other. While the results were basic at best and limited compared to the real-life images of today’s models like ChatGPT, DeepSeek, Claude, or Gemini, they laid the foundation for what was to come. ### **Early Milestones in Generative AI (2014–2022)** * **2014** – GANs by Ian Goodfellow: The first real leap toward AI-generated content, enabling synthetic image generation. * **2015** – Variational Autoencoders (VAEs): Introduced as another generative approach to learn latent representations of data for image and text generation. * **2016** – DeepDream by Google: A convolutional neural network that visualised and generated dream-like images from neural activations. * **2017** – Transformer Architecture (Vaswani et al.): The paper “Attention Is All You Need” introduced the transformer model — the backbone of nearly all modern GenAI tools. * **2018** – GPT (OpenAI): The first Generative Pre-trained Transformer capable of producing coherent paragraphs of human-like text. * **2019** – GPT-2 and BERT: GPT-2 demonstrated scalable text generation; Google’s BERT revolutionised natural language understanding. * **2020** – GPT-3 (175 billion parameters): Set new benchmarks in language generation; laid the groundwork for conversational AI applications. * **2021** – DALL·E and CLIP (OpenAI): Merged text and image modalities, paving the way for prompt-based image generation. * **2022** – Stable Diffusion, Midjourney, ChatGPT: Democratized GenAI for public use; these tools made AI-generated text and imagery mainstream. ### **Development of Generative AI Systems and Tools** As we talked about earlier, you’ve most likely come across GenAI-generated content while using the internet. So it’s important you understand which tools and technologies are behind such creations. #### **The Most Popular Generative AI Tools** * **ChatGPT (OpenAI):** The most well-known text-based conversational AI, capable of generating text, code, summaries, and more. * **Claude (Anthropic):** Focused on safe and context-aware AI-assisted writing and reasoning. * **Gemini (Google DeepMind):** A multimodal AI model integrating text, vision, and reasoning capabilities. * **DeepSeek:** A high-performance LLM focusing on reasoning and accuracy across languages. * **Midjourney:** Specialises in high-quality AI image generation through prompt-based design. * **DALL·E 2 & 3 (OpenAI):** Converts text prompts into highly realistic or creative images. * **Stable Diffusion (Stability AI):** Open-source image generation model allowing local customisation and integration into apps. * **Runway ML:** Offers AI-powered video editing and content generation tools for creators. * **Synthesia:** AI-driven platform for generating videos with digital avatars. ### **Lesser-Known but Equally Important GenAI Systems** These tools might not get the same fanfare as conversational or creative models, but they power key business-critical applications across industries: * **GitHub Copilot (by OpenAI & GitHub): **Assists developers with AI-powered code completion and generation. * **Tabnine:** Code suggestion engine leveraging GenAI for developer productivity. * **Jasper AI:** AI writing assistant for marketing and business content creation. * **Descript:** AI-based tool for audio and video editing via text commands. * **Runway Gen-2:** Advanced video generation from text or still images. * **SynthID (Google DeepMind):** Embeds invisible watermarks in AI-generated images for traceability. * **Hugging Face Transformers:** Provides thousands of pre-trained open-source GenAI models for various tasks. * **Cohere:** Focuses on enterprise-scale language generation and retrieval-augmented generation (RAG) systems. * **Adobe Firefly:** AI-integrated creative suite for generating and editing digital media safely and commercially. * **ElevenLabs:** Industry-leading AI voice generation and cloning platform. These specialised tools often operate behind the scenes but form the backbone of AI-powered automation, content creation, and digital transformation happening across enterprises worldwide. ## **What Role Does Cloud Play in Generative AI ?** To say that the cloud plays a minor role in the story of GenAI would be a gross understatement. This is because Generative AI requires intensive model training — the hardest part of development. And the hardware and processing muscle required for it, is often found only with the cloud providers like GCP, Azure, AWS, etc. Training a single model demands: * Massive computational power * Consistent uptime * High I/O throughput * Scalable storage * Robust networking These are exactly the capabilities that cloud providers deliver. While it’s technically possible to train models on your own systems, the OPEX would be prohibitive for most companies. For many, it could run into millions of dollars, just for infrastructure. The following are the key services provided by cloud providers that power Generative AI: ### **1.AWS SageMaker** Fully managed machine learning service for building, training, and deploying AI/ML models at scale. Tools include: * SageMaker JumpStart – pre-trained models ready to use * SageMaker Studio – end-to-end development environment * SageMaker Training Compiler – optimised GPU/TPU usage Used by enterprises to fine-tune large language models (LLMs) and deploy them efficiently. Learn more about AI and LLMs here. ### **2.Azure OpenAI Service** * Provides secure, scalable access to OpenAI models like GPT-4, DALL·E 3, and Codex. * Enables businesses to integrate advanced language and generative AI into their apps. * Benefits from Azure’s enterprise-grade compliance, data privacy, and regional deployment options. * Bridges the gap between frontier AI research and practical enterprise adoption. ### **3.Google Vertex AI** * Unified platform for developing and managing ML and GenAI models. * Supports training, tuning, and deployment with powerful MLOps features. * Integrates tightly with TPU-based compute instances for large-scale training. * Features like Vertex AI Studio and Generative AI support for Gemini models enable multimodal AI applications — combining text, image, and video generation. It’s surprising because AI workloads are usually associated with runaway costs, but Together, these cloud services provide the computational backbone of modern Generative AI. They enable large-scale training, deployment, and real-time inference — reliably and cost-effectively. ## **What is the Future of Generative AI?** Generative AI has been advancing rapidly. The rapid advancements we’ve witnessed over the past 11 years (2014–2025) were remarkable. While progress has slowed compared to those early exponential gains, the field continues to evolve steadily. Moving forward, Generative AI will further permeate into businesses and continue to advance and grow. Its outputs will become increasingly refined, accurate, and context-aware, enabling more reliable, human-like, and useful interactions across a wide range of applications. ### **Major Innovations on the Horizon** #### **1.Transformer-Based Machine Learning** * Transformers will continue to evolve, enabling even more efficient, scalable, and versatile AI models for text, image, and multimodal generation. * Expect improvements in parameter efficiency, faster training, and reduced resource consumption. #### **2.Multimodal AI** * AI systems will increasingly handle multiple types of data — text, images, video, and audio — in a single model. * This will allow more immersive experiences, such as generating videos from text prompts or creating interactive digital environments. #### **3.Artificial General Intelligence (AGI)** While still a long-term goal, progress toward AGI — AI systems capable of human-level reasoning and learning across domains — will continue. Future models may exhibit broader understanding, context awareness, and reasoning abilities, potentially transforming industries like healthcare, finance, and education. ## **Industry Applications of Generative AI Technology** Generative AI has use cases across the spectrum — from simply drafting your emails to generating complex demonstration or explanation videos. It is this versatility that has led to its adoption across nearly every profession — whether it’s teaching, engineering, content creation, or other creative domains. Some of the popular applications of Generative AI include: * **Content creation:** Articles, blogs, social media posts, marketing copy * **Video and audio generation:** Tutorials, explainer videos, voiceovers * **Software development:** Code generation, debugging assistance, automation scripts * **Design and art:** UI/UX design, digital art, concept generation * **Data analysis and insights** : Automated reports, summaries, predictive models * **Customer support:** AI chatbots, virtual assistants, interactive help systems ## **Why Many Companies Still Hesitate with Generative AI Adoption?** Despite the immense potential and versatility of Generative AI, many companies approach its adoption with caution. While the technology can automate tasks, enhance creativity, and improve efficiency, it also comes with a set of challenges and risks that organisations must carefully consider. From high costs to data privacy concerns, the following factors contribute to why some businesses remain hesitant to fully embrace Generative AI: 1. **Generative AI is expensive:** Training and deploying models require high computational resources, which can lead to significant costs. That’s precisely why the popularity of 2. **Compliance and security concerns:** Companies worry about 3. **Breach of privacy:** The use of personal or proprietary data in training or inference can pose privacy risks if not managed properly. 4. **Hallucination of models:** AI sometimes generates outputs that are plausible-sounding but factually incorrect, which can be risky in critical applications. 5. **Accuracy issues and bias:** AI models can reflect biases in training data and may produce inaccurate or unfair results, which can impact decision-making and credibility. ## **Build Smarter AI: CloudKeeper’s GenAI Launchpad for custom AI Models** It’s about time the allure of AI pulls your organisation in and compels you to build a model of your own. And for that, CloudKeeper offers its The best part? You won’t be forced to break the bank because we, being ## **To Sum Up** If today’s GenAI boom impresses you, the future will absolutely blow your mind.. However, concerns remain regarding the quality of results generated by the tools, as well as the ethical and security issues around individual privacy and the proprietary data that GenAI models might be trained on. Hence, the developers are striving to put in place safeguards while using GenAI tools, such as data anonymisation, access controls, model auditing, and bias monitoring, since, when used well, these can prove to be a valuable asset to the business; else, they can also cause significant harm. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Automate Beyond Limits with n8n: Your Open-Source Automation Powerhouse This blog will help you gain a working understanding of automating with n8n through a practical example and a comparison with Make and Zapier. By Pratik Singh 04 Nov, 2025 5 Common Mistakes to Avoid in AWS Auto Scaling Groups AWS Auto Scaling Groups (ASG) adjust EC2 capacity automatically, maintaining your infrastructure effectively. Learn here the 5 common mistakes you should avoid. By Rachana Kumari, Aditya Sinha 31 Aug, 2023 How to Maximize Cloud Cost Efficiency by Utilizing Automation and Scripting? Automation and scripting can be powerful tools for optimizing cloud costs. This blog post will show you how to use these techniques to significantly reduce your cloud bill and improve resource utilization. By Satyam Negi 25 Aug, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents If you're running applications on For years, teams have wrestled with two problematic approaches: embedding long-lived service account keys in containers or allowing all pods on a node to share the same overly permissive node service account. Both methods violate security best practices and create significant risks. In 2026, there's a better way: Workload Identity Federation for GKE—Google's recommended approach for secure, scalable workload authentication. ## **What is the Workload Identity Federation for GKE?** Workload Identity Federation for GKE allows your This approach leverages IAM Workload Identity Federation, the same technology that enables secure authentication from external environments like AWS and Azure. For GKE specifically, Google manages the entire workload identity pool and provider infrastructure automatically, so you don't need to configure external identity providers. ## **Why Traditional Methods Fall Short** Before diving into how Workload Identity Federation works, it's important to understand why the alternatives are problematic. ### **Service Account Keys: A Ticking Time Bomb** Service account keys are long-lived credentials—some valid for up to 10 years. This creates several critical vulnerabilities: * **Accidental exposure:** Keys embedded in container images, configuration files, or source code can leak through container registries, logs, or version control systems * **Manual rotation burden:** You must implement rotation schedules and securely distribute new keys across your infrastructure * **Large blast radius:** If a key is compromised, an attacker has access until you discover the breach and rotate the key * **Poor auditability:** Tracking which workloads use which keys becomes a nightmare as your infrastructure scales _Point to Remember:_ Service account keys can be valid for up to 10 years and cannot be automatically rotated by Google Cloud. Once created, you are responsible for their entire lifecycle, including secure storage, distribution, and rotation. ### **Node Service Accounts: Over-Privileged by Design** Using the Compute Engine default service account or assigning a service account to an entire node pool means every workload on that node shares the same identity and permissions. This approach: * Violates the principle of least privilege * Makes multi-tenant clusters insecure * Enables privilege escalation attacks * Allows SSRF vulnerabilities in one application to compromise your entire cloud environment In fact, without Workload Identity Federation enabled, any pod can retrieve Google Cloud credentials from the underlying worker node through the metadata server—a serious security gap. While the older metadata concealment feature can mitigate this, Workload Identity Federation is the modern replacement that Google recommends. _Point to Remember:_ Even with Workload Identity Federation enabled on the cluster, if you don't enable it on specific node pools (Standard clusters), those node pools will still allow pods to access node credentials. ## **How Workload Identity Federation Works** Workload Identity Federation operates through an elegant token exchange mechanism that happens transparently to your application. Understanding this flow helps you troubleshoot issues and appreciate the security model. ### **Understanding the Architecture Components** When you enable Workload Identity Federation on a GKE cluster, Google automatically provisions three key components: #### **1. Workload Identity Pool** A fixed-format identity pool _**(PROJECT_ID.svc.id.goog**_) is created for your #### **2. Identity Provider Registration** Your GKE cluster is registered as an identity provider within the workload identity pool, giving it a trusted relationship with Google Cloud IAM. #### **3. GKE Metadata Server** A metadata server runs as a DaemonSet (one pod per Linux node) on every node in your cluster. This server intercepts credential requests from workloads and orchestrates the token exchange. All traffic to this metadata server stays within the VM instance—it never traverses the network. _Point to Remember:_ The GKE metadata server takes a few seconds to start accepting requests on a newly created pod. Therefore, attempts to authenticate using Workload Identity Federation for GKE within the first few seconds of a pod's life might fail. Retrying the call will resolve the problem. ### **The Credential Exchange Flow** When your application requests a Google Cloud API, here's what happens behind the scenes: 1. **Token Request:** Your application uses Application Default Credentials (ADC) to request an access token from what it thinks is the Compute Engine metadata server 2. **Interception:** The GKE metadata server intercepts this request at _**http://metadata.google.internal or 169.254.169.254:80**_ 3. **Kubernetes Authentication:** The metadata server requests a Kubernetes ServiceAccount token (a signed JSON Web Token) from the Kubernetes API server, authenticating itself using mutual TLS with node credentials 4. **Token Exchange:** The metadata server calls Google's Security Token Service to exchange the Kubernetes JWT for a short-lived federated access token (valid for one hour by default) 5. **Optional Impersonation:** If needed, this federated token can be exchanged for an IAM service account token via the Service Account Credentials API 6. **API Access:** Your workload uses the resulting token to access Google Cloud APIs with the permissions granted in IAM policies The beauty of this design is that existing code using Google Cloud client libraries works without modification. Your application code remains unchanged—only the infrastructure configuration differs. ## **Two Configuration Approaches** Workload Identity Federation for GKE supports two configuration patterns, each suited to different scenarios. ### **Approach 1: Direct IAM Principal Identifiers (Recommended)** This modern approach, introduced as part of the 2024 update that renamed the feature to "Workload Identity Federation for GKE," allows you to grant permissions directly to Kubernetes resources using IAM principal identifiers. #### **How It Works Conceptually** * You grant IAM permissions directly to your Kubernetes ServiceAccount using a special principal identifier syntax * The federated token is used directly to access Google Cloud APIs * No Google Cloud IAM service account needed * No annotations on Kubernetes ServiceAccount required #### Principal Identifier Syntax A principal identifier follows this format: You can grant permissions to different scopes: * Specific ServiceAccount by name: _**principal://...subject/ns/NAMESPACE/sa/KSA_NAME**_ * Specific ServiceAccount by UID: **principal://...subject/kubernetes.serviceaccount.uid/SA_UID** * All pods in a namespace: **principalSet://...attribute.namespace/NAMESPACE** * All pods in a cluster: **principalSet://...attribute.cluster_id/CLUSTER_ID** _Point to Remember:_ Use principal (singular) for specific resources like a single ServiceAccount. Use principalSet (plural) for groups of resources like all pods in a namespace or cluster. #### **Key Advantages** * Fewer IAM policy bindings to manage * No need to create Google Cloud service accounts for impersonation * No annotations required on Kubernetes ServiceAccounts * Cleaner, more maintainable infrastructure ### **Approach 2: Service Account Impersonation (Alternative)** When a Google Cloud service doesn't support federated tokens directly, you can configure Kubernetes ServiceAccounts to impersonate IAM service accounts. This method exchanges the federated token for a full IAM service account token. #### **How It Works Conceptually** * You create a Google Cloud IAM service account * You grant that IAM service account permissions to Google Cloud resources * You allow your Kubernetes ServiceAccount to impersonate that IAM service account * The federated token is exchanged for an IAM service account token via the Service Account Credentials API #### **Requirements** * IAM policy binding: Grant _**roles/iam.workloadIdentityUser**_ to allow the Kubernetes ServiceAccount to impersonate the IAM service account * Annotation: Add _**iam.gke.io/gcp-service-account=IAM_SA_NAME@PROJECT_ID.iam.gserviceaccount.com**_ to the Kubernetes ServiceAccount _Point to Remember:_ Both the IAM policy binding AND the annotation are required for service account impersonation. Missing either one will result in authentication failures. #### **When to Use This Approach** * Some Google Cloud services have limitations with federated tokens * You have existing IAM service accounts with complex permission configurations you want to reuse * You need to access resources across While more complex, this method provides compatibility with all Google Cloud services and allows you to leverage existing IAM service account configurations. ### **Which Approach Should You Choose?** Start with Approach 1 (Direct Principal Identifiers) whenever possible—it's simpler and requires less infrastructure. Fall back to Approach 2 (Service Account Impersonation) only when you encounter service limitations or have specific requirements that necessitate it. ## **Step-by-Step Configuration Guide** Let's walk through setting up the Workload Identity Federation using both approaches. ### **Prerequisites** Ensure you have: * GKE cluster (Autopilot or Standard) * _**roles/container.admin**_ and _**roles/iam.serviceAccountAdmin**_ IAM roles * IAM Service Account Credentials API enabled * Understanding of which Google Cloud services your workload will access ### **Enabling Workload Identity Federation** #### **For Autopilot Clusters** Workload Identity Federation is always enabled in Autopilot—no configuration needed at the cluster level. Skip directly to configuring your applications. #### **For Standard Clusters** **Step 1:** Enable at the cluster level **Step 2:** Enable on node pools (new or existing) The _**--workload-metadata=GKE_METADATA**_ flag configures the node pool to use the GKE metadata server. Point to Remember: Updating existing node pools to enable Workload Identity Federation requires recreating the nodes. Plan for a maintenance window or use node pool migration strategies to avoid downtime. ### **Configuring Application Access (Approach 1: Direct Principal Identifiers)** **Step 1:** Create a Kubernetes namespace and ServiceAccount **Step 2:** Grant IAM permissions using a principal identifier This example grants the Storage Object Viewer role to all pods using the _**my-app-sa**_ ServiceAccount in the _**my-app-namespace**_ namespace. **Step 3:** Deploy your workload with the ServiceAccount **Step 4:** Verify the configuration Deploy the pod and test access: If configured correctly, you'll see a list of objects in the bucket. ### **Configuring Application Access (Approach 2: Service Account Impersonation)** **Step 1:** Create Kubernetes namespace and ServiceAccount (same as Approach 1) **Step 2:** Create an IAM service account **Step 3:** Grant the IAM service account permissions to Google Cloud resources **Step 4:** Allow the Kubernetes ServiceAccount to impersonate the IAM service account **Step 5:** Annotate the Kubernetes ServiceAccount **Step 6:** Deploy your workload (same pod YAML as Approach 1) ## **Understanding Identity Sameness** Point to Remember: If workloads in multiple clusters share the same workload identity pool (because they're in the same Google Cloud project), and they have the same namespace and ServiceAccount names, IAM treats them as identical identities. For example, if you have a _**backend**_ namespace with a _**database-reader**_ ServiceAccount in both Cluster A and Cluster B within the same project, any IAM permissions granted to that principal apply to both clusters. ## **Key Limitations to Know** 1. Cannot rename workload identity pool: The pool name (_**PROJECT_ID.svc.id.goog**_) is fixed 2. Host network pods: Pods with _**hostNetwork: true**_ cannot use Workload Identity Federation (exception: Cloud Storage FUSE CSI driver in GKE 1.33.3-gke.1226000+) 3. Built-in agents: GKE's logging and monitoring agents continue using the node's service account 4. VPC Service Controls: Federated identities don't support cross-perimeter access control; use service account impersonation instead 5. Service account identifier format: By default returns _**SERVICEACCOUNT_NAME.svc.id.goog**_ format; add annotation _**iam.gke.io/return-principal-id-as-email: "true"**_ for IAM principal identifier format ## **Summary** Workload Identity Federation for GKE eliminates the security risks and operational burden of managing service account keys while providing fine-grained, per-workload access control to Google Cloud services. By leveraging short-lived, automatically rotated tokens and native Kubernetes identities, you can build a secure, scalable infrastructure that adheres to modern security best practices. Whether you're migrating from service account keys or deploying new workloads, implementing Workload Identity Federation should be a top priority. Start with the direct principal identifier approach for simplicity, fall back to service account impersonation only when necessary, and always follow the principle of least privilege. Your GKE workloads—and your security team—will thank you. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Aman is a seasoned DevOps professional skilled in cloud infrastructure, CI/CD pipelines, containerization, and automation. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Picking your compute model on the In this blog, we provide a detailed comparison between the two across multiple parameters and benchmarks such as cost, management overhead, scaling, security, and more, so you can choose the service that actually holds up as your workloads grow. ## **What Is Google Compute Engine (GCE)?** GCE is Google Cloud's IaaS offering. You provision virtual machines, pick your OS, configure CPU and memory, attach storage, and manage everything from there. It behaves like a traditional server, without the hardware rack and the datacenter lease. When opting for Google Compute Engine, you have end-to-end ownership and control over the environment, which means installing only the services you need, choosing the OS you want, and maintaining lifecycle control at the machine level. ### **Key features:** * Linux and Windows Virtual Machines across predefined and custom machine types * Per-second billing with automatic sustained-use discounts * * * GPU and TPU support for ML training and inference * Persistent disk storage that survives VM restarts * Free tier: one e2-micro VM up to 720 hours/month in select regions GCE handles web servers, APIs, data pipelines, CI/CD runners, lift-and-shift migrations, and any application that needs full OS-level control to run properly. ## **What Is Google Kubernetes Engine (GKE)?** GKE is Google Cloud’s managed Kubernetes platform. It handles the orchestration of containerized applications, including deployment, scaling, networking, storage, and health monitoring, across clusters of nodes. Google manages the control plane, while you define workloads and configure clusters, and GKE runs in two modes. Standard mode provides node-level control, whereas Autopilot fully manages the nodes for you, with billing based on pods instead of virtual machines. ### **Key features:** * Fully managed Kubernetes control plane with 99.95% SLA on regional clusters * Cluster and node autoscaling tied to actual workload demand * Vertical Pod Autoscaler for automated resource right-sizing * Spot Pods (Autopilot) and Spot VMs (Standard) for significant cost reduction * Native integration with * GKE Anthos for hybrid and multi-cloud cluster management * Free tier: $74.40/month in credits per billing account, covering one zonal Standard or Autopilot cluster GKE is the preferred choice for cloud-native architectures, microservices, stateless applications, data processing pipelines, and ML workloads that need dynamic scaling. Through GCE, you get complete control of the virtual environment. Whereas Google Kubernetes Engine runs the application inside pods that are scheduled across a managed cluster with a higher degree of abstraction. The difference, which might seem trivial at a broader level, becomes much more evident as it starts in the workflow and across engineering operations, and most importantly, in the bill spent. That’s why GCE gives more granular flexibility and rewards it. GKE trades some of that granularity for automated cluster management, self-healing deployments, and built-in orchestration that would take months to build manually on VMs. At the scaling layer, Google Compute Engine provisions new VMs through managed instance groups based on custom metrics. Google Kubernetes Engine scales at two levels simultaneously. Pods expand horizontally within existing nodes, then nodes are provisioned when pods can no longer be scheduled. That layered response is faster and more granular when demand spikes suddenly. ## **Google Compute Engine vs Google Kubernetes Engine Cost Breakdown** ### **GCE pricing:** * Billed per second based on machine type, vCPU, memory, region, and storage * Sustained-use discounts kick in automatically when VMs run 25%+ of a month * Committed Use Discounts: up to 57% off for 1-3 year commitments * Preemptible/Spot VMs: 60-91% off standard pricing for interruptible workloads * No base management fee. You pay for resources provisioned, nothing more ### **GKE pricing:** * Cluster management fee: $0.10/hour per cluster (~$72/month) for regional/multi-zonal clusters * Free tier credit: $74.40/month covers one zonal Standard or Autopilot cluster * Standard mode: pay for underlying GCE VMs (nodes), starting from $0.0449/hour * Autopilot mode: billed per pod on CPU, memory, and storage requested—no VM management * Persistent Disk: $0.04/GB/month (standard), $0.17/GB/month (SSD) * Committed Use Discounts apply to compute inside GKE clusters **Where GCE wins on cost:** Long-running, predictable workloads where sustained-use discounts compound month after month. Applications needing custom machine configurations are unavailable in standard Kubernetes node pools. Teams running fewer, larger workloads that don't need container orchestration layered on top. **Where GKE wins on cost:** Variable workloads with unpredictable traffic patterns. Autopilot's pay-per-pod model means idle node capacity leads to a reduced spend. Applications running many small containers where bin-packing across nodes increases overall utilization. Using preemptible VMs, GKE can impact nearly 70% cost savings over GCE for containerized workloads. One nuance worth understanding on Autopilot: per-pod pricing runs roughly 191% higher than Standard node compute on paper. The savings surface through efficiency gains, if workloads consume less than 53.5% of a Standard node's CPU and 50% of memory, Autopilot eliminates idle node spend and comes out ahead. Regardless of the choice, oversized nodes, idle resources, and unoptimized workloads pile up costs fast on both platforms. ## **Operational Overhead: What You're Actually Signing Up For** On GCE, you own the full stack. OS updates, security patches, monitoring agents, logging configurations, network rules, and instance lifecycle management become the responsibilities of your cloud team. Engineers with strong Linux administration backgrounds handle this well. For teams without that depth, the management burden drains engineering time that could go toward shipping product. On GKE, Google handles control plane management, version upgrades, and cluster repairs. Your team focuses on workload configurations, resource requests, namespace policies, and application deployments. Kubernetes, being a challenging skill to master in itself, adds to the complexity because YAML-heavy configurations, pod scheduling behavior, container networking quirks, and persistent storage management all require real expertise to get right. ### **Performance, Scaling, and Reliability** GCE performs well for**stable workloads** where resource requirements are known and predictable. Vertical scaling requires VM downtime. Horizontal scaling through managed instance groups works, but VM boot times of 1-3 minutes mean demand spikes take a few minutes to absorb. GKE handles **dynamic workloads** better. Pods start in seconds. The Cluster Autoscaler provisions new nodes automatically when existing capacity fills. Vertical Pod Autoscaler adjusts resource requests without manual work. For applications where traffic spikes are common, such as consumer apps, SaaS platforms, and e-commerce platforms, GKE can often respond more efficiently than GCE because it supports built-in High availability on GCE requires deliberate configuration. Regional managed instance groups, health checks, and load balancers must be explicitly set up to achieve redundancy across zones. GKE provides strong high-availability capabilities by default at the workload level through pod replication and automatic rescheduling when a node fails. Additionally, regional GKE clusters can distribute control plane and workloads across multiple zones, although multi-zone or regional configuration must still be explicitly enabled. ### **Security and Governance** GCE security operates at the VM level. Firewall rules, GKE provides Kubernetes RBAC for fine-grained access control at namespace, resource, and operation levels. Workload Identity ties Kubernetes service accounts to Google Cloud IAM, removing the need to manage credentials inside containers entirely. Node auto-upgrade keeps underlying VMs patched without manual coordination. Both support VPC Service Controls, Cloud Audit Logs, and Binary Authorization for supply chain security. GKE adds pod security policies, network policies between namespaces, and container image vulnerability scanning through Artifact Registry. For teams operating under compliance requirements, GKE’s centralized governance, config management for policy enforcement, pod-level audit logging, and namespace-based isolation make demonstrating control to auditors considerably more straightforward. ## **When Google Compute Engine Makes More Sense** **Legacy or monolithic applications** that weren't built for containers. Containerizing a monolith typically requires significant refactoring. Running it on VMs first gets you into the cloud immediately, without the architectural overhaul. **Stateful workloads with complex storage requirements.** Databases, file servers, and applications that tightly couple process state to the underlying OS run more naturally on VMs, where filesystem and storage configuration stay fully in your control. **Maximum infrastructure control**. Specialized hardware configurations, specific kernel versions, custom networking setups, or OS-level performance tuning that Kubernetes simply can't accommodate. **Teams without Kubernetes experience** who need to ship now without a steep ramp. GCE runs on skills already in the building. ## **When Google Kubernetes Engine Makes More Sense** **Cloud-native microservices** are independent services that need independent scaling, deployment, and lifecycle management. Kubernetes was built exactly for this pattern. **Frequent deployment cycles.** Rolling updates, canary deployments, and blue-green strategies are native Kubernetes concepts that GKE automates without additional tooling. **Traffic that moves unpredictably.** Consumer apps, SaaS platforms, and e-commerce workloads benefit from GKE's sub-minute scaling response in ways that managed instance groups on GCE can't match. **Teams already comfortable with Kubernetes** who can operate the platform without a prolonged learning investment. ## **Common Mistakes Cloud Teams Make** **Picking GKE for workloads that don't need it.** A three-tier web app running fine on two GCE VMs doesn't justify Kubernetes overhead. Adding complexity without a corresponding benefit is just a waste. **Underestimating Kubernetes operations.** Debugging pod scheduling failures, container networking problems, and persistent volume issues requires real depth. Teams that underestimate this often spend weeks troubleshooting problems that wouldn't exist at all on GCE. **Skipping resource requests in GKE.** Containers without proper CPU and memory requests get scheduled onto nodes badly, leading to bloated clusters and wasted spend. Estimated wasted cloud spend hit 27% industry-wide in 2025 and is only projected to rise in 2026, and Kubernetes resource misconfiguration is a significant contributor. **Ignoring node pool rightsizing.** Running uniform large node types across workloads with varying resource profiles leaves significant idle capacity on the table. ## **Decision Framework: How to Choose Between GCE and GKE** In order to decide which service to choose, try answering these six questions first. 1. **Are your workloads containerized?** No → start with GCE. Yes, or planning to containerize → GKE. 2. **Does your team know Kubernetes?** No experience → GCE or invest in training first. Experienced team → GKE. 3. **How variable is your traffic?** Predictable and steady → GCE with committed use discounts. Highly variable → GKE Autopilot. 4. **Do services need to scale independently?** Yes → GKE. Single application → GCE. 5. **Are there compliance requirements for workload isolation?** Complex multi-tenant governance → GKE. Straightforward → either. 6. **What's your timeline?** Ship quickly with minimal ramp-up → GCE. Building toward cloud-native maturity → GKE. ## **Conclusion: Google Compute Engine or Google Kubernetes Engine?** **To sum up in one line:** Choose GCE for predictable, VM-based workloads requiring full control, and choose GKE for containerized, scalable applications that demand automation and rapid growth. GCE suits teams running traditional workloads, needing full infrastructure control, or operating without Kubernetes depth. Reliable, flexible, and cost-effective for predictable compute on long-running VMs. GKE suits teams running containerized applications, building out microservices, or needing fast autoscaling across workloads that don't stay predictable. The operational investment pays back through deployment velocity, scaling efficiency, and infrastructure automation that compound over time. Many mature organizations run both GCE for legacy systems and databases, and GKE for modern application services. Starting on GCE and migrating containerizable workloads to GKE incrementally as expertise grows is a common and sensible path. Whichever direction you go, cost control needs attention from day one. Both GCE and GKE generate sprawl through idle resources, oversized instances, and configurations that made sense initially but never got revisited. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents When you run Without proper handling, workloads can be cut off mid-flight, leading to failed requests, degraded performance, or even downtime. Enter the AWS Node Termination Handler (NTH), an open-source project by AWS that makes ## **What is the AWS Node Termination Handler?** The AWS Node Termination Handler is a Kubernetes component that listens for AWS events like instance terminations or maintenance notices and ensures the node is **cordoned** and **drained** before shutdown. That means: * No new Pods get scheduled on the node that’s going down. * Existing Pods get time to exit gracefully. * The cluster remains stable even during infrastructure churn. **Note:** NTH is mainly needed for**self-managed node groups** (Amazon EC2-based). For **Amazon EKS managed node groups** , AWS automatically handles some termination behaviors, though NTH can still enhance observability and handling in edge cases. NTH listens for AWS events such as: * * Scheduled Maintenance Events * Instance Rebalance Recommendations * ASG Scale-In Terminations * Instance State-Change Notifications ## **How AWS Node Termination Handler Works** NTH can run in two distinct modes, and you must choose only one at a time. ### **1. IMDS Processor Mode (DaemonSet)** This mode runs as a **DaemonSet** , with one pod on every node. It polls the Instance Metadata Service (IMDS) for signals like: * Spot Interruption Notices * Scheduled Maintenance Events * Instance Rebalance Recommendations #### **Pros** * Lightweight (no extra AWS infra required) * Perfect for Spot-heavy or test clusters #### **Limitations** * Does not support ASG lifecycle hooks or lifecycle heartbeats * Can’t handle Amazon EC2 instance state-change notifications #### Installation ### **2. Queue Processor Mode (Deployment)** This mode runs as a **centralized Deployment** that consumes events from Amazon EventBridge → Amazon SQS. It listens for all the events IMDS mode handles, plus a few more: * ASG Lifecycle Hooks (_EC2_INSTANCE_TERMINATING_) * Amazon EC2 Instance State-Change Notifications * Spot Interruptions & Rebalance Recommendations #### **Pros** * Full coverage of all event types * Supports lifecycle heartbeats, extending termination time up to 48 hours * Ideal for production clusters #### **Requirements** * Amazon EventBridge rules * SQS queue * IAM permissions via IRSA (or Kiam/Kube2iam) * ASG lifecycle hook setup #### Installation **Best practice:** If _**enableSqsTerminationDraining**_**=true** , do not enable IMDS draining in the same release. Choose one mode only. ## **Lifecycle Heartbeats - Buying More Time** When ASG scale-in starts, the instance moves into the _**Terminating:Wait state**_. Normally, you get a few minutes (default 300s) before it’s forcibly terminated. In Queue mode, NTH can send lifecycle heartbeats (RecordLifecycleActionHeartbeat) that keep the instance in WAIT state, up to 48 hours total, letting long-running Pods finish cleanly. **Use cases:** * Batch jobs or ML workloads that need longer drain times * Stateful workloads that require controlled rebalance across AZs **Note:** Heartbeat interval must be shorter than the ASG lifecycle hook timeout. If heartbeats stop or draining completes, AWS proceeds with termination. ## **Prerequisites for Queue Mode** ### **Minimal IAM Policy Example:** ## **Observability with Prometheus** NTH emits metrics you can scrape using **Prometheus Operator** : * actions_total → number of node drains performed * events_error_total → errors while processing AWS events Depending on your deployment: * Use PodMonitor for IMDS mode * Use ServiceMonitor for Queue mode Also, NTH can emit **Kubernetes Events** (PreDrain, NodeDraining, PostDrain) for audit visibility. ## **Best Practices for Using AWS Node Termination Handler** * **Pick your mode wisely** **a)** Use Queue mode for production or mixed node groups (ASG hooks + Spot). **b)** Use IMDS mode for lightweight Spot clusters or dev environments. * **Protect workloads** **a)** Define PodDisruptionBudgets (PDBs). **b)** Give pods time with a sensible terminationGracePeriodSeconds (60s+). **c)** Ensure drains don’t deadlock due to strict PDBs. * **Monitor and alert** **a)** Use Prometheus + Grafana dashboards. **b)** Monitor EventBridge and SQS for dropped messages. * **Don’t double-enable modes** **a)** Running both IMDS and Queue at once causes unpredictable behavior. ## **Testing Amazon Node Termination Handler** Let’s validate your setup: 1. Pick an instance in your Amazon EKS cluster. 2. Terminate it manually: _**aws ec2 terminate-instances --instance-ids i-xxxxxxxxxxxxxxxxx**_ 3. Watch the node cordon and drain: _**kubectl describe node | grep -i cordon**_ _**kubectl get pods -A -o wide | grep **_ 4. Check events and logs: _**kubectl get events -A --field-selector reason=PreDrain**_ _**kubectl logs -n kube-system -l app=aws-node-termination-handler**_ 5. You should see: **a)** Node cordoned **b)** Pods draining gracefully **c)** Termination completed cleanly ## **Troubleshooting Quick Notes** ## **Conclusion** Running Kubernetes on AWS means dealing with ephemeral infrastructure. By default, Amazon EC2 interruptions are abrupt — but with AWS Node Termination Handler, you can make them graceful and predictable. * **IMDS Mode -** lightweight, simple, good for Spot use cases. * **Queue Processor Mode** - production-grade, full-featured, heartbeat-powered. If you’re running Amazon EC2 Spot Instances, using Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Aamir has hands-on experience across AWS, Kubernetes, Terraform, Docker, and Python, with a strong foundation in cloud infrastructure, automation, and container orchestration. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 The Silent Bottleneck: Avoiding Subnet IP Exhaustion in Amazon EKS A practical guide to avoiding subnet IP exhaustion while scaling an Amazon EKS cluster, covering causes, impact, and prevention strategies. By Manish Negi 27 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Cloud services have become a dominant force in the software industry over the past decade. Cloud computing offers a paradigm shift in data storage and application management by enabling scalability, accessibility, and cost-effectiveness. In today's data-driven world, secure and accessible storage is vital. Once the data is stored in a cloud environment, the businesses are entitled to avail several benefits such as faster information deployment, better collaboration, disaster recovery, and less requirement of management and supervision. As enterprises expand and augment their cloud services, understanding the various Cloud Pricing Models is imperative to ensure that they invest in the one that best aligns with their specific requirements. Proper comprehension of these models can significantly reduce the risk of overspending or underutilization of cloud resources. Thus, it is essential to carefully evaluate the pricing models offered by cloud service providers before making a decision. ## **Importance of Cloud Pricing Model** Cloud pricing models are the foundation of your cloud spending. They determine your cloud expenses and have a significant impact on your business's ability to adapt swiftly to changing business requirements and maintain a cost-effective approach. By selecting the right cloud pricing model, businesses achieve a trifecta of efficiency, agility, and transparency. If you are going for AWS, cloud pricing models offer a powerful toolset for ## **Types of Cloud Pricing Models in Cloud Computing** As businesses and startups increasingly embrace cloud, understanding the intricacies of cloud pricing models becomes paramount. For organizations that prioritize ### **1. Pay-As-You-Go (PAYG) Cloud Pricing Model** **Pros -** This model eliminates the risk of overpaying for unused resources and is useful for short-term or experimental projects. No need for large investments, you only pay for what you use. **Cons -** Changing usage patterns can lead to significant cost fluctuations. It can be tough for businesses to keep track of resource scaling, and they may not even realize it's happening until the monthly bill arrives. **Suitable for -** This cloud pricing model is suitable for businesses with fluctuating needs. It allows them to adapt quickly to growth or dynamic business demands. ### **2. Subscription-Based Cloud Pricing Model** A fixed number of cloud resources are provided in this cloud pricing model for a predetermined monthly or yearly fee. Businesses can choose a suitable package that aligns with their needs at a predictable cost regardless of actual usage. This model is equivalent to a Netflix for cloud - you pay a flat fee for a pre-defined resource package. **Pros -** Fixed costs ensure predictable cloud expenses, simplifying financial planning for your business. This skips the need to have a dedicated team with expertise in predicting cloud usage fluctuations. **Cons -** This model can lead to paying for resources that you may not always use, impacting budget efficiency. Any scale-up requirements would add unprecedented costs. **Suitable for -** The subscription-based cloud pricing model is perfect for businesses with consistent resource requirements. It offers budget predictability and eliminates the worry of fluctuating costs associated with usage-based models. ### **3. Reserved Instance Cloud Pricing Model** This cloud pricing model works like the car lease concept. The Reserved Instances model lets you reserve cloud resources for a predetermined period (1-3 years) at a discounted upfront cost. This model offers significant cloud cost savings for businesses with predictable workloads, guaranteeing capacity and offering substantial cost savings. Different RI options cater to specific needs, like scheduled instances for fixed usage hours. **Pros -** **Cons -** Quickly adjusting resource allocation can be challenging with Reserved Instances. Unused resources during periods of lower usage would impact cost efficiency. The commitment is for a specific instance. **Suitable for -** The RI based cloud pricing model is most appropriate for businesses with predictable usage. ### **4. Spot Pricing Model for Cloud** Spot Instances offer fluctuating prices based on supply and demand, just like the stock market. These are available at a specific time, but the provider may pull back these resources at a notice of just a few minutes resulting in interruptions. **Pros -** Spot instances are available at highly discounted prices. **Cons -** Spot Instances are unsuitable for applications requiring guaranteed uptime, like databases or e-commerce platforms. **Suitable for -** Spot Instances are ideal for flexible workloads being used for non-essential tasks that can tolerate interruptions. They can be used for non-critical workloads like batch processing or simulations. ### **5. AWS Savings Plan** This cloud pricing model offers discounted rates compared to on-demand pricing in exchange for a one or three-year commitment, just like Reserved Instances. However, savings plans are more flexible as your commitment is based on total hourly spending across various AWS services, not specific instances. When you AWS Savings Plans are of three types, offering flexibility to match your needs: * Compute Savings Plans: These plans offer the broadest coverage, applying discounted rates to your entire bill across various compute services like EC2, Lambda, and Fargate. * EC2 Savings Plans: Tailored specifically for Amazon EC2 instances, these plans provide targeted discounts if your workloads primarily rely on EC2. * SageMaker Savings Plans: Focus is solely on reducing costs for your SageMaker usage, ideal in case of heavy utilization of SageMaker for machine learning tasks. **Pros -** The commitment is for a specific dollar amount resulting in cost advantage and more flexibility. **Cons -** Savings Plans cannot be sold in the AWS Marketplace. Once the plan is purchased, the buyer is locked into that commitment. The terms of the commitment cannot be altered once the purchase has been made. **Suitable for -** The savings plans are suitable for organizations with flexible resource requirements and predictable usage that can be committed in advance. ## **Maximize the Cloud Cost Savings** By demystifying cloud pricing models, businesses can effectively navigate the cloud landscape. CloudKeeper offers a perfect guide to choosing the right cloud pricing model for maximizing AWS cost savings. With CloudKeeper as your end-to-end Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Today, businesses increasingly rely on multi-cloud environments, focusing on digital business and the new processes required of enterprise IT to improve flexibility and scalability. This new agility adds complexity and makes it more difficult to control high cloud costs. This blog examines the growing importance of FinOps practices and cloud cost solutions in a multi-cloud context. According to IDC’s Intelligent CloudOps Survey (October 2023), over 98% of large enterprises have two or more public cloud providers, while the median across surveyed companies is three different hyperscalers. Figure 1 shows the breakdown of the number of active public cloud vendors used by large enterprises in Q4 2023, with all companies using at least one public cloud company. The digital transformation many enterprises have undertaken in the last few years has pushed them to select cloud providers that were the quickest at addressing the specific project. Over time, this meant using ## **Q. How many public cloud providers or hyperscalers is your organization currently utilizing for IT Infrastructure as a Service or Platform as a Service or other external server hosting?** **FIGURE 1: Number of Public Cloud Providers in Use** n = 104 (Source: FinOps can address the increasing costs of multi-cloud complexity. Since 2019, companies have been embracing the growing practice of FinOps, and IDC found that 74% of enterprises have begun their FinOps journey. It is not too late for companies that haven’t yet started. They can begin their journey today with the FinOps best practices discussed here that can help them. Figure 2 demonstrates the incredible growth of enterprise FinOps adoption in just a few years. __ FinOps involves disparate teams collaborating to create a culture of accountability to find cloud savings and improve return on investment in a multi-cloud environment. The FinOps team is typically led by a full-time FinOps practitioner, who regularly brings together the other (part-time) team members to review current cloud spending and future cloud investments. Maturity levels vary greatly between companies, with many taking a pre-crawl (planning), crawl, walk, and run approach to FinOps. This continual improvement approach allows celebrating easy wins such as cost savings with leadership as more advanced capabilities, including full charge-back and unit economics, are added as the team matures. ## **Q. Does your organization have a FinOps team and processes in place today?** **FIGURE 2: FinOps Adoption** ​​​​​​n = 104 (Source: A FinOps team can't mature or deliver quick wins without a **1. Select appropriate cloud cost management tools:** Selecting a tool that supports all of a company’s current and planned public cloud providers is an obvious goal. Teams risk blind spots if their tool doesn't support all cloud providers that the enterprise uses. Enterprises should select a tool or platform specifically designed for multi-cloud cost management, where all the dashboards and pricing recommendations are visible centrally. FinOps teams can then collaborate and hold one another accountable for implementing all agreed recommendations. **2. Automate resource optimization:** Some tools support only cost and pricing analysis. Selecting one that can optimize cloud resources across multiple clouds is also important. Many tools will continuously monitor resource utilization and the right size of a company’s cloud infrastructure as needed. FinOps teams should seek continual improvement by reviewing resources and proper configuration. Enterprises can downsize over-provisioned resources or decommission abandoned virtual servers. This approach can save significant costs without impacting the user experience. **3. Automate cost allocation with tagging:** FinOps teams must agree on and implement a robust **4. Monitor costs and budgeting:** Many modern cloud cost tools can **5. Use Reserved Instances (RI) and savings plans:** FinOps teams should secure long-term savings with cloud providers. Vendor negotiation requires a team approach, and the FinOps team must accurately forecast demand. Once forecasts are created, teams should match this demand with RIs or savings plans to maximize their cloud savings. Proper forecasting and commitment to these arrangements require business owners, procurement, and legal groups to collaborate to lock in substantial cost reductions for predictable workloads. **6. Schedule shutdowns and tuning:** Not all workloads are in use 24/7, especially in development and disaster recovery environments. IT operations teams working with FinOps groups can automate the shutting down or scaling of resources during off-peak times. Scheduled shutdowns during non-business hours or reduced resources based on workloads can prevent unnecessary spending on idle resources. However, finding idle resources across multiple clouds is difficult, so an accurate inventory and central dashboard of all resources are essential. **7. Use spot instances available in many public clouds:** Using spot instances or preemptible VMs for less critical workloads or applications load-balanced across both spot instances and RIs can save enterprises 70%–80% compared to on-demand pricing. IT automation is essential when using spot instances to maintain resilience and bring the environment back to full capacity if the hyperscaler pulls the spot resources. Many modern applications, such as container-based Kubernetes, can support this architecture. **8. Training and awareness:** Educating FinOps teams about the latest best practices, including obtaining By ## **Finding the Right FinOps Partner** The importance of Cloud FinOps in organizations is on the rise. However, with varying FinOps maturity across organizations, it is essential to find the appropriate partner who can help adopt FinOps, optimize cloud costs as well as help you track these metrics. CloudKeeper is a Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents With the many advantages of cloud computing come the challenges of managing costs effectively. Discovering the sweet spot for **cloud cost savings** is a bit like finding the perfect recipe. At its essence, it boils down to two key ingredients - First, understand your business's cloud consumption needs, and second, choose the right rate when buying from your cloud provider. Although your consumption requirements may fluctuate as your business grows, there is always a considerable opportunity to fine-tune your cloud rates. This involves considering elements like reserved instances, commitment discounts, and savings plans provided by your cloud service provider. These factors hold significant potential to influence and reduce your overall cloud expenditure, providing a recipe for cost-effective and efficient cloud management. **Cloud rate optimization** , hence becomes crucial for ensuring that your organization maximizes the benefits of the cloud without overspending. ## **The Pitfalls of Ignoring Rate and Usage Balance** Without effective Cloud Rate Optimization, businesses face significant challenges: 1. **Budget Overruns:** Exceeding budgetary limits can lead to unexpected expenses, impacting financial stability and strategic resource allocation. 2. **Inefficient Resource Utilization:** Failure to optimize cloud rates results in over-provisioning or under-provisioning, causing unnecessary costs or performance issues. 3. **Limited Strategic Value:** Neglecting optimization hinders businesses from maximizing strategic value, impacting operational excellence and ROI alignment with broader business objectives. ## **Prerequisites for Seamless Cloud Rate Optimization** Now that you recognize the critical importance of Cloud Rate optimization for your organization, to seamlessly align financial goals with business objectives, you must consider the following prerequisites as you work for cloud cost optimization: 1. **Start with a Clear Understanding of Your Cloud Usage:** Begin your cloud rate optimization journey by gaining a 2. **Benchmarking and Comparative Analysis:** Regularly benchmark your cloud usage against industry standards and perform comparative analysis. This helps you stay informed about the latest trends and technologies, ensuring your optimization strategies remain effective and competitive. 3. **Collaboration and Communication:** Foster collaboration between IT, finance, and operations teams to align cloud strategies with broader business objectives. Maintain open communication to address any changes in requirements or priorities that may impact optimization efforts. 4. **Flexibility and Scalability:** Prioritize cloud solutions that offer flexibility and scalability. Choose services that allow 5. **Utilize Automation Tools:** Leverage automation tools to ## **Potential Cost Savings and Key Strategies** The achievable cost savings through **Cloud Rate Optimization** depend on factors such as business size, nature, specific cloud services, and the effectiveness of optimization strategies. Businesses commonly report savings as high as 25% of their entire cloud spend after implementing robust optimization strategies. Key Strategies for Cloud Rate Optimization: 1. **Right-sizing Resources:** Make sure you choose the appropriate instance types and sizes based on your actual workload needs. By aligning your resources with actual requirements, you prevent over-provisioning, ensuring that you only pay for the computing power and storage you truly need. Regularly review and adjust resource configurations to match evolving workload demands. 2. **Utilize Reserved Instances or commitment Plans:** Reserved Instances or Reserved Virtual Machine Instances offer a cost-effective solution for workloads with predictable usage patterns. By committing to a specific instance type and term, businesses can 3. **Implement Auto-scaling Policies:** Auto-scaling allows your infrastructure to dynamically adjust to changing demand. During peak usage, additional resources are automatically provisioned, ensuring optimal performance. Similarly, during periods of lower demand, excess resources are scaled down, preventing unnecessary costs. Using auto-scaling you can 4. **Leverage Spot Instances for Non-Critical Workloads:** For workloads that can tolerate interruptions, consider using spot instances. Spot instances allow you to take advantage of spare capacity at a significantly lower cost compared to on-demand instances. While not suitable for all scenarios, incorporating spot instances can yield substantial savings for certain non-critical workloads. 5. **Optimize Data Transfer Costs:** Minimize 6. **Optimize Data Storage:** Efficient data storage management is integral to cloud cost optimization. Evaluate your data storage needs and choose appropriate storage classes based on access frequency. Consider archiving infrequently accessed data to lower-cost storage options, thereby reducing overall storage costs. 7. **Regularly Review and Delete Unused Resources:** Frequently review your cloud environment and identify unused or obsolete resources. Whether it's unattached storage volumes, idle virtual machines, or outdated snapshots, removing these redundant elements can contribute significantly to cloud cost optimization. Implementing a regular cleanup routine ensures that you only pay for resources that actively contribute to your operations. 8. **Monitor and Analyze Your Costs Continuously:** Establish a robust cloud cost monitoring strategy to keep track of your expenses in real time. Leverage cloud provider tools or third-party like 9. **Educate Your Team on Cost Awareness:** Promote a culture of cloud cost awareness within your organization. Provide training and resources to your team members to make informed decisions regarding resource utilization. Encourage the adoption of best practices for cloud cost optimization, making it a collective effort. 10. **Third-Party FinOps Solutions:** Leverage * **Seamless Process:** Initiate a straightforward billing change to CloudKeeper, and a dedicated team of certified FinOps experts takes charge of optimizing your cloud rates. * **Maximum Efficiency:** CloudKeeper ensures maximum efficiency and cost-effectiveness, simplifying your cloud cost optimization process. Its capabilities in Rate Optimization has been validated by leading analyst firms. Effective **cloud rate optimization** involves a combination of strategic planning, continuous monitoring, and informed decision-making. As you embark on the cloud rate optimization journey, focus on strategically maximizing the value derived from cloud investments. This guide not only provides the recipe for cloud cost reduction but also emphasizes enhancing operational efficiency, fostering continuous improvement, and aligning cloud strategies with broader business objectives. By applying these strategies, your organization will be able to confidently navigate the dynamic landscape of cloud expenditure for a future-proofed, cost-effective cloud infrastructure. _today if you need assistance with the process of cloud rate optimization or would like to learn more about how CloudKeeper can help._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Imagine you're hosting a party, and the number of guests can vary. Vertical scaling is like renting a bigger venue to accommodate more people. It involves increasing the capacity of the existing space, like moving to a larger hall with more capacity. On the other hand, horizontal scaling is akin to hiring additional rooms in the same-sized venue. Instead of enlarging the existing space, you add more identical spaces to handle the increasing number of guests. Each room operates independently, contributing to the overall capacity and ensuring a smooth flow of the party. In AWS terms, vertical scaling means increasing the size of a single server (more CPU, RAM, etc.), while horizontal scaling involves adding more servers to distribute the load across multiple machines. Let’s understand more about horizontal vs vertical scaling. ## **Scaling in AWS - Types and Differences** Scaling in AWS refers to the ability to dynamically adjust the resources of your application or system to accommodate changes in demand, ensuring optimal performance, cost efficiency, and reliability. There are two primary types of scaling: horizontal and vertical scaling. ### **1. Vertical Scaling (Scaling Up)** Vertical scaling involves increasing the capacity of a single resource, such as upgrading a server's CPU, RAM, or storage. **AWS Example:** You might vertically scale an Amazon EC2 instance by choosing a larger instance type with more compute power or memory. ### **2. Horizontal Scaling (Scaling Out)** Horizontal scaling involves adding more instances or resources to your application or system to distribute the load and handle increased demand. **AWS Example:** You might horizontally scale a web application by adding more EC2 instances behind a load balancer, allowing the application to handle a higher number of concurrent users. ## **AWS Services and Resources - Scaled Horizontally, Vertically, or Both** Scaling extends across your cloud applications and infrastructure, encompassing EC2 instances, Elastic Load Balancer (ELB), Relational Database Service (RDS), Lambda functions, DynamoDB, and SQS (Sequence Queue Service). The ability to scale resources, both horizontally and vertically, depends on the specific AWS service and resource in question. To answer the question of horizontal vs vertical scaling, consider the following breakdown of how each mentioned resource can be scaled: In summary, many AWS resources can be horizontally scaled by adding or removing instances, while others, like EC2 instances and RDS databases, can also be vertically scaled by adjusting their configuration. The specific scalability options depend on the nature and design of each service. ## **Scaling Benefits in AWS** The ease for businesses to quickly add to its available pool of cloud resources, during high-demand usage, is what guides the success of the operation in hand. Horizontal and vertical scaling in AWS works towards striking the balance between seamless resource allocation and the performance of the system. Based on a particular use case, whether you choose horizontal scaling or vertical scaling, the following benefits can be enjoyed: * ### **Performance Optimization** Imagine a single-lane highway struggling with traffic. Horizontal scaling in AWS is like adding lanes, allowing more traffic to flow smoothly and preventing delays. The power of horizontal scaling to deliver a consistently delightful experience can be seen during a sudden influx of online shoppers or a peak season for your SaaS platform. * ### **Cloud Cost Efficiency** Think of paying for a gym membership you rarely use. Traditional infrastructure often leads to wasted resources and unnecessary costs. Scaling helps optimize resource usage. By employing vertical scaling, you can upgrade the resources of existing instances instead of maintaining an unnecessarily large infrastructure. This translates to cloud cost optimization, akin to downsizing the infrastructure during slower periods. Furthermore, horizontal scaling empowers you to * ### **Reliability and High Availability** Imagine a single bridge being the only way to cross a river: If it collapses, transportation grinds to a halt. Scaling helps build redundancy and resilience. With horizontal scaling, you create a safety net of redundant instances. If one instance encounters a technical error, like a stumbling acrobat, the others seamlessly pick up the slack, ensuring minimal downtime and uninterrupted performance. This distributed workload model * ### **Elasticity** Think of a rubber band that can stretch and contract: Your AWS infrastructure should be able to adapt to changing demands. AWS Auto Scaling offers a similar level of flexibility. You define your scaling policies, like the magician's pre-planned tricks and Auto Scaling takes care of adjusting resources based on predefined metrics, be it CPU usage or network traffic. This ensures your application thrives amidst sudden market shifts or unexpected growth, allowing you to quickly add resources and scale up your performance in response to the market's applause. Based on the details provided above, you can explore the benefits of horizontal and vertical scaling for your AWS resources and determine the most suitable option for your needs. **Whether you need to adapt to bursts of traffic or optimize costs, there's a scaling option for you. Horizontal scaling adds "rooms" (instances) to handle bigger crowds, while vertical scaling "upgrades" the existing space (resources).** Unsure about the best cloud strategy to adopt? CloudKeeper provides comprehensive Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents **Maximize Your Cloud Efficiency: Introducing Hourly Dashboards in CloudKeeper Lens** It is essential for every organization to manage cloud costs in the long run to optimize the cloud investments made across many verticals within the organization. In order to assist you with more granular-level insights, we are excited to announce the launch of a powerful new feature in Lens, a **Hourly Dashboard**. ## **What Are Hourly Dashboards?** The main purpose of Hourly Dashboards is to provide an hour-by-hour view of the AWS spending, i.e., what is the cost incurred in each hour of the day? This helps ensure that we are able to track our AWS spending with better precision, which in turn gives us the ability to visualize how our expenses fluctuate over the course of the day. We have enabled our customers with such granular insights that actually help them to make rational and informed decisions as far as cloud cost optimization is concerned. ## **Key Features of Hourly Dashboards** * **Hourly Cost Breakdown** The dashboard provides the split of your AWS costs at the hour level, which enables you to identify the hours when the overall cost rises and hours when the overall cost goes down. It is very important for businesses to have this level of detailed view of their AWS spend so that they can take necessary action as per the dynamic nature of the industry. **Track AWS costs at hourly granularity to optimize spending and respond quickly to changes** * **Cost split by Service, Region, Pricing Type, and OS** **Service:** This shows the amount of dollars getting spent on various services such as EC2, S3, RDS, etc. **Region:** Clear understanding of how the AWS spend is distributed across various regions. **Pricing Type:** Here, expenses can be tracked as per the **Operating System:** Track expenses as per the breakdown across various operating systems used in your instances. **Visualize AWS costs by Service, Region, Pricing Type, and OS to gain detailed insights and optimize your spending** * ### **Metrics** **Min, Max, and Average:** To give you a holistic idea of the dips and peaks, hourly dashboards also provide users with minimum, maximum, and average costs for each day as per the selected date range. This enables users to identify patterns and get a good idea of variance in AWS spend. * ### **Heat Map Visualization** One of the most important and unique features of the Hourly Dashboard is the heat map. This is a visual tool that makes the highest and lowest hourly costs more prominent, which makes it easier and quicker to detect the variance and cost anomalies pattern. Users are able to identify and make out the distribution of costs at a glance and, if needed, can dive deeper into the hourly cost data. ## **How Can an Hourly Dashboard be useful for you?** The Hourly Dashboard is an important functionality for customers aiming to gain clarity and transparency over their AWS spending. By facilitating a detailed breakdown of your cost at the hourly level, it assists you in making more informed and smarter decisions about how and when to utilize your AWS instances and overall cloud resources. This is how it can assist users: * **Optimize Resource Usage:** Identify certain durations in the day when cloud resources are not optimally used and make smarter decisions to re-adjust your cloud resources for optimal utilization and ensure cloud cost reduction. * **Optimize Peak Costs:** Find patterns and take note of specific time duration when cloud expenditure is at its peak and find ways to cut down those costs by implementing certain methods, which can * **Set Accurate Budgets:** Utilize the average cost information displayed in the Hourly Dashboard to establish more accurate budgets for your cloud usage. * **Enhance Forecasting:** using the detailed hourly data, you can * **Improved Cost Transparency:** Customers get a clear view of AWS spend segregated at the hourly level, which enables them to understand the variations in the spend pattern during the entire day. * **Strategic resource planning:** Many systems have time-bound usage, i.e., at certain hours of the day the usage would be higher as compared to the rest of the hours, hence, hourly dashboards can help in planning the deployment of resources accordingly. * **Increased Accountability:** Detailed reports can be created by the customers based on the hourly level cost, which increases the accountability of the stakeholders as far as optimal spending is concerned. * **Anamoly Detection:** Heatmap is one such feature that can help in ## **Get Started with Hourly Dashboards in CloudKeeper Lens** CloudKeeper’s aim is to enable its customers with powerful functionalities and AWS cost monitoring tools that are required to have control and a close eye on AWS cloud spend; this enables them to save a lot of costs in the long run and We have added the below hourly dashboards that would help you better manage and keep track of your AWS cloud spending on a daily and hourly basis so that you can * Compute * RDS * ElastiCache * Redshift * OpenSearch Excited to start taking control of your AWS spend and optimize costs? Get onboarded on Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Product Manager Harsh is a distinguished Cloud Expert with an extensive background in product management. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Cloud cost problems rarely start with billing. They start with scale, speed, and complexity. As organizations grow, ship faster, and adopt data-heavy and AI-driven workloads, cloud environments become harder to govern, harder to predict, and easier to waste money in. Looking across CloudKeeper’s customer case studies, clear patterns of failure and recovery emerge. The most successful organizations didn’t just “optimize cost.” They fixed deeper operational, architectural, and This article groups real-world results by problem area, not by company. ## Problem Area 1: “We Don’t Know Where Our Cloud Money Is Going” This is the most common and the most dangerous problem: lack of ### Pattern Observed Organizations at scale often had: * No SKU-level or service-level visibility * No way to attribute cost to teams or products * No reliable forecasting or budgeting model * Billing data that arrived too late and too aggregated to act on ### How teams approached similar issues? **_Eshopbox_** Eshopbox (GCP) was running a complex, high-scale e-commerce operations platform and struggled with: * Excess spending and underutilized resources * No visibility into service-level consumption * Poor cost tracking and forecasting After implementing structured cost governance and real-time service-level visibility, they achieved ₹1M+ cumulative savings and regained predictability over spend. **_RevSure_** RevSure (GCP) had fragmented infrastructure, unclear cost drivers, and manual incident handling. By implementing unified cost attribution and resource-level right-sizing across BigQuery and Google Compute Engine, they achieved ₹1M+ in cumulative savings while improving operational resilience. **_ZenduIT_** ZenduIT (GCP) had no SKU-level chargeback and major blind spots across IoT/video workloads. After implementing SKU-level billing visibility and storage governance, they achieved ~$1,800/month in savings and predictable storage + egress costs. ### Core Lesson You cannot optimize what you cannot explain. Every successful optimization journey started with cost visibility, not optimization. ## Problem Area 2: “Our Infrastructure Is Stable, But Way Over-Provisioned” This is the silent budget killer: systems that work fine, but are sized for a peak that no longer exists. ### Pattern Observed Common symptoms: * Oversized EC2, RDS, Compute Engine * Underutilized clusters and disks * Logging and data pipelines generating uncontrolled spend * Compute and storage running far above actual demand ### How teams approached similar issues? **_eLocal_** eLocal (AWS) was: * Overpaying due to conservative RI/SP management * Lacking visibility and rightsizing discipline By fixing compute sizing, storage, and load balancer inefficiencies, they achieved: * 10% immediate savings * Another 15% through rightsizing and tuning * Total impact: ~25% AWS cost reduction **_RippleHire_** RippleHire (GCP) had: * GKE instability with 12,000+ pending pods * Disk saturation and autoscaling failures * No pod/node-level cost visibility After stabilizing GKE and rightsizing SQL, logging, and compute, they achieved: * $4,400+ monthly savings * Stable clusters and predictable autoscaling ### Core Lesson Overprovisioning is not safety. It’s unmanaged risk- financial and operational. ## Problem Area 3: “Our Storage & Data Architecture Is Quietly Bleeding Money” Storage and data transfer costs don’t spike- they creep. ### Pattern Observed * Unclear retention policies * Unpredictable egress costs * Uncontrolled data ingestion pipelines * No lifecycle governance ### How teams approached similar issues? **_ZenduIT_** ZenduIT had: * Uncertainty around GCS retention, egress, and tiers * Massive IoT/video ingestion (~165 TB/month) * Vertex AI waste due to poor planning After implementing storage governance and ingestion modeling, they achieved: * Predictable storage & egress costs * ~$1,800/month direct savings * Controlled AI/IoT growth. **_OneAssist_** OneAssist (AWS) was suffering from: * High CDN and data transfer costs with Akamai * Complex multi-domain setup After migrating 25 domains to CloudFront and optimizing caching, they: * Eliminated data transfer costs * Improved performance and reliability * Reduced operational complexity ### Core Lesson Data movement is often more expensive than data storage and far less visible. ## Problem Area 4: “Our Kubernetes or AI Stack Is Scaling Faster Than Our Governance” Modern stacks (GKE, AI, ML, BigQuery, Vertex, Gemini) magnify cost mistakes. ### Pattern Observed * No namespace/pod-level cost visibility * AI APIs and BigQuery queries running without guardrails * Logging and analytics exploding bills * No FinOps model around data workloads ### How teams approached similar issues? **_Nanonets_** Nanonets (GCP AI workloads) had: * No visibility into Gemini API spikes * Expensive Vision API usage patterns * Uncontrolled BigQuery and Compute usage After implementing * Reduced BigQuery & compute costs * Gained real-time dashboards * Established governance for scalable AI workloads ### Core Lesson In modern stacks, cost, reliability, and architecture are inseparable. ## Problem Area 5: “We Scale Fast, But Operations and Governance Don’t Keep Up” This is not a cost problem. It becomes a cost problem. ### Pattern Observed * Teams depend on external support * Slow incident response * Risky upgrades * No standard governance patterns ### How teams approached similar issues? **_FranConnect_** (AWS MSK + SQS) faced: * Risky MSK upgrade * Inconsistent SQS patterns * Heavy operational dependency After training 60+ engineers and executing a zero-downtime upgrade: * Achieved zero SQS tickets * Reduced dependencies * Improved operational maturity ### Core Lesson Operational maturity is a cost control mechanism. ## Problem Area 6: “We Need to Migrate or Isolate Systems Without Breaking Everything” Migrations are high-risk cost events. ### How teams approached similar issues? **_Loylogic_** Loylogic / Pointspay needed: * Infrastructure isolation * Compliance guarantees * Zero disruption to live systems Through phased migration and strong planning: * Achieved minimal downtime * Improved cost tracking * Improved scalability and governance ## Patterns We See in Teams That Successfully Control Cloud Costs Across all these success stories, the same pattern repeats: The biggest savings came from: * Visibility before optimization * Ownership before enforcement * Governance before scale * Architecture before commitments ## Final Takeaway If your cloud bill feels unpredictable, it’s not a pricing problem. It’s a systems, visibility, and ownership problem. These case studies show that when organizations fix those foundations, cost reduction becomes a side effect of good engineering and good operations not a quarterly firefight. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents Since its introduction in 2009, AWS Reserved Instances (RIs) have been one of the most effective ways to reduce AWS costs. RIs offer discounted hourly usage rates of up to 75%, in exchange for a one or three-year usage commitment. They do not need any re-architecture or refactoring and generate aws cost savings immediately. When organizations gradually attain some level of predictability into how much infrastructure they’ll need, RIs turn out to be the However, RIs do not offer a one-size-fits-all flat discount package and only a few organizations achieve the maximum potential savings from the offering. The discount rates vary depending on the instance type, tenancy, usage term, geographic region, upfront payments you make, your operating system, and the type of RIs (Standard or Convertible) used. All these combinations offer different levels of savings, break-even points, and performance capabilities, making monitoring and optimizing your AWS RI crucial for maximizing ROI. The primary goal of any cloud cost optimization plan should be to minimize the usage costs along with providing the required flexibility for your computing needs. One of the key metrics for measuring the effectiveness of your ## **What is AWS RI Coverage?** AWS Reserved Instances (RI) Coverage reports offer a comprehensive analysis of resource usage across Amazon EC2, Redshift, RDS, OpenSearch, and ElastiCache instances. These reports furnish a detailed breakdown of how many instance hours are covered by RIs, On-Demand spending, and potential savings through increased reservations for all Users can establish coverage targets, visualized on charts with colored indicators, for easy assessment. The reports also feature customizable filters, including availability zones, instance types, and more, facilitating focused analysis. A coverage threshold can be set to identify areas requiring additional reservations. These could be accomplished by using tools like AWS Cost Explorer or AWS Budgets. With daily and monthly charts tracking RI hours over time, AWS RI Coverage reports empower users to optimize ## **Why should you aim for 100% RI Coverage?** A 100% RI Coverage helps in maximizing the advantages of reserved capacity. Maintaining complete coverage ensures that every eligible instance hour benefits from the discounted rates provided by AWS RI pricing, minimizing overall expenditure. It also enhances financial predictability, allowing for better budgeting and resource planning. Additionally, full RI Coverage provides stability to long-term projects and workloads by guaranteeing reserved capacity, avoiding potential disruptions due to insufficient resources. This approach aligns with ## **What strategies can be employed to achieve 100% AWS RI coverage?** Achieving 100% AWS RI coverage demands a comprehensive strategy that combines insightful analysis, strategic planning, and ongoing optimization. Here are key strategies and practices to help organizations attain maximum RI coverage: **Understand your usage patterns** - The first step to achieving 100% RI coverage is to understand your usage patterns. This includes understanding which instance types you use most often, how long you use them, and **Set Coverage Targets** - Establishing coverage targets based on historical usage data is paramount for AWS reserved instance savings. Regularly adjusting these targets ensures alignment with evolving workload demands, fostering adaptability in resource allocation. This strategic approach allows for a more precise and responsive utilization of RIs, optimizing coverage and cost-effectiveness. **Leverage Predictive Analytics** - Harness the power of predictive analytics tools to forecast future resource needs. By leveraging historical data, organizations can anticipate workload fluctuations and proactively optimize RI purchases. This forward-looking strategy ensures that the coverage remains aligned with the evolving demands of the business and the corresponding AWS reserved instances billing, thereby enhancing efficiency. **Implement Automation** - Efficiency is key to achieving comprehensive RI coverage. Explore automation tools to streamline the reservation process. By **Diversify Reservation Types** - A well-rounded coverage strategy involves the strategic combination of Standard and Convertible RIs. Standard RIs provide fixed capacity in specific regions, while AWS Convertible reserved instances offer flexibility by allowing modifications to attributes like instance type. This diversification ensures adaptability to different workload scenarios, enhancing the overall flexibility of the coverage strategy. **Regularly Monitor and Optimize** - **Encourage Collaboration** - Foster collaboration between finance, operations, and development teams to ensure that RI purchasing decisions align with the overall business strategy. This collaborative approach enhances communication and coordination, leading to more effectiveness in AWS cost optimization and strategic coverage planning. ## **What challenges you could face while maximizing AWS RI coverage?** Like every other Cloud FinOps strategy, planning to achieve 100% RI coverage also comes with its challenges. These include - **Accurately forecasting usage patterns** - It can be difficult to accurately forecast your usage patterns, especially if your EC2 reserved instances usage is unpredictable or seasonal. If you underestimate your usage, you may not be able to purchase enough RIs to cover your entire usage. Conversely, if you overestimate your usage, you may have RIs that are not fully utilized, which can lead to wasted spending. **Keeping up with instance type changes** - AWS is constantly introducing new instance types, and existing instance types are often deprecated. This can make it difficult to keep up with the latest instance types and ensure that your **Adapting to evolving workloads** - Dynamic workload changes pose challenges in accurately adapting RI coverage strategies, making it complex to predict future resource needs and the corresponding AWS reserved instances requirements effectively. **Manual processes** - Even a slight involvement of manual AWS RI management processes becomes time-consuming, impeding the agility needed for timely and efficient RI purchases. **Managing RIs across multiple accounts** - If you have multiple AWS accounts, it can be difficult to manage your RIs across all of them. This can lead to situations where you have RIs in one account that need to be fully utilized, while you are paying On-Demand prices for instances in another account, making it difficult to reduce AWS costs. **Avoiding lock-in** - RIs are purchased for a fixed term, and you cannot cancel them without penalty. This can lead to lock-in, which can be a problem for AWS cost savings if your usage patterns change unexpectedly. **Upfront payments for better discounts** - The necessity for upfront payments to secure better discounts on AWS reserved instance costs adds another layer of complexity. Organizations may face financial challenges in committing upfront, affecting their ability to capitalize on more substantial cost savings through upfront payment options. Balancing budget constraints with the desire for enhanced discounts becomes a ## **How to easily achieve 100% AWS RI Coverage using CloudKeeper Auto?** After delving into the best practices and challenges, one might question the feasibility of attaining 100% RI coverage for their AWS infrastructure. However, it is easily achievable with CloudKeeper Auto by your side. CloudKeeper Auto is an AI-powered Fully **on-demand EC2 instances at 3-year RI pricing**. And to make it more convenient for you, this requires **no lock-ins, commitments, or upfront costs** from your side. This makes it easier to have all your EC2 use-cases covered by various AWS reserved instance types, thus achieving a 100% RI coverage. CloudKeeper Auto also offers **guaranteed buyback for unused RIs** , assuring that your RI investments remain risk-free and unused capacity doesn't go to waste. That’s not all! Once you are onboarded to CloudKeeper Auto, you **get complimentary access to CloudKeeper Lens** , our proprietary Additionally, CloudKeeper also offers **free****, backed by a team of 300+ cloud experts**. This will streamline your overall cloud operations, significantly reduce AWS costs, and help in establishing a strong FinOps culture. A screenshot from CloudKeeper Auto showcasing potential AWS Savings ## **Conclusion** RI Coverage is a key metric for your cloud cost management strategy, which enables AWS cost optimization by tracking the percentage of instance hours covered by reservations. This helps in efficient resource allocation and reducing overall AWS costs. Users need to follow certain best practices like understanding the history of instance usage, implementing predictive analytics, and Even though there are certain challenges to achieving this feat, cloud consumers can streamline their AWS RI management and maximize RI coverage with the help of cloud cost optimization solutions like CloudKeeper Auto. These solutions not only help them enhance their RI utilization and coverage but also empower them to establish a strong FinOps culture. _Want to know how much you can save with CloudKeeper Auto, down to the exact percentage?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 AWS Reserved Instances Buying Guide: Common Pitfalls and Essential Considerations Your strategy guide to making informed AWS Reserved Instance (RI) purchases. Know the common mistakes and prioritize essential considerations for maximizing cost-efficiency. By Sushil Chandra 04 Oct, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Amazon Web Services (AWS) offers a wide range of cloud-based services to organizations, including storage, databases, computing power, and more. Although these resources are intended to assist organizations in running their operations in a more cost-effective and efficient manner, if they are not properly managed and optimized, they have the potential to quickly turn into a source of unnecessary complexity and expense. The process of managing and optimizing these resources in order to guarantee that they are being used effectively and economically is known as AWS Resource Optimization. We will discuss the significance of using AWS DevOps tools to effectively automate the resource optimization process. ## **Why Automate AWS Resource Optimization with DevOps Tools?** * It enables organizations to guarantee that their resources are being used productively and cost-effectively without the need for frequent manual intervention. * By automating everyday processes like resource provisioning and deprovisioning, businesses can save time and effort in * It can assist organizations in ensuring compliance with industry standards and legal obligations. Automating security checks, such as ensuring that all resources are appropriately secured and that access is restricted to authorized personnel only. ## **Some AWS Resource Optimization Tools** * **AWS Cost Explorer** is one of the most used AWS cloud cost optimization tools that helps businesses figure out what's costing them money and how to use their resources better. AWS cost explorer resource optimization gives you added advantage of historical and current cost info, plus features like forecasting, budgeting and cost allocation. * **AWS Budgets** lets you set your own AWS cost and usage budgets. With AWS Budgets, you’ll receive real-time notifications when AWS costs or usage exceed your budgeted amounts. * **AWS Trusted** Advisor offers automated, best practice-based, and AWS experience-based recommendations to improve the performance, cost, and security of AWS resources. * **AWS Compute Optimizer** analyzes the usage patterns of AWS compute resources and provides recommendations on how to optimize them. These recommendations include the * **AWS Auto** Scaling enables businesses to automatically increase or decrease the capacity of their AWS resources in response to demand. * **AWS Lambda** is an all-in-one compute service that lets you run code without having to set up or manage servers which is also a crucial part of cloud infrastructure automation. You can run code in real-time or on a set schedule, giving you a highly scalable and cost-effective way to execute code. ## **Effective Automation of AWS Resource Optimization with DevOps Tools:** * **Implement Infrastructure as Code:** Using IaC tools such as AWS CloudFormation or Terraform, businesses can enable cloud infrastructure automation by dynamic resource provisioning and deprovisioning thereby, eliminating the risk of resource outages and saving you money. * **Use Continuous Integration/Continuous Deployment (CI/CD) Tools:** CI/CD tools automate the development, validation, and deployment of software updates. For example, AWS CodePipeline and Jenkins are two AWS DevOps tools that help businesses quickly and easily roll out changes to production, making sure new features get the best possible results from the start. * **Use Monitoring and Alerting Tools:** Real-time monitoring and * **Use AWS Cost Optimization Tools:** Tools such as AWS Trusted Advisor and AWS Cost Explorer offer cost-reduction and resource-efficiency recommendations to help businesses save money and increase productivity. * **Implement Resource Scheduling:** With resource scheduling, businesses can schedule resources based on predefined schedules. This means that resources are used only when they’re needed, ## **Best practices for AWS Resource Optimization** * **Using Automation:** Utilizing AWS infrastructure automation tools in resource management processes, such as resource provisioning and deprovisioning, can help businesses minimize the potential for human error and optimize resource utilization. Additionally, cloud infrastructure automation can facilitate resource scaling, allowing for resource availability when required and cost reduction in periods of low demand. * **Using Reserved Instances:** RIs are AWS cost optimization tools that provide businesses with the ability to commit to a specific level of resource utilization in exchange for reduced pricing. Purchasing reserved instances for recurring resources can result in savings of up to 75% over on-demand pricing. * **Implementing Security Best Practices:** By implementing security best practices such as limiting access to resources and reviewing permissions regularly, unauthorized use can be prevented and security incidents can be minimized, resulting in zero downtime or data breaches. * Using Serverless Technologies: Serverless technologies, * **Optimizing Network Usage:** AWS offers a variety of network optimization tools and services to help businesses improve performance and cut costs. This includes using content delivery networks (CDNs) to improve data transfer speeds, optimizing network traffic routing and peering, and establishing dedicated network connections between AWS and on-premises infrastructure using AWS Direct Connect. * **Using Tags:** Businesses can use AWS tagging to assign metadata to resources, making them easier to identify underutilized or unneeded resources and take action to optimize resource usage and reduce costs. * **Optimizing Storage Usage:** By choosing the right type of storage, optimization, data transfer and DevOps tools for AWS, businesses can delete unused storage resources on a regular basis, utilize object lifecycle policies to manage data retention, reduce storage requirements by using data compression or deduplication. ## **Conclusion:** Automation of AWS resource management through DevOps tools plays an integral role in reducing costs, improving performance, and increasing scalability for businesses. Utilizing tools such as Terraform to automate provisioning, configuring, and managing AWS resources, businesses can quickly and easily optimize their resources based on evolving requirements. By implementing the appropriate automation strategies and tools, as well as various AWS deployment tools, businesses can realize substantial cost savings and improve overall AWS infrastructure performance, while allowing their teams to dedicate more time to more strategic initiatives. _With_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents The cloud is a crucial component in almost all organizations for accelerating business growth, driving innovation, and achieving easy scalability. Yet, like any complex machine, it comes with its own set of components—its “nuts and bolts”—that need careful management to ensure smooth operations. Cloud support plays a vital role here, facilitating seamless operations while ensuring cost efficiency, performance optimization, security oversight, and business continuity planning. Every cloud provider offers a variety of support tiers, each differing in service level agreements (SLAs), access to support engineers, and guidance on application or architecture. For organizations with highly complex cloud infrastructures or mission-critical workloads, a comprehensive support system is essential. Among AWS support services users, AWS enterprise support comes highly recommended, with all bases covered, offering extensive support across their cloud setup. ## **What is AWS Enterprise Support?** AWS support services offer features for all kinds of businesses and infrastructures, ranging from basic billing support to architectural-level guidance. AWS enterprise support pricing makes it the top-tier support package from AWS, which in turn offers extensive, Unlike basic support plans, the AWS enterprise support pricing calls for a significant financial investment, as it’s designed to offer much-needed services for businesses with complex cloud infrastructures. This AWS premium support program offers proactive planning, advisory services, automation tools, and 24/7 expert assistance. Businesses get access to a team of specialized support engineers, facilitated by a dedicated Technical Account Manager (TAM). This level of cloud support is essential for organizations with large infrastructures, complex workloads, and substantial budgets at stake, ensuring streamlined cloud performance without disruptions. ## **AWS Enterprise Support Features** The support plan offers a comprehensive range of features impacting each and every aspect of a cloud infrastructure. The core features include the following - * **Billing and Account Management -** One of the basic support features of the program, this offering makes sure AWS billing and account experts work with you on billing and account inquiries and help implement billing and account best practices, with proactive assistance. * **Designated Technical Account Manager (TAM) -** Businesses get a designated Technical Account Manager (TAM) who acts as a bridge between you and AWS, ensuring you get to leverage the AWS support services to the maximum. An AWS and Cloud expert, the TAM offers proactive support for your AWS setup, gives personalized recommendations, and also assists you with your AWS support services tickets. * **24x7 Technical Support -** One of the major ROIs from the AWS enterprise support cost is the round-the-clock access to AWS support engineers via phone, web, and chat. You can be assured that technical assistance is always available, whether it’s troubleshooting issues or answering service-related questions. You also get an unlimited quota for cases. * **Case Severity / Response Times -** This AWS premium support program provides some of the fastest SLAs and response times in the industry. Here’s how their response times are structured: General guidance: within 24 hours System impaired: within 12 hours Production system impaired: within 4 hours Production system down: within 1 hour Business/mission-critical system down: within 15 minutes * **AWS Service Guidance -** With this feature, you get expert advice on * **Architecture Reviews -** Your architecture is regularly assessed to ensure it aligns with best practices for performance, scalability, and security. AWS also provides a designated Solution Architect as part of your cloud support team, who oversees your architecture and guides you through * **Business Reviews -** Experts from the AWS support services team conduct regular business reviews to assess your cloud usage, identify areas for improvement, and align your cloud strategy with your business objectives. * **Third-party Application Guidance -** AWS enterprise support assists with specific application workloads, fine-tuning them to run efficiently on the cloud. The guidance covers best practices for deployment, configuration, interoperability, troubleshooting, and scaling on AWS infrastructure. * **Infrastructure Event Management -** Offered under the service AWS Countdown, this includes proactive cloud support for major infrastructure events such as large-scale migrations, product launches, or business campaigns that could have peak traffic periods. AWS experts collaborate closely with your technical team to mitigate risks and ensure success. AWS Countdown Premium is available for an additional fee. * **AWS Trusted Advisor Priority -** * **AWS Support Proactive Services -** This service helps you optimize cloud operations, and scale efficiently through workload reviews, best practices workshops, and deep dives. It has two main components: _**Operational Reviews:** Analyzes your infrastructure across_ _OpenSearch, and Kubernetes, and provides tailored recommendations._ _**Workshops & Deep Dives: **AWS experts guide you through best practices on cost optimization, incident management, security, and operational excellence._ * **Self-Service Options -** With AWS enterprise support, customers gain access to several self-service tools that empower them to proactively manage and resolve issues on their own, leveraging powerful services and support APIs. These self-service options include _**AWS Health:** Delivers personalized insights into service events, planned changes, and account notifications, helping you manage your cloud infrastructure better. _ _**AWS Support API:** Allows integration with AWS cloud support features, enabling users to create, manage, and monitor support cases programmatically._ _**AWS Support Automation Workflows:** Provides pre-built runbooks that automate common support tasks, simplifying troubleshooting and issue resolution._ _**AWS Support Apps:** Facilitates seamless access to AWS support services directly within popular chat platforms like Slack and Microsoft Teams._ _**AWS re:Post:** A community-driven platform where users can ask and answer technical questions, gaining insights from AWS experts and peers._ * **Training and Workshops -** AWS enterprise support pricing also includes access to 500 free training credits and access to workshops. Additional credits are available at a 30% discount. These resources help your team build cloud expertise and ### **Additional Offerings** In addition to its core offerings, you get access to premium services for an additional fee on top of the AWS enterprise support cost. These include: * **AWS Incident Detection and Response:** Offers 24x7 custom cloud support for critical workloads with proactive engagement, 5-minute response times, and advanced incident management. * **AWS Managed Services (AMS):** Available on a per-account basis, AMS offers help with managing cloud operations at scale, executing best practices, and providing preventative solutions. * **AWS Countdown Premium:** Provides critical project support from design through post-launch. These ensure smooth execution during key events such as migrations or sales cutovers, * **AWS re: Post Private:** Also available on a per-account basis, it helps teams to collaborate more efficiently, leverage trusted AWS resources, and remove technical roadblocks, enhancing productivity and innovation at scale. ## **How AWS Enterprise Support Pricing Works** AWS enterprise support pricing follows a tiered model, charging a percentage of your monthly AWS usage based on different thresholds. Here's how the pricing works: * 10% of the first $150,000 in monthly AWS charges * 7% of monthly charges between $150,000 and $500,000 * 5% of monthly charges between $500,000 and $1 million * 3% of monthly charges exceeding $1 million If the usage thresholds are not met, this AWS premium support program charges**a minimum monthly fee of $15,000, regardless of your AWS usage**. ## **Factors Influencing AWS Enterprise Support Pricing** AWS enterprise support cost structure applies universally to organizations, regardless of their size, industry, or level of cloud maturity. However, several factors can influence the monthly support cost, such as usage levels, optional services, regional differences, and contract terms. ### **AWS Usage** AWS enterprise support pricing is directly tied to your AWS usage, applying tiered percentages as your cloud costs increase. As a result, the more you use AWS, the more you pay for support, making usage a key driver of support costs. Your usage could be tracked using services like AWS Cost and Usage Reports, Daily usage profile, Data Transfer dashboard, and AWS Pricing Calculator, as well as ### **Contract Terms** AWS enterprise support does not require long-term contracts. But if an organization opts for a longer-term commitment (like an ### **Regional Variations** While AWS enterprise support pricing works consistently worldwide in terms of the tiered structure, AWS usage costs can vary by region due to differences in infrastructure costs, availability zones, and service pricing. As a result, the support fees tied to usage will also reflect these regional variations in AWS pricing. ### **Pricing for Additional Services** Specialized services such as migration assistance, system architecting, or ## **How AWS Enterprise Support Compares to Other Support Plans** AWS support plans vary in terms of their range of service offerings, response times and SLAs, level of personalization, and pricing structure. The below image shows an overview of various support plans from AWS. This image also depicts that AWS enterprise support cost is substantially higher compared to other plans such as the AWS business support cost. ## **When Should You Invest in AWS Enterprise Support** For your investment towards the AWS enterprise support pricing to make sense, the infrastructure should necessitate a comprehensive range of support services. Here are scenarios where this is financially justified: * **Large-Scale or Complex Environments:** If your organization operates extensive and intricate cloud setups, the advanced support services offered can help ensure optimal performance. * **Critical Workloads:** Businesses with mission-critical workloads require constant uptime and quick resolutions. With this cloud support tier, you * **Continuous Support:** Organizations that require continuous support and guidance benefit from AWS enterprise support's comprehensive resources, including 24/7 access to technical support. * **Personalized Support and Guidance:** Companies seeking a customized approach to optimizing their cloud architecture can leverage the expertise of dedicated Account Managers and AWS architects. ## **More Value from AWS Enterprise Support at a Lesser Cost** Many organizations that require premium cloud support services could find the budget as a barrier. They can access the AWS Partner-Led Enterprise Support program, offering the same level of support at a reduced cost. AWS partners within the Solution Provider Program provide As an AWS Premier Consulting Partner, * Guidance on DevOps practices and cloud-native technologies. * Cloud Automation solutions to enhance efficiency and minimize errors. * Continuous monitoring and performance optimization * Support for integrating the latest AWS services. * Consulting and advisory on modernization and cost optimization strategies. _Recommended reading:_ ## **Conclusion** For businesses with complex cloud architectures and mission-critical workloads, signing up for a comprehensive cloud support program is essential. However, the AWS enterprise support cost can be a significant barrier for many organizations. This is where AWS Partner-Led Enterprise Support comes into play. Offered by trusted AWS Partners like CloudKeeper, the Partner-Led Support program delivers the same high level of support and personalization as AWS enterprise support but at a significantly lower, custom-discounted price. CloudKeeper also provides additional benefits such as Businesses that require top-tier support for their cloud workloads can leverage the Partner-led model and achieve maximum ROI on their AWS premium support costs. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Chief Growth & Marketing Officer Naman is a seasoned GTM leader with deep expertise in technology sales, marketing, & strategic planning. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents ## **What is Infrastructure as Code (IaC)?** Infrastructure should be defined in a logical and methodical manner, exactly like application code, according to the DevOps philosophy, which emphasizes treating infrastructure as code . Using tools and procedures similar to those used for application code, this method defines infrastructure as a collection of code scripts or configuration files that are tested, continually integrated, and deployed. As a result, it is possible to track and audit changes over time and manage and deploy infrastructure modifications using a consistent, repeatable approach. With this strategy, communication is enhanced, errors are decreased, and quicker and more frequent releases are possible. IAC's goal is to improve infrastructure management's effectiveness, consistency, and dependability. Infrastructure components can be tested, deployed, and versioned using the same procedures and tools as software code by treating infrastructure as code. As a result, deployments are quicker and more dependable, teamwork is simpler, and swift rollbacks of modifications are possible when necessary. ## **Available options and its features** * **Configuration Management Tools:** Automating the configuration of virtual machines, servers, and other infrastructure components is possible with the help of configuration management solutions, which concentrate on customizing software and systems. Ansible, Puppet, and Chef are a few configuration management tool illustrations. * **Orchestration Tools:** These tools allow you to automate the deployment and configuration of multiple systems or services, and are often used in cloud environments. Examples of IaC tools for orchestration include Terraform and CloudFormation. * **Scripting Languages:** Scripting languages like Python, Ruby, and PowerShell can be used to write code that automates the configuration and deployment of infrastructure components. * **Containerization Tools:** Containerization tools like Docker can be used to package applications and their dependencies into containers, which can be deployed to various environments in a consistent and repeatable manner. * **Infrastructure Provisioning Tools:** These tools automate the process of creating and configuring infrastructure resources, such as virtual machines and networks. Examples of infrastructure provisioning tools include Packer, Vagrant, and OpenStack Heat. ## **Following reasons make IAC Cost Effective** * **Eliminating manual infrastructure setup:** IAC automates the setup of infrastructure, eliminating the need for manual setup, which can be time-consuming, error-prone, and expensive. * **Faster and more efficient deployments:** With IAC, infrastructure can be created and updated much more quickly and efficiently, reducing the time and cost of deployments. * **Reduced risk of errors:** IAC makes it possible to build up infrastructure with greater accuracy and consistency, lowering the possibility of mistakes and the accompanying expenses of downtime and maintenance. * **Improved resource use:** IAC can improve resource use by allowing infrastructure to scale up or down automatically in response to demand, saving money on over-provisioned resources. * **Simplified management and maintenance:** IAC makes it easier to manage and maintain infrastructure over time, reducing the need for manual intervention and enabling AWS cost optimization by reducing costs associated with support and maintenance. ## **Terraform** Terraform is one of the widely used infrastructure as code tools that enables you to create, modify, and version your cloud and on-premises resources in a safe and efficient manner. HashiCorp Terraform is an IaC tool that allows you to define your cloud and on-premises resources using easy-to-read configuration files that you can share and reuse. With Terraform, you can provision and manage your entire infrastructure using a consistent workflow. Terraform can handle various components, from low-level elements such as compute, storage, and networking resources to higher-level ones like DNS entries and SaaS capabilities. Terraform leverages APIs to create and manage resources on cloud platforms and other services. Providers allow Terraform to work with almost any service or platform that has an API interface. As for the core Terraform workflow, it has three stages: **Write:** In this stage, you specify the resources that you want to create or modify, which can span multiple cloud providers and services. For instance, you can define a configuration that deploys an application on virtual machines within a Virtual Private Cloud (VPC) network that has security groups and a load balancer. **Plan:** Terraform generates an execution plan that outlines how it will create, update, or remove the infrastructure based on your configuration and the existing resources. **Apply:** Once you approve the plan, Terraform applies the changes in the correct order, taking into account any dependencies between resources. For example, if you modify the properties of a VPC and change the number of virtual machines within it, Terraform will recreate the VPC before scaling the virtual machines. We can use Terraform for managing our infrastructure, collaborating, tracking our infrastructure, automating changes, and it also helps in AWS cost optimization. Terraform uses a "plan and apply" model to make changes to infrastructure. This allows you to preview the changes that will be made before applying them, reducing the risk of errors and unnecessary changes that can result in unexpected costs. ## **AWS Cloudformation** CloudFormation is an AWS Infrastructure as Code tool that aids in the modeling and configuration of your AWS resources so that you may spend more time concentrating on your AWS-based applications and less time managing those resources. The AWS resources you require (such as Amazon EC2 instances or Amazon RDS DB instances) are listed in a template that you build, and CloudFormation handles the provisioning and configuration of those resources on your behalf. CloudFormation takes care of the creation, configuration, and identification of the dependencies between AWS resources, so you don't have to. ## **Below are the few features of AWS Cloudformation** **Simplify infrastructure management** You might use an Auto Scaling group, an Elastic Load Balancing load balancer, and an Amazon Relational Database Service database instance for a scalable web application that also has a backend database. These resources might be provisioned using each service separately, and after they are made, they would need to be configured to function together. Before you even get your application running, all of these procedures can add complexity and time. Instead, you can create a CloudFormation template or modify an existing one, which describes all your resources and their properties. When you use that template to create a CloudFormation stack, CloudFormation provisions the Auto Scaling group, load balancer, and database for you. After the stack has been successfully created, your AWS resources would be taken up and running. You can delete the stack just as easily, which deletes all the resources in the stack. **Quickly replicate your infrastructure** If your application requires additional availability, you might replicate it in multiple regions so that if one region becomes unavailable, your users can still use your application in other regions. The challenge in replicating your application is that it also requires you to replicate your resources. Not only do you need to record all the resources that your application requires, but you must also provision and configure those resources in each region. Reuse your CloudFormation template to create your resources in a consistent and repeatable manner. To reuse your template for the Infrastructure as Code practice, describe your resources once and then provision the same resources over and over in multiple regions. **Easily control and track changes to your infrastructure** In some cases, you might have underlying resources that you want to upgrade incrementally. For example, you might change to a higher performing instance type in your Auto Scaling launch configuration so that you can reduce the maximum number of instances in your Auto Scaling group. If problems occur after you complete the update, you might need to roll back your infrastructure to the original settings. To do this manually, you not only have to remember which resources were changed, you also have to know what the original settings were. While performing Infrastructure as Code exercise with a CloudFormation template, it describes exactly what resources are provisioned and their settings. Because these templates are text files, you simply track differences in your templates to track changes to your infrastructure, similar to the way developers control revisions to source code. For example, you can use a version control system with your templates so that you know exactly what changes were made, who made them, and when. If at any point you need to reverse changes to your infrastructure, you can use a previous version of your template. With these properties, the CloudFormation service helps ## **AWS CDK** AWS CDK (Cloud Development Kit) is an open-source Infrastructure as Code tool developed by Amazon Web Services (AWS) for defining cloud infrastructure in code and deploying it using AWS CloudFormation. The CDK uses familiar programming languages such as TypeScript, JavaScript, Python, Java, C# and Go, to define AWS resources and infrastructure. This allows developers to leverage their existing coding skills and workflows to create and manage AWS infrastructure as code. The AWS CDK provides a set of high-level object-oriented libraries, known as constructs, which are used to define AWS resources and infrastructure. These constructs are reusable and can be easily shared between projects and teams, allowing developers to create complex infrastructure patterns and architectures with ease. The CDK also includes a CLI tool for building, testing, and deploying AWS infrastructure using AWS CloudFormation. The AWS CDK provides the flexibility and expressive power of a programming language to build highly scalable applications while also * Utilize high-level constructs that offer secure defaults for your AWS resources, allowing you to define more infrastructure with less code. * Employ programming idioms like loops, composition, and inheritance to model your system design using building blocks provided by AWS and other sources. * Store your infrastructure, application code, and configuration all in one place, ensuring that you have a complete, cloud-deployable system at every milestone. * Use software engineering practices like code reviews, unit tests, and source control to make your infrastructure more robust. * Connect your AWS resources (even across stacks) and grant permissions using simple, intent-oriented APIs. * Utilize the power of AWS CloudFormation to deploy infrastructure predictably and repeatedly, with rollback on error. * Share design patterns used for the infrastructure as code frameworks, with teams within your organization or even with the public with ease. ## **Conclusion** In conclusion, the use of Infrastructure as Code (IAC) has become increasingly popular in the world of software development and IT operations. With IAC, teams can manage their infrastructure using code, allowing for greater automation, consistency, and scalability. By adopting IAC, organizations can achieve faster deployments, fewer errors, and improved collaboration between development and operations teams. Additionally, IAC provides better control over the infrastructure, allows for easy tracking of changes and modifications and also helps with cloud cost management. Overall, the benefits of IAC are clear and can greatly improve an organization's software development and IT operations. We can use Terraform, AWS Cloudformation, AWS CDK,etc., for AWS cost optimization along with building the Infrastructure. Streamline your Infrastructure as Code strategies with the help of architectural level guidance from our Cloud and FinOps experts at Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents In cloud deployment, each workload is distinct, and its requirements might change over time. Users may spin up additional cloud resources in a matter of clicks, making enterprise IT infrastructure a dynamic and complicated environment. Furthermore, one can select from a variety of instances, storage kinds, and payment methods, each tailored to particular use cases and resource consumption levels, leading to a complex bill. The traditional cloud computing cost management and budgeting approach doesn’t always work effectively in the current scenario due to multiple limitations. * **Lack of traceability:** Most businesses manage many accounts. Hence, maintaining an * **Unexpected or unexplainable billing:** Buyer autonomy, without any guardrails for cloud financial management, can lead to vastly disparate invoices, unexpected or unexplained expenditures, as well as an increase in compliance and security threats. * **Insufficient cost oversight:** Cost-conscious operations are not always mandated by the traditional cost management approaches. As a result, they frequently prioritize cloud investments exclusively on the basis of IT needs and purchase resources that are not cost-efficient. In fact, businesses that do not have a defined plan for Experts necessitate that organizations come up with cloud cost management tools that Cutting cloud costs isn't the only goal of cloud financial management. It can also boost company agility, operational resilience, and employee productivity. For example, a cloud cost optimization solution for AWS typically covers the following key aspects. * **Organizing and reporting costs:** AWS cost optimization starts with better-than-guess forecasting, planning, and budgeting of the predicted cloud spend. This gives engineers the overview that they need to see the cost impact of their work. * **Hard-coding accountability into cloud billing:** Costs are tracked and * **Flexible forecasting and budgeting in AWS:** Various processes are implemented for dynamic forecasting and budgeting, enabling organizations to stay on top of expenditures as they relate to budgetary constraints. These AWS cost optimization best practices help in determining the efficacy of key FinOps is a paradigm for managing cloud spending, an ecosystem of software and service vendors focusing on specific stages of the cloud lifecycle. FinOps boosts the business value of cloud computing by bringing together technology, business, and finance professionals through a new set of processes. It does so by distilling cloud cost management into the following basic steps: * Monitoring your cloud costs and usage * Analyzing the data to find savings * Taking action to realize the savings Establishing FinOps and cloud cost optimization practices helps **Inform = > Optimize => Operate.** ## **What to look for in cloud cost management tools?** A good cloud cost optimization solution is holistic and brings together cost savings, analytics, and services & support in a seamless manner. These three pillars work together to form the foundation of * **Significant Cost Savings** The solution should reduce your spending on all your cloud consumptions, including on-demand instances, allowing you to save big enough money on your overall cloud payment right away. This cloud cost control should take place without any commitments or lock-ins, without jeopardizing your cloud security, and without any complex adjustments to your setup. * **Cloud Analytics Dashboard** A dashboard provides a complete view of your infrastructure utilization expenses, billing breakdowns, daily cost usage, and more, allowing you to find out possible optimization avenues. These dashboards provide * **Services and Support** Knowing where your cloud spending is going wrong isn't enough; you'll need round-the-clock support to make the necessary adjustments, to get the most out of the data that your dashboard is generating. This is possible with To be cloud-ready, a transparent and effective cloud cost optimization framework necessitates an improvement of the traditional cloud budgeting processes. Rather than just driving down costs, FinOps helps businesses to efficiently leverage AWS and other cloud providers by embracing agility, innovation, and scale, to maximize the value derived from cloud computing. _When it’s about a one-stop solution for all your cloud cost optimization needs, CloudKeeper stands tall as the best choice out there. With a wide array of offerings that help you optimize your entire cloud infrastructure, CloudKeeper delivers_ _, in-depth cost analytics, and expert-backed optimization guidance._ _Want to learn more?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Cloud optimization is one of the hottest topics in today’s era. With more and more companies adopting cloud computing, cloud optimization has become an absolute necessity to stay ahead in the game and enjoy a sustained competitive advantage. A sizable chunk of the IT budget is spent on cloud providers like Amazon Web Services. According to a survey, 82% of companies listed cloud spend management as their biggest challenge. Needless to say, A game-changer in the area of AWS cost optimization is the AWS well-architected review framework. Let us understand what the AWS well-architected review framework is and how it can leapfrog your AWS cost optimization strategies in this article. ## **What is AWS Well-Architected Review?** AWS Well-Architected Reviews are a set of best practices and guidelines provided by Amazon Web Services (AWS) to help businesses build reliable, secure, efficient, and cost-effective systems in the cloud. These reviews offer a comprehensive overview of the AWS infrastructure that can ensure that your systems align with best practices, which in turn can offer the best The AWS Well-Architected Review Framework consists of six pillars: * Operational Excellence * Security * Reliability * Performance Efficiency * Cost Optimization * Sustainability Let us deep dive into each of the above 6 pillars and understand how you can achieve operational proficiency with your AWS FinOps strategy. ## **1. Operational Excellence Pillar** The first of the 6 pillars relates to governance issues and is called the operational excellence pillar. One of the most critical pillars is the ability to run workloads effectively while gaining operational insights, and continuously improving processes and procedures to deliver business value. The processes should thus align with the desired business outcomes and provide an approach to create scalable architectures. The pillar also ensures that the AWS infrastructure can manage changes, respond to events, and automate standard tasks. * Perform operations as code * Make frequent, small, reversible changes * Refine operations procedures frequently * Anticipate failure * Learn from all operational failures ## **2. Security Pillar** The Security pillar of AWS Well-Architected Review pertains to the confidentiality, integrity, and availability of your data and applications in the cloud. A multi-faceted strategy involving network security, access management, data encryption, and threat detection and response is generally helpful in this regard. Another key aspect is Identity and Access Management (IAM), which basically controls who has access to the AWS resources and what actions they can perform. Businesses can avail a number of tools and services to enhance their network security such as Virtual Private Cloud (VPC), Security Groups, and Network Access Control Lists (NACLs). AWS recommends the following seven design principles for strengthening your security pillar: * Implement a strong identity foundation * Enable traceability * Apply security at all layers * Automate security best practices * Protect data in transit and at rest * Keep people away from data * Prepare for security events ## **3. Reliability pillar** To ensure that your AWS infrastructure performs its intended functions consistently is crucial for success in the cloud. Availability, building fault-tolerant systems, automated backups, performance monitoring, failure recovery etc. are a few of AWS’s recommendations. To achieve availability, which is critical in building reliable systems, AWS offers a range of tools and services including Elastic Load Balancing (ELB), Auto Scaling, and Multi-AZ databases etc. Again, for data recovery, AWS offers Amazon S3, Amazon Glacier, and AWS Backup etc., using which businesses can automatically backup their data and applications to secure, durable storage, for recovery later in case the systems fail. ## **4. Performance Efficiency pillar** The performance efficiency pillar recommends using resources efficiently in order to Businesses should be able to automatically scale resources up or down based on demand, reduce idle capacity, and optimize database performance. Tools and services offered by AWS in this regard are EC2 Auto Scaling, AWS Lambda, and Amazon RDS. Optimization is also key to building an efficient cloud system. Tools and services such as There are five principles of best practices, in order to achieve performance efficiency: * Democratize advanced technologies * Go global in minutes * Use serverless architectures * Experiment more often * Consider mechanical sympathy ## **5. Cost optimization pillar** The AWS Well-Architected Framework (WAF) cost optimization pillar provides guidance for reducing the costs of your cloud-based systems and improving ROI. Cost optimization involves reducing waste and improving system efficiencies. AWS recommends the following principles for effective cloud cost savings: * * Adopt a consumption model * Measure overall efficiency * Stop spending money on undifferentiated heavy lifting * AWS recommends a range of best practices, including selecting the right pricing models, optimizing resource utilization, and implementing cost-saving measures, etc. AWS offers a range of tools and services that can help businesses reduce their costs, including EC2 Spot Instances, Reserved Instances, and Savings Plans. Other tools like AWS Trusted Advisor, AWS Cost Explorer, and AWS Budgets allow businesses to monitor their usage and costs, identify areas for optimization, and implement ## **6. Sustainability pillar** The Sustainability pillar of the AWS Well-Architected review Framework enables businesses to consider the broader environmental impact of the AWS operations and how businesses can make a positive impact on the environment, economy, and society. Reducing the carbon footprint is the key goal under this last pillar which also means operating in a wise and efficient manner, ultimately reducing costs. Environmental sustainability is a shared goal between AWS and businesses. The sustainability of the cloud is the responsibility of AWS, which offers effective, shared AWS infrastructure, water management, and renewable energy sources, to name a few. To enable the same, AWS provides the AWS sustainability dashboard. There are six design principles for sustainability in the cloud: * Understand your impact * Establish sustainability goals * Maximize utilization * Anticipate and adopt new, more efficient hardware and software offerings * Use managed services * Reduce the downstream impact of your cloud workloads ## **Get a FREE AWS Well-Architected Review** AWS Well-Architected Review Framework is certainly a stepping stone for establishing consistent practices that mitigate risks and enhance the cloud ROI. It should be considered a key aspect of your FinOps strategy. Businesses can opt for doing a review themselves, however considering the complex nature of the underlying technologies of AWS, _**CloudKeeper is a certified AWS Well-Architected Partner and ranked among the**_ _**. Our team of AWS experts has successfully conducted over 400 successful AWS Well-Architected reviews.**_ _**today and unlock the full potential of AWS architecture with CloudKeeper.**_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents As an experienced AWS specialist transitioning to Azure, I encountered a well-known challenge in a new environment. One notable issue was the high transaction costs in Azure Table Storage. Leveraging my AWS expertise, I developed a custom solution that efficiently cleans Azure Tables while minimizing transaction expenses. In this blog post, I’ll be sharing the insights from my journey. ## **Archive Data Problem** Keeping old data on the cloud can be costly and negatively impact performance. Our long-standing customers are heavily reliant on IoT devices and it deliver data to an Azure Storage Table. With over 10 million entities added daily, this has resulted in massive data collection over time. Significant effects have been observed in terms of costs and performance, especially in terms of transaction costs for data inserts, as a result of the noteworthy fact that this data has been held in the absence of retention restrictions. Optimizing these transaction costs while preserving the system's functioning is now the difficult part. Here are the current costs for the consumer to examine. _Note: The current rate is $0.0045 per GB and $46.0800 per TB_ _Operation and Data transfer price ($0.0004 on 10K Insert Transaction vary by tier_ _**Data storage and transaction pricing for account-specific key encrypted Tables that rely on a key that is scoped to the storage account to be able to configure the customer-managed key for encryption at rest._ _The end goal is to lower the data transaction cost and implement a retention period of 1 month which means older data more than 1 month should be removed._ **Current Total Cost over 1 year** Total Storage Cost: Increasing storage cost by 13.5 USD every month = $1053 USD (13.5 + 27 +...) Total Transaction Cost: $144 USD Grand Total: $165+$144=$309 USD Before diving into the solution, let's briefly review Azure Table Storage. ## **Understanding Azure Table Storage** * It's a cloud-based NoSQL datastore for structured data * Offers a key/attribute store with a schemaless design * Provides fast and cost-effective access for many applications * Ideal for storing flexible datasets like user data, device information, and metadata * Can store terabytes of structured data * Supports authenticated calls from inside and outside the Azure cloud An entity group transaction must meet the following requirements: * Every entity involved in the transaction that is subject to operations needs to have the same PartitionKey value. * In a transaction, an entity can only appear once and can only be the target of one operation. * The transaction's overall payload size cannot exceed 4 MiB, and it can contain up to 100 entities in total. * All entities are subject to the limitations described in ## **Crafting a Custom Solution** We had a discussion with the customer and it turns out they are only doing insertion in the table and not using the data after a month. Also, every insertion in the Azure table was of 2KB and doing single insertions which is costing a lot. So we buffered all rows to be inserted with a batch of 2000 and used Batch write transactions. To delete older data, I leveraged my AWS experience to create a custom solution for removing outdated records from Azure Tables. **Data Identification:** Leveraging timestamps and partition keys to efficiently locate outdated entries. Here’s a snippet of the data identification logic older than 6 months: | from azure.data.tables import TableServiceClient from datetime import datetime, timedelta storage_account_name = "YOUR_ACCOUNT" storage_account_key = "YOUR_KEY" # Create a TableServiceClient using the account name and key connection_string = f"DefaultEndpointsProtocol=https;AccountName={storage_account_name};AccountKey={storage_account_key};TableEndpoint=https://{storage_account_name}.table.core.windows.net/" table_service_client = TableServiceClient.from_connection_string(conn_str=connection_string) # Time threshold (1 Month ago) days_to_keep = 1 threshold_date = datetime.utcnow() - timedelta(days=days_to_keep * 30) threshold_date_str = threshold_date.isoformat() | | --- | **Deletion Strategy:** Using the Azure Python SDK to automate the deletion process, inspired by AWS Boto3. Here's a snippet of the core deletion logic: | # Query entities to delete query_filter_old = f"Timestamp lt datetime'{threshold_date_str}'" old_entities = table_client.query_entities(query_filter=query_filter_old) for entity in old_entities: table_client.delete_entity(entity['PartitionKey'], entity['RowKey']) print(f"Deleted entity: PartitionKey={entity['PartitionKey']}, RowKey={entity['RowKey']} from table '{table_name}'.") | | --- | This automated approach allows for periodic cleanups without manual intervention, keeping tables lean and efficient. Now, the current cost looks like this: _Note: The current rate is 0.0045 per GB and 46.0800 per TB_ __ Operation and Data transfer price (0.075 on 10K Batch Insert Transaction vary by tier) **New Total Cost Over 1 Year** 1. Total Storage Cost: $162 USD 2. Total Transaction Cost: $27 USD Grand Total: $162+$27=$189 USD **Cost Savings** Total cost savings after deleting data every year= $1053 -$162 = $891 Total cost savings from moving to single insertion to batched insertion = $144 - $27 = $117 Total cost savings = ($1053+$144) - ($162 + $27) = $1008 (84.21% cost savings) You would save about 84 % on your bill if you implement a tailored retention solution to remove data on a monthly basis and use batch transactions. With this method, regular data maintenance is possible and storage and transaction costs are greatly reduced. **Benefits of the Custom Solution** * **Cost Reduction:** Reduction in storage expenses for out-of-date entries was significant * **Performance Improvement:** Significant increases in the speed of data retrieval and queries. * **Automation:** The reduction of manual intercept in data management activities. * **Scalability:** The ability to modify the solution to accommodate increasing volumes of data. ## **Conclusion** Regardless of the platform you are using, effective data management is essential to maximizing your cloud's performance and expenses. **1]: Please check the most recent price as it may vary:** Code for Reference: | from azure.data.tables import TableServiceClient from datetime import datetime, timedelta storage_account_name = "YOUR_ACCOUNT" storage_account_key = "YOUR_KEY" # Replace with your actual key # Create a TableServiceClient using the account name and key connection_string = f"DefaultEndpointsProtocol=https;AccountName={storage_account_name};AccountKey={storage_account_key};TableEndpoint=https://{storage_account_name}.table.core.windows.net/" table_service_client = TableServiceClient.from_connection_string(conn_str=connection_string) # Time threshold (6 Month ago) days_to_keep = 6 threshold_date = datetime.utcnow() - timedelta(days=days_to_keep * 30) #threshold_date = datetime.utcnow() - timedelta(hours=days_to_keep) threshold_date_str = threshold_date.isoformat() # Get all tables in the storage account all_tables = table_service_client.list_tables() # Ask user for a table name or to apply to all tables table_name_input = input("Enter a table name to delete old entities or press Enter to apply to all tables: ").strip() # Prepare to collect entities to delete to_delete_entities = [] # Function to process tables def process_table(table_name): table_client = table_service_client.get_table_client(table_name) # Query entities with Timestamp older than the threshold query_filter_old = f"Timestamp lt datetime'{threshold_date_str}'" old_entities = table_client.query_entities(query_filter=query_filter_old) # Collect old entities for review entity_count = sum(1 for _ in old_entities) # Count old entities return entity_count # Process specified table or all tables if table_name_input: entity_count = process_table(table_name_input) table_names = [table_name_input] else: table_names = [table.name for table in all_tables] entity_count = sum(process_table(table_name) for table_name in table_names) # Display the results print(f"\nRetention Period: {days_to_keep} Months") print(f"Number of entities older than {days_to_keep} Months: {entity_count}") # Ask for user confirmation before proceeding with deletion confirm = input("\nDo you want to delete these entities? (yes/no): ").strip().lower() if confirm == 'yes': # Delete old entities for specified or all tables for table_name in table_names: table_client = table_service_client.get_table_client(table_name) # Query entities again to delete them query_filter_old = f"Timestamp lt datetime'{threshold_date_str}'" old_entities = table_client.query_entities(query_filter=query_filter_old) for entity in old_entities: table_client.delete_entity(entity['PartitionKey'], entity['RowKey']) print(f"Deleted entity: PartitionKey={entity['PartitionKey']}, RowKey={entity['RowKey']} from table '{table_name}'.") print("Deletion completed.") else: print("Deletion aborted.") | | --- | Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Software Engineer Varshit is a Senior Software Engineer with over five years of experience in DevOps and Platform Engineering. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents _This article is part of a five-blog series where we share a real client use case — how we reimagined their cloud infrastructure strategy with Crossplane, GitOps, and a hybrid approach with Terraform._ _📖 Missed the first part? Read Blog 1 –_ ## **Bridging from Blog 1** In Blog 1, we shared why we looked beyond Terraform. It worked well for provisioning static infrastructure, but as our platform grew to **50+ microservices with global ambitions** , cracks began to show. * **Ephemeral environments:** Developers needed to spin up infra for every pull request, but Terraform’s state locks made this slow and painful. * **Drift management:** If AWS resources drifted, Terraform wouldn’t act until the next manual apply — a risky delay at scale. Crossplane solved these gaps with its **continuous reconciliation model**. Just like Kubernetes keeps pods aligned with their declared spec, Crossplane keeps infra in sync with Git. That made it the better fit for our growing platform. **Takeaway** : Terraform provisioned well, but Crossplane managed better. In this post, we’ll dive into the**hybrid architecture** we designed — balancing Terraform’s stability with Crossplane’s agility, all running inside a single ## **A Real-World Tradeoff** One of the first debates we faced was simple but critical: **“Go all-in on Crossplane or keep Terraform for the base?”** * **App teams** wanted Crossplane for its GitOps-native workflows and self-service ephemeral environments. * **Platform engineers** were cautious. Base infra ( The compromise: * **Terraform → Foundation:** VPC, subnets, AWS EKS control plane (stable, rarely changes, already trusted). * **Crossplane → Dynamic layer:** AWS RDS, **Takeaway:** Terraform gave us stability, Crossplane gave us speed. Together, they gave us both. ## **The Hybrid Design: Terraform + Crossplane in One Cluster** We landed on a **two-layer hybrid design** — both inside the same Kubernetes cluster: ### **Terraform (Foundation Layer)** * Provisioned VPCs, subnets, and the AWS EKS control plane. * Best for stable, less-frequently changing infra. ### **Crossplane (Dynamic Layer)** * Managed AWS RDS, AWS S3, AWS SQS directly from Kubernetes. * Continuously reconciled with AWS → no drift. * Integrated with ArgoCD → fully GitOps-native. **Takeaway** : Terraform laid the runway. Crossplane flew above it. GitOps was the control tower. _Terraform builds the base. Crossplane manages the edge. GitOps keeps them in sync._ _"This hybrid design let us use each tool where it was strongest — Terraform for the stable foundation (VPCs, networking, AWS EKS control plane), and Crossplane for dynamic, developer-facing resources like AWS RDS, AWS S3, and AWS SQS. By combining them in a single cluster, we gained both stability and agility, all fully reconciled through GitOps with ArgoCD."_ ## **Why This Approach Worked** The hybrid model worked because it played to the strengths of each tool: * **Terraform gave stability** → Base infra like VPCs and control planes rarely change, and Terraform was already trusted here. * **Crossplane unlocked agility** → Perfect for high-churn resources such as databases, queues, and storage. * **A single cluster simplified ops** → Fewer moving parts, less overhead. * **Scalability for teams** → Developers self-served infra through Git, while platform teams enforced guardrails. T**akeaway:** Hybrid wasn’t a compromise — it was optimization. ## **Standardized Developer Workflow** Once the hybrid foundation was in place, the next challenge was consistency. **Helm + GitOps:** ### **Each microservice had two Helm charts:** * **Application chart** → deployments, configs, autoscaling. * **Infrastructure chart** →Crossplane-managed resources. ### **Developers only touched values.yaml — e.g.:** Guardrails (versioning, encryption, deletionPolicy) were hardcoded in templates, so developers got **freedom with safety**. **Takeaway:** Developers declared intent. Guardrails enforced compliance. ## **Modular Repository Structure** After standardizing workflows, the next challenge was scaling infra code across teams. We solved this by modularizing Helm charts. We modularized infra into reusable Helm charts: * **terraform-base/** → VPCs, AWS EKS control plane. * **crossplane-eks/** → node groups, cluster add-ons. * **rds-guard/** → AWS RDS with encryption & backups. * **s3-secure/** → AWS S3 buckets with versioning & policies. **Takeaway:** Modular charts = reusability, consistency, and built-in security guardrails. ## **Separate Repositories for Terraform & Crossplane** Even with modularity, one problem remained: Terraform and Crossplane in the same repo created friction. The solution was clear — separate them. ### **Terraform Repository** * Handled base, less-frequently changing infrastructure * Examples: VPCs, Subnets, Core Networking, AWS EKS Control Plane ### **Crossplane Repository** * Ran inside the Kubernetes cluster for dynamic, developer-facing resources * Examples: AWS RDS Instances, S3 Buckets, SQS Queues, Provider configs & guardrails This separation gave platform teams control of the foundation with Terraform, while enabling developers to move fast with Crossplane without worrying about Terraform state files. **Takeaway:** Separation gave platform teams control and developers freedom. ## **Infra Workflow in Action** End-to-end flow in the hybrid model: 1. Terraform provisions the base (VPC, subnets, AWS EKS control plane). 2. Crossplane is deployed in the cluster to manage AWS RDS, AWS S3, and AWS SQS. 3. Developers update **values.yaml** in Git. 4. ArgoCD syncs changes. 5. Crossplane reconciles infra in AWS. **Takeaway:** Infra requests became Git commits. No tickets. No manual drift fixes. ## **Conclusion** Terraform gave us stability. Crossplane gave us speed. GitOps kept it aligned. Together, they created a balanced model that scaled without slowing teams down. **Takeaway:** “Hybrid Infra isn’t compromise — it’s the sweet spot”. **Next: Blog 3** – Onboarding AWS Resources & Importing Existing Infra, where we show how we safely onboarded VPCs, EKS, and RDS with Crossplane and imported existing AWS resources without downtime. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Devops Engineer Neetesh specializes in designing, automating, and managing scalable DevOps pipelines across cloud-native infrastructures. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 How We Strengthened Application Security with AWS WAF Learn how to secure web apps using AWS WAF with rate limiting, custom rules, and layered controls to reduce abuse and ensure reliable performance. By Aryan Kulshrestha 09 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents In this blog, however, we’re not going to talk about how AI is the black sheep that drives up cloud costs. Instead, we’re going to see how your FinOps teams can co-opt it to optimize cloud costs. But why bring AI into Cloud FinOps and start discussing AI in FinOps in the first place? Because cloud environments are now too complex to rely solely on the expertise of individual FinOps teams. With multi-cloud architectures, distributed workloads, and growing scale, teams can quickly become overwhelmed. By the end of this blog, you will know how to add AI in FinOps and, as a result, save hours of manual effort while achieving more precise ## **Where Do FinOps Practices Go Wrong Today** FinOps is built around three iterative phases: **Inform** , **Optimize** , and **Operate**. In the Inform phase, teams build These phases run in parallel, continuously, as cloud environments evolve. The problem is that many FinOps teams today report spending the bulk of their time stuck in the Inform phase. Manually assembling data, chasing down cost owners, and building reports. Cloud cost control is reactive by default, and cloud cost optimization is something teams get only after the monthly bill has landed. Here's where the issues arise: ### **1. Having Too Many Dashboards that Overwhelm Teams** Currently, whether it’s service-specific dashboards like Common dashboards teams often juggle simultaneously: * AWS Cost Explorer tracks spend across AWS services, accounts, and tags * GCP Billing Reports surface usage and cost breakdowns for * Azure Cost Management provides budget tracking and cost analysis for Azure environments * Third-party platforms like CloudHealth, Apptio, and Spot by NetApp add their own reporting layers In a multi-cloud or hybrid environment, FinOps teams end up toggling between platforms and manually reconciling numbers. Instead, a unified dashboard like CloudKeeper Lens addresses this challenge by providing a single source of truth that connects insights directly to the underlying infrastructure. ### **2. Delayed Remediation Steps by Engineering Teams** Cloud pricing is dynamic, with spot instance availability shifting by the hour, autoscaling events occurring within minutes, and While visibility itself is delayed due to billing data latency (often 8–24 hours across cloud providers), remediation lags even further. Most engineering teams act on cost signals in the next operational cycle, typically hours to days later, by which time the overspend has already been incurred and cannot be reversed. * Cost data from cloud providers often takes 8-24 hours to generate, making same-day decisions significantly challenging * By the time a cost spike is identified, root-caused, and escalated, the spend has already compounded * Engineering teams receive optimization recommendations days after the relevant resource decisions have already been made * Remediation workflows rely on email threads and Jira tickets, adding more delay between insight and action * The gap between insight and action is where cloud cost optimization breaks down most visibly. ### **3. Siloed FinOps and Engineering Practice** Cloud cost optimization requires shared ownership between FinOps and engineering teams. In practice, these two teams operate on different cadences, toolsets, and often different definitions of what 'efficient' means. * FinOps teams own the billing data but lack the infrastructure context to understand why costs changed * Engineering teams own the infrastructure, but rarely have cloud cost visibility built into their day-to-day workflows * Cost allocation relies on manual tagging, which engineering teams deprioritize under delivery pressure * Cloud cost control decisions made in finance are often disconnected from the architectural decisions driving the spend The result is a constant back-and-forth that slows down cloud cost optimization and produces recommendations that engineering teams are reluctant to act on. ### **4. SaaS and Non-Cloud Spend Governance** The FinOps Foundation's 2026 Framework update acknowledges what practitioners have been navigating for years: FinOps scope has expanded well beyond public cloud. * SaaS licenses accumulate across teams without centralized tracking or renewal oversight * Shadow IT spend creates blind spots in cloud cost visibility * Usage data for SaaS tools is fragmented across HR, finance, and IT systems, with no unified allocation model * Non-cloud infrastructure costs, like on-prem, colocation, and data center spend, are increasingly expected to fall under FinOps governance Managing this expanded scope manually, alongside core cloud cost optimization work, stretches FinOps teams beyond what is sustainable. ### **5. Measuring the Business Value of AI Workloads** As AI spend crosses 22% of total cloud spend for many organizations, FinOps teams are being asked a question that traditional cloud cost control frameworks were not built to answer: Is this AI spend generating commensurate business value? * GPU and TPU compute for model training generates some of the highest per-hour cloud costs of any workload type * Model inference endpoints often run at low utilization but stay provisioned continuously to avoid cold start latency * Cost-per-inference and cost-per-training-run are emerging metrics, but most FinOps teams don't yet have the tooling to track them * Tying AI infrastructure spend to business outcomes like revenue or retention requires cross-functional data that rarely sits in one place Without the ability to measure AI workload value against cost, cloud cost optimization for AI becomes guesswork. ## **How Does AI Change Cloud FinOps?** AI accelerates the FinOps framework while the core phases **Inform** , **Optimize** , and **Operate** remain the same. The difference lies in how quickly and at what scale teams can move through them. Tasks that once required hours of manual effort, such as identifying cost anomalies, generating rightsizing recommendations, or explaining billing spikes, can now be completed in seconds. This shift gradually transforms cloud cost optimization from a periodic exercise into a continuous process. As a result, the way teams interact with cloud cost data also evolves. Visibility becomes more conversational rather than dependent on dashboards, and cost control expands beyond FinOps specialists to a wider set of stakeholders who can access insights and act on them more efficiently. Also, if your in-house ### **1. Natural Language Querying for Cost Insights** Cloud cost visibility has traditionally been difficult for those unfamiliar with scripting or underlying cloud technologies. AI-powered tools that support Natural Language querying democratize it by giving non-technical people, such as C-suite executives and finance teams, insight into cloud spend. * Any team member can ask, "Why did our * Finance teams can query spend by business unit, product, or environment without needing engineering to pull the data * Engineering teams can ask cost questions directly within their workflow, without switching to a separate billing tool * Responses include the reasoning behind the answer, making cloud cost control a shared capability across functions ### **2. Cloud Spend Pattern Detection** AI-powered anomaly detection catches what dashboards miss. Spend patterns that don't trigger threshold-based alerts but still signal waste or risk. This is where cloud cost optimization shifts from reactive to proactive. * ML models trained on historical spend data detect unusual patterns across services, accounts, regions, and time windows * Anomalies are surfaced with context: what changed, which resources are involved, and what the likely cause is * Cost spikes linked to autoscaling events, misconfigured services, or unexpected data transfer are flagged in real time * Patterns indicating commitment underutilization are identified before they affect unit economics ### **3. Automated Cost Remediation Through Rightsizing** Rightsizing is one of the highest-impact levers in cloud cost optimization and one of the most consistently underused. The reason is straightforward: manual rightsizing recommendations require engineering sign-off, and engineering teams don't act on recommendations they don't trust. * AI-generated rightsizing recommendations are grounded in actual utilization data rather than averages, making them more defensible to engineering teams * Recommendations include performance impact analysis alongside cost savings projections, giving engineers the context they need to act * For non-production environments, automated rightsizing actions can be applied directly without manual review * Continuous rightsizing keeps cloud cost control from drifting back toward overprovisioning as usage patterns evolve ### **4. Intelligent Commitment Management** Reserved Instances, Savings Plans, and * AI models analyze trailing usage across instance families, regions, and account structures to recommend the right commitment type and term * Flexible commitment recommendations account for workload volatility, avoiding over-commitment on resources that scale down * Utilization monitoring runs continuously, flagging commitment waste before it compounds across billing cycles * Renewal timing, expiry alerts, and coverage gap analysis are automated, removing the manual calendar management that commitment strategies typically require ### **5. Automated Tagging and Cost Allocation** Tagging governance is the foundation of cloud cost visibility, and it's also where it most often breaks down. AI can close the gap between tagging intent and tagging reality. * Untagged resources are automatically identified and mapped to likely owners based on naming conventions, account structure, and deployment patterns * AI-suggested tag values are surfaced in engineering workflows at the point of resource creation, not discovered weeks later in a billing audit * Cost allocation models are continuously validated against actual resource usage, flagging misalignments before they distort chargeback reporting * Policy enforcement recommendations are generated based on observed tagging drift, providing FinOps teams with actionable cloud cost-control levers rather than just a report. However, to set up automation efforts, you need an expert audit of your infrastructure. ## **CloudKeeper LensGPT Brings AI to FinOps** Most AI-powered cloud cost optimization tools stop at generating insights, whereas CloudKeeper LensGPT goes a step further by CloudKeeper Lens also integrates with popular AI tools such as Cursor, Kiro, Claude, and * **Conversational cost queries:** Ask any question about your cloud spend and get a clear, context-rich answer in seconds. * **Multi-step agentic reasoning:** LensGPT applies multi-step reasoning to identify cost drivers, links spending patterns to actual infrastructure, and returns action plans rather than raw numbers * **On-the-fly dashboard generation:** LensGPT creates dashboards and fetches analysis on demand, supporting instant decision-making across services, accounts, and environments * **Enterprise-grade governance:** Role-based access controls ensure cloud cost visibility aligns with organizational responsibilities. End-to-end encryption and secure data handling are built in, supporting compliance requirements across finance, engineering, and leadership * **Plug-and-play with CloudKeeper Lens:** LensGPT connects directly with CloudKeeper Lens for seamless, connected cloud cost optimization workflows With CloudKeeper LensGPT, teams get insights into cloud spend faster, reduce reliance on manual reporting, and gain greater clarity. ## **To Sum Up** AI in FinOps augments the engineering team's efforts by taking on repetitive, monotonous tasks, acting as a sidekick rather than an outright replacement for human expertise. Today, FinOps teams spend a significant portion of their time assembling data, chasing tags, and waiting on engineering to act. With AI, that effort can be redirected toward strategy, governance, and the decisions that actually move cloud cost control forward. The entrance of With AI in FinOps, teams gain a sidekick. AI will help them keep up with this complexity and make FinOps future-ready for current advanced technologies and those to come. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 10 Costly BigQuery Mistakes Engineers Make (And How to Avoid Them) A comprehensive guide to the top 10 BigQuery mistakes that cause cloud cost runaways and how to optimize queries, storage, and usage. By Team CloudKeeper 12 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents In today’s cloud-native world, unpredictable workloads are the norm, not the exception. When running Since we are using **unscheduled state** until a new node is provisioned. Once the new node is available, the pod will then be scheduled and deployed. Please note that this provisioning process may take some time, depending on the availability of Spot Instances. ## **The Problem: Delays When It Matters Most** Your Amazon EKS cluster might scale beautifully during normal load, but when a new deployment hits, perhaps due to a new product development, your high-priority workloads can end up stuck waiting for new nodes to become available. So what happens when your high-priority pods can’t find available compute? They sit unscheduled, waiting for nodes to spin up — and this delay can translate directly into downtime, poor user experience, or SLA penalties. Let’s break this down as a practical **Problem → Root Cause → Solution** , so you can walk away with an approach you can deploy today. By default, **Cluster Autoscaler** works reactively: it adds nodes only when unschedulable pods are detected. But spinning up new EC2 instances takes time. ## **The Root Cause: Reactive Scaling and No Buffer Capacity** The problem isn’t that Kubernetes or Amazon EKS are flawed — it’s just how the autoscaling mechanism works. Here’s what happens under the hood: * **Node creation is not instant:** Even with fast instance types, provisioning can take several minutes. * **No spare capacity:** If there are no idle nodes or reserved compute, there’s nowhere for new pods to run. * **No eviction policy:** If all pods have equal priority, Kubernetes can’t decide which to evict for urgent workloads. Together, this creates a gap where your high-priority services are left waiting — exactly when you can’t afford it. ## **The Solution: Over-Provisioning with Cluster Autoscaler and Pod Priority** The answer is to **turn reactive scaling into proactive scaling**. This is done by combining: * Cluster Autoscaler * Kubernetes Pod Priority & Preemption * Low-priority placeholder pods This approach is called **Over-Provisioning**. It works like this: you deploy low-priority pods that occupy spare capacity on your nodes. When critical workloads arrive, Kubernetes evicts the placeholders immediately to make room. Meanwhile, Cluster Autoscaler detects that the freed capacity is gone and spins up new nodes to replenish the buffer. Result? Your high-priority workloads start instantly — no waiting, no lag. ## **How To Set It Up: A Practical Guide** Here’s how you can put this into action on Amazon EKS: **1. Create or Use an Amazon EKS Cluster** If you don’t have an Amazon EKS cluster yet, create one with a managed node group. A typical setup might be: Instance Type: **t3.medium** Minimum Size: 2 Maximum Size: 10 Desired Size: 2 Pick appropriate add-ons for networking and autoscaling. **2. Configure IAM OIDC Provider** Enable OIDC to allow Kubernetes workloads to assume IAM roles securely: eksctl utils associate-iam-oidc-provider \ --region us-east-1 \ --cluster \ --approve **3. Create an IAM Role for Cluster Autoscaler** Create a new IAM role: * Use **Web Identity** with the OIDC provider. * Attach **AmazonEKSClusterAutoscalerPolicy** or a custom policy with autoscaling and EC2 permissions. * Update the trust relationship so the **cluster-autoscaler** service account can assume this role. **4. Install Cluster Autoscaler** Add the official Helm chart and deploy: Confirm the **cluster-autoscaler** pod is running. **5. Define Priority Classes and Workloads** Create three YAML files: * **priority-classes.yaml:** Defines low and high-priority classes. * **low-load-pods.yaml:** Runs low-priority placeholder pods. * **force-high-priority.yaml:** Deploys high-priority pods to simulate a spike. **6. Apply them:** kubectl apply -f priority-classes.yaml kubectl apply -f low-load-pods.yaml Simulate a Spike and Watch Autoscaling in Action Apply the high-priority workload: kubectl apply -f force-high-priority.yaml The high-priority pods will evict the low-priority placeholders immediately, freeing up resources. Cluster Autoscaler notices the change and provisions new nodes, so the placeholders can be rescheduled and the buffer stays ready for the next spike. ## **What To Expect** * High-priority workloads are scheduled immediately. * Placeholder pods are evicted and rescheduled when new capacity is ready. * The cluster scales out to maintain the buffer for next time. ## **A Few Trade-Offs To Consider** Like every powerful tool, Over-Provisioning has some caveats: * **EC2 nodes still take time to spin up** , so placeholder pods buy time but don’t eliminate provisioning delay entirely. * **Low-priority pods may starve** if traffic remains high. * **Idle nodes can increase costs** during the scale-down grace period. ## **Best Practices To Make It Work Smoothly** * **Size placeholder pods carefully** to match your expected workloads. * **Use clear PriorityClasses** to control eviction. * **Deploy over-provisioning pods in a separate namespace** for easy management. * **Tune scale-down timers** to avoid cost spikes from idle nodes. * **Monitor autoscaler logs and node usage regularly** to catch inefficiencies early. **Helpful References** ## **Final Thoughts** Over-Provisioning is a practical, proven pattern for teams that care about high availability. It helps bridge the gap between your cluster’s current capacity and sudden surges in demand, ensuring your mission-critical workloads run without delay. If you rely on Running Amazon EKS at scale? Want hands-on support for your Amazon EKS deployments? Let our experts handle the complexity - explore our **Related Resources:** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Devops Engineer Neetesh specializes in designing, automating, and managing scalable DevOps pipelines across cloud-native infrastructures. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents We all dread that call: "Production is down!" But what happens when the outage becomes a regular occurrence? This is the story of how we helped a customer escape a recurring production nightmare by upgrading their Amazon EKS cluster to version 1.30. It wasn't just about new features; it was about bringing back stability and trust. ## **Identifying the Root Cause: The Vanishing Nodes and Silent Kubelet** Our customer was running a large-scale production workload on Amazon EKS v1.29, heavily utilizing Apache Airflow to trigger pods frequently. They faced a persistent issue: their Amazon **EKS nodes would frequently go into a NotReady state** , leading to significant production disruptions. Initial investigations into the _**kubelet logs**_ from affected nodes revealed a critical pattern: * Nodes were dropping every 5-7 days. * Errors like "Failed to get node when trying to set owner ref to the node lease" and "update node status exceeds retry count" indicated the _**kubelet**_ was failing to update its heartbeat lease with the API server. * The most critical finding was _**containerd[3661]: SIGABRT: abort**_ , signifying a containerd crash. This crash, in turn, brought down the aws-node pod, responsible for VPC networking, leading to a complete loss of API server communication and the node being marked _**NotReady**_. ## **Uncovering Critical CSI Driver Issues** Our deep dive into the system revealed significant issues with **CSI drivers.** Pods attempting to mount Amazon EFS volumes were failing with "connection refused" errors, and the _**efs.csi.aws.com**_ driver's communication socket was missing. The customer was running _**aws-efs-csi-driver:v2.0.1-eksbuild.1**_ , which was **outdated**. The latest version, v2.1.6, included crucial bug fixes for socket handling, systemd compatibility, and mount retries. This outdated driver was not merely buggy; it was directly contributing to node instability and crashes. Furthermore, the **Secrets Store CSI driver (v1.4.4)** was also failing. While the cluster ran Kubernetes v1.29, which enforced _VOLUME_MOUNT_GROUP_ compatibility, the deployed driver version didn't fully implement it. This caused secrets to fail during mounting, leading to pod crashes and Airflow DAG failures. Adding to the complexity, the customer's use of **custom AMIs** for their nodes presented a significant challenge. These "black box" AMIs lacked transparent configurations for base image versions, **containerd setups** , and init systems, hindering effective troubleshooting and making consistent patching nearly impossible. ## **Strategic Decision: From Patching to a Full Amazon EKS Upgrade** Initially, we implemented several stabilization measures: * Upgraded _**aws-efs-csi-driver**_ to v2.1.6. * Upgraded _**secrets-store-csi-driver**_ to v1.4.6. * Installed AWS's node auto-repair agent. * Enabled detailed metrics and alerts via Datadog. * Resized memory limits for OOMKilled containers. * Collected comprehensive logs using the Amazon EKS Log Collector. While these steps provided some stability, the underlying issues, such as misaligned kube-proxy and drifted CNI plugin configuration, indicated the cluster was fundamentally unhealthy. The decision was made to perform a **full upgrade to Amazon EKS v1.30,** not just for new features, but primarily for enhanced stability and predictability. ## **Upgrade Strategy and Execution** We presented two upgrade strategies: **1. In-Place Upgrade:** Lower disruption, but no easy rollback once the control plane is upgraded. This involves upgrading the control plane, launching new v1.30 node groups, and gradually draining old nodes. **2. Blue-Green Migration:** Safe rollback, but higher complexity and time commitment due to the need to mirror workloads, secrets, CI/CD, and observability in a new cluster. Given the cluster's complex dependencies (VPC peering, numerous route tables, hardcoded selectors in Helm charts), the customer opted for the In-Place Upgrade. **Our execution involved a meticulous process:** * **Control plane upgrade:** Achieved with zero downtime, verified by synthetic probes and real traffic traces. * **Add-on upgrades:** VPC-CNI, CoreDNS, and kube-proxy were upgraded and validated. * **New node group provisioning:** A custom-built v1.30 node group was provisioned, with all taints, labels, and IAM roles surgically replicated. * **Drain-and-validate:** Old nodes were drained one by one, with continuous monitoring of logs (piped to OpenSearch via Fluent Bit) for any anomalies. This meticulous approach ensured a smooth upgrade process, largely attributed to extensive preparation and validation at each step. ## **Post-Upgrade Impact: Restored Trust and Predictability** The transformation post-upgrade was significant: * **Airflow DAGs** executed without misfires. * EFS mounts are attached without delay. * **Secrets injected** on the first attempt. * The team's reliance on its infrastructure was restored. The psychological shift from constant firefighting to confident operation was paramount. **This experience reinforced several key lessons:** * **Add-ons are not optional dependencies:** Outdated CSI drivers can lead to cascading failures. * **Custom AMIs pose control challenges:** Without consistent validation and patching, they introduce significant exposure. * **Version upgrades enhance reliability:** Newer Kubernetes versions, like 1.30, bring crucial stability improvements. * **Effective debugging requires forensic analysis:** The truth of system behavior is often hidden in detailed log analysis. This upgrade transcended a simple version bump; it marked a pivotal shift from reactive firefighting to proactive foresight, transforming a brittle system into a reliable, predictable, and "boring" (in the best way possible) production environment. Is your Kubernetes environment causing more chaos than confidence? We specialize in stabilizing complex Amazon EKS deployments and can help you achieve predictable, reliable operations. Check more about our Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Gourav specializes in helping organizations design secure and scalable Kubernetes infrastructures on AWS. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents ## ## **Introduction** The utilization of event-driven architectures has gained popularity due to its ability to tackle the complexities inherent in building intricate systems that modern organizations commonly use. This approach emphasizes the use of microservices, which are small, specialized applications designed to perform a specific set of functions. This blog post will examine an event-driven architecture and how we are monitoring it to ## **Scenario** We are utilizing AWS ECS Fargate to handle event-driven workloads that process substantial quantities of customer data simultaneously for various clients. This presents us with an opportunity to experiment with this type of architecture, which is becoming increasingly popular for various use cases. These include facilitating communication between microservices, integrating with third-party SaaS applications, replicating data across regions and accounts, and enabling parallel event processing and fanout. **User-flow:** When users submit a request via the UI, the EBS code acts as the primary backend and transmits a message with event attributes such as clientId and jobId to the SNS topic. The AWS Fargate is then called upon by a lambda invocation triggered by the SNS topic to handle these requests. However, once the AWS Fargate is initiated, our ability to manage it is limited. As a result, to prevent lengthy tasks, we require ## **Solution Approach** The following queries arise: * How do we monitor lengthy tasks? * How do we track expenses? * How can we ensure our system's functionality? To address these concerns, we have implemented a lambda function that is triggered by an event bridge rule every 15 minutes. This function enables us to monitor tasks that run for more than an hour, allowing us to track expenses and ensure that the system is functioning correctly and not losing progress over time. ## **Solution Steps** Create an SNS topic that will be used by your lambda to get alerts: 1. Go to SNS. 2. Create an SNS with your name and then add a subscription to your email address where you want to receive the alerts. 3. Here we can also integrate it with Slack which we have discussed in the Bonus section. Create a lambda Function: 1. Go to AWS Lambda. 2. Click on Create Function. 3. Create a Python lambda. 4. Use the default settings and click Create Function. 5. Copy and paste this code into the code section. 6. Now, Click on Configuration and then set environment variables. 7. Once this is done configure the EventBridge Rule according to the steps described in the next section and you will see a trigger in this lambda as below: Create an EventBridge Rule: 1. Go to Cloudwatch > Events > Rules. 2. Create Rule. 3. Give the Rule Name. 4. Select the schedule and click Next. 5. Define the schedule for example here we will be running it every 15 mins. 6. Click Next and select the lambda you want to trigger in the Select Targets menu. You can add multiple targets if you want. 7. Review the config and click Create rule. Your rule will be created. ## **Bonus** Integration with Slack ## **Conclusion** In conclusion, utilizing Lambda to track long-running AWS Fargate tasks can result in significant AWS cost savings for organizations. By __ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents In today's era of cloud computing, serverless architectures have gained immense popularity due to their scalability, cost-effectiveness, and ease of management. AWS Step Functions is a full service offered by Amazon Web Services (AWS) that enables developers to build and coordinate complex workflows effortlessly. In this blog post, we will explore the capabilities of Step Functions, delve into their cost considerations, leverage their use to reduce AWS costs and highlight some real-world use cases where Step Functions excel. ## **Understanding Step Functions** AWS Step Functions is a fully managed service that allows you to design and visualize workflows using a state machine-based approach. It simplifies the process of orchestrating and coordinating multiple AWS services and custom actions, eliminating the need for manual management and enabling robust error handling. ## **Key Features and Benefits** **1. State Machine Design:** Step Functions enable you to design workflows as a collection of states, representing individual tasks or actions. These states can be arranged to create sophisticated workflows, allowing for sequential, parallel, or conditional execution. **2. Visual Representation:** With Step Functions, you can visualize your workflows using a graphical interface, making it easier to understand and communicate the logic of your application. The visual representation provides an intuitive view of the entire workflow and helps in **3. Fault Tolerance and Error Handling:** Step Functions automatically handle retries, timeouts, and error handling, ensuring your workflows are robust and resilient. Suppose an error occurs during the execution of a state. In that case, you can define error-handling strategies such as retrying the state, branching to an error-handling state, or stopping the execution altogether. **4. Integration with AWS Services:** Step Functions seamlessly integrate with various AWS services, allowing you to orchestrate complex workflows involving Lambda functions, ECS (Elastic Container Service) tasks, Glue jobs, Batch jobs, SNS (Simple Notification Service) notifications, and more. This integration enables you to ## **Cost Considerations** When considering the cost of Step Functions, it's important to understand that you are charged for two main components: **1. State Transition Costs:** AWS charges based on the number of states transitions your workflows make. A state transition occurs when a state changes to another state, and the cost varies based on the region and the number of transitions. It is crucial to optimize your workflows to minimize unnecessary transitions and **2. State Execution Costs:** This cost is associated with the duration of state execution, which depends on the resources consumed by each state. The execution time includes the time taken by AWS services like Lambda or ECS tasks. Optimizing the execution time by designing efficient state logic and resource allocation helps in effective AWS cost management. ## **Reduce AWS costs with Step Functions** By utilizing Step Functions, you can bring down your AWS bill in several ways: **1. Eliminating Idle Resources:** With Step Functions, you only pay for the actual execution time of your workflows. There are no idle resources running in the background when workflows are not being executed. This means you can avoid the cost of running servers, databases, and other resources that are not being used. **2. Improved Resource Utilization:** By using Step Functions, you can optimize resource utilization by coordinating and orchestrating distributed applications and services in a more efficient manner. This means you can avoid overprovisioning resources and paying for more than what you actually need. This is one of AWS cost optimization’s best practices. **3. Reduced Developer Effort:** With Step Functions, developers can build and manage workflows using a visual interface, rather than having to write and manage custom code. This reduces the time and effort required to build and maintain workflows and allows developers to focus on other critical aspects of their applications. **4. Reduced Operational Overhead:** Step Functions automatically manage the scaling and availability of your workflows, eliminating the need for operational overhead such as managing servers, databases, and other infrastructure components. This results in reduced costs associated with maintaining and scaling your applications. Overall, AWS Step Functions can help ## **Use Cases for Step Functions** **1. ETL (Extract, Transform, Load) Pipelines:** Step Functions are ideal for orchestrating complex ETL pipelines. By integrating with AWS Glue, Step Functions can coordinate the execution of various transformation steps, handle errors, and provide visibility into the overall progress of the pipeline. **2. Media Processing Workflows:** Step Functions can orchestrate the processing of multimedia assets by coordinating Lambda functions, Elastic Transcoder, and other AWS services. For example, you can create a workflow to resize images, transcode videos, and generate thumbnails in parallel or sequentially, ensuring efficient utilization of resources. **3. Order Processing and Fulfillment:** Step Functions can be used to automate order processing workflows, from capturing orders to managing inventory, payment processing, and shipping notifications. The ability to handle error scenarios and retry failed states ensures the reliability of the order fulfillment process. **4. Serverless Microservices:** Step Functions can serve as a coordination layer for serverless microservices, enabling complex interactions between multiple services. Let's explore a real-time use case for AWS Step Functions, including a cost estimation and a workflow diagram. ## **Use Case: Order Processing Workflow** **Description:** Imagine an e-commerce platform that processes customer orders through a series of steps, including order validation, inventory check, payment processing, and order fulfillment. To handle this workflow efficiently and **Workflow Steps:** **1. Order Validation:** Verify the order details, including item availability, customer information, and order validation rules. **2. Inventory Check:** Query the inventory system to ensure that the ordered items are in stock and available for shipment. **3. Payment Processing:** Initiate the payment processing workflow, which may involve making API calls to payment gateways, validating payment details, and capturing the payment. **4. Order Fulfillment:** Once the payment is confirmed and inventory is available, initiate the process to fulfill the order, including packaging, labeling, and shipping. **5. Order Completion:** Send notifications to the customer with order confirmation details, tracking information, and any additional updates. ## **Cost Estimation:** The cost of using AWS Step Functions depends on the number of state transitions, state executions, and the duration of each execution. In this use case, let's assume an estimated cost breakdown based on typical usage: * **State Transitions:** Each step in the workflow represents a state transition. Assuming an average of 5 state transitions, the cost is approximately $0.000025 per state transition. * **State Executions:** The number of state executions depends on the number of orders processed. Assuming 10,000 orders are processed per month, with an average of 5 state executions per order, the cost is approximately $0.000004 per state execution. * **Execution Duration:** The cost is based on the duration of each execution state. Assuming an average duration of 10 seconds per state execution, the cost is approximately $0.00000014 per second. **Workflow Diagram:** Below is a simplified workflow diagram for the Order Processing Workflow using AWS Step Functions: Workflow - Order Processing using Step Functions It's important to consider that the cost estimation provided is a rough approximation. While implementing _Cloudkeeper, with its promise to provide guaranteed cost savings to up to 25%, helps its customers to optimize their spending through different optimization techniques, including Step Functions. We recommend reading our whitepaper on_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents **Picture this:** You're on the cutting edge of application deployment, navigating the fast-paced world of container image management. As you strive for streamlined processes and rock-solid security, Amazon Elastic Container Registry (ECR) emerges as our trusted ally. But hold on, there's an exciting development from Amazon Web Services (AWS) called the VPC Endpoint for Amazon ECR. In this brief article, we're diving deep into the cost-saving benefits, the configuration magic, and a treasure trove of use cases that will ## **Problem Statement** Conventional setups often involve Private ECS/EKS tasks pulling container images from private ECR repositories over the internet. This setup has a dependency on NAT gateways for internet access which incurs **data processing** and **operational expenses**. Additionally, it poses security risks and increases the chances of security breaches or unauthorized access to confidential application images. To solve these challenges, using Amazon ECR with VPC Endpoint is the optimal solution. ## **VPC Endpoints** Think of a VPC endpoint as a virtual device that helps you establish private connections to certain AWS services. It allows your Amazon instances/containers to communicate with these resources without needing public IP addresses. The best part is that the traffic between your VPC and the service stays within the secure Amazon Web Services network and doesn't go over the public internet. ### **There are 2 types of VPC endpoints:** **1. Interface endpoints:** These are highly available and scalable components within your Amazon VPC. They enable smooth communication between instances within your VPC and the supported AWS services. You don't have to worry about network traffic availability risks or bandwidth limitations. **2. Gateway endpoints:** These are used for services like Amazon S3 and DynamoDB. They provide a secure and scalable path for accessing these services from your VPC, ensuring that the traffic remains within the Amazon network. In a nutshell, VPC endpoints enable secure and direct connections between your Amazon VPC and supported AWS services. ## **Understanding Amazon ECR VPC Endpoint** The Amazon ECR VPC Endpoint is a valuable feature that enables a secure and private connection between your VPC and the Amazon ECR service. This connection removes the need for internet gateways, Network Address Translation (NAT) instances/Gateway, or public IP addresses when accessing ECR. By using VPC endpoints, you can ensure that container image traffic remains within your VPC. This has several advantages, including enhanced network performance, reduced exposure to the public internet, and improved security measures. Let us understand the feature better by implementing a demo deployment of an Amazon ECR Private Link using VPC Endpoints. **Architecture** **** 1. In this demo, we will be utilizing the ECS Fargate Cluster. Please ensure that you have an active ECS Fargate Cluster running. 2. In your AWS account, you should have an Amazon Elastic Container Registry (ECR) that contains a container image. This image will be pulled by ECS tasks. 3. To set up the environment, you need a Virtual Private Cloud (VPC) with DNS resolution and DNS hostnames enabled. 4. Additionally, you will require a task definition and an ECS service. ## **Deployment Steps Amazon ECR VPC endpoints:** 1. **Security Group Creation:** - Create a Security Group that will be attached to all the VPC Endpoints we are going to create in order to allow your VPC's CIDR as Ingress. The security group attached to the VPC endpoint must allow incoming connections on port 443 from the private subnet of the VPC. 2. To create a VPC endpoint for ECR, go to the VPC dashboard in the AWS Management Console and click on "**VPC Endpoints** " in the left panel. 3. Click on "**Create Endpoint** " to begin creating the VPC endpoint for ECR Docker (dkr). * Provide a name for your endpoint. * Under "**Service Category** ," select "**AWS Services**." * For "**Service types** ," enter " **com.amazonaws. .ecr.dkr**" Replace with the region you are working in. 4. Choose the VPC and subnets where you want to deploy the VPC endpoint. 5. Select the security group that was created in step 1. Optionally, you can add tags to the VPC endpoint. Finally, click on "**Create Endpoint** " to create the endpoint. 6. If you are using * Provide a name for your endpoint. * Under "**Service Category** ," select "**AWS Services**." * For "**Service types** ," enter " **com.amazonaws. .ecr.api**" . * Rest, follow the same steps 4 & 5 . 7. **Gateway Endpoint for S3** - In this step, we create a gateway VPC endpoint for Amazon S3 because ECR uses S3 to store container images in layers. When other AWS cloud computing services need to pull images from ECR to build containers, they access both ECR to retrieve the image metadata and S3 to download the actual image layers. * Provide a name for your endpoint. * Under "**Service Category** ," select "**AWS Services**." * For "**Service types** ," enter " **com.amazonaws.us-west-2.s3** " . * Attach route table to vpc endpoint. Click on **Create Endpoint**. 8. (**Optional if you are using Cloudwatch Logs**) Finally, we need to create a VPC endpoint for the Logs endpoint to allow your container to log in to CloudWatch. Amazon ECS tasks hosted on Fargate that pull container images from Amazon ECR that also use the AWS logs log driver to send log information to CloudWatch Logs require the CloudWatch Logs VPC endpoint. * Provide a name for your endpoint. * Under "**Service Category** ," select "**AWS Services**." * For "**Service types** ," enter " **com.amazonaws. ecr.logs** " . * Continue following the same steps 4 and 5 for the remaining configurations. < style="margin: 20px 0 -50px;" img data-src="" src="/cms-assets/s3fs-public/2023-08/image55.jpg" /> **Test and Validate:** Deploy and test your ECS tasks to ensure they can successfully pull container images from the private ECR repository through the VPC endpoint. ## **Benefits of using Amazon ECR VPC Endpoint** 1. **Costs Savings on Data Transfer:** When using the VPC Endpoint for Amazon ECR, container image traffic remains within your Virtual Private Cloud (VPC). This means that you can 2. **Savings on Public IP Expenses:** The ECR VPC Endpoint allows you to access ECR without relying on public IP addresses. This eliminates the need to allocate and manage public IP resources, which can result in cloud cost savings, especially in scenarios where a large number of containers or instances require access to ECR. 3. **Improved Performance:** Utilizing ECR VPC endpoints results in improved efficiency. This leads to lower latency and faster data transfer, which is particularly beneficial for large-scale deployments or bandwidth-intensive workloads. 4. **Efficient Resource Utilization:** By simplifying network configuration and eliminating the need for additional components like proxy servers or VPC peering, the VPC Endpoint reduces the overhead and complexity associated with managing and maintaining these resources. This can result in improved resource utilization and 5. **Lower Network Bandwidth Costs:** With the ECR VPC Endpoint, you can optimize network bandwidth usage. By bypassing internet gateways or NAT instances, you reduce the data transfer requirements and effectively lower the associated costs. This can be advantageous for high-traffic container image transfers, minimizing network-related expenses. 6. **Enhanced Security:** By using the VPC Endpoint for ECR, you can increase the security of your container images. Removing the need for internet gateways/NAT’s reducing potential attack vectors and reduces exposure to the public internet. Keeping container image traffic within your VPC adds an extra layer of security, guarding against unauthorized access and potential data breaches. 7. **Simplified Network Configuration:** The ECR VPC Endpoint simplifies network configuration by eliminating the need for complex setups like proxy servers or VPC peering. It provides a direct connection to ECR, reducing operational overhead and making container management easier. ## **Conclusion:** If you find yourself constantly shuffling large monolithic Rails apps in ECR and dealing with the overhead of NAT Gateways, here's a tip: enable the VPC endpoint and watch your savings stack up! By keeping your ECR traffic within the VPC, you'll optimize performance, enhance security, and enjoy significant cost savings. So go ahead, turn on that VPC endpoint and start saving dollars! _Just like Amazon ECR VPC Endpoints offer you multiple benefits including substantial_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents If you run AWS with multiple accounts, private DNS resolution becomes important very quickly. Maybe you have a **centralized shared services account** where networking and DNS are managed for everyone. Or maybe you have a **decentralized model** where each account owns its own services and DNS. Both patterns are common, and both can work well, but the way private DNS resolution behaves in each design is often misunderstood. The key to understanding this is simple: AWS already provides a built-in DNS resolver inside every Virtual Private Cloud. Once you understand how that resolver works, it becomes much easier to design cross-account private DNS the right way. ## **Two common multi-account DNS architectures** Let’s start with the two architectures most teams use. ### **1) Multi-account centralized architecture** In a centralized model, DNS is mostly managed from one shared services account or shared services VPC. For example: * Private Hosted Zones (PHZs) live in a shared services account * Shared networking components also live there * Other application accounts consume DNS from that central place This is attractive because it gives you one place to manage private domains, records, and integrations with on-premises DNS. A typical example looks like this: * A shared services VPC owns the Private Hosted Zone, such as **corp.internal** * That same zone is associated with the shared services VPC * The zone is also associated with application VPCs in other AWS accounts * On-premises DNS forwards AWS private domain queries to Route 53 Resolver inbound endpoints * Route 53 Resolver outbound endpoints are used for forwarding on-premises domain queries back out when needed. You can This model gives you**central governance and consistent DNS management.** But it also raises a common question: **How do VPCs in other accounts resolve private names?** The answer is not “by forwarding queries to another VPC.” The better answer is usually **by associating the same Private Hosted Zone with those VPCs.** ### **2) Multi-account decentralized architecture** In a decentralized model, each AWS account owns its own DNS. That means: * Each account can manage its own Private Hosted Zones * Each team controls its own DNS records * Failures and mistakes are isolated to that account * Teams can move faster without depending on a central DNS owner For example: * Account A has its own PHZ * Account B has its own PHZ * Account C has its own PHZ * A shared services VPC may still exist for hybrid DNS connectivity with on-premises * PHZs can still be associated across accounts and even across Regions where needed This model is useful when different teams need independence. It reduces the blast radius because one team’s DNS changes do not automatically affect everyone else. The tradeoff is that you now have **distributed ownership** , so you need naming standards and governance to keep things organized. Before cross-account DNS, understand DNS inside a VPC This is the part many people skip, but it is the most important one. Every VPC in AWS comes with an **Amazon-provided DNS resolver**. This resolver is available at: * **169.254.169.253** * **fd00:ec2::253** * The base IP address of the VPC CIDR block plus 2 Examples: * **10.0.0.0/16 → 10.0.0.2** * **172.31.0.0/16 → 172.31.0.2** * **192.168.100.0/24 → 192.168.100.2** That resolver is local to the VPC experience. Instances inside the VPC use it for DNS lookups. So when an **efs.corp.internal** the flow is normally: **Instance → Amazon-provided Route 53 Resolver inside the VPC → DNS answer** That answer might come from: * a Private Hosted Zone associated with that VPC * public DNS * forwarding rules if you configured hybrid DNS The important idea is this: **Instances do not need to query a DNS server in another VPC just because the record is managed elsewhere.** If the right Private Hosted Zone is associated with the VPC, the query is resolved through the local Amazon-provided resolver. ## **Where designs go wrong** Historically, many teams tried to solve cross-account private DNS by doing one of these: * Deploying DNS proxy servers on an * Using Active Directory DNS servers as central forwarders * Forwarding queries between VPCs through Route 53 Resolver endpoints That works in some cases, especially for hybrid DNS with on-premises, but for AWS-to-AWS private name resolution, it often adds unnecessary complexity. Why? Because it turns a local DNS lookup into a network dependency. Instead of resolving locally inside the VPC, the query has to travel somewhere else first. That creates extra cost, more moving parts, and more failure scenarios. ## **The correct architecture for AWS-to-AWS private DNS** For private DNS resolution across AWS accounts, the better design is usually: **Share or associate the Private Hosted Zone with every VPC that needs to resolve it.** For example, imagine this setup: * Private Hosted Zone: **corp.internal** * VPC A in Account A * VPC B in Account B * VPC C in Account C * Shared Services VPC in a networking account Instead of forwarding **corp.internal** queries from VPC A to a central resolver endpoint, you associate the same PHZ with: * VPC A * VPC B * VPC C * Shared Services VPC Now each VPC resolves the same private records locally. ### **Query flow now** From an instance in VPC A: **efs.corp.internal** The flow is: **Instance → Amazon DNS Resolver inside VPC A → Private Hosted Zone lookup → Answer returned** Key points of this design: * No forwarding. * No DNS proxy server. * No centralized DNS hop for AWS-to-AWS lookups. ## **Why is this better** ### **1) Resolution stays local to the VPC** Each VPC uses its own built-in Route 53 Resolver path. That means resolution is not dependent on a central DNS forwarding layer for internal AWS private names. If one part of the environment has trouble, other VPCs are less likely to be affected. For example: * If VPC A has a local issue, VPC B can still resolve it using its own resolver path * You avoid introducing a shared DNS choke point for every private lookup * You reduce cross-VPC dependency for something as basic as name resolution This is especially valuable in multi-account environments where resilience matters. ### **2) It is simpler** A lot of DNS pain comes from unnecessary forwarding chains. When you use the PHZ association: * There are fewer components * There are fewer rules to debug * There are fewer network paths involved When something fails, troubleshooting is easier because the question becomes: “Is the PHZ associated with this VPC, and is the record there?” That is much easier than tracing forwarding rules across accounts and endpoints. ### **3) It is cheaper** Resolver endpoints cost money. If you deploy inbound and outbound endpoints across multiple Availability Zones, the cost adds up fast. By contrast,**associating a Private Hosted Zone with VPCs does not require you to build a resolver-endpoint-based design just for AWS-to-AWS private resolution.** So for many internal AWS use cases, PHZ association is the more cost-effective design. ### **4) It scales better operationally** If you grow from 3 VPCs to 30, or from 10 accounts to 100, centralized forwarding becomes harder to manage. You have more: * rules * dependencies * endpoints * failure domains PHZ association keeps the design cleaner. The DNS data is shared where needed, and resolution remains local inside each VPC. ## **When Resolver endpoints still matter** This does not mean Resolver endpoints are useless. They are still important for **hybrid DNS** , especially when you need DNS between AWS and on-premises environments. Examples: * On-premises DNS forwarding private AWS domain queries into AWS * AWS forwarding on-premises domain queries back to the enterprise DNS * Centralized hybrid name resolution patterns So the rule of thumb is: * **AWS-to-AWS private DNS:** prefer PHZ association * **AWS-to-on-premises DNS:** Resolver inbound and outbound endpoints are often the right tool That distinction clears up a lot of confusion. ## **Why the built-in VPC resolver matters so much** The Amazon-provided DNS resolver is the reason this architecture works so well. Because every VPC already has a native resolver, AWS can let workloads in that VPC resolve records from any Private Hosted Zone associated with it. That means you do not need to “send DNS traffic” to wherever the zone was created. This is a big conceptual shift for beginners. Many people assume: “The hosted zone lives in another account, so my query must go there.” But that is not how it works from the workload’s point of view. What matters is not where the PHZ was created. What matters is whether the PHZ is associated with the VPC that is making the query. Once it is associated, workloads in that VPC can resolve the records using the built-in resolver. That is why private DNS works smoothly in some designs and fails in others. ## **Centralized vs decentralized: which is better?** There is no single answer. It depends on how your organization works. A **centralized model** is better when: * You want strong governance * A central networking team owns DNS * You want one place to manage shared private namespaces A **decentralized model** is better when: * Teams need autonomy * Accounts own their own services end-to-end * You want to reduce blast radius and team dependencies In both models, the same DNS principle still applies: **Do not force AWS-to-AWS private DNS through central forwarding if PHZ association can solve it more directly.** ## **Final takeaway** The recommended approach in most cases : **Private DNS resolution in AWS works best when each VPC resolves names locally using its built-in Route 53 Resolver, with the required Private Hosted Zones associated directly to that VPC.** That design is usually simpler, cheaper, and more resilient than pushing every query through centralized DNS forwarders. AWS already gives you a DNS resolver in every VPC. The smartest design is usually the one that takes advantage of it. And in multi-account AWS, that often means sharing the zone, not forwarding the query. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Akash is an engineering enthusiast who enjoys building scalable, reliable systems. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents ## **Introduction to AWS GLUE** AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy to move data between data stores. It is a serverless service, which means that it will automatically provision and scale the infrastructure required to perform data processing tasks. **AWS Glue consists of three components** * Data Catalog: Data Catalog is a centralized metadata repository that stores information about data sources and targets, including schema and partition information. * ETL Engine: An Apache Spark-based engine that performs the AWS ETL (extract, transform, and load) operations on the data. AWS Glue provides pre-built transforms, or you can create your own custom transforms using Apache Spark code. * Jobs: The ETL process is defined as a job in AWS Glue. You can schedule AWS Glue jobs to run on a regular basis, trigger them based on events, or run them on demand. AWS Glue works with various data sources and targets, including Amazon S3, Amazon RDS, Amazon Redshift, and various other databases and file systems. It provides a simple and flexible way to move data between different data stores, perform the data transformations, and then process the data at scale. ### **Below example may help us to illustrate how AWS Glue could be used** Suppose you work for a retail company that has multiple data sources, including customer orders, product inventory, and website clickstream data. You need to combine and transform this data to generate insights for the marketing team. **Follow the below steps** You start by using AWS Glue's Data Catalog to create a centralized metadata repository that stores information about your data sources. You can easily import metadata from your data sources or manually create tables in the catalog. You create tables for each of your data sources, including schema and partition information. Next, you use the AWS Glue with the AWS ETL services to perform the extract, transform, and load operations on the data. You create an AWS Glue job that reads data from each of the tables in the Data Catalog and perform transformations using pre-built transforms. For example, you might join customer orders with product inventory data to get insights into which products are selling well, or you might aggregate website clickstream data to understand how customers are interacting with your website. Finally, you schedule the job to run on a regular basis, such as once a day or once a week. The output data is then stored in Amazon S3 or another data store of your choice, where it can be analyzed by the marketing team. With AWS Glue, you were able to easily combine and transform data from multiple sources, and automate the AWS ETL process to generate insights on a regular basis. ## **Few ways to save money on AWS Glue jobs** * **Use a smaller instance size: AWS Glue offers various instance types and sizes, with varying amounts of CPU and memory.****can significantly reduce your Glue job's cost.** * Optimize the code: Optimize your AWS ETL code to make it more efficient and reduce the job's processing time. You can do this by using the right data structures, applying data partitioning, and optimizing the algorithms. * Use data compression: Using data compression techniques like GZIP or Snappy can help you reduce the amount of data transfer and storage required, which can save you money. * Monitor the job logs: Monitoring the job logs and identifying any errors or issues can help you optimize the Glue job's performance and reduce the AWS Glue cost. * Use reserved capacity: AWS Glue offers reserved capacity for those who want to commit to using Glue for a certain period. This option can help you save up to 50% on your Glue job's cost. * Use spot instances: AWS provides a spot instance pricing model, which can help you by up to 90%. Spot instances are spare EC2 instances that AWS makes available at a discounted rate. However, keep in mind that using spot instances comes with the risk of instance termination when the spot price exceeds your bid price. * Automate job scheduling: Using AWS Lambda or AWS Step Functions to automate job scheduling can help you save time and money by reducing the need for manual intervention. ## **How optimizing the code can save money on AWS Glue** Suppose you have a Glue ETL job that processes data stored in Amazon S3. The job reads the data from S3, applies some transformations, and writes the results back to S3. The AWS Glue S3 job is currently taking 6 hours to complete and is using an instance type with 16 vCPUs and 64 GB of memory, which costs $1.20 per hour. To optimize the code and reduce the job's processing time - * If the data in S3 is stored in a large number of small files, you could use partitioning to group the data into larger files based on a common attribute. This can reduce the amount of data scanned and processed by the Glue job, leading to faster processing times and lower AWS Glue costs. * which will help reduce memory usage and improve processing times. * If possible, split the Glue job into smaller, parallel tasks that can be processed simultaneously. This can help reduce the overall processing time and allow you to use a smaller instance type, leading to cost savings. * Optimize the transformations applied to the data to reduce the amount of processing required. For example, you can use filters to remove unnecessary data or reduce the size of the dataset that needs to be processed. ## **Data compression can help save money on AWS Glue** Suppose you have an AWS Glue ETL job that processes a large amount of data stored in Amazon S3. The data is stored in CSV format and takes up a lot of storage space in S3. The job reads the data from S3, applies some transformations, and writes the results back to S3. To save money on processing costs, you can use data compression to reduce the amount of data that needs to be processed by the Glue job. You can use a compression format such as GZIP or BZIP2 to compress the data before storing it in S3. Example of how you can use GZIP compression with AWS Glue: 1. First, create a GZIP-compressed version of the input data using the following command: 2. Upload the compressed file to Amazon S3. 3. Modify your Glue ETL job to read the compressed file from S3 and decompress it in memory using Python's built-in gzip module: By using GZIP compression, you can significantly reduce the amount of data that needs to be read and processed by your Glue job. This can result in lower processing costs, as the job can be completed faster and require less memory and computing resources. ## **Monitoring job logs also helps in saving money on AWS Glue** Monitoring job logs is an important practice for optimizing AWS Glue ETL. By , you can identify issues that are causing your job to consume excessive resources or fail, and take corrective action to address these issues. ### **Examples of how you can monitor job logs in AWS Glue** **Enable CloudWatch Logs** Flex Execution - AWS Glue provides functionality that can help us to save 35% of the costs of executing Spark jobs. By utilizing spare compute capacity for workloads and making it free for non-time-sensitive jobs, we can reduce the cost of jobs. * Cost of running standard jobs is $0.44 per hour. * Cost of running flexible jobs is $0.29 per hour, by which we can achieve 35% of savings _helps you cost-optimize your entire cloud infrastructure and provides instant and guaranteed savings of up to 25% on your AWS bills.__, to learn more._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents ## ## **Introduction** AWS QuickSight is a powerful and feature-rich business intelligence service that enables organizations to gain valuable insights from their data. While AWS QuickSight offers tremendous value, it's essential to optimize its usage to ensure cost-effectiveness. In this blog, we will explore various strategies and best practices to save money while leveraging the capabilities of AWS QuickSight. ## **Setting up the AWS Cost and Usage Report** The first thing you’ll need is to have AWS Cost and Usage Reports enabled in your account. You’ll need to create an S3 bucket, configure its permissions and enable AWS Cost and Usage Reports in the Make sure you select “Hourly” as the time unit and that you check the “Include Resource IDs” option. For this exercise, the more granular the data, the better. Also, make sure the boxes for “Redshift” and “QuickSight” support are enabled. ## **Understand and Optimize Data Storage** **a) Data Preparation** Before importing data into AWS QuickSight, ensure that it is clean, relevant, and optimized. Remove any unnecessary columns or rows, apply appropriate data compression techniques, and aggregate data where possible. By reducing the data volume, you can lower storage costs and improve query performance. **b) Leverage SPICE** AWS QuickSight uses the Super-fast, Parallel, In-memory Calculation Engine (SPICE) to accelerate data processing. SPICE stores data in memory, reducing the need for frequent data retrieval from the source. By optimizing the use of SPICE, you can minimize data transfer costs and improve overall performance. **c) Data Partitioning** If you have large datasets, consider partitioning the data based on relevant criteria, such as date or category. Partitioning allows QuickSight to process only the required data segments, reducing query execution time and costs. ## **Choose the Right Data Refresh Settings** AWS QuickSight offers different options for data refresh, including on-demand and scheduled refreshes. Evaluate the frequency at which your data needs to be updated and choose the appropriate refresh settings. For example, if your data changes infrequently, scheduling less frequent refreshes can help reduce costs associated with data ingestion and processing. ## **Optimize Visualization Design** **a) Limit Data Points** When designing visualizations, avoid displaying a large number of data points or using excessively detailed visuals. Overloading visualizations with data can impact performance and increase data transfer costs. Use filters, aggregations, or sampling techniques to focus on the most relevant data points for analysis. **b) Reduce Rendering Complexity** Complex visualizations with multiple layers, interactive elements, or real-time data updates can increase rendering time and costs. Simplify visual designs and interactions to strike a balance between usability and performance. ## **Monitor Usage and Adjust User Licenses** **a) User Licenses** AWS QuickSight offers different user license tiers, such as Standard and Enterprise. Assess the needs of your organization and assign appropriate license types to users. Consider allocating higher-tier licenses only to power users who require advanced features, while assigning lower-tier licenses to users who primarily consume dashboards and reports. **b) Monitor User Activity** Regularly review user activity and usage patterns to identify inactive or underutilized users. Deactivate or adjust licenses for users who no longer require access to AWS QuickSight, ensuring that you only pay for active users. ## **Enable Cost and Usage Monitoring** **a) AWS Cost Explorer** Utilize AWS Cost Explorer to monitor and analyze your QuickSight-related costs. It provides insights into your usage patterns, identifies cost spikes, and enables you to optimize your spending based on data-driven decisions. **b) Cost Allocation Tags** Implement cost allocation tags to track and allocate AWS QuickSight costs to specific projects, teams, or departments. This helps in identifying areas where cost optimizations can be applied and facilitates accurate cost attribution. ## **Take Advantage of QuickSight Pricing Options** **a) Pay-as-You-Go Pricing** AWS QuickSight follows a pay-as-you-go pricing model, allowing you to scale usage based on demand. Leverage this flexibility to adjust your usage during periods of lower activity or when specific dashboards or reports are not actively accessed. **b) Reserved Capacity** If your organization has predictable usage patterns or requires dedicated resources, consider purchasing ## **Advantages of QuickSight over AWS Cost Explorer** **a) More and better graphs** AWS Cost Explorer only has 3 graphs: vertical bar, stacked vertical bar and line. AWS QuickSight has way more options, including horizontal (single and stacked), vertical (single and stacked), pie, line, area line, pivot table, heat map, scatter plot, tree map. **b) More options to group data by** AWS Cost Explorer gives you the option to group data by: API Operation, Availability Zone, Instance Type, Purchase Option, Region, Service, Tag, Usage Type. In AWS QuickSight, you can group and display data by any of the more than 90 fields included in the AWS Cost and Usage Report. **c) Better report granularity** AWS QuickSight lets you drill-down to the actual hour an event took place. **d) More options to measure data by** AWS Cost Explorer (as its name implies) only gives you the option to see the cost incurred by any of the supported data dimensions (Service, API Operation, etc.) Sometimes this is not enough - especially when you want to find inefficiencies in usage. For example, you want to find patterns in data transfer types that will help you optimize your application. Or patterns in certain API calls or EBS storage types. You won’t be able to get to this level of detail using the AWS Cost Explorer. **e) You can filter by AWS Resource ID** Sometimes you need to drill down to specific **f) You can create dashboards** With AWS QuickSight you can create rich dashboards where you can visualize multiple graphs at once. This is definitely a time saver when analyzing and presenting conclusions to your team or clients. ## **Conclusion** AWS QuickSight provides a robust platform for data visualization and analysis, but it's crucial to optimize its usage to save costs. By following these strategies, organizations can maximize the value derived from QuickSight while keeping expenses in check. From optimizing data storage and refresh settings to monitoring user licenses and utilizing cost monitoring tools, these practices enable you to strike a balance between cost savings and the insights gained from QuickSight. __ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents Connecting on-premises infrastructure with cloud services is crucial for scalability and flexibility. We have multiple options for establishing this connection, including Direct Connect via Partner Network and Site-to-Site VPN over MPLS. Each option offers unique benefits, and choosing the right one depends on your requirements. This blog will discuss connection options and how to establish seamless communication between on-premises infrastructure and AWS Cloud services using AWS Direct Connect. ## **Connection Options** When connecting your on-premises environment to the AWS Cloud, you have **two primary options** , depending on your requirements for performance, security, and cost: ## **1. Direct Connect via Partner Network** Direct Connect via a partner network provides a dedicated, private connection to AWS Cloud. It is ideal for businesses requiring high bandwidth, low latency, and secure connectivity for mission-critical workloads ### **Features and Benefits:** * **Dedicated Connection:** Private, high-performance link between your on-premises environment and AWS. * **Low Latency:** Ensures consistent and predictable network performance, which is crucial for latency-sensitive applications. * **High Bandwidth:** Designed for workloads requiring**large-scale data transfers or hybrid cloud** setups. * **Enhanced Security:** Avoids exposure to the public internet, providing an extra layer of security. * **Managed Service:** AWS Direct Connect Partners handle setup, provisioning, and maintenance. ### **AWS Direct Connect Partners in India:** AWS collaborates with **several trusted partners to provide Direct Connect** services in India, including: * Bharti Airtel * GPX * Global Cloud Xchange * NetMagic Solutions * Reliance Jio * Sify * Tata Communications * Other AWS-certified partners ## **2. Site-to-Site VPN Over MPLS** A Site-to-Site VPN over MPLS provides a secure, encrypted connection to AWS Cloud using your existing MPLS network. It is a viable option when **Direct Connect is not feasible or as a backup solution.** ### **Features and Benefits:** * **Secure Connectivity:** Establishes an encrypted VPN tunnel (IPsec) over the MPLS network for data protection. * **Leverages Existing Infrastructure:** Utilizes your current MPLS setup, reducing additional overhead. * **Cost-Effective:** Suitable for businesses with moderate data transfer needs or as a fallback. * **Faster Deployment:** This can be deployed faster than Direct Connect, making it ideal for urgent use cases. ### **Use Cases:** * Ideal for businesses with **limited bandwidth requirements.** * Functions as a **disaster recovery or failover solution** alongside Direct Connect. Choosing between the two connection options ## **What is MPLS + AWS Direct Connect?** **MPLS (Multi-Protocol Level Switching):** A private network service offered by many telecom providers, enabling secure, low-latency connections between remote locations. **AWS Direct Connect:** A dedicated private network connection between on-premises infrastructure and AWS offers more consistent network performance than traditional internet connections. By integrating these two technologies, you can ensure a high-performance, secure, and scalable connection between your on-premises environment and AWS Cloud. ## **Step-by-Step Guide: AWS Direct Connect with MPLS** AWS Direct Connect offers two main types of connections for establishing communication between your on-premises environment and AWS Cloud: **Dedicated Connections** and**Hosted Connections.** _**Note:- In this article, we have utilized Tata MPLS and AWS Direct Connect Partner, however depending on the use case and availability, one can go for other available partners as well.**_ ### **1. Dedicated Connections** A Dedicated Connection is a physical connection provided directly by AWS between your on-premises data center and an AWS Direct Connect location. ### **2. Hosted Connections** A Hosted Connection is a shared connection where an AWS Direct Connect Partner (Tata Communications) provides an infrastructure connection to an AWS Direct Connect location on your behalf. In this section, we will explore Hosted Connections in detail, discussing their setup, configuration, and the process of connecting to AWS via MPLS. ### **What is a Hosted Connection?** A Hosted Connection is a connection provisioned and managed by an AWS Direct Connect Partner, Tata Communications. Unlike Dedicated Connections, where AWS provides a direct physical link from your on-premises data center to an AWS Direct Connect location, Hosted Connections use shared infrastructure managed by the partner. The partner handles the physical infrastructure and provisioning, and you access AWS Cloud resources via a shared connection. #### **Key Features of Hosted Connections:** * **Lower Entry Cost:** Hosted Connections offers a more cost-effective solution as the AWS partner manages the infrastructure, removing the need for your business to invest in expensive hardware and installation. * **Scalability:** With Hosted Connections, businesses can start with lower bandwidth requirements (50 Mbps to 10 Gbps) and scale as needed without the upfront cost of dedicated hardware. * **Managed Service:** The partner, Tata Communications, takes care of provisioning, setup, monitoring, and troubleshooting, reducing your team's operational overhead. * **Flexible Bandwidth Options:** Hosted Connections come with flexible bandwidth options, typically ranging from 50 Mbps to 10 Gbps, allowing businesses to choose the right bandwidth for their needs. * **Quick Setup:** Because the partner manages the physical infrastructure, Hosted Connections can be set up quickly, ensuring faster time to market for cloud-based applications. ## **How do you configure a hosted connection with TATA MPLS?** Setting up a Hosted Connection via TATA MPLS requires several steps. These steps involve coordination between your on-premises infrastructure, TATA Communications, and AWS Direct Connect. Here’s a step-by-step guide: ### **Step 1: Choose Your AWS Direct Connect Partner** * Select an AWS Direct Connect Partner that supports MPLS connectivity (like Tata MPLS) based on your region and requirements * Work with TATA Communications to understand the available bandwidth options and select the appropriate bandwidth (50 Mbps to 10 Gbps) based on your needs. ### **Step 2: Request a Hosted Connection** * Once you’ve selected your bandwidth and partner, submit a request to your chosen AWS Direct Connect Partner ( Tata MPLS) to provision the Hosted Connection. * AWS Direct Connect partner TATA will provision the necessary infrastructure and set up the connection from their side to the AWS Direct Connect location. ### **Step 3: Provision the Hosted Connection in AWS** * After TATA provisions the connection, the AWS Direct Connect Partner will initiate the setup process on AWS’s side. You will receive the AWS Direct Connect Letter of Authorization and Connecting Facility Assignment (LOA-CFA), which is a critical document to proceed with connecting the Hosted Connection. * AWS will verify the connection, and once approved, it will be available for use. ### **Step 4: Establish BGP Routing** * With the Hosted Connection in place, you will need to configure Border Gateway Protocol (BGP) for routing between your on-premises network and AWS Cloud. * BGP ensures that the network traffic between your on-premises infrastructure and AWS Cloud is routed efficiently, dynamically adjusting routes in case of network failures or performance issues. ### **Setting Up BGP Routing** To establish efficient and dynamic routing between your on-premises infrastructure and AWS Cloud, follow these steps for BGP (Border Gateway Protocol) configuration: #### **Step i: Exchange BGP Details** * When setting up BGP routing, you will receive the following details: * AWS Side ASN * The ASN is provided by AWS (default: 64512 or custom upon request). * BGP IP Addresses * A pair of IP addresses for the BGP session, typically in a /30 subnet. * Example: * AWS Router IP: 192.168.1.1 * Customer Router IP: 192.168.1.2 * MD5 Authentication Key (Optional) * If enabled, AWS provides an MD5 key for securing the BGP session. * Prefixes Advertised by AWS * CIDR ranges of AWS resources that will be shared with your on-premises router. #### **Step ii: Configure Your On-Premises Router** **On your on-premises router:** * Set the BGP Neighbor * Add AWS's router IP as the BGP neighbor. * Advertise Your Prefixes * Specify the IP ranges (CIDR blocks) of your on-premises network to share with AWS. * Apply MD5 Key (if applicable) * Secure the BGP session with the provided MD5 key. * Configure Route Policies * Control the inbound and outbound routes to optimize traffic flow. #### **Step iii: Test and Verify** * Verify BGP Session * Ensure the BGP session state is Established. * Check Route Tables * Confirm that both AWS and on-premises prefixes are correctly advertised and visible in the routing tables. * Perform Connectivity Tests * Use ping or traceroute to verify connectivity through the Hosted Connection. ### **Step 5: Create a Virtual Private Gateway (VGW)** * **Navigate to the AWS Management Console:** * Go to VPC > Virtual Private Gateways. Virtual Private Gateways listed in AWS Management Console * **Create a VGW:** * Click Create Virtual Private Gateway. * Specify a name and enter your ASN (default: 64512 or a custom private ASN). * **Attach VGW to the VPC:** * Select the VGW. * Click Actions > Attach to VPC. * Choose the VPC you want to associate. ### **Step 6: Set Up VLANs and Virtual Interfaces** AWS Direct Connect uses **Virtual Interfaces (VIFs)** to separate traffic for different AWS services or environments (e.g., Public and Private). Set up **Private VIF** to connect to the AWS VPCs Service. Set up **Public VIF** to access AWS public services such as S3 or EC2 directly over the Direct Connect link. **Create a Private Virtual Interface (VIF)** **Navigate to AWS Direct Connect:** 1. Go to AWS Management Console > Direct Connect > Virtual Interfaces. 2. Create a Private VIF: * Click Create Virtual Interface. * Select Private Virtual Interface. * Provide the following details: * **Connection** * Select the AWS Direct Connect connection. * Virtual interface owner: Select a virtual interface owner like My AWS account. * Gateway type: Select the gateway type you want to use, such as Direct Connect Gateway (for multiple VPCs) or Virtual Private Gateway. * **Direct Connect gateway -** Select the gateway name. * **VLAN ID:** Enter the VLAN ID for traffic segmentation * **BGP ASN:** Use the same ASN as specified during VGW creation. * **IP Addresses:** Optionally, specify IP addresses for BGP peering (AWS provides default IPs if left blank). ### **Step 6: Update the Route Table** Updating the Route Table ensures that traffic between your on-premises infrastructure and AWS services is routed through the AWS Direct Connect link instead of traversing the public internet. **Steps to Modify the Route Table** * **Access Your AWS VPC Route Table** * Go to the Amazon VPC Console in the AWS Management Console. * Navigate to Route Tables under the Virtual Private Cloud section. * Identify the route table associated with the VPC where you want to direct traffic. * **Add a Route for Your On-Premises Network** * Edit the route table by clicking the Edit Routes button. * **Add a new route** * Destination: Specify the CIDR block of your on-premises network (e.g., 192.168.0.0/16). * Target: Select the Direct Connect Gateway (DX Gateway) or Virtual Private Gateway (VGW) associated with your Direct Connect connection. * Propagate Routes from the VGW (Optional). * If you're using a Virtual Private Gateway (VGW), enable route propagation to automatically add routes advertised by your on-premises BGP peers: * Go to the Route Tables section. * Select the route table and click Route Propagation. * Enable propagation for the Virtual Private Gateway linked to your Direct Connect. ### **Step 7: Testing the Connection** * Once the Hosted Connection is configured, you must test the link to ensure the connection is stable and performs as expected. Use AWS and TATA Communications' monitoring tools to track performance metrics such as latency, throughput, and uptime. * Conduct performance tests to verify the bandwidth and latency levels meet your business requirements. ## **Wrapping Up** By the end of this blog, you should be able to set up a Hosted Direct Connect connection. This document provides high-level information on how to establish a secure connection between your on-premises environment and the AWS Cloud using an MPLS-backed AWS Direct Connect setup. **References:** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Devops Engineer Neetesh specializes in designing, automating, and managing scalable DevOps pipelines across cloud-native infrastructures. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents CloudKeeper, a leading Cloud FinOps and cloud cost optimization solutions provider recently entered into a partnership with Solve.care, a global leader in integrating healthcare with blockchain solutions. The partnership is deemed by many to be a game-changer in the healthcare technology space. With the best of both the worlds of healthcare and cloud technologies joining hands, this is set to transform healthcare innovation on a global scale. Let’s understand the specifics of this alliance and the future it holds for healthcare, technology, and the emerging discipline of Cloud FinOps. ## **A partnership driven to transform healthcare** Solve.Care took a strategic decision to entrust the management of its AWS nodes to CloudKeeper. Through this collaboration, Solve.Care's powerful healthcare solutions will be combined with CloudKeeper's FinOps expertise to drive the company's mission of revolutionizing healthcare and improving operational efficiency. Solve aims to be at the forefront of the technological evolution in the healthcare sector aided by AI-powered cloud technologies. The advanced cloud optimization solutions by CloudKeeper will play a key role in enhancing the performance of Solve’s cloud infrastructure while addressing the limitations within the healthcare domain. ## **Accelerating Growth Trajectory with AI-Driven Cloud Technology** **Pradeep Goel, CEO of Solve.Care** , stated, "_Uniting our healthcare blockchain platform with CloudKeeper’s AI-powered cloud optimization is a significant milestone in Solve.Care’s journey to innovate and optimize its technological infrastructure. We are paving the way for a future where AI-driven cloud technology becomes more than a tool; it becomes a catalyst for fast growth and transformation that benefits our clients, partners, and the healthcare industry as a whole._ " **Deepak Mittal, CEO of CloudKeeper** , reiterates their commitment to driving efficiency and value through AI-powered cloud optimization. He stated that “ _CloudKeeper has always been driven by customer satisfaction and ensuring maximum benefits on cloud investments for our customers. We are excited to partner with Solve.Care in revolutionizing healthcare management through our advanced cloud optimization solutions. Together, we aim to drive efficiency, security, and accessibility in the healthcare industry._ ” He further highlighted that - _“working with Solve.Care gives us this unique opportunity to create a positive impact on millions of lives across the globe._ ” In the healthcare sector, security and accessibility are paramount to meeting the evolving needs of patients, healthcare providers, and organizations. CloudKeeper’s It transcends conventional approaches by integrating AI-driven cloud optimization to ensure organizations not only save costs but also ## **AI, Blockchain, and Data Analytics in Healthcare** Public health is at the forefront of all global economies and a lot is being invested into healthcare technologies for the betterment of patients worldwide. Emerging technologies like Artificial Intelligence (AI) and Blockchain can be game-changers when it comes to optimizing healthcare processes and ensuring better patient treatment and outcomes. AI, Blockchain, and predictive data analytics can help secure health records, monitor drug manufacturing and transportation, conduct trials and research, aid in diagnostic treatment, and even handle administrative duties, overall contributing to the comprehensive goals of efficiency and accessibility in healthcare services. Looking ahead, Solve.Care and CloudKeeper will also work together to explore new technologies like blockchain, artificial intelligence, and data analytics. ## **Conclusion** In a world where the demand for quality healthcare has become more critical than ever, CloudKeeper’s partnership with Solve.Care will certainly go a long way to bridge the gap between healthcare service providers and patients. With the help of the integration of Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Recently, the Everest Group surveyed 450 organizations globally across North America, Europe, and APAC to understand the cloud FinOps adoption patterns, buying trends, and key challenges. According to the Let’s examine the ## **Growing need for Cloud FinOps** In today's digital world, taming cloud bills is critical. This is where There are several benefits of practicing cloud FinOps in the organization, including: 1. **Improved cloud cost savings** - Cloud FinOps goes beyond basic cloud cost reduction. It's a strategic approach that optimizes cloud usage, eliminates inefficiencies, and ensures cloud cost optimization, paving the way for future innovation. 2. **Increased profitability** - Cloud FinOps implementation improves the financial performance of your business. As a result, there can be more opportunities to attract investments and boost stakeholder satisfaction. 3. **Increased transparency** - By tracking and understanding cloud costs, FinOps fosters transparency across teams. This shared accountability sparks productive discussions, ignites innovative ideas, and ultimately leads to more profitable outcomes that wouldn't be possible in a siloed environment. 4. **Better decision-making** - FinOps provides the data and insights that one needs to become a more decisive leader. It offers a ## **Understanding the Problem: Cloud FinOps Skill Gap in Business** The effectiveness of cloud FinOps hinges on skilled professionals who understand both finance and cloud complexities. The By addressing this skills gap, organizations can unlock the full potential of FinOps and benefit from cloud cost optimization. The widening cloud and IT skills gap significantly impacts organizational success. Businesses face potential consequences like: * **Missed financial goals:** Without skilled professionals managing cloud costs, overspending can derail financial targets. * **Stalled digital transformation:** The absence of skilled cloud and IT talent can hinder critical digital initiatives. * **Inefficient resource utilization:** Due to a lack of professional efficiency, there could be inefficient resource utilization. * **Difficulty in negotiating optimal pricing structures with cloud providers:** Skilled FinOps consulting professionals are in a better position to negotiate with the cloud providers and get a better deal. * **Lack of visibility and control over cloud finances:** A lack of visibility and accountability in cloud spending impact budgeting and forecasting. * **Inability to leverage cost-saving opportunities:** Without the right skills to continuously monitor and optimize cloud usage and costs, organizations may not be able to leverage multiple cloud cost saving opportunities. ## **The Solution: Bridging the Cloud FinOps Skill Gap** To mitigate these challenges, companies need to take proactive steps. Here's how to get started: 1. **Identify Skills Gaps:** Conduct a thorough assessment to identify critical skill sets missing within your organization. 2. **Invest in Upskilling:** Train existing employees to bridge the knowledge gap through targeted training programs and certifications. 3. **Consider Upskilling & Reskilling Programs:** Explore external resources that provide 4. **Attract and Retain Talent:** Develop competitive compensation packages and create a positive work environment to attract and retain qualified personnel. 5. **Hire dedicated FinOps professionals to manage cloud finances.** 6. **Partner with managed service providers (MSPs) with FinOps expertise:** 7. **Utilize cloud automation tools to streamline cost management tasks:** Cloud automation tools can automate repetitive tasks, generate real-time reports, and identify cloud cost optimization opportunities, ## **Benefits of building a FinOps culture** While the cloud and IT skills gap poses a significant challenge, FinOps (cloud financial management) offers a strategic solution by fostering a cross-functional culture that maximizes cloud value. Here's how: * **Executive Sponsorship:** Strong leadership buy-in encourages collaboration and prioritizes cloud skills development. * **Effective Governance:** Clear frameworks and policies provide a roadmap for responsible cloud use and optimization. * **Cross-Team Collaboration:** Breaking down silos between procurement, finance, DevOps, and security fosters knowledge sharing and facilitates efficient cloud management. By implementing these FinOps principles, companies can bridge the skills gap by: * **Promoting Skill Development:** Collaboration across teams encourages cross-training and knowledge exchange, organically developing the needed skills. * **Optimizing Resource Utilization:** Effective FinOps practices can reduce the dependency on specialized cloud expertise in the short term, allowing existing staff to manage resources efficiently. * **Data-Driven Decision Making:** FinOps leverages data and analytics, empowering teams to make informed decisions without extensive cloud knowledge. By proactively addressing the cloud and IT skills gap, businesses can overcome these challenges and achieve their digital transformation goals. Partnering with experienced FinOps consulting and Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents AWS EBS costs can significantly impact your cloud bill, and understanding how to utilize storage services effectively is crucial for lowered spending. Amazon Elastic Block Storage (EBS) is a scalable and high-performance block storage service designed for AWS EC2 instances. It provides persistent storage through EBS volumes. One of the key advantages of AWS EBS is the pay-as-you-go model, where you only pay for the storage resources you use. However, EBS volumes that are attached to EC2 instances retain data even when the instances are stopped or terminated. This means that the storage resources associated with the EBS volumes continue to incur costs, contributing to your overall AWS bill. Therefore, it's important to be mindful of this and In this blog, we will explore widely used best practices for AWS EBS cost optimization and its usage. ## **AWS EBS Volume Types** **1. General Purpose SSD (gp2):** This is the default and most commonly used EBS volume type. It offers a balance of price and performance for a wide range of workloads. General Purpose SSD volumes are suitable for most transactional workloads that require moderate IOPS performance. **2. Provisioned IOPS SSD (io1):** This EBS volume type is designed for applications that require high-performance storage with consistent and low-latency I/O. It allows you to specify the desired number of IOPS (input/output operations per second) when provisioning the volume. Provisioned IOPS SSD volumes are ideal for critical database workloads or applications that demand predictable and high-performance storage. **3. Throughput Optimized HDD (st1):** This volume type is optimized for frequently accessed, large sequential workloads that require high throughput but can tolerate higher latency. Throughput Optimized HDD volumes are well-suited for big data workloads, data warehouses, log processing, and streaming applications. **4. Cold HDD (sc1):** Cold HDD volumes are designed for less frequently accessed workloads with large data sets. They offer the lowest cost per gigabyte compared to other EBS volume types but with higher latency. Cold HDD volumes are suitable for workloads with sequential and cold data, such as backup storage, archival data, or long-term storage of infrequently accessed data. **5. Magnetic (standard):** This is the legacy EBS volume type, which is being phased out in favor of General Purpose SSD and other newer volume types. Magnetic volumes provide the lowest cost per gigabyte but with lower performance and higher latency compared to other EBS types. They are suitable for workloads with low I/O requirements or where cost optimization is the primary consideration. ## **Factors that Influence AWS EBS Costs** **1. EBS Volume Type:** AWS EBS offers different volume types, each with its own performance characteristics and pricing. The cost can vary depending on whether you choose General Purpose SSD, Provisioned IOPS SSD, Cold HDD, Throughput Optimized HDD, or other available types. **2. Volume Size:** The size of your EBS volumes directly affects the cost. As you increase the storage capacity, the pricing will incrementally rise. **3. Provisioned IOPS:** If you require high input/output operations per second (IOPS) for your applications, Provisioned IOPS SSD volumes provide guaranteed performance levels but at a higher cost. Provisioning more IOPS will increase the overall expense. **4. Data Transfer:** Data transfer costs can be a significant factor in your overall EBS expenses. This includes data transferred into and out of your EBS volumes, data transferred between availability zones, and data transferred to other AWS services. **5. Snapshots:** EBS snapshots, used for data backup and replication, incur costs based on the amount of data stored. The number and frequency of snapshots, as well as their retention periods, can influence expenses. **6. Storage Duration:** The length of time you retain EBS volumes, impacts your AWS EBS costs. If you have long-term storage needs or require frequent volume changes, it can affect your overall expenses. **7. Region and Availability Zone:** AWS EBS pricing can vary between regions and availability zones. Choosing the most cost-effective region and availability zone for your EBS resources can have an impact on your expenses. ## **Strategies to save money on AWS EBS Volumes** **1. Right-size your EBS volumes:** Regularly review the storage needs of your applications and adjust the volume sizes accordingly. Avoid overprovisioning by accurately estimating the required capacity. Downsizing volumes that are not fully utilized can help reduce costs. **2. Use appropriate volume types:** Select the EBS volume type that aligns with the performance requirements of your applications. Avoid using Provisioned IOPS SSD volumes unless necessary, as they come at a higher cost. General Purpose SSD volumes are often suitable for most workloads and offer a good balance between performance and cost. **3. Optimize snapshots:** EBS snapshots are used for backup and replication purposes. Evaluate your snapshot retention policies and delete unnecessary snapshots regularly. Implement lifecycle policies to automate the deletion of outdated snapshots. This helps minimize storage costs associated with snapshots. **4. Monitor and adjust storage duration:** Assess the storage duration requirements for your EBS volumes. If you have volumes that are no longer needed, consider deleting them to avoid unnecessary charges. For long-term storage needs, consider **5. Utilize volume elasticity:** Take advantage of the elasticity of AWS EBS volumes. With Amazon Elastic Volumes, you can dynamically adjust the size and performance characteristics of your EBS volumes without detaching them from the EC2 instances. This allows you to match the storage resources to the changing demands of your applications and optimize costs. **6. Leverage instance storage:** In certain scenarios, consider **7. Optimize data transfer:** **8. Explore AWS cost management tools:** Take advantage of By implementing these strategies, you can effectively manage your AWS EBS costs and optimize the utilization of storage resources, resulting in potential cost savings for your organization. _FinOps is a specialized branch that clubs together ways to engage cross-functional teams in a collaborative effort to control cloud costs. Getting a_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents In Modern Container-Based Application Deployments or Microservices Environments, Scalability is one of the most important aspects to be considered. Therefore As we are seeing that K8s has become a leader for container orchestration, therefore we need to think about how we can scale applications deployed on K8s on demand and scale down when not in use. However, almost every cloud provider comes with a respective **Cluster Autoscaler** , which in addition to container autoscaling makes a powerful duo to scale any applications with minimal cloud cost. ## **Cluster Autoscaler** It is a capability provided by different cloud providers to scale in-scale out compute resources (instances,VM) on demand based on application workload. In general, scaling works two ways: * CA looks for pods that can’t be scheduled on nodes due to insufficient resources, then it automatically increases the number of computenodes. In case there are no pods running on compute nodes then it will scale in that node automatically. * In the K8s cluster **Horizontal Pod Autoscaler****(HPA)** uses the Metrics Server to monitor and check for resource demand. In case of application resource requirement, HPA will scale out pods horizontally by increasing PODS count and scale in as per lower resources requirement. ## **What is KEDA?** **KEDA** is a KEDA Architecture ## **How KEDA works?** In K8s KEDA implement three roles as below: 1. **Agent** — This act runs a container named keda-operator whose main aim is to detect whether the deployment is active or passive 2. **Metrics****** — This runs as a keda-operator-metrics-api server container whose primary aim is to expose external event sources data to K8s HPA for operating scaling and serve metrics. 3. **Admission Webhooks** — This is K8s CRD(Custom Resource Definition) whose primary role is to validate the resource changes in order to prevent misconfiguration. It also enforces best practices by using an ### **ScaledObject** ScaledObject is a K8s CRD (Custom Resource Definition) whose main goal is to define how KEDA should scale an application and what triggers to use. In this article, we will be going to see how we can implement KEDA to autoscale RabbitMQ Producers & Consumers Pods in the Kubernetes cluster, based on the queue count events. ### **Prerequisites** * ****Kubernetes cluster** : **We will need a running Kubernetes cluster. In case Kubernetes Cluster is not available then we can follow the instructions to * **Docker Hub Account** : An account at Docker Hub for storing Docker images that we will create during this tutorial. Refer to the * **kubectl** : Refer to * **Helm** : Here we will use Helm ( ## **Installation of KEDA** There are several ways to install KEDA in a K8s Cluster. Here we will be using Helm to install it. Note: KEDA creates multiple deployments which is highly configurable through changes in values in a .yaml file. ## **Deploying RabbitMQ Application** _RabbitMQ Application Deployment includes below steps:_ ### **1. Deploy RabbitMQ Cluster K8s Operator** _For more, you can refer_ ### **2. Deploy RabbitMQ Server Cluster** This deployment will create K8s CRD as RabbitMQCluster Server with replicas _For more, you can refer_ ### **3. Deploy RabbitMQ Consumer and Producer** ### **Deploying KEDA Event Scaler** This event scaler is RabbitMQ based which consists of few K8s KEDA objects and scaling will be done on the basis of queue count i.e. if the publisher is not publishing a message then KEDA scaled object will not scale up consumer pods. Hence Autoscaling will be done based on the event trigger. **1. Encrypt RabbitMQ Connection String** **2. Create a Secret for the Connection String** **3. Create Trigger Authentication** **4. Deploy KEDA Scaled Object for Scaling** ### **Testing Auto-Scaling with Event Scaler** In order to test scaling with Event Scaler, We have updated the replica count of publisher deployment to “0” i.e. publisher will not produce or publish any messages in the queue, therefore, queue count will become zero, Hence KEDA Scaled Object will start scaling down the consumer pods. KEDA is a powerful tool that can help you to optimize your cloud costs and improve the performance of your Kubernetes workloads. Here are some of the benefits of using KEDA: **Cost savings:** KEDA can help you to save money by automatically scaling your workloads up and down based on demand. This can help you to avoid overprovisioning resources, which can lead to wasted resources and unnecessary costs. **Performance improvement:** KEDA can help you to improve the performance of your Kubernetes workloads by ensuring that they have the right amount of resources available. This can help to reduce latency and improve throughput. **Scalability:** KEDA can help you to scale your Kubernetes workloads up and down to meet demand. This can help you to ensure that your applications are always available and that they are able to handle peak traffic loads. __Would you like to know more about the best practices that can streamline your Kubernetes workloads and cloud architecture as a whole?__ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents ## **Understanding the Initial Challenges** When the customer reached out to us, they weren’t starting from scratch. Their But under the hood, they were struggling with persistent inefficiencies. CPU utilization across their clusters was low. ## **Diagnosing Utilization and Instance Fit** One of the first things we found was that their clusters, although configured well, weren’t running efficiently. Karpenter’s bin-packing was not effective, which meant that many of their We recommended moving these memory-heavy workloads to R-series instances, which offer higher memory-to-CPU ratios ideal for services that are RAM-intensive but compute-light. While R-series instances can be slightly more expensive on a per-vCPU basis, they make better use of allocated memory when CPU demand is low, helping improve overall bin-packing. The team had primarily been using M-series, which provides a balanced 1:4 memory-to-vCPU ratio. They found M-series more predictable across mixed workloads, particularly for services that don’t fully saturate memory or CPU. After discussion, we agreed that a blend of both families, using R-series for clearly memory-heavy deployments and M-series for more balanced ones, would achieve a better cost-to-performance ratio without compromising stability. which provide better memory-to-CPU ratios. The team explained they had been using M-series instances more often, as their memory-to-CPU ratio was usually 1:4. We agreed that M-series was still a good choice for many workloads, but emphasized that resource requests needed to be tuned based on actual usage. During this process, we also clarified that average CPU is a better metric for right-sizing decisions than max CPU, since container workloads can burst briefly without justifying higher provisioning. ## **Improving Scheduling and Node Pool Strategy** We found that some node pools were being consolidated too aggressively. In earlier setups, pods were getting evicted frequently because of short idle timers, sometimes as short as one minute. This led to constant pod churn and unnecessary scheduling overhead. The team had already begun segmenting workloads into different node pools: API services on on-demand nodes, cron jobs on spot-backed pools, and worker services on their own pool. This was a strong move in the right direction. We helped further by reviewing their consolidation settings and advising more realistic consolidation windows between 15 and 30 minutes. ## **Introducing and Applying Vertical Pod Autoscaler (VPA)** To right-size pods, we introduced them to the ## **Correcting Oversized Instance Provisioning** Another problem was oversized instance types in Karpenter. We discovered this during a configuration audit of their NodeClaim policies, where instance types like 32xlarge and 48xlarge were unintentionally allowed. These configurations had gone unnoticed initially because they did not always result in active provisioning, but they created the risk of provisioning large, expensive nodes during bursts or capacity crunches. We helped the team identify these through a combination of reviewing Karpenter configurations and validating the NodeClaim templates directly. Once spotted, we worked together to restrict the instance types to a more appropriate range, targeting sizes like 4xlarge or 8xlarge, depending on the workload class. Their NodeClaims had allowed provisioning of massive instances like 32xlarge and 48xlarge, which wasn’t intentional. We reviewed the configuration and helped them restrict instance types to more practical sizes like 4xlarge or 8xlarge, depending on the workload class. They also set up a dedicated node pool for cron jobs that scaled to zero when not in use and consolidated workloads based on job frequency. This pool had a five-minute termination policy and was isolated from ## **Cost Attribution and Observability** For observability and cost tracking, they had started using Kubecost but were facing issues with configuration and visibility. We demonstrated how ## **Results and Measurable Improvements** The impact of these changes was significant. CPU allocation dropped across clusters, and Amazon EC2 bin-packing improved. Pod churn decreased as consolidation settings were made more realistic. In some environments, pod lifetimes increased from a few hours to several days. The team also cleaned up unused NodePools, replaced ## **Final Infrastructure Audit and Security Recommendations** As part of our final audit, we went through their ## **Long-Term Adoption and Early Outcomes** At the end of the engagement, the customer committed to applying the recommendations across all their production regions. Within the first 48 hours of implementation, they observed a meaningful drop in CPU over-allocation and saw pod restart rates decline significantly. ## **Reflections and Lessons Learned** What we learned from this engagement is that having the right tools is only the first step. Effective Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Gourav specializes in helping organizations design secure and scalable Kubernetes infrastructures on AWS. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents While deploying a database on Amazon EKS, suddenly your pods crashed with `Too many open files` errors, followed by AWS CNI plugin failures breaking your networking? Here is the step following which you can solve it:- ## **Introduction** Running workloads on ## **The Problem** While spinning up a database pod, the logs showed errors like: * Too many open files ulimit: open files limit reached Initially, this appeared to be a straightforward resource configuration issue. However, soon after, the AWS CNI plugin pods (`aws-node`) were restarting repeatedly with errors such as: * failed to setup eni: failed to set ulimit failed to allocate ENI: unable to assign IP address This created a failure: not only was the database pod crashing, but also the other workloads started failing due to broken pod networking. ## **Root Cause Analysis** I have listed the breakdown into three parts : 1. Checking Node Limits: Running `ulimit -n` on the 2. Reviewing Launch Template Configurations: Our node group was created with an AWS Launch Template. Although we had increased instance size, we hadn’t tuned OS-level limits. 3. Inspecting the AWS CNI DaemonSet: The CNI plugin relies on host networking and often inherits system limits. If the host settings are insufficient, pods using the plugin fail too. ## **The Solution** ### **Step 1: Update Launch Template** I modified the Launch Template to apply proper ulimit values via AWS EC2 user data: **#!/bin/bash** **echo "fs.file-max = 2097152" >> /etc/sysctl.conf ** **echo "* soft nofile 65535" >> /etc/security/limits.conf ** **echo "* hard nofile 65535" >> /etc/security/limits.conf ** **ulimit -n 65535** ### **Step 2: Rolling Update of Node Group** I performed a rolling replacement of nodes in the Amazon EKS Node Group so that new instances inherited the updated limits. ### **Step 3: Restart AWS CNI Plugin Pods** Finally, I restarted the aws-node DaemonSet: **kubectl rollout restart ds aws-node -n kube-system** This reloaded the CNI plugin with the corrected host limits. ## **Results** * The database pod deployed successfully without hitting file descriptor limits. * The CNI plugin stabilised, and pod networking returned to normal. * Node-level health metrics improved, and no further restarts occurred. ## **Key Points** * Always tune OS-level limits when running stateful or networking-heavy workloads in Amazon EKS. * Launch Templates + User Data are a powerful way to enforce consistent settings across nodes. * Don’t just fix the symptom (application)—trace the failure upstream (in this case, to node and CNI configurations). * Consider using Amazon Bottlerocket OS or Managed Node Groups with pre-validated limits to reduce operational overhead. ## **Conclusion** What looked like a database-specific error turned out to be a deeper issue with EKS worker node system limits. By adjusting the ulimit settings in the Launch Template and restarting the AWS CNI plugin, I restored stability to the cluster. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Aman is a skilled Cloud Infrastructure Specialist with expertise in designing, managing, and optimising scalable cloud environments. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents As our web application footprint expanded, we realized that static filtering alone was no longer enough to protect the platform against modern traffic abuse patterns. We needed a security design that could respond to behavioral signals, not only signature-based payloads, while still preserving smooth performance for legitimate users. Our production implementation focused on **Reduce abusive external traffic** without interrupting trusted internal traffic that supports monitoring, integrations, and operational workflows. To achieve this, we implemented a layered strategy that combined custom blocking logic, rate-based controls, internal IP whitelisting, and AWS managed rule groups. Instead of treating each rule as an isolated control, we intentionally designed the rule ordering so that trusted flows are handled first, and unknown traffic is progressively filtered through stricter checks. This approach gave us better security outcomes and a more stable operational model. ## **Why Rate Limiting Matters for Web Applications** Many attacks begin as high-frequency traffic behavior rather than explicit exploit payloads, which means they can appear harmless in isolated request analysis while still causing serious operational impact. Brute-force attempts, endpoint scraping, token enumeration, and reconnaissance bursts often stem from repeated requests originating from a limited set of IPs. If such traffic is allowed to scale unchecked, it can degrade user experience, increase backend load, and hide more targeted attack attempts inside noisy request streams. Rate limiting gives security teams strong behavioral control by enforcing request thresholds at the edge and reducing abuse before it reaches core services. In our case, we configured AWS WAF to block traffic when a single source exceeded **1000 requests per IP** in the configured evaluation window. That threshold was selected after traffic baseline review so it would suppress abusive spikes without harming normal user interaction patterns. The result was a measurable reduction in noisy traffic and a clearer separation between legitimate traffic variation and malicious request bursts. ## **Our Implementation Approach in AWS WAF** We approached implementation as a policy architecture exercise, not just a rule creation task, because control sequencing matters as much as control selection. The first design principle was to explicitly protect trusted internal traffic before evaluating external threat logic, which prevented accidental disruption to business-critical dependencies. The second principle was to use layered enforcement so that obvious malicious patterns are dropped quickly while more ambiguous behavior is evaluated by rate and managed by intelligence controls. The third principle was to roll out high-impact rules in observation mode first, then promote to block mode only after log validation. This process helped us avoid false-positive incidents and gave teams confidence in production enforcement decisions. We also aligned logging, dashboards, and alerting with each rule category so operational tuning could happen continuously rather than reactively. By combining technical enforcement with disciplined rollout governance, we converted WAF from a static configuration into an active security control plane. * Custom blocking rules for known high-risk request patterns. * Rate-based control for high-volume abuse from single IP sources. * Internal IP whitelisting for trusted service and enterprise traffic. AWS managed rule groups for broad threat detection coverage. ### **1. Custom Blocking Rules for Known Malicious Patterns** Before enabling broad behavioral controls, we implemented precise custom filters for request patterns that have little to no legitimate business value in our environment. This included known sensitive paths, repository exposure attempts, and technology probe signatures that are commonly used in reconnaissance campaigns. Blocking these requests early improved signal quality in our logs because low-effort scanning traffic was reduced before deeper analysis stages. It also lowered unnecessary load on backend services by preventing pointless request traversal through application components. We treated these rules as high-confidence controls, but still validated hit patterns during early rollout to confirm no legitimate path dependencies were overlooked. This gave us a clean first layer that removed predictable noise and made subsequent security tuning more effective. In practical terms, custom rules became the fast rejection layer that complements dynamic controls such as rate limiting. * Sensitive administrative URI paths. * Requests targeting exposed repository artifacts like **.git**. * Stack-specific crawl patterns not used by our application runtime. ### **2. Rate Limiting Rule for Abuse Control** To reduce rollout risk, we first evaluated the rule in **monitoring mode** on ‘**COUNT** ’ action and analyzed observed hit patterns against expected traffic baselines. Once we confirmed the threshold behavior was aligned with production traffic, we promoted the rule to ‘**BLOCK** ’ mode and monitored the impact through dashboards and alerting. This staged activation approach helped us avoid user-facing regressions while still moving quickly toward stronger enforcement. Over time, rate control became one of the most operationally valuable protections because it reliably reduced repetitive traffic abuse during burst events. It also improved analyst efficiency by turning diffuse traffic spikes into clear policy-triggered events. * Per-source request rate tracking. * A threshold of 1000 requests per IP. * Progressive rollout from Count to Block after validation. ### **3. Internal Request Whitelisting** A critical requirement in our design was preserving reliability for internal systems that must continue functioning during any external attack event. Internal services such as health-check pipelines, enterprise integrations, and controlled automation can naturally produce traffic profiles that resemble high-volume behavior under specific conditions. Without explicit exceptions, generic enforcement controls could inadvertently affect these trusted dependencies and create operational instability. To prevent this, we created IP allowlists using Amazon Web Services WAF IP sets and placed allow rules at a higher priority than rate and threat rules. This ensured trusted internal CIDR ranges were evaluated first and passed through without unnecessary friction. We also implemented governance around allowlist updates so additions remain intentional, documented, and periodically reviewed for relevance. That combination of explicit trust boundaries and rule precedence gave us strong external protection while maintaining internal continuity. * Corporate NAT egress ranges. * Monitoring and health-check sources. * Approved integration and platform service IP ranges. ## **Extending Beyond Rate Limiting: Additional Controls** Rate limiting materially improves resilience, but by itself, it does not provide comprehensive protection against diverse web attack paths. We therefore extended the control set with geofencing and managed rule intelligence to improve both preventive coverage and detection depth. This broader model allowed us to address traffic context, payload risk, and source reputation in a coordinated manner. Instead of enforcing every rule with immediate block actions, we used a risk-weighted strategy where uncertain signals could start in count or challenge mode. That gave us cleaner telemetry and reduced false positives before strict enforcement was applied. The overall effect was a policy framework that is both defensive and adaptable, which is essential for long-term web security operations. ### **GeoFencing** Geofencing helps to reduce irrelevant exposure by aligning traffic acceptance with your actual business geography. Where traffic originated from regions with no valid customer or partner footprint, one can apply block or challenge policies based on risk tolerance and observed request behavior. For regions with legitimate demand, use more conservative enforcement and monitor anomalies before adjusting controls. This prevents overblocking while still shrinking the attack surface in a measurable way. Geo controls are especially useful during burst events where request origins are clustered in unexpected locations. By combining geography with rate and signature context, we can improve decision quality and reduce unnecessary alert fatigue. Geofencing must not be treated as a Standalone Defense, but as a high-value contextual layer in the overall Amazon WAF architecture. ### **AWS Managed Rule Groups** AWS managed rule groups gave us broad baseline protection against common web threats without requiring constant manual signature maintenance. These managed controls helped detect and block SQL injection attempts, cross-site scripting payloads, suspicious input constructs, and known high-risk source categories. We still tuned rule actions thoughtfully by using a phased model for rules that showed mixed confidence in early telemetry. High-confidence malicious matches were enforced as block actions, while ambiguous patterns were temporarily monitored to assess false-positive potential. This approach preserved security strength while maintaining application reliability and user experience. Managed rules also improved operational consistency because updates and improvements are continuously delivered as part of the managed service. In practice, they became a strong force multiplier that complemented our customs and behavioral controls. * SQL injection detection. * Cross-site scripting protection. * Known bad input signatures. * Anonymous and reputation-based source intelligence. * Linux and Unix exploit pattern defenses. ### **Bot and Reputation Awareness** Not all suspicious traffic should be blocked immediately, especially when the behavior is anomalous but not conclusively malicious. For such cases, we used count or challenge modes to gather telemetry and validate risk before applying hard enforcement. This reduced false-positive risk and gave security teams better context for tuning thresholds and action policies. Reputation-aware controls also helped prioritize attention toward sources with a higher likelihood of abuse. Over time, this improved the quality of both automated responses and analyst-led investigations. The key benefit was confidence, since enforcement decisions were backed by evidence rather than assumption. That discipline made our AWS WAF policy more robust and easier to evolve. Generic Must-Have WAF Rule Guide For teams building a production-ready web ACL baseline, the following controls are essential and should be implemented with clear rule precedence and observability: * Associate web ACLs across all internet-facing entry points consistently. * Place trusted internal allowlist rules at top priority. * Apply rate-based protection for abuse-prone paths and overall traffic. * Enable managed rule groups for common exploits and reputation coverage. * Use geo controls where business traffic boundaries are well defined. * Harden sensitive paths, methods, and mutation endpoints explicitly. * Inspect headers, query strings, and bodies for malicious payload signals. * Enable full logging, dashboards, and alerting for continuous tuning. * Roll out new rules in Count mode before promoting to Block. * Maintain exception governance with documented owner and expiry review. ## **Conclusion** Rate limiting remains one of the highest-leverage controls for public web applications when implemented with careful precedence and internal trust exceptions. When combined with AWS managed protections, geofencing, and structured rollout governance, it can significantly reduce external abuse without compromising service continuity. The real value comes from treating WAF as a continuously tuned control plane backed by logs, telemetry, and periodic review. Organizations that adopt this layered approach typically gain stronger security outcomes and clearer operational predictability. Our experience confirmed that protection and reliability can coexist when policy design is intentional and context-aware. This is the model we recommend for teams looking to mature web application defense in production environments. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Aryan is a cloud infrastructure and DevOps enthusiast with a sharp focus on cloud cost optimization and automating complex, manual workflows across AWS and Azure. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents Amazon CloudFront is a **fast content delivery network (CDN) service** that securely delivers data, videos, applications, and APIs to customers globally with low latency, high transfer speeds, all within a developer-friendly environment. When building performant and globally distributed applications, AWS now offers a more lightweight and cost-effective alternative: CloudFront Functions. In this post, we’ll walk through: * What CloudFront Functions are * How to implement redirection logic using them * Why you should choose CloudFront Functions over Lambda@Edge for certain use cases * When to choose Lambda@Edge ## **What Are CloudFront Functions?** CloudFront Functions are **lightweight, JavaScript-based functions** that run at the CloudFront edge locations. They’re ideal for simple, high-performance tasks that need to execute very quickly on viewer requests — such as **header manipulation, redirects, and URL rewrites.** Unlike Lambda@Edge, which uses full-fledged AWS Lambda functions, CloudFront Functions: * Have**ultra-low latency** (microsecond-level) * They are **cheaper and faster to deploy** * Can **scale to millions of requests per second** * Run only during the viewer request/response phases, not at origin request/response Cloudfront Functions can be attached at 2 ends : 1. **Viewer Request** - Runs before request reaches Cloudfront (edge cache) 2. **Viewer Response** - Runs before Cloudfront forwards request to the client (edge cache) **Source: AWS** If you need some of the capabilities of Lambda@Edge that are not available with CloudFront Functions, such as network access or a longer execution time, you can still use Lambda@Edge before and after content is cached by CloudFront. **Source: AWS** ## **Use Case: URL Redirection** Let’s say if the user visits: ### **How to Deploy** 1. Go to the **CloudFront Console** 2. Click on **Functions → Create function** 3. Give a name: Cloudfront-redirection 4. Paste the below code into the editor 5. Click Save and Publish the function 6. Click Add Association: * Select the CloudFront Distribution * Choose the Viewer Request event * Attach it to the cache behavior that covers /test1.html ## **Why you should choose CloudFront Functions over Lambda@Edge for certain use cases** ## **Benefits of Cloudfront Functions over Lambda@Edge :** 1. **Ultra-Low Latency (Sub-Millisecond Execution)** CloudFront Functions **are optimized for speed and run in microseconds**. If you want seamless, nearly-instant redirection (e.g., /test1 → /test2.html), CloudFront Functions are measurably faster. 2. **Significantly Lower Cost** **CloudFront Functions are much cheaper than Lambda@Edge** , especially at scale. With Lambda@Edge, you pay $0.60 per 1 million requests plus the execution time. With CloudFront Functions, you pay $0.10 per 1 million Invocations and nothing for execution time. 3. **Instant Deployments (No Regional Propagation Delay)** **Changes to CloudFront Functions propagate in seconds globally**. With Lambda@Edge, changes must be replicated to regional edge locations, which takes more time than CloudFront functions ## **When to use Lambda@Edge:** * For more complex logic that requires access to external services (e.g., other AWS services). * When you need to interact with the origin (e.g., for content generation or origin failover). * When you need to support origin requests or response triggers. * When you need more compute power or longer execution time * Use of non-JS languages (like Python) ## **Conclusion** CloudFront Functions offer a powerful, lightweight, and cost-effective way to implement edge-level logic like URL redirection with minimal latency and near-instant deployments. For use cases that demand ultra-fast performance and simplicity—such as header manipulation, basic routing, or conditional redirects—they're an excellent alternative to Lambda@Edge. While Lambda@Edge remains essential for more complex scenarios that involve origin access, extended execution time, or integrations with other AWS services, CloudFront Functions shine when we need blazing-fast performance at a fraction of the cost. By leveraging the right implementation, we can build smarter, more efficient, and globally responsive applications with AWS. Whether we are optimizing for performance, cost, or both, CloudFront Functions will always be the best fit. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Rohit is passionate about designing and implementing scalable, secure, and efficient DevOps solutions including automation pipelines, cloud architectures, and infrastructure as code. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents In today's cloud-native landscape, API gateways play a critical role in serverless and microservices architectures. This is a powerful tool for building scalable APIs, but it's also easy to overlook the cost-effectiveness, especially if the APIs are frequently called or redundant. For FinOps practitioners who are sure to focus on reducing costs without compromising, the use of API Gateways integrated with a cache is a game-changer. ## **What Is API Gateway Caching?** Amazon API Gateway provides integrated response caching, interfering with edge **layer endpoints** , eliminating the need to **access back-end services** (such as Lambda, EC2, RDS) for each request. Here’s how it works: * When caching is enabled on a **stage or method** , API Gateway stores responses in an in-memory cache. * Subsequent requests with the same parameters hit the cache instead of the backend. * You control cache **TTL (Time to Live)** and **cache keys** for precision. ## **How Should Cache be Handled?** **1. Reduce Backend Invocation Costs** **Back-end views** (such as Lambda or RDS calls) often incur the majority of API-related costs. These calls are **avoided in intermediate storage** if the same query from the cache is being operated on. **2. Control Data Transfer Charges** Output data transmission (especially for large payloads) is reduced, leading to savings in **data transmission costs (DTO)**. **3. Enhance User Experience** Faster response times and lower latency mean you don’t need to scale up infra (saving both cost and operational effort). ## **Use Case** Suppose you want to run the Product Catalog API for your e-commerce platform. To retrieve the product listings. **Without caching:** * Every user requests to call the backend service. * During high usage, our backend suffers from the load, and it impacts the performance. * Each query adds latency due to DB access and data processing. **With Caching Enabled:** Multiplying this by multiple APIs can save **thousands of dollars each year**. ## **How to Enable Caching (Step-by-Step)** Sign in to the API Gateway * Choose Stages. * In the Stages list for the API, choose the stage. * In the Stage details section, choose Edit. * Under Additional settings, for Cache settings, turn on Provision API cache. * This provides a cache cluster for your stage. * To activate caching for your stage, turn on Default method-level caching. This turns on method-level caching for all **GET** methods on your stage. Any additional **GET** methods that you deploy to this stage will have a method-level cache. Note: If you have an existing setting for a method-level cache, changing the default method-level caching setting doesn't affect that existing setting. **Note:** If you have an existing setting for a method-level cache, changing the default method-level caching setting doesn't affect that existing setting. * Choose Save changes. For more information, please refer to the **Pro Tip:** Use stage variables to toggle caching across environments without redeploying code. ## **When to Use API Gateway Caching** **Ideal For:** * Read-heavy, infrequently changing endpoints (e.g., product catalog, FAQs, blog posts). * Microservices with repetitive payloads. * APIs fronting expensive operations (DB lookups, ML inference). **Avoid Caching When:** Data changes frequently (e.g., real-time stock prices). You require request-by-request freshness (e.g., personalized responses). ## **Best Practices** ## **Conclusion** API Gateway Caching is one of the easiest ways to reduce costs and improve performance. Doing more in less amounts. If you're managing serverless APIs or want to advise your team on cost strategies, put caching in your roadmap today. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Software Engineer Varshit is a Senior Software Engineer with over five years of experience in DevOps and Platform Engineering. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents In today's digital age, businesses are increasingly leveraging cloud computing to drive innovation and agility. However, amidst the myriad benefits lie the complexities of managing cloud costs effectively. Recognizing this challenge, CloudKeeper organized FinOps Accelerate, a panel discussion series aimed at addressing ## **Top Four Mistakes in FinOps Adoption** The discussion dives into four critical subtopics: **Fumbles in equating FinOps solely with cloud cost reduction, overlooking its broader scope:** Many firms make the mistake of ignoring the wider use of FinOps and instead equate it only with cloud cost reduction. This limited viewpoint frequently results in lost chances for innovation and optimization in cloud resource management. **Fumbles in collaboration amongst teams:** A frequent cause of failure in FinOps adoption is the absence of coordination between the development, operations, and finance teams. Organizations find it difficult to maximize the value of their cloud investments and optimize cloud expenditures in the absence of cross-functional alignment. **Fumbles in setting the right KPIs for FinOps implementation and tracking them:** Setting the **Fumbles in choosing the right FinOps tools and processes:** The process of ## **Speakers of the Panel Discussion** The panel discussion was joined by distinguished speakers, each bringing their unique expertise to the conversation. * * * The session was moderated by ## **Key takeaways of the panel discussion** The discussion kicked off with the acknowledgment that many organizations prioritize immediate cloud cost savings when adopting FinOps, with a significant percentage focusing solely on this aspect. However, pigeonholing FinOps as a cost-cutting measure fails to recognize its Emphasizing a shift from cloud cost reduction to value creation, panelists advocated aligning cloud spend with business goals for agility and innovation. Shared ownership and a nuanced understanding of cloud costs were highlighted for informed decisions. "Return on Cloud Spend" (ROCS) was introduced as a metric for measuring business value derived from cloud spending. A proactive approach focusing on long-term value creation and data-driven decision-making was emphasized. By embracing FinOps as a strategic framework, organizations can embark on a During the discussion on team collaboration, the panel addressed They underscored the need for a common language across various enterprise silos, essential for successful FinOps practices. The panel stressed the significance of executive buy-in, acknowledging leadership support as crucial for integrating FinOps principles into day-to-day activities. Practical strategies for enhancing team collaboration included establishing a common language, joint ownership of budgets, and real-time access to reports. Additionally, they advocated for involving engineering teams and defining clear roles for centralized and decentralized FinOps teams. The conversation then delves into the Continuing the discussion from the challenges of setting and tracking the right KPIs, the conversation shifts towards Panelists emphasize the importance of assessing organizational needs and aligning tools with specific goals and objectives. They caution against the temptation to either build internal solutions or rely solely on single commercial tools. Instead, they advocate for a balanced approach, leveraging a mix of cloud-native, commercial, and internal tools. Key considerations include interoperability, flexibility, and the ability to curate data from various sources. Panelists also stressed the importance of building a tooling capability matrix to evaluate and select tools based on their strengths and alignment with organizational capabilities. Additionally, leveraging existing tools within the organization, such as Power BI, can provide a foundation for the initial visualization of KPIs. Ultimately, the conclusion was the choice of tools should be tailored to suit the unique needs and objectives of each organization. Panelists emphasize the importance of assessing organizational needs and aligning tools with specific goals and objectives. They caution against the temptation to either build internal solutions or rely solely on single commercial tools. Instead, they advocate for a balanced approach, leveraging a mix of cloud-native, commercial, and internal tools. Key considerations include interoperability, flexibility, and the ability to curate data from various sources. Panelists also stressed the importance of building a tooling capability matrix to evaluate and select tools based on their strengths and alignment with organizational capabilities. Additionally, leveraging existing tools within the organization, such as Power BI, can provide a foundation for the initial visualization of KPIs. Ultimately, the conclusion was the choice of tools should be tailored to suit the unique needs and objectives of each organization. In conclusion, navigating the challenges of FinOps implementation requires a nuanced approach, from Watch the complete panel discussion Interested in joining our next FinOps Accelerate? Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents “We cannot optimize what we cannot see.” Looking at the dynamic nature of cloud management in today’s time, that’s more true than ever. If you are among those entities that are leveraging the cost optimization offered by the ## **The Issue with Managing AWS EDP Spend Today** Theoretically, everything looks good for Enterprise Commitment from a cost point of view i.e. commit to spending a big amount and in lieu of it, you can get above average discounts. But what happens when: * There is no track of the cost, and teams keep on over-consuming. * Projects underdeliver, leaving the spend unused? * Are there different definitions of budget for Finance and Engineering? This major disconnect at times results in **overspending, sub-optimal utilization of discounts** , and **frustrated teams.** There are some tools available that display only the snapshots or lagging reports, but this is not what businesses need. Below is the actual requirement of an aware business unit: * A real-time dashboard * that has knowledge of AWS EDP pricing * and facilitates teams to act before the cost overruns (or underspends), not react That is the real reason behind bringing in the AWS EDP Tracker in CloudKeeper Lens. ## **What is the AWS EDP Tracker?** It is a purpose-built, real-time interactive dashboard in CloudKeeper Lens, built to facilitate you: * Keep a track of the actual and forecasted AWS EDP spend for the entire tenure of EDP (1st year, 2nd year, 3rd year, and so on). * Compare costs involved in AWS EDP,that is, spend that was committed, actual spend, and what the forecast would be based on the current trend. * Visualize and draw patterns from monthly spends, deviation from the committed amount and the overall health of the system. * Take corrective actions to ensure the delta between committed spend and actual spend gets reduced. Irrespective of what your EDP worth is, the AWS EDP tracker makes it very convenient and easy for you to track and manage the monthly and yearly spends. ## **What is in it for you?** This is not just another dashboard for tracking the spend, it is much more than that. It’s your AWS EDP cloud spend control unit. **1. Stay aware of the budget and actual spend — Always** This tool allows you to have the visibility of real-time actual spend and forecasted costs, which keeps you always aware of AWS EDP spend, and you can also draw a lot of inferences by understanding the spending patterns. No more unpleasant surprises at the end of the financial year. **2. Optimize Savings** Ensure that you are not **3. Enable Smart, Timely Decisions** Tracking the AWS EDP monthly spending trends helps in identifying the cost patterns so that reallocation decisions can be taken. For example, moving workloads to adjust the spend, pausing some services, or reallocating resources. **4. Single view of AWS EDP spends for all teams** Different teams within the company, such as the Engineering team, the Finance department, and DevOps, all stakeholders get to access the same dashboard for AWS EDP spend trends. No more misalignment or miscommunication among the groups. **5. Own your Cloud FinOps** As per FinOps, there should be accountability for cloud spend within the teams. The AWS EDP Tracker serves as the fundamental tool for any company that is trying to ## **Feature Highlights** Below are the functionalities that customers would get in the AWS EDP Tracker: **1. Tenure-Based Cost Granularity** Track year-by-year AWS EDP spends and compare it with your commitments to understand the deviation. It gives a good idea of the pace at which spending is being done and the current status of the overall health of the system. **Tenure-Based Cost Granularity - A snapshot of AWS EDP Tracker** **2. Actual spend vs. Committed value vs. Forecasted spend** Track how many dollars have been spent to date, what is the forecasted spend, and how close or far the value is to the committed amount. This helps in ensuring that you are not underspending so that you do not have to pay for resources that you never used. **3. Health Indicators** Users can see in real time that, are they spending optimally or underspending, or the costs are touching the roof. This feature gives an indication to the customers whether there is any need for any action to be taken. **4. Month-wise spend breakdown** Granular month-on-month tracking to identify sudden increases or decreases in cloud spending so that corrective measures can be taken immediately instead of waiting for the entire year. **5. Interactive Graphs** Cumulative spend trends, commitment identifiers, and projected forecast— all visual, all intuitive. **A snapshot of AWS EDP Tracker** **6. Deviation %** Now users would always be aware that what is the delta between the actual spend and committed spend. ## **Scenarios in which AWS EDP Tracker can assist** **Scenario 1:** If the Engineering team needs more environments to function, they spin up a new one, the overall cost goes up, and you can witness a deviation from the committed amount, then course correction can be done within time, as you had the option of tracking your monthly costs. **Scenario 2:** Due to seasonal changes, the cloud spend goes down in quarter 1, forecasts adjust itself as downward, business has the opportunity to move the underutilized commitment to other services within the company. **Scenario 3:** Senior management wants to know whether we will cross $15M EDP this year? AWS EDP Tracker is the single source of truth for you to answer this in seconds. ## **There is more to come!** This is just the V1 of AWS EDP Tracker. CloudKeeper is actively working on advanced functionalities to ensure AWS EDP Tracker becomes even more powerful to give you better insights about your committed spend. * Alerts based on the actual spend. * Granular level insights as per region, service, etc. * Forecasted spend modeling based on historic workloads to draw more meaningful patterns. * Goal estimation and corresponding tracking for FinOps team members. ## **All Set to Take Charge of Your AWS EDP Spends?** CloudKeeper Lens is already optimizing AWS spends, avoiding budget overruns, and assisting in staying ahead of the curve for 400+ customers across various industries. If you want your AWS investments to 👉 Schedule a Allow data and insights to lead the way! Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Product Manager Harsh is a distinguished Cloud Expert with an extensive background in product management. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Complete Guide to AWS PPA Contract Negotiation for Growing Enterprises A practical guide to AWS PPA or EDP negotiations, covering commitments, discounts, flexibility, risks, and best practices to help growing enterprises secure better pricing and long-term cloud value. By Team CloudKeeper 19 Dec, 2025 Ask the Cloud Expert: A Deep Dive Q&A on AWS PPA In this Q&A, CloudKeeper’s AWS PPA expert Aman Dixit shares real-world insights to help clients navigate PPAs and make smarter, cost-effective decisions. By Team CloudKeeper 05 Sep, 2025 From Good to Great: Supercharge Your AWS EDP Plan with a Partner Learn how partnering with the right AWS EDP partner can simplify the complexities of AWS EDP, helping you secure great benefits at lower commitments & cost. By Team CloudKeeper 17 May, 2024 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents ## **Overview** This guide shows how to deploy KEDA on an ## **What is KEDA** KEDA is a Kubernetes-based Event Driven Autoscaler. KEDA is a single-purpose and lightweight component that can be added to any ## **Architecture** KEDA creates external metrics from event sources and feeds those metrics to Kubernetes HPA. KEDA Architecture (source: keda.sh) In this POC, KEDA polls an Amazon SQS queue and scales a Kubernetes Deployment. Read more about EKS Pod Identity + KEDA polling SQS and scaling via HPA (source: AWS Prescriptive Guidance) ## **Prerequisites** You need: * An Amazon EKS cluster (Kubernetes 1.24+ recommended). * kubectl configured for the cluster. * Helm v3 installed. * AWS CLI v2 installed and authenticated. * Permissions to create ## **Set environment variables** Set these variables to match your environment: ### **Step 1 — Create an SQS queue** Create a standard Amazon SQS queue and capture its URL: ### **Step 2 — Install the EKS Pod Identity agent add-on** Install the Amazon EKS Pod Identity agent. If you are using EKS Auto Mode, the agent is built-in and you can skip this step. Verify the agent is running on nodes: ### **Step 3 — Install KEDA** Install KEDA into the dedicated namespace keda using Helm: ### **Step 4 — Create IAM roles for Pod Identity** Create two IAM roles: KEDA operator role: reads AWS SQS queue attributes for scaling. Worker role: receives and deletes messages. Both roles use a Pod Identity trust policy with principal pods.eks.amazonaws.com. Attach POC-friendly permissions (tighten later to least privilege): ### **Step 5 — Create service accounts and Pod Identity associations** Create the application namespace and service account: Associate IAM roles with Kubernetes service accounts: Restart the KEDA operator to pick up the new identity (recommended): ### **Step 6 — Deploy the SQS worker Deployment** Create worker.yaml: Replace the placeholder and apply: ### **Step 7 — Configure KEDA to scale the worker from SQS** Create keda-sqs.yaml: ### **Step 8 — Test autoscaling** Watch the Deployment/HPA and pods: Send messages to SQS (example: 50 messages): Expected behavior: when the queue has unread messages, KEDA activates the HPA and scales the Deployment up. After the worker drains the queue and cooldownPeriod passes, it scales back down to 0. ## **Operational checks** Useful commands during the POC: ## **Cleanup** Remove Kubernetes resources: Optionally uninstall KEDA: Remove IAM roles (example): Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Abhay Joshi is a problem solver who enjoys playing with algorithms and building scalable distributed systems. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents In today's digital era, the Cloud stands as a transformative force, reshaping the way businesses operate and innovate. If a The rapid adoption of cloud has however posed another big challenge for companies. It is to manage cost overruns and unexpected cloud costs. As per a As we walk into 2024, let us identify the ## **1. Complex nature of multi-cloud environments** One of the biggest challenges for enterprises today is the adoption of a multi-cloud environment, characterized by the use of services from multiple cloud providers. This adds up to the complexity of an already complex cloud system, thus requiring new mitigating mechanisms. Each cloud provider offers a different pricing model, a unique bouquet of services, and operational modalities. Thus, it becomes impossible for enterprises to work with one unified approach for cloud cost management. Hence, businesses face challenges while navigating their cloud infrastructural costs, tracking, and more importantly Moreover, factors such as data transfer costs between multiple clouds, storage costs on different platforms, and differences in services can also lead to a lack of cloud cost transparency. Additionally, managing security and compliance across multiple clouds adds another layer of complexity to the operational landscape. **Solution:** Comprehensive cloud cost management platforms can help enterprises by providing a unified view of cloud spending across multiple cloud platforms thus resulting in greater cost transparency and cost control. Automation is also critical for dynamic resource optimization based on cost and performance metrics. ## **2. Ever-changing pricing models** In the One of the most apparent impacts of this challenge of keeping pace with pricing updates is that organizations need more resource allocation and utilization. **Solution:** Enterprises must align their cloud cost optimization strategies with the latest pricing models introduced by cloud service providers even if it means regularly reviewing and updating their strategies using a more proactive and strategic approach. Additionally, ## **3. Effective reserved instances management** Reserved Instances(RIs) or reservations present a more promising way to organizations for cloud cost savings than on-demand pricing models. However, the biggest challenge when dealing with reserved instances is the **Solution:** Organizations can take the help of predictive analytics and machine learning algorithms to forecast future resource demands, thus making ## **4. Cloud cost visibility and a culture of accountability** One of the key factors of a successful cloud cost optimization journey is ensuring transparency and a culture of accountability for cloud cost management across cross-functional teams within an organization. Lack of cloud cost visibility and details of who is consuming what resources can hinder effective cost allocation and cloud cost optimization efforts. A culture of accountability must be encouraged and can go a long way in **Solution:** Organizations must implement robust resource tagging strategies for cloud cost optimization, enabling clear identification and attribution of costs. Fostering a culture of accountability, where ## **5. Keeping track of cloud cost spikes** Unexpected spikes in cloud cost can cause a big dent in your cloud cost optimization efforts. Such spikes can arise from different factors including heightened demand, suboptimal resource allocation, or changes in application workloads. Detecting and addressing these sudden cost spikes promptly is critical for maintaining cost efficiency and Proactive resource allocation and optimized workload configurations in response to changing demands are key to avoiding these unforeseen cost spikes which can hurt your cloud optimization efforts. **Solution:** Organizations must Implement alert systems and resource monitoring to detect unusual spikes in real-time. AI-based predictive analytics platforms can also help foresee potential spikes based on historical cloud cost optimization patterns and mitigate all risks. ## **6. Setting up security and compliance norms** For an enterprise operating in the public cloud domain, balancing cloud cost optimization with stringent security and compliance requirements remains one of the most critical challenges. Failure to do so can result in a Cloud FinOps hazard, negatively impacting the organization’s reputation and all cloud optimization efforts. Organizations must navigate the complexities of securing cloud environments without compromising cost-efficient configurations in their cloud cost optimization strategies. **Solution:** To tackle this ever-important challenge, organizations must Integrate security considerations into their ## **7. Upskilling and training of cloud teams** Cloud computing and its emerging technologies are ever-evolving and this in turn demands continuous upskilling, training, and development among teams responsible for cloud cost optimization. Any technology skill gap can impede the effective implementation of cost-saving measures. **Solution:** Organizations must regularly ## **8. Balancing Performance and Cost** The final challenge in this article relates to striking a fine balance between optimizing cloud costs and achieving an optimal cloud system without tilting too much on any side. Striking the right equilibrium between resource efficiency and meeting performance expectations is the key, especially in dynamic and rapidly changing cloud environments. **Solution:** Organizations must Implement comprehensive performance monitoring tools to understand the impact of cloud cost optimization measures on workloads and system performance to achieve a balance between the two. It is important to note that the cost optimization strategies must be constantly reviewed and updated to align the costs with performance. ## **Conclusion** Effective cloud cost management is crucial in today's rapidly changing cloud landscape. Businesses need to be proactive in reviewing and adjusting their approach to keep up with evolving business needs and trends. Mitigating the challenges addressed above can result in sustainable and efficient cloud cost management. By leveraging modern tools, fostering a culture of accountability and collaboration, and constantly upskilling on key cloud technologies, businesses can overcome these challenges and unlock the full potential of the cloud while achieving a greater level of cloud efficiency. _With a strong team of certified AWS experts and FinOps enthusiasts, CloudKeeper has helped 300+ businesses across the globe achieve_ _, without affecting their performance benchmarks. We would love to show you how we could help you too!__._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 The Silent Bottleneck: Avoiding Subnet IP Exhaustion in Amazon EKS A practical guide to avoiding subnet IP exhaustion while scaling an Amazon EKS cluster, covering causes, impact, and prevention strategies. By Manish Negi 27 Feb, 2026 Where are groups in Kubernetes? A detailed walkthrough explaining Kubernetes groups, how RBAC uses them, what happens on EKS, plus best practices, pitfalls, and examples. By Abhay Joshi 04 Feb, 2026 KEDA Autoscaling on Amazon EKS using SQS + EKS Pod Identity A complete guide to deploying KEDA on Amazon EKS using SQS and EKS Pod Identity, with step-by-step autoscaling setup, along with examples. By Abhay Joshi 30 Jan, 2026 A Closer Look at Kubernetes’ In-Place Pod Resize Deep dive into Kubernetes In-Place Pod Resize: learn how it works, see the architecture, and resize CPU/memory live using real examples and code snippets. By Priyansh Pathak 23 Jan, 2026 Multi-Cluster GitOps with ArgoCD for Kubernetes A complete guide to Multi-Cluster GitOps for Kubernetes using ArgoCD, with step-by-step setup, best practices, and troubleshooting. By Abhay Joshi 13 Jan, 2026 Kubernetes 1.35: Understanding PreferSameNode and PreferSameZone Traffic Distribution Explore Kubernetes 1.35 PreferSameNode and PreferSameZone, their evolution, use cases, and how they improve pod placement and performance on Amazon EKS. By Gourav Kumar Pandey 06 Jan, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 2 2 Table of Contents Hyderabad was buzzing with Cloud Native energy last week. KubeCon + CloudNativeCon brought together developers, architects, and innovators from across the globe — and I was lucky enough to be part of it. This blog is my attempt to capture not just the technical sessions I attended, but also the inspiration, connections, and reality checks I experienced. ## **1. Inspiration and Reality Check** I went in thinking I knew my way around Kubernetes fairly well… but the depth of talks and the skill of speakers (some with just 3–4 years of experience!) was both inspiring and humbling. **A standout was:** * A deep dive into what really happens during pod termination — so much more complex than I had imagined. ## **2. AI in Unexpected Places** It was fascinating to see non-core-tech companies using AI in impactful ways, like PepsiCo’s strategy for deploying LLMs on Kubernetes to drive business outcomes. * ## **3. Learning Without a Production-Grade Setup** We often complain about not having a “real” environment to experiment with. **But** : * Showed how a Raspberry Pi + eBPF + OpenTelemetry can be enough to learn advanced observability concepts. ## 4. Kubernetes at Scale – Node Churn & GPU Optimization Two technical deep dives that stood out: * * ## **5. Bridging Big Data and ML** **The conference ended for me with:** * which explained very well why GPU utilization remains a challenge in AI/ML workloads on Kubernetes, a recurring theme I noticed in many talks at KubeCon. ## **6. The Fun Side – Capture the Flag** I squeezed in some time for the Kubernetes**Capture the Flag** by the ControlPlane team. Even 30 minutes was enough to learn security best practices and rekindle my interest in CTFs. ## **7. People & Conversations** Catching up with old friends and meeting so many passionate engineers was a highlight in itself. Even the audience Q&A sessions were full of insights from real-world challenges. ## **Closing Thoughts** KubeCon wasn’t just a conference for me — it was a mirror, a motivator, and a massive dose of inspiration. I’m walking away with new ideas, a refreshed perspective, and the urge to double down on learning. If you get a chance to attend one, do it. The hallway conversations alone are worth it. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Architect Raghu specializes in Kubernetes, cloud infrastructure, and automation. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents If you’ve ever juggled workloads that need GPUs, FPGAs, or other hardware on With Kubernetes v1.34, that’s changing. The Dynamic Resource Allocation (DRA) framework has officially graduated to General Availability (GA), and it’s loaded with new powers. This update offers greater flexibility, control, and observability than ever before, from improved device sharing to real-time health reporting. Not only that, it also simplifies ## **DRA Graduates to GA: Managing Devices Just Got Smarter** Fundamentally, Dynamic Resource Allocation facilitates dynamic management of specialised hardware by Kubernetes. Instead of hardcoding which GPU a pod gets, DRA lets workloads describe what kind of device they need, say, any GPU with at least 20 GB of memory, and leaves the scheduler to figure out the best allocation. That means: 1. Better hardware utilisation (no GPU sits idle). 2. More reliable scheduling, the scheduler chooses the best fit. 3. Cleaner abstractions, workloads declare intent instead of specific device IDs. Imagine a team running both AI training and data preprocessing workloads. Training jobs need top-tier GPUs, while preprocessing can survive on mid-range hardware. DRA’s prioritised device list allows you to define acceptable alternatives, so if the best GPU isn’t available, the scheduler can automatically select the next best fit, thereby simplifying overall Kubernetes management. No manual reconfigurations. With GA, DRA is a stable, default part of Kubernetes 1.34. The stable API (resource.k8s.io/v1) is on by default, so you can adopt it with confidence. ## **New in Beta: Control and Flexibility for Kubernetes Cluster Admins** Several DRA features are promoted to beta in Kubernetes 1.34, providing developers and administrators with more precise control. ### **1. Labelling for Admin Access** Admins can now use namespace labels to limit device usage. For instance, devices that grant elevated rights can only be used by namespaces that have resource.k8s.io/admin-access set to "true". By doing this, ordinary users can avoid inadvertently (or purposely) using high-privilege resources, which could result in privilege escalation. ### **2. Prioritised device lists** For a task, you can now list several devices that are suitable. Example (from a device request list or claim template) preferredEquipment: ### **3. Pod resource visibility** The DRA-managed devices assigned to each pod are now reported by the Kubelet's API. This information can be used by monitoring agents to correlate hardware utilisation and pod performance. ## **Alpha Features: A Glimpse of What’s Next** ### **1. Extended Resource Mapping** Allows a smooth transition between DRA-managed devices and conventional extended resources. It merely indicates that devices under DRA management will be handled like any other resource. ### **2. Consumable Capacity: Smarter, Safer Device Sharing** Allows fine-grained sharing of devices like GPUs or NICs. Developers can allocate specific capacities (e.g., 10GiB out of a 40GiB GPU) safely. Consumable Capacity lets drivers expose a device’s total capacity and define policies for slicing it among multiple consumers across different Pods, namespaces, or claims. * Share the *same device* across multiple ResourceClaims or DeviceRequests. * Scheduler enforces that the sum of allocations never exceeds device capacity. * Each allocation gets a unique ShareID so drivers can enforce per‑share limits. #### **How to use consumable capacity?** ##### **1. Enable the feature gate** We need to enable it on kubelet, kube-apiserver, kube-scheduler, and kube-controller-manager ##### **2. Driver author notes (Golang)** Allow multiple allocations on a device and define request policies for capacity units (min/step/default). With this we make a device within a ResourceSlice allocatable to multiple ResourceClaims just by doing this. ##### **3. ResourceSlice publication (YAML)** ##### **4. Consumer example: request a share** Request 10 GiB of memory from any device class `resource.example.com` that can satisfy it: Filter only devices that support multiple allocations using a CEL selector: After allocation, the status gains a per‑share identifier so your driver can distinguish and police each consumer independently: The driver can differentiate between allocations that originate from distinct ResourceClaim requests but relate to the same device or statically-partitioned slice thanks to this ShareID. It serves as a distinct identity for every shared slice, giving the driver the ability to autonomously control and enforce resource limitations among several users. ### **3. Resource Health Reporting: Diagnosing Hardware Issues in Real-Time** Kubernetes now reports device health directly in Pod status. Operators can instantly identify failing devices without deep debugging. The new health reporting for DRA feeds hardware health straight into the Pod’s status, so you can spot failing devices without checking logs. How it works: * Drivers implement a new gRPC service `dra-health/v1alpha1` with `DRAResourceHealth`. * The kubelet’s DRAPluginManager opens a long‑lived `NodeWatchResources` stream and caches updates. * When health changes, kubelet updates Pod `.status.containerStatuses[].allocatedResourcesStatus`. **Enable the feature gate** **Kubectl Output Example** Between GA stability, beta flexibility, and alpha innovation, Kubernetes 1.34 makes DRA more than just a framework. It's becoming the foundation for modern hardware orchestration. As AI, ML, and edge workloads become the norm, DRA ensures hardware resources are used efficiently, dynamically, and safely. Kubernetes 1.34 gives you more control, better insight, and safer sharing, keeping your workloads humming across even the most demanding hardware. Looking to optimise your Kubernetes at Scale? Whether you're just getting started or already running production clusters, CloudKeeper helps you achieve better performance, more control, and a lot of savings. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Aditya is passionate about simplifying and strengthening Kubernetes operations on AWS. He works on improving cluster reliability, automation, and deployment efficiency in cloud environments. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents ## **What Problem Does This Solve?** When you deploy an application in By default, Kubernetes distributes traffic across all healthy endpoints. That works in many cases, but it can cause a couple of real problems once clusters grow, making **Problem 1: Unnecessary Network Latency.** If a request arrives at Node A but gets routed to a pod running on Node B in a different zone, the traffic has to travel across the network. That extra hop adds latency and can even cause **Problem 2: Cross-Zone Data Transfer Costs .** Most cloud providers charge for traffic that crosses availability zones. At scale, this adds up quickly. Services handling large volumes of traffic can end up paying more than expected simply because traffic is bouncing between zones. Beyond cross-zone data transfer costs, several pitfalls can lead to an unexpected Amazon EKS bill shock at the end of your billing cycle. Here’s your ## **The Evolution of Traffic Distribution in Kubernetes** Kubernetes didn’t solve this problem overnight. The current approach is the result of a few iterations. ### **a) Earlier Approaches** **externalTrafficPolicy and internalTrafficPolicy** Before **trafficDistribution** existed, Kubernetes provided two related options: Setting these to Local forced traffic to stay on the same node. If no local endpoints were available, traffic would fail instead of falling back to remote pods. This behavior was sometimes useful, but risky. A node without a local pod would simply drop traffic, which made these settings hard to use safely in production. ### **b) The Introduction of trafficDistribution** The **trafficDistribution** field was introduced to provide a softer, safer approach. Instead of enforcing strict rules, it lets you express preferences, while still allowing fallback when local endpoints are unavailable. This small change makes a big difference operationally. ## **What Changes in Kubernetes 1.35** In Kubernetes 1.35, the **trafficDistribution** feature becomes stable, and two important updates come with it. To get a better understanding of the change, ### **1. New Option: PreferSameNode** **PreferSameNode** tells Kubernetes to try to keep traffic on the same node when possible. If traffic arrives on a node and a healthy pod exists on that same node, Kubernetes will send traffic there. If not, it simply falls back to any other healthy pod. The key thing to remember is that this is a **preference** , not a hard rule. Traffic will not fail if local pods are missing. **Note: trafficDistribution** expresses a preference, not a guarantee. The exact behavior depends on the cluster’s networking implementation (iptables, IPVS, or eBPF-based proxies). ### **2. Renamed Option: PreferClose Becomes PreferSameZone** The older option **PreferClose** , has been renamed to **PreferSameZone**. The behavior is the same, but the new name makes it much clearer what Kubernetes is actually doing. **PreferClose** still works for backward compatibility, but **PreferSameZone** is the recommended option going forward. ## **How These Options Differ** The difference between these two options becomes clearer with an example. Assume a cluster with: * 3 availability zones (zone-a, zone-b, zone-c) * 2 nodes per zone * 6 application pods spread across the cluster **_Scenario: Traffic arrives at Node-1 in Zone-A_** **a)** With **PreferSameNode** * Kubernetes first looks for a healthy pod on Node-1. * If it finds one, traffic goes there. * If not, traffic falls back to any healthy pod in the cluster. **b)** With **PreferSameZone** * Kubernetes looks for healthy pods anywhere in Zone-A. * If it finds one, traffic goes to one of those pods (not necessarily on the same node). * If no pods exist in that zone, traffic falls back to the rest of the cluster. ## **Which One Should You Choose?** **Choose PreferSameNode when:** * Lowest possible latency matters * Pods are spread across most or all nodes * You’re running DaemonSets or very high replica counts **Choose PreferSameZone when:** * Reducing cross-zone costs is the main goal * Pods are not present on every node * Zone-level locality is “good enough” for latency ## **Technical Details: How It Works Under the Hood** When you set trafficDistribution, the control plane (for AWS, The proxy uses EndpointSlices to understand where endpoints live. EndpointSlices include topology information such as node and zone. Based on this data, the proxy programs' routing rules that prefer local endpoints when possible. You normally don’t need to interact with EndpointSlices directly, but knowing what’s inside them helps a lot when debugging traffic behavior. **EndpointSlice Example** The proxy reads the **nodeName** and **zone** fields to decide which endpoints to prefer based on your configuration. ## Comparison with Older Traffic Policies ## Because of the fallback behavior, **trafficDistribution** is much safer for production workloads. ## **Things to Consider Before Using This Feature** ### **a) Pod Distribution Matters** **PreferSameNode** only helps if pods actually exist on most nodes. If pods are concentrated on a few nodes, traffic will frequently fall back to remote endpoints and you won’t see much benefit. DaemonSets work especially well here. Deployments can also work, but they need enough replicas and proper scheduling. ### **b) Health Checks Still Apply** Preferences only apply to **healthy** endpoints. If a local pod is failing readiness checks, traffic will be routed elsewhere. Make sure readiness probes are accurate. ### **c) Load Distribution Can Become Uneven** With PreferSameNode, traffic depends on where requests arrive. Some nodes may receive more traffic than others, which can lead to uneven load. HPA can help, but it won’t guarantee pods land on the busiest nodes. This is something to keep in mind for latency-sensitive services. ## **Real-World Use Cases** * Sidecar proxies running as DaemonSets * Local caching layers with fallback to remote cache nodes * Log collection agents running per node * Multi-zone services looking to reduce cross-zone costs These patterns already exist today. **trafficDistribution** simply makes them easier and safer to implement. ## **What This Means for Amazon EKS Users** At the time of writing, Amazon EKS does not yet support Kubernetes 1.35. Once Amazon EKS adds support, the **trafficDistribution** field with **PreferSameNode** and **PreferSameZone** will be available without any API changes. Until then, you can: * Identify services that would benefit from traffic locality * Plan migration from **PreferClose** to **PreferSameZone** * Review pod placement strategies to prepare for **PreferSameNode** ## **Looking Ahead** With **trafficDistribution** now marked stable, Kubernetes considers this feature ready for production use. The API is stable and not expected to change in future releases. The addition of **PreferSameNode** fills an important gap. Earlier releases allowed zone-level preferences, but node-level locality with safe fallback was missing. Kubernetes 1.35 finally addresses that. This work was delivered as part of KEP 3015 by the SIG Network team, after several release cycles of iteration and feedback. ## **Summary** Kubernetes 1.35 improves service traffic routing with a stable **trafficDistribution** API: * **PreferSameNode** prefers same-node endpoints with safe fallback * **PreferSameZone** prefers same-zone endpoints with safe fallback (formerly **PreferClose**) These options reduce latency and cross-zone costs without the failure risks of older policies. When managed Kubernetes platforms like Amazon EKS roll out support for 1.35, these features can be used to fine-tune traffic behavior in real production clusters. For more tips, check out this Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Gourav specializes in helping organizations design secure and scalable Kubernetes infrastructures on AWS. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Kubernetes has become the backbone of modern cloud infrastructure, but growth brings a hidden challenge. As the number of Kubernetes clusters grows from 3 to 30 and beyond, often driven by expanding engineering efforts and more code, complexity rises quickly. Kubernetes requires deep expertise, which many teams lack, and Sound familiar? You're not alone. 82% of users now run Kubernetes in production, yet 59% of CPU usage is undefined, according to recent ## **Why Kubernetes Costs Skyrocket During Rapid Growth** The abstraction layers that make Kubernetes powerful also hide where money goes. Traditional cloud infrastructure offers relatively predictable pricing because it comes with provisioned, fixed-capacity instances, and the infrastructure can be managed by a generalist team. With Kubernetes, cost behavior becomes more dynamic. Kubernetes itself is not the problem. The challenge lies in ## **Kubernetes Cost Optimization Challenges in High-Growth Companies** ### **a) Rapid onboarding of new teams and services** Every new engineering team needs clusters. Each product launch requires isolated environments. What starts as 5 namespaces becomes 50 in six months. Without standardized provisioning processes, every team configures resources differently, some conservative (wasting money), others aggressive (risking performance). ### **b) Uncontrolled cluster and namespace expansion** High-growth companies often run hundreds of namespaces across dozens of clusters. Each cluster adds operational overhead, including monitoring tools, logging pipelines, and security scanning. That baseline cost multiplies faster than revenue when proliferation goes unchecked. ### **c) Dev/Test environment sprawl** Engineers spin up test clusters for POCs. Those clusters run 24/7 even though actual usage happens 40 hours per week. Multiply that across 20 engineering teams, and you find yourself shelling out $15K-$30K monthly on idle development environments. ### **d) Lack of ownership and accountability** When six teams use the same infrastructure, no one feels responsible for Kubernetes cost optimization. As a result, finance cannot charge back accurately, and engineers themselves don’t know the actual cost of their workloads. All of this stems from a lack of visibility into cloud infrastructure. ### **e) Reactive Kubernetes Cost Optimization efforts vs proactive optimization** Most teams only optimize after bill shock. By then, you've already overspent for months. Proactive optimization requires visibility, automation, and cultural change, which is precisely what gets deprioritized when everyone's focused on shipping features. ## **How to Build Cloud Cost Visibility at Scale** 1. **Granular Monitoring:** Track resource usage at pod, namespace, and cluster levels. Use tools like Prometheus and Grafana to capture real-time metrics for CPU, memory, storage, and network. 2. **Consistent Labeling:** Apply standardized labels across all resources to enable cost allocation. Tag workloads by team, product, environment, and customer. This allows precise attribution of spend and eliminates manual effort in cost breakdowns. 3. **Anomaly Detection:** Set up automated alerts for cost deviations. Sudden increases in resource consumption, such as a spike in a production namespace, should trigger immediate investigation. 4. **Hidden Costs:** Account for external dependencies such as APIs, managed databases, backups, and SaaS integrations. These scale with usage and must be tracked alongside infrastructure. Solutions like CloudKeeper LensGPT unify this visibility by correlating Kubernetes resource usage with actual cloud billing across AWS and GCP. ## **Right-Sizing for Fast-Changing Workloads** Resource requests and limits determine how Kubernetes schedules pods. Set them too high, and you waste capacity—nodes reserve resources that workloads never use. Set them too low, and pods get throttled or evicted, degrading performance. For high-growth companies where workload patterns shift weekly, right-sizing becomes an ongoing challenge. Continuous monitoring reveals actual consumption patterns. If a service consistently uses 200m CPU and 512Mi memory, reduce requests from 1000m CPU and 2Gi memory. Start with non-production workloads where performance degradation has a lower business impact. Vertical Pod Autoscaler (VPA) automates request tuning based on historical usage. It analyzes metrics and adjusts CPU/memory requests automatically. However, VPA requires pod restarts to apply changes. CloudKeeper Tuner applies ML-driven analysis across clusters, recommending optimal configurations without disruptive restarts that VPA requires. ## **How to Autoscale Without Overspending** Horizontal Pod Autoscaler (HPA) adds replicas when the load increases. Cluster Autoscaler provisions nodes when existing capacity is exhausted. Both are essential for performance, but misconfiguration creates runaway costs. HPA defaults to CPU-based scaling, but CPU alone is a poor proxy for application health. A web service saturated with requests at 50% CPU still needs more capacity. Configure HPA on application-level metrics—requests per second, queue depth, response latency. Tools like KEDA enable event-driven autoscaling on these custom metrics. Set conservative target utilization thresholds. Targeting 90% CPU leaves no headroom for traffic bursts. Targeting 40% wastes resources. Industry practice recommends 60-75% utilization for most workloads, providing buffer capacity without excess waste. Cluster Autoscaler works well, but can be slow—provisioning nodes takes 2-5 minutes. For workloads with unpredictable bursts, maintain baseline capacity through minReplicas and let HPA scale within existing nodes first. Only provision additional nodes when horizontal scaling exhausts the current capacity. Karpenter offers faster, more flexible node provisioning than traditional Cluster Autoscaler. It launches right-sized nodes in seconds based on pending pod requirements, improving bin-packing efficiency. However, Karpenter requires engineering expertise to configure properly, or a platform like CloudKeeper that automates Karpenter tuning. ## **Optimizing Infrastructure & Node Strategy** * **Instance Selection** Choosing the right instance type directly impacts cost and performance. Match workload requirements with compute-optimized or memory-optimized instances to avoid overspending. * **Spot Usage** Spot instances offer significant cost savings for fault-tolerant workloads. They are ideal for batch jobs and stateless services but require fallback strategies due to interruptions. * **Hybrid Mix** Combining Spot and On-Demand instances helps balance cost and reliability. This approach ensures critical workloads remain stable while optimizing variable workloads. * **Reserved Capacity** Reserved Instances and Savings Plans reduce costs for predictable usage. Commit to baseline capacity while allowing autoscaling to handle fluctuations. * **Multi-Tenancy** Running multiple workloads on shared nodes improves utilization. Proper isolation using quotas and priorities prevents resource contention. ## **Eliminating Waste in High-Velocity Environments** High-growth companies accumulate waste faster because they're moving too fast to clean up. **Zombie workloads:** POC deployments never deleted. Test services are running months after the projects ended. Regular audits identify orphaned resources. **Idle dev/test environments:** Schedule non-production workloads off-hours. Developers working Monday-Friday 9-5? Shut down staging environments nights and weekends—76% time savings translates to 76% cost reduction. **Over-provisioned storage:** Persistent volumes don't shrink automatically. A database scaled to 500GB for load testing might only need 100GB post-test, but you keep paying for 500GB. **Unused load balancers:** Each cloud load balancer costs $15-30/month plus data transfer. Unused Elastic IPs cost $3-5/month. These charges multiply across forgotten resources. ## **Storage & Networking Cost Control** Storage costs creep up slowly, then compound. Block storage ( Object storage bills for storage plus API calls. Lifecycle policies move infrequently accessed data to cheaper tiers automatically. Network data transfer is the hidden cost driver. Cross-region transfers cost $0.01-$0.02/GB. Internet egress costs $0.09-$0.12/GB. A service moving 10TB/month externally pays $900-$1,200 monthly in data transfer alone. Optimize networking through regional affinity—keep workloads and data in the same region. Use CDNs for static content. Enable compression on API responses. ## **Automation & AI-Driven Kubernetes Cost Optimization** Manual Kubernetes cost optimization doesn't scale. At 5 clusters, spreadsheet tracking works. At 50 clusters across regions and clouds, manual processes break. Automation transitions from nice-to-have to a requirement. Policy-driven Kubernetes cost optimization enforces standards automatically. Define resource quotas per namespace. Require labels for cost allocation. Block expensive instance types in non-production. These guardrails prevent costly mistakes. AI-driven platforms adapt to workload changes in real-time. Traditional autoscaling follows static rules. AI systems learn usage patterns and optimize proactively, adjusting before performance degrades or costs spike. ## **FinOps & Governance for Scaling Organizations** Engineers need cost visibility within workflows, which can be achieved through the following: * Show developers what their namespace costs daily. Surface optimization recommendations in Slack. * Make cost part of code reviews and sprint planning. Implement chargeback or showback to create accountability. When product teams see infrastructure costs allocated to their P&L, they care about optimization. Even showback (reporting without actual charges) changes behavior. Establish targets tied to business metrics. Cost per transaction, cost per user, cost per API call—these unit economics make spending tangible. Regular reviews maintain momentum. Monthly cost reviews with engineering, quarterly deep-dives with finance, and annual audits of cloud strategy. CloudKeeper's ## **Tooling and Tech Stack for Kubernetes Cost Optimization** ### **Open-source options:** * **Kubecost:** Cost allocation and monitoring with free community tier * **Prometheus + Grafana:** Metrics collection and visualization * **Karpenter:** Advanced node provisioning for better bin-packing ### **Cloud-native tools:** * **AWS Cost Explorer:** Service-level spend analysis * **GCP Billing Reports:** Detailed usage and cost breakdowns * **Azure Cost Management:** Multi-cloud cost tracking ### **Commercial platforms:** **CloudKeeper:** End-to-end Kubernetes cost optimization with AI-driven automation, FinOps consulting, and 24/7 cloud support across AWS, GCP, Azure **Datadog:** Observability with cost tracking capabilities **Cast.AI:** AI-powered cluster optimization Choose tools based on scale and maturity. Small teams (1-5 clusters) can start with open-source. Mid-size organizations (10-50 clusters) benefit from commercial platforms. Enterprises (50+ clusters) require comprehensive solutions with multi-cloud support, governance features, and dedicated expertise. ## **Pitfalls and Myths to Avoid** **Myth: "Kubernetes is expensive."** Instead, poor configuration is. Properly managed Kubernetes reduces infrastructure costs 30-50% versus traditional VMs. **Myth: "Autoscaling solves everything."** Autoscaling scales out, but scaling over-provisioned pods multiplies waste. Right-size before autoscaling. **Pitfall: Optimizing too aggressively,** cutting resources until pods constantly restart, creates a burden worse than overspending. Leave 15-20% headroom. ## **Kubernetes Cost Optimization Roadmap for High-Growth Companies** ### **30-day quick wins:** 1. Schedule non-production environments off-hours (save 35-40% on dev/test) 2. Identify and delete zombie resources (typical savings: 8-12%) 3. Enable Cluster Autoscaler if not already running 4. Implement basic cost allocation labels 5. Set up anomaly detection alerts ### **90-day stabilization plan:** 1. Right-size the top 20 highest-cost workloads 2. Implement HPA on custom metrics for critical services 3. Deploy mixed Spot/On-Demand node pools 4. Establish FinOps review cadence 5. Calculate unit economics (cost per transaction/user) ### **12-month maturity roadmap:** 1. Achieve 90% resource labeling coverage 2. Implement a full chargeback model 3. Deploy an AI-driven optimization strategy 4. Utilize Reserved Instance/Savings Plan 5. Build an internal FinOps community of practice ### **Scaling sustainably:** As you grow from 10 to 100 to 1000+ microservices, Kubernetes cost optimization should become a core competency. High-growth companies that master it early establish sustainable Companies that succeed at Kubernetes cost optimization build awareness into their engineering culture from day one. Instead of treating optimization as a barrier to innovation, they see it as added revenue, where every dollar saved is a dollar earned. ## **How CloudKeeper drives Kubernetes Cost Optimization for High-Growth Companies** CloudKeeper combines AI-powered automation with expert FinOps guidance. **CloudKeeper Tuner** continuously right-sizes workloads across clusters, eliminating manual analysis. It identifies over-provisioned pods, schedules non-production resources off-hours, and automates zombie cleanup—delivering 15-25% cost reductions without engineering work. **CloudKeeper Lens** provides granular cost visibility across namespaces, clusters, and teams. Finance gets an accurate chargeback. Engineering sees costs in Slack. Leadership tracks unit economics in real-time. **24/7 Expert Support** from 150+ certified Kubernetes professionals. CloudKeeper has optimized costs for 400+ companies. High-growth companies using CloudKeeper achieve an average 15% cost reduction in 90 days, 4-6 hours weekly time saved per team, and sustainable unit economics supporting continued growth. ## **Conclusion: Scaling Fast Without Burning Cash** Kubernetes cost optimization for high-growth companies requires cultural change, operational discipline, and sustained focus. Start small. Pick three quick wins from the 30-day roadmap and implement them. As optimization becomes routine rather than reactive, you'll establish the foundation for sustainable scaling. Ready to optimize your Kubernetes infrastructure for sustained growth? Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Season 2 of "Latte on Cloud Costs" kicks off with a compelling conversation between host ## **The Evergreen Nature of Cloud Cost Challenges** Hassan opens the discussion by establishing a fundamental truth: cloud cost is an evergreen problem that requires continuous attention. Unlike traditional infrastructure costs that were relatively predictable and static, cloud costs demand ongoing vigilance and active management. This reality sets the stage for understanding why ### **The Complexity Explosion** One of the most striking insights from the conversation is Hassan's observation that "The complexity has just gone through the roof." This statement encapsulates a major shift in the cloud cost optimization landscape. Where early cloud adopters dealt with relatively straightforward pricing models, today's organizations navigate an intricate web of services, pricing tiers, and optimization options. This complexity stems from several factors: * The proliferation of cloud services and features * Increasingly sophisticated pricing models * Multiple deployment options and configurations * The rise of multi-cloud and hybrid environments For CTOs and engineering leaders, this complexity presents both opportunities and challenges. While more options can lead to better cloud optimization, they also require deeper expertise and more sophisticated management approaches. ### **The Decentralization Challenge** A significant portion of the discussion focuses on how decentralization in cloud management creates unique Hassan explores how this shift impacts: * Visibility: Understanding who is spending what becomes more difficult * Accountability: Establishing clear ownership of cloud costs across distributed teams * Governance: Maintaining cost controls without stifling innovation * Optimization: Coordinating cost-reduction efforts across multiple autonomous teams This decentralized reality requires new approaches to cloud cost management that balance autonomy with fiscal responsibility. ### **Shifting Left: Integrating Cost Awareness Early** One of the key concepts discussed is the importance of shifting left in FinOps practices. This means integrating cost awareness earlier in the development process, rather than treating it as an afterthought or periodic review activity. The shift-left approach involves: * Design-time considerations: Evaluating cost implications during architecture and design phases * Development integration: Building cost awareness into development workflows and tools * Early feedback loops: Providing developers with real-time cost information * Proactive optimization: Addressing cost issues before they compound in production This proactive approach helps organizations avoid the accumulation of what Hassan refers to as "cloud debt" - the technical and financial burden that builds up when cost considerations are deferred. ### **The Cloud Debt Crisis** Hassan introduces the critical concept of cloud debt, stating that "Cloud debt is a real issue we need to address." This represents the accumulation of suboptimal cloud configurations, unused resources, and inefficient architectures that compound over time. Unlike technical debt, which primarily affects development velocity, cloud debt has direct financial implications. It manifests as: * Unused or underutilized resources * Inefficient service configurations * Legacy architectures that don't leverage modern cost optimization features * Lack of Organizations must address cloud debt proactively, as it becomes increasingly expensive and difficult to resolve over time. ### **The Invisible Checkout Problem** A particularly insightful observation from Hassan is that "There's no checkout screen for the cloud." This simple statement captures a fundamental challenge in cloud cost management: the absence of natural friction points that would typically prompt cost consideration. Unlike traditional purchasing processes where costs are visible and require explicit approval, cloud resources can be provisioned instantly without immediate cost visibility. This creates an environment where costs can spiral without obvious warning signs, making proactive monitoring and governance essential. ## **Generative AI: Promise and Peril** The conversation explores the potential of generative AI to transform cloud cost management while acknowledging the associated risks. Hassan discusses how AI can assist with: * Pattern recognition: Identifying cost optimization opportunities across complex environments * Predictive analytics: Forecasting future costs based on usage patterns * Automated optimization: Implementing cost-reduction measures without human intervention * Anomaly detection: Identifying unusual spending patterns that might indicate issues However, the integration of AI also introduces new challenges and risks that organizations must carefully manage. ## **Understanding the Cloud Cost Formula** Hassan emphasizes the importance of understanding the fundamental formula of cloud costs for effective management. This involves recognizing that cloud costs are driven by: * Resource provisioning: The infrastructure and services allocated * Usage patterns: How those resources are actually utilized * Pricing models: The specific cost structures and optimization options available * Operational efficiency: How well resources are managed and optimized This formula-based approach helps organizations identify the most impactful optimization opportunities. ## **Prioritizing Usage Optimization** A key takeaway from the discussion is the importance of prioritizing usage optimization for impactful cost savings. Rather than focusing solely on procurement or contract negotiations, Hassan advocates for examining how resources are actually used and optimizing consumption patterns. This approach involves: * Analyzing actual usage patterns versus provisioned capacity * Identifying opportunities for right-sizing and resource optimization * Implementing automated scaling and scheduling policies * Optimizing application architectures for cost efficiency ## **Strategies for Decentralized Optimization** Given the decentralized nature of modern cloud environments, Hassan discusses the need for decentralized optimization strategies. These approaches recognize that effective cost optimization cannot be managed solely from a central team but must be embedded throughout the organization. Key elements of decentralized optimization include: * Democratized tools: Providing cost visibility and optimization tools to individual teams * Clear accountability: Establishing ownership and responsibility for costs at the team level * Governance frameworks: Creating guidelines and policies that enable autonomous decision-making * Cross-functional collaboration: Facilitating cooperation between finance and engineering teams ## **The Critical Role of Collaboration** Throughout the discussion, the importance of collaboration between finance and engineering teams emerges as a key theme. Hassan emphasizes that successful cloud cost management requires breaking down traditional silos and creating shared understanding between these traditionally separate functions. This collaboration involves: * Shared metrics: Establishing common KPIs that both teams can understand and act upon * Regular communication: Creating forums for ongoing dialogue about cost optimization * Aligned incentives: Ensuring that both teams are motivated to achieve cost efficiency * Knowledge sharing: Facilitating the exchange of domain expertise between finance and engineering ## **Practical Implications for Leaders** For CTOs and engineering leaders, this episode provides several actionable insights: * Embrace complexity: Rather than fighting the increasing complexity of cloud costs, develop systems and processes to manage it effectively * Invest in shift-left practices: Integrate cost awareness into development processes from the earliest stages * Address cloud debt proactively: Don't let suboptimal configurations accumulate; address them systematically * Build decentralized capabilities: Enable teams to manage their own costs rather than relying solely on central oversight * Foster collaboration: Break down silos between finance and engineering to create shared ownership of cost optimization ## **Looking Forward** As Season 2 of "Latte on Cloud Costs" begins, this conversation with Hassan Hosseini sets the stage for exploring the evolving landscape of cloud cost optimization. The themes of complexity, decentralization, and collaboration will likely continue to shape how organizations approach cloud financial management. The episode underscores that cloud cost optimization is not a static discipline but one that must continuously evolve to meet new challenges and opportunities. As cloud environments become more sophisticated and distributed, the approaches to managing their costs must evolve accordingly. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents In the latest episode of "Latte on Cloud Costs," host ## The Evolution of Cloud Adoption: From Hype to Reality Varsha outlines four key phases of cloud adoption: **Phase 1: Cloud First Mentality** Initially, organizations embraced a “cloud first” approach, moving workloads en masse to the cloud with the assumption it would be more cost-effective. This often resulted in straightforward lift-and-shift migrations without much architectural rethinking. **Phase 2: The Reality Check** It soon became clear that simply migrating on-premise workloads didn’t always deliver cost savings. Companies started realizing they were spending more in the cloud and began considering cloud-native or optimized architectures. **Phase 3: Strategic Cloud Evaluation** As cloud maturity grew, organizations began evaluating which workloads actually benefited from being in the cloud. Instead of blindly migrating everything, they assessed the cloud-worthiness of each application. **Phase 4: AI Integration** Today, cloud strategy includes evaluating how AI can be embedded into cloud operations. This includes understanding AI-friendliness of workloads and exploring how AI can assist with automation and decision-making. ## The Hidden Costs of Cloud Migration One of the most overlooked aspects of cloud migration is the dual-cost period, where both on-premises and cloud environments run simultaneously to ensure uptime during transition. This leads to double spending. Additional challenges include: * **Licensing Complexities:** Issues like overlapping licenses for platforms like SQL Server. * **Disaster Recovery Duplication:** Managing multiple DR sites during transition. * **Technical Debt:** Legacy systems and certificates that delay progress. * **Timeline Pressure:** The need to balance speed with cost control. ## The MSP Decision Framework Varsha emphasizes that whether to engage a Managed Service Provider (MSP) depends on organizational maturity: * **Small Enterprises:** Often benefit from MSPs due to limited in-house expertise. * **Mid-size Organizations:** May adopt a hybrid approach, using cloud-native tools and MSPs selectively. * **Large Enterprises:** Require coordinated efforts across multiple business units and often need both internal and external support. She also notes that time itself is a cost metric. Delays and inefficiencies carry an operational cost that must be considered alongside financial spend. ## Beyond Dashboards: The Future of Cloud Cost Visibility Traditional dashboards are often not enough. Varsha stresses the importance of tailoring visibility to user personas and ensuring data quality. ### Three Core Issues: 1. **Data Quality:** Insights are only as good as the data behind them. 2. **Proper Attribution:** Different teams need customized views aligned with their responsibilities. 3. **Chargeback Complexity:** Linking cloud resources to the correct cost centers remains a major hurdle. ### The AI Opportunity Looking ahead, AI has the potential to revolutionize cost visibility. Rather than navigating dashboards, users could simply ask for EC2 costs or compare pricing across regions. AI could surface personalized insights based on an organization’s SLAs, discounts, and sustainability goals—reducing reliance on manual queries and credentials. ## Debunking Cloud Cost Optimization Myths Varsha debunks three common myths: **Myth 1: "Our Data is Clean"** In reality, most organizations have unused or forgotten resources that quietly inflate cloud bills. **Myth 2: "It's Just About Cost"** Effective optimization involves leadership, governance, application ownership, finance, engineering, and security teams. Each plays a role in controlling cloud spend. **Myth 3: "It’s Someone Else’s Job"** Cost optimization is a shared responsibility. It isn’t just an engineering or finance issue—it requires cross-functional collaboration and accountability. ## The Shared Responsibility Model When asked about who should be the "first responder" to cloud cost problems, Varsha advocates for a shared responsibility approach: "everybody has to do their part, right? It's not like you pin it on one person." **CTOs:** Must review projections regularly and balance modernization with budget constraints Application Owners: Know their applications intimately and can optimize tags, dependencies, and disaster recovery **Finance:** Provides regular monitoring and accountability **Engineers:** Implement deployment best practices and parameter optimization When everyone contributes, cost optimization becomes a natural part of the development lifecycle—not a separate burden. ## Key Takeaways for Cloud Leaders 1. **Budget for Dual Infrastructure Periods:** Plan for the reality of maintaining both on-premises and cloud environments during migrations. 2. **Evaluate MSP Needs Based on Organizational Maturity:** Consider your technical depth, timeline constraints, and resource availability when deciding on external partnerships. 3. **Embrace AI for Cost Visibility:** Move beyond static dashboards toward conversational, AI-powered cost intelligence that provides personalized, contextual insights. 4. **Address Misconceptions Head-On:** Recognize that cloud cost optimization is a multi-faceted discipline involving multiple stakeholders and metrics beyond just cost reduction. 5. **Implement Shared Responsibility:** Create accountability structures where every role has clear responsibilities for cost optimization within their domain. 6. **Focus on Multiple Metrics:** Consider cost, efficiency, sustainability, time, and governance as interconnected elements of successful cloud management. ## Looking Forward Varsha's insights reveal an industry in transition from reactive cost management to proactive, AI-enhanced optimization. The future belongs to organizations that can combine technical expertise with cultural change, leveraging AI to make cost intelligence accessible to all stakeholders while maintaining rigorous governance and accountability. As cloud environments become increasingly complex with AI workloads and multi-cloud architectures, the principles Varsha outlines—shared responsibility, comprehensive visibility, and strategic evaluation—will become even more critical for sustainable cloud operations. The conversation reinforces that successful cloud cost optimization isn't about finding the perfect tool or dashboard—it's about building the right processes, culture, and technology foundation that evolves with your organization's needs. * * * _Want to dive deeper into cloud cost optimization strategies? Connect with CloudKeeper to learn how we can help you implement these expert insights and build a sustainable, cost-effective cloud operation._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Season 1 of CloudKeeper's "Latte on Cloud Costs" podcast has been a remarkable journey through the complex landscape of cloud cost optimization and FinOps. Host ## **Meet Our Season 1 Guests** ## **Universal Truths: What Every Expert Agreed On** ### **1. Cost Optimization is a Continuous Journey, Not a Destination** All four guests made it clear that cloud cost optimization isn’t just a one-off task; it’s a continuous journey that demands ongoing focus and fine-tuning. Avinash pointed out, "Cost optimization is an ongoing activity," emphasizing how his team at Physicswalla integrates it into their everyday operations. Christian reinforced this by explaining that continuous optimization should become a habit within organizations, comparing it to other essential business practices that require consistent attention. This perspective challenges the common approach of treating cost optimization as a quarterly exercise or crisis response. ### **2. It's About Value Maximization, Not Just Cost Cutting** A recurring theme across all episodes was the shift in mindset from simply reducing costs to maximizing value. Victor articulated this perfectly: "Maximize the value instead of always dropping down," emphasizing that FinOps should focus on getting the most business value from cloud investments. Rakesh echoed this sentiment, stating that "FinOps is about making the most out of every dollar," and explained how his approach centers on resource utilization rather than just savings. This value-first approach helps organizations ### **3. Culture and Collaboration are Critical** Every guest highlighted the importance of creating a cost-conscious culture across the organization. Victor stressed that "FinOps creates the environment and culture for cost awareness," explaining how this cultural shift enables teams to make better decisions autonomously. Avinash declared that "It's everyone's job to optimize costs," describing how Physicswalla engages all teams in cost accountability. Rakesh emphasized the collaborative nature of effective cost management, noting that cloud cost optimization requires coordination across teams. This cultural emphasis represents a fundamental shift from traditional IT cost management, where only specific teams were responsible for infrastructure expenses. ## **Common Misconceptions Debunked** Our experts consistently addressed several dangerous misconceptions that plague organizations: ### **Myth 1: Moving to the Cloud Automatically Guarantees Savings** Rakesh made it clear that "Moving to the cloud doesn't guarantee savings." He pointed out that without the right optimization strategies in place, cloud expenses can quickly get out of hand. ### **Myth 2: Optimization is Straightforward** Christian pointed out that many companies suffer from "analysis paralysis," believing that cost optimization is simple when it actually requires technical expertise and careful implementation. ### **Myth 3: It's Only the IT Team's Responsibility** Everyone agreed that optimizing costs is a team effort. It takes collaboration among developers, operations, and business teams, with each group playing a vital role in the process. ## **Essential Strategies and Best Practices** ### **Start with Visibility and Measurement** **Tagging Strategy** : Rakesh emphasized that "implementing a **Key Metrics to Track:** * Unit economics (cost per customer/transaction) * Resource consumption patterns * ROI of optimization efforts * Data transfer costs (identified by Avinash as "the number one culprit") ### **Focus on High-Impact Areas** **Right-Sizing Resources:** Multiple guests highlighted the importance of matching resource allocation to actual needs, with Christian noting that understanding "specific metrics for each resource is crucial." **Automation with Purpose** : Victor cautioned that "automation should be evaluated for its actual necessity," ensuring that automated solutions actually provide value rather than adding complexity. **Prioritize by Impact** : Avinash recommended "focusing on large impact items" to yield significant cost reductions, while Christian suggested prioritizing high-cost services for better returns on investment. ### **Technical Implementation Focus** Christian brought a unique technical perspective, emphasizing that cost optimization requires hands-on implementation rather than just analysis. His Auto Spotting tool demonstrates how technical solutions can automate the use of spot instances for substantial savings. ## **Practical Tips for Getting Started** ### **Phase 1: Foundation Building** * Implement comprehensive tagging strategies. * Set up * Establish regular reporting mechanisms. * Build visibility into current spending patterns. ### **Phase 2: Culture Development** * Engage teams through hackathons and training. * Make cost considerations part of the development process. * Establish accountability across teams. * Create cost-conscious decision-making frameworks. ### **Phase 3: Advanced Optimization** * Implement automated right-sizing solutions. * Leverage * Optimize data transfer costs through architecture changes. * Implement scheduled scaling for peak and off-peak optimization. ## **The Role of FinOps Teams** A significant insight from multiple episodes was the importance of centralized FinOps teams. Rakesh highlighted that "a centralized FinOps team fosters a cost-conscious culture," while Victor emphasized focusing on "one aspect of FinOps at a time for better results." The consensus was that FinOps teams should: * Provide tools and visibility rather than dictate solutions * Enable other teams to make cost-conscious decisions * Measure and communicate the value of optimization efforts * Facilitate cross-team collaboration and knowledge sharing ## **Key Takeaways for Different Stakeholders** ### **For Leadership:** * Invest in building a cost-conscious culture * Support continuous optimization initiatives * Measure and communicate ROI of FinOps efforts * Ensure proper tooling and resources for teams ### **For DevOps/Engineering Teams:** * Integrate cost considerations into development processes * Implement comprehensive monitoring and alerting * Focus on technical implementation of optimization strategies * Collaborate closely with business teams on requirements ### **For Finance Teams:** * Move beyond simple cost cutting to value maximization * Partner with technical teams to understand cloud economics * Implement proper attribution and chargeback mechanisms * Focus on unit economics and business metrics ## **Conclusion** Season 1 of "Latte on Cloud Costs" has provided a comprehensive foundation for understanding modern cloud cost optimization. From Rakesh's emphasis on collaboration and visibility, to Christian's technical implementation focus, Victor's culture-building insights, and Avinash's real-world scaling experiences, we've gathered a wealth of practical wisdom. The common thread throughout all episodes is clear: successful cloud cost optimization requires a holistic approach that combines technical expertise, cultural change, continuous measurement, and relentless focus on value creation. As we move forward, these principles will continue to guide organizations toward more efficient and effective cloud operations. _Ready to start your cloud cost optimization journey? Connect with CloudKeeper to learn how we can help you implement these expert insights and maximize your cloud ROI._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents In today's enterprises, business intelligence is a crucial aspect of informed decision-making based on data. The type of visualization platform a business uses can have a huge impact on how successfully it fulfills its strategic goals and how productive it is. Google's Looker Studio and This in-depth study looks at both platforms in terms of important business factors, giving enterprise teams the technical information they need to make smart decisions. There is no one "winner" in the Looker Studio vs. Amazon Quicksight comparison. The best decision for your firm relies on its needs, current infrastructure, and long-term goals. ## **1. Understanding the Platforms: Looker Studio and Amazon Quicksight** Looker Studio and Amazon Quicksight are both cloud-based business intelligence tools that make sense of raw data. But their architectural roots and business positioning demonstrate that they do enterprise analytics in quite different ways. ### **What is Looker Studio?** Looker Studio, originally Google Data Studio, represents Google's concept of democratized business intelligence. It started out as a free visualization platform with the purpose of making data analysis accessible for corporate customers without requiring a lot of technical knowledge. The technology works seamlessly with Google's ecosystem, which includes Ads, Analytics, and Workspace apps. #### **Core Advantages of Looker Studio:** #### **Primary Limitations of Looker Studio:** * **Data Source Architectural Fragility or Schema Fragility:** The platform's data source reusability paradigm poses major maintenance problems, as schema changes can cascade across reports and disrupt computed fields. * Performance Constraints: Row constraints ranging from 150,000 to 1,000,000 records, depending on the connector type, impede enterprise-scale applications. * **Limited Advanced Analytics:** The platform lacks native support for advanced statistical analysis, machine learning insights, and predictive modeling capabilities. * **Third-Party Dependency:** Enterprise data communication generally requires expensive third-party connectors, with monthly expenses ranging from $200-500 per connector. ### **What is Amazon Quicksight?** Amazon Quicksight is Amazon's enterprise-grade business intelligence service, developed from the bottom up to manage enormous datasets with sub-second performance. The platform leverages AWS's cloud infrastructure and interfaces tightly with the broader AWS analytics ecosystem. #### **Core Advantages of Amazon Quicksight:** #### **Primary Limitations of Amazon Quicksight:** * **Learning Curve Complexity:** The platform requires moderate technical expertise and AWS familiarity, potentially slowing adoption among non-technical business users. * **Licensing Investment:** While cost-effective at scale, the per-user monthly licensing model represents a significant upfront investment compared to free alternatives. * **AWS Ecosystem Dependency:** Organizations without existing AWS infrastructure may face additional complexity and costs in achieving optimal implementation. For organizations that already have an existing setup, I recommend ## **2. Pricing Models and Total Cost of Ownership** Understanding the full cost implications of each platform involves examination beyond initial license payments, incorporating hidden expenses, scalability issues, and the long-term total cost of ownership. **Winner:** **Amazon Quicksight** - AWS Amazon Quicksight billing, being transparent, offers superior cost predictability and often results in a lower total cost of ownership at the enterprise scale. To further optimize your Amazon Quicksight costs, you should ## **3. Architecture and Infrastructure Considerations** Each platform's core architectural choices result in essentially distinct capabilities, security postures, and scalability attributes that have an immediate influence on corporate deployments. **Winner:** **Amazon Quicksight** - Dedicated infrastructure provides superior enterprise security and compliance capabilities. ## **4. Data Connectivity and Integration Capabilities** The capacity to effectively and consistently connect to several data sources is the basis of every successful business intelligence solution. **Winner: Amazon Quicksight** - Comprehensive native connectivity eliminates third-party dependencies and provides superior enterprise data access. ## **5. Data Modeling and Preparation Features** The platform's data modeling capabilities determine its suitability for complex analytical requirements and enterprise-scale implementations. **Winner: Amazon Quicksight** - Superior data modeling flexibility and enterprise-scale capabilities. ## **6. Visualization Capabilities and Advanced Analytics** The platform's analytical capabilities determine its suitability for various business intelligence use cases and user sophistication levels. **Winner: Amazon Quicksight** - Superior visualization variety and significantly advanced AI/ML integration capabilities. ## **7. Collaboration and Distribution Features** Effective collaboration and sharing capabilities are essential for enterprise-wide adoption and organizational alignment. ### **Mobile and Remote Access Capabilities** ### **Alerting and Notification Systems** ### Embedding and API Capabilities **Winner: Amazon Quicksight** - Superior mobile applications, comprehensive alerting, and advanced embedding capabilities. ## **8. Performance and Scalability Analysis** Performance characteristics directly impact user adoption and the platform's viability for enterprise-scale implementations. ### **Data Processing and Query Performance** ### **Scalability Architecture** **Winner:** **Amazon Quicksight** - Unmatched performance and scalability for enterprise workloads. ## **9. Security and Compliance Framework** Enterprise security requirements often determine platform viability for regulated industries and security-conscious organizations. **Winner: Amazon Quicksight** - Comprehensive enterprise security architecture and extensive compliance certifications. ## **10. User Experience and Implementation Considerations** The balance between platform capability and user accessibility determines adoption success across different organizational roles. ### **Implementation Timeline and Complexity** **Winner: Google Looker Studio** - Superior initial user experience and faster time-to-value for basic requirements. ## **11. Ecosystem Integration and Extensibility** ### **Third-Party Integration Ecosystem** ### **Programmatic Access and Automation** **Winner: Amazon Quicksight** - Comprehensive ecosystem integration and superior programmatic capabilities. ## **12. Enterprise Support and Professional Services** Support quality and availability directly impact implementation success and ongoing operational effectiveness. ### **Vendor Support Models** ### **Migration and Professional Services** **Winner: Amazon Quicksight** - Comprehensive enterprise support infrastructure and professional services availability. ## **13. Return on Investment and Strategic Considerations** Understanding the long-term value proposition requires analysis of both quantitative costs and qualitative benefits. ### **Implementation and Operational Costs** Total Cost of Ownership Analysis: ### **Strategic Value Considerations** **Winner: Amazon Quicksight** - Superior long-term value proposition and strategic alignment for enterprise growth. ### **Strategic Recommendations** This detailed research finds that Amazon Quicksight outperforms in 10 of the 13 evaluation categories, particularly in performance, scalability, security, and advanced analytics. However, the best option is determined by the specific organizational needs and strategic goals. ### **Recommendation Framework** **Choose Amazon Quicksight for:** * **Enterprise-Scale Requirements:** Organizations supporting 500+ users or analyzing datasets exceeding 100 million records * **AWS Ecosystem Integration:** Companies with existing AWS infrastructure investments seeking seamless integration * **Advanced Analytics Capabilities:** Teams requiring machine learning insights, predictive analytics, or natural language querying * **Regulatory Compliance:** Industries with strict security, privacy, or compliance requirements (healthcare, financial services, government) * **Long-Term Scalability:** Organizations anticipating significant growth in data volume and user base **Choose Looker Studio for:** * **Google Ecosystem Integration:** Organizations heavily invested in Google Analytics, Google Ads, and Google Workspace for use cases such as * **Budget-Constrained Deployments:** Small-to-medium enterprises with limited BI budgets requiring immediate value * **Simple Reporting Requirements:** Teams needing basic dashboards without complex analytical requirements * **Rapid Implementation:** Scenarios requiring dashboard deployment within days rather than weeks * **Non-Technical User Base:** Organizations with limited technical resources and a preference for self-service analytics ### **Strategic Considerations for Decision Makers** The decision between Looker Studio and Amazon Quicksight is crucial to your organization's business intelligence strategy. **Amazon Quicksight's architectural benefits** , particularly the SPICE engine's ability to handle 2 billion rows with sub-second performance, extensive connectivity to the AWS ecosystem, and advanced AI capabilities, make it the clear choice for enterprise-scale applications. However, **Google Looker Studio's accessibility and Google ecosystem integration** add substantial value to enterprises with unique requirements that match its capabilities. The platform's strength comes from its ability to democratize basic data visualization within Google's ecosystem. ### **Key Decision Factors:** 1. Current and projected data volume requirements 2. Existing cloud infrastructure and ecosystem investments 3. Security and compliance requirements 4. User sophistication and technical capabilities 5. Budget constraints and total cost of ownership considerations 6. Long-term strategic data architecture vision ## **Final Recommendation** Organizations researching business intelligence platforms should consider **Amazon Quicksight for enterprise implementations that require scalability, powerful analytics, and full security**. The platform's solid architectural foundation, transparent pricing strategy, and deep integration with the AWS ecosystem ensure compelling long-term value. **Looker Studio is still useful for narrow applications, including Google ecosystem integration, financial limits, and minimal reporting requirements**. However, companies should carefully consider the hidden costs and scale constraints before committing to long-term solutions. The most important factor is to ensure that platform capabilities fit with corporate requirements. Although both platforms are evolving, their core architectural principles and strategic positioning within their respective ecosystems are likely to remain stable. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Viransh is passionate about exploring Cloud Computing and AI. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents Being aware of the client's actual IP address is important in cloud-native architectures today—logging, geolocation, security, personalization, compliance, and rate limiting. Yet, when you add ### **1. Application Load Balancer (ALB) & X-Forwarded Headers ** * **How it works** ALBs run at Layer 7 (HTTP/HTTPS). They transparently maintain client IP addresses by injecting regular HTTP headers—primarily the X-Forwarded-For header—so your backend can easily get the real IP of the client. * **Header modes** ALBs have three modes: **a)** append (default): Appends the client IP to the X-Forwarded-For header—maintaining existing values. **b)** preserve: Does not modify the header. **c)** remove: Removes the header. You can set this field through the AWS Console or CLI. * Usage tips Be careful with X-Forwarded-For—only trust values added within your secure AWS environment. Don't use or expose this header to untrusted clients. ### **2. ALB + AWS Lambda: Capturing Client IP in Functions** If your ALB forwards to This pulls out the client's original IP (the first one in the list) and nicely falls through to the AWS Lambda's own sourceIp if the header is not present. ### **3. Classic AWS Load Balancer (CLB) & Instance-Level Choices ** CLBs (Layer 4/7 hybrid) can support Proxy Protocol as an option: * CLBs forward traffic normally without the proxy protocol—logging will show the AWS load balancer's IP address. * When Proxy Protocol is enabled, the connection context (such as source IP and port) is appended in front of every request. Your backend has to parse that header accordingly. ### **4. Network Load Balancer (NLB): Layer 4 and Raw Client IP** * **Default behavior** NLBs (Layer 4) maintain the source IP by default—backend instances receive the client's IP as the connection origin. * **When Proxy Protocol Is Needed** Scenarios such as remote, cross-VPC targets, PrivateLink, or hairpinning may obscure the source IPs. Proxy Protocol v2 can be enabled on NLBs to explicitly pass client data (including IP, port, protocol, checksum, and more) in the TCP header. **PrivateLink Connection**. Source: **Hairpinning traffic through a Network Load Balancer.** Source: * **Important:** Your backend must support parsing Proxy Protocol v2—or it will break connections. ### **5. NLB Behind AWS Global Accelerator: Preserving IP Across the Edge** AWS Global Accelerator in front of an NLB makes client IP retention even more critical: * **Feature:** Global Accelerator can now retain the original client IP via NLB endpoints, enabling backend destinations to receive the actual source IP—even through anycast edge routing. * **Why it matters:** Supports geo-based routing logic, IP-based auditing, compliance checks, and user-specific personalization. * **Requirements:** The NLB should be in a VPC with a security group that permits client IP addresses and health checks. ◦ If the NLB is internal, the VPC should have an Internet Gateway. Both Accelerator and NLB should be set to keep the client IP. Source: ## **Quick Comparison: Which Tool for Which Use Case?** ## **Considerations** 1. **Security First** Never trust client-supplied headers unless they are from secured AWS load balancers in your own VPC. 2. **Ensure Backend Compatibility** If proxy protocol is being used, ensure that your backend application supports and anticipates it (e.g., NGINX, HAProxy, Envoy). 3. **CloudFormation Automates Setup** For instance, AWS offers templates for Proxy Protocol configurations with NLB + NGINX or HAProxy—for testing by hand. 4. **IP + Port Preservation** ALB can also retain the client port if it is set right through the xff_client_port configurations. 5. **Global Accelerator Use Cases** Maintaining IP with Global Accelerator is best suited for geo-targeted functionality, data residency compliance, and analytics. ## **Summary** Capturing an actual client IP in AWS is load-balancer and architecture dependent: * **ALB** —use X-Forwarded-For * **Lambda behind ALB** —parse header in code * **CLB** —use Proxy Protocol if necessary * **NLB** —native IP or Proxy Protocol for edge or cross-network * **Global Accelerator** —allow IP preservation on the accelerator and NLB Selecting the proper method provides greater logging, enhanced personalization, greater security, and regulatory compliance—all part of cloud computing applications today. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Jatin is an AWS-certified SysOps Administrator Associate with extensive expertise in AWS cloud services and a broad spectrum of DevOps tools. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents An AWS Reserved Instance (RI) is a billing discount that allows you to save on your compute usage costs. RIs are considered to be one of the most effective ways for AWS cost optimization. AWS says, “With Reserved Instances, you can save up to 75% over equivalent on-demand capacity.” Now think about an organization having 10 AWS accounts, a total account billing $80,000 monthly, running on-demand compute instances. According to AWS reserved instance pricing, your bill will effectively reduce from $80,000 to somewhere around $20,000! That looks awesome! However To address these challenges effectively, you need to leverage DevOps and automation tools. * **Use AWS Cost Explorer:** AWS Cost Explorer is a free tool that provides you with insights into your AWS usage and costs. You can use it to visualize your RI utilization and identify opportunities for AWS cost optimization. * **Leverage AWS Lambda:** AWS Lambda is a serverless compute service that can help you automate your RI management tasks. For example, you can create a Lambda function tuned to the AWS reserved instance pricing, to automatically purchase RIs when they are available at a discounted price, or to modify or exchange RIs based on your usage patterns. * **Use AWS CloudFormation:** AWS CloudFormation is a service that lets you define and manage your AWS infrastructure as code. You can use * **Use AWS Trusted Advisor:** AWS Trusted Advisor is a service that provides you with real-time recommendations to help optimize your AWS infrastructure. It can also provide you with recommendations for optimizing your RI usage, such as identifying underutilized RIs and opportunities to modify or exchange RIs. * **Use AWS Organizations:** AWS Organizations is a service that lets you manage multiple AWS accounts as a single entity. You can use AWS Organizations to centralize your RI management and optimize their usage across all your accounts. While AWS RI management tools can be useful, there are some potential drawbacks and limitations that you should be aware of: * **Limited customizability:** AWS RI management tools may have limited customizability and flexibility compared to third-party tools. This may be a concern if you have specific use cases or requirements that are not supported by the AWS tools. * **Complexity:** Some AWS RI management tools may be complex to set up and use, requiring advanced technical skills and knowledge. This may be a barrier for some users, especially smaller organizations or those with limited resources for AWS cost optimization. * **Cost:** While some AWS RI management tools are free, others may come with additional costs, which may not be suitable for organizations with limited budgets. * **Limited integration:** Some AWS RI management tools may have limited integration with other AWS services. This may limit your ability to * **Lack of Alerting System:** AWS RI Management tools do not provide a notification or alerting system to track daily budget breaches according to the AWS reserved instance pricing, upcoming RI expiries, and RI utilization thresholds. There needs to be a proper RI implementation strategy, to bring in the maximum benefits with minimum drawbacks or complexities. A _Do you think you need a hand with optimizing your EC2 resources and managing Reserved Instances?_ _CloudKeeper Auto could help you streamline your entire AWS EC2 infrastructure and bring in substantial savings._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Cloud Financial Management has evolved into a pivotal aspect of modern businesses harnessing Cloud services. Financial Operations (FinOps) serves as the linchpin in ensuring efficient Cloud cost management. This comprehensive guide aims to delve deeply into the significance of FinOps services, emphasizing the necessity of building a robust team and culture around it while exploring key elements ## **Understanding FinOps: Navigating Cloud Financial Management** In today's tech-driven landscape, the Cloud has revolutionized how businesses operate. However, this scalability often brings complexities in managing costs effectively. FinOps bridges this gap, merging financial best practices with technological innovation. It optimizes Cloud spending by aligning resources with actual needs while maintaining performance and scalability. ### **The Core Principles of FinOps** At the heart of FinOps lie fundamental principles that guide its implementation: #### **Visibility and Transparency** Providing clear insights into Cloud expenditure to stakeholders, ensuring transparency in cost allocation, and enabling informed decision-making. In Cloud FinOps services, visibility and transparency are the bedrock for effective cloud cost management. It entails providing #### **Accountability and Responsibility** The principle of accountability and responsibility in AWS FinOps revolves around fostering a culture where teams take ownership of their cloud usage. It involves instilling a sense of responsibility among individuals and teams, making them cognizant of the financial implications of their actions in the cloud environment. When teams understand how their decisions impact costs, they become more proactive in optimizing cloud resources and ensuring cost efficiency. Creating a culture of ownership encourages teams to actively participate in cost management. This might involve setting clear guidelines, establishing budgets for projects, or implementing policies that incentivize cost-conscious behaviors. It's about empowering teams to make decisions aligned with both their operational needs and the financial objectives of the organization. #### **Efficiency and Optimization** Continuously refining processes to optimize resource utilization, ensuring cost efficiency without compromising performance. It's not merely about reducing costs but rather about maximizing value from cloud investments. This principle emphasizes the importance of regularly reviewing and fine-tuning cloud resources to eliminate waste and enhance efficiency. It involves assessing whether the current resource allocations are aligned with actual needs and making adjustments accordingly. This might include rightsizing instances, ### **The Value of Embracing Cloud FinOps** Implementing AWS FinOps practices yields numerous tangible benefits: * **Cost Efficiency:** Cloud FinOps methodologies serve as a strategic approach to scrutinize cloud expenditure, enabling organizations to pinpoint and eliminate unnecessary costs. By leveraging detailed analytics and optimization techniques, companies identify areas where resources are underutilized or overspent, leading to substantial cost reductions. * **Collaboration between teams:** FinOps transcends traditional departmental barriers, fostering collaboration among finance, operations, and IT teams. By encouraging shared responsibility for cost management, Cloud FinOps creates a cohesive environment where teams collectively work towards optimizing cloud spending. This collaborative culture not only enhances cost control but also promotes innovative solutions and cross-functional understanding. * **Continuous Improvement:** Central to FinOps is the principle of continual enhancement in cost management strategies. Organizations employing AWS FinOps adopt an iterative approach to refine their cloud cost management techniques. This involves regularly reassessing spending patterns, identifying optimization opportunities, and adapting strategies to evolving business needs. This iterative refinement drives ongoing efficiency and adaptability in a dynamic cloud environment. ### **Building a FinOps-Centric Team** #### **People: The Cornerstone of Success** * Leadership Support: Securing buy-in from top leadership to instill a cost-conscious culture across the organization, setting a precedent for prudent financial practices. * Cross-functional Collaboration: Bringing together diverse skill sets from finance, operations, and IT to address cost management challenges holistically, fostering innovation through varied perspectives. * Skill Development: Investing in training programs and workshops to equip teams with Cloud FinOps expertise, enabling them to leverage tools and strategies effectively. #### **Principles: Guiding the Way** * Data-Driven Decisions: Leveraging analytics to make informed choices about resource allocation and usage, ensuring data-backed decision-making and accurate predictions. * Automation and Tooling: Implementing automated tools for continuous monitoring, analysis, and optimization, minimizing manual errors and improving operational efficiency. * Cost Accountability: Instilling a culture where teams understand the financial implications of their actions, promoting a sense of ownership and responsibility in cost management. #### **Processes: The Operational Backbone** * Budgeting and Forecasting: Creating accurate forecasts and budgets based on historical data and business projections, enabling better cost predictability and resource allocation. * Continuous Monitoring: Regularly assessing spending patterns and optimizing resource allocation accordingly, facilitating proactive cost management and optimization. * Governance and Compliance: Implementing policies and controls to ensure compliance with industry standards and internal regulations, mitigating risks associated with non-compliance and overspending. #### **Technology: Empowering Efficiency** * AWS Cloud Cost Management Tools: Leveraging specialized tools for real-time visibility into cloud spending and resource utilization, aiding in * AI and Machine Learning: Utilizing advanced technologies to predict and optimize cloud usage patterns, enhancing efficiency and cost-effectiveness through predictive analytics. AI-driven predictive analytics provide insights into future usage trends, enabling proactive decision-making in resource allocation and cost management. * Automation: Automation stands as a ## **Conclusion: Embracing the FinOps Mindset** Beyond being a methodology, FinOps represents a commitment to excellence in AWS cloud financial management. Aligning people, principles, processes, and technology enables organizations to embark on a successful AWS FinOps journey. Cultivating a culture that values technological innovation alongside financial prudence is key, which can be leveraged with reliable In conclusion, the integration of FinOps principles and practices empowers organizations to transform their cloud operations. Embracing the FinOps mindset ensures that cloud spending is not just managed but optimized, contributing significantly to the overall success and sustainability of businesses in the ever-evolving cloud landscape. ## **Kickstarting your FinOps journey with CloudKeeper** Organizations can navigate the complexities of cloud cost optimization, ensuring not just savings but also an optimized cloud infrastructure tailored to their unique needs. CloudKeeper, a FinOps & cloud cost optimization solution, is committed to delivering substantial cloud savings, helping organizations kickstart their Cloud FinOps journey. _**CloudKeeper offers a tailored suite of**_ _**and**_ _**, catering to diverse customer segments**_. CloudKeeper's distinction as an AWS Premier Partner and FinOps Foundation Premier Partner, along with its influential role on the FinOps Foundation's Governing Board, underscores its commitment to shaping the future of Cloud FinOps practices. Navigating the intricacies of cloud cost optimization is pivotal for organizations, ensuring not just savings but also an optimized infrastructure tailored to unique needs. Expertise in automated management, robust cost visibility tools, and Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents ## **1. What happens by default in normal EKS nodes** When you launch an Amazon EKS node, either through Managed Node Groups or a self-managed **/etc/eks/bootstrap.sh** runs automatically. This script makes the node join the cluster and sets important kubelet parameters. By default, the script calculates how many pods a node can run based on the instance type and the number of ENIs (network interfaces) available. When **--use-max-pods=true** , the script internally calls /etc/eks/max-pods-calculator.sh to find the right value based on ENI and IP limits. For example, an m5.large instance might be assigned **--max-pods=29**. This is the safe and recommended behavior by AWS for standard EKS clusters that use the default ## **2. When we set****--use-max-pods=false** If we configure the bootstrap script like this: The script skips the ENI-based calculation and uses the provided value directly. That means the kubelet will allow up to 110 pods on that node, regardless of ENI limits. This is only safe if your networking setup supports that many IPs, for example, when you are using prefix delegation or a custom CNI. ## **3. What user data Karpenter uses by default for AL2 AMI** Karpenter does not use the same default AWS user data. It automatically generates its own MIME-style user data for Amazon Linux 2 nodes. Here is the default format from the Karpenter documentation: By default, Karpenter sets **--use-max-pods=false** and defines **--max-pods=110** for every AL2 node it launches. ## **4. Why Karpenter disables auto-calculation** This behavior is intentional. Karpenter disables the AWS **max-pods-calculator.sh** because that script still uses the old Amazon ENI-based logic and does not account for prefix delegation, which increases the number of available IPs per ENI. Since most modern Amazon EKS clusters now use prefix delegation by default, the calculator would assign a value that is too low. To avoid this, Karpenter does the following: * Sets **--use-max-pods=false** to skip automatic calculation. * Manually sets **--max-pods=110** as a safe upper limit. * Keeps node behavior consistent across all instance sizes. * This makes pod density predictable and keeps networking stable. ## **5. When to override this manually** You usually do not need to change Karpenter’s user data. Only override it if: * You are using a custom AMI that is not Amazon EKS optimized. * You are using a non-VPC CNI like Calico or Cilium. * You want to adjust pod density for specific workloads. Example override in Amazon EC2NodeClass: ## **6. Best Practice Summary** ## **7. Final takeaway** * For normal Amazon EKS nodes, keep **--use-max-pods=true**. * For Karpenter, it is already **false** , and that is the correct setting. * Do not mix both settings unless you fully understand your network limits. * If you are unsure, stay with the default setting because it is tested and safe. ## **8. Quick check command** To verify what value your node is using, run: * **cat /etc/systemd/system/kubelet.service.d/10-kubelet-args.conf | grep max-pods** This command shows the active **--max-pods** value used by the kubelet. ## **9. How Karpenter supports prefix delegation mode** Prefix delegation is a feature in the Amazon VPC CNI plugin that allows each ENI to receive a small prefix, usually a /28 subnet, instead of individual secondary IPs. Each prefix contains 16 IP addresses that the CNI can assign directly to pods without extra API calls to Amazon EC2. This improves IP allocation speed and lets each node handle more pods. Karpenter supports prefix delegation completely, even though it sets **--use-max-pods=false**. It does this by staying out of the ENI-based calculation logic and letting the CNI handle IP management dynamically. When Karpenter launches a node, it runs the bootstrap script with: This means the bootstrap script does not run **/etc/eks/max-pods-calculator.sh** , which is still based on old ENI logic and does not understand prefix delegation. Instead, Karpenter sets a fixed kubelet limit of **--max-pods=110** , which is high enough for most instance types when prefix mode is active. Prefix delegation itself is managed by the VPC CNI plugin, not by Karpenter. You enable it using the aws-node DaemonSet in the kube-system namespace by setting the following environment variables: After enabling these, each node gets one or more /28 prefixes attached to its ENIs. The VPC CNI then assigns IPs to pods from those prefixes automatically. Karpenter does not need to calculate anything; it just ensures kubelet allows enough pods. This design separates responsibilities clearly: With this setup, Karpenter nodes fully benefit from prefix delegation. The VPC CNI handles pod IP assignment, and Karpenter ensures kubelet does not block scheduling too early with old ENI limits. This keeps the node setup simple, allows efficient pod density, and ensures the cluster uses modern VPC networking features properly. ## **Closing note** This flag may seem small, but it affects how efficiently your cluster uses each node. Karpenter’s default configuration (--use-max-pods=false) is intentional and matches how Amazon EKS works with prefix delegation today. Avoid changing it unless there is a clear technical reason. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Gourav specializes in helping organizations design secure and scalable Kubernetes infrastructures on AWS. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents The cloud initiatives of your organization scale with the company’s growth. The role of ## **AWS Enterprise Discount Program (AWS EDP)** An AWS EDP is a cloud pricing program that provides a discount to organizations in exchange for an annual consumption commitment. The size of the discount is directly proportional to your committed annual spend and term length. This plan is highly beneficial for organizations if: - In the next three years, your projected spend is more than $1 million/annum across all AWS services. (The commit requirement might be lower in a few geographies) - You can accurately forecast your service consumption requirements. - You are already subscribed to AWS Enterprise Support or see a value in opting for it, as signing up for an EDP is a mandatory requirement. - The projected AWS spending is unlikely to go down but is expected to continuously grow in the future - You do not have any plans to switch your cloud provider during the EDP tenure. In order to avoid the risk associated with AWS EDPs, ensure that your organization is likely to consume the amount of resources that are committed. Usage of ISV tools like NewRelic, DataDog, Snowflake, F5, etc. can also be routed via AWS Marketplace to offset AWS EDP commitment. With said that, It is always advisable to have an experienced Cloud Partner by your side as they ensure to devise a perfect AWS EDP plan that is well aligned with the business needs & priorities with better negotiation and maximum savings. ## **How can CloudKeeper help you with AWS EDP?** Here’s how ### **Maximizing Cloud Savings with the AWS EDP Plan & CloudKeeper Guaranteed Saving** As an AWS Premier Consulting Partner, In addition to the discount you'll receive with the AWS EDP plan, CloudKeeper provides guaranteed savings of up to 15% on your entire AWS bill at no extra cost. This means that you can enjoy even more cost savings over and above the EDP benefits. ### **Better Cost Management of** Once the plan is ready we can help validate the overall progress of EDP consumption and outline the best ways to meet spending commitments. Our proprietary cost management platform CK Lens™ offers you a granular view of your infrastructure usage costs to ensure efficient AWS deployment and cost optimization. It also helps you understand cloud cost spending patterns, allocation, chargebacks, and tagging. It offers you recommendations for right-sizing & right-costing cloud usage. Furthermore, periodic assessments by our AWS-certified cloud engineers ensure the success of your AWS EDP Plan. ### **Analyzing Critical Factors & Variables before finalizing AWS EDP Plan** With our diverse experience of working with global clients in finding their best AWS EDP plan, we know the nitty gritty that comes along with it. Discount plans may appear attractive at first glance, but they require nuanced analysis to determine if they are actually profitable based on multiple factors. Some of these factors are like using the latest generation instance types, using the right size instance types, new ongoing initiatives & planned initiatives in the coming quarters/years, adoption of new technologies/frameworks, and migration to/from cloud providers. The finalization of the AWS EDP plan requires a deep understanding of how various services of AWS impact costs. CloudKeeper examines the factors and variables that have significantly impacted past cloud usages, such as costs, security issues, unexpected overruns, and more, as well as the upcoming market trends that may impact your future user demands. Subsequently, many businesses, especially the ones that are new to the cloud benefit greatly from a reliable cloud partner at this critical phase. ### **Taking away the burden of Cloud Support** The real journey does not end at AWS EDP plan selection, but rather begins here. As the business expands, support costs required to optimize resources and reduce vulnerabilities can cost a pretty penny, bringing you back to square one. With CloudKeeper you can easily navigate through this. We are one of the very few ## **The Final Thoughts** Before pursuing any AWS discount program, make sure to do your own due diligence. AWS EDP offers many advantages, but that doesn’t mean they’re right for every organization. A detailed examination and strategic planning should help you determine if it is potentially the right plan for you. CloudKeeper is actively managing tens of millions of AWS EDP spends across multiple customers and as a partner we ensure that you navigate seamlessly through cloud transformation and ## **Related Blog :** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Complete Guide to AWS PPA Contract Negotiation for Growing Enterprises A practical guide to AWS PPA or EDP negotiations, covering commitments, discounts, flexibility, risks, and best practices to help growing enterprises secure better pricing and long-term cloud value. By Team CloudKeeper 19 Dec, 2025 Ask the Cloud Expert: A Deep Dive Q&A on AWS PPA In this Q&A, CloudKeeper’s AWS PPA expert Aman Dixit shares real-world insights to help clients navigate PPAs and make smarter, cost-effective decisions. By Team CloudKeeper 05 Sep, 2025 Introducing the AWS EDP Tracker in CloudKeeper Lens AWS EDP Tracker is a real-time interactive dashboard that gives you end-to-end visibility to monitor, forecast, and optimize your EDP spend throughout its term. By Harsh Agarwal 06 May, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents In the cloud era, one of the standout benefits of migrating to the cloud is the promise of seamless, uninterrupted services. Businesses rely on this continuity to maintain smooth operations and avoid disruptions. To fully leverage this advantage, you should have a robust cloud support system, which is crucial for managing outages, interruptions, and technical challenges effectively. Cloud support options vary widely, ranging from basic billing and payment support to extensive end-to-end support programs by hyperscalers or even the more specialized third-party offerings catering to niche use cases. AWS, for instance, offers a spectrum of support tiers designed to meet different needs. Basic tiers like AWS Developer Support, costing under $30 a month, cover general queries and billing issues but often have slower response times and limited service access. AWS offers higher-tier support for organizations with more complex needs, including the renowned AWS Enterprise Support stands out with its extensive range of services which includes proactive planning, advisory services, automation tools, and 24/7 access to expert guidance. With a dedicated Technical Account Manager (TAM), you receive However, AWS Enterprise Support does come with a significant cost, starting at around $15,000 per month. This investment may not be suitable for every organization, and AWS has specific criteria for qualifying for this level of support. Additionally, some AWS programs, like the The key is to strike a balance—leveraging the benefits of premium cloud support while managing costs effectively. This needs a tailored approach to meet your organization's needs effectively and economically. ## **Partner-led Enterprise Support - Top-tier Services at a Fraction of the Cost** For businesses who need a wide range of cloud support offerings but cannot commit to a large service cost, the right way to go about is the Partner-led Enterprise Support program. This involves qualified AWS partners offering the same level of support, but also sharing some of their partner benefits with their customers in the form of lower costs and commitments. ### **How does it work?** AWS partners who have qualified for the AWS Solution Provider partner program can offer Partner-led Enterprise Support to their customers. They undergo rigorous certification processes and once qualified, establish a Support Agreement with AWS, outlining the services, SLAs, and responsibilities. When the partner onboards a customer for the Partner-led Support program, they become their primary point of contact, providing technical support and guidance. The In case any cloud support issues require deeper cloud expertise or an escalation with the hyper scaler, the partner can access the AWS support team and raise tickets on behalf of the customer. It adds an extra layer of assistance between the customer and AWS, offering comprehensive support at a significantly reduced cost. ## **Let’s Compare the Offerings** Although both Partner-led Support and AWS Enterprise Support offer access to certified experts, proactive support, and efficient problem resolution, there are a few notable differences between them. Here’s a snapshot of how the two programs compare. Partner-led Support provides nearly all the core support services AWS Enterprise Support offers. However, there are two key differences: * **Training Credits:** AWS Enterprise Support includes 500 training credits per year, which can be used to * **Pricing:** AWS Enterprise Support follows a tiered pricing model, averaging around $15,000 monthly. In contrast, Partner-led Support utilizes a custom pricing model, which is significantly more affordable. ## **Advantages of Partner-Led Support** While the offerings of Partner-led Enterprise Support and normal AWS Enterprise Support are very similar, here are the benefits you can expect while signing up for the former. * **Cost Savings:** Partner-led Support generally comes at a lower cost than AWS Enterprise Support, making it accessible for organizations with tighter budgets. * **Flexible Pricing:** Partners offer * **Lower Costs for Partner Programs:** Customers who sign up for programs like AWS EDP could avail of Partner-led Support as an alternative, to fulfill the mandate at a reduced cost. * **Personalized Service:** With a focus on customer relationships, Partner-led Support often includes tailored advice and solutions specifically aligned with the business’s unique requirements. * **Extended Expertise:** Partners bring additional expertise in cloud-native technologies and DevOps, which can be beneficial for more specialized cloud support needs. ## **Dependency on AWS** Partner-led Support covers a broad range of features suitable for nearly all business use cases. However, there are specific instances where support still relies directly on AWS services. * **Service Limit (Service Quota) Increases:** Requests for quota increases must still be handled directly through AWS. * **Pre-warming Requests for Load Balancer:** Essential for avoiding latency issues during major events, this request must be managed through AWS. * **RCAs for AWS Services Issues:** Root Cause Analysis for issues such as latency on load balancers and network status checks failing on EC2 instances must be addressed with the AWS team. * **AWS Service Degradation:** Direct cloud support from AWS is necessary for * **Account and Billing Issues:** Problems with credits, refunds, or account-related queries need to be resolved directly with AWS. However, the partner can act on behalf of the customer, raising support tickets and working with them in resolving their issues promptly. ## **Premier Support Services by CloudKeeper** At CloudKeeper, we offer premium cloud support services, expert guidance, and round-the-clock assistance to you, with In addition to all the benefits of the partner program and the cost discounts, we also offer certain extended benefits at no additional cost. * **Support for DevOps & Cloud-native Technologies: **Specialized cloud support for modern DevOps practices and cloud-native technologies, enhancing your cloud operations. * **Adoption of New AWS Services:** Guidance on adopting new AWS services and technologies, including transitioning from self-managed solutions to AWS-managed services. * **Workload Modernization:** Assistance with modernizing workloads, such as * **Cloud Automation:** Supports implementing cloud automation to streamline operations and optimize performance. * **Cloud Cost Optimization:** Resource-level insights and expert strategies to optimize cloud costs for your entire infrastructure. * **Performance Optimization:** Unique techniques and tools to enhance the performance of your cloud environment. * **Consulting and Advisory:** Expert advice on cloud innovations, migration strategies, and resource optimization. CloudKeeper offers you almost everything that you get with AWS Enterprise Support and more, at a fraction of the original cost. ## **Conclusion** The AWS Enterprise Support program offers a comprehensive range of cloud support for all kinds of businesses but has a substantial cost barrier. Partner-led Support Program is a valuable alternative that offers the core support services at a more accessible price point. In addition to the cost discounts, Partner-led Support by Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Cloud provides you with various benefits, including significant cost savings, increased workforce productivity, operational resilience and continuity of services, along with business agility. Organizations around the world realize the importance of Cloud, with 83% of enterprise workloads expected to be in the cloud by 2020. According to a 2019 survey, 91% of businesses utilize public cloud, while 69% of enterprises deploy hybrid cloud solutions, involving both public and private clouds. Amazon Web Service (commonly known as AWS), a subsidiary of Amazon, is the world’s leading public cloud provider, catering to over a million active users worldwide. AWS provides you with on-demand cloud computing platforms on a pay-as-you-go model. AWS solutions are economical, scalable, and reliable, and are used by organizations of all sizes, including enterprises like AirBnB and GE. Are you planning to deploy your applications on the AWS cloud? Read on to learn how you can simplify the process. ## **AWS Migration for your Business** You can deploy your digital assets like data, applications, and other business elements, entirely or partially, to a cloud computing environment through a process called cloud migration. One of the most common models of cloud migration is the transfer of data and applications from a local data center to a public cloud like AWS cloud. Migration to AWS is not always as simple as ‘lifting and shifting’ applications (shallow cloud integration) from the on-premise data center to the AWS cloud. If you want a deep cloud integration to take advantage of cloud capabilities, you may have to modify certain applications. You may face challenges, including issues with legacy application migration, data security, and regulatory compliance. You require significant planning and expertise for AWS migration to save time and costs and meet your business objectives. Here is our 7 step process to migrate from an on-premise data center to AWS cloud: ### **Step 1- Preparation & Planning** Proper preparation and planning before migration help make the process simple and hassle-free. * Start by finding out which applications can be migrated to the AWS cloud easily and which ones would need modifications. * Modify the application architecture to allow servers, networks, and data services to run and interact in the cloud computing environment. * Plan how you will operate and run services on the cloud after completing the migration. * If you can not afford downtime for your users while migrating, formulate a strategy to transition without impacting them. * Evaluate your security on a public cloud and plan your migration taking data security and regulatory compliance into account. * Define cloud migration Key Performance Indicators (KPIs) for your applications and services to track the progress and discover any issues. ### **Step 2- Discovery & Migration Approach** In this step. you start by collecting information about servers, applications, and data along with their inter-dependencies. Choose a discovery tool, like RISC, to track migration tasks and get more visibility into the migration progress. A discovery tool helps you gather information about the inter-dependence of the workloads by collecting server utilization data like configuration, usage, and behavior on your on-premise data center. Plan your data and application migration based on these dependencies. Then, you finalize a migration approach for the applications. Below are the 6R’s of application migration- you can follow one of these approaches for each app: * **Rehost** : You simply ‘lift-and-shift’ the app from a local data center to cloud * **Replatform** : Here you lift the app, change the operating system or database version and move it to cloud- this also know as ‘lift-tinker-and-shift’ approach * **Repurchase** : You switch to a different application * **Refactor/Re-architect** : Following this approach, you change the middleware and app code to utilize cloud features for the application * **Retire** : You remove or ‘get-rid-of’ the app * **Retain** – You do nothing or keep the app as it is, usually until you can choose one of the other approaches- this may be a temporary arrangement as you may not want to keep many apps on the local data center ### **Step 3- Design** Design your cloud architecture based on your need for a public, private or hybrid cloud, and optimize your applications to run accordingly. Pick a tool to automate migration to AWS and set up for testing- automated or manual. Following this, plan for migration cutover. You can choose to continuously replicate data so that it is synced in real-time. This helps in reducing downtime during the cutover window. Another essential thing to do is to have a rollback plan. In case you encounter an issue while migrating, have a step-wise roll back option to undo the last migration. ### **Step 4- Migrate** Your AWS migration can be very smooth depending on how well you have planned it as planning can help you minimize unexpected problems. * If you have smaller application and database sizes, you can copy them over the internet. For larger workloads, you may need to compress the data or use physical drives to transfer the data to the AWS cloud. * Ensure that your sensitive data is secure during the migration by securing all temporary storage locations and end destination. * Choose the right tools for migration. * Match the new structure and limitations with your database. * Track the application metadata to keep your application portable in the future. * ### **Step 5- Validate** Test your applications and services to ensure smooth working. Evaluate if your apps and services work, and your data was migrated and it is accessible to the users. Check whether all the components are communicating and admin tools are monitoring the new cloud app. An automated testing strategy is ideal for these checks. Evaluate your performance against the cloud migration KPIs to determine the migration is successful. ### **Step 6- Operate** Decide whether you want to switch your production from the on-premise solution to the on-cloud solution by taking users all at once or in phases. Choose an approach based on the complexity and architecture of your apps, data, and data center. You can: * Move the entire app to the cloud, validate that it works, and switch traffic to the cloud stack, or * Shift a few customers at once and test the app until all the customers are on the cloud-based app. ### **Step 7- Optimize** Review the application resource allocation and optimization to take maximum ## **Conclusion** AWS public cloud offers you many benefits for your business, including better productivity, operational resilience, and business agility. Migrating to AWS can be overwhelming, depending on the level of cloud integration and in-house expertise. That is where a cloud managed service provider can help. You can hire an experienced Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents If you’re using Amazon RDS for MySQL 8.0.35, you already enjoy the benefits of a managed database service, such as automated backups, easier maintenance, and less manual work compared to running MySQL yourself. But as applications grow, you start to need more performance, faster scaling, and stronger high availability. That’s when Amazon Aurora is still MySQL at its core, so your applications don’t need big changes. But under the hood, it’s built on a cloud-native storage system that makes it faster, more resilient, and easier to scale than standard Amazon RDS MySQL. ## **Pre-Migration Assessment** Before you begin with the actual cloud migration, it’s important to do a **1. Check Version Compatibility** Since you’re on But it is still recommended to review the latest Amazon Aurora release notes to confirm your application’s specific needs, like supported features, security patches, and known issues. **2. Backups and Logging** Ensure to have safety backups. * Take a manual snapshot of your source Amazon RDS MySQL instance. * Double-check that automated backups are enabled and that you’ve actually tested restoring from one. **3. Review Feature Compatibility** Amazon Aurora MySQL aims to stay compatible with MySQL, but it isn’t identical. One key difference is that it works exclusively with the InnoDB storage engine. That means if your database still uses MyISAM tables, you’ll need to convert them before migrating. Also, some MySQL system functions and configuration parameters may behave differently in Amazon Aurora. That’s why it’s worth taking the time to review your database setup for things like features, triggers, stored procedures, and custom configurations, to make sure nothing depends on functionality that Amazon Aurora doesn’t support. **4. Test in a Staging Environment** Test application interactions with Amazon Aurora in a staging environment to ensure compatibility. This step helps you confirm: * Queries run without errors. * Application behavior is consistent. * Performance meets expectations. Catching issues in staging is much easier than discovering them mid-migration in production. **5. Plan for Downtime** Even with replication-based approaches, there is always a cutover step where you switch your application. That usually required some downtime. So plan for a realistic maintenance window and testing immediately after cutover to confirm everything is working. ## **Migration Approaches** ### **Approach 1: Using an Amazon Aurora Read Replica** Using this method, you create an Aurora MySQL Read Replica of your current RDS MySQL primary instance to migrate from RDS MySQL 8.0.35 to Aurora. Here's how it works: * By using your current Amazon RDS MySQL 8.0.35 primary instance, create an Aurora MySQL read replica (targeting Aurora MySQL 3.x). Make sure it runs in the same AWS Region. * Allow some time for AWS to sync data automatically using MySQL binlogs, and keep monitoring the replication lag in * Promote the Amazon Aurora read replica to a stand-alone Aurora cluster once the replication lag is negligible or zero. Remember this is a one-way operation as the original RDS instance and replicas won’t be linked after this step. * In the newly promoted Aurora cluster, create an Aurora reader (read replica) to maintain your high-availability setup and handle read traffic. * Update your applications and any connected tools (like Debezium) to point to the Aurora writer endpoint for writes and the reader endpoint for read-only workloads. * Test your applications and queries to confirm everything works as expected. Ensure to check latency, replication, triggers, and stored procedures. * Monitor Aurora performance using CloudWatch metrics and logs. If required, you can make parameter adjustments. After successful validation and observation, decommission the old Amazon RDS MySQL primary and replicas to avoid unnecessary costs. **Key Considerations:** * Plan the cutover window and perform cutover only after confirming that replication lag is at zero. * Expect a short downtime during the cutover, so schedule a proper maintenance window. * Make sure your application works correctly with Amazon Aurora’s features before making the switch. * Promoting an Amazon Aurora Read Replica to a standalone cluster is a one-way operation. After the promotion, the original Amazon RDS * MySQL instance and its replicas will not be part of the new Amazon Aurora cluster. * The Amazon RDS primary and the Aurora replica must both be in the same AWS Region. ### **Approach 2: Binlog-Based Replication** Since AWS Blue/Green Deployments don’t support cross-engine migrations (like RDS MySQL to Aurora MySQL), this method using binlogs is the next best option, as it's based on the general concept of Blue/Green Deployments. This method follows the same idea as a Blue/Green deployment, where one environment stays live (Blue) while the new one (Green) is synced in the background. Here’s how it works: * Create a new Amazon Aurora cluster (Aurora MySQL 3.x) in the same Region. * Enable binary logging on your Amazon RDS MySQL instance if it’s not already enabled. * Set up replication from Amazon RDS MySQL to Aurora by configuring Aurora as a replica of your RDS instance using the binlogs. This ensures all ongoing changes from Amazon RDS are applied to Aurora. * Monitor replication lag closely and keep the Aurora cluster in sync until you’re ready to switch. * When you decide on a cutover window, stop writes to the Amazon RDS MySQL instance, wait for Aurora to catch up (lag = 0), and then point your applications to the new Aurora cluster. **Key Considerations:** * This method requires manual setup and monitoring of replication. * Cutover still requires downtime for switching applications. **Note:** Although AWS DMS is an alternative option, it’s not the best fit in this case. Since this is a homogeneous migration, using DMS would only add extra cost and complexity. ## **Impact of Migration in terms of Performance, Stability, and Cost** **1. Performance and Stability:** * Amazon Aurora offers up to five times the throughput of a standard MySQL database running on the same hardware. * Aurora automatically scales storage in increments of 10 GB as you grow your database, up to 128 TB. * Your data is copied six times across three Availability Zones, so it stays safe even if a disk or an entire AZ fails. * Because of its replication, Amazon Aurora can automatically recover from a failure in less than 30 seconds, so your downtime is minimal. * Amazon Aurora continuously checks its storage for errors and automatically repairs any bad blocks or disks. All of these features make **2. Cost:** There are no upfront costs or long-term licenses. Amazon Aurora works on a pay-as-you-go model. You are billed hourly for all database instances you run, in addition to storage and I/O costs (based on your pricing plan). The actual cost depends on your workload, especially how many I/O operations your application performs and how often it reads from storage. Amazon Aurora gives two pricing options: * **Amazon Aurora I/O-Optimized** – This is best for I/O-heavy workloads like payments, eCommerce, and financial systems. You only pay for compute and storage, with no extra I/O charges. For very busy databases, this can cut costs by up to 40%. * **Amazon Aurora Standard** – This is a better fit for low to moderate I/O workloads. In this model, you pay for compute, storage, and each I/O request, which often works out cheaper if your app isn’t very I/O-intensive. ## **Conclusion** Migrating from Amazon RDS MySQL 8.0.35 to Amazon Aurora MySQL-Compatible Edition 3.x is not a task that should be rushed. Proper planning is essential, especially in terms of version compatibility and your chosen migration method. In most circumstances, using replication or a snapshot will be a good option, but if you cannot use one of these options because of version differences between the two versions, a logical dump and restore will be a trusted and safe option. **Note:** * It is strongly recommended to test and validate your selected approach in a staging or non-production environment before deploying to a production environment. * Ensure you have proper backups, and have logging enabled to assist in troubleshooting and rollback if needed. It is advised to schedule your cutover during a maintenance window to minimize the impact of downtime on your users. **Planning a cloud database migration?** CloudKeeper supports organizations at every stage — from cloud migration planning and architecture design to seamless implementation and ongoing optimization. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Cloud Engineer Pranav has hands-on experience in AWS cloud infrastructure, F5, and DNS. He is passionate about building secure, scalable, efficient cloud solutions and learning new technologies. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents ## ## **Introduction** Cron jobs are a useful tool for automating tasks on an operating system. They allow you to schedule tasks to run automatically at specified times, such as running backups or cleaning up temporary files. Traditionally, cron jobs are running on linux systems. However, as more and more organizations migrate their workloads to the cloud, Managing cron jobs on Linux can be challenging due to their configuration and scheduling requirements and if something happens on the server, it can potentially affect the execution of cron jobs so to overcome these issues we need to find out the cloud-based solutions such as Amazon Elastic Container Service (Amazon ECS) and Amazon EventBridge. ## **Problem Statement** Running cron jobs in Jenkins can certainly pose some challenges, particularly when it comes to maintaining the system and **Upgrading Jenkins:** We cannot upgrade Jenkins to a newer version, it can cause issues with your existing cron jobs. This is because the upgrade may introduce new features or changes to the platform that can affect how your cron jobs run. To mitigate this, you will need to thoroughly test your cron jobs after each upgrade and make any necessary adjustments. **Dedicated slaves:** We have dedicated slaves for our cron jobs, this can add to the cost of maintaining your Jenkins infrastructure. Dedicated slaves require their resources, which can quickly add up if you have a large number of cron jobs. Additionally, maintaining and scaling these slaves can be time-consuming and may require additional expertise. **Downtime:** The cron jobs are a critical part of our system which populates the data in the production system. So it is important to have all the jobs running properly without any exception which is not the case right now as for any activity to be done on Jenkins such as upgrade Jenkins, plugins, simply restarting the Jenkins or during unexpected Jenkins’s downtime, few cron-jobs which run frequently fail or get skipped during the maintenance windows. ## **Solution Approach** To address these challenges, you may want to consider migrating your cron jobs to a cloud-based solution like Amazon ECS. This can help you take advantage of the scalability and cost savings that come with running your cron jobs in the cloud. Alternatively, you can use a dedicated cron job management tool like AWS Eventbridge Rules to manage your cron jobs. These tools can help you monitor and manage your cron jobs more effectively, without the need for dedicated Jenkins slaves or the overhead of managing your infrastructure. Based on the cost analysis conducted, it appears that migrating to a cloud-based solution like Amazon Elastic Container Service (Amazon ECS) could potentially offer significant cost savings compared to maintaining a dedicated instance setup. In the analysis, it was found that the dedicated instance, including an On the other hand, the cost of an Amazon ECS task was estimated to be around $50. This cost is generally lower because ECS optimized resource allocation and allows for better utilization of container instances. Additionally, While cost reduction is a significant advantage of migrating to a cloud-based solution like Amazon ECS, it's important to consider other factors as well. These may include scalability, performance, security, and the overall management and operational benefits that come with cloud-based services. Conducting a comprehensive evaluation considering all these factors will help ensure a well-informed decision that aligns with your specific requirements and goals. ## **Step-by-Step Procedure** Migrating your cron jobs from Jenkins to Amazon ECS by EventBridge is a straightforward process that involves the following steps: **Step 1: Create a Docker Image** To migrate your cron jobs to Amazon ECS, you must first create a Docker image that contains your cron job code and any dependencies. Docker images provide a portable and reproducible way to package your application, making it easy to deploy across different environments. Once you have created your Docker image, you can store it in a container registry such as Amazon Elastic Container Registry (ECR). **Step 2: Create a Task Definition** A task definition is a blueprint that defines how your Docker container should be launched in Amazon ECS. It specifies the Docker image to use, the CPU and memory requirements, and any environment variables or port mappings required by your application. You can create a task definition using the Amazon ECS console, AWS CLI, or **Step 3: Create a Scheduled Event in EventBridge** To trigger your cron job in Amazon ECS, you must create a scheduled event in AWS EventBridge. Scheduled events allow you to specify when and how often your cron job should run. You can create a scheduled event using the AWS EventBridge console or AWS CLI. **Step 4: Create a Rule in****AWS EventBridge** A rule in AWS EventBridge is a way to match incoming events to specific targets. In this case, you will create a rule that matches your scheduled event and triggers your Amazon ECS task. You can create a rule using the AWS EventBridge console or AWS CLI. **Step 5: Test and Monitor Your Cron Job** Once you have created your scheduled event and rule, you can test your cron job by monitoring the logs generated by your ECS task. You can also use ## **Conclusion** Migrating your cron jobs from Jenkins to Amazon ECS by AWS EventBridge provides several benefits, including scalability, cost efficiency, and simplified management. By following the steps outlined in this blog, you can easily migrate your cron jobs to Amazon ECS and take advantage of the benefits of cloud-based solutions. Whether you are a small startup or a large enterprise, Amazon ECS by AWS EventBridge provides a scalable and cost-effective solution for running your cron jobs in the cloud. _If you are looking to streamline your AWS infrastructure, ensuring maximum performance, reliability, and cost-efficiency for your workloads,_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents In this blog, we will address how organizations can migrate workloads from legacy x86- based Cloud adoption is no longer merely a matter of "lifting and shifting" workloads. Enterprises today must optimize for performance, cost savings, and sustainability—without compromising agility. AWS Graviton2, based on ARM processors, provides a special opportunity to achieve all three. In this blog, we’ll explore how organizations can migrate workloads from x86-based ## Why Graviton2 Matters and Excites • **Cost Savings:** AWS benchmarks show up to 40% better price-performance compared to equivalent x86 instances. • **Sustainability:** ARM-based Graviton2 instances are more energy-efficient per transaction, helping reduce carbon footprint directly. • **Scalability:** The increased core density lets you accomplish more with fewer instances, reducing your infrastructure footprint. •**Future-Proofing:** With increasing ARM adoption in cloud, mobile, IoT, and edge, being ARM-ready future-proofs long-term competitiveness. • **Comprehensive Ecosystem Support:** From Spark to Kubernetes to serverless workloads, ARM64 is first-class in AWS. • **Tooling Support:** Docker Buildx, Terraform, Helm, Jenkins, GitHub Actions, and CI/CD pipelines all support ARM builds. •**Versatility:** Run workloads in multi-architecture modes (ARM + x86) during transition for zero downtime. • **Performance Tuning:** ARM64 offers efficiency improvements in compute-intensive workloads (e.g., Spark joins, ML inference). ## Migration Playbook: Step-by-Step In the following, we detail the migration journey workload by workload with business impact and technical execution side by side. ### **1. Migrating Apache Spark Workloads (EC2: c5.xlarge ➝ c6g.xlarge)** Spark jobs tend to be large compute expenses. Moving them to Graviton2 can save as much as 30% of costs while decreasing data pipeline job completion times. #### **Technical Steps:** **a.** Verify Spark runtime and third-party JAR compatibility with ARM64. **b.** Utilize ARM64-supported OpenJDK 8/11. **c.** Revise provisioning scripts: resource "aws_instance" "spark { instance_type = "c6g.xlarge" ami = "" } **d.** Run benchmarks comparing job throughput, CPU utilization, and $/job. **e.** Use canary deployments on small datasets before full rollout. ### **2.****(EKS: t3.xlarge ➝ t4g.xlarge)** Microservices clusters can realize ~30–40% savings on compute costs. ARM further enhances per-node density, saving scaling overhead. #### **Technical Steps:** **a.** Verify Amazon EKS version ≥ 1.20 supports ARM64. **b.** Launch ARM64-optimized AMIs: _NodeGroup:_ _Type:_ _AWS::EKS::Nodegroup_ _Properties:_ _InstanceTypes:_ _- t4g.xlarge_ _AmiType: AL2_ARM_64_ **c.** Check Helm charts for architecture-specific labels. **d.** Utilize nodeSelector for ARM64 scheduling: _nodeSelector:_ _kubernetes.io/arch:_ _arm64_ **e.** Verify operators and sidecars for ARM support; segregate incompatible workloads to x86 if necessary. ### **3. Web & Application Servers** Execution of APIs, content delivery, or backend applications on Amazon Graviton2 lowers operational costs for always-on workloads. **Technical Steps:** **a.** Rebuild containers with ARM64 base images: _FROM arm64v8/nginx: latest_ **b.** Update IaC templates (t4g or c6g). **c.** Perform integration testing across runtimes (Node.js, Python, Ruby, Java). ### **4. Containerized Microservices (Amazon ECS /****)** Pay-as-you-go workloads on **Technical Steps:** **a.** Create multi-arch images with Buildx: _docker buildx build --platform linux/arm64,linux/amd64 -t myapp:latest ._ **b.** Update ECS task definitions to include ARM64 platform. **c.** Staging test before production deployment. ### **5. CI/CD Pipelines** CI/CD runners tend to create invisible infrastructure costs as a result of continuous builds. Migrating runners brings future cost savings and ARM-native mobile/IoT builds. **Technical Steps:** **a.** Jenkins/GitHub Actions runners to t4g.large. **b.** Cross-check build tools and dependencies ARM64. **c.** Benchmark runtime improvements and optimize caching. ### **6. Databases** Self-serviced databases on Graviton2 can reduce the cost of hosting while maintaining performance—essential for data-driven workloads. **Technical Steps:** **a.** Verify PostgreSQL, MySQL, and Redis binaries on ARM64. **b.** Backup and restore databases to fresh instances. **c.** Optimize configs for latency, IOPS, and throughput. **d.** Monitor using AWS CloudWatch for regression detection. ### **7.** Lambda functions that moved to ARM64 can observe as much as 34% reduced execution costs with negligible code modification. **Technical Steps:** **a.** Change Amazon Lambda architecture to ARM64 in the console or IaC. **b.** Perform full regression test coverage. **c.** Observe cold starts and pricing savings through Amazon CloudWatch. ## **Test Scenario: Moving Analytics & Microservices to Graviton2** A SaaS business was hosting its analytics pipeline on x86-based **c5.xlarge** Amazon EC2 instances and its Kubernetes-based microservices on t3.xlarge EKS nodes. Cloud expenses were increasing with growing workloads. **Migration Strategy:** **a.** Relocated Spark jobs from c5.xlarge to c6g.xlarge. • Re-created Helm charts and container images to enable ARM64 for EKS workloads. • Implemented multi-arch Docker images for compatibility. **Results (3-month benchmark):** **Takeaway:** By moving only two large workloads (analytics and microservices), the company lowered monthly compute expenses by ~35%, accelerated data processing pipelines, and made a measurable step toward sustainability objectives. ## Best Practices **a.** Benchmark before scaling—every workload acts differently. **b.** Adopt iterative migration—use blue-green or rolling deployments. **c.** Monitor costs—track savings with **d.** Plan rollbacks—keep x86 instances ready for fallbacks. ## **Conclusion** Moving to AWS Graviton2 is so much more than a cost-saving move—it's a strategic shift in cloud computing. For business executives, it provides real ROI through lower infrastructure expense, quantifiable steps toward sustainability targets, and the ability to scale with confidence. For technical professionals, it opens up new toolchains, improved performance, and the flexibility to execute workloads across multi-architecture environments without compromise. By adopting ARM-based computing now, businesses are not just maximizing for today but also future-proofing their cloud strategy. Early adopters get a head start—getting the best of performance, cost savings, and sustainability in one sweeping transition. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Jatin is an AWS-certified SysOps Administrator Associate with extensive expertise in AWS cloud services and a broad spectrum of DevOps tools. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents Upgrading or migrating an AWS OpenSearch cluster is a critical task that demands a well-structured approach to ensure data integrity and zero downtime. This approach provides a comprehensive overview of strategies and tools to facilitate a seamless transition from an older OpenSearch cluster to a newer one — whether you're performing an upgrade or moving to a new environment. This blog outlines the key migration techniques—such as Logstash, Fluentd, Cross-Cluster Replication (CCR), Snapshots and also offers guidance on selecting the most suitable method to ensure a reliable and low-risk migration process. **Note** - It is highly recommended to test all approaches in a non-production environment before migrating to the production environment. ## **Prerequisites for AWS OpenSearch Migration** Before starting the migration, here are the key factors to consider: **1. Compatibility & Version Considerations ** * Verify that the new OpenSearch version supports your existing data, indices, and configurations. * Review AWS OpenSearch upgrade documentation—some versions introduce changes that may affect mappings, queries, or * APIs. Read OpenSearch release notes to check for breaking changes. **2. Cluster & Resource Planning ** * Ensure the new cluster has enough compute, storage, and memory for your workload. * If migrating to a different AWS region, factor in network latency and data transfer speed. **3. Backup & Disaster Recovery ** * Take a full snapshot of your current OpenSearch cluster. * Store the snapshot in Amazon S3 for safe recovery. * Have a rollback plan in case of migration failure. **4. Data Migration Strategy** There are two primary methods for migrating data: * Snapshot & Restore – Best for major upgrades (batch migration). * Cross-Cluster Replication (CCR) – This is Best for live migration with minimal downtime. **5. Application & Query Compatibility ** * Ensure your queries, field mappings, and configurations are compatible with the new OpenSearch version. * Some queries might need optimization post-migration. **6. Monitoring & Performance Tuning ** * Enable OpenSearch Logs & CloudWatch Metrics to track performance. * Monitor CPU, JVM heap size, disk I/O, and query latency after migration. ## **Approach to Reduce Downtime During Migration** One of the biggest challenges in OpenSearch migration is avoiding downtime. The best way to achieve this is through Blue-Green Deployment. **Blue-Green Deployment Approach** **What is Blue-Green Deployment?** A strategy where you create a new (Green) cluster while keeping the old (Blue) cluster running. Once the Green cluster is fully set up and tested, traffic is switched over. **How it Works:** * Set up a new cluster (Green) with the upgraded OpenSearch version. * Migrate data from the old cluster (Blue) to the new cluster (Green) using: ✔ **Snapshots & Restore** – (For historical data) ✔ **CCR** – (For real-time synchronization) ✔ **Fluentd** – (For real-time logs & events) ✔ **Logstash** – (For structured data & full migration) * Test the Green Cluster for stability and performance. * Switch Traffic to the Green Cluster. * Decommission the Blue Cluster once the migration is successful. ## **Data Migration Methods** **Snapshot & Restore (Best for Batch Migration) ** **Steps:** * Take a snapshot of your existing OpenSearch cluster. * Store the snapshot in an S3 bucket. * Restore the snapshot in the new OpenSearch cluster. **When to Use:** * Best for major version upgrades where direct upgrades are not possible. * Ideal for batch migrations when downtime is acceptable. **Cross-Cluster Replication (CCR) (Best for Live Migration)** **Steps:** * Set up CCR to replicate data in real-time from the Blue Cluster to the Green Cluster. * This ensures that both clusters stay synchronized before switching over. **When to Use:** * Best for low-latency, real-time migrations. * Ideal when OpenSearch is used for structured search (e-commerce, analytics, dashboards, etc.). **Fluentd (For Log Streaming & Incremental Migration) ** **Steps:** * Configure Fluentd to stream logs from the Blue Cluster to the Green Cluster. * Ensures real-time log forwarding without downtime. **When to Use:** * Best for real-time log migration (not full data migration). * Works well when OpenSearch is primarily used as a log store. _**Fluentd does NOT migrate historical data — only new logs/events. For full migration, use Fluentd + Snapshots together.**_ **** **Logstash (Best for Full Data Migration & Transformation) ** **Steps:** * Set up Logstash on EKS or EC2. * Configure Logstash input to pull data from the old cluster. * Transform data as needed (filtering, enrichment, restructuring). * Send processed data to the new OpenSearch cluster. **When to Use:** * Best when you need to migrate both historical and new data. * Ideal for structured logs, event processing, and full database migrations. ## **Fluentd vs. CCR vs. Logstash – Which One Should You Use?** **Which One Should You Choose?** * **Use Snapshots** → If you need to migrate old data in batches. * **Use Fluentd** → If you only need to migrate real-time logs to the new cluster. * **Use CCR** → If you need real-time data synchronization for a live OpenSearch cluster. * **Use Logstash** → If you need to migrate both historical & live data with transformations. * **Use Snapshots + Fluentd** → If you want to migrate old data (snapshots) and new data (Fluentd) together. **Final Thoughts** Migrating OpenSearch to a newer version doesn’t have to be a complex task. With the right planning and by leveraging proven strategies — such as **Blue-Green Deployment, Snapshots, Cross-Cluster Replication (CCR), Fluentd, and Logstash** — you can achieve a seamless, low-risk migration with minimal or zero downtime. Whether you're preparing for a version upgrade or transitioning to a new environment, following these best practices will help you avoid common pitfalls and ensure business continuity throughout the process. Have experience with OpenSearch migrations? We’d love to hear from you—which migration method has worked best for you: Fluentd, CCR, Logstash, or Snapshots? Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Abhishek is experienced in building, automating, and optimizing mission-critical deployments in cloud-native environments. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents In modern cloud-native architectures, resiliency isn’t a bonus—it’s a baseline requirement. Just like a seemingly redundant This write-up explores how the Model Context Protocol (MCP), when paired with Amazon Bedrock, eliminates the disconnect between foundation models and real-world systems. We’ll walk through the architecture, the root problems MCP solves, and the technical best practices that ensure availability, reliability, and intelligent automation. ## **The Scenario: Intelligent AI, Isolated from Action** Large Language Models (LLMs) like ChatGPT, Claude, and Titan are great at language reasoning—but by default, they’re siloed. They can’t access APIs, query AWS, or trigger workflows unless explicitly wired to external services. That’s why it is essential to s ### **Before MCP, that meant:** * Manual integrations with every external tool * Brittle workflows with no standardized interface * Loss of context across multi-step chains * Higher engineering overhead and maintenance risk In short, intelligence without execution. ## **Digging Into the Root Cause** The real limitation wasn’t the models—it was the lack of a standard interface between models and tools. ### **The core problems:** * LLMs couldn’t invoke external APIs in a reliable, structured way. * Ad-hoc code integrations lacked fault tolerance and reusability. * Teams duplicated effort trying to reimplement similar connectors. The failure mode was always the same: the model knew what to do, but had no clean path to do it. ## **Enter MCP: A Modular, Standardized Protocol** MCP introduces a structured approach to connect LLMs to external services using a clean, modular client-server model. Think of it as a universal adapter that allows foundation models to operate in the real world. ### **Core Components:** * **MCP Host** The primary LLM-based app (e.g., a Bedrock chatbot) that initiates requests. * **MCP Client** Translates the request into JSON-RPC 2.0 format and forwards it. * **MCP Server** Receives the request and executes it by calling external APIs, querying databases, or performing computations. * **External Services** AWS APIs, internal systems, third-party APIs, or custom scripts. ### **Transport Mechanisms:** * **stdio:** Used during local testing or development. * **Streamable HTTP** : Used in production environments. Supports retries, fault-tolerance, and session tracking. ## **How MCP Integrates with Amazon Bedrock** Amazon Bedrock provides foundation models as managed services. With MCP, those models can now invoke live tools as part of their reasoning chain. ### **Example Workflow:** 1. A user asks: “Estimate AWS cost for my infrastructure.” 2. The LLM issues a tool request: _**get_cost_estimate**_ 3. The MCP Client routes the call to an MCP Server. 4. The MCP Server queries 5. The result is returned through the MCP Client back to the LLM. 6. The LLM incorporates the data into its final, context-aware response. This happens seamlessly within seconds. No manual API calls. No hardcoded logic. ## **Real-World Architecture: MCP + Amazon Bedrock +AWS Lambda** To run this in production securely and at scale, AWS components are used to glue the system together. ### **Architecture Flow:** MCP Client → API Gateway → AWS Lambda (MCP Server) → AWS Services ### **Core Code Components:** AWS Services Used: * * **API Gateway:** Auth and rate-limiting * **CloudWatch:** Logs and error tracking * **:** Least privilege roles with secure secrets * **Amazon Bedrock:** Foundation models for intelligent analysis ## **What We Learned: Best Practices for High Availability** Using MCP is not enough—you have to build it right. Here’s how to avoid common failure patterns: ### **Option 1: Harden Your MCP Configuration** #### **1. Always Have More Than One MCP Server** Just like a single Aurora Reader causes downtime if it fails, a lone MCP server creates a single point of failure. * Always deploy redundant MCP servers for critical tasks. * Use fallback logic and exponential backoff in the client. * Use smaller or idle-capable instances for redundancy if needed. #### **2. Set Priority Tiers** Not all requests are equal. Don’t treat them like they are. * Separate high-priority (e.g., AWS cost) from low-priority (e.g., news feed). * Assign priority tiers to queues or endpoints. * Build logic for fast retries or safe degradation. ### **Option 2: Remove Bottlenecks with Clustered Endpoints** Instead of relying solely on a single RDS proxy (or MCP endpoint), consider clustered approaches. * Use Bedrock’s orchestration tools (like Agents) to route requests. * Keep servers stateless and scalable. * Implement connection pooling at the application layer, not hardcoded in Lambdas. ## **Wrapping Up** Model Context Protocol bridges the gap between intelligent models and real-world action. But just like Aurora’s proxy failed during a Reader crash, even a powerful tool like MCP can fall short if not deployed with resiliency in mind. ### **Key Takeaways:** * MCP standardizes LLM-to-tool interactions. * Amazon Bedrock enables seamless execution of complex workflows. * Reliability depends on redundancy, failover strategies, and endpoint management. ### **Summary Table** ## **What’s Next for MCP?** * **Dynamic Server Discovery:** Register and detect servers on the fly. * **Unified Security Model:** Centralized authentication for all servers. * **Retry-Orchestration Layers:** Better state management for long chains. * **Model-Driven Planning:** Let the LLM decide the best toolpath dynamically. If you’re ready to put LLMs to work in the real world, MCP is your foundation. Just don’t forget the lessons from production outages—redundancy, fallback logic, and structured protocols always win. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Navneet is a DevOps Engineer specializing in migrations, CDN solutions, and infrastructure as code. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents There are several ways of **Amazon SNS** , to receive alerts about cost and resource utilization. Almost everyone working with AWS has used SNS at some point, and if you’re a beginner, you’ve likely at least heard of it. In this article, I’ll walk you through how to leverage the Simple Notification Service (SNS) to monitor AWS costs and resources effectively. ## **Why Amazon SNS?** The very first question that may come to mind is: **why SNS?** Amazon Simple Notification Service (SNS) is a versatile solution that can be integrated with**AWS CloudWatch** and **AWS Budgets** to trigger real-time notifications across multiple endpoints such as email, These real-time notifications ensure that cost anomalies and resource overutilization can be addressed immediately. One of the major advantages of Amazon SNS is its scalability. It can trigger alerts across multiple channels at once, providing the right visibility to different stakeholders in real time. Even in the rare case where one channel fails, other endpoints will still receive the alerts, ensuring that the responsible teams can take timely action. Moreover, Amazon SNS is not limited to alerting. It can also be used to perform **automated optimization tasks** by triggering Lambda functions to stop idle or unused resources, or to resize over-provisioned resources. This makes SNS not just a monitoring tool, but also a mechanism for taking corrective action when needed. Finally, when it comes to cost, SNS itself is **very cost-effective** compared to building a custom alerting system. It is simple, fully managed, and economical. To give you an idea, the **first 1 million requests per month are free** , making it a budget-friendly option for organizations of any size. ## **Topics in Amazon SNS** At the core of SNS lies the topic, which serves as the central communication unit and a logical access point where publishers send messages and subscribers receive them. AWS Simple Notification Service topics enable a**decoupled, scalable, reliable, and flexible workflow**. Publishers don’t need to know the details of subscribers, making the system loosely coupled. Scalability is built in, as a single topic can support millions of subscribers. Reliability and flexibility come from the fact that subscribers can be entirely different systems, ranging from applications to monitoring tools. Topics are commonly used for **alerting teams in real time** about cost and resource utilization, application events, or even triggering automation workflows. ## **Integrating SNS with****for Cost Alerts** Now that we understand the value of SNS, let’s walk through the process of integrating it with **AWS Budgets** to receive alerts whenever your costs exceed a predefined threshold. The process is straightforward: 1. **Log in to your AWS Account** Access the 2. **Navigate to Billing and Cost Management** From the console, open the **Billing and Cost Management** dashboard. 3. **Go to Budgets** In the left-hand menu, select **Budgets**. 4. **Create a New Budget** Click **Create budget** and configure the budget details. 5. **Configure Alerts** * Set your **threshold amount** (e.g., when actual or forecasted costs reach 80% of your budget). * Select the option for **Amazon SNS alerts**. * Provide the **SNS Topic ARN** you created earlier. 6. **Review and Confirm** Double-check your configuration and confirm to save the budget. ### **How It Works** From this point onward, whenever your monthly budget threshold is exceeded, AWS Budgets will automatically trigger the SNS topic. All subscribers to that topic, whether via email, SMS, Slack, Lambda functions, or other endpoints, will instantly receive the alert. This ensures that the relevant teams are informed in real time and can take timely action. ## **Setting Up an Amazon SNS Topic for Resource Utilization** In addition to monitoring costs, SNS can also be used to **track resource utilization.** For example, let’s take an**CPU utilization reaches 70% or higher**. This allows the relevant team to take timely action before performance is impacted. Let’s assume we have an EC2 instance already running. As we know, AWS provides several pre-configured instance metrics through Amazon CloudWatch, and CPU utilization is one of the most important among them. **Steps to Configure:** 1. **Navigate to CloudWatch** **a)** Open the AWS Management Console and go to **CloudWatch**. 2. **Select Metrics** **a)** Click on **All Metrics**. **b)** Choose EC2. **c)** Locate the **CPUUtilization** metric for your specific instance. 3. **Create an Alarm** **a)** Select **Create Alarm**. **b)** On the configuration page, define the **threshold** (e.g., CPU utilization ≥ 70%). 4. **Configure Actions** In the **Actions** section, provide the **Amazon** **SNS Topic details**. This ensures the relevant team is notified via the subscribed protocols (Email, SMS, Slack, etc.) whenever the threshold is breached. Optionally, you can define additional automated actions such as triggering a **Lambda function** , scaling policies via an **EC2 level**. (We’ll cover these in detail in another blog.) 5. **Name the Alarm** Assign a descriptive name to your alarm for easy identification. 6. **Review and Create** Review the configurations and create the alarm linked to your SNS topic. ## **Outcome** With this integration in place, whenever the CPU utilization of your AWS EC2 instance reaches 70% or higher, CloudWatch will trigger the SNS topic. All subscribed endpoints, whether Slack, Email, or SMS will immediately receive the notification, enabling teams to take timely action. ## **Conclusion** Amazon SNS makes This combination scales effortlessly across teams and channels, Email, SMS, Slack, Lambda, and more, so the right people are alerted at the right time. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Cloud Engineer Naveen is a cloud and infrastructure professional with hands-on experience in building, automating, and managing scalable AWS environments. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents ## 1. MS-SQL Server EC2 Standalone Running Microsoft SQL Server on ### Cost Components: 1. SQL Server Licensing 2. EC2 Instance Pricing 3. 4. Data Transfer Charges ### Licensing Costs: Licensing costs vary based on the edition and licensing model selected: * ****(License Included) pricing: _a) Standard Edition:_ $73 per core per month (~$0.10/hr) _b) Enterprise Edition_ : $274 per core per month (~$0.375/hr) * **Subscription-based licensing** : a) Standard Edition: $1,418 per 2 cores per year b) Enterprise Edition: $5,434 per 2 cores per year Licensing costs must be multiplied by the number of cores used in your EC2 instance. ### Licensing Notes: * A single SQL Server license includes one passive standby in the same region. This standby is non-operational and intended for high availability (HA) only—no read or write workloads can be executed on it. * For cross-region disaster recovery (DR), only Enterprise Edition supports readable replicas. Additionally, a separate license must be procured for the DR server. For complete and up-to-date Microsoft SQL Server licensing details, refer to the official pricing guide: Microsoft SQL Server 2022 Pricing ### Other Cost References: * EBS Pricing: Amazon EBS Volume Pricing * EC2 On-Demand Pricing: Amazon EC2 Pricing * Data Transfer Pricing: AWS Data Transfer Pricing #### Cost Example (Region: US East – N. Virginia) Let’s consider a deployment using an r5.xlarge instance (4 vCPUs = 2 physical cores): * **EC2 Instance Cost (Windows Base AMI):** $0.436/hour = $3,817.44/year With passive standby: $7,634.88/year * **EBS gp3 (200 GB):** $0.08/GB/month = $192/year * **Data Transfer:** 100 GB between AZs (same region): ~$1 100 GB to another region: ~$2 * **SQL Server Enterprise License:** $5,434/year (for 2 cores) Total Estimated Annual Cost (Without DR): * EC2 (Primary + Standby): $7,634.88 * SQL Enterprise License: $5,434 * EBS Storage: $192 * Total: ~$13,260/year Total Estimated Annual Cost (With DR in Another Region): * Add a second SQL Server license: $5,434 * Add another EC2 instance + EBS: ~$6,822 * Total: ~$22,516/year ## 2. RDS managed MS-SQL Amazon RDS for SQL Server is a fully managed service provided by AWS, designed to reduce operational overhead by handling routine database tasks such as provisioning, patching, backup, monitoring, and failover. It is particularly well-suited for production environments that require high availability, compliance, and scalability, with minimal manual intervention. You can learn more about Amazon RDS vs Amazon Aurora here. This helps you gain further clarity on the concept we’re discussing. In this model, AWS includes licensing costs for both Windows Server and Microsoft SQL Server under the License Included pricing model, which simplifies procurement and compliance management. ### Key Cost Components: 1. AWS RDS Instance Pricing (includes SQL Server Enterprise license) 2. Elastic Block Storage (e.g., gp3 or io1 volumes) 3. Optional Data Transfer Charges 4. Optional Cross-Region Disaster Recovery (DR) ### Example Configuration (Region: US East – N. Virginia) * Instance Type: **db.r5.xlarge** * Edition: Microsoft SQL Server 2022 Enterprise * Deployment Type: Multi-AZ (for high availability) * Storage: 200 GB gp3 * Backup Retention: Default (7 days) ### **Estimated Costs:** * Monthly Cost: $2,675 * Annual Cost: * $2,675 × 12 = $32,100/year * With DR in Another Region: A second RDS instance in a different region would incur a similar cost (license + compute + storage), plus cross-region data transfer. Estimated annual cost including DR: ~$54,300/year For more detailed pricing of RDS MS-SQl Server, please refer to this **For r5.xlarge instance type - 4vcpu and 32gb memory** Although Amazon RDS for SQL Server Enterprise (Multi-AZ) may appear more expensive than a standalone ### Primary Advantage: Full AWS Operational Support With Amazon RDS, AWS manages the entire database environment, including infrastructure, patching, backups, and monitoring. In the event of performance issues or failures, AWS Support can investigate and resolve them directly. In contrast, Amazon EC2-based deployments leave all responsibilities—database configuration, patching, backup, and recovery—on the customer, with AWS support limited to the EC2 layer only. ### Key Benefits of RDS (Multi-AZ) vs. EC2 Standalone SQL Server * **Managed High Availability:** AWS RDS provisions a synchronous standby in another AZ with automatic failover. On Amazon EC2, this requires a complex manual setup of clustering or Always On. * **Automated Backups & Point-in-Time Recovery:** Amazon RDS handles backups and PITR natively. On Amazon EC2, this must be scripted and managed manually. * **Automated Patching & Maintenance:** AWS RDS applies patches during maintenance windows. AWS EC2 requires manual patching, increasing risk. * **Integrated Monitoring:** RDS integrates with CloudWatch for real-time insights. EC2 requires a custom monitoring setup. * **Simplified Licensing:** AWS RDS includes SQL Server and Windows licenses. EC2 requires BYOL or License Mobility management. * **Security & Compliance:** RDS offers encryption, IAM integration, audit logging, and VPC support out of the box. EC2 demands a custom configuration to achieve similar compliance. For the connection guide to RDS MS-SQL server, please refer to this resource ### **When EC2-Based SQL Server May Be Preferred** Full administrative control over the OS or SQL Server is needed. Certain SQL Server features not available in AWS RDS are required. Cost-sensitive dev/test environments. In-house expertise is available to manage availability, backups, and licensing. ## **Conclusion** While the upfront cost of AWS RDS (Multi-AZ) is higher, it delivers major operational advantages—automated high availability, backups, patching, simplified licensing, integrated monitoring, and comprehensive AWS support. For critical production environments where uptime, scalability, and supportability are key, RDS offers a more reliable and low-maintenance solution. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Shaswat Vashistha is a results-driven DevOps professional with 4+ years of experience across AWS, Azure, and GCP. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Modern In this blog, we walk through: 1. Multi-account cross-cluster GitOps fundamentals 2. ArgoCD Hub–Spoke model architecture 3. Setting up ArgoCD using CLI (easy, fast) 4. Manually TLS/CA configuration (for deeper understanding) 5. Recommended best practices 6. Troubleshooting TLS and cluster authentication issues ## Understanding Multi-Account Cross-Cluster GitOps In a multi-account or multi-cluster environment, you typically have: * **Management (Hub) Account / Cluster:** Runs the central ArgoCD control plane. * **Workload (Spoke) Accounts / Clusters:** Run application workloads. ArgoCD manages deployments to these clusters via service accounts, AWS IAM roles, or kubeconfigs. ### **Why Use Multi-Cluster GitOps?** 1. Centralized control and cloud governance. Know 2. Separation of concerns (Hub is admin, spokes run workloads) 3. Easier RBAC, audit, and policy management 4. Unified multi-cluster observability 5. Faster onboarding of new clusters ## **Hub–Spoke ArgoCD Architecture** In this model, a central hub cluster runs the ArgoCD control plane, and one or more spoke clusters run workloads. * **Hub Cluster Runs:** ArgoCD API server, ArgoCD Repo server, ArgoCD Application Controller, ArgoCD Dex (optional, for SSO) * **Spoke Clusters Have:** Only the ArgoCD-managed workload namespaces, Service accounts, RBAC roles/role bindings that allow ArgoCD to manage resources The hub connects to spokes either by: 1. Providing the spoke cluster’s kubeconfig, or 2. Configuring OIDC / IAM roles (AWS IRSA) ## **Prerequisites** You will need: 1. At least two Kubernetes clusters (one Hub, one or more Spokes) 2. kubectl configured for all clusters 3. Optional: domain/TLS certificates if you want to expose ArgoCD securely 4. ArgoCD CLI installed ## Install ArgoCD on the Hub Cluster a) Create the namespace and install ArgoCD: b) Expose the ArgoCD API server (example using LoadBalancer): c) Get the initial admin password: d) Login using the CLI: Use --insecure only for testing if you do not have TLS. For production, configure proper TLS. ## Register Spoke Clusters (CLI vs Manual) There are two main ways to register a spoke cluster with ArgoCD: * **Easy** : Using the ArgoCD CLI (recommended for most real-world use) * **Manual** : Full TLS + CA + ServiceAccount setup (for deep understanding and strict environments) ### Easy: Using ArgoCD CLI (Recommended) **Step 1** — Switch to the spoke cluster context: **Step 2** — Register the cluster with ArgoCD: What this does: * Creates a ServiceAccount in the spoke cluster * Binds appropriate RBAC (e.g., cluster-admin or a restricted role) * Creates and stores a kubeconfig as a Kubernetes Secret in the hub’s argocd namespace * Enables ArgoCD to manage applications on that spoke cluster Step 3 — Verify the registration: ### **Manual: Full TLS + CA + ServiceAccount Setup** This method is useful when: * You need very fine-grained security control * Clusters are in different cloud accounts without direct trust * Compliance requires an explicit certificate and CA management We will: * Create a ServiceAccount + RBAC on the spoke cluster. * Export the ServiceAccount token and CA. * Build a dedicated kubeconfig for that cluster. * Create a cluster Secret in the hub ArgoCD namespace referencing that kubeconfig. #### **Step 1: Service Account + RBAC on Spoke Cluster** On the spoke cluster, create a ServiceAccount and a ClusterRoleBinding: Note: For production, you should create a more restricted ClusterRole instead of using cluster-admin. #### **Step 2: Export ServiceAccount Token and CA Certificate** Get the Secret associated with the ServiceAccount: Extract the token: Extract the CA certificate: **CA=$(kubectl -n kube-system get secret $SECRET -o jsonpath="{.data['ca\\.crt']}")** Get the spoke cluster API server endpoint: #### **Step 3: Create a Kubeconfig for the Spoke Cluster** Create a file named spoke1-kubeconfig: This kubeconfig tells ArgoCD how to talk to the spoke1 cluster using the argocd-manager ServiceAccount and the given CA. #### **Step 4: Create ArgoCD Cluster Secret in Hub Cluster** Example cluster secret manifest (on the hub cluster): Replace: * with the actual SERVER value * with the ServiceAccount token * with the CA certificate in base64 (same as CA variable above) **kubectl apply -f cluster-spoke1-secret.yaml** After this, ArgoCD should recognize spoke1 as a managed cluster. ## **Deploy an Application to the Spoke Cluster via ArgoCD Hub** Now that ArgoCD can connect to spoke1, let us deploy a sample application (Guestbook). Create an Application manifest on the hub cluster: b) Apply the Application: ArgoCD will: 1. Create the guestbook namespace on the spoke cluster (if it does not already exist) 2. Deploy the manifests from the Git repo 3. Continuously reconcile the desired vs the actual state ## **Verifying TLS, CA, and Connectivity** From the ArgoCD hub side, you can verify cluster and app status. If something breaks, also check events on the hub cluster: ## **Best Practices for Multi-Cluster GitOps** ### **a) Security:** * Prefer cloud-native identity mechanisms (IRSA) over static ServiceAccount tokens when possible. * Rotate any tokens or credentials regularly. * Use TLS everywhere; avoid --insecure in production. * Restrict ArgoCD admin access via SSO and RBAC. Learn how to ### **b) Scalability:** * Use ApplicationSets to manage dozens or hundreds of clusters or cluster namespaces programmatically. * Group applications logically by environment (dev, stage, prod) or region. * Consider sharding ArgoCD instances if you manage a very large fleet. ### **c) Observability:** * Integrate ArgoCD metrics with Prometheus and Grafana. * Use ArgoCD Notifications for Slack/Teams/Email alerts on sync and health. * Combine with Argo Rollouts for progressive delivery (blue/green, canary). ## **Troubleshooting TLS/CA Issues** Common issues and how to think about them: ### **1) x509: certificate signed by unknown authority** **Likely cause:** ArgoCD is not using the correct CA, or the API server’s certificate does not match the CA. **Fix:** Ensure caData in the cluster secret is the correct CA for the spoke cluster’s API server. ### **2) Unauthorized or Forbidden errors** **Likely cause:** The ServiceAccount does not have the necessary RBAC permissions. **Fix:** Check ClusterRoleBinding and permissions. Verify that the token used in the secret is actually from the intended ServiceAccount. ### **3) Cluster shows “Unknown” or “Unreachable” in ArgoCD UI** **Likely cause:** Network connectivity issue (firewalls, private clusters, Virtual Private Cloud routing). **Fix:** Make sure the hub cluster / ArgoCD has a network path to the spoke cluster’s API server (via VPC peering, VPN, or another secure tunnel). ## **Conclusion** In this blog, we covered: 1. The fundamentals of multi-account, multi-cluster GitOps. 2. The ArgoCD Hub–Spoke architecture for central control with distributed workloads. 3. A quick, CLI-driven way to register clusters with ArgoCD. 4. A manual, TLS/CA-focused approach that gives deeper insight into how ArgoCD authenticates and connects to remote clusters. 5. Best practices and common troubleshooting tips. Using these approaches, you can centralize governance and visibility, maintain strong security and separation between accounts, and onboard new clusters quickly and consistently using GitOps. If you’re looking for a tool to complement the governance and visibility practices discussed above, look no further than In this blog, we discussed Multi-Cluster GitOps with ArgoCD and how it can be used to manage Kubernetes environments. For an even better understanding of this concept, it is important to have a deeper understanding of Kubernetes as well. Check out our Here’s what you should do next: * Template your cluster secrets and Application manifests for repeatable onboarding. * Explore ApplicationSets for managing many clusters. * Integrate Argo Rollouts and progressive delivery strategies on top of this foundation. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Abhay Joshi is a problem solver who enjoys playing with algorithms and building scalable distributed systems. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents It’s 9:00 AM on a Monday morning, and Max, a cloud engineer, logs into the AWS Console. Before he can even grab his coffee, a Slack message pings: _“Hey, our cloud spend seems off the charts this month. Can you dig into it?”_ Max takes a deep breath and begins navigating through the AWS cloud optimization tasks. As the hours tick by, Max toggles between dashboards and multiple cost reports. First, he hunts for “zombie” resources—those unused instances still silently eating away at the budget. Then, he shifts to analyzing over-provisioned instances, trying to figure out which ones can be right-sized without compromising performance. As the list of tasks grows longer, Max deletes unused indexes, downgrades instances to lower configurations, and investigates services that could be upgraded to newer, more efficient technologies. Each action requires careful consideration. The day quickly turns into a battle, balancing cloud cost savings with performance needs—all while ensuring nothing breaks. This scenario highlights the AWS Cloud Usage Optimization challenges faced by DevOps and engineering teams in their day-to-day tasks. These major pain points can be broadly classified as: * **Cloud Waste:** Unintentional overspending due to unused resources, inefficient configurations, and underutilized services. * **Lack of Continuous Optimization:** The need for constant monitoring and adjustments to maintain optimal cloud costs. * **Balancing costs while keeping performance high:** Achieving the lowest possible cost without sacrificing performance and ensuring applications consistently deliver optimal performance. * **Outdated AWS instances:** The constant challenge of upgrading to the latest technologies to leverage performance improvements and cost efficiencies. * **Missed Savings Opportunities:** Focusing only on development and scaling often leads to overlooked cost optimizations and inefficient resource usage. Max, like many cloud engineers, seeks a solution that addresses these pain points and simplifies AWS cloud optimization without sacrificing performance. Max wonders what if there was a real-time assistant who could tell exactly what, when, and why to optimize. ## **More Than Just a Tool—Industry’s first Real-Time AWS Cloud Optimization Assistant** Meet, CloudKeeper Tuner, an Built with cloud & DevOps engineers in mind, CloudKeeper Tuner acts as a**real-time assistant for smarter AWS cost and usage optimization** while seamlessly **integrating with the flow of work across multiple AWS accounts**. **Here's what makes CloudKeeper Tuner a non-negotiable for your team:** * ### **150+ Tailored Recommendations across 50+ AWS Services** CloudKeeper Tuner stands out as the industry’s first platform to offer **150+ tailored recommendations across 50+ AWS services, covering nearly 90% of a typical AWS bill**. This unparalleled breadth ensures no cost-saving opportunity goes unnoticed, making your cloud cost optimization efforts truly comprehensive. On average, teams using CloudKeeper Tuner save **10% or more on their AWS bills** , all while maintaining peak performance. * ### **Intelligent Optimization Algorithms** Powered by **advanced algorithms based on the AWS Well-Architected Framework** , CloudKeeper Tuner delivers actionable insights that align with cloud best practices. It goes beyond surface-level suggestions to provide strategic guidance, helping your team optimize resources with precision. * ### **Seamless Integration with AWS Console via Browser Extension** Why juggle between tools when everything you need can be accessed directly within the AWS Console? With **its intuitive browser extension** , CloudKeeper Tuner **integrates effortlessly into your team’s flow of work**. In just a few clicks, you gain instant, actionable recommendations that turn your AWS Console into a powerhouse of insights. * ### **Measurable ROI for Each Recommendation** Every recommendation from CloudKeeper Tuner comes with **estimated savings** , ensuring full visibility into what you’re optimizing, why it’s necessary, and how much you’ll save. This transparency empowers your team to make data-driven decisions with confidence. * ### **Smart Data Ingestion for Real-Time Insights** CloudKeeper Tuner passively ingests usage and cost telemetry from your AWS accounts, adapting dynamically to ongoing updates in your environment. It ensures that your cloud optimization strategy evolves alongside your infrastructure without missing a beat. ## **CloudKeeper Tuner: Features That Drive Results & Create Impact** Let’s take a closer look at how Tuner makes optimization both effortless and precise, helping you save on unnecessary costs. ### **1. Smart Recommendations: Maximize Efficiency, Minimize Waste** * **Eliminate Waste:** Easily identify and remove zombie or unused resources to reduce unnecessary spending. * **Right-Size Resources:** Optimize over-provisioned compute and storage services for maximum cost-efficiency without compromising performance. * **Modernization Upgrades:** Stay ahead by upgrading to the latest AWS instances, ensuring improved performance and significant savings. ### **2. SpotBot: Save Big with Dynamic Spot Optimization** * **Up to 65% Cost Savings:** Automatically switch ECS Fargate tasks between Spot and On-Demand instances, based on availability, for optimal cost reductions. * **Seamless Execution:** Maintain task reliability while balancing costs and instance availability through dynamic, automated adjustments. ### **3. Scheduler: Intelligent Resource Management** * **Cut Idle Costs:** Automatically shut down inactive resources during off-hours to avoid unnecessary expenses. * **Environment Conscious Operations:** Lower energy usage and reduce your environmental impact with optimized scheduling of cloud resources. ## **Implementation Support by AWS experts to further ease your AWS Cloud Optimization** CloudKeeper Tuner goes beyond offering recommendations —you get a helping hand to turn them into action.**Backed by a team of over 100 AWS-certified engineers** , we’re here to make the implementation process smooth and hassle-free. For every AWS cloud optimization recommendation, from cleaning up unused resources to rightsizing instances and fine-tuning configurations, our experts handle the implementation process with precision. This means you don’t have to worry about the complexities of execution or disruptions to your workflow. Think of it as having a **optimization becomes a hassle-free experience, saving you a lot of time, money & resources.** Subsequently, CloudKeeper Tuner becomes the **only platform that your DevOps & engineering team needs** for smarter & precise AWS Cloud Usage Optimization. It enables teams with powerful insights to make informed, data-driven decisions, achieve significant savings, and maintain peak performance—all in a single interface. **In less than a month****, CloudKeeper Tuner received a great response, and 20 customers have already signed up** and begun leveraging it for smarter & effortless AWS Cloud Optimization. Experience the transformative impact of CloudKeeper Tuner and join the ranks of organizations that have achieved substantial savings and operational efficiency. Ready to experience the benefits of CloudKeeper Tuner firsthand? Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Director Praneet brings over 14 years of experience in building high-growth SaaS companies right from 0$ to IPO. He has held key roles at Udemy, Gainsight, and Deloitte. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents More than 53% of companies who have set out on their Cloud FinOps journey do not still have a clear understanding of their cloud costs. To successfully manage cloud costs, a robust cloud cost visibility framework is critical. In other words, it is crucial to have a clear visibility into how you use cloud resources and what they cost you. In this article, we will look into the basics of cloud cost visibility and the common challenges that companies encounter while trying to optimize their cloud infrastructure to save cloud costs. ## **What is cloud cost visibility and why it matters** The basic premise of cloud cost visibility is that to be in greater control of your costs, you must understand where your costs are being spent. This involves diving into your cloud services and instances and exactly having a clear view of what each resource is consuming, along with ways and means to optimize them. Think of it as the process of monitoring, tracking, and analyzing your cloud costs, and then getting actionable tips on With a cloud cost visibility solution in place, you can better analyze your data, look for trends, identify underutilized resources, and Cloud cost visibility also helps in setting up budgets and forecasting future spending to avoid cost escalations. Cloud cost visibility platforms can also help automate your cloud cost optimization by turning off unused resources, detecting anomalous usage and spending thresholds, or sending alerts when spending exceeds a predefined budget. ## **Challenges to cloud cost visibility** Cloud cost visibility is often plagued with a lot of challenges. Some of them are: **Complex cloud prices:** The complexity of AWS offerings with different configurations and **Tagging complexities:** Tags are critical to a cloud visibility strategy. However, working with tags can be time-consuming and highly complex. Untagged resources can also lead to incorrect cloud spend and usage reports. **Dynamic cloud resources:** The dynamic nature of cloud resources can make it difficult to predict costs and further manage their spending. **Report granularity:** The monthly bill that AWS provides does not include a granular breakup for different departments, business units, services, resources, or applications, making achieving cloud cost visibility challenging. **Multi-account and multi-region:** Tracking and monitoring costs become highly challenging when the AWS accounts or resources are distributed across different regions and geos. ## **Navigating the challenge in cloud cost visibility** Cloud cost visibility can be achieved by a concerted effort of every team and stakeholder and with a clear understanding of your cloud infrastructure. Here are a few key steps. **1. Collaboration of different stakeholders:** A strong and cohesive FinOps team with stakeholders from engineering, operations, finance, etc. is the first towards towards gaining complete visibility into your organization’s overall cloud costs. The whole team should collectively understand the correlation between cloud infrastructure, AWS infrastructure costs, and business goals and actively towards value achievement. The team should imbibe a culture of cloud cost visibility and awareness. **2. Follow a unified Tagging strategy:** Organizations need to create and follow a plan around how to tag resources in a unified and consistent manner. It is important to note that tags are meaningful only in the context of an organization, so you need to create a tagging strategy that reflects your internal structure and reporting system. When executed in the right manner, a unified tagging strategy can give you high tag coverage and also create a culture of visibility where all the resources are tagged correctly, and there is complete allocation of costs. **3. Cost Allocation strategy:** Cost allocation can play a key role in establishing a robust cloud cost visibility foundation. Cost allocation tags provide a structure for you to categorize your cloud resources and infrastructure. While cost allocation tags have no semantic purpose, they help identify the purpose and owner of every resource thus helping with tracking, accountability, and reporting. Learn more about the **4. Leverage Granular Business Reporting:** Granularity in reporting can help you scrutinize resource utilization with precision, allowing you to make informed decisions that positively impact your bottom line and result in Granular reporting will exactly pinpoint and monitor any abnormal spike in cloud utilization, any cost trends and patterns, and also the usage of reserved instances identifying the ones that are being underutilized. **5. Scale Efficiently with Centralized Cloud Management:** You can efficiently navigate the complexities of multiple cloud accounts by managing them through a central unified dashboard. This centralized approach provides a comprehensive overview, empowering you to scale operations seamlessly. With the right set of cloud cost visibility platforms and tools, the formidable task of managing multiple cloud accounts is made very easy. Despite the hurdles and complexities, cloud cost visibility remains an indispensable element for successful Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Amazon Elastic Block Store (EBS) volumes are a crucial component of Amazon Web Services (AWS). They provide durable and persistent block-level storage for Amazon EBS volumes come in four different types, each designed for specific use cases: **1. General Purpose SSD (gp2) volumes:-** This is the most common AWS EBS volume type. It provides a balance of price and performance and is suitable for a wide range of workloads. GP2 volumes deliver a consistent baseline performance of 3 IOPS per GB, with the ability to burst to higher levels for short periods. **2. Provisioned IOPS SSD (io1) volumes:-** This AWS EBS volume type is designed for workloads that require high and consistent I/O performance. IO1 volumes can deliver up to 64,000 IOPS per volume and can be configured to deliver the exact level of IOPS required by the workload. **3.****Throughput Optimized HDD (st1) volumes:-** This type of EBS volume is designed for workloads that require frequent access to large, sequential datasets, such as big data and data warehousing. ST1 volumes provide consistent throughput performance of up to 500 MB/s per volume. **4. Cold HDD (sc1) volumes:-** This is the most cost-effective type of EBS volume. It is designed for infrequently accessed workloads, such as backups and archives. SC1 volumes deliver low-cost storage at a rate of up to 250 MB/s per volume. In addition to these types, AWS also offers EBS volumes that are optimized for specific workloads, such as EBS Magnetic volumes, which are ideal for small workloads with low throughput requirements, and EBS Throughput-Optimized HDD volumes, which are designed for large, sequential workloads with high throughput requirements. In conclusion, EBS volumes are an essential component of AWS storage. Their durability, low-latency access, and scalability make them suitable for a wide range of workloads, and the variety of types and optimized volumes allow users to tailor their storage to their specific needs. ## **Benefits of Moving to GP3 from IO1/GP2** Moving from IO1 or GP2 EBS volumes to GP3 volumes in AWS can provide several benefits, including cloud cost savings and improved performance. GP3 volumes offer a higher baseline performance than GP2 volumes, providing a baseline of 3,000 IOPS and 125 MB/s throughput. This makes them ideal for workloads that require more consistent performance, such as databases or mission-critical applications. GP3 volumes also offer a higher IOPS per GB ratio than GP2 volumes, which means users can potentially achieve the same or better performance with fewer GB of storage. This can result in significant When migrating to GP3 volumes, it is important to consider the workload's I/O patterns, as well as the performance requirements and available budget. AWS provides tools such as the AWS Cost Explorer and the EBS Cost Optimization report to help users estimate the cloud cost savings they can achieve by migrating to GP3 volumes. In conclusion, moving from IO1 or GP2 volumes to GP3 volumes in AWS can provide significant ## **Benefits of Moving to IO2 from IO1 if GP3 is not feasible** If moving to GP3 volumes is not feasible, upgrading to IO2 volumes in AWS can still provide improved performance and greater reliability. IO2 volumes offer a higher durability and longer lifespan than IO1 volumes, making them ideal for critical workloads that require high levels of data protection. IO2 volumes also provide a higher maximum IOPS per volume (up to 64,000) and higher throughput than IO1 volumes, making them suitable for workloads with high I/O requirements. IO2 volumes also come with an added feature of Multi-Attach, which allows the same volume to be attached to multiple instances at the same time. This feature is useful for applications that require multiple EC2 instances to share the same data, such as clustered databases. Migrating from IO1 to IO2 volumes can be done with minimal downtime and disruption, as the process involves taking a snapshot of the existing volume and creating a new IO2 volume from the snapshot. However, it is important to carefully plan the migration and ensure that the appropriate backup and recovery processes are in place. In summary, upgrading to IO2 volumes in AWS can provide improved performance, greater reliability, and enhanced features such as Multi-Attach. While not as cost-effective as GP3 volumes, IO2 volumes are still a viable option for workloads that require high levels of data protection and performance. ## **Throughput limitation and IOPS charges for GP3** GP3 volumes in AWS EBS have two types of charges associated with them: IOPS charges and throughput charges. The IOPS charges are based on the number of provisioned IOPS, which determine the performance of the volume, and the throughput charges are based on the amount of data transferred to and from the volume. While GP3 volumes offer a baseline performance of 3,000 IOPS and a throughput of 125 MB/s, users can burst up to 16,000 IOPS for short periods, based on the amount of unused I/O credits available. However, if the volume exceeds its baseline performance, additional IOPS are charged at a rate of $0.05 per provisioned IOPS per month. GP3 volumes also have a throughput limit based on the size of the volume. Volumes smaller than 1 TiB have a maximum throughput of 250 MiB/s, while volumes larger than 1 TiB have a maximum throughput of 1,000 MiB/s. If the volume exceeds its maximum throughput, additional throughput is charged at a rate of $0.04 per GB per month. It is important to carefully plan and monitor the IOPS and throughput usage of GP3 volumes to avoid unexpected charges. AWS provides tools such as Amazon CloudWatch and the AWS Trusted Advisor to monitor and optimize EBS usage. In summary, while GP3 volumes offer a lower-cost alternative to IO1 and GP2 volumes, it is important to be aware of the IOPS and throughput charges associated with them. Careful planning and monitoring can help ensure that the volume remains within its baseline performance and throughput limits, avoiding unexpected charges. _If you are looking to streamline your AWS infrastructure, ensuring maximum performance, reliability, and cost-efficiency for your workloads,_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents We all know that keeping tabs on cloud spending is crucial, but let’s face it - it's often as clear as mud. About To tackle this, it's crucial to have a clear visibility into how you use cloud resources and what they cost you. A strong cloud cost analytics framework is instrumental in successfully managing cloud costs, ensuring a more streamlined and informed Cloud FinOps strategy. Without much ado, let's dive straight into the basics of cloud cost visibility and the common challenges that organizations often encounter when trying to understand what's going on with their cloud infrastructure. ## **The What, Why, and How of Cloud Cost Visibility** The core concept of cloud cost visibility revolves around understanding the various costs associated with running your cloud infrastructure. This involves diving into your cloud services and instances and coming out with a clear picture of where your money is going. Think of it as the process of Simply put, cloud cost visibility gives you the power to visualize, comprehend, and optimize your cloud costs. It is not just about making information available, but to derive insights from them and to deliver actionable recommendations. Thankfully, cloud providers have thrown us a lifeline here with in-house visibility tools. AWS Cost Explorer is one such tool offered for AWS cost analytics and usage forecasting. Similarly, you have Azure Cost Management for Now, you might think, "Great, we have the tools, so what's the big deal?". Well, if it were that simple, everyone would be a pro at it (remember the statistic we mentioned earlier?). So what’s holding you back from implementing crystal-clear visibility measures on your cloud infrastructure? ## **Challenges to Cloud Cost Visibility** In the ever-changing landscape of the cloud ecosystem, achieving cost control necessitates a proper cloud cost tracking and analytics strategy. However, attaining cloud cost visibility proves to be a formidable challenge for numerous organizations, akin to navigating a labyrinth. There are quite a few reasons for this. **Complex Cloud Prices:** Cloud providers like AWS, Azure, and GCP boast a plethora of services, **Tagging Quandaries:** Efficient tagging is crucial for accessing accurate cloud cost reports. However, the complexities and efforts involved can lead to inaccurate reports and cost mismanagement. **Dynamic Cloud Resources:** The scalability of AWS resources introduces unpredictability into cloud cost forecasting, much like predicting the weather. **No Granular Reports:** Monthly bills from native analytics tools like the AWS Cost Usage Report or Azure Cost Management lack granularity, hindering the ability to break down costs for different departments or services. **No Central Dashboard:** Managing multiple cloud user accounts could be as difficult as herding cats. While consolidated billing is an option, it lacks efficiency in providing a centralized overview. **Multi-Account & Multi-Region Challenges: **Organizations with dispersed cloud accounts or resources across regions encounter difficulties in tracking and managing costs. ## **Impact of Poor Cloud Cost Visibility on Your Finances** In the face of these obstacles hindering a straightforward, walk-in-the-park approach to achieving robust cloud cost visibility, one might be tempted to opt for subpar outcomes. But that’s a problem in itself since this play of hide and seek with cloud costs could have multiple repercussions. **Operational Disruptions:** Overlooking performance lags or system downtime can unleash havoc on day-to-day operations, leading to disruptions that may go unnoticed until they escalate. **Security Vulnerabilities:** The absence of **Cost and Resource Inefficiencies:** Ineffectively managing and utilizing resources results in operational inefficiencies, driving up costs unnecessarily and impacting the overall financial health of the organization. **Compliance Risks:** Ignoring compliance standards opens the door to legal consequences and reputational damage. Non-compliance could lead to regulatory penalties, tarnishing the organization's standing in the industry. Now that we have understood the hurdles and why you should not just take your hands off the steering wheel, let’s understand the solutions that pave the way for a robust cloud cost optimization strategy. ## **Unlocking Cloud Cost Clarity** Embarking on a journey to conquer the intricacies of cloud costs demands a strategic approach. Here are essential practices to steer you in the right direction: **1. Build Your Cloud FinOps Team:** Forge a Cloud FinOps team that brings together expertise from development, operations, engineering, and finance. This collaborative effort ensures a cohesive alignment of your cloud infrastructure with overarching business goals. **2. Strategic Tagging for Precision:** Implement **3. Granular Business Reporting for Informed Decisions:** Dive deep into spending patterns through granular reporting. Uncover opportunities for optimization by scrutinizing resource utilization, allowing you to make informed decisions that positively impact your bottom line and fuelling accurate cloud cost forecasts. **4. Foster a Culture of Visibility with Unified Tagging:** Cultivate a culture of cloud cost visibility by enforcing a unified tagging strategy across all resources. Consistency in tagging practices ensures that every aspect of your cloud infrastructure is transparent, facilitating streamlined cost management. **5. Scale Efficiently with Centralized Cloud Management:** Efficiently manage the complexity of multiple cloud accounts by centralizing control through a unified dashboard. This centralized approach provides a comprehensive overview, empowering you to scale operations seamlessly. While this might seem like a formidable task, the good news is that a robust ## **Why You Should Bet on CloudKeeper Lens?** While the native cloud cost analytics tools of the cloud providers might have several features, there are several other use cases and needs that span out of their range of capabilities. That’s why you need a comprehensive, one-stop cloud cost visibility solution like CloudKeeper Lens. The solution offers you real-time insights, cost optimization recommendations, and a granular view of your cloud spending patterns and cost usage. The best part, the solution has: * No Upfront Costs. * No Access Requirements to your Cloud Account. * Support both AWS and Azure Infrastructures. Practically, the platform requires zero effort from your side and would serve you in-depth insights into your costs, with just a few minutes of onboarding. It also offers a wide array of services that help you tackle your cost visibility challenges. **Billing Summary:** CloudKeeper Lens provides a detailed cloud bill summary, unveiling daily spending and breaking down costs across AWS and Azure services, turning numbers into actionable insights. **RI & Savings Plan Utilization: **The platform deciphers hourly usage patterns, ensuring reserved instances and savings plans aren't just data points but vital tools for maximizing your cloud investment. **Compute and Storage Services Breakup:** With advanced cloud cost analytics capabilities, it helps **Daily Cost Breakup Reports:** CloudKeeper Lens uses a heatmap to transform daily variations into a visual map, simplifying the identification of specific usage types for AWS and Azure services. **VM Instances & Storage Breakup:** The solution goes beyond costs, understanding the most resource-intensive VM instances and storage components. Make informed decisions aligning spending with strategic objectives. With all these features, along with proactive guidance and support from certified Cloud and DevOps experts, CloudKeeper Lens can help you navigate the cloud cost maze easily. ## **Solving the Cost Visibility Puzzle** Despite the hurdles and complexities, cloud cost visibility remains an indispensable element for successful Let CloudKeeper Lens be your beacon, lighting up the path to clarity, cost savings, and Cloud FinOps brilliance! _Would you like to take a look at how CloudKeeper Lens demystifies the cost and usage insights of your cloud infrastructure?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents ## **Introduction** AWS EC2 provides stability in computing, networking, and handling a request. AWS provides different types of options when choosing any virtual machine that contains different CPU, Memory, and networking capabilities with all that AWS also provides options in processors as well. While choosing a processor for your VM can improve the performance as well as it will impact the pricing. By selecting a processor aligned with your requirements, you can boost efficiency and potentially realize significant ## **Advanced RISC Machine (ARM)** ARM is an architecture used in chipsets and requires a much smaller instruction set. This type of processor architecture is commonly used in mobile devices and other small devices. ARM processors refer to the CPU architecture designed by AWS that is optimized for cloud workloads. ARM processors are available for use in ## **Advanced Micro Devices (AMD)** AMD processors are a type of processor architecture commonly used in servers, laptops, and gaming consoles. It is based on the Zen architecture and is designed to offer high performance and scalability for cloud workloads. AMD processors are better suited for workloads that require a high level of parallel processing and scalability. AMD gives you all the tasks at once. It offers up to 64 cores per processor, making them well-suited for workloads. ## **Cost Impact on Using ARM** ARM processors are more cost-efficient than AMD and will provide scalability and availability according to the requirements. ### **Migrating running infrastructure from AMD to ARM** To migrate running infrastructure from AMD to ARM contains some steps and prerequisites by which we can do that in a practical way, Below mentioned steps are helpful in that. **Step 1:** The beginning of this migration starts with creating a multi-architecture image of your Java application which can run on both AMD and ARM-type processors and promises zero downtime while migrating your services. Docker Buildx does the same for you and allows you to create a multi-arch image of your services. Set-up docker buildx Install Docker on Server Install Git Setup Docker Buildx on the server Vim into the daemon.json file and paste the content. save exit Experimental = true indicates the following command works Check buildx working **Step 2** : Build and push all the java services docker files using docker buildx and push to ECR. Sample docker-file Command to build and push the image to the ECR. --push will push the image to the ECR repository **Step 3:** Hosting on AWS EKS Set up node-group on AWS. Create all docker base images using buildx and push them to ECR. Create a Docker file that can support buildx creation. Create a new version of the launch template from the existing node group. Use arm AMI in the launch template. Using a new version of the launch template, launch a new node group and provide a graviton-type instance in ASG. After the successful creation of a new node-group delete the old node-group after that uninstall all services and deploy using the docker buildx command. **Handle docker buildx volume** In the server where the docker buildx is configured check the location cd /var/lib/docker/volumes/ id there is any buildx volume is creed and size get increased after each buildx build you have to create a cron job for The command has to be run periodically according to the number of deployments. _If you are looking for a trusted partner in your journey of_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents The Let’s look at some of the easiest ways to optimize cloud spend that do not require any kind of development changes: * **Talk To Your Service Provider To Get The Best Deal:** One of the easiest things, to begin with, would be to have price negotiations with cloud service providers or value-added providers about optimization or discounting possibilities to get the best deal for your business. For example, * **Optimize the Cloud Infrastructure:** It is a good strategy to have an easy mechanism that can automatically bring up and shut down the infrastructure that is not needed in a 24*7 work environment, which mainly includes development, QA, UAT, and performance testing, which are not required for more than eight to nine hours five days a week. It is possible to save up to 40-60% in non-production environments. * **Storage Optimization** Organizations can opt for different archival and cloud storage mechanisms that can be leveraged based on the usage pattern. Cloud provides the flexibility to store data based on its usage, that are classified into three categories : **Hot Storage:** It includes the data that is accessed very frequently. **Warm Storage:** It includes data that is accessed less frequently, accessed as quickly as hot data, so it can be stored on slightly slower, capacity-optimized. **Cold Storage:** It includes data that is rarely accessed. It is important to consider access patterns when deciding what data to store. Setting cloud mechanisms properly will lead to cost efficiency. * **Leverage Auto-Scaling** Being cloud-native, it is important to pick the right tool for the tasks, and dynamically allocate capacity with features like The auto-scaling eliminates the need to respond manually in real-time to traffic spikes that require additional resources and instances by automatically altering the number of active servers. _These are the few action steps that can help you avail quick wins before moving on to mature optimization practices. Now, let's look at some other key practices for reducing your cloud bills:_ ## **Rightsize Your Compute Resources Proactively** Cloud computing has a variety of procurement options, such as On-Demand, Scheduled, Reserved Instances, Savings Plans, and Spot. The different types of options may be suitable for a different organizations based on the approach that they are using. For example, In the initial stage, if you are starting with re-factoring the legacy system or vertical scaling, you can go with the Reserved Instances(RI) Option. In another scenario, if the need is to speed up the delivery time and make the system more scalable in terms of data, we can move towards saving plans. In the case of discounting, as the data keeps on growing, one can work out with vendors on private pricing to grab the best deal. The idea here is to align your option with the approach or goal you are aiming for. ## **Invest in Automation** Automating tasks induces muscle memory and helps avoid mistakes and make informed decisions. Automating tasks such as tag governance is a critical foundation for your cloud governance initiatives. Tag governance helps identify infrastructure that is making an impact and infrastructure that is less often used. The use of consistent tagging policies can have multiple benefits, from improving compliance and automation to cost management and enhancing cloud environments. ## **Take help from Service Provider and Third-party in the FinOps journey** It is a fast-evolving crowded space, and a business cannot do it all on its own, hence it is a good idea to take help from tools or collaborate with a partner who can make your FinOps journey easier. A service provider can be classified into three categories: * **Managed service provider:** They generally provide services in a combination of using their own homegrown tools or using third-party tools, along with technically competent and capable people who are providing solutions to organizations. They can be working completely in an outsourced model or they are embedded into the technology teams of the client organizations and providing FinOps as a service. * **Saas Solution or products:** these are products that different organizations can use depending upon their need depending upon their life cycle, As the space is fast evolving businesses can have products which are providing very customized or deep dash-boarding, reporting, all the way to automation for reserved instances for a savings plan, etc. But you have to use them, integrate them into your ecosystem, and see what makes sense for you. * **Dedicated FinOps Vendors:** They provide everything from informing reporting dashboard things to helping you with saving plans and architecture. _CloudKeeper provides instant savings of up to 15% starting from Day 1 as soon as the customer signs up with us in addition to a cost management platform and a team of cloud experts for periodic evaluation and audits, 24*7 monitoring, and finops services._ _If you would like to know the best cloud cost management strategy for your business_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 14 14 Table of Contents Modern applications require modern infrastructure to run. At this time and age, everything is running on Microservices based architecture and monoliths are a thing of the past. Containers and container management have become a huge aspect of delivering your applications to a large audience without compromising overall performance for better user experience. The one technology synonymous with scalability and container orchestration is Kubernetes. Hence being well versed in running and managing your K8s workloads is a big requirement and the right way to go is to optimize the cloud costs of these resources. In this blog we would be taking a look at some AWS cost reduction strategies that you could implement in your EKS environment to prevent it from burning a hole in your pocket. ## **What is EKS?** According to the official AWS documentation, Amazon EKS is a managed Kubernetes service to run Kubernetes in the AWS cloud and on-premises data centers. But what does a managed Kubernetes service mean? Does that mean that AWS would manage your EKS cluster on behalf of you or does it means that AWS will have full control over your deployed application? If you are thinking about the former, you might be wrong. A managed Kubernetes service means that AWS would take care of setting up of your Kubernetes control plane and install all the necessary components required for smooth running of your Kubernetes infrastructure. If you have ever set up a Kubernetes cluster from scratch you would know the pain you have to go through to get it working, AWS helps you by setting up the cluster automatically, leaving you with deploying your workload on that infrastructure. EKS can help you manage your Kubernetes workload on AWS cloud as well as the on-premises data centers. ## **Components of an EKS cluster:** An EKS cluster consists of two primary components: * EKS control plane which consists of all the necessary requirements for running the Kubernetes software like etcd, Kubernetes API server. * EKS nodes that are registered with the control plane. ## **EKS pricing:** To know how to realize cloud cost savings on EKS resources, you first need to understand how you are going to be billed for using EKS. Let’s start with creating your EKS cluster, for every EKS cluster that you create there is a fixed flat $0.10 hourly fee. You have multiple options of running EKS, you can either run EKS on Amazon EC2 instances, AWS Fargate or on-premise using AWS outposts. We will get into the details of running your EKS cluster on EC2 and Fargate in later sections of this blog. If you are running your EKS workloads on EC2 instances, you will be paying for what you use. The fee would depend on the type of EC2 instances and the resources like EBS you use for running your instances. For a more detailed overview of EC2 cloud cost management, you can refer to the If you are running your cluster on AWS Fargate, you will be billed for vCPU and memory consumption right from the beginning of the image download till your pod termination. ## **Understanding your EKS costs:** Now that you have a basic understanding of EKS pricing, let's take a deeper dive into how you can better manage your existing EKS infrastructure. There are several tools available to help you understand and visualize your EKS cluster costs. You can configure your EKS cluster with cluster-level cost allocation tagging provided by AWS. If you are running your EKS workload on EC2, enabling these tags will automatically allocate them to your EC2 instances attached to your EKS cluster. These tags can be used to monitor how much the EC2 instances attached to your EKS cluster are costing. By using these tags, you can assign EC2 expenses to specific EKS clusters via Another way to ## **Understanding compute purchase options** Now, we know how you are billed on your EKS cluster. Let’s take a look at the compute options available to you. We have already talked about them but now, we will be trying to get a better understanding of how they can be useful for you while you are optimizing your EKS costs. You already know you are going to be charged a flat $0.10 hourly fee for every time you create an EKS cluster. The right cloud cost management strategy here is selecting the right compute option to go with your EKS workloads. There are three option available for you: * EC2 Instances - Let’s first talk about the most simplest method available to you to deploy your EKS cluster, the EC2 instances. If you are beginning to set up your EKS infrastructure using EC2 is a good place to start. * AWS Fargate - AWS Fargate is a service offered by AWS which enables you to run your containers without worrying or provisioning any server. This service is useful if you are running large scale infrastructure and don’t want an additional overhead of managing your servers. * Amazon Outposts - If you are running your EKS workload on your On-Premises infrastructure, you could leverage Amazon Outposts. Outposts enables you to run AWS services, APIs and tools at your own in-house datacenters. ## **Understanding your cluster requirements:** It’s important to first correctly know the ins and outs of your requirements. If you are starting out with EKS or you are hosting a new application which would not have a number of users it would be an overkill to use a huge instance fleet or compute optimized instances. Similarly understanding the usage behavior and resource consumption of your application is an important part of your For example you are running an application for your team’s internal use only which would only be having 10-15 users, and selecting EC2 instances as your preferred type, With compute optimized instances, it will be difficult to achieve cloud cost savings. ## **Enable ClusterAuto Scaling:** Autoscaling in EKS means that the service can automatically adjust the number of resources allocated to your application based on its current demand. This includes adding more worker nodes, which are like individual computers that run your application, or scaling up the capacity of your existing nodes to handle more workloads. For example, if your application suddenly experiences a spike in traffic, EKS can automatically add more worker nodes to handle the increased demand. And when the traffic subsides, EKS can also automatically remove the excess nodes to save resources and reduce costs. EKS autoscaling can help ensure that your application is always available and responsive to users, without you having to manually adjust the resources or worry about capacity planning. It can also help optimize cloud costs by automatically scaling up or down based on actual demand. Autoscaling can help optimize EKS costs in several ways: * **Right-sizing resources:** Autoscaling can help you allocate just the right amount of resources needed to handle your application's workload. This means that you're not wasting resources on over-provisioned infrastructure that sits idle and incurs unnecessary costs. With autoscaling, you can add more resources when needed and remove them when they're no longer required. * **Avoiding over-provisioning:** Over-provisioning means having more resources than necessary to handle the workload, which can lead to higher costs. Autoscaling can help you avoid over-provisioning by scaling resources up or down based on actual demand. For example, if your application experiences a sudden spike in traffic, autoscaling can add more resources to handle the increased load, and then remove them when the traffic subsides. * **Saving on compute costs:** Autoscaling can help you in cloud cost savings by automatically selecting the most cost-effective instance types and sizes based on the workload requirements. This means that you're only paying for what you use. * **Reducing manual intervention:** Autoscaling can help reduce the need for manual intervention in scaling resources, which can be time-consuming and error-prone. With autoscaling, you can set up policies and rules to automatically scale resources based on predefined thresholds and parameters, which reduces the likelihood of human error and helps ensure consistent performance and availability. Overall, autoscaling boosts your AWS cost reduction strategies by dynamically adjusting the resources allocated to your application based on actual demand, avoiding over-provisioning, and reducing the need for manual intervention. ( ## **Using Spot Instances:** A Spot Instance is a purchasing option for Amazon Elastic Compute Cloud (EC2) instances, where you can bid for unused EC2 instances at a significantly lower price compared to On-Demand instances. It allows you to take advantage of Amazon's spare computing capacity, which can be sold at a discounted price when the demand for instances is low. When you launch a Spot Instance, you specify the maximum hourly price you're willing to pay for the instance. The actual price you pay is the current Spot Price, which fluctuates based on supply and demand. If the spot price goes above your maximum price, your instance will be terminated automatically. In EKS, you can use Spot Instances to run your Kubernetes worker nodes, which are the instances that run your containerized applications. By using Spot Instances, you can optimize cloud costs, with discounts up to 90% compared to On-Demand instances. However, Spot Instances come with the risk of being interrupted or terminated at any time, which can affect your application's availability and performance. To mitigate this risk, you can use strategies such as instance diversification, which spreads your worker nodes across different availability zones and instance types to reduce the impact of interruptions. You can also use a combination of Spot Instances and On-Demand or Reserved Instances to ensure that you have enough capacity to meet your application's requirements. In summary, using Spot Instances in EKS can help in cloud cost management by taking advantage of discounted EC2 capacity, but it requires careful planning and risk management to ensure that your application remains available and performant. ## **Using AWS Fargate:** Autoscaling can help optimize EKS costs in several ways: * **No need to manage EC2 instances:** With Fargate, you don't need to provision, manage, or scale EC2 instances for running your containers. This means that you don't have to worry about the cost and complexity of managing EC2 instances and you can focus on your application instead. * **Pay for what you use:** Fargate pricing is based on the actual compute and memory resources used by your containers, with a minimum billing increment of one second. This means that you only pay for the resources your application needs and you can optimize cloud costs by right-sizing your containers based on their actual usage. * **Higher resource utilization:** With Fargate, you can achieve higher resource utilization compared to running containers on EC2 instances. This is because Fargate can pack multiple containers on the same underlying infrastructure, reducing the overhead of running multiple EC2 instances. This means that you can achieve better resource utilization and reduce your overall costs. * **Reduced operational overhead:** Fargate can help reduce operational overhead by abstracting away the complexity of managing EC2 instances. This means that you don't have to worry about patching, scaling, or monitoring EC2 instances, which can reduce the amount of time and resources required to manage your infrastructure. Overall, Fargate can help achieve cloud cost savings by eliminating the need to manage EC2 instances, paying for what you use, achieving higher resource utilization, and reducing operational overhead. ## **Minimizing Inter-AZ data transfer charges in EKS:** In Amazon Elastic Kubernetes Service (EKS), data transfer charges refer to the fees associated with transferring data between different AWS services or different Availability Zones (AZs) within the same region. For example, if your EKS cluster has worker nodes in one Availability Zone (AZ) and your application's database is in another AZ, any data transfer between the worker nodes and the database will incur data transfer charges. Similarly, if your EKS cluster is using an Elastic Load Balancer (ELB) to distribute traffic to your application, any data transfer between the ELB and the worker nodes will also incur data transfer charges. AWS charges for data transfer based on the amount of data transferred and the destination region or service. The charges vary based on whether the data transfer is between different AWS services or different AZs within the same region. Cloud cost management by reducing inter-Availability Zone (inter-AZ) data transfer charges takes the following these best practices: * **Use the same zone for your EKS control plane and worker nodes:** By using the same availability zone for your EKS control plane and worker nodes, you can avoid inter-AZ data transfer charges for communication between the control plane and worker nodes. * **Use Cluster Autoscaler to minimize the number of worker nodes:** Cluster Autoscaler can automatically scale up or down the number of worker nodes based on the application's demand. By minimizing the number of worker nodes, you can reduce the amount of inter-AZ data transfer required for communication between the nodes. * **Use multi-AZ deployment only when necessary:** Multi-AZ deployment provides high availability and fault tolerance by replicating your application across multiple AZs. However, this also increases inter-AZ data transfer charges since data needs to be replicated across multiple AZs. Only use multi-AZ deployment when it's necessary for your application's requirements. * **Use Amazon S3 or Amazon EFS for data storage:** Amazon S3 and Amazon EFS are highly scalable and durable storage services that can be used to store data outside of your EKS cluster. By using these services for data storage, you can introduce cloud cost savings by reducing inter-AZ data transfer charges for accessing and replicating data within your cluster. * **Use Amazon CloudFront for content delivery:** Amazon CloudFront is a content delivery network (CDN) that can distribute your content globally with low latency and high data transfer speeds. By using CloudFront, you can reduce inter-AZ data transfer charges for serving content to your users. Overall, minimizing inter-AZ data transfer charges in EKS requires careful planning and optimization of your infrastructure. By following these best practices, you can reduce your inter-AZ data transfer charges and optimize your cloud costs. In conclusion, optimizing EKS costs requires careful planning and a strategic approach. By leveraging best practices such as using spot instances, scaling clusters based on demand, and minimizing data transfer charges, businesses can significantly reduce their EKS costs while maintaining high availability and performance for their applications. Additionally, using tools like AWS Cost Explorer, Cluster Autoscaler, and third-party tools like Kubecost can help in cloud cost management by monitoring and optimizing their EKS costs in real-time. Ultimately, the key to optimizing EKS costs is to right-size resources based on actual usage, implement automation wherever possible, and continuously monitor and analyze costs to identify potential cost savings opportunities. By adopting these AWS cost reduction strategies and best practices, businesses can successfully optimize their EKS costs, improve their bottom line, and focus on driving innovation and growth. When it comes to Cloud Cost Optimization, having an expert by your side is the right way to go about. Know how CloudKeeper can help you accelerate your FinOps journey. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents AWS S3 is one of the most popular cloud storage services, providing high performance, durability, and security to meet the needs of many types of data storage. But as data grows, so does the cost of storing it in the cloud. S3 pricing is based on the storage class, data transfer, and request frequency, hence, it's easy to incur significant costs if you're not careful. This is where cloud cost management comes into play. By using best practices to optimize AWS S3 costs, you can bring in cloud cost savings while managing your data. In this article, we'll explore six best practices for optimizing AWS S3 costs and how to use them effectively. ## **Use S3 Lifecycle Policies** AWS S3 provides lifecycle policies that allow you to automatically transition objects to different storage classes based on their age. This feature can be used to move objects that are not frequently accessed to cheaper storage classes like Glacier or Deep Archive. This can significantly reduce storage costs and make it easier to manage your data. According to AWS, customers who have implemented S3 Lifecycle Policies have saved up to 40% on their S3 storage costs. By moving objects to a lower-cost storage class, you can **Pros:** * Automatically moves objects to a cheaper storage class or deletes them when they are no longer needed. * Optimize Cloud Costs by reducing the amount of data stored in expensive storage classes. **Cons:** * Requires careful planning and configuration to avoid accidentally deleting important data. * May impact application performance if objects are not immediately accessible when needed. ## **Use S3 Intelligent-Tiering** S3 Intelligent Tiering is an S3 storage class that automatically moves objects between two access tiers based on changing access patterns. This can help you in According to AWS, customers who have implemented S3 Intelligent Tiering have saved up to 70% on their S3 storage costs. By automatically moving data to a lower-cost storage tier, you can practice cloud cost management while still maintaining real-time access to your data. **Pros:** * Automatically moves objects to the most cost-effective storage class based on usage patterns. * Provides cloud cost savings by reducing the amount of data stored in expensive storage classes. **Cons:** * Requires monitoring to ensure that the correct storage class is being used for each object. * Higher cost compared to standard S3 storage class. ## **Use S3 Object Lock** S3 Object Lock is a feature that prevents objects from being deleted or modified for a specified period. This feature can help you avoid accidental deletion of important data and ensure compliance with data retention requirements. It can also help optimize cloud costs by reducing the need for backup and recovery processes. According to AWS cloud cost management statistics, customers who have implemented S3 Object Lock have saved up to 30% on their backup and recovery costs. By preventing objects from being deleted or modified, you can reduce the risk of data loss and reduce the need for expensive backup and recovery processes. **Pros:** * Provides an additional layer of security and compliance for critical data. * Prevents accidental or intentional deletion of objects. **Cons:** * Requires careful planning and configuration to ensure that the retention period is set correctly. * May impact application performance if objects cannot be modified or deleted when needed. ## **Use S3 Requester Pays** S3 Requester Pays is a feature that allows you to charge users for accessing your S3 objects. This can be useful when you are providing data to external parties and want to offset some of the storage costs associated with providing the data. According to AWS, customers who have implemented S3 Requester Pays had 80% cloud cost savings on their **Pros:** * Cloud cost management by transferring the cost of data access to users who require access to your data. **Cons:** * Requires additional configuration and management to set up. * This may create additional complexity for users who need to access your data. ## **Use S3 Batch Operations** S3 Batch Operations is a feature that allows you to perform large-scale batch operations on your S3 objects. This can be used to perform tasks like changing object metadata, copying objects to another bucket, and deleting objects. By using S3 Batch Operations, you can reduce the time and cost associated with performing these tasks manually. According to AWS, customers who have implemented S3 Batch Operations have saved up to 80% on the time and cost associated with performing these tasks manually. By using S3 Batch Operations, you can perform these tasks quickly and easily, resulting in significant **Pros:** * Enables you to perform large-scale operations on objects in S3 quickly and efficiently. * Can save time and effort by automating repetitive tasks. **Cons:** * Requires careful planning and configuration to ensure that batch operations are performed correctly. * May require additional costs depending on the type and frequency of batch operations. ## **Use S3 Storage Class Analysis** S3 Storage Class Analysis is a feature within Amazon S3 that allows you to analyze the access patterns of your S3 objects. This analysis helps you identify objects that are no longer actively used, making it possible to transition them to a lower-cost storage class. Moreover, it assists in identifying objects that experience frequent access, enabling you to move them to a higher-performance and more accessible storage class. **Pros:** * Enables you to identify objects that are stored in expensive storage classes unnecessarily. * Provides insights into usage patterns that can **Cons:** * Requires monitoring and analysis to ensure that the correct storage classes are being used for each object. * This may create additional management overhead to act on the insights provided by the analysis. ## **Conclusion** Optimizing AWS S3 costs is an important aspect of cloud storage management, and following the best practices outlined in this blog can help organizations achieve significant cloud cost savings. By selecting the appropriate storage class, setting lifecycle policies, optimizing object size, and utilizing cloud cost management tools, organizations can minimize their storage costs while still maintaining high levels of data availability and durability. It's important for organizations to continuously monitor and evaluate their AWS S3 usage to identify opportunities for cost optimization and adjust their strategies accordingly. With proper planning and implementation of these best practices, organizations can effectively manage their AWS S3 storage costs and achieve a better return on their cloud investments. _CloudKeeper can help you significantly reduce costs on the entire AWS infrastructure, including storage, compute, database, and more. Sounds interesting?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Aman is a FinOps enthusiast with in-depth expertise in streamlining cloud infrastructures of all scales. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Jenkins is a popular open-source automation server that is used to automate the software development process. It enables you to build automated pipelines that speed up the development, testing, and deployment of your applications. Jenkins shared library, which streamlines the development process and can help you save time and money, is one of its most powerful features. This article talks about Jenkins shared libraries and how they can accelerate your ## **What is a Jenkins Shared Library?** A Jenkins Shared Library is a set of code that can be reused across multiple pipelines. Although it resembles a typical Java library, it was created specifically to be used in Jenkins pipelines. You can create unique steps and functions that can be used in your pipelines by defining them in shared libraries rather than having to write the code from scratch each time. A Git repository can be used to store the shared libraries, making it simple to manage and version them. In order to further increase the functionality of your Jenkin pipeline shared library, you can also use external libraries. ## **How to setup shared libraries on your Jenkins server** * You need to have your GitHub credentials set on the Jenkins server for cloning the Jenkins shared library and application repo. If not, then go to **Manage Jenkins >Credentials>Global credentials** and add the required credentials. * Shared Library Declaration: After configuration, you need to provide a shared library name and repo into the Global Pipeline Libraries. Go to **Manage Jenkins > Configure system>Global Pipeline Libraries**. Here you can see Pipeline Libraries section as shown below: * To create a new multi-branch job, click on **New-item** in the **Dashboard** and give a name to your job. Then select **Multibranch Pipeline**. * Then in multi-branch, add your **source-code repository** with branch name and credentials. * Add the Jenkinsfile in the application repo with the following lines in it: ## **How Shared Libraries Help You Save Money** Here are a few ways in which Jenkins Shared Libraries help you save your overall operating costs. ### **Reduced Development Time** The ability to speed up the development process is one of the main advantages of using shared libraries. You can simply reuse the code that is kept in the shared library instead of having to write unique code for each pipeline. By doing this, you can shorten the time it takes to create your pipelines, which could ultimately help in cost savings. ### **Improved Pipeline Consistency** You can achieve greater consistency throughout your pipelines by using shared libraries. You can make sure that each pipeline follows the same procedure by creating custom steps and functions that can be used by different pipelines. This can assist you in lowering the possibility of mistakes and inconsistencies in your pipelines, which can ultimately help you save money and perform ### **Reduced Maintenance Costs** Additionally, shared libraries might lower your maintenance expenses. You can make updates and enhancements to your code in one place by centralizing it in a shared library. This can save you time and money by preventing you from having to make the same adjustments in numerous pipelines, which also makes it one of the most effective cloud FinOps tools. ### **Scalability** Finally, shared libraries can aid in your development process' increased scalability. You can keep reusing the code from the shared library as your development team expands, which can help you retain consistency and speed up development. You may ### **Reusability and Code Standardization** Shared libraries encourage standardization and code reuse within your organization. You can use the preset functions and procedures in the shared library rather than having to come up with new methods for basic activities. This not only reduces development time but also guarantees standardized and consistent practices across all of your workflows. It lowers the likelihood of mistakes and raises the general caliber of your program. ### **Collaboration and Knowledge Sharing** Your development teams will work together more effectively and share expertise thanks to shared libraries. Developers can contribute to and gain from a common codebase by consolidating reusable code in a library. It encourages a collaborative environment where programmers may benefit from one another's experience and expand on current solutions. By accelerating development cycles and preventing wasteful duplication of effort, this shared knowledge eventually reduces costs. Engineers could also collaborate and work together on improving the Jenkins shared library best practices. ### **Easy Maintenance and Updates** Your pipelines and procedures might need to be optimized as your programme develops. Your pipelines will be easier to update and maintain if you use shared libraries. You may make modifications to the shared library code since it is kept in a central repository, and those changes will instantly be reflected in all pipelines that utilize the library. This streamlines upkeep, lowers the possibility of discrepancies, and decreases the time and labor required for manual updates. ### **Extensibility and Integration** Jenkins' functionality may be expanded and integrated with other tools and systems via shared libraries. Your shared library code might include additional libraries and plugins, facilitating easy interaction with third-party technologies. With this flexibility, you can make the most of your current investments in tools and technologies rather than having to create bespoke solutions from the beginning. You may also ### **Automated Testing and Quality Assurance** Shared libraries' codebases may have automated testing tools and quality control procedures. This guarantees that the shared code has undergone extensive testing and is up to par. You may lessen the possibility of introducing bugs and mistakes into your pipelines by incorporating testing and quality checks into your shared library. As a result, less expensive debugging, troubleshooting, and problem-solving are required to resolve problems brought on by inadequately tested code. ### **Flexibility and Adaptability** Shared libraries provide the flexibility to adapt and evolve your pipelines as your requirements change. You can easily modify and extend the shared library code to accommodate new features, technologies, and best practices. This adaptability helps you stay agile in a rapidly changing software development landscape and could also be considered as a part of the ## **Conclusion** Jenkins Shared Libraries are an effective solution that can aid in cloud cost optimization and an overall cost reduction of your software development initiatives. Shared libraries can speed up your development process and enable you to make long-term financial savings by decreasing development time, enhancing pipeline consistency, lowering maintenance expenses, and attaining higher scalability. It’s high time you explored how shared libraries can help you reach your cost-saving objectives if you are not already using them in your Jenkins pipelines. _Get your entire cloud setup audited and implement architectural-level best practices, with a team of Certified Cloud Experts from CloudKeeper._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents We're back from AWS re:Invent 2023, and let us tell you, it was an exhilarating journey of five days packed with great learnings, insights, connections, and collaboration. Yes, we are a bit tired (in the best way possible) but still buzzing with excitement because of the experiences that we had. AWS re:Invent, the world's largest conference hosted by Amazon Web Services, is a highlight of the year for the global cloud community. Held from Nov 27th - Dec 1, 2023, in Los Angeles, with over 50,000 attendees, this year's event was nothing short of spectacular, exceeding expectations and CloudKeeper, was proud to be part of it as a The keynote announcements, innovation talks, product launches, breakout sessions, workshops, and much more, left the audiences eager to explore the possibilities, and that echoed through the halls. But beyond the technical knowledge, the event offered a unique opportunity to connect with fellow enthusiasts, industry leaders, and potential partners. The energy was infectious, creating an atmosphere of collaboration and innovation. ## **CloudKeeper at AWS re:Invent** On the morning of November 27th, we (a team of 18) were pumped up, and eager to dive into the new experiences the event had in store. Over the next five days, our booth became a hub of activity, hosting more than 1000+ curious minds. We had meaningful conversations about Cloud and FinOps, addressing specific challenges in cloud cost management and showcasing our AWS cloud cost optimization and FinOps solutions. The CloudKeeper team connected with leading analysts, industry veterans, and FinOps experts, discussing the evolving cloud landscape, cost optimization challenges, best practices, and the crucial role of FinOps in driving business value. ### **Lightning Theatre Session by Aman Aggarwal** Our Business Head, In this session, Aman explained the advantages and disadvantages of an AWS EDP, determining your ideal annual commitment amount and span, how to maximize the benefits of an EDP while retaining flexibility, and using Our session will be available on-demand soon, so stay tuned for insights and takeaways! **_Relive AWS re:Invent 2023 in a flash!_** ## **The key takeaways from the event** In addition to our own activities, we were thrilled to witness the exciting announcements made by AWS at re:Invent 2023. Here are some major key takeaways and highlights from the event: * At AWS re:Invent 2023, Generative AI took center stage. The keynote by Adam Selipsky, Amazon Web Services - CEO, provided insights into advancements in data, infrastructure, artificial intelligence, and machine learning, showcasing their role in accelerating the achievement of AWS customers. He went on to describe how AWS is investing in the Generative AI Stack. We got to know an amazing fact that over 80% of Unicorns run on AWS. * The most interesting highlight of the event was the launch of Amazon Q, a groundbreaking generative AI-powered assistant tailored specifically for work environments. * Further on in the announcements, Adam unveiled the Amazon S3 Express One Zone, a new Amazon S3 storage class with high-performance and low-latency capabilities. This storage class delivers single-digit millisecond latency, 10x faster data access, and 50% lower request costs compared to S3 Standard. * Project Kuiper, Amazon's ambitious initiative to provide global internet access, received further attention during the keynote. * Dr. Swami Sivasubramanian, Vice President of Data and AI at AWS, delivered a captivating keynote at AWS re:Invent 2023, exploring the dynamic relationship between humans, data, and AI. He highlighted how companies can leverage their data to build differentiated generative AI applications.He also launched the New Amazon Titan Image Generator, an innovative platform allowing users to generate and customize high-quality, realistic images simply by using natural language prompts. * Dr. Werner Vogels, CTO of Amazon and VP of Amazon delivered a compelling keynote at AWS re:Invent 2023, introducing the "Frugal Architect" approach, outlining seven key principles to guide organizations in building cost-effective, sustainable, and modern AWS architectures.When discussing the impact of AI on technologist jobs, he stressed that humans play a crucial role in making final decisions. Vogels advocated for continual learning as the only way for technologists to keep up with the rapidly evolving tech landscape. Of course, no conference is complete without some fun and relaxation and AWS re:Invent didn't disappoint, with multiple parties, games, after-hours events, and great food to keep the energy high. We danced the night away, celebrated successes, and forged lasting connections – all the while surrounded by the AWSome community of AWS re:Invent. As we return from this enriching experience, we carry with us renewed energy to continue setting benchmarks in the cloud cost optimization space and empowering businesses to excel in their FinOps journey. ## **A Heartfelt Thank You** We extend our heartfelt gratitude to everyone who crossed paths with us, shared insights, and joined in the vibrant discussions. A special note of gratitude to those who visited our booth. Your presence and engagement made our experience all the more meaningful. Thank you for being a crucial part of our re:Invent story! And if you missed visiting our booth, worry not! You can still connect with us Stay tuned as we unpack more insights and takeaways from our re:Invent adventure. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents In the world of cloud computing, AWS has emerged as one of the most popular platforms. While AWS offers a range of services that can help you build scalable and cost-effective solutions, it's crucial to keep an eye on all aspects of cost. One of the often-overlooked factors is the cumulative cost of This article is designed to help you navigate the intricacies of AWS Data Transfers and identify some cost-effective strategies for routing your data. By following these strategies, you can implement AWS data transfer cost optimization and ensure that you're only paying for the data you actually need. ## **What are AWS Data Transfers?** AWS Data Transfers refer to the movement of data either to or from AWS, or between AWS instances across different Regions or Availability Zones. In simple terms, whenever data is moved within or outside of AWS, it constitutes a data transfer. It's worth noting that inbound transfers to AWS are typically free of charge, while outbound data transfers and transfers between different Regions or Availability Zones are subject to costs. These costs are typically calculated on a per-Gigabyte basis and can vary depending on the specific service used and the regions involved. Therefore, it's essential to ## **AWS Data Transfer Pricing Categories** Data transfers into AWS is typically free while transfers out are charged ## **Describing Internet Out data charges** Internet Out data charges refer to the cost incurred when data is transferred from AWS to the internet. This cost is incurred when data is accessed or downloaded from AWS services such as Amazon S3, Amazon EC2, or Amazon RDS. AWS data transfer costs vary based on the amount of data transferred, the specific region involved, and the type of service used. For instance, EC2 data transfer costs are different from AWS RDS data transfer cost. These charges are typically calculated on a per-GB basis and can add up quickly if there is a high volume of outbound data transfer. It is important to note that AWS offers various options to minimize these charges. One strategy is to use AWS Edge Locations, which are distributed around the globe and can provide low-latency data transfer for end-users. Another strategy is to use content delivery networks (CDNs), which can help to reduce AWS data transfer costs by caching data closer to the end-users. Additionally, AWS offers tools such as Amazon CloudFront, which can help optimize data transfer and minimize costs. By monitoring and optimizing data transfer, users can reduce their internet Out data charges and achieve cost-efficient usage of AWS services. Cost-Optimizing AWS services by utilizing Amazon CloudFront with ALB ## **CloudFront with ALB** Amazon CloudFront is a content delivery network service provided by AWS, while an Application Load Balancer (ALB) is a load balancer service provided by AWS. When using CloudFront with ALB in AWS data transfer, the CloudFront distribution acts as a front-end to the ALB, which is used to distribute incoming traffic across multiple targets, such as Amazon EC2 instances. By leveraging CloudFront with ALB, users can benefit from reduced data transfer costs and improved performance. CloudFront caches frequently accessed content closer to the end-users, reducing the amount of data that needs to be transferred from the ALB. This reduces the load on the ALB and helps to reduce AWS data transfer costs associated with the ALB. Additionally, CloudFront provides SSL/TLS encryption, which helps to improve security and protect against network attacks. Overall, using CloudFront with ALB in AWS data transfer can provide an efficient and cost-effective solution for distributing incoming traffic and for AWS data transfer cost optimization. ## **CloudFront with S3** CloudFront with S3 in AWS data transfer refers to the combination of Amazon CloudFront and Amazon S3 services. CloudFront is a content delivery network service provided by AWS, while S3 is an object storage service provided by AWS. When using CloudFront with S3 in AWS data transfer, the CloudFront distribution acts as a front-end to the S3 bucket, which is used to store the content. By leveraging CloudFront with S3, users can reduce S3 data transfer cost and improve performance. CloudFront caches frequently accessed content closer to the end-users, reducing the amount of data that needs to be transferred from the S3 bucket. This reduces the load on the S3 bucket and helps to minimize the AWS data transfer costs associated with the S3 bucket. Additionally, CloudFront provides SSL/TLS encryption, which helps to improve security and protect against network attacks. Overall, using CloudFront with S3 in AWS data transfer can provide an efficient and cost-effective solution for storing and delivering content, while providing an effective way to ## **S3 VPC Endpoints** An S3 VPC endpoint is a managed virtual device that: * Can be attached to any routing table within a single VPC * Can be used to route traffic S3 within a single region * Can be used in a multi-account setting * Has lower network latency than accessing S3 via NAT * Is more secure because the network packets never leave the internal AWS network S3 VPC Endpoints in AWS data transfer refer to a feature that allows users to access Amazon S3 from within an Amazon Virtual Private Cloud (VPC) without using the public internet. When data is transferred from an EC2 instance in a VPC to an S3 bucket, it typically goes through the internet, which can create security risks and increase data transfer costs. By creating an S3 VPC Endpoint, users can establish a private connection between their VPC and S3, which helps to reduce S3 data transfer costs and increase the security of their data. This private connection is established using an Elastic Network Interface (ENI), which is assigned a private IP address within the VPC. When data is transferred from an EC2 instance to an S3 bucket, it is transmitted over this private connection, bypassing the public internet. Using S3 VPC Endpoints in AWS data transfer can provide a more secure and cost-effective way to access and transfer data between EC2 instances and S3 buckets. It eliminates the need to transfer data over the internet, which helps to reduce the risk of data breaches and can save on data transfer costs. It is important to note that S3 VPC Endpoints are only available within the same AWS Region, and there may be additional charges associated with using this feature, such as for data processing or ENI usage. Data transferred through the interface endpoint is charged at $0.01/per GB (depending on Region). ## **Types of VPC endpoints for Amazon S3** There are two types of VPC endpoints available for accessing Amazon S3: * Gateway endpoints * Interface endpoints that make use of AWS PrivateLink. A **gateway endpoint** allows you to access Amazon S3 through a gateway specified in your route table over the AWS network. Gateway endpoints are used to connect your VPC to AWS services that have a VPC endpoint service available. These services include S3, DynamoDB, and Kinesis. Gateway endpoints are used to route traffic between your VPC and the service over the AWS private network. On the other hand, **interface endpoints** provide more functionality than gateway endpoints as they use private IP addresses to route requests to Amazon S3 from within your VPC, as well as on-premises or from a VPC located in another AWS Region through the use of VPC peering or AWS Transit Gateway. Interface endpoints are used to connect your VPC to AWS services that do not have a VPC endpoint service available. These services include EC2 instances, RDS instances, and Elasticsearch domains. Interface endpoints use Elastic Network Interfaces (ENIs) to create a private connection between your VPC and the service. ## **Using NAT Instance for some use cases** When it comes to AWS data transfer cost optimization using NAT instances, there are a few things to keep in mind. First, it's important to Additionally, it's important to consider the data transfer costs associated with using a NAT instance. NAT instances incur data transfer costs for traffic that goes through them, so it's important to monitor and optimize this traffic to minimize costs. One way to reduce data transfer costs is to use a NAT Gateway instead of a NAT instance. NAT Gateways are a managed solution that can handle higher traffic volumes and have lower data transfer costs than NAT instances. However, they may not be suitable for all use cases and can be more expensive than NAT instances for lower traffic volumes. Another way to optimize costs when using a NAT instance is to leverage spot instances. Spot instances are a cost-effective way to run instances with flexible start and stop times. By using spot instances for NAT instances, organizations can potentially save money on instance costs. Finally, it's important to monitor usage and adjust the number of NAT instances as needed. Scaling up or down the number of NAT instances based on traffic patterns can help optimize costs and ensure that resources are being used efficiently. Overall, by considering the instance type and size, minimizing data transfer costs, leveraging spot instances, and monitoring usage, organizations can optimize costs when using NAT instances in AWS. For more information, you can refere following link - ## **Conclusion** Optimizing AWS data transfer costs through architecture optimization and caching strategies can be achieved using various techniques such as CloudFront with ALB, CloudFront with S3, and S3 VPC Endpoints. These techniques can help reduce AWS data transfer costs by caching frequently accessed content and reducing the amount of data transferred over the internet. By implementing CloudFront with ALB, traffic can be directed to the nearest edge location, reducing latency and the need for data transfer over long distances. Additionally, CloudFront with S3 can provide a highly available and scalable solution for hosting static content, reducing S3 data transfer costs by caching content at edge locations. Furthermore, S3 VPC Endpoints provide a secure and cost-effective way to access S3 resources within a VPC, reducing data transfer costs by keeping traffic within the AWS network. Overall, implementing these optimization and caching strategies can help organizations optimize their AWS infrastructure and reduce data transfer costs, while improving performance and reliability. Optimize your AWS Data Transfer Costs and achieve enhanced cloud cost savings with Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 13 13 Table of Contents As engineering teams increasingly rely on cloud services to support their projects, managing cloud costs becomes a crucial aspect of ## **I.****The Importance of Cloud Cost Optimization** In today's engineering landscape, AWS cloud services are indispensable. However, cloud costs can quickly spiral out of control without proper management. Effective ### **Leveraging Automation and Scripting for Cost Reduction** Automation and scripting techniques provide engineering teams with the means to reduce manual intervention, improve operational efficiency, and achieve significant cost savings by optimizing resource allocation and utilization. ## **II. Understanding Cloud Cost Optimization** ### **Cloud Cost Management: An Overview** Cloud cost management involves ### **Identifying Cost Optimization Opportunities** Thoroughly analyzing cloud usage patterns and identifying cost optimization opportunities are essential steps in reducing cloud costs. This involves understanding the pricing models of cloud providers and leveraging tools for cost analysis and reporting. ### **Balancing Cost and Performance** Cost optimization should not compromise the performance and reliability of applications and services. Striking the right balance between cost reduction and meeting performance requirements is crucial for successful ## **III. Automation for Cost Optimization** ### **Infrastructure as Code (IaC)** In addition, IaC allows engineers to easily scale infrastructure up or down as needed. This means that resources can be added or removed based on demand, which can help to optimize costs and ensure that resources are being used efficiently. Another benefit of IaC is that it allows engineers to easily test and validate infrastructure changes before they are deployed. This can help to reduce the risk of errors or downtime, which can also lead to cost savings. ### **Automated Resource Provisioning and Scaling** One way to automate resource provisioning and scaling is through the use of auto-scaling groups and load balancers. Auto-scaling groups allow engineering teams to automatically adjust the number of instances in a group based on demand. This means that as demand increases, additional instances can be added to the group, and as demand decreases, instances can be removed. This helps to ensure that resources are being used efficiently, as instances are only added or removed as needed. Load balancers are another important tool for automated resource provisioning and scaling. Load balancers distribute incoming traffic across multiple instances, helping to ensure that workloads are evenly distributed and that no single instance is overloaded. By using load balancers in conjunction with auto-scaling groups, engineering teams can ensure that resources are being used efficiently and effectively, while also reducing the risk of overprovisioning and underutilization. ### **Dynamic Workload Management** Automation is a key component of workload management in infrastructure management. By automating the process of allocating resources, engineering teams can ensure that resources are being used efficiently and effectively, while also reducing costs during peak and non-peak periods. During peak periods, workloads can put a strain on infrastructure resources, leading to increased costs and reduced performance. On the other hand, during the non-peak periods, resources may be underutilized, leading to wasted resources and increased costs. By automating workload management, engineering teams can allocate resources where they are needed the most, ensuring that workloads are handled effectively and efficiently. This can help to reduce costs by ensuring that resources are being used efficiently, while also improving performance by ensuring that workloads are being handled effectively. ### **Automated Cost Tracking and Reporting** Implementing automated cost tracking and reporting mechanisms is a critical component of cost optimization in infrastructure management. By automating the process of tracking and reporting costs, engineering teams can gain visibility into resource usage and associated costs, which can facilitate informed decision-making and proactive cost optimization measures. Automated cost tracking and reporting mechanisms allow engineering teams to monitor resource usage and associated costs in real time. This means that they can quickly identify areas where costs are high and take proactive measures to optimize costs. For example, if a particular resource is being used heavily and driving up costs, engineering teams can take steps to optimize its usage or find a more cost-effective alternative. Automated cost tracking and reporting mechanisms also provide valuable insights into resource usage patterns and trends. This information can be used to identify areas where resources are being underutilized or overprovisioned, which can help to optimize costs and improve resource utilization. For example, if a particular resource is consistently underutilized, engineering teams can take steps to reduce its allocation or find a more cost-effective alternative. ## **IV. Scripting Techniques for Cost Optimization** ### **Right Sizing and Resource Optimization** Right Sizing Instances is a critical component of cost optimization in infrastructure management. It involves matching resource capacity to workload demands and eliminating underutilized or overprovisioned resources. Automated scripts can analyze usage patterns and recommend appropriate resource configurations. Automated scripts can analyze usage patterns and recommend appropriate resource configurations. This means that engineering teams can quickly identify areas where resources are being underutilized or over-provisioned and take proactive measures to optimize costs. For example, if a particular resource is consistently underutilized, automated scripts can recommend reducing its allocation or finding a more cost-effective alternative. Similarly, if a particular resource is consistently overprovisioned, automated scripts can recommend reducing its allocation or finding a more cost-effective alternative. Right Sizing instances also involve matching resource capacity to workload demands. This means that engineering teams need to ensure that resources are being allocated appropriately based on workload demands. For example, during peak periods, resources may need to be allocated more heavily to ensure that workloads are being handled effectively and efficiently. During non-peak periods, resources may need to be reduced to ensure that costs are being kept under control. Overall, right sizing is a critical component of cost optimization in infrastructure management. By matching resource capacity to workload demands and eliminating underutilized or over-provisioned resources, engineering teams can optimize costs and improve resource utilization. Automated scripts can analyze usage patterns and recommend appropriate resource configurations, helping to ensure that resources are being used efficiently and effectively. ### **Scheduled Start/Stop of Non-Critical Resources** Scheduling the start and stop times of non-critical resources such as development and test environments is a cost optimization practice that engineering teams can leverage through scripting. This practice ensures that resources are only active when needed, significantly reducing costs. Development and test environments are typically used for short periods of time and are not critical to the operation of the production environment. By scheduling the start and stop times of these environments, engineering teams can ensure that resources are only active when needed, reducing costs associated with idle resources. Scripting can be used to automate the process of starting and stopping non-critical resources. For example, a script can be created to start a development environment at the beginning of the workday and stop it at the end of the day. Similarly, a script can be created to start a test environment when a new build is available and stop it once testing is complete. By leveraging scripting to schedule the start and stop times of non-critical resources, engineering teams can significantly reduce costs associated with idle resources. This practice ensures that resources are only active when needed, reducing costs and improving resource utilization. Overall, scheduling the start and stop times of non-critical resources such as development and test environments is a cost optimization practice that engineering teams can leverage through scripting. By automating the process of starting and stopping resources, engineering teams can significantly reduce costs associated with idle resources, improving resource utilization and optimizing costs. ### **Auto-scaling and Load Balancing** Implementing auto-scaling and load balancing scripts is a cost optimization practice that enables dynamic resource allocation based on real-time demand. Scaling resources up or down as needed optimizes cost efficiency without compromising performance. Auto-scaling scripts allow engineering teams to automatically adjust the number of instances in a group based on demand. This means that as demand increases, additional instances can be added to the group, and as demand decreases, instances can be removed. This helps to ensure that resources are being used efficiently, as instances are only added or removed as needed. Load balancing scripts distribute incoming traffic across multiple instances, helping to ensure that workloads are evenly distributed and that no single instance is overloaded. By using load balancing scripts in conjunction with auto-scaling scripts, engineering teams can ensure that resources are being used efficiently and effectively, while also reducing the risk of overprovisioning and underutilization. Implementing auto-scaling and load balancing scripts enables dynamic resource allocation based on real-time demand. This means that resources are allocated based on the actual demand, ensuring that resources are being used efficiently and effectively. This helps to optimize cost efficiency without compromising performance, as resources are only allocated as needed. Overall, implementing load balancing scripts and ### **Usage Monitoring and Cost Predictions** Scripting usage monitoring and cost prediction mechanisms is a cost optimization practice that enables engineering teams to gain insights into resource consumption trends. This information allows proactive cost optimization measures and helps in forecasting future expenses. Usage monitoring scripts can be used to track resource consumption patterns in real time. This means that engineering teams can quickly identify areas where resources are being overutilized or underutilized and take proactive measures to optimize costs. For example, if a particular resource is consistently overutilized, usage monitoring scripts can recommend increasing its allocation or finding a more cost-effective alternative. Similarly, if a particular resource is consistently underutilized, usage monitoring scripts can recommend reducing its allocation or finding a more cost-effective alternative. Cost prediction scripts can be used to forecast future expenses based on historical usage patterns. This means that engineering teams can anticipate future costs and take proactive measures to optimize costs. For example, if cost prediction scripts indicate that costs are likely to increase in the future, engineering teams can take proactive measures to optimize costs and reduce expenses. By scripting usage monitoring and cost prediction mechanisms, engineering teams can gain insights into resource consumption trends. This information allows proactive cost optimization measures and helps in forecasting future expenses. This helps to ensure that infrastructure costs are kept under control, while also ensuring that resources are being used efficiently and effectively. Overall, scripting usage monitoring and cost prediction mechanisms is a cost optimization practice that enables engineering teams to gain insights into resource consumption trends. By tracking resource consumption patterns in real time and forecasting future expenses, engineering teams can take proactive measures to optimize costs and improve resource utilization. This helps to ensure that infrastructure costs are kept under control, while also ensuring that resources are being used efficiently and effectively. ## **V. Case Studies: Real-World Examples of Successful Cost Optimization** ### **Case Study 1: Right Sizing Instances in a Data-Intensive Application** Netflix used right sizing instances in a data-intensive application. Netflix is a streaming service that relies heavily on data processing and storage infrastructure to deliver content to its users. Netflix's engineering team implemented a right sizing strategy to optimize costs and improve resource utilization. They began by analyzing usage patterns and identifying instances that were consistently underutilized or overprovisioned. They then used automated scripts to adjust the resource allocation of these instances based on demand. The engineering team also implemented auto-scaling and load balancing scripts to dynamically allocate resources based on real-time demand. This helped to ensure that resources were being used efficiently and effectively, while also reducing the risk of overprovisioning and underutilization. As a result of these efforts, Netflix was able to significantly reduce costs associated with its data processing and storage infrastructure. They were also able to improve resource utilization, ensuring that resources were being used efficiently and effectively. Netflix's engineering team also developed a tool called "Scryer" to help with right sizing instances. Scryer is a machine learning-based tool that analyzes usage patterns and recommends appropriate resource configurations. This tool has helped Netflix to further optimize costs and improve resource utilization. Overall, Netflix's implementation of a right sizing strategy in their data-intensive application demonstrates the effectiveness of this approach. By analyzing usage patterns and implementing automated scripts to adjust resource allocation based on demand, engineering teams can optimize costs and improve resource utilization. This helps to ensure that infrastructure costs are kept under control, while also ensuring that resources are being used efficiently and effectively. ### **Case Study 2: Implementing Usage Monitoring and Cost Predictions** Pinterest used usage monitoring and cost predictions. Pinterest is a social media platform that allows users to discover and save ideas for various projects and interests. Pinterest's engineering team implemented usage monitoring and cost prediction mechanisms to gain insights into resource consumption trends. They used AWS CloudWatch to monitor resource usage in real-time and identify areas where resources were being over utilized or underutilized. The engineering team also used AWS Cost Explorer, an AWS cost optimization tool to forecast future expenses based on historical usage patterns. This helped them to anticipate future costs and take proactive measures to optimize costs. As a result of these efforts, Pinterest was able to significantly reduce costs associated with their infrastructure. They were also able to improve resource utilization, ensuring that resources were being used efficiently and effectively. Pinterest's engineering team also developed a tool called "Pinball" to help with usage monitoring and cost predictions. Pinball is a workflow management system that allows engineering teams to define and execute workflows as code. It integrates with AWS CloudWatch and Cost Explorer to provide real-time usage monitoring and cost predictions. ### **Case Study 3: Utilizing Auto-scaling Scripts for Bursty Workloads** Airbnb used auto-scaling scripts. Airbnb is a popular online marketplace for short-term lodging and vacation rentals. Airbnb's engineering team implemented auto-scaling scripts to dynamically allocate resources based on real-time demand. They used Amazon Web Services (AWS) auto-scaling groups to automatically adjust the number of instances in a group based on demand. The engineering team also implemented load balancing scripts to distribute incoming traffic across multiple instances. This helped to ensure that workloads were evenly distributed and that no single instance was overloaded. As a result of these efforts, Airbnb was able to significantly improve resource utilization and reduce costs associated with idle resources. They were also able to improve the reliability and performance of their platform, ensuring that users had a seamless experience. Airbnb's engineering team also developed a tool called "Airflow" to help with auto-scaling and load balancing. Airflow is a platform for programmatically authoring, scheduling, and monitoring workflows. It allows engineering teams to define workflows as code and execute them on a variety of platforms, including Amazon Web Services (AWS). Airbnb's implementation of auto-scaling and load balancing scripts demonstrates the effectiveness of this approach. By dynamically allocating resources based on real-time demand and distributing workloads across multiple instances, engineering teams can optimize costs and improve resource utilization. This helps to ensure that infrastructure costs are kept under control, while also ensuring that resources are being used efficiently and effectively. ## **Conclusion** Implementing automation and scripting techniques empowers engineering teams to reduce cloud costs significantly. By leveraging infrastructure-as-code, automation for resource provisioning and scaling, and scripting for optimization, engineering teams can achieve cost efficiency while maintaining performance and reliability. By adopting best practices, collaborating across teams, and continuously optimizing, organizations can achieve sustainable cost optimization and Remember, cost optimization is an ongoing journey that requires regular monitoring, analysis, and adaptation to changing business needs and technological advancements. By embracing automation and scripting, engineering teams can unlock the full potential of the cloud while minimizing expenses and maximizing cost efficiency. _To further simplify your cloud cost optimization journey, consider partnering with CloudKeeper. With CloudKeeper's team of AWS-certified experts by your side, you can confidently offload your AWS cost optimization efforts while saving up to 25% instantly and guaranteed on the entire AWS bill._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Generative AI Explained: Concepts, Tools & Important Use Cases A clear, practical guide to Generative AI covering core concepts, future trends, leading tools, and real-world industry applications. By Team CloudKeeper 20 Nov, 2025 Automate Beyond Limits with n8n: Your Open-Source Automation Powerhouse This blog will help you gain a working understanding of automating with n8n through a practical example and a comparison with Make and Zapier. By Pratik Singh 04 Nov, 2025 5 Common Mistakes to Avoid in AWS Auto Scaling Groups AWS Auto Scaling Groups (ASG) adjust EC2 capacity automatically, maintaining your infrastructure effectively. Learn here the 5 common mistakes you should avoid. By Rachana Kumari, Aditya Sinha 31 Aug, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents Serverless applications help businesses save the total cost of ownership (TCO) by effectively shifting operational responsibilities such as managing servers to a cloud provider. Since AWS Lambda is often the compute layer in the AWS serverless architecture workloads, it comprises a significant portion of the overall cost. Hence, understanding AWS Lambda Cost and methods to optimize your serverless applications can bring home the bacon. ## **Introduction to AWS Lambda pricing** Lambda's pricing is determined by three factors: * The overall quantity of requests made. * The total length of the invocations. * The quantity of memory allocated. Optimizing Lambda functions involves optimizing each of these components in order to reduce overall monthly expenses. This pricing structure becomes relevant once a user has exceeded the Lambda services that are offered for free by AWS. ## **Performance efficiency** Lambda pricing is largely determined by the overall duration of each invocation, which means that longer running functions will incur higher costs and increase application latency. Therefore, it is crucial to optimize your code for efficiency and adhere to Lambda's recommended guidelines to minimize these issues. In order to improve the efficiency of code, it is important to optimize it at a higher level. * One way to speed up the download and unpacking of deployment packages is to minimize their size by only including the necessary runtime components. * Simplifying the dependencies in your code can also help to increase loading speed, especially if you use lightweight frameworks. * For AWS Lambda’s performance optimization, try initializing SDK clients and database connections outside of the function handler and caching static assets locally in the /tmp directory. This approach can reduce the need to open new connections and resources with each invocation. * It is essential to follow standard coding performance best practices for your chosen language and runtime to ensure maximum efficiency. * To visualize your application's components and identify potential performance issues, consider using AWS X-Ray with Lambda. You can enable X-Ray active tracing on both new and existing functions by modifying the function configuration using the AWS CLI, for instance. To trace all AWS SDK calls within Lambda functions, the AWS X-Ray SDK can be utilized, which aids in detecting any performance bottlenecks in the application. Additionally, the X-Ray SDK for Python can capture data for various libraries, including requests, sqlite3, and httplib, as exemplified in the following illustration: While building applications in an AWS serverless architecture, it is important to utilize both, ## **Using AWS Graviton2** Lambda functions, which are powered by Arm-based AWS Graviton2 processors, were made available to the public in September 2021. These Graviton2 functions are specifically designed to deliver better AWS Lambda performance optimization (up to 19%) at a lower cost (up to 20%) compared to the x86 processors. By using Arm, you could also potentially reduce the function duration due to the improved CPU performance, leading to further cost reductions. It is possible to configure both new and existing functions to target the AWS Graviton2 processor, and doing so won't affect how the functions are invoked or integrated with services, applications, and tools. While some functions may only require a configuration change to take advantage of the Graviton2 price/performance benefits, others may need to be repackaged to use Arm-specific dependencies. To ensure a successful transition, it is recommended to test your workloads before making any changes. For this purpose, you can use the Lambda Power Tuning tool to compare the performance of your code against x86. This tool allows you to view and compare two results on the same chart. ## **Provisioned concurrency** Provisioned concurrency enables customers to mitigate Lambda function cold starts and burst throttling by providing execution environments that are always ready to be invoked. The consistent volume of traffic here, can bring down AWS Lamda’s costs. The pricing model of provisioned concurrency comprises price components for total requests, total duration, and memory configuration, along with the cost of each provisioned concurrency environment based on its memory configuration. Fully utilizing the execution environment of provisioned concurrency can result in up to a 16% reduction in duration cost compared to on-demand pricing. This is because the combined cost of invocation and execution environment is lower than the regular on-demand pricing. Even if the execution environment is not fully utilized, provisioned concurrency can still offer a lower total price per invocation. For instance, it becomes cheaper than on-demand pricing once it is consumed for more than 60% of the available time, and the savings increase with capacity usage. To establish a Lambda function's baseline invocation rate, it's advisable to examine the average hourly metrics for concurrent executions during the preceding 24-hour period. This approach enables you to identify a stable baseline that accounts for the utilization of multiple execution environments over the course of the day. ## **Compute savings plans** These plans cover various services such as Amazon EC2, AWS Fargate, and Lambda, with the latter being eligible for up to 17% discounted rates for usage that involves duration and provisioned concurrency, provided that a 1- or 3-year term is agreed upon. Savings Plans can be implemented without requiring any changes to function code or configuration, making it a simple way to save money on Lambda-based workloads. However, it is important to analyze previous usage patterns to identify any variations before deciding to use a savings plan. ## **Event filtering** One of the widely used serverless architecture patterns involves configuring Lambda to receive events from a stream or queue, such as Amazon SQS or Amazon Kinesis Data Streams. To accomplish this, an event source mapping is employed to specify how the Lambda service processes incoming messages or records from the event source. At times, it may not be necessary to handle all messages present in a queue or stream, especially if the information contained within is irrelevant. Consider an instance where data from IoT vehicles is transmitted to a Kinesis Stream and the objective is to only process events where the tire pressure is below 32. In such a case, the Lambda code could resemble the following example. The current method of invoking and executing Lambda functions can be inefficient because it incurs costs for both invocations and execution time, even when filtering is the only business value. However, Lambda now offers a solution to this problem. With the new feature, you can filter messages before the invocation, making your code more straightforward and cost-effective. This way, you will only be charged for Lambda when the event matches the filter criteria and triggers an invocation. To implement filtering, simply specify the filter criteria when setting up the event source mapping for Kinesis Streams, Amazon DynamoDB Streams, or SQS. For instance, you can use the following AWS CLI command to set up filtering. Lambda will be triggered only if the tyre_pressure in messages from the Kinesis Stream is less than 32 after the filter is applied. This could be a sign of a vehicle issue that needs to be addressed. ## **Avoid idle wait time** The duration of a Lambda function is a factor in calculating billing. If a function's code includes a blocking call, the time it spends waiting for a response is included in the billing. This idle wait time can become significant when Lambda functions are linked together or when a function acts as an orchestrator for other functions. This can add management overhead for customers with workflows, such as batch operations or order delivery systems. Additionally, it may be impossible to complete all workflow logic and error handling within the maximum Lambda timeout of 15 minutes. To address these issues, it's advisable to redesign the solution to use AWS Step Functions as a workflow orchestrator instead of handling the logic in the function code. With a standard workflow, you are charged for each state transition in the workflow, rather than the total duration of the workflow. Furthermore, you can move support for retries, wait conditions, error workflows, and callbacks into the state condition, allowing your Lambda functions to focus on business logic. The following example illustrates a Step Functions state machine that divides a single Lambda function into several states. There is no charge during the wait period, and you are only billed for state transitions, hence promoting AWS Lambda optimization. ## **Direct integrations** If a Lambda function is simply acting as a pass-through to other AWS services without any custom processing, it might not be essential and an alternative direct integration option that is less expensive could be considered. An instance of this could be utilizing a Lambda function with API Gateway to retrieve data from a DynamoDB table. This could be replaced using a direct integration, removing the Lambda function: The API Gateway allows for custom response transformations, enabling clients to receive output in their desired format without requiring a separate Lambda function for the conversion. Direct integration with AWS services is also available through Step Functions, which supports a wide range of services and API actions. This eliminates the need for a proxy Lambda function in many cases, ## **Reduce logging output** Lambda automatically stores logs generated by function code through Amazon CloudWatch Logs. This feature can be valuable for gaining insights into your application's real-time behavior, but keep in mind that CloudWatch Logs incurs charges for the amount of data ingested each month. To keep AWS Lambda cost under control, it's best to limit the amount of data you output to only the necessary information. When preparing to deploy workloads into production, it's essential to review your application's logging level. In pre-production environments, debug logs can be beneficial for fine-tuning the function, while in production workloads, you may want to disable debug-level logs and use a logging library like Lambda Powertools Python Logger. By defining a minimum logging level via an environment variable, you can configure the output without modifying the function code. Structuring your log format with a defined schema can help enforce consistency and reduce the amount of text in your logs. For example, defining error codes and associated metrics can make it easier to filter logs for specific error types, reducing the risk of mistyped characters in log messages. ## **Use cost-effective storage for logs** The monthly storage fee for logs is per-GB. However, as log data gets older, its value diminishes, and you may only need to review it historically as and when needed. The pricing for CloudWatch Logs storage, however, remains the same. To solve this issue, you can define retention policies on your CloudWatch Logs log groups to automatically remove old log data. This retention policy applies to both current and future log data. Certain application logs may need to persist for several months or years to comply with regulatory requirements. In such cases, instead of keeping the logs in CloudWatch Logs, you can export them to Amazon S3. This approach will enable you to leverage lower-cost storage object classes while considering the anticipated usage patterns for the data and help you ## **Save on your AWS Lambda pricing - a wrap-up** Ensuring cost optimization is crucial when creating well-architected solutions, and this holds true for serverless architectures as well. In this blog series, we delved into some best practices to help you reduce your AWS Lambda costs. If you're currently running AWS Lambda applications in production, you'll find that some of these techniques are easier to implement than others. For instance, purchasing Savings Plans is a quick fix that doesn't require any changes to your code or architecture. However, eliminating idle wait time will require new services and modifications to your code. Before making any changes to your production environment, it's important to assess which technique is appropriate for your workload by testing it in a development environment. __ __ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents Encountering 502 errors in production environments can be both frustrating and disruptive, especially when they occur at scale. In this blog, I’ll walk you through the **systematic approach I used to diagnose, troubleshoot, and ultimately reduce these errors** to just a handful per day. This real-world case study sheds light on common misconfigurations, overlooked bottlenecks, and key best practices that can make a significant difference in stabilizing containerized applications running on AWS Fargate. ## **What Went Wrong?** I worked on a challenging case where an application running on Amazon ECS with the AWS Fargate launch type was experiencing a high volume of 502 Bad Gateway errors behind an Application Load Balancer (ALB). The service was intermittently failing, **generating 30 to 50 such errors per day** , severely impacting reliability and user experience. ## **Error Metrics Observed** 1. Since **ALB access logs** were enabled, we observed that **elb_status_code** was **502** and **target_status_code** was **“-”** , indicating the request wasn’t reaching the target. 2. The **request_processing_time** showed values for some requests, while **response_processing_time** was **-1** , meaning the **target was closing the connection before a response was sent.** ## **Digging Into the Root Cause** Upon deeper investigation, we identified several contributing factors: **1. Task CPU Configuration:** Each task was allocated only 0.256 vCPU, and CPU utilization consistently spiked above 90%, triggering frequent scaling events. **2. Target Tracking Policy:** Scaling was configured based on both CPU utilization at 60% and memory utilization at 60%. **3. No Slow Start Duration:** There was no slow start configuration on the ALB target group, which meant new targets started receiving traffic immediately upon registration, even before being fully ready. **4. High Request Load:** The service began throwing 502 errors when it received around 800 requests per second, despite normal traffic being only 100–120 requests per second. ## **How We Resolved It — and What We Learnt** ● **Resource Optimization** After analyzing CPU usage patterns, I recommended increasing the task size to at least 2 vCPUs, as the workload was evidently CPU-intensive. This adjustment significantly stabilized resource utilization and reduced the frequency of scaling events. ● **Scaling Policy Conflict Resolution** We discovered a conflict between the CPU and memory-based target tracking policies: 1. CPU utilization consistently exceeded 80%, triggering scale-out. 2. Memory utilization, on the other hand, remained below 35%, often triggering scale-in. This imbalance led to **premature scale-in events** , causing task deregistration and resulting in 502 errors when requests were routed to targets during the deregistration process. To resolve this, we removed the memory-based policy and retained **CPU utilization at a 60% threshold** for more accurate scaling behavior. ● **Introducing Slow Start for Stability** The absence of a slow start duration in the target group configuration allowed the load balancer to immediately route traffic to newly launched tasks, even before they had completed initialization. This contributed to the 502 errors observed during scaling events. To mitigate this, we configured a **60-second slow start period** , aligning with the typical time required for tasks to become healthy and ready to serve traffic. ● **Traffic-Based Scaling Enhancement** To further fine-tune auto-scaling and better respond to fluctuating traffic loads, we implemented a scaling policy based on **ALBRequestCountPerTarget**. This approach aligned more closely with the application’s actual request patterns and ensured a more responsive and resilient scaling mechanism. ## **Wrapping Up** To address issues like this effectively: ● **Observe application startup and shutdown behavior** to avoid premature traffic routing. ● Be cautious when **combining multiple scaling policies** , especially if your application is primarily sensitive to a single metric (CPU vs memory). ● Always consider configuring slow start durations for ALB target groups to allow your application time to warm up before handling production traffic. ● Match your scaling strategies with actual usage patterns—for example, by using **ALB request count** for scaling when appropriate. While ALB is a powerful and reliable service, troubleshooting issues behind the scenes requires a clear understanding of application behavior, resource metrics, and AWS service configurations. When those elements are aligned, stability and performance naturally follow. **Explore our other related resources on AWS Fargate, you might find them useful.** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer With extensive hands-on experience across AWS, Kubernetes, Docker, and Python, Romu has a strong foundation in cloud infrastructure, automation, and container orchestration. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * * * * * * I am looking for blogs on Automation Cloud Cost Management AWS EDP AWS Services Cloud Cost Analytics Cloud Cost Optimization DevOps FinOps Strategy RI Management Kubernetes The Power of Automation in AWS Reserved Instance Management Discover how automation can revolutionize your AWS Reserved Instance Management, optimizing costs and streamlining operations for maximum efficiency and savings. By Team CloudKeeper 23 Apr, 2024 AWS Bans Reselling of RIs: Are your Cloud Savings Affected? AWS has announced an RI resale ban on Discounted Reserved Instances on AWS Marketplace from Jan 2024. Learn more about this and ensure your cloud savings are not impacted. By Team CloudKeeper 29 Dec, 2023 How to achieve 100% AWS Reserved Instances Coverage? Understand the importance of AWS Reserved Coverage in cloud cost optimization, the best practices to follow, the challenges in achieving 100% AWS RI coverage, and how CloudKeeper Auto could help. By Team CloudKeeper 24 Nov, 2023 AWS Reserved Instances Buying Guide: Common Pitfalls and Essential Considerations Your strategy guide to making informed AWS Reserved Instance (RI) purchases. Know the common mistakes and prioritize essential considerations for maximizing cost-efficiency. By Sushil Chandra 04 Oct, 2023 How to optimize AWS EC2 instances and save costs by migrating to an ARM processor? Learn how to optimize AWS EC2 instances by migrating to an ARM processor for peak efficiency and cost savings. A step-by-step guide to migrate your infrastructure from AMD to ARM processor. By Ratan Karan Srivastava 18 Aug, 2023 How to save money on AWS using EC2 Auto Scaling Groups Features? Discover strategies to effectively save money using EC2 Auto Scaling Groups. Explore strategies to optimize EC2 expenses and achieve significant savings while maintaining performance and scalability. By Team CloudKeeper 11 Aug, 2023 AWS Cost Optimization with Reserved Instances Learn how to effectively use Reserved Instances to achieve AWS cost savings. Explore the benefits & limitations of Convertible RIs and its usage in different scenarios. By Meghna Rawat 28 Jul, 2023 AWS EC2 Cost Optimization: Right-Sizing and Instance Selection Tips Discover how right-sizing and instance selection can be an effective AWS cloud cost-reduction strategy for your system. By Ajay Jha 21 Jul, 2023 AWS Savings Plans Vs. Reserved Instances: When To Use Each? Get to know the essentials of AWS Savings Plans and Reserved Instances and learn when to use each of them to achieve a cost-optimized AWS EC2 infrastructure. By Aditya Mishra 04 Jul, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Right-sizing is a process in cloud infrastructure management, which involves optimizing the resources allocated to a system, service, or application to ensure that it is using just the right amount of resources it needs, without wasting any resources or being under-provisioned. In the context of AWS EC2 instances, right-sizing refers to optimizing the amount of resources allocated to instances, such as CPU, memory, and storage, to ensure that they provide cloud cost savings, while meeting the requirements of the workload running on them. This can involve scaling up or down the instance size, selecting the right instance family, leveraging autoscaling, and optimizing storage options. By right-sizing your infrastructure, you can reduce your costs and improve your system's performance and reliability. As a DevOps team, one of your responsibilities is to implement cloud infrastructure management while improving performance and optimizing costs. One way to do this is by right-sizing your EC2 instances. In this blog, we'll explore some strategies for doing this effectively. **Analyze Your Workloads:** The first step in right-sizing your EC2 instances is to analyze your workloads. Identify which instances are over-provisioned or underutilized, and determine the optimal resource requirements for each workload. You can use AWS CloudWatch to monitor your instances and collect performance data to help with this analysis. **Use Instance Families:** AWS offers different instance families, each optimized for specific use cases. For example, compute-optimized instances are designed for CPU-intensive workloads, while memory-optimized instances are optimized for memory-intensive workloads. By **Autoscaling:** Autoscaling allows you to automatically adjust the number of instances based on changes in demand. **Spot Instances:** Spot instances are spare EC2 instances that AWS makes available at a lower price than on-demand instances. By using spot instances, you can save money on your EC2 costs. However, spot instances are not always available, and their availability can fluctuate based on demand. This must be taken into account in cloud infrastructure management. **Reserved Instances:** EC2 Reserved instances are a way to save money on your EC2 costs by committing to a certain usage level over a specified period. By reserving capacity ahead of time, you can save up to 75% compared to on-demand pricing. **Elastic Block Store (EBS) Optimized Instances:** EBS-optimized instances are optimized for use with Amazon EBS, which provides persistent block storage for your EC2 instances. By using EBS-optimized instances, you can improve the performance of your EBS volumes. Right-sizing your EC2 instances can help you optimize the performance and cost of your AWS infrastructure. By analyzing your workloads, using the appropriate instance families, using autoscaling, leveraging spot and reserved instances, and using EBS-optimized instances, you can ensure that your instances are using the appropriate amount of resources and help you deliver significant ## **A Smarter and Easier Way to Streamline your EC2 Architecture** The best practices mentioned above could help you improve your right sizing strategy and bring in substantial cloud cost savings. However, when businesses start scaling up, this cloud infrastructure management activity will require a lot of effort and manual dependency. This involves constant monitoring of the workloads, relying on inaccurate usage predictions, using multiple tools to analyze and provision the required resources, staying regularly updated on the pricing and commitment models of various service plans and more. This takes up a lot of time and cost, that could be used to enhance their core business functions. This is where RI/Savings Plan management tools come into the picture. These tools will help streamline the right sizing of EC2 resources and make sure that the organization achieves the maximum potential cost savings while provisioning EC2 volumes. The proprietary AI engine automatically buys/sells RIs on behalf of the organization, with just a simple IAM access to their AWS account. CloudKeeper Auto uses a Results Based Pricing strategy, where the solution doesn’t charge anything extra and only takes up a small percentage of the EC2 Savings as the platform fee. CloudKeeper Auto completely takes away all manual dependencies on RI management and delivers cloud cost savings with - - Automated buying/selling of RIs on the secondary marketplace - Guaranteed buyback of RI reservations made through the platform - Risk-free coverage with no commitments and no billing transfer As a conclusion, businesses must ensure to follow the best practices in right sizing the EC2 resources, which will help them optimize their cloud infrastructure management strategy and bring in cost savings. RI Management Platforms will be highly beneficial for these organizations, which can manage their EC2 infrastructure on their behalf and bring in cloud cost savings, while they focus on their core business functions. _Want to know more about how CloudKeeper Auto could help you make the most out of your EC2 Reservations?_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents As cloud adoption continues to grow, managing cloud costs has become a critical aspect of financial operations (FinOps) for businesses. One way to effectively reduce cloud costs is through automation. Automation tools can help businesses continuously monitor their cloud usage, identify cost optimization opportunities, and streamline their workflows. In this blog post, we will discuss the ## **Continuous Monitoring and Optimization** Cloud services offer many benefits for businesses, including scalability, flexibility, and cost-effectiveness. However, cloud costs can quickly add up, if left unchecked. This is why By continuously monitoring cloud usage, businesses can identify areas to reduce cloud costs, like over-provisioned resources, underutilized instances, or inefficient storage solutions. Continuous optimization can help businesses maximize their cloud investments by ensuring that resources are allocated appropriately and effectively. Here are some FinOps best practices for implementing continuous monitoring and optimization for AWS cloud cost management: 1. **Define a Cloud Cost Management Strategy** A well-defined cloud cost management strategy is essential for effective monitoring and optimization. This strategy should define your cloud usage policies, governance, and cost optimization goals. It should also identify key performance indicators (KPIs) for monitoring cloud costs and provide a framework for implementing continuous monitoring and optimization practices. 2. **Establish a Cost Monitoring and Reporting System** To effectively monitor cloud costs, businesses need a cost monitoring and reporting system in place. This system should provide visibility into your cloud usage, costs, and resource utilization. It should also enable you to track your KPIs, identify trends, and make informed decisions about resource allocation. 3. **Implement Cloud Cost Optimization Techniques** Cloud cost optimization techniques can help businesses reduce cloud costs while maximizing their cloud investments. These techniques include rightsizing resources, using spot instances, implementing auto-scaling, and using reserved instances. Continuous optimization can help businesses ensure that these techniques are implemented effectively and consistently. ## **Tagging and Cost Allocation** In the world of cloud computing, effective cost allocation and chargeback are critical in cloud FinOps to accurately track and manage their cloud spending. This is where tagging and cost allocation comes into play. Tagging is the process of assigning metadata to cloud resources, such as instances, volumes, and snapshots. This metadata can include information about the resource's purpose, owner, and cost center. By tagging resources, businesses can more Cost allocation, on the other hand, is the process of attributing costs to specific business units or cost centers. This is typically done to enable chargeback, where businesses charge internal customers or departments for their usage of cloud resources. Effective cost allocation ensures that cloud costs are allocated fairly and accurately and can help businesses identify areas to reduce cloud costs. Here are some FinOps best practices for tagging and cost allocation for effective cloud cost management 1. **Define a Tagging Strategy** To effectively tag resources, businesses need a well-defined tagging strategy in place. This strategy should define the tags to be used, the metadata to be included in each tag, and the processes for tagging resources. It should also establish governance around tagging to ensure consistency and accuracy. 2. **Implement Automated Tagging** Automated tagging can help businesses streamline the tagging process and ensure that resources are consistently and accurately tagged. Automation tools can automatically assign tags to resources based on pre-defined rules and policies, reducing the risk of human error and ensuring that all resources are properly tagged. 3. **Use Tag-Based Cost Allocation** Tag-based cost allocation enables businesses to allocate costs based on the tags assigned to each resource. This allows for more granular cost allocation and can help cloud FinOps practitioners identify areas to reduce cloud costs. Tag-based cost allocation can be done manually or through automation tools that use tags to allocate costs automatically. 4. **Implement Chargeback** Chargeback enables businesses to charge internal customers or departments for their usage of cloud resources. To implement chargeback, businesses need a well-defined cost allocation strategy and the ability to track usage and costs by department or cost center. Chargeback can be done manually or through automation tools that provide usage and cost reports by department or cost center. ## **Alerts and Notifications** Businesses need to manage their cloud spending carefully to ensure they are not overspending on cloud resources. Using Automation Tools is one of the most helpful FinOps best practices that can help provide alerts and notifications when cloud spending exceeds a certain threshold. Here are some ways automation tools can provide alerts and notifications, especially for AWS cloud cost management: 1. **Threshold-based Alerts** Automation tools can monitor cloud usage and spending in real-time, and send alerts when spending exceeds a pre-defined threshold. For example, businesses can set a threshold for monthly spending on a particular service, and receive an alert when spending exceeds that threshold. This allows businesses to quickly identify and address any unexpected increases in spending before they become a problem. 2. **Usage-based Alerts** In addition to threshold-based alerts, automation tools can also provide alerts based on usage patterns. For example, businesses can set alerts for when usage of a particular service spikes unexpectedly or when usage of a service drops below a certain level. These alerts can help businesses identify opportunities to reduce cloud costs by adjusting their usage patterns. 3. **Cost Optimization Alerts** Automation tools can also provide alerts and notifications for cost optimization opportunities. For example, businesses can receive alerts when they are overprovisioning resources or when they can save money by using a different pricing model. These alerts can help businesses identify areas where they can optimize their cloud spending and reduce costs. ( on how to choose the right AWS Service for your business) 4. **Real-Time Notifications** Automation tools can also provide real-time notifications for critical events, such as instances being stopped or terminated, or when spending on a particular service spike suddenly. These real-time notifications enable businesses to quickly respond to any issues and prevent them from causing further problems. ## **Workflow Automation** Workflow automation can help streamline AWS cloud cost management and cloud FinOps. Automation tools can automate many of the tasks involved in cloud spend management, including identifying cost optimization opportunities and allocating resources to the right cost centers or business units. Here are some ways automation tools can be used for workflow automation in cloud cost management and cost optimization: 1. **Automated Cost Allocation** One of the challenges of cloud cost management is accurately allocating costs to the right cost centers or business units. Automation tools can automate this process by tagging resources with the appropriate cost center or business unit. This ensures that costs are allocated accurately, enabling businesses to track their cloud spending more effectively and make better decisions about where to optimize. 2. **Automated Budget Management** Automation tools can automate budget management by providing real-time updates on cloud spending and alerts when spending exceeds predefined thresholds. This helps businesses stay within their budget and avoid overspending on cloud resources. 3. **Automated Rightsizing** Automation tools can analyze cloud usage data and identify opportunities to rightsize resources. Rightsizing involves optimizing resources to ensure they are the right size for the workload they are running. By automating rightsizing, businesses can optimize their cloud resources and reduce cloud costs. 4. **Automated Resource Provisioning and Deprovisioning** Automation tools can automate the provisioning and de-provisioning of cloud resources based on workload demand. This ensures that resources are only provisioned when they are needed, and are de-provisioned when they are no longer required. This enforces one of the basic concepts of FinOps best practices, allowing businesses to optimize their cloud spending by only paying for resources that they are actively using. ( about Autoscaling best practices) 5. **Automated Purchasing** Automation tools can automate the purchasing of cloud resources based on predefined policies. For example, businesses can set policies to purchase reserved instances when utilization rates exceed a certain threshold. This helps businesses optimize their cloud spending by taking advantage of cost-saving opportunities. _CloudKeeper helps you implement Workflow Automation using_ _, an AI-powered automated RI Management platform. The solution automatically buys EC2 resources on-demand, at 3-year Reserved Instance pricing, the highest discount tier for reservations. Notably, the solution does not require any type of volume or term commitment from the user._ ## **Collaboration** Collaboration between IT, finance, and business teams is critical to successful cloud cost management. Here are some ways effective collaboration between IT, finance, and business teams can help with cloud FinOps: 1. **Aligning Cloud Usage with Business Goals** Effective collaboration between IT, finance, and business teams can ensure that cloud usage is aligned with business goals. IT teams can work with business teams to understand their requirements, and finance teams can provide insights into the costs associated with those requirements. By collaborating effectively, businesses can ensure that they are using the cloud infrastructure in the most cost-effective way possible. 2. **Establishing Clear Governance Policies** Effective collaboration between IT, finance, and business teams is essential for establishing clear governance policies. This involves defining roles and responsibilities, establishing policies for cloud usage, and ensuring that everyone is on the same page. This can help businesses reduce cloud costs by ensuring that resources are used efficiently and effectively. 3. **Sharing Insights and Data** Effective collaboration between IT, finance, and business teams can help businesses gain insights into their cloud usage and identify areas for optimization. IT teams can provide data on usage patterns and costs, while finance teams can provide insights into budgeting and cost allocation. By sharing insights and data, businesses can identify areas for optimization and 4. **Conducting Regular Reviews** Effective collaboration between IT, finance, and business teams is critical for conducting regular reviews of cloud usage and costs. By working together, teams can identify areas for optimization and make adjustments as needed. This can help businesses avoid unnecessary costs and ensure that they are getting the most value from their cloud FinOps initiatives. 5. **Establishing Effective Communication Channels** Effective collaboration between IT, finance, and business teams requires effective communication channels. This involves establishing regular meetings, ensuring that everyone is kept up-to-date on changes in cloud usage and costs, and providing feedback on performance. By establishing effective communication channels, businesses can ensure that everyone is on the same page and working towards the same cloud cost management goals. ## **Conclusion** Automation plays a critical role in AWS cloud cost management. By leveraging automation tools, businesses can continuously monitor their cloud usage, identify cost optimization opportunities, and streamline their workflows. Tagging and cost allocation, alerts and notifications, workflow automation, and collaboration are all important FinOps best practices for cloud cost management. By following these best practices, businesses can effectively reduce cloud costs, improve financial transparency, and optimize their cloud FinOps strategies. At To know how, Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Generative AI Explained: Concepts, Tools & Important Use Cases A clear, practical guide to Generative AI covering core concepts, future trends, leading tools, and real-world industry applications. By Team CloudKeeper 20 Nov, 2025 Automate Beyond Limits with n8n: Your Open-Source Automation Powerhouse This blog will help you gain a working understanding of automating with n8n through a practical example and a comparison with Make and Zapier. By Pratik Singh 04 Nov, 2025 5 Common Mistakes to Avoid in AWS Auto Scaling Groups AWS Auto Scaling Groups (ASG) adjust EC2 capacity automatically, maintaining your infrastructure effectively. Learn here the 5 common mistakes you should avoid. By Rachana Kumari, Aditya Sinha 31 Aug, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents **Docker orchestration** is the process of managing and scaling multiple Docker containers across a cluster of machines. It enables you to automate the deployment, scaling, and management of containerized applications. Docker orchestration tools like Kubernetes, Docker Swarm, and Apache Mesos, provide a framework for managing containerized applications. These tools enable you to deploy, scale, manage, and monitor Docker containers, applications, and services across a cluster of machines or servers. ## **Companies that saved cloud costs by migrating to Docker orchestration:** Docker orchestration has become increasingly popular among companies that want to improve their application deployment and management processes while also reducing costs. Docker orchestration is a set of tools and services that automates the deployment, scaling, and management of containerized applications. It includes Docker Swarm, Kubernetes. In this article, we will look at some real-world examples of companies that have saved money by migrating to Docker orchestration. PayPal is a well-known company that provides online payment solutions. In 2016, PayPal moved its infrastructure to Docker containers and **** Visa is one of the world's largest financial services providers, and they migrated their entire infrastructure to Docker containers and Kubernetes orchestration. This migration enabled them to reduce deployment time from weeks to hours, improved their availability and reduced operational costs. **** MetLife is a well-known insurance company that provides life insurance, annuities, and employee benefits. In 2018, MetLife implemented Docker orchestration for its application development and deployment. This move resulted in a 30% **** Spotify is a popular music streaming service that has a massive infrastructure. In 2014, Spotify started using Docker containers and Kubernetes orchestration to manage its infrastructure. The company has reported a 75% reduction in server costs and a 90% reduction in deployment time. Spotify's move to Docker orchestration allowed the company to better manage its resources and scale its applications more efficiently. The move also allowed the company to deploy new features more quickly and improve the reliability of its service. **** Capital One is a well-known bank that offers credit cards, loans, and banking services. In 2018, Capital One migrated its application infrastructure to Docker containers and Kubernetes orchestration. This move allowed the company to save over $10 million in infrastructure costs annually. The company was also able to improve its application deployment time and reduce the number of outages. ## **The most common reasons why companies move to Docker orchestration:** **Efficient use of resources:** Docker orchestration allows you to deploy and manage multiple containers on a single machine or across multiple machines. This approach can improve resource utilization, enabling companies to **Simplified deployment:** Docker orchestration tools provide a simple and unified way to deploy and manage applications, enabling companies to save time and money on application development and deployment. **Scalability:** Docker orchestration allows you to scale up or down the number of containers based on demand. This approach helps companies save costs by ensuring that they are only using the resources they need at any given time. **High availability:** Docker orchestration tools ensure that containers are highly available and running by automatically replacing failed containers with new ones. This approach can help companies save costs by minimizing downtime and preventing lost revenue. **Improved developer productivity:** Docker orchestration tools can simplify application development, testing, and deployment, improving developer productivity and reducing the time and costs associated with application development. **Security:** Docker orchestration provides security features, such as network isolation and access controls, to ensure that applications and data are secure. This ensures that companies are not at risk of data breaches or other security threats. In summary, companies move to Docker orchestration to improve their application deployment and management processes, reduce costs, and improve the reliability and security of their applications. Docker orchestration provides benefits such as scalability, automation, high availability, resource optimization, portability, and security that help companies to achieve these goals. ## **Smarter ways to adopt Docker orchestration:** Moving to Docker orchestration can be a complex process, and there are many factors to consider. It's important to plan carefully and seek expert advice to ensure a successful transition. **Containerize your application:** To move to Docker orchestration, your application needs to be containerized. You can use Dockerfile to create a container image that includes your application and its dependencies. **Choose a Docker orchestration tool:** There are several Docker orchestration tools available, including Kubernetes, Docker Swarm, and Apache Mesos. Choose a tool that best suits your organization's needs and requirements. **Setup your Docker environment:** Setup your Docker environment by installing Docker on your servers or machines, creating a Docker registry to store your container images, and configuring Docker networking. **Deploy and manage containers:** Use your chosen Docker orchestration tool to **Monitor and troubleshoot:** Monitor your Docker environment and troubleshoot any issues that arise. Use logging and monitoring tools to keep track of your application's performance, identify potential bottlenecks, and optimize your Docker environment for maximum efficiency. ## **Conclusion:** In conclusion, Docker orchestration is a powerful tool for managing and scaling containerized applications in a distributed environment. Its benefits include scalability, automation, high availability, resource optimization, portability, and security. Companies like PayPal, Groupon, MetLife, Spotify, and Capital One have saved money by migrating to Docker orchestration. These companies were able to better manage their resources, scale their applications more efficiently, and reduce their infrastructure costs. __ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents As AWS Elasticsearch grows in popularity, many companies are starting to realize that running an Elasticsearch cluster can be costly. The service offers a lot of features and capabilities, but those benefits come at a price. Fortunately, there are a number of ways to reduce AWS Elasticsearch cost. In this blog, we'll discuss several optimization strategies you can use to make your Elasticsearch cluster more cost-effective. ## **Right-size your cluster** One of the biggest costs associated with AWS Elasticsearch is the size of the cluster you're running. The more nodes you have in your cluster, the more you'll pay. To reduce costs, it's important to right-size your cluster. That means finding the minimum number of nodes you need to run your Elasticsearch workload effectively. You can start by looking at your current cluster utilization. AWS provides a number of metrics and dashboards to help you monitor your Elasticsearch usage, including CPU utilization, storage utilization, and query performance. You can also use tools like AWS Elasticsearch Curator to analyze your cluster data and identify areas where you can improve. Once you have a better understanding of your cluster utilization, you can start to make adjustments. For example, if you're running a small Elasticsearch workload, you may be able to get by with just one or two nodes. Conversely, if you have a large workload, you may need to add more nodes to handle the load. The goal is to find the right balance between performance and cost. ## **Use instance types wisely** AWS offers a range of instance types for Elasticsearch, each with different levels of CPU, memory, and storage. Choosing the right instance type can have a big impact on your AWS Elasticsearch costs. If you're running a workload that requires a lot of CPU, you may want to choose an instance type with more CPU cores. If you're running a workload that requires a lot of storage, you may want to choose an instance type with more storage capacity. However, it's important to keep in mind that larger instance types can be more expensive. To reduce costs, it's important to use instance types wisely. Consider using a mix of instance types in your AWS Elasticsearch cluster to optimize for performance and cost. You can also take ## **Optimize storage usage** Another major cost that affects overall AWS Elasticsearch pricing is storage cost. Elasticsearch requires a lot of storage for its indexes, which can quickly add up. To reduce costs, it's important to optimize your storage usage. One way to do this is to use Index Lifecycle Management (ILM) to manage your indexes. ILM allows you to set policies that automatically move data between different storage tiers based on age or other criteria. For example, you can configure ILM to move older data to cheaper, slower storage as it becomes less frequently accessed. You can also take advantage of Elasticsearch's data compression features to reduce your storage usage. Elasticsearch supports several compression algorithms that can be used to reduce the size of your indexes without sacrificing performance. ## **Use smaller nodes** One way to reduce costs is by using smaller nodes. AWS Elasticsearch is designed to scale horizontally, which means you can add more nodes to your cluster to handle more data. However, smaller nodes can be more cost-effective than larger ones, especially when you have a high volume of data. By using smaller nodes, you can distribute the workload across more machines, which can help reduce the load on each node and improve performance. ## **Use spot instances** Another way to ## **Optimize index settings** AWS Elasticsearch stores data in indexes and the settings of these indexes can have a significant impact on performance and cost. To optimize your index settings, you should consider factors such as the size of your data, the frequency of updates, and the type of queries you're running. For example, you can reduce the number of replicas you're storing to save on storage costs. You can also adjust the refresh interval to balance performance and cost. ## **Use shard allocation awareness** Shard allocation awareness is a feature in Elasticsearch that allows you to distribute shards across nodes based on their location in the network. By using shard allocation awareness, you can ensure that each node has a copy of the data it needs, which can improve performance and reduce the load on the network. This can also help reduce AWS Elasticsearch cost by minimizing the amount of data that needs to be transferred between nodes. ## **Use bulk API for indexing:** When you're indexing data into Elasticsearch, you can use the bulk API to index multiple documents at once. This can help reduce the number of requests you need to make, which can improve performance and reduce costs. The bulk API also allows you to specify indexing options, such as the number of replicas to create, which can help optimize your index settings. ## **Use caching wisely** Elasticsearch provides a number of caching mechanisms to improve query performance. However, caching can also consume a lot of resources, which can increase costs. To reduce costs, it's important to use caching wisely. You can start by tuning Elasticsearch's cache settings to optimize for your workload. Elasticsearch provides a number of cache settings, including the field data cache, query cache, and filter cache. By tuning these settings, you can optimize cache performance while minimizing resource usage. You can also use external caching solutions like Amazon ElastiCache to offload some of the caching workloads from your Elasticsearch cluster. ElastiCache provides in-memory caching for frequently accessed data, which can improve query performance. ## **Opt for the best Architecture which suits your use case to get more discount on AWS Elasticsearch reduce cost** ### **Single Node Architecture** A single-node Elasticsearch cluster consists of a single machine that runs all the AWS Elasticsearch services. This architecture is suitable for small projects with limited data volumes. However, as the data volume increases, a single-node Elasticsearch cluster may not be able to handle the workload, leading to performance degradation. To optimize Elasticsearch cost using a single node architecture, you can upgrade your hardware to a more powerful machine with more memory and faster CPUs. You can also configure Elasticsearch to use less memory and CPU resources to reduce costs. However, this may negatively impact performance. ### **Multi-Node Architecture** In a multi-node Elasticsearch architecture, the Elasticsearch cluster is spread across multiple machines. This architecture is suitable for projects with larger data volumes that require more processing power. By spreading the workload across multiple machines, the performance of the Elasticsearch cluster can be improved, and the cost per node can be reduced. To optimize AWS Elasticsearch cost using a multi-node architecture, you can use cheaper machines with less memory and CPU power, as the workload is spread across multiple nodes. However, it's important to ensure that each node has enough resources to handle the workload to avoid performance degradation. ### **Hot-Warm Architecture** The Hot-Warm architecture is a hybrid architecture that combines the benefits of a single-node and multi-node architecture. In this architecture, the Elasticsearch cluster is divided into two sets of nodes - Hot nodes and Warm nodes. Hot nodes handle the incoming data and queries, while warm nodes store the older data. This architecture is suitable for projects that have a mix of hot and warm data. By separating the workload across two sets of nodes, the performance of the Elasticsearch cluster can be optimized, and the cost per node can be reduced. To optimize Elasticsearch cost using a Hot-Warm architecture, you can use cheaper machines for the warm nodes, as they only store data and don't handle the incoming workload. This can significantly reduce the cost per node while maintaining performance. ### **Hot-Warm-Cold Architecture** The Hot-Warm-Cold architecture is an extension of the Hot-Warm architecture. In this architecture, a third set of nodes called Cold nodes are added. Cold nodes store the oldest data that is rarely accessed. By separating the workload across three sets of nodes, the performance of the Elasticsearch cluster can be optimized, and the cost per node can be further reduced. To optimize Elasticsearch cost using a Hot-Warm-Cold architecture, you can use the cheapest machines for the cold nodes, as they store the oldest and rarely accessed data. This can significantly reduce the cost per node while maintaining performance. ### **Search-As-You-Type Architecture** The Search-As-You-Type architecture is a specialized architecture that is optimized for search-as-you-type applications. In this architecture, Elasticsearch is configured to handle the incoming queries in real-time, as the user types. This architecture requires a high level of performance and responsiveness to provide a good user experience. To optimize Elasticsearch cost using a Search-As-You-Type architecture, you can use more powerful machines with faster CPUs and more memory to handle real-time queries. However, this can significantly increase the cost per node. In conclusion, AWS Elasticsearch service is popular but can be costly to run. However, there are several optimization strategies that you can use to reduce costs. Firstly, it's important to right-size your cluster to find the minimum number of nodes you need to run your Elasticsearch workload effectively. Secondly, you can choose the right instance types, use instance types wisely, and take advantage of AWS's Reserved Instances to save money on instance costs. Thirdly, optimize your storage usage, use smaller nodes, use spot instances, optimize index settings, use shard allocation awareness, use bulk API for indexing, and use caching wisely to reduce costs. By implementing these optimization strategies, you can make your Elasticsearch cluster more cost-effective while still achieving optimal performance. _With our comprehensive solution,_ _Sounds like something your business can take advantage of!_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Recently, a customer exploring _“We have recently started exploring AWS QuickSight and noticed that the Amazon QuickSight URL is publicly accessible. We would like to understand if it is possible to restrict access and make the URL private. Additionally, we want to explore the options for_ _for Amazon QuickSight users.”_ This real-world query prompted us to evaluate Amazon QuickSight’s access control mechanisms. In the process, we also encountered and addressed a critical consideration: the fact that AWS QuickSight’s home region cannot be changed once created. ## **Problem Statement** When adopting Amazon QuickSight for business intelligence, enterprises often realize that the AWS QuickSight URL is publicly accessible by default. While AWS QuickSight provides user-level permissions, many organizations require stricter controls to ensure that Amazon QuickSight is accessible **only from corporate VPN or private networks**. In parallel, enterprises want to enforce **SSO login** so that users authenticate only through their existing identity providers. During implementation, another challenge emerged: when attempting to configure a _us-west-2 (Oregon)_ , indicating that the account’s home region is fixed and cannot be changed. This creates limitations when VPCs are deployed in regions different from the AWS QuickSight home region. ### **Challenges include:** * Restricting Amazon QuickSight URL access to VPN/corporate networks. * Enforcing * Navigating the limitations of Amazon QuickSight’s fixed home region. ## **Solution Overview** To address these concerns, we evaluated three approaches: 1. **IP Range Restrictions** Configure Amazon QuickSight to allow access only from approved VPN or office IP addresses. 2. **VPC Endpoint Restrictions (PrivateLink)** Use AWS PrivateLink to enforce QuickSight access through an Interface VPC Endpoint. Any traffic outside of approved VPCs is blocked from reaching the QuickSight console. 3. **SSO Enforcement** Integrate Amazon QuickSight with After careful evaluation, we selected **VPC endpoint–based restrictions** as the preferred approach, since they provide the strongest network isolation and compliance guarantees. ## **Architecture Overview** ### **Access Restriction** * **IP Allow-listing** In _Security & Permissions → IP and VPC endpoint restrictions,_ add your corporate VPN or office egress CIDRs to ensure only traffic from those ranges can access AWS QuickSight. * **VPC Endpoint via PrivateLink** Create an Interface VPC Endpoint for: **com.amazonaws. .quicksight-website** * Update corporate DNS so that **< region>.quicksight.aws.amazon.com **resolves to the VPC endpoint. * In AWS QuickSight, add the endpoint ID under restrictions and enforce it. This ensures QuickSight is accessible only through approved VPCs, eliminating public internet exposure. ### Identity & Authentication * #### **IAM Identity Center (Recommended)** * Add AWS QuickSight as a customer-managed application. * Integrate with your enterprise IdP (e.g., Okta, Azure AD). * All logins are routed through SSO, ensuring MFA and conditional access policies are applied. * #### **SAML Federation** If Identity Center is not available or supported in the Amazon QuickSight region, configure SAML federation directly from your IdP to IAM roles that provide AWS QuickSight access. This still enforces enterprise SSO and MFA policies. ## **Region Limitations & Migration Considerations** During testing, we attempted to create a VPC connection in **us-east-1** , but AWS QuickSight redirected us to **us-west-2 (Oregon)**. This behavior highlights an important limitation: * **Amazon QuickSight home region is fixed at account creation.** * Account-level operations (VPC connections, SPICE capacity, account settings) can only be performed in the home region. * VPC connections are region-bound and must exist in the same region as AWS QuickSight’s home region. **Workarounds:** * If Amazon QuickSight is tied to **us-west-2** , either: **a)** Place data sources in that region, or **b)** Use cross-region networking (PrivateLink/peering) to connect east-coast resources. * If the long-term strategy requires AWS QuickSight in **us-east-1** , unsubscribe from Amazon QuickSight in us-west-2 and re-subscribe in us-east-1. **a)** This migration requires re-creating datasets, analyses, dashboards, and permissions. ## **Performance & Cost Considerations** ### **Performance (SPICE vs. Direct Query)** * **Direct Query** → Sends queries directly to the data source each time. * **SPICE** → In-memory cache with scheduled refreshes; faster performance, reduced load on the database. #### **Best practices:** * Use SPICE where possible for a faster user experience. * Keep refresh schedules aligned with business needs. * Reserve Direct Query for real-time requirements. ### SLA * Amazon QuickSight provides 99.9% uptime SLA for the service. * Data source availability depends on the underlying infrastructure. ### Pricing * User roles directly affect cost (Pro vs. Reader vs. Author/Admin). * Plan license types carefully to optimize spend. * Reference: ## **Results** With this solution, we achieved: * **Private URL access** – Amazon QuickSight is reachable only via VPN/corporate IP or approved VPC endpoint. * **SSO enforcement** – All users authenticate via corporate IdP, ensuring governance and MFA. * **Secure data access** – Data sources accessed via VPC connection, not exposed to the internet. * **Awareness of regional design limitations** – Clear understanding of AWS QuickSight’s home region impact. * **Optimized performance and cost** – Balanced use of SPICE, Direct Query, and user roles. This approach delivers secure, governed, and enterprise-ready Amazon QuickSight deployments, ensuring both compliance and user productivity. ## **Conclusion** Enterprises adopting Amazon QuickSight must address both network isolation and identity enforcement to ensure secure deployments. By implementing VPC endpoint restrictions and federated SSO login, we created a design that meets enterprise security, compliance, and usability requirements. If your organization is looking to secure Amazon QuickSight with private connectivity and SSO, Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Anjali Jain is a cloud enthusiast specializing in Amazon Web Services (AWS) solutions. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Managing network traffic in microservices is complex. Developers must configure communication, set up retries, handle timeouts, and enforce security policies—adding significant operational overhead. In So, how can we simplify this? A service mesh is a dedicated infrastructure layer that manages In this blog, we will explore how Istio on ## **How Service Mesh Works?** A service mesh is also known as a Programmable Network, since you can offload all your network configurations from the application code, like setting up retries, timeout handling, and establishing trust to the service mesh, and focus on the business logic. A service mesh works as a dedicated infrastructure layer sitting somewhat between the application Layer and the network Layer. The main benefit of using a service mesh is that an upgrade in the network configuration across the application would not require rebuilding each microservice and redeploying it; everything can be handled by upgrading the service mesh configuration. ### **Service Mesh under the hood** A service mesh operates by deploying distributed proxies alongside each instance of an application or service. These proxies handle all incoming and outgoing traffic, removing the need for the application to manage traffic directly. This approach centralizes traffic control within the mesh, providing greater visibility and fine-grained control over network flows. In Kubernetes, where each instance of an application/service is itself running in a container inside a pod, these proxies are implemented as another container running inside the pod as a sidecarside car container. This, this is known as a proxy container, and the whole process is called meshing a pod. This sidecar proxy is co-located and has the same lifecycle as the application instance running in the pod. ## **Why use a Service Mesh** Let’s take a closer look at why we should use a Service Mesh to control inter-service communications in our Kubernetes cluster: 1. **East-West Load Balancing:** In a Kubernetes environment, east-west load balancing is simply managing the traffic between various Kubernetes services in a Kubernetes cluster, as opposed to traditional north-south load balancing, which corresponds to managing traffic between external clients and internal services. A service mesh can help us to do that effectively and efficiently while keeping the management overhead to a minimum. 2. **Security:** In certain scenarios, the network request should be validated at each service, i.e., at both source and destination. Including this functionality at the application level can result in a huge overhead both in terms of development effort and the application performance;, hence, including a service mesh in this scenario is more effective as it provides mTLS-based inter-service communication. 3. **Observability:** As established earlier in a service mesh, traffic is flowing through the proxy container, hence we can inspect real-time and historical behavior of our traffic flow. 4. **Hybrid Environments:** In the case of a Kubernetes cluster spanning multiple cloud accounts or even cloud providers, using a service mesh makes it easier for the administrators to set up and manage the services. ## **Setting Up Istio on Amazon EKS** We'll implement Istio, an open source service mesh developed by Google in partnership with IBM and Lyft. Istio supports two data plane modes: 1. **Sidecar Mode:** Traffic flows through Envoy proxy containers deployed alongside each pod 2. **Ambient Mode:** Uses per-node L4 proxies or optional per-namespace Envoy proxies for L7 functionality This blog focuses on the sidecar mode, using Istio's BookInfo sample application as an example. **Prerequisites:** * An Amazon EKS cluster with one Node Group (minimum two nodes) * Configured kubeconfig file for cluster communication Now, let's set up Istio and deploy the BookInfo application. **Installing Istio:** Go to the _**curl -L https://istio.io/downloadIstio | sh -**_ Let’s add Istio to path: _**export PATH=$PWD/bin:$PATH**_ **Install Istio using Istioctl:** We will be using the default configuration profile (configuration profiles provide the level of customization you can add to the istio control plane based on deployment strategies and platforms). _**istioctl install --set profile=default -y**_ Add a namespace label to instruct Istio to automatically inject Envoy sidecar proxies when you deploy your application later: _**kubectl label namespace default istio-injection=enabled**_ By doing this, we have configured Istio to ingest sidecar containers to applications deployed to the default namespace. In case you want to create a designated namespace for your application, run the above command by replacing default with your namespace. Let’s deploy the application: _**kubectl apply -f samples/bookinfo/platform/kube/bookinfo.yaml**_ Istio sidecar will be deployed with every application: Now, we have the application deployed and ready. We need to make it accessible over the internet.For this, we will be using Istio Gateway and AWS Load Balancer Controller. Gateways in Istio are used to configure ingress and egress access to your application;, they are also deployed as Envoy proxies that run at the edge of the mesh, rather than as a sidecar container with your application. To deploy the Gateway, run the following command: _**kubectl apply -f samples/bookinfo/networking/bookinfo-gateway.yaml**_ Now, we have deployed the gateway, let’s deploy an Application Load Balancer to grant external access to our application. I have already installed the AWS Load Balancer Controller. You can use this You can use the **following yaml** to deploy the load balancer: ``` apiVersion: networking.k8s.io/v1 kind: Ingress metadata: name: bookinfo-ingress namespace: istio-system annotations: kubernetes.io/ingress.class: alb alb.ingress.kubernetes.io/scheme: internet-facing alb.ingress.kubernetes.io/target-type: ip alb.ingress.kubernetes.io/listen-ports: '[{"HTTP": 80}]' alb.ingress.kubernetes.io/healthcheck-path: /productpage spec: rules: - http: paths: - path: /productpage pathType: Exact backend: service: name: istio-ingressgateway port: number: 80 - path: /static pathType: Prefix backend: service: name: istio-ingressgateway port: number: 80 - path: /login pathType: Exact backend: service: name: istio-ingressgateway port: number: 80 - path: /logout pathType: Exact backend: service: name: istio-ingressgateway port: number: 80 - path: /api/v1/products pathType: Prefix backend: service: name: istio-ingressgateway port: number: 80 ``` After applying the following yaml spec, you can get the load balancer DNS using: Notice, we have installed the ingress in istio-system namespace. Navigate to **http:// /productPage** and you should see the following page: Istio provides a Kiali dashboard to provide insights about your service mesh, network topology, and various observability metrics. Let’s install it and access it using the commands below: _**kubectl apply -f samples/addons**_ _**istioctl dashboard kiali**_ This will open the Kiali dashboard, which will look like this: Let’s take a look at the traffic graph for BookInfo application in default namespace: We can filter it out on the basis of deployments and analyse our network performance and inter-service communication. ## **Conclusion** In this blog, we've explored the fundamentals of service meshes, specifically how Istio can be implemented on Amazon EKS to enhance the observability, security, and management of service-to-service communication within a Kubernetes environment. By using Istio, you can offload complex networking tasks like traffic routing, retries, timeouts, and mTLS from your application code, simplifying your microservices architecture. Through the setup of Istio in sidecar mode on Amazon EKS, we've demonstrated how to deploy and expose a microservices application while ensuring high availability, security, and real-time visibility into your network traffic. With Istio, the Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Setting up SSO with AWS VPN Client enables secure, user-based authentication using To configure this, follow the guidelines below: ## **Step-1: Generate Server Certificate and Associate Client Keys** To configure SSO with user-based authentication for AWS Client VPN, a server certificate and the associated client certificates/keys must be generated. git clone ./easyrsa init-pki ./easyrsa build-ca nopass ./easyrsa --san=DNS:server build-server-full server nopass ./easyrsa build-client-full client1.domain.tld nopass Above, you can see that I have successfully generated server and client certificates and keys. ## **Step 2: Import Certificates into AWS Certificate Manager** **Step 1:** Log in to the AWS Management Console and go to AWS Certificate Manager (ACM). **Step 2:** In the left-hand menu, click on Certificates. **Step 3:** Click the Import a certificate button. **Step 4:** On the Import Certificate page, upload the certificate files: Certificate body → Upload your server.crt file. Certificate private key → Upload your server.key file. Certificate chain → Upload your ca.crt (CA root or intermediate chain certificate). **Step 5:** (For client certificates, repeat the same steps with the client.crt, client.key, and ca.crt). **Step 6:** Click Next, review the details, and then click Import. **Step 7:** Once imported, you should see a message confirming that the certificate has been successfully issued/imported into ACM. ## **Step 3: Application (SAML 2.0) Configuration** **Step 1:** In IAM Identity Center, go to the Applications section. **Step 2:** Click Add Application → Add custom SAML 2.0 application. **Step 3:** Create two applications: * Application 1: AWS-VPN-Client * Application 2: VPN-Self-Service **Step 4:** For each application, configure the SAML settings: ACS URL / Reply URL → Will be the Client VPN endpoint SAML URL (to be configured later). Audience URI (SP Entity ID) → Use the Client VPN Entity ID. **Step 5:** Save both applications and download the metadata files (one for each application). ### **For Application 1 (****AWS-VPN-Client****):** Attribute mapping in IAM Identity Center passes user details (email, name, groups, etc.) to the SAML app, allowing the VPN to identify users and apply group-based access rules. ## **Step 4: Configure Attributes** **Step 1:** Go to IAM Identity Center → Applications. **Step 2:** Select your application (AWS-VPN-Client or VPN-Self-Service). **Step 3:** Open the Attribute mappings tab. **Step 4:** Add mappings between IAM Identity Center attributes and SAML attributes. Common mappings include: * Subject → **${user:email**} (used as the user’s unique identifier) * Name → **${user:username}** * FirstName → **${user:givenName}** * LastName → **${user:familyName}** * Groups → **${user:groups}** (used to enforce access rules with SAML authorization) **Step 5:** Click 'Save changes'. ### **For Application 2 (****VPN-Self-Service****):** ## **Step 5: Create IAM Identity Providers (SAML 2.0)** Creating an IAM Identity Provider (SAML 2.0) links your AWS account with the IAM Identity Center applications. This allows AWS services like Client VPN to trust the SAML metadata and authenticate users via SSO. **Step 1:** Log in to the AWS Management Console and open the IAM service. **Step 2:** In the left navigation pane, click on Identity providers. **Step 3:** Click the Add provider button. **Step 4:** On the Add an identity provider page: * For Provider type, select SAML. * For Provider name, enter a name (e.g., **VPN-SAML-Provider-1**). * For Metadata document, upload the first SAML 2.0 metadata file (downloaded when creating the AWS-VPN-Client application in IAM Identity Center). * Click Add provider. **Step 5:** Repeat the same process to create a second Identity Provider: * Provider name: e.g., **VPN-SAML-Provider-2**. * Metadata document: upload the second SAML 2.0 metadata file (downloaded when creating the VPN-Self-Service application). ## **Step 6: Create a Client VPN Endpoint** Creating a Client VPN Endpoint establishes the secure entry point for users to connect to your AWS VPC. It defines the client CIDR, authentication method, certificates, and acts as the gateway for remote access. **Step 1:** Log in to the AWS Management Console and open the VPC service. **Step 2:** In the left navigation pane, click on Client VPN Endpoints. **Step 3:** Click the Create Client VPN Endpoint button. **Step 4:** Fill in the required details: * **Name/Description:** Provide a name for your VPN endpoint (e.g., **My-Client-VPN**). * **Client IPv4 CIDR Range:** Enter a CIDR range for clients (must be different from your VPC CIDR, because the source and destination networks should not overlap). * **Server Certificate ARN:** Select an SSL/TLS certificate from ACM for secure communication. * **Authentication Options:** Choose **SAML-based authentication** and attach the IAM Identity Provider you created earlier. **Step 5:** Configure Connection Logging (optional, for auditing). **Step 6:** Under VPC Settings: * Select the VPC where you want to deploy the Client VPN endpoint. * Attach the Security Group (SG) that allows VPN traffic (e.g., inbound/outbound rules for necessary ports). **Step 7:** Review the settings and click on the Create Client VPN Endpoint button. ## **Step 7: Associate Target Network with Client VPN Endpoint** Associating a target network connects the Client VPN endpoint to a specific VPC subnet. This allows VPN users to access resources inside the VPC through either a public or private subnet, depending on requirements. **Step 1:** In the AWS Management Console, go to the VPC service. **Step 2:** From the left-hand menu, click on Client VPN Endpoints. **Step 3:** Select the Client VPN Endpoint you created earlier. **Step 4:** Go to the Target network associations tab. **Step 5:** Click on Associate target network. **Step 6:** Choose the following: * **VPC:** Select the same VPC where you want to enable VPN access. * **Subnet:** Choose a Public Subnet (if you want users to access the internet through the VPN). * Alternatively, you can select a Private Subnet (if you only want users to access internal resources and not the internet). **Step 7:** Click on **Associate**. ## **Step 8: Create Authorization Rule for SAML Users** Creating an authorization rule defines which users or groups from IAM Identity Center can access specific networks. This ensures only authorized SAML users are allowed to connect to your VPC resources via the VPN. **Step 1:** In the AWS Management Console, go to the VPC service. **Step 2:** From the left-hand menu, click on Client VPN Endpoints. **Step 3:** Select your Client VPN Endpoint. **Step 4:** Go to the Authorization rules tab. **Step 5:** Click on Add authorization rule. **Step 6:** Provide the following details: * **Destination network:** Enter the VPC CIDR block or the specific subnet you want users to access (**e.g., 10.0.0.0/16**). * **Grant access to:** Select Allow access to users in a specific access group. * **Access group ID:** Choose the SAML Group you created in IAM Identity Center (e.g., VPN-Users). **Step 7:** Click Add authorization rule. * For accessing the internet, you have to allow one route also with 0.0.0.0/0 * Now you can see our client VPN endpoint is in an available state. ## **Step 9: Download and Install AWS VPN Client** The AWS VPN Client is required on end-user machines to establish a secure connection with the Client VPN endpoint. It uses the configuration file, certificates, and SAML authentication to enable seamless and secure access. **Step 1:** Open a terminal on your Ubuntu/Debian system. **Step 2:** Import the AWS VPN Client public key: **wget -qO- https://d20adtppz83p9s.cloudfront.net/GTK/latest/debian-repo/awsvpnclient_public_key.asc | sudo tee /etc/apt/trusted.gpg.d/awsvpnclient_public_key.asc** **Step 3:** Add the AWS VPN Client repository to your system sources: **echo "deb [arch=amd64] https://d20adtppz83p9s.cloudfront.net/GTK/latest/debian-repo ubuntu main" | sudo tee /etc/apt/sources.list.d/aws-vpn-client.list** **Step 4:** Update the package lists: * **sudo apt-get update** **Step 5:** Install the AWS VPN Client: * **sudo apt-get install awsvpnclient** **** **** ## **Step 10: Download and Connect with VPN Configuration** **Step 1:** In the AWS Management Console, go to the VPC service. **Step 2:** From the left-hand menu, click Client VPN Endpoints. **Step 3:** Select your Client VPN Endpoint and go to the Client configuration tab. **Step 4:** Click Download client configuration to get the **.ovpn** file. **Step 5:** Open the AWS VPN Client application on your machine. **Step 6:** Import the downloaded **.ovpn** configuration file into the client. **Step 7:** Connect to the VPN. You will be redirected to the IAM Identity Center (SSO) portal for authentication. **Step 8:** Sign in using your SAML (IAM Identity Center) credentials. ## **Step 10: (Optional) If You're Using the Self-Service VPN Application** **Step 9:** After authentication, go to the Self-Service VPN application (created earlier in IAM Identity Center). **Step 10:** Open the application and download the cvpn-endpoint configuration file. **Step 11:** Import this new configuration file into the AWS VPN Client (if required). **Step 12:** Connect again, and the connection will also be authenticated via the SSO portal. ## **Conclusion** Integrating AWS Client VPN with IAM Identity Center (SSO) via SAML 2.0 provides secure, scalable, and user-friendly remote access. It eliminates the need for managing individual VPN credentials by centralising authentication and authorisation. Administrators gain stronger security and compliance, while users enjoy seamless access with their existing SSO credentials—a modern, efficient solution for secure AWS VPN access. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Pritam possesses strong expertise in AWS, CI/CD, and Infrastructure as Code. He focuses on designing scalable, automated cloud environments and enhancing overall system performance. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents ## **ZooKeeper's Role: The Cluster's "Executive"** ZooKeeper is the central nervous system of the Kafka cluster. Its main job is to maintain a synchronized, up-to-date view of the entire cluster's state. It manages all the behind-the-scenes coordination that makes the system resilient and reliable. Here’s what ZooKeeper does: 1. **Broker Management:** It keeps a registry of all active Kafka brokers. Each broker sends a regular heartbeat to ZooKeeper, so if a broker fails, ZooKeeper knows instantly. 2. **Leader Election:** When a broker goes down, ZooKeeper is responsible for electing a new leader for any partitions that the failed broker was leading. This ensures that the system stays online and continues to function smoothly. 3. **Cluster State:** It stores and tracks critical cluster information, including: * The list of topics and their configurations (like the number of partitions and replication factor). * The In-Sync Replicas (ISRs), which are the replicas that are fully caught up with the leader partition. * Access Control Lists (ACLs) and quotas for security. In short, ZooKeeper handles all the metadata and coordination, providing the stable foundation that Kafka needs to operate. ## **Kafka's Role: The "Operations Team"** Kafka is the workhorse that handles all the data and direct client interactions. Once ZooKeeper has set up the cluster and decided on the leadership and topology, Kafka gets to work. Kafka is responsible for: * **Client Connections** : It manages all connections with producers (clients that write data) and consumers (clients that read data). * **Data Handling** : It handles the actual topic logs, which are the partitioned, ordered streams of data. This includes writing new messages, replicating them, and serving them to consumers. * **Consumer Groups:** It tracks which messages each consumer group has processed using offsets, ensuring that messages are delivered correctly and efficiently. Together, ZooKeeper and Kafka create a robust, fault-tolerant messaging system. ZooKeeper provides the brain and stability, while Kafka provides the brawn and direct client interaction. ## **Using Zookeeper: Understanding the files created** Besides myid, the rest of the files should remain untouched. They are managed by ZooKeeper. * **myid:** file representing the server id. That's how Zookeeper knows its identity. * **version-2/:** folder that holds the zookeeper data. * **AcceptEpoch and CurrentEpoch:** internal to Zookeeper. * **Log. X:** Zookeeper data files. ## **Zookeeper Architecture: Quorum sizing** * ZooKeeper needs to have a strict majority of servers up to form a strict majority when votes happen * Therefore, Zookeeper quorums have 1, 3, 5, 7, 9, (2N+1) servers * This allows for 0, 1, 2, 3, 4, or N servers to go down ## **Cluster Architecture Overview:** ### **Step 1: Installation: (Follow the same steps on all the machines in the cluster)** * Updates the package list on your Linux system. _**sudo apt update**_ * Installs the default OpenJDK (Java Development Kit), which is required to run Apache Kafka. _**sudo apt install default-jdk**_ * Check the Java version to verify that the installation was successful. _**java -version**_ * Download the Apache Kafka source code (version 3.5.1) from the Apache Kafka website. _**wget https://downloads.apache.org/kafka/3.5.1/kafka-3.5.1-src.tgz**_ * Extract the downloaded Kafka source code archive. _**tar -xvf kafka-3.5.1-src.tgz**_ * Rename the directory containing the extracted Kafka source code from "kafka-3.5.1-src" to "kafka" for convenience. _**mv kafka-3.5.1-src kafka**_ * Change the current working directory to the "kafka" directory, which contains the Kafka source code and configuration files. _**cd kafka/**_ * Enter the following command. **./gradlew jar -PscalaVersion=2.13.10** This command uses the Gradle build tool (specified by "./gradlew") to build the Kafka JAR files, and it sets the Scala version to 2.13.10 during the build process. Building the JAR files is necessary before running Kafka. ### **Step 2: Zookeeper Configuration: (Follow the same steps on all the machines in the cluster except for the last step where myid is set)** * Remove the default ‘zookeeper.properties’ file from the config/ directory. _**rm config/zookeeper.properties**_ * Now, create a new ‘zookeeper.properties’ file in the config/ directory. _**sudo vim config/zookeeper.properties**_ * Enter the following configurations in the zookeeper.properties file: 1. **_Data Directory (dataDir):_** This setting specifies the directory where ZooKeeper stores its snapshot and transaction log data. In this case, it's set to /home/azureuser/data/zookeeper. This is where ZooKeeper persists its data. 2. **_Client Port (clientPort):_** This is the port on which clients will connect to the ZooKeeper ensemble. In this configuration, it's set to 2181, which is the default port for ZooKeeper clients. 3. ** _Max Client Connections (maxClientCnxns)_** : It defines the maximum number of connections per IP address. Setting it to 0 disables this limit, as it's specified for a non-production configuration. 4. **_Tick Time (tickTime):_** Tick time is the basic time unit in milliseconds used by ZooKeeper. It's used for timekeeping, heartbeats, and timeouts. The tickTime is set to 2000 milliseconds (2 seconds). 5. **_Init Limit (initLimit):_** The initLimit specifies the number of ticks during which ZooKeeper servers must connect and synchronize. In this configuration, it's set to 10 ticks, which translates to 20 seconds (10 * 2 seconds). 6. **_Sync Limit (syncLimit):_** The syncLimit defines the number of ticks that can pass between sending a request and getting an acknowledgment. It's set to 5 ticks, meaning 10 seconds (5 * 2 seconds). 7. **_Zoo Servers (server 1, server 2, server 3):_** These lines define the configuration for ZooKeeper servers in the ensemble. Each server.x entry consists of three components: hostname or IP address, the quorum port, and the leader election port. In this example, you have a three-node ensemble with each node specified by its IP address and ports. 8. **_Admin Server Configuration (admin.enableServer, admin.serverPort):_** The admin server is disabled by default to avoid port conflicts. You can enable it by setting admin.enableServer to true and specifying the port using admin.serverPort. In this configuration, it's disabled (admin.enableServer=false). 9. **_4-Letter Words (4lw.commands.whitelist):_** This setting configures the list of 4-letter word (4lw) commands that are allowed by the ZooKeeper server. The * in this configuration indicates that all 4-letter words are allowed. These commands are short, textual commands used for interacting with ZooKeeper for diagnostics and management purposes. * Create a directory structure for ZooKeeper data. _**mkdir -p data/zookeeper**_ * Change the ownership of the data/ directory and its contents to the user ‘azureuser’. This is important because ZooKeeper will write data to this directory, and the user running ZooKeeper (typically azureuser) needs to have the necessary permissions. _**sudo chown -R azureuser:azureuser data/**_ * Create a file named myid inside the ~/data/zookeeper/ directory and set its content to "3". The myid file is used to identify the ZooKeeper server's unique ID in a multi-server ensemble. In this case, you are setting the ID of this ZooKeeper server to 3. _**echo "3" > ~/data/zookeeper/myid**_ Note: Set a different number in myid for each member of the zookeeper cluster. ### **Step 3: Creating zookeeper service: (Follow the same steps on all the machines in the cluster)** * Create the /etc/init.d/zookeeper file using the vim text editor. In this file, we’ll define how the ZooKeeper service should start, stop, and restart. You'll specify the actions to be taken when the service is managed by the system's init process. _**sudo vim /etc/init.d/zookeeper**_ * Copy and paste the following script into the /etc/init.d/zookeeper file * Make the /etc/init.d/zookeeper script executable. The system must run it as a service. _**sudo chmod +x /etc/init.d/zookeeper**_ * Change the ownership of the /etc/init.d/zookeeper script to the root user and root group. _**sudo chown root:root /etc/init.d/zookeeper**_ * Add the ZooKeeper script to the default runlevels, which means that ZooKeeper will start automatically when your system boots. The update-rc.d tool manages the symlinks in the /etc/rc*.d/ directories to control service execution during system startup and shutdown. _**sudo update-rc.d zookeeper defaults**_ * Start the ZooKeeper service using the system's service management utility. Once configured and added to the default runlevels, you can start the service this way. _**sudo service zookeeper start**_ * Check the status of the ZooKeeper service, indicating whether it's running, stopped, or encountering any issues. _**sudo service zookeeper status**_ ### **Step 4: Checking Zookeeper connectivity:** * Run the following command, which will send the "stat" command to the ZooKeeper server running on localhost and display the server's status information as a response. _**echo "stat" | nc localhost 2181 ; echo**_ You can also run `echo "stat" | nc 2181 ; echo` to check other stats of other zookeeper servers in the cluster. * Run the following command to display the contents of the zookeeper.out log file from the specified location. It contains the output generated by the ZooKeeper server, which can help diagnose issues or monitor ZooKeeper's behavior. _**cat kafka/logs/zookeeper.out**_ #### **The logs indicate:** * The server with ID 1 is in the "LOOKING" state, which means it's participating in the leader election process. It eventually becomes a follower (FOLLOWING) and accepts the leadership of server 2 (LEADING), which is the leader. * Server 2 becomes the leader and is now in the "LEADING" state. * Server 3 is in the "FOLLOWING" state and is following server 2. These logs indicate that the ZooKeeper servers have successfully elected a leader, and they are in a functioning ensemble. So, yes, your ZooKeeper servers appear to be connected and are functioning as expected. * Start a ZooKeeper shell and connect to a ZooKeeper server running on localhost at port 2181. The ZooKeeper shell allows you to interact with the ZooKeeper server to perform various operations, such as creating, deleting, and reading ZooKeeper znodes, which are like nodes or paths in a hierarchical data structure. _**kafka/bin/zookeeper-shell.sh localhost:2181**_ * Use the following command inside the Zookeeper shell to list or create a znode (node) _**ls /**_ _**create /my-node "some data"**_ _**ls /**_ _**quit**_ * Make sure all the zookeeper shell commands work exactly the same on each ZooKeeper machine and are properly synchronized. ### **Step 5: Attaching a new disk to Kafka brokers:** Attach a new disk to your Kafka brokers for storing Kafka’s data. The steps may vary depending on the cloud platform. ### **Step 6: Mounting the newly created disk to a specific path:** _**sudo su**_ _**lsblk**_ _**apt-get install -y xfsprogs**_ _**file -s /dev/sda**_ _**fdisk /dev/sda**_ _**mkfs.xfs -f /dev/sda**_ _**mkdir /home/azureuser/data/kafka**_ _**mount -t xfs /dev/sda /home/azureuser/data/kafka**_ _**chown -R azureuser:azureuser data/kafka/**_ _**df -h data/kafka**_ ### **Step 7: Kafka configuration: (Follow the same steps on all the machines in the cluster)** * To ensure that the user azureuser has the necessary permissions to work with the Kafka data and configuration files, change the ownership of the ~/data/kafka directory. _**sudo chown -R azureuser:azureuser ~/data/kafka**_ * Allow all users to have a higher limit for open files (file descriptors). This can be useful for applications like Kafka, which might require a large number of open file descriptors. _**echo "* hard nofile 100000**_ _*** soft nofile 100000" | sudo tee --append /etc/security/limits.conf**_ * * Reboot your system to allow your configurations to take place. _**sudo reboot**_ * SSH back into your server. * Start the zookeeper service. _**sudo service zookeeper start**_ * Remove the default configuration file of Kafka. _**rm config/server.properties**_ * Create a new server.properties file for Kafka. _**vim config/server.properties**_ * Enter the following configurations in that file: MAKE SURE TO USE ANOTHER BROKER ID AND `advertised.listeners` IN ALL THE MEMBERS OF THE CLUSTER * Launch Kafka - make sure things look okay _**bin/kafka-server-start.sh config/server.properties**_ ### **Step 8: Creating Kafka service: (Follow the same steps on all the machines in the cluster)** * Install Kafka boot scripts _**sudo vim /etc/init.d/kafka**_ * Use the following script: * Make the /etc/init.d/kafka script executable. The system must run it as a service. _**sudo chmod +x /etc/init.d/kafka**_ * Change the ownership of the /etc/init.d/kafka script to the root user and root group. _**sudo chown root: root /etc/init.d/kafka**_ * Add the Kafka script to the default runlevels, which means that Kafka will start automatically when your system boots. The update-rc.d tool manages the symlinks in the /etc/rc*.d/ directories to control service execution during system startup and shutdown. _**sudo update-rc.d kafka defaults**_ * Start the Kafka service using the system's service management utility. Once configured and added to the default runlevels, you can start the service this way. _**sudo service kafka start**_ * Check the status of the Kafka service, indicating whether it's running, stopped, or encountering any issues. _**sudo service kafka status**_ * Verify that it is working _**nc -vz localhost 9092**_ ### **Step 9: Checking Kafka connectivity:** * View the last few lines of the "server.log" file located in the "/home/azureuser/kafka/logs" directory. _**tail /home/azureuser/kafka/logs/server.log**_ * Open the zookeeper shell _**kafka/bin/zookeeper-shell.sh localhost:2181**_ * List the children of the /kafka/brokers/ids znode, which typically stores information about Kafka broker registrations. _**ls /kafka/brokers/ids**_ * Create a topic named "second_topic" with the specified replication factor and number of partitions on your Kafka cluster. _**kafka/bin/kafka-topics.sh --bootstrap-server 10.1.0.5:9092,10.1.0.4:9092,10.1.0.6:9092 --create --topic second_topic --replication-factor 3 --partitions 3**_ * Now, list all the topics that currently exist in your Kafka cluster. _**kafka/bin/kafka-topics.sh --bootstrap-server 10.1.0.5:9092,10.1.0.4:9092,10.1.0.6:9092 --list**_ * Now delete the `second_topic` _**kafka/bin/kafka-topics.sh --bootstrap-server 10.1.0.5:9092,10.1.0.4:9092,10.1.0.6:9092 --delete --topic second_topic**_ * List all the topics again _**kafka/bin/kafka-topics.sh --bootstrap-server 10.1.0.5:9092,10.1.0.4:9092,10.1.0.6:9092 --list**_ **Note: Follow these steps on all the machines inside the Kafka cluster to check the connectivity and synchronization of data.** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Jatin is a DevOps Engineer with expertise and multiple certifications in Azure and AWS. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 2 2 Table of Contents **Amazon Managed Grafana (AMG)** provides a secure, scalable way to visualize and analyze data from multiple sources. One of the key requirements in enterprise environments is integrating Grafana with existing identity providers for **Single Sign-On (SSO)**. In this post, we’ll configure Amazon Managed Grafana to use **Google Workspace as an Identity Provider via SAML 2.0** so your users can log into Grafana with their Google credentials. ## **Prerequisites** **1. Create an Organizational Unit (OU)** in **GrafanaUsers**) and place intended Grafana users in it. By default, they’ll have read-only access. **2. Decide who should be Grafana admins** and, for each, set **User Information → Employee Information → Department = Grafana** in the Google Admin Console. You can also use a custom field or any available field here, but note that it has to be updated in Step 3 too. **3.** (Optional) Create environment-specific groupings if you run multiple workspaces (dev/stage/prod). ## **Steps to Enable Amazon Managed Grafana Sign-In with Google Workspace** ### **Step 1: Create a Custom SAML App in Google Workspace** In **Google Admin Console → Apps → Add custom SAML app** , create a new app (e.g., Amazon Managed Grafana Prod) and **download the IdP metadata file**. When asked for the service provider details, take a pause and move on to Step 2 of this blog. ### **Step 2: Configure SAML in Amazon Managed Grafana** Open **Amazon Managed Grafana** → your **workspace → Authentication → Security Assertion Markup Language (SAML) → Complete Setup**. Copy the values AWS shows for: * ACS URL (Assertion Consumer Service URL) * Entity ID * (Optional) Start URL Put these values in the Google Workspace page where you were setting up the SAML app. ### **Step 3: Attribute Mapping** In your Google Workspace SAML app, add these mappings so Grafana can assign identities and roles correctly: ### **Step 4: Assign Access** In the Google Workspace SAML app **User Access** , target the **GrafanaUsers** OU and set **Service status = On** , then hit the **Override** button. ### **Step 5: Upload IdP Metadata & Finish SAML Config (in Amazon Managed Grafana)** Upload the IdP metadata you downloaded from Google Workspace and complete the following fields: ### **Step 6: Test** Visit your **Grafana URL** and click **Sign in with SAML**. You’ll be redirected to Google to pick/confirm the permitted account and then returned to Grafana. If you see “app not enabled for user”, verify: * The user is in the **Grafana OU.** * The OU is assigned to the SAML app. * Wait for up to **15 minutes** for Google Workspace changes to propagate. ## **Wrap-up** With this configuration, your organization centralizes authentication for Amazon Managed Grafana using Google Workspace. It simplifies onboarding, keeps roles consistent, and leverages your existing identity controls. Questions or need assistance? Contact CloudKeeper for Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Simran has a knack for integrating tools and automating workflows to improve efficiency and scalability. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents This guide will walk you through setting up SAML authentication for your Amazon Grafana Workspace, allowing users to log in through AWS IAM Identity Center (formerly AWS SSO). This process enhances security and streamlines user management by centralizing access control. ## **Step 1: Get Your Grafana Service Provider Details** First, you'll need to retrieve some key details from your Grafana workspace to configure the application in the IAM Identity Center. Navigate to your Amazon Grafana Workspace and click on the SAML configuration button. **a)** Navigate to your Amazon Grafana Workspace and click on the SAML configuration button. **b)** Copy the following three URLs and IDs. You'll need these in the next step: * Service provider identifier (Entity ID) * Service provider login URL * Service provider reply URL (Assertion consumer service URL) ## **Step 2: Create a New Application in IAM Identity Center** Now, we'll create a new application in the IAM Identity Center that will represent your Grafana workspace. 1. Open **AWS IAM Identity Center** in a new browser tab or window. 2. Go to **Application assignments** -> **Applications**. 3. Click the **Add application** button. 4. Select the setup preference as **I have an application I want to set up** , and the application type as **SAML 2.0**. Click **Next**. 5. Give your application a descriptive name (e.g., "Amazon Grafana Workspace") and an optional description. 6. Find and **copy the IAM Identity Center SAML metadata file URL**. ## **Step 3: Configure Grafana with IAM Identity Center Metadata** Next, you'll use the metadata URL from IAM Identity Center to configure Grafana. 1. Go back to your Amazon Grafana Workspace's SAML configuration page. 2. In the "Step 2: Import the metadata" section, paste the **IAM Identity Center SAML** **metadata file URL** into the **Metadata URL** field. ## **Step 4: Map Grafana Details to the IAM Identity Center Application** Now, you'll need to go back to IAM Identity Center and map the Grafana service provider details you copied in Step 1. 2. Return to the IAM Identity Center application you created. Paste the Grafana details into the following fields: * Grafana's **Service provider login URL** -> IAM Identity Center's **Application start URL** * Grafana's **Service provider reply URL (Assertion consumer service URL) - >** IAM Identity Center's **Application ACS URL** * Grafana's **Service provider identifier (Entity ID)** -> IAM Identity Center's **Application SAML audience** 3. Click the Submit button to save these settings. ## **Step 5: Configure Group-Based Access** To manage user roles, you'll create groups in IAM Identity Center and link them to Grafana roles. 1. Create two new groups in IAM Identity Center, for example: **Grafana-Admins** and **Grafana-Viewers**. 2. Go to the details page for the Grafana-Admins group and copy its Group ID. 3. Go back to your Amazon Grafana SAML configuration page. 4. In the **Admin role values** field, paste the **Group ID** of the **Grafana-Admins** group. 5. Keep the other values as shown in the screenshot below and save the configuration. ## **Step 6: Assign Groups and Configure Attribute Mappings** The final step is to assign the newly created groups to the application and define the attribute mappings that will pass user and role information from IAM Identity Center to Grafana. 1. In IAM Identity Center, go to **Customer-managed applications** and open the Grafana application you created. 2. Click on the **Assign users and groups** button and add the **Grafana-Admins** and **Grafana-Viewers** groups to the application. 3. Click the Actions button in the top right corner and select Edit attribute mappings. 4. Add the attribute mappings as shown in the provided example and save the changes. 5. Now, the Amazon Grafana application should appear on your AWS access portal. Users added to the **Grafana-Admins** group will be able to log in as administrators in Grafana. Similarly, users in the **Grafana-Viewers** group will have standard viewer access. You've successfully configured SAML authentication! 🎉 Check out our other guide: Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Jatin is a DevOps Engineer with expertise and multiple certifications in Azure and AWS. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents If you’ve ever**subnet IP exhaustion**. It’s one of those issues that doesn’t show up in small dev clusters, but once your workloads grow, it sneaks up fast and brings everything to a halt. Let’s break down what’s really happening, why it matters, and how you can keep your clusters from running out of IPs. ## **What subnet IP exhaustion looks like** Here’s the story. You’re running an Amazon EKS cluster, things are humming along, then a deploy happens, and pods just won’t start. You check the events: * Insufficient pods * Failed to create pod sandbox: failed to set up sandbox container network At first glance, it looks like a ## **Why Amazon EKS eats through IPs so quickly** By default, AWS EKS uses the AWS VPC CNI plugin. That means: * Each node gets one or more Elastic Network Interfaces (ENIs). * Each ENI maps to a subnet and gets a pool of IPs. * Every pod on that node gets a real VPC IP from that pool. This is great for native VPC networking; pods can talk to anything in the VPC without NAT or overlays. The downside? You’re burning through subnet IPs at the same pace you’re spinning up pods. Here’s the kicker: * A /24 subnet gives you 251 usable IPs. * That sounds like a lot until you realize every node reserves some for itself, and each pod also needs one. * Add in scaling events, DaemonSets, and sidecars, and suddenly that /24 is bone dry. ## **The quick fixes** If you’re already stuck, here are the emergency levers: Expand your subnets **a)** Add larger subnets (/19 or /20 instead of /24). **b)** Or attach secondary CIDR blocks to the VPC and create new subnets. **c)** This buys you breathing room, but it’s really just a band-aid. Spread pods across multiple subnets **a)** Make sure your node groups are using more than one subnet per AZ. **b)** This balances IP usage and avoids concentrating pressure on a single small subnet. ## Smarter long-term strategies If you don’t want to keep playing whack-a-mole with subnet sizes, here are better approaches: * **Prefix delegation (VPC CNI feature)** Instead of assigning individual IPs, AWS can hand out /28 prefixes to nodes. Each prefix provides 16 pod IPs, which dramatically reduces ENI churn and subnet pressure. * **Custom networking mode** Use secondary ENIs from a different subnet or CIDR just for pod traffic. This way your node management IPs and pod IPs don’t fight over the same pool. * **Consider IPv6** If you’re planning for very large clusters, enabling IPv6 gives you essentially unlimited pod IP space. It’s still a bit of a shift operationally, but it’s future-proof. * **Overlay networking (e.g., Cilium)** If you don’t need every pod to have a native VPC IP, an overlay CNI can decouple pod scaling from VPC IP limits. ## **How to know before it bites you** Subnet exhaustion is sneaky, but it leaves clues: * Watch the aws-node DaemonSet logs for IP allocation errors. * Set * Track pod density per node and compare against subnet free IPs. Proactive monitoring beats getting paged when half your pods are stuck in Pending. ## **Wrapping it up** Subnet IP exhaustion in Amazon EKS isn’t a bug; it’s just how the VPC CNI works. The problem is that most of us don’t think about subnet sizing until it breaks production. The good news: once you understand how pods consume IPs, you can design around it. Start with larger CIDRs, enable prefix delegation, and keep monitoring subnet usage. That way, your scaling story is about smooth growth, not a surprise bottleneck. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Cloud Engineer Manish is an AWS-focused expert known for optimizing infrastructure performance, controlling costs, and designing secure and reliable cloud solutions. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents More and more product companies are now installing business agility by moving to Cloud and bidding goodbye to the traditional legacy systems. In this constant chase to remain Agile and launch products faster to market, companies are also leveraging DevOps. DevOps as a service not only helps to automate redundant tasks and the entire delivery pipeline but also orchestrate the overall infrastructure in a better way. While there are multiple benefits of adopting DevOps, it is still very difficult to convince all the stakeholders and have a buy-in for automation in legacy companies. Some companies are still not able to understand the value that DevOps can bring to the table. According to the State of DevOps 2017 survey, approximately 29% respondents saw no value in adopting DevOps while 31% stated that they do not have the expertise. Outlined below are some of the common barriers to adopting DevOps and ways to overcome them. 1. **Lack of Experimentation** Experimentation is the key to success for any forward thinking business. Adopting new digital technologies not only helps to remain Agile but also stay ahead of the competition. Most legacy companies have a fear of failure, and they feel adopting DevOps might impact stability and lead to downtime and latency. Moreover, they are also afraid as there are costs associated with automation and failing at it could impact bottom-line drastically. Some companies also fear to adopt DevOps as they think automation is time-consuming. In the long term, automating delivery pipeline is cost-effective as it eliminates redundant tasks and facilitates continuous delivery. Lack of experimentation remains a barrier till the time there is fear of failure. It is only by setting up the automation and reaping its benefits companies can overcome this failure. Moreover, companies can invest time in identifying their core infrastructure problems so that they are addressed with automation and DevOps tools. 2. **Lack of Buy-in** Apart from lacking experimental mindset, legacy companies also need to have a strong buy-in from all the stakeholders to adopt a new technology or culture. At times, there is no buy-in from management while at times development and operations team do not want to move out of their own comfort zones and understand problems and support each other. Legacy companies also have a resistance to change because their legacy systems and way of working are complex and changing them to set up automation is difficult. Development, testing, and operations team must be open to learning new methods and skills to upgrade themselves. Management should not fear to fail and facilitate cross-functional working environment. Moreover, lack of buy-in can also be tackled by looking at the success stories of other companies in the similar space who have successfully adopted DevOps. 3. **Monitoring is Challenging** Infrastructure Monitoring is the key to Agile IT. Many companies do not have the necessary tooling skill sets and expertise to monitor the health of the delivery pipeline and infrastructure. Application, database, and server need constant monitoring, and most companies feel that DevOps will only add to the complexity. This is however not the case. Monitoring challenges do not grow with DevOps but rather reduce. There are various DevOps tools to monitor resources, set up alerts and provision infrastructure automation and leveraging them is a sure fire way to adopt DevOps swiftly. Some Agile teams also split software modules so that each can be independently developed, tested, deployed, and released. 4. **Complexity of Architecture and Hybrid Design** Companies prefer hybrid cloud because of benefits such as improved security, enhanced agility, and capabilities to mitigate risk with workload testing. Moreover, some of the legacy companies also have a complex app architecture because of multiple enterprise-level functionalities included in it. Companies with a hybrid environment and complex architecture most often feel that adopting DevOps would be a painful exercise and setting up automation without manual intervention might not work. This is mainly because applications are sometimes developed, tested or managed in isolated environments due to the hybrid design. It makes the deployment and release of each separate component sluggish and automation, a tough nut to crack. However, the complexity can be tackled by migrating workloads and leveraging microservices. DevOps would prove to be beneficial when blended with microservices and containerization. 5. **Cultural Differences** Outsourced software product engineering and distributed development are very common with most product companies. At times, these teams work in silos, and the development teams have limited knowledge about operations team. Product owners, development team, testing team, and operations team work in different time zones making coordination extremely difficult. Development teams do not wish to understand ops challenges and are limited to working only on dev tasks. The culture of the two traditional teams and mindset can limit automation. Dev and Ops team need to come together to make DevOps successful. If teams are working in distributed environment, they need to overlap time zones to facilitate continuous integration and deployment. They can connect to one another via video and audio conferencing systems. A strong culture can not only help in realizing the real business value but also encourage strong coordination. Moreover, there could be a remote DevOps leader who could train both the teams on tools and processes. Disparate application functionalities should work seamlessly along with optimized resource allocation. 6. **Change Management is just thought of as a New Team** Change Management is not about forming a new team “DevOps” by combining pre-existing teams. DevOps is a complete transformation in the way of working, culture, monitoring, optimizing, and automating tasks. With tech teams need to release shipping multiple times a day, automation is crucial. Combining development and operations team will not automate the pipeline or make the system resilient. One of the major goals of DevOps is to automate redundant tasks and make the system fault tolerant. Apart from automation, DevOps also focuses on improving time to market with early and continuous bug detection and fixing. Wrapping it up, there might be various technical challenges that come along the way while implementing automation, but there are hardly any barriers that should stop companies from implementing automation. It is a big myth that most companies feel DevOps is complex. In fact, it helps to simplify complexities and go to market faster. There are various DevOps automation tools such as Docker, Chef, Puppet, Jenkins, and others that companies can use for a swift DevOps transformation. If companies plan out a strategic roadmap to DevOps, they would be able to overcome hurdles and barriers to DevOps. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents If you're managing costs on But here’s the kicker: while you can view CUD data in the GCP Console, you can’t access it via BigQuery billing export, which is where most teams do their reporting and automation. That means this vital information is trapped in the UI, disconnected from your dashboards, pipelines, or alerting systems. While working on So, I decided to build my own automation. In this post, I’ll share exactly how I solved this problem — using Python, Selenium, and some practical engineering — and how it now helps both my team and our clients get better visibility into their cloud spend. ## **The Problem: CUD Data Is Trapped in the Console** Google’s billing export to BigQuery provides an excellent foundation for * Which commitments are active or expiring? * What services and SKUs are covered? * How well they’re being utilized. * Which projects are benefiting from them? Without this data, it’s almost impossible to build alerts for expiring discounts, compare committed vs actual usage, or create a transparent cost model across engineering and finance. ## **My Approach: Automating GCP CUD Reports with Selenium** 1. **Secure Login** The script securely logs into the GCP Billing Console with multi-factor authentication support. It can handle verification codes and recovery steps if required, using secure storage for credentials. 2. **Identify Billing Accounts** It fetches a list of billing accounts associated with the user or service account and filters out irrelevant ones, ensuring that we extract CUD data for every valid account. 3. **Navigate and Download Reports** For each billing account, the script opens the Committed Use Discounts page and downloads two types of reports: * Flat List Report – Detailed view by SKU and project * Grouped List Report – Aggregated view of active commitments 4. **Store and Distribute the Data** The downloaded reports are automatically: * Uploaded to a central cloud storage bucket * Shared with finance or platform teams via email or Slack * Optionally pushed to internal dashboards or data pipelines 5. **Enable Alerts and Monitoring** Once we had the data, we built custom alerts on: * Commitment expirations (e.g., notify 30 days before) * Under-utilized commitments * Missed savings opportunities These alerts help teams take timely action — whether that means renewing commitments, shifting workloads, or re-evaluating spend. ## **Code Walkthrough: Automating GCP CUD Report Extraction** Here's a look at the core components of the Python script I built to automate the retrieval of GCP Committed Use Discount (CUD) reports. This script logs in with MFA, downloads CSV reports, and uploads them to GCS while emailing them to stakeholders. ### **1 - Initial Selenium Setup** ### **2- Login with MFA and Recovery Email** ### **3 - Fetching Billing Account IDs** ### **4 - Downloading CUD Reports** ### **5 - Uploading to Google Cloud Storage** ### **6 - Sending the Reports via Email** ### **7 - Main Function** ## **The Outcome: Visibility, Control, and Optimization** This automation has unlocked previously inaccessible data, transforming it into a central asset for Teams now have real-time insight into how well CUDs are performing. Finance and engineering share a unified view, which helps in planning and accountability. We’ve already optimized spend by renewing the right commitments and reallocating underutilized ones. In short, we’ve gone from guesswork to clarity — and we’ve done it without waiting for Google to fill in the gaps. ## **Why This Matters to Every Cloud Team** This isn’t just a technical workaround — it’s a strategic enabler. If your team is using CUDs, you owe it to yourself to track them properly. And unless you have this data in your reporting and monitoring workflows, you're flying blind. Automation puts you back in control. It ensures your cloud discounts are being used as intended and helps you avoid surprises at renewal time. ## **Final Thoughts: Until GCP Adds an API, We Built Our Own Bridge** It’s entirely possible that Google Cloud will one day expose CUD data via an API or include it in billing exports. But until then, browser automation gives us what we need: visibility, control, and the ability to act. At Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Manav specializing in Google Cloud Platform (GCP) with expertise in designing and implementing automation solutions to optimize and streamline cloud operations. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents ## **Introduction** Many organizations struggle to keep their rising AWS costs under control due to the increasing ‘cloud chaos’. With decentralized teams, unpredictable infrastructure requirements, and unusual spends, monitoring AWS costs has become highly complex. While Cloud brings agility and innovation with itself, it also brings the opportunity for unplanned runaway spend. These costs can sometimes be the result of uncommon deployments that could arise from absence of automated deployment and configuration tools. Any organization using the AWS Cloud should have a cloud cost monitoring plan in place. It is important to identify the scope of increasing cost efficiencies on AWS and the earlier one optimizes their costs, the better it is for their ecosystem. ## **Cost Monitoring Significance** AWS tracking is hard and requires a keen set of eyes, certified Cloud architects and a process in place that affirms the safety and overall performance of AWS deployment in any organization through the right metrics. These practices depend upon numerous tools that collect, analyze, and provide statistics. The insights can then be utilized to perceive vulnerabilities and issues, improving overall performance, and optimize configurations. ## **Automation Solutions for Better Monitoring** An automation solution that enables cloud spend optimization can significantly help in monitoring these costs. These solutions also offer an advanced AWS Cloud usage analytics and optimization dashboard that provides real-time insights into the AWS spend to help organizations manage cloud resources effectively. Key features of an ideal solution include the following: * **Detailed usage summary:** The solution should provide Insights into the AWS bill summary, average daily spend, and past day costs along with monthly forecast & daily cost breakup on AWS services. It should also enable an organization to drill-down into past-month cost variations to identify specific usage types leading to any sudden cost changes. * **View of daily/monthly costs:** A mechanism should be in place to drill down into the daily & monthly cost variation for the services. This would certainly help organizations in understanding usage patterns & help make more informed decisions. * **Monitoring EC2 costs:** The costs on relational databases forms the biggest chunk in AWS. EC2 is a popular choice as it offers more control & flexibility. An ideal automated solution should help organizations understand the data transfer charges for all the EC2 instances and identify the ones costing maximum. Organizations must have pre-built dashboards where the right teams can view the data transfer charges for EC2. This will help in identifying EC2 instances with most data transfer out charges. The solution should provide usage quantity (no. of hours), the cost for on-demand, reserved, & spot instances along with data transfer charges for all EC2 instances. * **Manage RDS costs:** RDS is a cost effective database that lets you focus on important tasks by offering automation at multiple stages. The automation solution should track storage for data that has not been accessed for a while. An automation tool can move such data off RDS to a less costly storage service such as S3 by detecting unused & under utilized RDS instances. Policies should also be set up to avoid data dump into RDS. ## **Know the Metrics to Watch** Monitoring some key metrics can help keep a track of the health and performance of resources, inventory and usage. It’s important to understand the metrics that absolutely need to be monitored and the ones which could be redundant. Metrics like cost per day, response times, transaction rates, traffic stats, I/O stats, memory, and disk usage are some of the key areas that need constant tracking. Monitoring these enables users to account for future usage and issues, and optimize performance. Organizations must also ensure that the priorities for each monitoring task is clearly defined. This will help ensure that the critical services remain operational and that there are no security breaches. Additionally, prioritizing notifications helps teams to effectively manage their time and efforts. The period and thresholds of these alarms must be set at a reasonable value. The necessary actions that need to be taken with each alarm should also be stated. ## **Monitoring needs to be a continuous process** Monitoring is not a “one and done” process as new projects and workloads will add cloud resources, which can drive increased AWS costs due to overprovisioning. It’s challenging to monitor costs manually on a continuous basis which makes it all the more important to monitor infrastructure changes continuously to optimize resource utilization and cost to eliminate surprises in AWS invoices. Every single change that occurs across the AWS workload needs to be tracked so that the analytics solutions can provide insights on who made what change and when the change was made. ## **Conclusion** Cost optimization in the cloud can no longer be considered an ad hoc operation. It must be a well-structured, ongoing methodology that establishes a company's standard monitoring protocols. Efficient AWS cost control necessitates tracking instance usage and controlling it accordingly. To establish cost transparency, set up tagging, monitoring, and real-time dashboarding. Most significantly, when it comes to AWS setup, the cost of indecisiveness and poor decision making is much greater than the time and energy required to fully comprehend AWS cost monitoring. This is needed in order to fully leverage the Cloud's scalability advantages and reduce AWS spend. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents The State of FinOps 2026 is here! This annual survey by FinOps Foundation includes responses from over 1,000 practitioners managing $83bn+ in annual cloud spend. In 2026, the discipline of FinOps has moved far beyond its original roots in cloud cost control into comprehensive technology value management. ## **Why the ‘State of FinOps 2026’ Is Important for Modern FinOps Teams?** The technology landscape has never been more complex: AI pilots everywhere, SaaS sprawl, data centers that refuse to die, and pressure to prove ROI on every investment. The * Where do they focus their time? * What skills are they trying to build? * How are they organizing internally? * Which tools and practices are actually working? In this blog, we break down the most important insights from the report - what FinOps looks like in 2026, where it’s headed, and why it matters to organisations of all sizes. Whether you’re a FinOps practitioner, technology leader, or business executive, these findings can help you understand how organisations are approaching technology spend in 2026 and how FinOps is becoming a strategic driver of value. ## **A Defining Moment: From Cloud to Technology Value** Sometimes, the biggest shift in an industry is captured in a single sentence. In 2026, the FinOps Foundation updated its mission from “**advancing the people who manage the value of cloud” to “advancing the people who manage the value of technology**.” That small change says a lot. FinOps has moved beyond What started as a practice focused on controlling cloud costs has evolved into one that guides smarter technology decisions and drives business value. This mission evolution isn’t cosmetic - it reflects the reality practitioners see every day. ## **TL;DR: State of FinOps 2026** * **FinOps has evolved** from cloud cost control to **technology value management**. * **Scope is expanding** - teams now manage **AI, SaaS, licensing, private cloud, and data centers**. * **AI in FinOps is the top priority - 98% of teams manage AI spend** , and demand for AI cost skills is rising. * **Optimization alone isn’t enough** - focus is shifting to **governance, forecasting, and value measurement**. * **FinOps is becoming strategic - 78% of teams now report to CTO/CIO** and influence major tech decisions. * **Shift-left FinOps** embeds cost insights **earlier in architecture and development**. * **Cross-team collaboration and better tooling** are key as FinOps scales across the technology stack. ## Key Finding #1 - FinOps Is No Longer Cloud-Only One of the most striking insights from the report is how broadly organisations are applying FinOps practices. What used to be a discipline almost exclusively tied to public cloud spend now embraces multiple domains. * 90% of teams manage SaaS spending (up 25% Y-o-Y) * 64% handle software licensing * 57% cover private cloud * 48% manage data centers * 98% address AI costs (up from 63% in 2025) * 28% track labor costs (Source: State of FinOps 2026 Report) This expansion reflects a key shift: organisations want financial clarity across all technology investments, not just cloud bills, with AI management at 98% leading all categories. ## **Why does this matter?** Because tech spend today isn’t just about servers and services. It’s about tools that drive innovation, automation, customer experience, and competitive differentiation. When organisations can view all of that through the same financial lens, they gain insights that finance teams alone could never uncover. ## Key finding #2- AI Takes Center Stage Let’s talk about the elephant in the room: **AI**. One of the top forward-looking priorities in 2026 is (Source: State of FinOps 2026 Report) Now, managing AI spend isn’t just part of the conversation - it’s the biggest priority teams have this year. According to the latest findings, an astounding **98% of organisations surveyed are managing AI spend in their FinOps practice** , up from just 31% two years ago. That’s not incremental growth - it's a massive breakthrough. And here’s what makes it really interesting: * FinOps teams aren’t just tracking AI costs - they are being asked to support AI investments directly by finding efficiency gains elsewhere. In other words, they are helping organisations find the money to innovate. * AI cost management has become the #1 skillset FinOps teams are hiring for, highlighting how central it has become to the discipline itself. But it’s not just about curbing expensive AI bills. It’s about ensuring AI spending delivers measurable value - whether that’s automating workflows, driving product innovation, or unlocking new revenue streams. So, while old perceptions of FinOps focused on saving money, the new reality is about balancing cost and strategic impact. (Source: State of FinOps 2026 Report) ## **AI in FinOps: New Challenges and Opportunities** The State of FinOps 2026 report identifies three interconnected challenges and opportunities when extending FinOps practices to AI workloads. ### **Core Challenges** AI spend creates unique visibility gaps compared to traditional cloud services: * Complex pricing: Variable models (tokens, GPU-hours, inference vs. training) vary across providers * Allocation difficulties: Shared models, exploratory pilots, and mixed GPU workloads complicate business unit attribution * ROI uncertainty: Experimental nature makes value measurement difficult during early phases AI is also beginning to **improve FinOps operations themselves**. Early use cases include: * Anomaly detection and faster cost alerts * Automated rightsizing recommendations * Natural-language queries for cost data * Automated discount optimization * AI-assisted tagging and cost allocation AI is emerging as a **productivity lever** - helping teams analyze complex spending patterns faster and make more informed financial decisions. ## **Key Finding #3 - Optimization is Table Stakes; Value Is the Goal** For years, many organisations focused on cutting obvious waste: turning off unused servers, The 2026 report shows that **those easy wins are largely behind us**. _Practitioners report diminishing returns in cloud optimization: “We have hit the ‘big rocks’ of waste and now face a high volume of smaller opportunities that require more effort to capture.”_ _Another described reaching 97% optimization in their Cost Optimization Hub, with the remaining 3% intentionally not actioned for business reasons._ (Source: State of FinOps 2026 Report) ### A Shift in Priorities This shift suggests a maturing discipline where savings alone are no longer the end goal. Optimisation and waste reduction are still the top current activities, but teams are now placing equal or greater emphasis on: * * Organisational alignment * Forecasting and budgeting * * Influencing technology selection Mature FinOps practices are less about cutting costs alone and more about increasing the value technology investments deliver. (Source: State of FinOps 2026 Report) ## **Key Finding #4 - Power Shift: Closer to the CTO** One of the most significant trends captured in the report is where FinOps sits in organisations. In 2026: * **78%** of FinOps teams now report to the **CTO** or **CIO** , rather than finance. * Teams that engage at the VP/C-suite level have **2–4× more influence** over strategic decisions like cloud provider selection, hybrid vs. cloud placement, and long-term investment decisions. This matters because influence means a shift from reporting cost to shaping strategy. FinOps professionals today help guide major decisions - from negotiating multi-year commitments to determining whether a workload should be built in AI, on-prem, or in a hybrid cloud. (Source: State of FinOps 2026 Report) FinOps is no longer a back-office analytics function - it’s part of strategic technology decision-making. Teams are influencing long-term contracts, provider choices, and investment roadmaps. ## **Key Finding #5 — Shift Left Is Here, But Measurement Is Hard** Another big theme emerging in 2026 is “Shift Left.” Unlike older FinOps practices that focused on analysing bill after bill, teams are increasingly embedding financial context before code is written or infrastructure is provisioned. That means: * Engineers and architects get cost visibility during design phases * Teams estimate the spend impact before deployment * Forecasting and budgeting are integrated with planning workflows The idea is simple: **avoid cost rather than react to it.** But here’s the tricky part - while everyone talks about this shift, measuring its impact remains challenging. If a cost never materialises because you prevented it, how do you quantify those savings? FinOps teams are still figuring that out. ## **Key Finding #6 - Intersecting Disciplines Are Converging** FinOps isn’t a siloed team anymore. It’s a cross-functional operating model where numerous disciplines intersect: * IT Financial Management (ITFM) — shared governance data * IT Asset Management (ITAM/SAM) — compliance and efficiency * IT Service Management (ITSM) — shared processes and policies * Platform Engineering — early cost guidance embedded in development * ESG and sustainability teams — aligning cost and carbon/energy metrics This convergence shows that effective technology value management isn’t achieved in silos - it’s a team sport. (Source: State of FinOps 2026 Report) ## **Key Finding #7 - Lean Teams, High Demand for Skills** Despite this broad scope, most FinOps teams remain lean. Instead of adding headcount to scale, organisations rely on automation, tooling, federated champions embedded in product and engineering teams, and stronger governance frameworks. But what skills are in demand today? * AI cost and value management - **#1 skillset teams plan to add** * Tooling expertise and automation development * Data analytics and forecasting ability This reflects that FinOps is increasingly data-driven, engineering-aligned, and forward-looking - not just a cost accounting discipline. (Source: State of FinOps 2026 Report) ## **Key Finding #8 - Evolving Tooling Expectations** The report shows that expectations from FinOps tooling are evolving alongside practice maturity. Top requested features include: * Granular monitoring of AI spend (tokens, LLM requests, GPU utilization) * Shift‑left capabilities, such as pre‑deployment architecture costing * A single pane of glass that brings together different technology spend types (Source: State of FinOps 2026 Report) ## **Key Finding #9 - The Role of Data Normalisation (FOCUS)** To deliver value across technology domains, one of the biggest enablers has been improvements in how cost and usage data are standardised. The FinOps Open Cost and Usage Specification (FOCUS) is becoming a foundation for this work. It allows organisations to bring together billing data from multiple sources—cloud, AI services, SaaS platforms, licensing systems, and more—into a consistent format. ### **Why is that important?** Because when data speaks the same language across all technology domains, teams can: * Compare performance across tools and services * Spot trends and anomalies earlier * Align spend with business outcomes consistently * Provide leaders with insights that inform strategy FOCUS is more than a technical specification - it’s becoming the language that lets FinOps teams operate at scale across diverse tech landscapes. ## **Closing Thoughts: What This Means for Organisations** The State of FinOps 2026 report clearly shows that FinOps is no longer a niche cost management function. It has grown into a strategic capability that helps organisations understand technology investment and derive measurable value from it. What it tells us is simple but profound: __ If you are shaping a FinOps or technology strategy, three practical moves stand out: * **Broaden your scope** Look beyond the public cloud into SaaS, licensing, data center, AI, and eventually labor. Use standards like FOCUS to keep the data manageable. * **Secure strong technology leadership backing** Align under CTO/CIO ownership, ensure VP+ sponsorship, and push for a seat at the table where technology choices are made. * **Invest in AI on both sides** Build strong governance around AI spend while also adopting AI capabilities that enhance the FinOps practice itself. As you think about your own organisation’s journey, ask yourself: Are you still thinking about FinOps as cost-cutting or as value creation? Because the best teams in 2026 are already answering that question - and acting on it. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents Amazon RDS Blue/Green Deployments provides a safe and easy way to test changes to your database before applying them to your live environment. It creates a green (staging) setup that copies your blue (production) setup and stays in sync with it. You can make updates or changes to the green environment without affecting your live production system. **Architecture of Blue/Green Deployment with RDS** ## **Benefits of Using Blue/Green Deployments** * You will have minimal downtime during switchover. * You can perform thorough and safe testing of changes before production rollout. * You will have an easy rollback if any issue arises. * There will be continuous data sync between environments. * Lesser deployment risks. * It helps to simplify the maintenance and configuration changes. ## **Steps to Optimize RDS Storage Using Blue/Green Deployment** The following is a simplified procedure to reduce allocated storage for Amazon RDS via Blue/Green deployments: 1. Log in to the AWS console. 2. Open the RDS dashboard and select your current (Blue) RDS instance. 3. Take snapshots and all necessary backups of the RDS instance before initiating any changes. This ensures you have a restorable version in case you need to roll back. 4. Click “Create Blue/Green Deployment” from the Actions menu. 5. In the setup wizard, customize the Green environment: 6. Under “DB instance settings”, locate the storage configuration. 7. Set the reduced allocated storage size here as per your requirements(e.g., reduce from 100 GB to 50 GB). 8. You can also change instance type, networking, and other parameters if needed. 9. Launch the deployment. The Green environment will be created with your modified storage settings, and data replication will begin automatically. 10. Wait for the deployment to complete, and ensure both environments are active and synced. 11. Test the Green environment thoroughly: 1. Validate data consistency 2. Run application queries and performance checks 3. Simulate real traffic if possible 12. Once verified, click “Switchover” in the RDS Console. 13. The switch happens in less than a minute, with no data loss and minimal to zero downtime. 14. After a successful switchover, monitor your application. 15. Finally, delete the old (Blue) environment if everything looks good, to avoid unnecessary costs. ## **Key Considerations** When * If your database is allocated with more storage than the current requirement, consider reducing it. Enable storage autoscaling to allow it to grow automatically when needed. * Ensure to align the read replica storage with your newly optimized primary DB storage for better savings. * Avoid allowing write operations on the Green environment unless it's absolutely required. Writing to it can cause replication conflicts and unexpected behavior during switchover. * Once you've allocated storage for an RDS instance, you can’t reduce it later, so plan the size carefully at the start. * If you're using storage autoscaling, it's best to start with a lower initial size as per your minimum requirements, then enable autoscaling to handle growth when needed. * Storage optimization can take a few hours, and you won’t be able to make additional storage changes until the process is finished or at least six hours pass. * Try to schedule the switchover during off-peak hours to avoid any potential disruption to your users. * You can configure a switchover timeout between 30 seconds and 1 hour. If it exceeds the time limit, the operation cancels automatically with no changes made. * Always check replication health and lag between the Blue and Green environments before initiating a switchover. A healthy sync ensures minimal downtime and a smooth cutover. * If your DB uses IAM roles, remember they won’t automatically transfer to the Green environment. You’ll need to manually attach them after the switchover. ## **Limitations of Blue/Green Deployments** When planning a blue/green deployment in Amazon RDS, be aware of the following restrictions: * AWS Secrets Manager doesn’t support managing master passwords during Blue/Green deployments. * If is Dedicated Log Volume (DLV) is enabled in your Blue instance, it must also be enabled for all related instances, including replicas. * Make sure the Event_Scheduler is turned off in the Green environment to prevent unexpected jobs or data changes during deployment. * You can’t switch between encrypted and unencrypted databases as part of a Blue/Green deployment. * You can’t downgrade the database engine version; the Green environment must use the same or newer database engine version than the Blue one. * Cross-account deployments are not supported, so both the Blue and Green environments must exist in the same AWS account. ## **An Ending Note** It's strongly recommended to perform testing and a thorough assessment in a staging or non-production environment before proceeding with implementation in the production environment. Before you begin, check for any engine-specific requirements—steps may vary based on whether you're using MySQL, PostgreSQL, or another supported engine. Please refer to the official AWS documentation and check the prerequisites accordingly for your specific engine version. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Cloud Engineer Pranav has hands-on experience in AWS cloud infrastructure, F5, and DNS. He is passionate about building secure, scalable, efficient cloud solutions and learning new technologies. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents For enterprises operating at scale on the cloud, costs play a critical role. Costs can make or break your cloud initiatives. Cloud cost management becomes such a pressing matter for enterprises that any neglect in this area could lead your business returns to go downhill, or worse, cause a collapse of the business altogether. Cloud service providers like AWS realized this long back, so they started offering discounts and incentives to companies based on factors like volume, scale, loyalty, etc. These discounts and privileges collectively form what is called the **AWS Enterprise Discount Program** or simply **AWS EDP**. The discount program is however complex territory. Enterprises rarely can leverage the full potential of the program without an eligible AWS EDP partner, who can handhold them into negotiating a wholesome contract, availing better discounts, etc. In today’s article, we will explore how you can ## **What is the AWS Enterprise Discount Program(AWS EDP)?** ## **Who is eligible for the AWS EDP?** Usually, enterprises who qualify for AWS EDP must have spent more than $1 million annually on AWS services and must have a similar projection for future spending. The discount increases significantly for larger annual commitments and term lengths, and the spending thresholds range from $1 million to $50 million annually. The tenure of commitment ranges from 1 to 5 years. Naturally, customers who commit more dollar spending and for a higher term length will move toward the higher discount tier. ## **Benefits of participating in AWS EDP** There are several benefits associated with the AWS EDP. **1. Discounts:** The core benefit of the program is discounts that enterprises can enjoy to achieve better **2. Better support from AWS:** AWS Enterprise Discount Program customers enjoy enhanced collaboration, support, and close partnership with AWS. Being an AWS EDP partner, the organizations demonstrate a strategic and long-term commitment to AWS which unlocks tier-1 benefits and resources. **3. Predicted budgeting:** Because AWS EDP requires enterprises to make plans over an extended period, budgeting becomes predictable and stable. There is long-term clarity over where you will be spending your budgets throughout 1 to 5 years, depending on your commitment. **4. Versatile applicability:** The AWS EDP discounts are applicable across all major AWS services and transcend regions, processors, and operating systems. Although the basic EDP plan in itself is a very lucrative option for enterprises, it is not without a set of limitations. ## **Limitations and challenges of EDP** As mentioned earlier, despite the numerous benefits that AWS EDP offers, enterprises find it difficult to realize the true potential of the program because of certain limitations or challenges associated with it. **1. High commitment levels:** Enterprises need to commit to very large spending on AWS to even be eligible for AWS EDP. Getting it right requires a deep understanding of cloud usage patterns and the various options available through the EDP. **2. Limited discounts:** Although in principle the discounts offered under AWS EDP are significantly high, to realize it, companies need to employ the right cloud FinOps expertise along with a deep **3. Contract negotiation:** Negotiating an AWS Enterprise Discount Program demands careful planning, strategic foresight, and collaboration. Companies need to leverage market insights, foster open communication with AWS representatives, and emphasize long-term commitments and growth potential, all of which complicate things further. **4. Higher costs of AWS support:** AWS requires all organizations opting for EDP to also sign up for AWS Enterprise Support, which can cost up to 10% of your monthly AWS spending. Organizations that aren’t already on Enterprise Support will need to factor the increased support costs into their AWS EDP. All of the above points certainly make navigating AWS EDP on your own quite a challenging ride. ## **How can an AWS EDP partner upgrade your plan from good to great?** Selecting the perfect AWS EDP plan requires a highly nuanced view of your resource utilization, AWS service types, target platforms, AWS marketplace apps, savings plan and reservations, etc. Hence, realizing the full value of the AWS Enterprise Discount Program might need a complete paradigm shift in how you go about the agreement in terms of forecasting, using the right analytics, etc. This will ensure that you create favorable negotiation terms for the AWS EDP agreement. Without the right set of cloud FinOps expertise, enterprises might end up getting lower discounts and higher costs than what was initially expected. An experienced cloud FinOps partner can handhold organizations to calibrate the AWS EDP program for their specific needs and constraints. They could also provide support for the cloud strategy based on the prevailing economic and market trends. Here are some advantages of working with a partner. **1. Contract Negotiation:** One of the most valuable contributions of an AWS EDP partner is in the negotiation phase. They can ensure that your organization’s commitments and requirements are properly aligned with the EDP, negotiate favorable terms, and help optimize the contract to maximize cloud cost savings. **2. Cloud cost optimization:** An expert partner generally comes with in-depth knowledge of AWS pricing models, resource utilization, and **3. Resource planning:** Resource planning is a critical element of your AWS EDP initiatives. An AWS EDP partner can help with resource planning by analyzing the organization’s workloads, infrastructure requirements, and anticipated growth. They can guide rightsizing instances, utilizing reserved instances effectively, and optimizing resource allocation to align with the EDP commitment levels to achieve maximum cloud cost savings and reduced wastage. **4. Architecture review:** The AWS architecture must run optimally in the whole scheme of things. Hence, a partner can review the organization’s infrastructure design and provide recommendations to optimize performance, security, and cost-efficiency. They can modify the architecture to align with AWS EDP discounts, such as better AWS service options, features, or design patterns that offer significant cost advantages. **5. Discounted enterprise support:** An AWS EDP partner can significantly bring down the costs of your enterprise support, which otherwise could put a big dent in your overall cloud bill. As the business expands, support costs required to optimize resources and reduce vulnerabilities can cost a pretty penny, bringing you back to square one. **6. Migration and Optimization Tools:** An AWS EDP partner can also facilitate specialized tools or platforms that help in migration to AWS or for ongoing optimization. These tools can automate the ## **Why CloudKeeper EDP+?** As seen above, an **AWS EDP** partner can prove to be an invaluable addition to your cloud cost optimization journey. Once your mind is made up for associating with an AWS EDP partner, the next stage is zeroing down on the right AWS EDP Partner, to help you strengthen your EDP initiatives. There are certainly several cloud FinOps vendors offering a range of cloud cost optimization solutions, and it is easy to be overwhelmed by choice and might require rigorous planning and discussions to finalize the desired partner. CloudKeeper, one of the leading companies in this space is a comprehensive With more than 12 years of experience in the cloud domain, CloudKeeper has helped 300+ organizations worldwide save more than 20% of their AWS costs. Being an AWS Premier Consulting Partner, CloudKeeper can bring in a wide range of cloud services and exclusive relationships with AWS, to steer the commitment-planning the right way ahead. When you are looking for a one-stop solution for all your cloud cost optimization needs, CloudKeeper guarantees instant cloud savings. Want to learn more? Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources The Complete Guide to AWS PPA Contract Negotiation for Growing Enterprises A practical guide to AWS PPA or EDP negotiations, covering commitments, discounts, flexibility, risks, and best practices to help growing enterprises secure better pricing and long-term cloud value. By Team CloudKeeper 19 Dec, 2025 Ask the Cloud Expert: A Deep Dive Q&A on AWS PPA In this Q&A, CloudKeeper’s AWS PPA expert Aman Dixit shares real-world insights to help clients navigate PPAs and make smarter, cost-effective decisions. By Team CloudKeeper 05 Sep, 2025 Introducing the AWS EDP Tracker in CloudKeeper Lens AWS EDP Tracker is a real-time interactive dashboard that gives you end-to-end visibility to monitor, forecast, and optimize your EDP spend throughout its term. By Harsh Agarwal 06 May, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents ## **Why is FinOps Crucial?** In this era of a multi-cloud, there is constant pressure on the CIOs to deliver more for less at a very fast pace. The emergence of multiple teams and organizational complexities has pushed the need for cross-functional collaboration to drive end-to-end cost management. This is where FinOps plays an extremely crucial role. FinOps goes beyond just the cost of tools or the cost of applications, rather it's a holistic and disciplined approach to drive transparency and evaluate the value being extracted from money spent. ## **Why Cloud Cost Optimization has become more important than ever?** With the COVID-19 pandemic, many enterprises have moved to virtual operations for employees and online experiences to operate smoothly, innovate faster, collaborate more broadly, and reduce costs. Despite this, many IT leaders are wondering why even after transferring so many workloads to the cloud, savings are not yet evident. Well, to find out the reason behind this businesses need to take a closer look at their practices. A few of the key reasons that could be obstacles in your * Performing traditional show back and chargeback activities * Only relying on public cloud providers for data on cloud spend and ROI * Not having the right team and key stakeholders in place leads to inefficient tracking and control * Lack of financial governance due to misalignment between business, finance, and IT team * Not The language of business is finance, hence it's extremely important to have the right team on board early and have a FinOps strategy in place to help you scale in your cloud cost optimization journey. _**Now, let's have a look at key considerations that help reduce the cost of the cloud.**_ ## **Leverage Tagging to Organize Cloud Costs:** A well-defined cloud tagging strategy can be the backbone of a cloud governance system. Tagging cloud resources help build accountability among different teams and give a clear picture of cloud spend and usage across different functions. An organization can assign tags based on what aspects of cloud spending the business wants to view and make the most effective use of It's a good practice to segregate people into multiple teams who are using one common account in case there are many people involved which makes it unmanageable and leads to over utilization. The different teams should be made responsible for different accounts. And, then decide on a baseline number, and in case of any anomaly is found, the responsible team should justify the reason for that. This eventually makes account management much easier giving a clearer picture of the “where” and “why” of the spend. ## **Adopting the Right Strategy to Transit from a Traditional model to a Cloud-based model:** Cloud models are more customer-centric than traditional models, but they must be implemented with the right steps and strategies. In the pandemic, the customer engagement model has changed, therefore, moving to an agile approach in business strengthens the relationship with customers. With the cloud operating model, we get flexibility like cost transparency, applying analytics to the data sets, having a centralized DevOps principle, and many other factors that are driving business awareness which the traditional model lacks. It is therefore of utmost importance to have a plan, strong leadership, and technical expertise to optimize your infrastructure as per the new model when shifting to a cloud-based model. Furthermore, it is advisable to collaborate with a ## **Perform Budget Forecasting:** Budget forecasting helps you avoid unwanted surprises in your bills to a certain extent. However, to perform budget forecasting it is important to have the right people in place. Instead of only involving finance to discuss cloud costs, invite different stakeholders including developers, system operators, DevOps specialists, and anyone who affects cloud costs. It is a collaborative approach between business, finance, and engineering. Finally, analyze the past patterns and align your decision with what’s lying ahead which includes your upcoming business initiative and business strategy. As we say data is stubborn, always back your decision with data. ## **Keeping up with the Ever-Changing Information:** With large chunks of information and options available for cloud platforms, this becomes a challenge to keep up with updated information and processes set in place. First and foremost, to overcome it is extremely important to have a good tool foundation. Secondly, decide the stakeholder who will be accountable for collecting and updating the right information. Understand that the goal here is better decision-making, optimized opportunities, and continuous improvement, hence have a pragmatic approach and be agile enough to counter any challenges through strong leadership and team. ## **Consider Investing in a Cloud Financial Management Solution:** We know that only relying on public cloud providers for data on cloud spend and ROI isn't enough for you to scale as the environment increases in size and complexities. Thus, it is a good idea to invest in a third-party cloud cost management solution that gives you a deeper view of budget management, tagging strategies, detailed dashboard and reporting, trend analysis, etc, which eventually helps you make informed buying decisions, and avoid money wastage and controlling over-consumption. As per Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents The simplicity with which cloud-based platforms like Azure can be used to develop and implement apps has completely changed the way organizations function in today's digital environment. The days of stressing about the nuances of infrastructure, such as availability, stability, and scalability, are long gone because cloud providers take care of these details with ease. However, there is a major drawback: expense, especially when it is left unchecked! The ease of cloud deployment, if not properly supervised, can result in unforeseen high cloud costs, which could quickly double or even triple the budget allotted. In severe circumstances, companies have seen their yearly allotment for technology disappear in a matter of weeks. This makes utilizing ## **Azure Cost Optimization Best Practices** ### **1. Rightsizing your instances** Azure makes it easy to provision servers with just a few clicks, but this convenience can lead to overspending. Even though hosting on a large server may seem dependable, it can quickly eat into your budget. It's smart to regularly check your resource usage and adjust as needed. ### **2. Determine virtual disks and underutilized resources** Charges for all resources purchased—even those that are no longer actively used—will be included in a cloud service bill. In these situations, the expense is derived from virtual disks and underutilized storage, both of which can be easily removed. To find resources that can be eliminated and to make sure they are not being used, continuous monitoring is necessary. ### **3. Workload optimization based on types of Azure Virtual Machine (VM)** Monitoring the resources that have been allocated is a recommended ### **4. Selecting Appropriate Services** Azure offers a plethora of serverless resources. We can pay for the capacity we utilize on a server, rather than paying for the entire capacity. The majority of the time, using serverless resources is preferable because they automatically reduce costs while the system is idle. Many workloads operating in virtual machines (VMs) and Cloud Service Web/Worker roles can be replaced by Azure Functions running under a consumption plan. Many other services are also available in a Serverless plan. To cut costs, think about utilizing serverless resources whenever possible. ### **5. Autoscale and club unused resources** Idle resources are those that operate at a CPU optimization level of 1% to 5%. When it comes to billing, it's just another example of unnecessary spending. Businesses can reduce costs and take advantage of on-demand scalability to minimize their Azure expenses by grouping these idle resources. For your database virtual machines (VMs), compute, and storage resources to scale automatically when they go above or below a given threshold, use the auto-scaling functionality and set up predefined rules. ### **6. Move to containers** Although virtual machines (VMs) are a great alternative, the cloud platforms like Azure also offer containers. This consolidates several workloads onto fewer servers, hence ensuring Azure cost optimization. Other advantages of this solution include faster operation power, integrated monitoring systems, a smaller digital footprint, etc. ### **7. Choose Reserved Instances** One significant area where you can do well with Azure cost optimization and save resource costs by up to 80% is with Azure Reservations. Microsoft Azure offers resource discounts according to a stated one- to three-year usage commitment. ### **8. Move data to a different geographical region** Azure prices differ by area. Thus, it is sensible to take the geographic location of your resources into account when determining expenses. Transfer your workload to a less expensive area if at all possible, for better ### **9. Azure budget planning and management with tools, reports, and alerts** To cut down on Azure spending and adhere to ### **10. Establish Guidelines and adhere to best practices** For engineering-related activities, technical brainstorming sessions, handover meetings, and retrospection meetings are typical. Arrange a regular meeting of this nature to talk about You should subscribe to a third-party service for controlling Azure costs to have the finest picture. It guarantees that all Azure cost optimization best practices are adhered to and is just as important for an application as an APM tool. ## **Conclusion** In summary, CloudKeeper is a trusted Azure Partner that specializes in helping businesses navigate the challenges of Azure cost optimization. Using cutting-edge technologies and Azure cost optimization best practices, our knowledgeable team provides customized solutions to maximize the return on your cloud investments. Businesses can cut expenses, accelerate their Azure journey, and seize chances for expansion and innovation in the cloud. To explore more, Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 13 13 Table of Contents The cloud is a powerful engine for growth - but without the right cost management strategy & tools, that engine can quickly become one of the largest line items in your budget. This blog walks you through the **top 10 best Cloud Cost Management tools featured in the G2 Leader’s Quadrant for the Winter 2026 Grid® Report.** The blog also shares key strengths and limitations of each platform to help you choose the right partner for your FinOps journey. ## **How G2 Evaluates Cloud Cost Management Tools?** To be included in the G2 * Monitor cloud infrastructure usage * Track spending as it relates to resource usage * Highlight opportunities to save by reducing or optimizing resources. The Cloud Cost Management tools are then scored based on a combination of user satisfaction and market presence, as reflected in genuine, verified reviews. And those with high satisfaction plus strong presence are placed in the Leader quadrant. ## **Why does cloud cost management matter now?** According to Strong cloud cost management tools change that by: * Centralizing visibility across accounts, projects, and business units * Enabling accurate allocation and showback/chargeback so teams own their spend * Providing forecasting, anomaly detection, and automation, so optimization becomes part of daily operations instead of a once‑a‑quarter cleanup. When this happens, cloud cost management stops being a reactive finance task and becomes a shared operating rhythm for engineering, FinOps, and finance. ## **10 Best Cloud Cost Management Tools in 2026 (According to G2)** (Source: Grid® Report for Cloud Cost Management | Winter 2026) ## #1. CloudKeeper – End‑to‑End Cloud Cost Optimization Partner **G2 Ratings: 4.7/5 (251+ Reviews)** CloudKeeper tops the list as the **#1 Cloud Cost Management tool with a perfect 100% satisfaction score from its users.** CloudKeeper is the only partner in the category to achieve a 100% satisfaction score - a rare achievement that reflects both performance and people-centric design. ### **Why is CloudKeeper indeed the best choice?** * CloudKeeper stands apart as the only truly**, covering every aspect of cloud management** - from rate and usage optimization to deep visibility, governance, and expert-led support. * It delivers * The******** brings visibility, optimization, governance, and automation together in one integrated solution - **eliminating the need for multiple cloud management tools** and simplifying cloud management at scale. * With advanced **and** ### **What users love:** * **Unified Cloud Cost Visibility:** A * **Intuitive & Insightful Dashboards: **User-friendly & intuitive dashboards that provide detailed visibility into cost trends and savings opportunities. * **Expert-Led Optimization Insights:** Reviewers value the actionable cost optimization insights shared by the CloudKeeper team, helping them make smarter spending decisions. Unlike others, CloudKeeper doesn’t just tell you where money is leaking - it helps you fix it. * **Effortless Cloud Cost Management:** Users appreciate the ease of managing cloud expenses, enabled by * **Proactive Customer Support:** The **customer success team is genuinely loved by users for its excellent & proactive ** * **Consistent, Proven Cost Savings:** Customers report significant cost savings, achieved through effective optimization and streamlined cloud management. * **Designed for Cross-Functional Collaboration:** Its ease of use makes it ideal for both engineers and finance teams. ### **Best for -** * High-growth organizations scaling rapidly on the cloud and looking for predictable, continuous cost optimization. * Teams that want to eliminate the headache of fragmented cloud management tools for different cloud needs. Also want to avoid the complexity, high costs, time consumption, and resource drain of managing multiple platforms - by moving to a single, unified cloud management solution. ### **We address every piece of feedback we receive!** At CloudKeeper, customer feedback doesn’t stop at reviews - it directly influences our product roadmap. Every insight, whether shared on G2 or through direct conversations, has been met with swift action. * **Challenge** : Limited SSO Capabilities **Resolved** : CloudKeeper introduced * **Challenge** : Delayed Data & Limited Real-Time Visibility **Resolved** : Platform performance was enhanced with faster data refresh cycles and improved real-time reporting. * **Challenge** : Limited Personalization Options **Resolved** : CloudKeeper added advanced personalization features that allow teams to tailor views, reports, and experiences to their needs. (Source: Grid® Report for Cloud Cost Management | Winter 2026) ## **#2. IBM Cloudability** **G2 Rating: 4.2/5 (190+ Reviews)** IBM Cloudability (formerly just Cloudability) is a long‑standing FinOps platform that focuses on financial governance for large, multi‑cloud enterprises. It empowers FinOps teams to manage and optimize multi-cloud, AI, and Kubernetes spend. _The satisfaction score is 69._ ### **Key Strengths** * Robust multi-cloud cost reporting and forecasting tools, ideal for large organizations. * Granular budgeting and allocation features that align finance teams with engineering. * Strong presence in enterprise environments for deep analytics and integration capabilities. ### **Limitations (as per****)** Reviewers mentioned issues with data reliability, lack of customization in the reporting feature, and difficulties with the initial setup process, as well as limitations in the rightsizing recommendations and the integration of the container agent with Kubecost. ## **#3. Flexera One** **G2 Ratings: 4.3/5 (120+ Reviews)** Flexera One is a mature cloud cost and IT asset management platform that delivers visibility and optimization across hybrid and multi-cloud environments. _The G2 Satisfaction score is 69._ ### **Key strengths:** * Unified dashboards that consolidate cost data across providers. * Integrates cost insights with broader IT operations workflows. * Well-suited for organizations combining cloud spend with wider software asset management. ### **Limitations (as per****)** Users report that Flexera One has a complex setup process and a steep learning curve, especially for first-time users. Its extensive features require significant time and effort to configure, making onboarding and full adoption challenging. ## **#4. ScaleOps** **G2 Ratings: 4.6/5 (90+ reviews)** ScaleOps is a cloud‑native optimization platform focused primarily on Kubernetes workloads, automating scaling and rightsizing decisions for clusters. _The G2 Satisfaction Score is 91._ ### **Key Strengths:** * Intelligence-driven optimization that helps teams cut waste. * Flexible reporting and budgeting features that appeal to both engineering and finance stakeholders. * Users highlight fast time‑to‑value and meaningful savings with minimal manual tuning once policies are set. ### **Limitations (as per****)** Users report that ScaleOps struggles with performance and scaling on large clusters, often leading to slow load times and maintenance issues. They also mention missing capabilities like observability and export options, a less intuitive UI, and a steeper learning curve due to complex onboarding and feature usability. ## **#5. Spendbase** **G2 Rating: 4.7/5 (120+ reviews)** Spendbase is a unified SaaS and Cloud Spend Management, providing data-driven insights and solutions for spend analysis and management. Their platform streamlines procurement workflows, strengthens financial decision-making, and boosts overall spending efficiency. _The G2 Satisfaction Score is 87._ ### **Key Strengths** * Users appreciate Spendbase’s intuitive interface and seamless integration with existing tools. * Reviews frequently cite meaningful savings driven by vendor negotiations, credits, and license optimizations. * Users value the clear, centralized view of SaaS expenses, making spend tracking and management more efficient. ### **Limitations (as per****)** Users report that Spendbase lacks key features like a mobile app and advanced reporting, along with limited dashboard customization. Integration challenges, complex setup, and a steep learning curve also affect usability - especially for smaller teams, making onboarding time-consuming. ## **#6. Vantage** **G2 Rating: 4.7/5 (65+ Reviews)** Vantage delivers unified cost tracking for engineering-led FinOps, with strong multi-cloud support. _The G2 Satisfaction Score is 84._ ### **Key Strengths** * Strong multi-cloud and data platform integrations for unified cost visibility * Advanced dashboards and granular cost allocation for deep spending insights * User-friendly interface with powerful analytics for proactive cost monitoring ### **Limitations (as per****)** Vantage focuses mainly on cost visibility and analysis. Some users report limited customization, inadequate reporting without extra tuning, and occasional integration challenges. The platform also has a learning curve for advanced features, and pricing can become expensive after the free tier. ## **#7. CAST AI** **G2 Rating: 4.6/5 (160+ Reviews)** CAST AI focuses on automated optimization for Kubernetes clusters, including intelligent node selection, rightsizing, and autoscaling across clouds. _The G2 Satisfaction Score is 73._ ### **Key Strengths** * Multi‑cloud cluster management and spot instance automation support hybrid and multi‑cloud Kubernetes strategies. * Reliable 24/7 customer support with fast issue resolution. * Easy-to-use platform that simplifies Kubernetes management. * Strong cost optimization delivering significant cloud savings without performance loss. ### **Limitations (as per****)** Some users report integration issues that affect cost accuracy and workload optimization. Pricing can be high for smaller clusters, with limited cost transparency, and the platform has a steep learning curve for Kubernetes beginners. ## **#8. DoiT Cloud Intelligence** **G2 Rating: 4.4/5 (75+ Reviews)** DoiT Cloud Intelligence is an intent-aware FinOps platform that extends beyond cost optimization to enhance reliability, performance, and security. It focuses on insight-driven optimization and accountability across cloud resources. _The G2 Satisfaction Score is 60._ ### **Key Strengths:** * Customers benefit from both a well‑rounded cloud cost management toolset and access to cloud experts. * Highly responsive, proactive, and expert customer support * Strong technical guidance and hands-on cloud management assistance ### **Limitations (as per****)** Users express frustration over expensive escalation fees for support tickets, which negatively impact their overall experience. Some users find the billing process complicated, leading to confusion in account management. Users also report that the system is complex, with a difficult learning curve that can take several months to master basic functionalities. ## **#9. CloudZero** **G2 Rating: 4.6/5 (60+ Reviews)** CloudZero differentiates itself by focusing on unit economics - cost per customer, feature, or transaction - so engineering teams can make better product decisions. _The G2 Satisfaction Score is 56._ ### **Key Strengths:** * Accurate and clear cost management with strong visibility into cloud expenses. * Easy to use and implement, with fast, intuitive dashboards. * Effective anomaly detection and supportive customer service. ### **Limitations (as per****)** Some users find CloudZero expensive for smaller teams and note challenges with billing delays. The platform can have a steep learning curve, with complex cost formation rules and configuration processes that may be difficult for less experienced users. It focuses more on insight and accountability, working best for teams that leverage unit economics to drive product and engineering decisions. ## **#10. Vertice** **G2 Rating: 4.6/5 (160 Reviews)** Vertice is a procurement platform for managing SaaS and cloud spend, using workflows and negotiation support to deliver savings and streamline purchasing cycles. _The G2 Satisfaction Score is 62._ ### **Key Strengths** * Easy-to-use platform that improves efficiency and speeds up negotiations. * Strong expert-led vendor negotiations delivering significant cost savings. * Highly responsive, knowledgeable support and SaaS spend management expertise. ### **Limitations (as per****)** Some users report missing features such as vendor assessments and advanced reporting tools. Limited information for stakeholders, integration challenges, platform complexity, and budgeting or payment constraints can also affect the overall experience. ## **Satisfaction Score by Cost Optimization Features** (Source: Grid® Report for Cloud Cost Management | Winter 2026) ## **How to Choose the Right Cloud Cost Management Partner** All 10 cloud cost management tools on G2’s Leader quadrant deliver real value; the “best” fit depends on your mix of clouds, maturity of FinOps practices, and how much automation or expert help you want. But it’s loud & clear that CloudKeeper goes a step further. Choosing CloudKeeper is a wise choice if you’re looking for a true end-to-end cloud cost optimization partner that brings together a powerful platform, guaranteed savings, and deep FinOps expertise. CloudKeeper is trusted by over 400+ customers worldwide - from fast-growing startups to global enterprises. ## **Here is a list of a few key questions you must ask before choosing a Cloud Cost Management Partner** * Does this platform only show my cloud costs - or actively help me reduce them? * Will I get expert guidance along with automation, or just dashboards and reports? * How quickly can I start seeing measurable cost savings? * Can this solution scale with my business as my cloud environment grows? * Does it support my current and future cloud providers and services? * How well does it integrate with my existing workflow & tech stack? * Will my teams actually use it? Is the interface intuitive and easy to adopt? * Does it offer role-based views for the different teams and SSO for seamless adoption? * Can I customize reports and views based on my business needs? * How transparent is the pricing and ROI model? * What level of customer support and ongoing optimization will I receive? ## **Final Thoughts** Cloud cost management isn’t just about trimming bills - it’s about smart decision-making, accountability, and aligning cloud spend with real business value. The cloud cost management tools help any team, from startup to enterprise, rethink how they manage cloud costs day-to-day. Ready to save time, money, and effort? Take the next step by Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 15 15 Table of Contents In 2026, you’d hardly find a large-scale software or digital service entirely hosted on private hardware. However, cloud services are costly, and prices keep rising, while the complexity of infrastructure makes Instances of bill shock were already hurting the bottom line of many digital-native businesses before. Now, AI workloads demand massive compute power. Bills can skyrocket in days, sometimes hours. According to a The coming cloud bill shocks will create an even bigger crater, and that bill shock is exactly what you need to avoid, especially because cloud workloads are rapidly evolving. That’s why we’ve compiled these 12 strategies to prepare you for what’s ahead in 2026. ## **What is cloud cost optimization?** Many organizations mistake The goal of cloud cost optimization is to maximize the value of each dollar that you pay to the cloud provider for your bill. Growth needs fuel, and cloud cost optimization walks that tightrope. The enemies are overprovisioned resources, unused instances, and inefficient architecture. These drain budgets silently. Most teams don’t notice until it’s too late. ## **How AI Will Shape Cloud Cost Optimization** While it’s common to associate AI workloads as the culprit in bill shocks and cost runaways, ### **a) AI-Powered Anomaly Detection** ML models analyze spending patterns across thousands of resources simultaneously. It establishes baselines for normal behaviour, and as a result, unusual spikes get flagged within minutes. Assume a scenario where a misconfigured Auto Scaling group launches 500 instances — in that case, the AI cloud cost optimization tool will catch it long before the bill arrives. These systems learn your usage patterns and get smarter over time. ### **b) Intelligent Rightsizing Recommendations** AI goes deeper than simple alerts. Modern An instance might show 20% CPU usage. But it hits memory limits during specific processing windows. AI catches these patterns. Simple threshold monitoring misses them completely. ### **c) Predictive Cost Forecasting** Machine learning forecasts spending with serious accuracy. Historical usage gets analyzed, seasonal patterns emerge, and as a result, growth trends become visible. You can simulate scenarios before committing resources. Thinking about migrating a workload? AI estimates the cost impact first. No surprises later. ### **d) Automated Resource Optimization** Instances get resized during off-peak hours. Reserved capacity gets purchased at optimal times. Workloads shift to spot instances when appropriate. This runs 24/7. Wouldn’t a human team miss these opportunities at 3 AM on a Sunday? ### **e) Smart Commitment Management** Almost every good AI-cost optimization tool in the market analyzes usage patterns for optimal instance mix. It is also common for those tools to recommend the right balance of on-demand, reserved, and spot instances on top of suggesting which savings plan to purchase. AI Cloud cost management platforms continuously optimize these commitments. Your infrastructure evolves. Your discounts stay maximized. ## **Top 12 Cloud Cost Optimization Strategies for 2026** ### **1. Leverage Cloud Provider Discount Programs** Every major provider offers discount mechanisms. AWS has Google Cloud provides Savings range from 30% to 75% on compute costs. The challenge? Choosing the right commitment level. Overcommitting can result in unused capacity. Undercommit and you leave money on the table. Start with a baseline compute needs analysis where you gauge which workloads run consistently and how much guaranteed capacity you actually need. Partner Purchase Agreements (PPAs) unlock another layer of discounts. In a ### **2. Deploy cloud cost optimization Tools** Visibility is your stepping stone into cloud cost optimization because you can't optimize what you You need to leverage tools that provide real-time dashboards and cost allocation. They show spending patterns with granular detail. Which team owns that expense? Which project burned through the budget? Answers to these questions, which could’ve taken hours to decipher by an analyst, tools can give in seconds. Look for tools with automated remediation capabilities because visibility alone isn't enough. You need action, and that action is taken care of by auto-remediation platforms since they identify waste and fix it automatically. One great example of such a tool is ### **3. Optimize Managed Services, Serverless & Container Workloads** Managed services simplify operations but can become expensive without oversight. They scale up automatically but rarely scale down. #### **Common Overspend Patterns** * RDS databases sized for peak, not average load * OpenSearch clusters that never shrink * Lambda functions are overprovisioned with high memory settings * EKS clusters over-padded due to “safe” pod requests #### **Container & Serverless Optimization** **For Kubernetes (EKS):** * Audit pod requests and reduce buffers * Use autoscalers for pods and nodes * Consolidate workloads to reduce node count * Use efficient node families (Graviton/AMD) **For Serverless (Lambda & ****):** * Adjust memory allocations downward if unused * Use Provisioned Concurrency only where necessary * Migrate long-running or predictable workloads to compute or containers #### **Managed Services (RDS, OpenSearch, Redshift)** * Downsize instances based on real usage * Review replicas—many aren’t needed * Scale down non-production clusters outside peak hours for Managed services often represent silent, recurring overspend, so periodic review is essential. ### **4. Enforce Tagging Across Your Organization** Spinning up and provisioning Without tags, you can't attribute costs accurately. Which department owns that database? Which project uses those storage buckets? You're guessing. And guesswork in cloud cost optimization often spells disaster. Implement a Use automation to enforce tagging policies. Resources without proper tags get flagged or even shut down. Sounds harsh? It works. Teams tag everything when non-compliance has consequences. Tags enable chargeback and showback, allowing teams to see their actual consumption, with the final result being better accountability and, ultimately, a reduced cloud bill. Accountability drives better behaviour, and wasteful practices end when teams are responsible for their own costs. The following are the 5 essential tags you should start with: * _**environment**_ * _**service**_ * _**team**_ * _**business_unit**_ * _**cost_center**_ ### **5. Rightsize Your Resources Continuously** #### **How to Right-Size Compute** **Step 1: Identify Underutilized Resources:** Look for consistently low CPU and memory utilization over 30–90 days. **Signs of oversizing include:** * <30% CPU usage * <40% memory usage * Kubernetes nodes running half-empty * RDS instance classes larger than required **Step 2: Move to Modern Instance Families** Many workloads still run on older instance types due to legacy AMIs or a lack of revalidation. Migrating Linux workloads to: * Graviton (ARM) typically reduces compute cost by 20–40% * AMD-based instances often reduce cost by 10–20% * These changes rarely require architectural redesign. **Step 3: Modernize Your Commitment Strategy** The old “lock RIs for 1–3 years” model is no longer the most efficient. Instead: * Use Compute Savings Plans for flexibility * Use Spot Instances for stateless, interruptible, or burst workloads (CI/CD, analytics, containerized microservices) **Step 4: Right-Size Kubernetes (EKS).** Kubernetes cost is driven by requested resources, not actual usage. To optimize: * Reduce inflated pod CPU/memory requests * Enable Horizontal Pod Autoscaler (HPA) * Use autoscaling for nodes (Cluster Autoscaler / Karpenter) * Choose cost-efficient node families (ARM/AMD) Engineers want flexibility for peak load hours. However, the result? Paying for capacity that sits unused 90% of the time. The better solution is to monitor CPU, memory, network, and storage utilization. Look at patterns over weeks, not days. A database might spike every Monday morning but remain idle for the rest of the week. Rightsizing considers these patterns. Cloud cost optimization tools automate much of this process. They analyze utilization continuously. Recommendations appear automatically. Some platforms even implement changes during maintenance windows. ### **6. Eliminate Idle and Unused Resources** No matter how significant the efforts put into optimizing the cloud, there are often some zombie resources that manage to stay undetected. Developers spin up test instances and forget them. Projects end, but infrastructure remains. Old snapshots accumulate. Unattached volumes pile up. These orphaned resources, over time, start racking up high costs. An idle m5.xlarge instance costs roughly $1,500 annually. Multiply that across hundreds of forgotten resources, and your bill sheets indicate thousands spent on “thin air.” The solution is to implement regular audits. Find resources with zero activity over 30 days. Identify unattached volumes and outdated snapshots. Track instances that haven’t been accessed in weeks. Automation helps tremendously here. Set up policies that flag idle resources automatically. After 14 days of inactivity, resources get tagged for review. After 30 days, they shut down automatically unless someone justifies keeping them. Some teams implement expiration tags. Every resource gets a TTL (time to live). When it expires, automated systems delete it. Encourage your teams to actively extend resources they need and let unused ones expire. ### **7. Optimize Storage Costs Aggressively** Compute and AI instances stay in the limelight for hogging up cloud budgets, but unoptimized cloud storage also contributes to unnecessarily high cloud bills. A few gigabytes here and there seem harmless. Over months, you're paying for terabytes of forgotten data. Implement lifecycle policies on object storage. Move infrequently accessed data to cheaper tiers automatically. S3 Intelligent-Tiering, Azure Blob Storage access tiers, and Google Cloud Storage classes all offer this capability. This should be followed by a review of your snapshot retention policies. Analyze whether you really need daily snapshots kept for a year. Since most compliance requirements are less stringent than teams assume, you need to reduce retention periods and delete obsolete snapshots. Here are more storage cost optimization strategies you should implement: #### **Convert All GP2 Volumes to GP3** A direct, no-risk cost reduction: * ~20% cheaper * Configurable performance * No app changes required #### **Clean Up Snapshots & Orphaned Volumes** Regularly remove: * Unattached EBS volumes * Old EBS snapshots * Excess S3 versions ### **8. Leverage Spot and Preemptible Instances** It’s no secret that spot instances are priced up to 90% lower than similarly configured instances you would have bought from the regular on-demand market. The catch? Cloud providers can reclaim them on short notice. Containerized applications with orchestration handle spot instances naturally. Kubernetes can manage spot and on-demand nodes together, and when spot instances terminate, workloads shift to regular instances automatically. Start small if you're nervous. Run a single non-critical workload on spot instances, and as you gain confidence, move a step forward with fault-tolerance verification through chaos engineering experiments, node-drain simulations, interruption notices, and controlled spot interruption testing using AWS Fault Injection Simulator or GCP’s Spot VM preemption signals. ### **Real-World Example: How SmartNews Cut AWS Costs by 50% Without Sacrificing Performance** SmartNews, a global news-aggregation platform, migrated its backend and ML workloads to a combination of Spot Instances + 50% cost savings on their main compute workload. 15% cost reduction on ML workloads, specifically by moving to Latency dropped from 190 ms to 60 ms — meaning their performance actually improved while costs dropped. They dynamically scaled their infrastructure based on demand. For ML inference and news feed workloads, they used This is a perfect example of cloud cost optimization + performance enhancement done right. ### **9. Implement FinOps Practices and Governance** Cloud cost optimization requires cultural change. You can bring in the best tools, perform all sorts of Create a FinOps team or designate champions and assign them the task of embedding cost consciousness across the organization, which gives you enhanced visibility, education, and accountability. Establish budgets and alerts at project and team levels. When spending approaches limits, stakeholders get notified. The cumulative result of this entire exercise is that you’ll accurately predict the next bill you’ll get in the cycle — and beyond prediction, it will be a smaller number too. Eventually, once the ### **10. Optimize Network and Data Transfer Costs** Network costs surprise many teams because data transfer charges accumulate quickly, especially cross-region or outbound to the internet. Keep data and compute in the same region whenever possible, since cross-region transfer adds up fast; architect your applications to minimize unnecessary data movement. Use Content Delivery Networks (CDNs) strategically. Serving static assets through Reduce NAT Gateway egress by creating VPC Endpoints (AWS PrivateLink) for commonly used services such as Amazon S3, DynamoDB, CloudWatch, STS, and Amazon ECR. This avoids NAT and removes unnecessary per-GB charges. Use Amazon CloudFront to serve public content instead of delivering it directly from EC2 or S3, as this helps reduce data transfer costs, improves global latency, and requires no application changes. Minimize cross-AZ traffic by using Multi-AZ deployments only where necessary, such as in production environments, while keeping Dev, Test, and Analytics workloads in a single Availability Zone. Review your architecture for inefficient data flows. Services calling each other across regions or databases being queried from distant locations silently inflate costs, so consolidate those interactions wherever practical. Private connectivity options like AWS PrivateLink, Azure Private Link, or Google Private Service Connect are not only more secure but also cheaper than public internet transfer, which makes them an obvious choice for both security and cost. ### **11. Automate Cost Governance and Resource Lifecycle Management** In 2026, don’t be surprised by the complexity your cloud infrastructure has grown into since it was first deployed. With this increased complexity, it’s no longer feasible to rely solely on manual cloud cost management and oversight. Choose automation mechanisms to handle repetitive optimization tasks. Through automation tools and practices such as (LIST), you can manage scheduled shutdowns, automated rightsizing, policy enforcement, and compliance checks. CI/CD pipelines, synonymous with The initial setup to configure automation tools will require engineering time and expertise, but the cloud savings and efficiency gains over time make it worthwhile. ### **12. Continuous Monitoring and Adaptive Optimization** Since cloud cost optimization is an ongoing process due to the ever-evolving nature of cloud, what worked last quarter will not necessarily work this quarter. As a business, you need to stay on top of the latest offerings from your cloud provider in terms of pricing and services. For monitoring your existing setup, set up Review your strategies quarterly. What new features are providers offering? How have your workloads changed? Which optimizations delivered results? Where should you focus next? ## **Optimize your Cloud Costs with CloudKeeper** We at CloudKeeper are well aware that cloud cost management can be overwhelming. Managing multiple providers, complex pricing, and constant changes requires proactive effort and significant bandwidth. CloudKeeper takes that hassle off your hands. Our offerings combine AI-powered optimization with ## **Conclusion** Your cloud cost optimization journey should start with the quick wins. Implement discount programs. Deploy monitoring tools. Eliminate obvious waste because early momentum builds organizational support for bigger changes. Once you have laid the groundwork, proceed to AI-powered optimization, comprehensive governance, and continuous automation to further solidify and deeply infuse cloud cost awareness and With the right approach and cloud cost optimization tools, you can keep a leash on your spending while never compromising system reliability or performance. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents ## **Introduction** As organizations head into 2026, Agentic AI is rapidly emerging as one of the most important shifts in enterprise automation. Artificial intelligence is no longer limited to generating content, summarizing information, or assisting users through chat interfaces. Organizations are now moving toward autonomous, goal-driven systems that can reason, act, and adapt across complex enterprise environments and enterprises are deploying autonomous AI agents that can plan, decide, and execute actions across complex systems with minimal human intervention. This evolution reflects a broader realization across industries - traditional automation has reached its ceiling. Rule-based systems struggle in dynamic environments, while human-dependent workflows slow execution. Agentic AI addresses these constraints by enabling continuous execution and adaptive decision-making across systems. This transition marks a fundamental change in how work gets done. Automation is no longer scoped to individual tasks, agentic AI enables end-to-end execution of workflows, spanning cloud operations, finance, IT, security, and software delivery. The result is faster execution, According to Gartner, by 2026, 40% of enterprise applications are expected to embed task-specific AI Agents, up from low single-digit adoption just a few years ago. This signals a decisive move from experimentation to operational deployment of Agentic AI. What makes 2026 a turning point is not theoretical progress, but operational readiness. Enterprises now have the architectures, governance models, and orchestration capabilities required to deploy AI agents in production environments without sacrificing control or accountability. As a result, agentic AI is moving out of experimentation and into the core operating fabric of modern enterprises. This blog explores the top Agentic AI trends to watch in 2026, focusing on enterprise-scale impact, governance, and real-world execution rather than speculative use cases. ## **What Is Agentic AI** Agentic AI refers to intelligent systems capable of autonomously pursuing objectives rather than simply generating outputs. An AI agent interprets goals, plans actions, uses tools or APIs, and adapts behavior based on outcomes or changing conditions. This capability differentiates agentic AI from earlier automation approaches: * Rule-based automation follows predefined logic * Generative AI produces content or recommendations * Agentic AI executes decisions and actions In enterprise environments, this distinction is critical. AI agents operate across systems, not within isolated applications. As noted by IBM in its enterprise AI outlook, the next phase of AI maturity is defined not by intelligence alone, but by the ability to act across tools and workflows with accountability. _(Recommended reading:__)_ ## **Why 2026 Marks a Structural Shift** Multiple forces converge in 2026 to accelerate Agentic AI adoption. Enterprises face increasing operational complexity, margin pressure, and talent constraints. At the same time, orchestration frameworks, governance models, and observability platforms have matured. The acceleration of agentic AI adoption in 2026 is driven by multiple enterprise realities. Microsoft’s AI roadmap points to a shift beyond assistive copilots toward autonomous systems that operate across business applications. At the same time, Google Cloud’s enterprise AI research shows organizations favoring AI that can act across tools and platforms, not models limited to generating outputs. Together, these trends explain why enterprises are Three patterns are now consistently visible across industries * AI Agents are moving from pilots into production systems * Execution authority is expanding beyond insights and recommendations * Enterprise platforms are being redesigned for autonomous execution Together, these shifts position 2026 as a clear inflection point for agentic AI. ## **Top Agentic AI Trends to Watch in 2026** 1. **Task-Specific Agentic AI Becomes Native to Enterprise Software** By 2026, Agentic AI is no longer something enterprises “add on.” It is built directly into core platforms. Organizations are deploying task-specific AI agents that take ownership of clearly defined responsibilities inside everyday enterprise systems. These AI agents manage functions such as These AI agents handle functions such as: * * Security incident remediation * Financial reconciliation and monitoring **2. AI Agents Transition From Assistive Tools to Autonomous Decision Engines** One of the clearest developments in 2026 is the progression of AI Agents beyond assistive roles. Instead of supporting human decisions, agentic systems are increasingly trusted to make decisions within well-defined boundaries. Agentic AI evaluates trade-offs, executes actions, and learns from outcomes. Humans stay involved, but their role shifts toward oversight, exception handling, and strategic direction. This operating model allows autonomous execution across high-volume environments where constant approvals would otherwise slow the business down. **3. Multi-Agent Orchestration Becomes the Enterprise Control Plane** As enterprises deploy dozens or hundreds of AI agents, coordination becomes critical and essential. Agentic AI orchestration platforms function as enterprise control planes, governing how AI agents collaborate, escalate issues, and comply with policies. These orchestration layers manage: * Task allocation across agents * Inter-agent communication * Conflict resolution * Policy enforcement Instead of isolated automation, enterprises operate scalable agent-based architectures where specialized AI agents work together toward shared objectives. In cloud environments, this orchestration layer becomes especially critical. Enterprises operating across **4. Low-Code Platforms Expand Access to Agentic AI** Agentic AI development is no longer limited to specialized engineering teams. Low-code and no-code platforms are enabling business users to design and deploy AI agents aligned with real operational needs. This change accelerates adoption while keeping Agentic AI initiatives close to the business. Domain experts can translate real-world processes into autonomous execution models or Intelligent process automation without long development cycles, ensuring Agentic AI delivers practical value rather than theoretical capability. **5. Real-Time Data Integration Enables Continuous Execution** Agentic systems are most effective when they operate on live data. Agentic AI systems gain significant effectiveness when connected to This capability is especially relevant in: * Cloud operations * IT monitoring * Financial oversight This capability moves enterprise operations from periodic review to continuous execution, allowing organizations to act before issues escalate rather than reacting after impact. **6. Human-in-the-Loop Governance Becomes the Standard Operating Model** Greater autonomy does not mean removing humans from the process. Instead, enterprises are formalizing human-in-the-loop governance as the standard operating model for Agentic AI. AI agents execute actions independently within defined thresholds, while humans intervene in high-risk, ambiguous, strategic or exceptional scenarios. Governance is embedded directly into workflows rather than layered on afterward, ensuring accountability scales alongside autonomy. This model is particularly important in cloud operations, where unrestricted autonomy can increase risk. Agentic AI enables AI agents to act independently on routine cloud decisions, such as resource scaling or cost controls, while escalating higher-risk actions for human review. This balance allows enterprises to **7. Interoperability Enables Scalable Multi-Agent Ecosystems** As AI agents spread across tools and platforms, interoperability becomes essential. Agentic AI architectures increasingly prioritize shared context, standardized communication, and cross-platform coordination. This foundation allows enterprises to build scalable multi-agent ecosystems without locking themselves into a single vendor or framework. Modular, interoperable designs ensure agentic systems can evolve as enterprise needs change. **8. Agentic AI Shifts Cloud Cost Optimization From Visibility to Execution** One of the most immediate and measurable applications of agentic AI in 2026 is cost optimization. Autonomous AI agents continuously monitor usage, rebalance resources, and enforce policies particularly in cloud environments. Capabilities such as real-time For many organizations, cost-focused agentic AI initiatives become the foundation for broader automation programs. **9. AI Agents Extend Into Governance, Risk, and Compliance** As autonomy increases, enterprises embed governance logic directly into agentic AI workflows. AI agents increasingly handle: * Policy enforcement * Audit readiness * Continuous risk monitoring This approach enables governance-first AI execution, where compliance and control scale alongside automation rather than restricting it. **10. Workflow Redesign Around Agentic AI Drives the Largest Gains** The greatest value from agentic AI comes not from incremental automation but from redesigning workflows around autonomous execution. In advanced operating models, AI agents own end-to-end workflows, while humans focus on strategic oversight, exception management, and continuous improvement. This creates ## Agentic AI vs. Generative AI Generative AI produces outputs but Agentic AI produces outcomes/Generative AI stops at outputs but Agentic AI is measured by outcomes | **Dimension** | **Generative AI** | **Agentic AI** | | --- | --- | --- | | Primary Function | Content Generation | Autonomous Execution | | Human Role | Prompting and Refinement | Governance and Oversight | | Integration | API- Based | Workflow-embedded | | Business Impact | Productivity Improvement | End-to-end automation | ## Preparing Enterprises for Agentic AI at Scale As agentic AI becomes foundational, enterprises must prioritize execution discipline over experimentation. Successful deployments focus on: * Orchestrated multi-agent execution * Enterprise-grade automation at scale * Policy-driven * AI-driven operational visibility Organizations that design systems around agentic execution gain compounding advantages over time. ## Agentic AI in Action: Cloud Cost Optimization with CloudKeeper A practical example of execution-led Agentic AI is cloud cost optimization. At CloudKeeper, LensGPT helps enterprises move beyond fragmented cost analysis toward continuous, intelligent decision-making. By integrating Agentic AI into daily workflows, enterprises not only optimize costs but also lay the foundation for broader autonomous operations. Explore how LensGPT can transform your cloud management and unlock the full potential of Agentic AI. Agentic AI is no longer experimental. It is operational, measurable, and essential for enterprise competitiveness in 2026 and beyond. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Amazon Web Services has maintained its position as a leader in the cloud market and is way ahead of the other cloud providers. This makes **AWS cloud certifications** the most sought-after certifications by IT professionals. An internationally recognized accreditation that validates IT professionals' AWS skills and expertise is the AWS (Amazon Web Services) Certification. This cloud certification program comprises key domains, including various aspects of AWS cloud computing such as architecture, development, and operations. The individuals who hold the top AWS certifications are in high demand in the industry due to the increased cloud adoption. One must become an AWS-certified individual to evaluate an individual’s ## **Advantages of obtaining an AWS certification** 1. **Skills Credibility Certification -** Getting top AWS certifications indicates expertise in the technical skills involved in cloud computing and cloud cost management. Earning top AWS certifications provides added value to the organization above and beyond the certification cost. 2. **Competitive advantage -** As companies build their cloud infrastructure, an AWS-certified person has a competitive advantage over others in the eyes of the organization as well as customers. One of the greatest advantages of doing cloud certification is that it helps to close skills gaps and stay up to date with the latest technology. 3. **Enhanced job effectiveness -** To make a promising career in AWS, AWS cloud certification are considered the most credible accreditation. So, cloud cost management certifications play a crucial role in enhancing job effectiveness and productivity. AWS-certified professionals are faster in troubleshooting the issues, and meeting the client requirements. Cloud computing companies prefer to invest in candidates with top AWS certifications. ## **Key AWS Certifications** The following are a few top AWS certifications available on the 1. **AWS Certified Cloud Practitioner** - This certification accesses cloud fluency and foundational AWS knowledge. This AWS Certification journey is for individuals with no prior IT or cloud experience. It is also for those individuals who want to switch to a cloud computing career. 2. **AWS Certified Data Engineer - Associate** - This certification evaluates the candidate's knowledge of core data-related AWS services. It includes areas such as the ability to monitor and troubleshoot issues, implement data pipelines, cost optimization, and performance optimization. 3. **AWS Certified Developer - Associate** - This AWS cloud certification showcases an understanding of core AWS services and their uses. This cloud certification involves basic AWS architecture best practices, and skills in developing, deploying, and debugging cloud-based applications using AWS. 4. **AWS Certified Solutions Architect - Associate** - This cloud certification is useful for individuals who want to demonstrate their AWS technology knowledge and skills. This cloud certification mainly focuses on 5. **AWS Certified SysOps Administrator - Associate** - This credential cloud certification helps organizations identify and develop talent with critical skills for implementing cloud initiatives. ## **AWS certifications accelerate career advancement** To validate one’s expertise in technology, certifications have proven to be an excellent way and AWS cloud certifications have become globally recognized. IT professionals pursue these cloud cost management As many organizations are heavily investing in **This is a major reason why AWS certifications are associated with some of the highest salary-paying jobs in the Cloud industry.** Moreover, for making careers in AWS, these cloud certifications can prove to be a great start. ## **Different paths and levels of AWS certifications** AWS has categorized all the cloud certifications– **Foundational, Professional, Associate, & Specialty**. These AWS certifications are categorized based on different skill sets & levels of expertise within the AWS platform. 1. ### **Foundational** Foundational certifications are suitable for individuals new to the AWS cloud. This certification level helps in getting a comprehensive **For this certification, no prior experience is required.** 2. ### **Professional** Professional certifications are ideal IT certifications for experienced individuals to demonstrate their expertise in a specific field. To clear a professional certification, candidates must showcase their ability to design & implement advanced AWS solutions. **2 years of prior AWS Cloud experience is recommended.** 3. ### **Associate** This AWS cloud certification level is ideal for individuals who possess complete knowledge of at least one AWS service. The AWS Associate certification is further divided into different sections - Solutions Architect, Developer, and SysOps Administrator. Solutions Architect certification lays focus on designing & deploying scalable fault-tolerant systems. The Developer certification emphasizes building & maintaining applications based on AWS whereas the SysOps Administrator certification covers deployment, management, & operating systems on AWS. **Prior cloud and/or strong on-premises IT experience is recommended.** 4. ### **Specialty** This AWS certification specializes in fields like big data, machine learning, & security. **For this exam, refer to the exam guides on the exam pages for recommended experience.** ## **Conclusion** Pursuing the top AWS certifications gives a great opportunity to start and gain expertise in the AWS cloud industry. Cloud Professionals with one or more cloud certifications are an asset to the organization and are beneficial in terms of career growth and good salary compensation. CloudKeeper is an AWS premier partner and has 300+ Cloud & DevOps professionals who have 12+ years of experience in Cloud. _Seeking career opportunities in the cloud?__for the latest job postings._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents Cloud computing has evolved into a fundamental element for contemporary businesses, with Amazon Web Services (AWS) recognized as the leading cloud solution for organizations around the globe. Nonetheless, the adaptability and scalability that AWS offers can lead to unpredictable expenses. As organizations expand, it becomes essential to manage cloud costs effectively, which is where AWS cost optimization tools are beneficial. This blog examines the top AWS-native and third-party tools providing advice on selecting the most suitable AWS cost optimization tool for your setup that eventually helps in ## **AWS Built-in Tools for Cloud Cost Optimization** AWS provides several integrated tools to assist organizations in tracking, managing, and cloud cost optimization. Below is a summary of the most effective options available: * ### **AWS Cost Explorer** **Function:** Analyzing and visualizing cloud costs and usage. With AWS Cost Explorer, businesses can thoroughly examine their AWS spending habits. One of the most helpful AWS cost optimization tools, featuring elements such as resource-level granularity and forecasting, organizations can pinpoint cost trends and **Key Features:** * Comprehensive reports on costs and usage. * Suggestions for Reserved Instances (RIs) and Savings Plans. * Forecasting capabilities extend up to 12 months for future expenses. Source: * ### **AWS Budgets** **Function:** Establishing and overseeing tailored cost and usage budgets. AWS Budgets assists organizations in remaining within their cloud spending by allowing them to set limits and receive notifications when expenses surpass specified thresholds. **Key Features:** * Alerts for cloud cost monitoring and usage. * Compatibility with AWS Cost Explorer for in-depth analysis. * Tracking budgets for AWS Reserved Instances and Savings Plans. Source: * ### **AWS Trusted Advisor** **Function:** Thorough insights on **Key Features:** * Suggestions for idle or underused resources. * Notifications for surpassing service limits. * Evaluations for security and fault tolerance. Source: * ### **AWS Compute Optimizer** **Function:** Enhancing compute resources for optimal performance and cost savings. AWS Compute Optimizer leverages machine learning to suggest the most suitable EC2 instance types, helping you avoid overprovisioning. **Key Features:** * Customized recommendations for EC2, Lambda, and Auto Scaling. * Practical insights for boosting workload efficiency. Source: * ### **Amazon S3 Intelligent-Tiering** **Function:** This storage class automatically transitions data to the most economical tier based on access trends, removing the need for manual adjustments. **Key Features:** * Automated tiering for data accessed infrequently. * Reduced retrieval fees for objects that are not often accessed. * No operational management is required. ## **Selecting the Appropriate AWS Cost Optimization Tool for Your Cloud Setup** With a variety of choices on the market, picking the ideal AWS cost optimization tool necessitates a thorough assessment. Here are some important aspects to take into account while selecting the AWS cost optimization tool: * **Size and Complexity of the Cloud** For smaller environments, AWS-native tools may be adequate. However, for larger and more intricate infrastructures, tools like CloudKeeper offer enhanced analytics and automation. * **Financial Constraints** Organizations operating on tight budgets should start with AWS-native options. Nonetheless, putting funds into third-party AWS cost optimization tools like CloudKeeper can lead to significant cost savings over time. * **Requirements for Multi-Cloud** If you engage in a multi-cloud setup, tools from third-party vendors that support * **Degree of Automation** Companies looking for minimal manual involvement should focus on tools that provide strong automation features, such as CloudKeeper Lens for budget management and CloudKeeper Auto for ## **The Increasing Demand for Comprehensive AWS Cost Optimization Tools** Although tools native to AWS are great for initial cost monitoring, organizations today need a more comprehensive approach to optimize their cloud costs, which are more aptly offered by comprehensive cloud cost partners and AWS Cost Optimization Tools. The * **Rising Cloud Expenditures** As companies expand, expenses associated with cloud services can escalate rapidly without adequate supervision. Comprehensive AWS cost optimization tools deliver insights into expenditures, enabling organizations with granular * **Disjointed Systems** Utilizing various tools for different facets of cost management—such as budgeting, resource utilization, and reporting—leads to inefficiencies. Unified solutions optimize processes, minimizing operational burdens. * **Heightened Cloud Complexity** Contemporary architectures frequently involve multi-cloud environments, microservices, and containerized applications. All-encompassing tools facilitate cost management in these intricate configurations. * **Insufficient Transparency** In the absence of integrated dashboards, businesses find it challenging to pinpoint underutilized resources or instances that are over-provisioned. Comprehensive AWS cost optimization tools provide an overview of all cloud operations. * **Requirement for Automation** Manual tasks are labor-intensive and susceptible to mistakes. Automation is crucial for activities like optimizing resource sizes, evaluating usage trends, and implementing cost-saving measures. The adoption of automation in the FinOps space is expected to grow quickly. Over 35% of organizations anticipate an increase in automation practices, driven by the limitations of current tools and the lack of a comprehensive approach from providers. * **Challenges in Scalability** As workloads increase, the necessity for scalable cloud cost optimization methods becomes essential. Comprehensive tools adjust to growing demands, ensuring ongoing efficiency. * **Improved Decision-Making** All-inclusive tools deliver actionable insights, empowering organizations to make well-informed choices regarding infrastructure modifications, purchasing commitments, and optimization plans. * **Efficiency Gains** Overseeing cloud expenses manually can detract focus from primary business objectives. By automating and consolidating processes, comprehensive solutions allow more time for innovation and strategic pursuits. * **Regulatory Compliance and Governance** As regulatory demands grow, companies require tools that not only optimize expenditures but also maintain compliance and * **Investing for the Future** Comprehensive tools offer the adaptability to progress alongside technological advances and business requirements, making them a valuable investment that aligns with the organization's growth. ## CloudKeeper: A Comprehensive Solution that Offers More than Just Savings CloudKeeper provides value by integrating advanced tools with expert assistance to help organizations maximize cloud cost savings and optimize cloud operations. Here’s what differentiates CloudKeeper: **Unlimited Cloud Support** * Gain access to dedicated cloud specialists who offer * Proactively manage your cloud environment to eliminate inefficiencies and address issues before they grow. * Customized advice on utilizing AWS, Microsoft Azure, and Google Cloud features to enhance cost-efficiency and performance. **Guaranteed Savings on Costs** * Utilizes the power of collective purchasing and management of commitments to obtain greater discounts. * Ensures predictable and steady savings on your cloud expenses, regardless of the size of your operations. * Personalized strategies for cloud cost optimization tailored to your specific cloud usage and business objectives. **Improved Cloud Cost Visibility of Cloud Costs** * A thorough analytics and reporting platform to monitor and comprehend cloud expenses. * In-depth insights into resource usage, spending trends, and opportunities for optimization. * Clear and actionable information to make educated decisions and eliminate unnecessary expenditures. With these strong features, CloudKeeper enables businesses to lower costs, enhance efficiency, and fully realize the benefits of their cloud investments. ## **Case Study: Damstra's Cost Transparency & Optimization** Damstra, a leading provider of enterprise protection and safety solutions in Australia realized an ## **Case Study: eLocal's Journey to Cost Visibility & Optimization ** eLocal, a seasoned marketing company in the US collaborated with CloudKeeper to improve their cloud expenditures and boost operational effectiveness. They realized an initial 10% decrease in AWS costs, followed by an ## **Conclusion** As the adoption of cloud technology increases, effectively managing costs in AWS is becoming essential. Built-in AWS cost optimization tools such as AWS Cost Explorer and Compute Optimizer offer basic functionalities, but third-party options like CloudKeeper provide a more thorough approach to optimizing expenditures. By leveraging both native and external solutions, organizations can realize substantial savings, improve cloud performance, and meet their financial objectives. Get the appropriate tools today to ensure an economical cloud experience in the future. With CloudKeeper Lens, you are not merely overseeing costs—you are creating value. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents Maximizing the value of cloud investments and ensuring alignment with strategic objectives is an ongoing challenge for many businesses. But, before we deep-dive into the realm of setting FinOps Key Performance Indicators(KPIs), let’s start by asking yourself the following questions: * Do you have a comprehensive understanding of your current cloud costs and cloud kpis? * Is your cloud cost allocation aligned with critical business units, cost centers, applications, and projects? * What specific business goals are you aiming to accomplish through FinOps? * Are you equipped with the necessary skills and resources, or do you identify any gaps that need to be addressed? * Is your IT department encountering challenges in identifying the ownership of cloud costs? * How well does your cloud spending align with your business requirements? These are a few fundamental questions that organizations must address before starting with the process of performance and benchmarking in FinOps. Undertaking a thorough assessment of your current IT environment and cloud ecosystem is the crucial first step towards gaining visibility and control over your cloud spending. This evaluation lays the foundation for your cloud financial management journey ahead. ## **FinOps Key Performance Indicators(KPIs): The guiding beacons of your FinOps strategy** A report by So what is the solution? FinOps, of course! FinOps has emerged as a critical discipline that empowers organizations to optimize their cloud spending while aligning it with their business objectives. FinOps enables teams to make informed trade-offs between speed, cost, and quality by bringing accountability to the cloud operating model. Every organization can have a The success of FinOps relies on key performance indicators (KPIs). FinOps KPIs are the true guiding beacons of your FinOps strategy allowing you to navigate your cloud investments with confidence, making informed decisions and course corrections along the way. As your cloud usage grows, it becomes increasingly important to measure and track the efficiency of your cloud consumption. Some of the prominent benefits of FinOps KPIs are: * Make data-driven decisions with improved business insights. * Improved financial performance and resource allocation. * Long-term success and enhanced customer satisfaction. * Gain a competitive advantage with quantifiable data. * Achieve business objectives by measuring targets. ## **Understanding Critical FinOps KPIs and their objective** Let's delve into some of the top Cloud FinOps KPIs that can propel companies toward greater financial success. The FinOps KPIs are categorized into three to drive results in all aspects of your cloud ecosystem. ### **Cloud Visibility KPIs** To effectively address any challenges, it is crucial to first identify them. Cloud visibility key performance indicators (KPIs) play a vital role in offering valuable insights into an organization's cloud infrastructure, facilitating appropriate resource allocation and efficient management of cloud costs. Without comprehensive visibility across all cloud environments, it becomes extremely difficult to enhance governance. Here are some important KPIs to consider when measuring visibility: * #### **Percentage of resources with proper tagging** Proper tagging ensures that resources are categorized and organized effectively, allowing for easier management, cost allocation, and resource tracking. The higher the percentage of * #### **Percentage of bill from untagged resource** Untagged resources make it difficult to allocate costs accurately and identify the specific purpose or owner of each resource. By tracking this percentage, you can identify areas where tagging compliance is low and take steps to improve visibility and cost management. * #### **Total spend against the cost of cloud resources per team** It helps identify teams with high or low cloud resource utilization compared to their allocated budget. You can optimize resource allocation, detect potential overspending, and align spending with business priorities by tracking this metric. * #### **Percentage of Waste** Firstly, to assess the percentage of cloud resource waste, it is necessary to define and categorize different types of waste within the cloud environment. This KPI can be calculated by determining the cost of unused and over-provisioned cloud resources as a percentage of the total cost. It helps identify potential cost savings by highlighting resources that can be right-sized, terminated, or optimized to eliminate unnecessary expenses. * #### **Forecast accuracy** Forecast accuracy is a FinOps KPI that helps refine future predictions, optimize resource planning, and enhance Below are the recommended thresholds by the 1. For FinOps practices operating at Crawl maturity, variance from actual spending cannot exceed 20%. 2. Variance of 15% for a FinOps practice operating at Walk maturity. 3. Variations of 12% for FinOps practices operating at Run maturity. * #### **Security incidents over a specific period by the team** This FinOps KPI tracks the number of security incidents or breaches within specific teams or departments over a given period. It helps measure the effectiveness of security measures, identify potential vulnerabilities, and evaluate the overall ### **Cloud Cost Optimization KPIs** Optimizing your cloud environment goes beyond just cloud cost considerations. It also involves operational efficiency and security enhancements. By focusing on key performance indicators (KPIs) for cloud optimization, organizations can achieve a well-rounded approach that balances * #### **Effective cloud cost per resource** This metric helps you identify cost outliers and areas where you can optimize your resources. By monitoring this metric, you can make cost-conscious decisions and ensure that you are using your resources efficiently. * #### **Percentage of money saved on Reservations, Savings Plans, or Committed Use Discounts against the total cost of cloud resources** It helps you identify the percentage of your total cloud resource costs that are covered by Reservations, Savings Plans, or Committed Use Discounts. A higher percentage indicates that you are effectively utilizing these cost-saving options, resulting in significant savings on your * #### **Cloud usage pattern on weekdays vs weekend** Businesses that experience variable cloud usage can save money by optimizing their spending on weekends versus weekdays. This can be done by shutting down or scaling down non-essential workloads on weekends. To identify opportunities to optimize weekend spend, businesses should * #### **Percentage change in the cost of cloud resources over time (%)** The percentage change in the cost of cloud resources over time measures the rate of cost fluctuation in your cloud environment. It provides insights into how the cost of your cloud resources is changing over a specific period, allowing you to assess the efficiency of your cost management efforts. * #### **Mean Time to Recovery (MTTR)** This metric measures how long it takes you to fix * #### **Percentage of infrastructure running on demand** This metric measures how much of your infrastructure is using on-demand pricing. On-demand pricing is the most expensive option, so you should try to move as much of your infrastructure as possible to discounted pricing options, such as reserved instances or savings plans. * #### **Reverted cloud deployments** This metric measures how often you have to roll back cloud deployments. A high number of reverted deployments indicates that there are problems with your deployment process. You should identify and fix these problems to reduce the number of reverted deployments. * #### **Meeting SLAs and uptime goals** This metric measures how well you are meeting your service level agreements (SLAs) and uptime goals. By monitoring this metric, you can identify areas where you need to improve your performance and ensure that you are meeting the expectations of your customers. ### **Cloud Governance and Automation KPIs** Cloud Governance and Automation KPIs are vital in upholding control and ensuring compliance throughout your cloud infrastructure. By tracking specific metrics, you can assess adherence to policies, automate processes, and enhance security. Here are some of the top FinOps KPIs for cloud governance and automation: * #### **Percent of policies in a compliant state** This metric measures how well your cloud environment is aligned with your organization's policies. A high percentage indicates that your environment is well-managed and secure. * #### **Cost-optimized per policy over time** It measures the cost optimization achieved for each specific governance policy implemented within your organization's cloud environment. It evaluates the impact of individual policies on reducing costs and tracks the effectiveness of cost-saving measures over a period of time. For example - Let's say an organization implements a policy to automatically shut down idle instances after a certain period of inactivity. Over time, they track the cost savings achieved by this policy. By monitoring this KPI over several months, they can assess the long-term effectiveness of the policy in optimizing costs. * #### **Number of reservations automated** This metric measures the number of cloud resources that are automatically reserved. A high number indicates that you are taking advantage of reserved pricing, which can save you money. * #### **Time to Resolve Security Issues** This KPI measures the average time taken to remediate security violations or vulnerabilities in your cloud environment. Monitoring this metric allows for timely response and prompt resolution of security concerns, reducing potential risks. * #### **Time saved as a result of policies** Tracking this KPI highlights valuable insights into the time saved due to policies and provides a tangible measurement of the benefits derived from governance policies. To measure this KPI starts with establishing baseline metrics that determine the average time spent on each identified task before policy implementation or automation. Post that Implement policies, rules, or automated processes to streamline and enforce desired behaviors or actions. For example, implement compliance checks through automated audits. The difference between the baseline time and the actual time spent represents the time saved as a result of policies. ## **Key things to keep in mind while setting FinOps KPIs** **Be S.M.A.R.T** : Ensure your FinOps KPIs are Specific, Measurable, Achievable, Relevant, and Time-Based. **Frequently Review and Update KPIs:** Keep your FinOps KPIs dynamic by frequently reviewing and updating them as your business evolves. Cloud financial management needs may change over time, so ensure your KPIs remain relevant and aligned with current priorities. **Communicate and Share Insights:** Regularly communicate FinOps KPI progress and insights to relevant stakeholders across the organization. This facilitates transparency, collaboration, and informed decision-making at all levels. **Don't just focus on cost:** Look beyond cost alone and measure efficiency when evaluating **Rely on Data:** Your KPIs should be data-driven and supported by evidence-based reasoning. Avoid making assumptions, as they can lead to failure or suboptimal results. Base your FinOps KPIs on reliable data to make informed decisions. In this journey, partnering with a FinOps expert can provide valuable support. _to discover how CloudKeeper can help you in your_ _Journey._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 23 23 Table of Contents As we approach the new year, it’s essential to take a closer look at the cloud computing trends in 2025 and cloud computing statistics that will shape the future of the industry. These cloud computing trends are not only transforming businesses today but will continue to dominate decision-making and strategy for the years ahead. ## **The Cloud Adoption Statistics** Cloud adoption has been growing at an unprecedented pace. The research shows a noteworthy cloud computing trend which is the surge in SaaS investments. Cloud-based applications, especially Software-as-a-Service (SaaS) solutions, dominate this spending, with investments nearing $300 billion in 2025, up from just over $250 billion in 2024. Meanwhile, infrastructure and platform services are the fastest-growing segments, with spending anticipated to jump by 25% and 22%, respectively. **Source: Gartner** ## **The Emerging Cloud Computing Trends & Statistics for 2025 & beyond** * ### **Cloud cost optimization will continue to be a critical topic in boardroom discussion** Cloud cost optimization has firmly established itself as a key topic in boardroom discussions, and its significance shows no signs of waning as we look toward 2025 and beyond. As we’ve emphasized in our Source: Taken from What’s particularly noteworthy is the involvement of senior leadership—SVPs, VPs, Directors, CIOs, and CTOs—actively driving FinOps initiatives. 86% of Senior Vice Presidents (SVPs) and 80% of Vice Presidents (VPs) are actively involved in their organization’s FinOps activities. Their engagement underscores how critical optimizing cloud investments has become for achieving organizational goals and maintaining competitive advantage. The next in cloud computing trend is a paradigm shift in the cloud cost optimization approach, with the focus being on long-term & sustained cost efficiencies. * ### **Long-Term Cloud Cost Optimization: A Strategic Priority** As cloud adoption matures, organizations are moving beyond the initial goal of quick The Everest Group survey highlighted that “The growing maturity of cloud adoption has shifted the focus from immediate cloud cost savings to sustained cloud cost optimization through a structured methodology for continuous monitoring, analysis, and adjustment of cloud costs, ensuring long-term efficiency." The instant savings in cloud cost optimization come with certain limitations, such as short-term focus and lack of scalability. Also, the mindset of immediate cloud cost savings restricts you from investing in new technologies and tools. This makes Long-Term Cloud Cost Optimization a strategic priority for every business. Here’s a detailed blog explaining * ### **AI-Driven Cloud Cost Management** The Artificial Intelligence (AI) is redefining the way businesses manage their cloud expenses, enabling smarter and more efficient cloud cost optimization strategies. AI-driven solutions are already playing a pivotal role, leveraging real-time data, predictive capabilities, and automation to minimize unnecessary spending and maximize value. For example - AI-based platforms such as CloudKeeper Auto make the * ### **The Synergy Between Generative AI and Cloud Computing** The collaboration between Generative AI (GenAI) and the Cloud is rapidly emerging as a transformative cloud computing trend. Cloud computing democratizes access to Generative AI, allowing businesses, regardless of size, to utilize AI without the need for expensive infrastructure or specialized teams. Small and medium-sized companies can leverage cloud-based AI tools on demand for their projects. Major cloud providers like AWS, Google Cloud, and Microsoft Azure are spearheading the evolution by offering powerful platforms & services. **AWS:** Through platforms like Amazon Bedrock, SageMaker, and Amazon Titan, AWS enables developers to integrate pre-trained models and create generative AI apps with minimal infrastructure management. Its serverless approach streamlines the deployment of AI models. **Google Cloud:** Google offers tools like Vertex AI, PaLM, and Imagen, enabling businesses to access, fine-tune, and deploy generative AI models with ease. Google also integrates AI into DevOps tools for enhanced workflows. **Microsoft Azure:** Partnering with OpenAI, Azure provides advanced foundation models like GPT-3 and GPT-4, offering businesses secure, scalable access to cutting-edge generative AI models through its Azure OpenAI service. As this powerful partnership continues to evolve, we can expect to see even more groundbreaking innovations and applications emerge in the coming years. * ### **Rising Demand for End-to-End Cloud Cost Optimization Service Providers** The Everest Group survey highlights that many current automation-driven FinOps tools are not meeting expectations, creating a rising demand for a more comprehensive and integrated approach. As the market progresses, cloud FinOps providers with end-to-end capabilities across various areas are expected to gain prominence. This has led to a growing preference for Understand in detail * ### **Evolving Cloud Cost Optimization Metrics** Currently, over 70% of organizations still rely on the outdated metric of tracking cloud costs by application. This method fails to address critical issues such as overprovisioned resources and ongoing inefficiencies. As the cloud landscape matures, we can expect cloud cost optimization metrics to evolve. Future metrics may encompass engineering costs, relevant cost data availability, business value alignment with costs, and enhanced cloud cost visibility granularity. These evolving metrics will provide a clearer, more accurate picture of cloud spending and support more effective cost optimization strategies. * ### **Embracing Cloud-Native Development to Avoid Technical Debt** Cloud-native development is another emerging cloud computing trend to prevent technical debt. Adopting public cloud services can sometimes lead to technical debt if not managed carefully. With a vast array of services and frequent updates from cloud providers, it's easy to overcomplicate architectures or face challenges like service deprecations, inefficient resource usage, and unexpected costs. This debt often stems from poor planning, overprovisioning, or failure to adapt to changes effectively. The solution lies in embracing cloud-native development—building resilient, scalable applications designed for auto-scaling, fault tolerance, and high availability. Key practices like microservices, serverless computing, and containerization can help organizations stay agile, optimize costs, and respond to market demands more effectively. With thoughtful planning and ongoing monitoring, businesses can leverage the cloud to innovate while minimizing technical debt. ## **The adoption outlook for FinOps in the coming years** Let’s explore some of the emerging key trends in the FinOps industry. Source: FinOps is set to evolve from simply managing cloud costs to becoming a strategic driver of business value. According to the Everest Group Survey. The next set of innovation areas within FinOps are expected to be embedded automation, provision of support for hybrid cloud environments, as well as cost linkages with business value. Here are some of the key trends driving this transformation: * ### **Increase in adoption of strong automation practices** The adoption of strong * ### **FinOps as a Business Enabler Beyond Cloud Cost Savings** Additionally, FinOps helps align cloud investments with ROI-focused strategies, enabling executives to measure the direct impact of cloud spending on business outcomes. As hybrid and multi-cloud environments grow more complex, FinOps becomes an indispensable framework for driving agility, accountability, and innovation across teams and departments. In 2025 and beyond, organizations leveraging FinOps as a strategic enabler will be better positioned to achieve sustainable growth and competitive advantage. * ### **More Multi-Cloud and Hybrid-Cloud Vendors** In 2025 and beyond, vendors that can deliver tailored solutions for hybrid and multi-cloud environments will not only capture market share but also empower businesses to operate with greater agility, scalability, and cost efficiency. * ### **Internal expansion of FinOps teams for upscaling** The need for skilled professionals in FinOps is more crucial than ever, as businesses seek to optimize their cloud environments and manage costs effectively. Having a dedicated FinOps team is no longer just a good-to-have—it’s a necessity. As cloud services become more ingrained in daily operations, tracking costs across departments can be challenging. A skilled FinOps team ensures that each unit’s cloud spending is visible, helping businesses make informed decisions and prevent unnecessary expenses. A disciplined FinOps team provides structure, setting guidelines, and establishing financial guardrails to prevent overspending. They also identify risks related to cloud usage and develop strategies to mitigate those risks, ensuring that the company’s cloud services remain secure and cost-efficient. By optimizing costs and managing cloud usage effectively, FinOps teams not only help businesses save money but also lay the foundation for long-term, sustainable growth. * ### **More M &As and Investor Interest in FinOps** As the demand for cloud cost optimization continues to grow, the FinOps landscape is set for a wave of mergers, acquisitions, and heightened investor interest. This influx of capital will fuel innovation, accelerate product development, and drive the adoption of FinOps practices across industries. * ### **FinOps for Carbon Footprint Optimization** FinOps will play a pivotal role in optimizing carbon footprints. By enabling organizations to gain granular Here's how FinOps contributes to a greener future: **Efficient Resource Utilization:** By identifying and eliminating wasteful resource usage, FinOps helps reduce the energy consumption associated with cloud infrastructure. **Optimized Workloads:** FinOps enables organizations to right-size workloads, ensuring that resources are allocated appropriately to meet specific needs, minimizing unnecessary energy consumption. **Sustainable Cloud Practices:** FinOps can help organizations adopt sustainable cloud practices, such as selecting energy-efficient cloud providers and optimizing workload placement to reduce carbon emissions. **Conclusion: Prepare for Cloud Cost Management in 2025 by being aligned with cloud computing trends** With cloud services spending predicted to reach over $723 billion, it’s clear that organizations need to sharpen their cloud cost management strategies and be aligned with these cloud computing trends to stay competitive & relevant. The rise of AI-driven optimization will be key, enabling more accurate, real-time cost adjustments and forecasting. At the same time, FinOps will grow in importance. As cloud financial operations mature, businesses will need a comprehensive, ongoing approach to cloud cost management that focuses on long-term optimization rather than short-term savings. The integration of AI and FinOps will make this even more seamless, helping organizations drive both innovation and financial efficiency. Businesses adopting these latest cloud computing trends will be better positioned to navigate the increasingly complex cloud environment and make cloud cost management a strategic & sustained advantage. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Imagine receiving a lengthy and complicated cloud bill from your service provider detailing the monthly consumption across various services. Overwhelming? Yes. Easy to understand? Not even close! Furthermore, it’s safe to assume that as your operations scale up, so will the size of your CUR file, making the cloud bill even harder to comprehend. There’s no doubt that the metadata provided in the bill by your cloud provider is highly detailed and important but is it useful if you can’t even deduce relevant insights from it to make smarter business decisions? The simple answer is no. If you seek to achieve cloud cost visibility, your bills are a critical piece of the puzzle. By understanding and monitoring your cloud expenses, you’ll know - what service you use, how much of it you use, at what rate you use it, and even know details about extra fees you paid due to unoptimized transfers or on-demand consumptions. ## **Establishing a Culture of Cloud Cost Visibility** Cloud cost visibility isn’t just a check box activity in your “to-do” list. Instead, it’s a culture that you must cultivate within your organization. Doing so will help you enjoy the following benefits: * **Efficient Cost Control:** Higher cloud cost visibility will offer you more opportunities to optimize, you can identify areas of overspending or inefficiency and take corrective actions accordingly. * **Budget Management:** Cloud cost visibility will provide you with insights into your current spending patterns and even help you make smarter predictions about your future consumption requirements leading to better * **Resource Optimization:** By understanding your usage patterns, you can identify idle and underutilized resources and accordingly take action to optimize your resource allocation, right-size instances, and even adopt cost-saving measures such as reserved instances or spot instances. * **Cost Allocation:** Cloud cost visibility facilitates better cost allocation and chargeback mechanisms. This will enable your teams to understand their usage and encourage a culture of cost visibility and accountability across your organization. Each team will hence contribute to the overall cost management efforts. * **Risk Management:** By monitoring costs closely, your organization will be able to quickly identify potential security risks, such as unauthorized usage or inefficient resource configurations, and mitigate them before they escalate. * **Strategic Decision Making:** With clear visibility into cloud costs, your organization will be able to make informed strategic decisions about cloud adoption, workload management, and even investment in Understanding the importance of cloud cost visibility is good but not enough. You can’t just haphazardly run around attempting to track everything within the thousand-plus line item cloud bill. You must identify and understand the key performance indicators that you should keep a close eye on to extract meaningful insights from your cloud bill that will help you make better decisions to achieve maximum value out of your cloud resources. ## **FinOps KPIs for effective Cloud Cost Visibility and Cloud Cost Monitoring** Here are some * **Cost per Unit:** This FinOps KPI measures the cost of running a specific virtual machine instance. By regularly monitoring the Cost per unit across different resource types and sizes, you’ll be able to identify the inefficiencies in your consumption which in turn provide you with * **Cost Allocation Accuracy:** This KPI evaluates how accurately costs are allocated to different departments, teams, projects, or customers. This will allow you to compare allocated cloud costs against the actual resource usage and business activities promoting a culture of cloud cost visibility & accountability by making each team responsible for their share of consumption. By Implementing * **Spend Variance:** This KPI measures the variance between budgeted and actual cloud spending over a specific period. This KPI will help you understand the reasons behind deviations from your cloud budget. This will enable you to either pinpoint the cause of such deviation and take corrective action or adjust your budgets and spending plans for the future accordingly. * **Cost Trend Analysis:** This KPI tracks the trend of cloud costs over time to identify patterns, anomalies, and potential cost-saving opportunities. By using charts or graphs to analyze cost trends effectively you’ll be able to identify the spikes, trends, or recurring patterns that may require your attention. Monthly or quarterly reviews will give you valuable insights for better cloud cost savings and avoid leakages and idle time reducing inefficiencies. * **Resource Utilization:** As the name states, this KPI measures the utilization of cloud resources to ensure that you are not over or under-provisioning your cloud resources. Monitoring resource utilization metrics regularly will enable you to take actions such as * **Savings Achieved:** This KPI quantifies the overall cloud cost savings achieved through your cloud cost optimization efforts using reserved instances, spot instances, or by using * **Cloud Cost Efficiency:** This KPI measures the efficiency of your cloud spending in delivering business value. This KPI is expressed as the ratio of spending to business output. You need to establish ## **Strategies track the FinOps KPIs effectively** **** To maximize your optimization effort and track these KPIs effectively, you should: * Implement robust tagging strategies to categorize resources accurately for cost allocation and analysis. * Regularly review and analyze KPIs to identify trends, anomalies, and opportunities for optimization. * Foster collaboration between finance, operations, and development teams to ensure alignment on cost management goals and initiatives. * Continuously optimize cloud spending based on insights from KPI analysis and feedback loops. * Utilize With the right tools, benchmarking, and regular review, you can achieve better cloud cost visibility. Once you know your spending and consumption patterns, you’ll learn how to properly optimize your cloud spending unlocking higher efficiencies on the cloud. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 2 2 Table of Contents A recent engagement with a client revealed a critical issue in their Amazon Elastic Kubernetes Service (EKS) cluster. Their GPU-enabled nodes (G4dn.xlarge instances) were failing to assign IP addresses to new pods, despite having available CPU and memory. The error message they encountered was: **"pod didn't trigger scale-up: 3 node(s) didn't match Pod's node affinity/selector, 6 max node group size reached."** This post walks through our troubleshooting approach, key discoveries, and the solution that resolved the problem. ## **Problem Analysis** ### **Client’s Challenges** * The Amazon EKS cluster was hosting GPU workloads on G4dn.xlarge instances. * Only one pod was running per GPU node, despite available resources. * New pods failed to schedule due to node affinity and scaling constraints. ### **Initial Investigation Findings** * Node Resource Allocation: Each G4dn.xlarge instance provides 1 GPU, 4 vCPUs, and 16GB memory. Kubernetes was allocating an entire GPU per pod unless explicitly configured otherwise. * Pod Affinity & Selector Rules: Anti-affinity and node selector configurations were correct and non-conflicting. ### **Potential Root Causes** * GPU Resource Requests: Pods requesting full GPU resources, restricted scheduling to one pod per node. * ENI Limitations: Initially considered but ruled out after further analysis. ## **Root Cause: GPU Resource Allocation** The primary issue was that each pod was requesting a full GPU, preventing multiple pods from running on a single node. Since the client needed multiple pods to share a GPU, we implemented GPU time-slicing using the NVIDIA device plugin. **Understanding GPU Time-Slicing** * Enables multiple pods to share a single GPU by time-division multiplexing. * No memory isolation—a crashing pod may affect others sharing the GPU. * Ideal for lightweight workloads that don’t require dedicated GPU resources. ## **Solution: Implementing GPU Time-Slicing** **Step 1: Uninstall the Existing NVIDIA Device Plugin** Ensured the previous plugin was removed before applying the new configuration. **Step 2: Configure GPU Sharing via ConfigMap** Defined a ConfigMap to allow 4 pods per GPU: **Step 3: Deploy the Updated NVIDIA Device Plugin via Helm** **Step 4: Apply Node Labels and Taints** To ensure only GPU workloads are scheduled on these nodes: Label the Node: (Required for newer NVIDIA plugin versions.) Taint the Node (Recommended): (Prevents non-GPU workloads from using GPU nodes.) ## **Best Practices & Recommendations** **1. Use EKS-Optimized AMIs for GPU Workloads** The client was using a custom AMI (Amazon Linux 2). We recommended: Switching to the Amazon Linux 2023 NVIDIA AMI (pre-configured with NVIDIA drivers). Reverse-engineering the AMI for custom builds, if needed. **2. Right-Sizing GPU Instances** For compute-heavy workloads, consider larger instances (e.g., G4dn.2xlarge). For lightweight workloads, time-slicing helps reduce costs by maximizing GPU utilization. **Key Takeaways** By enabling GPU time-slicing, we allowed multiple pods to share a single GPU, resolving the scheduling bottleneck. Key insights: * Default GPU requests assign 1 GPU per pod—adjust via time-slicing if sharing is needed. * Always label GPU nodes (nvidia.com/gpu.present=true) for compatibility with newer NVIDIA plugins. * Leverage EKS-optimized AMIs for reliable GPU support. **References** * * * Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Aamir has hands-on experience across AWS, Kubernetes, Terraform, Docker, and Python, with a strong foundation in cloud infrastructure, automation, and container orchestration. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 10 Table of Contents ## **Introduction** Amazon Web Services, touted as a pioneer in the Cloud service providers, has been a consistent frontrunner in the IAAS and PAAS space. Organizations irrespective of their size have chosen AWS as their go-to Cloud service provider making it an undisputed contender in the area of Cloud services. With the margin in the race to the top constantly widening between AWS and its closest market competitor, their predominance can be attributed to their carefully crafted market strategy. AWS retains the top position because of its continuous innovation approach strategy as well as an attitude of expanding partner ecosystem. Let us delve deeper into each of these attributes that make AWS stand out so emphatically in such a competitive situation. ## **Continuous Innovation Strategy** In a short span of time of the first half of this year AWS has successfully added 422 services to its already illustrious portfolio. It has taken it further by integrating analytics and machine learning capabilities into its offerings. This gives AWS an advantage to stay abreast with the latest cloud trends and ahead of its competition. ## **Partner Ecosystem** AWS is also constantly expanding its partner ecosystem by adding several credible names to the list which adds to its reliability as a global Cloud service provider. Apart from that, AWS is spreading its footprints across the world with a strong and dependable network. According to a CloudTech report, AWS continues its position a global leader in Cloud with more than 45% worldwide market share as compared to its competitors like Microsoft, IBM, and Google. The RightScale 2017 State of the Cloud Report reiterates that AWS continues to lead in public cloud adoption. Though AWS has come up with a myriad of services, one can’t help but notice that most of its services are either under-utilized or untapped to their true potential. The reason behind this under-utilization is often the lack of know-how and basic ignorance. This article, therefore, caters to insights from different user cases related to AWS. The primary objective is to offer your organization some hacks to save cost on the cloud infrastructure and manage it effectively. Let’s explore each of these tips and tricks. ## **20 Tips and Tricks to Get the Most Out Of AWS** 1. **Elastic IP can be a Free of Cost Feature** AWS provides one free Elastic IP with every running instance. However, additional EIPs for that particular running instance is often chargeable and it can cost you in certain scenarios. AWS charges its customers for EIPs in instances when they are either not associated with any instance or if they are attached to a stopped instance. They ensure that the stopped instances don’t have EIPs attached to them until required. On the other hand, EIPs can be remapped for up to 100 times per month without incurring any extra charge. 2. **Save Big by Judicious Use of ALBs** Regular and rampant classic load balancers can be detrimental for an organization’s budget. As per statistics, an organization is paying at least $18 for each load balancer. ALB comes to the rescue in such situations. They are not only cheaper than classic load balancers, but ALB also supports path based routing, host-based routing, and HTTP/2. AWS ECS effectively supports ALB and can replace up to 75 ELBs with single ALB by proper utilization. However, ALBs only support http and https. So, if companies are using TCP protocol, they will still have to use ELB. 3. **Record Aliases over the CNAME when Using Route 53** While using CNAMEs for various services like ALB Cloudfront etc., adding an Alias record type over the CNAME provides some additional benefits. AWS doesn’t charge for Alias records sets queries and Alias records save time as AWS Route53 automatically recognizes changes in the record sets. Also, Alias records sets are not visible in reply from Route53 DNS servers making them more secure. 4. **Follow the Best Practices of EBS Provisioning** EBS volumes are an essential part of the EC2 infrastructure and need special attention while provisioning. It is a better practice to Start with smaller sized EBS volumes as AWS has recently launched feature of 5. **Use Multi-AZ RDS for Effective Application Backup and Recovery** In case of failure, AWS switches the same RDS endpoint to the point of the standby machine which can take up to 30 seconds, but the applications keep on working seamlessly. Backups and maintenance are first performed to the standby instance, followed by an automatic failover making the whole process smoother. Also, IO activity is not suspended while taking backups as they are taken from standby instance. 6. **Configure Multiple Alarms on Cloudwatch to Spike Notifications** Cloudwatch alarms are triggered only when they breach certain threshold. If a metric has already breached its threshold value and notified a team, then the alarm will only notify for the second time if the same threshold, doesn’t have the option for escalating an alarm to a different team if that alarm is not resolved in a stipulated time period. Therefore, to tap the AWS Cloudwatch to its fullest, configure multiple alarms on Cloudwatch for a single incident at different time intervals to notify different teams. 7. **Make Sure to Delete Snapshots while Deregistering AMIs** EBS snapshots are stored in S3 and do incur storage cost. This means the more AMIs created, the more you pay for storage cost. An AMI gets removed from your account when you deregister the AMI but their EBS don’t get deleted automatically. These are called zombie or orphan snapshots as their parent AMI doesn’t exist and eat up the storage costs. One needs to manually delete these snapshots to free up some storage to combat this problem. 8. **Leverage Compression at the Edge Feature in Cloudfront** Organizations can use compression at edge feature of Cloudfront while serving web content. Cloudfront automatically compresses the assets and delivers the compressed content to the client not only saving the data transfer cost but also pace up the content download.With this, you can directly compress and serve content from S3. 9. **Efficient use of S3 enables higher savings** They can also use Glacier for archival of data as Glacier supports data retrieval in a few minutes. 10. **Replicating Critical S3 Data** To replicate or backup the critical S3 data to other regions, companies now have a feature of cross-region replication of an S3 bucket to a different region. As soon as the data is uploaded in the source bucket, it will automatically replicate to the destination bucket in a different region. This feature only works with buckets in a different region and not in the same region. 11. **Save Time and Effort while Data Retrieval from Glacier** Glacier is a very helpful feature in data archival. However, data retrieval from Glacier can be an expensive affair. Even though the process is slightly tedious in the beginning but data that can be placed in the form of large zipped files should be stored in smaller chunks. It is ideal to move data in in small chunks instead of large chunks because to it is easier to restore a small-sized file in small-sized chunk than in a large-sized chunk. This will also make it easier to access and at a smaller cost as retrieving a large data chunk for a small file will have you pay the cost for the retrieval of the entire big data chunk. 12. **Avoid using T2 Instances in Production Environment** T2 instances shouldn’t be used in production environment as they are not designed to handle continuous production workloads for a long duration. However, the instances get a specific number of CPU credits per hour which can be utilized at the time of heavy workload for some time. Once the system consumes all its CPU credits, then it will again come to its baseline performance, degrading any CPU intensive mission critical task running on the production server. 13. **Optimize IO Performance for High-performance Instances** Even the high-performance instances may warrant issues related to IO. One must be aware that EBS optimized instances offer better accessibility and faster response between EC2 and EBS volumes. The new-generation EC2 instances like C4, M4 series are EBS optimized by default. However, instances like C3 or M3, one still needs to manually check the EBS optimized option for high-performance. There is an additional cost associated to avail this feature. 14. **Use Versioned Object Names to avoid Cloudfront invalidations** Purging Cloudfront cache is a time taking process and it is free for up to 1000 requests every month. In order to prevent invalidating CloudFront cache multiple times, companies can use versioned object names. This can really help in fetching the updated object without overwriting the existing object on CloudFront and is a much faster and reliable approach. 15. **Save Costs on AWS Screenshots** When you create an EBS volume based on a snapshot, the new volume begins as a replica of the original volume. EBS snapshots stored in S3 are incremental in nature. If you are creating a snapshot of a volume for the first time, the snapshot size would be the same as the disk usage. However, if their data is not changing too much, the storage size accumulated by the snapshots would be more or less the same as previous due to incremental nature of EBS snapshots. 16. **Monitor your AWS Usage** You don’t need a third party application to keep a tab on your AWS account. AWS comes with a billing alert feature to keep the customer apprised about their usage and expenses. This allows customers to plan their AWS bandwidth and handle any sudden spikes in the bill. 17. **Give Your Account the AWS Limits Advantage** Every service of AWS comes with a soft limit in specific regions. Having a clear idea of the region-specific server requirements is helpful decreasing the server limits of other regions to zero. So, even if your account’s security is compromised, AWS limits will prevent attackers from being able to perform any malicious activity in other regions keeping the 18. **Remove Unnecessary CloudWatch Resources to Save Cost** You can remove alerts and notifications related to insufficient data, monitoring of nonproduction EC2 instances, redundant CloudWatch alarms and create custom metrics for the important parameters. It is also useful to remove non-functional and unused dashboards. This exercise will help you reduce some of the superfluous costs incurred. 19. **Save by Identifying and Segregating EC2 Workloads** Organizations can leverage spot instances for ad-hoc tasks and spot-fleet for QA/Test environments to 20. **Warm-up your ELB resources before the Big Day** An anticipated influx of heavy traffic on a certain occasion, event etc. can negatively impact an application with issues as the website may become unresponsive to the users beyond application bandwidth. It is advisable in a scenario to plan and prepare your ELB to handle such a huge traffic. You can inform AWS about such this sudden surge at least a day in advance by raising a ticket to AWS support system so that they can add more nodes behind LBs. This would make the application more reliable in handling such workloads. This will help your organization prevent any application downtime caused due to traffic. ## **Conclusion** AWS has rightly gained its status as the most sought-after cloud provider giving its users some compelling benefits. Since infrastructure entails a significant capital expenditure, organizations need to be very particular about maintaining their infrastructure on the cloud. A little wisdom on cloud expenditure can help you avoid procuring services that you will not use. AWS has effectively changed the world of startups with is user-friendliness, flexibility, scalability, pricing and many such advantages. If you are still contemplating whether or not to choose AWS, you can read our blog on AWS benefits to gain clarity. You can also download our whitepaper on 20 Tips and Tricks Companies Must Know While Working on AWS for a more in-depth take on these best practices. If you have already chosen AWS, with the help of these tricks and tips you can make a huge difference in Cloud cost and utilize your cloud infrastructure services to their full potential. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents AWS Cloud has provided a scalable, cheaper, and easier way of managing the infrastructure with the help of which corporations can easily set up their IT infrastructure in the cloud without very much less hassle and zero upfront cost. It provides numerous ## **Some of the AWS cost optimization best practices** **Scheduling on/off Time for Resources** For non-production environments, you can use automation tools that can switch off unused EC2 Instances and other services that are not in use. For example, non-production environments are often not used at night. Hence, if not switched off, they will generate costs for the whole period. Some of the resources that can be scheduled to start and stop are:- * Ec2 Instances * Relational Databases(RDS) * Elastic Container Services * Elastic Kubernetes Service(EKS) * DocumentDb * Auto Scaling Groups(ASG) How can you schedule on/off time on these resources? There are many automation-driven AWS cost optimization tools and services available that can be used for scheduling. Let us take a look at some of the examples. **Jenkins** Jenkins is a powerful CI/CD Tool that can be used to automate the scheduling process with the help of cron. You can set start and stop times for the days for which you want to perform the activity. **Lambda** Lambda is an AWS service that can also be used to schedule start-stop time, but lambda comes with an additional cost. **Cron** You can use cron to run scheduling scripts for desired timings. It is one of the easier ways to create a scheduling strategy. Using start-stop scheduling of AWS resources will help in AWS cost optimization as there will be a time when these resources will not be used, but they will be billed for their running time. ### **Using the Right Instance Family** AWS provides Ec2 Instances based on These instances come with different costs. For example, arm instances are cheaper than AMD instances. Moving your Non-production architecture to ARM-based will help you Always choose the instance family after thoroughly comparing the pros and cons and try to choose the latest generations. ### **Using spot instances for ECS/EKS services auto-scaling groups** For a non-production environment, you can use spot instances, which can help you save huge amounts of money. What are spot instances? Amazon sells its server Spot. This means Amazon sells its leftover server space that it has been unable to sell without using a data center. The server is the same server that they provide with the on-demand option. The significant difference is that Amazon can request the server back at 2 minutes' notice (this can cause your services to have an interruption). On the other hand, Amazon pricing optimization can help reach a discount of up to 90%. In most cases, the chances of them asking for the servers back is very low (around 5%). You can use spot instances by creating a spot fleet in your Auto-scaling groups and selecting the spot fleet instances based on your service requirements. ### **Use the minimum instance type required for the service type** Always select the instance type based on the service requirement, check the amount of memory and CPU that the service will use, and then select the instance type. If you do not use the right type of instance for your service, it may be possible that the instance is not being utilized to its fullest capacity, and you will be adhering to the cost of the instances. ### **Use 50% volume size as compared to the production environment** While using the volumes for EC2 instances always uses 50% less capacity than what is being used for the production environment. Because production environments handle more amount of data than non-production, it will be a wastage of resources if we use the same volume as production. ### **Don't use clusters in a non-prod environment** Some services, like Hazelcast, Rabbitmq, etc., need clusters when the amount of data is high. But in the case of a non-production environment, we can use a single node only because the non-prod environment is used for testing only, and clustering the resources would generate additional costs for the infrastructure. ### **Replica of application to one until it is required by the development team for high load** While using EKS/ECS for microservices architecture in non-production environments, always keep the count of replicas to one. For non-prod, a single replica of the service is enough. Using a high replica count will result in additional costs. You can increase the replica count when it is needed by the development team for testing purposes. ### **Setting backup of Logs for Cloudwatch, S3, etc.** Logs amount to high costs if they don't have a suitable retention period. Storing logs for a large amount of time generates lots of costs. To bring your bill down, set the retention period of the logs to the minimum desired time that doesn't affect your needs. Logs keep getting stored and make a huge stack for which AWS charges you a lot, whether they are For services like Elasticsearch, storing large amounts of logs affects the performance of the service. It fills the storage of the instance, which can result in system failure or slow response. ### **Creating desired ECR Image Lifecycle Policy** With a lifecycle policy, you can set rules to automatically delete old or unused images, which can help ### **Move infrequently-accessed data to lower cost tiers** Moving infrequently-accessed data to lower cost tiers in **Lower Storage Costs** : Amazon S3 offers several lower-cost storage tiers, such as S3 Standard-Infrequent Access (S3 Standard-IA) and S3 One Zone-Infrequent Access (S3 One Zone-IA), which offer lower storage costs than the S3 Standard storage class. By moving infrequently-accessed data to these lower-cost tiers, you can save on storage costs while still maintaining durability and availability. **Lifecycle Policies** : Amazon S3 allows you to automate the process of moving objects to lower-cost storage tiers using lifecycle policies. You can set policies based on access patterns, object age, or other criteria to automatically move objects to lower-cost tiers when they are no longer frequently accessed. **Retrieval Costs:** Lower cost tiers in Amazon S3 may have retrieval costs associated with accessing data, such as S3 Standard-IA and S3 One Zone-IA. However, if you are not frequently accessing the data, the savings from the lower storage costs can offset the retrieval costs. **Durability and Availability:** Amazon S3's lower cost tiers offer the same level of durability and availability as the S3 Standard storage class, ensuring that your data remains secure and accessible. **Improved Data Management:** Moving infrequently-accessed data to lower cost tiers in Amazon S3 can help you better manage your data by allowing you to tier your data based on access frequency and optimize costs based on the value of the data. Moving infrequently-accessed data to lower-cost tiers in These Methods can help you to bring your AWS infrastructure cost down by a high margin. _Optimize your AWS Costs and achieve enhanced cloud cost savings with CloudKeeper by your side. With contractually guaranteed savings, free access to AWS cost analytics platform, and recommendations from certified AWS experts, CloudKeeper can help reduce your overall AWS bills by up to 25%._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents With a lot of companies now planning to develop products faster and cut down on their release cycles, it is imperative for them to leverage new-age digital technologies such as Cloud, Mobility, IoT and many others. Out of the multiple technologies that companies can exploit, DevOps is quickly gaining traction. DevOps is enabling companies to automate their delivery pipeline and continuously integrate and deploy without any hassles. Unlike the traditional environment where Dev and Ops used to work differently, DevOps promotes a culture of collaboration breaking the traditional silos. According to _Jason Bloomberg, President of Intellyx_ , the first and only industry analysis and advisory firm focused on Agile and Digital Transformation, “DevOps is an organizational and cultural rethink of how software-driven organizations can become nimble enough to innovate at the speed of light and implement changes that come their way rapidly.” With the rising need of DevOps as a service, several organizations are looking to join hands with a DevOps partner that can help them automate their delivery pipeline, setup one click deployment, take care of the workload migration and support them with the overall strategy and DevOps consulting. DevOps consulting doesn’t merely give a direction or a convention that an organization should follow but it gives every IT organization the ability to stand out in its own unique way. According to one of the Gartner’s reports, DevOps and enterprise-scale development practices will have a major impact on organizations. It also suggests that DevOps as a service helps organizations build and manage their systems and provides application leaders with insights to guide their planning processes. Some of the mature DevOps players have also started leveraging DevOps tools such as Chef, Jenkins, Puppet, Ansible and much more. We have outlined below some of the most advanced business benefits that DevOps brings on the table. 1. **Improved Build Quality** DevOps is the process that binds development and operations together. DevOps creates an environment of knowledge and information sharing that lets the teams share same goals that positively impacts the build quality. DevOps compels a wide range of teams to perform regular specialized code reviews to improve code maintainability. DevOps brings together both dev-centric attributes such as features, performance, and reusability and ops-centric attributes such as deployability and maintainability to uplift the overall code quality. Several tests in the areas of distribution of deployment frequency, deployment lead time and mean time to recover (MTTR) suggest that DevOps helps in driving not only a better initial code quality but also improved testing. DevOps helps in making a mindset shift towards continuous delivery improvement that makes it a critical contributor to code quality and stability. 2. **Accelerated Application Delivery through Agile** DevOps leverages disciplined Agile Delivery is an established process for developing software. When we look at the traditional method of software release process, it is often observed that the development team first builds the code and then tests it in an isolated environment, where the operations team takes over for production. The lack of synchronization between the two teams creates several complexities and misunderstandings as they are not on the same page regarding infrastructure, configuration, deployment, log management, and performance monitoring, which in turn slows down the production process. With the help of DevOps services, companies can actually accelerate delivery and cut down the release time. It helps them to go to market in desirable time and stay ahead of the competition. DevOps with Agile also helps in early detection of errors leading to quick fixes. It lets the code be in the releasable state always. Overall, DevOps helps companies to focus more on innovation with more stable operating environments. 3. **Improved Application Reliability** DevOps tools and principles automate the entire delivery pipeline that enables teams to diminish the pitfalls of version control, configuration management, continuous integration, deployment and continuous performance monitoring. This improves application quality as it eliminates the time-consuming, cumbersome, as well as error prone manual processes. Automation increases application reliability as there is little manual intervention. Additionally, test automation and QA processes carried out in every stage give more control to the development team to have a foolproof QA mechanism in place. According to a recent report, several high performing IT organizations have experienced up to 60 times of fewer failure rates and 168 times faster recovery from failure. These organizations were also able to deploy 30 times more frequently with 200 times shorter lead time. According to the report, these organizations adopted DevOps and were able to integrate continuous delivery to their system. Hence, it has been well documented and proven that through the incorporation of automation, teams are able to build, package and deploy with much more ease and accuracy. It has successfully led to a shortening of lead time, improving the mean time to recovery with much lower failure rates and downtime. 4. **Improved Team Collaboration** It is never truly DevOps unless it becomes intertwined with the organizational culture. In a regular IT association, both dev and operations are frequently restricted to executing their specific tasks. DevOps, therefore, aims to blur the lines between development and operations by empowering the either side to understand the other’s workflow. This warrants the teams to comprehend the entire procedure end-to-end while making improvements to it. For example; ops also start understanding dev jobs and tools and vice versa. Living up to its Lean principles DevOps brings with itself a culture of constant learning and improvement. Moreover, as both the teams understand each other’s job and share larger goals, it also enhances the satisfaction levels. According to most DevOps consulting companies, working in isolated environments or silos can bring a lot of resentment and misunderstanding between different teams with very little transparency on either side. With both Dev and Ops team working in collaboration it helps in swift execution of projects through an Agile process and dynamically reduces bottlenecks. 5. **Minimized Impact of Complexity on Software Development** Many a time, the build quality is compromised due to the complexity of the project. Several software system functionalities get more and more complex as the deployment progresses. Many small software glitches can have significant consequences that can be detrimental for the software build. However, DevOps eliminates this risk by giving more control to the teams by managing smaller chunks of the software solution. It encourages the use of automated procedures to build, package and deploy the application. It is far easier to verify the interfaces, runtime dependencies with this automated support. This process helps to ensure that the configured environment is able to support all components comprehensively which includes the build and deployment of the components themselves. ## **Conclusion** DevOps brings an all-round growth in terms of software quality and culture. Many companies are looking for DevOps outsourcing partner that can help them to better their infrastructure with one click deployment and rollback, backups, and overall pipeline automation. A good DevOps partner that provides DevOps as a service doesn’t just stop at automation but also help to achieve significant business benefits with the configuration of automated alerts, centralized log management, infrastructure security, and disaster recovery. DevOps helps companies to become more Agile and efficient. DevOps is certainly a sure fire way to optimize quality and improve infrastructure. Do let us know what business benefits did you receive leveraging DevOps in the comments below. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources How to Design the Hybrid Crossplane Architecture? In the second blog in the "Reimagining Traditional IaC" series, we explore how we moved beyond Terraform to design a hybrid Crossplane architecture for scalable, reliable infrastructure management. By Neetesh Yadav 01 Jun, 2026 Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Why Amazon OpenSearch Often Outperforms Amazon CloudWatch A practical comparison of AWS OpenSearch and AWS CloudWatch, covering key parameters, use cases, and when to choose each for monitoring and log analytics. By Aditya Mishra 17 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents Amazon Web Services (AWS) has a variety of AWS pricing models for different businesses and their specific needs. Whether you are a startup with an idea or an enterprise concerned with optimizing workloads, the right choice of AWS pricing models can make huge differences in your cloud costs and efficiency. This blog will explain different AWS pricing models, key considerations, real-world use cases, and ## **An Overview of AWS Pricing Models** AWS offers five primary pricing models that have been devised for specific cases. The five AWS pricing models are: * **On-Demand Instances –** The pay-as-you-go AWS model where customers pay for compute capacity per hour or second. * **AWS Reserved Instances (RIs) –** The service permits customers to reserve a specific instance type for a reduced rate in exchange for committing to it for 1 or 3 years. * **AWS Savings Plans –** A flexible AWS pricing model that provides significant savings in exchange for committing to a certain usage level. * **AWS Spot Instances –** The unused AWS capacity that can be purchased at a discount of up to 90% and is great for fault-tolerant and flexible workloads. * **Dedicated Hosts –** Physical servers, providing compliance and licensing benefits. ## **Key Considerations for AWS Pricing Model Selection** The following factors need to be considered while choosing the AWS pricing model: * **Workload Classification:** Does your workload have consistent, predictable usage, or does it fluctuate based on demand? Predictable workloads may benefit from Reserved Instances (RIs) or Savings Plans, while variable workloads are better suited for On-Demand or Spot Instances. * **Budget Constraints:** While cost savings are a priority, performance should not be compromised. Businesses must balance affordability with reliability, ensuring the pricing model aligns with their financial goals. * **Scalability:** If your application requires rapid scaling up or down based on traffic spikes or resource demand, the pricing model should allow for seamless elasticity without incurring excessive costs. * **Level of Commitment:** Some AWS pricing models offer discounted rates in exchange for long-term commitments. If your workloads are predictable and steady, committing to 1-year or 3-year Reserved Instances or Savings Plans can lead to significant savings. * **Compliance & Licensing Needs:** Industries like healthcare and finance that require dedicated infrastructure for security, regulatory, or licensing compliance may need Dedicated Hosts or Reserved Instances to meet those standards. ## **AWS Pricing Models Use Cases** AWS pricing models are suited for variable use cases. Here are a few examples: ### **1. Start-Ups Launching MVPs (On-Demand Instances)** For start-ups testing new applications, the on-demand instances offer flexibility without any upfront commitment as they enable the business to scale up or down instantly depending on demand. _**Did you know that with CloudKeeper, you can run everything on-demand at commitment-based pricing with 100% coverage?**__**to explore more.**_ ### **2. Established Companies with Predictable Workloads (RIs/Savings Plans)** Organizations that run constant workloads like E-commerce websites or SaaS's can make use of AWS Reserved Instances or AWS Savings Plans to minimize costs over the long run while keeping performance steady. ### **3. Data Processing and Activities that Require High Compute Resources (Spot Instances)** Workloads in machine learning training, batch processing, and big data analytics can use Spot Instances to save substantially on cost, as these workloads can tolerate interruptions and work on resumes. ### **Factors Affecting AWS Pricing for the Most Preferred Services** Every AWS service has its own pricing policies. Here are the AWS pricing metrics based on usage for the most popular AWS services: * **Amazon EC2** – Pricing is based on the instance type, region, and usage model (On-demand, RI, Spot, Dedicated). * **Amazon S3** – Charges for storage, data retrieval, and transfer. * **AWS Lambda** – Pay-per-execution pricing based on function duration. * **Amazon RDS** – Charges based on database engine, instance type, and reserved capacity. * **Amazon DynamoDB** – Pricing is based on either pay-per-request or provisioned capacity. * **Amazon EBS** – Charged based on volume type, provisioned IOPS, and snapshots. * **Amazon CloudFront** – Pricing depends on data transfer and request volume. * **AWS Glue** – Charges per data processing unit (DPU) and job running time. * **Amazon ECS/EKS** – Compute pricing per EC2 or Fargate. * **Amazon Redshift** – Pricing is based on node type, cluster size, and reserved options. ## **Cloud Cost Optimization Across AWS Pricing Models** These are some of the proven methods & * **Use Auto Scaling** – Scale resources up and down automatically in real-time, based on demand. * **Monitor usage with AWS Cost Explorer** – Identify usage patterns and adjust resources accordingly. * **Utilize Spot Instances for Non-Critical Workloads** – Capitalize on the unused AWS capacity to save costs. * **Right-Size Instances** – Right instance types are chosen based on workload requirements. * **Commit to Reserved Instances or Savings Plans** – The long-term * **Use AWS Budgets and Alerts** – Set a limit on the budget and attach alerts to curtail unnecessary spending. ## **What Is the AWS Pricing Calculator?** The AWS Pricing Calculator is an advanced tool for estimating AWS pricing based on specific configurations. This helps businesses forecast expenditures prior to the deployment of resources, which can foster financial planning and optimization. ## **Frequently Asked Questions (FAQs)** **Q1: Where do I even begin to decide which AWS pricing model fits my business best?** Consider how predictable your workloads are while weighing costs and flexibility. Use On-Demand for flexibility, RIs/Savings Plans for predictable work costs, and Spot Instances for batch jobs. Check out our detailed guide on **Q2: Can I use different AWS pricing models in combination?** Yes! Companies often utilize a mix of pricing models—On-Demand, Reserved Instances, and Spot Instances—to suit performance and cost. **Q3: How much can I save on Spot Instances?** Spot Instances can save up to 90 percent on on-demand prices, but Amazon can interrupt the process when it needs the capacity. With the help of CloudKeeper Tuner, you achieve big savings up to 65% with automated & dynamic spot optimization. **Q4: What is the difference between Reserved Instances and Savings Plans?** RIs require a commitment to a particular instance type; whereas, AWS Savings Plans allow more flexibility in choosing instance families and regions. Learn more in this **Q5: Will AWS give me recommendations for cloud cost optimization?** Definitely! Tools like AWS Cost Explorer, Trusted Advisor, and Compute Optimizer are offered by AWS to guide businesses on the road to eliminating unnecessary costs. For more deeper and tailored insights, we suggest trying CloudKeeper Tuner, ## **Final Thoughts** As a certified AWS Premier Partner, CloudKeeper has helped 400+ global companies save an average of 20% on their cloud bills, modernize their cloud set-up and maximize value — all while maintaining flexibility and avoiding any long-term commitments. Need expert guidance on optimizing your AWS pricing? Contact CloudKeeper today, and let’s make your cloud spending smarter! Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 18 18 Table of Contents **“Good intentions never work, you need good mechanisms to make anything happen” — Jeff Bezos** This quote holds true for your AWS cloud infrastructure as well. You might have a great vision for your cloud and how it can help your business scale to new heights, but without a solid framework, your goals are unlikely to be realized. The specialists at AWS or other third-party providers that offer the This puts them in a constant learning loop about how well these trade-offs perform when deployed in the live environment. Based on these learnings, AWS has created the Well-Architected Framework. There is an over 850-page document that explains everything in depth about the ## **What is AWS Well-Architected Framework?** Imagine having a comprehensive guidebook that states the key concepts, design principles, and architectural best practices for designing and running workloads in the AWS ecosystem. In 2015, AWS launched one such comprehensive guide to building efficient and secure digital infrastructures—the AWS Well-Architected Framework. For a clear explanation based on our real-world experience addressing AWS infrastructure challenges for clients, consider reading By using this framework, organizations can evaluate their cloud workloads against established architectural standards and examine the pros and cons of their decisions when building systems on AWS. ### **The Expertise Behind the AWS Well-Architected Framework** The AWS Well-Architected Framework has been crafted by seasoned AWS Solutions Architects. Every day, AWS experts assist customers in designing systems to leverage cloud best practices. Not just AWS experts, third-party service providers have also honed their expertise with AWS infrastructure. Today, many reliable If you need more than just a framework review and are looking for a broader solution for your AWS infrastructure, going the reseller route will be a better choice. Their expertise ensures that the AWS Well-Architected Framework addresses ### **Who should use the AWS Well-Architected Framework?** The AWS Well-Architected Framework is a valuable resource for anyone involved in the design and operation of cloud systems on AWS. This includes professionals like: * Chief Technology Officers (CTOs) * Cloud Architects * Developers * Operations Team Members ## **What is an AWS Well-Architected Review (AWS WAR)?** As your business evolves, so does your AWS environment. The The purpose of the Thus, the AWS Well-Architected Framework is your construction manual for building systems in the cloud, and the AWS Well-Architected Review is like getting an inspection to determine whether your system has been built the right way. AWS Well-Architected Review expertise comes more from experience than from detailed theoretical know-how. So, you should _**AWS Well-Architected Framework Review Cycle (Source: AWS)**_ ## **The Six Pillars of an AWS Well-Architected Framework** Do you know what’s common between building a home and setting up a cloud infrastructure? In both cases, we have to focus on the foundation. Now that we have a basic understanding of The AWS Well-Architected Framework is built on six key areas, which we call pillars. These six pillars are the areas in which your AWS cloud architecture must excel to meet the desired standards for efficiency and effectiveness. These six pillars of the AWS Well-Architected Framework include: * Operational Excellence * Security * Reliability * Performance Efficiency * Cost Optimization * Sustainability By prioritizing these six pillars during the design phase, you As defined by AWS, each pillar within the Well-Architected Framework has its own set of elements as stated below: * Design principles * Best practices * Assessment Questions During the AWS Well-Architected Review, these elements guide the effective implementation and optimization of cloud architectures to meet the goals and requirements of each pillar. If you’re planning to bring in a third-party consultancy, the best way to determine whether they provide the best consulting services for AWS Well-Architected Review is to evaluate their real-world experience and the diversity of infrastructure environments they’ve worked with, rather than relying solely on certifications. Let’s dive into each pillar in detail and understand how the workload in the AWS WAR process is evaluated for each. ### **Pillar 1: Operational Excellence** The Operational Excellence Pillar of AWS WAR involves running and monitoring systems, understanding what is happening, and continuously seeking ways to improve processes. ### **Design Principles for Operational Excellence** Let us look at the design principles for AWS operational excellence. * **Perform operations as code:** Manage your entire * **Make Small, Frequent Changes:** Rearrange your workload with small changes in it. This reduces the risk involved and enables a quick adjustment to market shifts. * **Refine operations procedures frequently:** As your workloads evolve, so should your operation procedures. Regularly review and update them to ensure they are effective. Share best practices among teams and make sure everyone knows what to do. * **Anticipate Failure:** Identify potential issues ahead of time, and come up with mitigation strategies. Test these scenarios so that the team knows how to react. * **Learn from all operational failures:** All events, whether success or failure, have lessons that can be learned from them. Capture these learnings across your team and share them so that you can always get better. * **Use managed services:** Take advantage of * **Implement observability for actionable insights:** Establish _**Actionable Advice:** You can leverage the __like CloudKeeper Lens to achieve real-time cost monitoring and a granular view of your cloud cost usage._ ### **Best Practices for Operational Excellence** The Best Practices for Operational Excellence are focused on four major areas: Organization, Prepare, Operate, and Evolve. In the AWS Well-Architected Review, a specific set of questions are aimed at assessing operational excellence in the cloud, focusing on the areas of best practices: AWS has established standard best practices for each of these questions, which serve as benchmarks for determining whether you are efficiently managing your cloud operations or not. ### **Pillar 2: Security** The security pillar is all about protecting your data, systems, and assets in the cloud. It leverages the inherent strengths of cloud technologies to create a more secure environment for your information. ### **Design Principles for the Security** * **Implement a strong identity foundation:** Make sure the team only has the essential permissions based on their needs and try to eliminate lengthy static credentials. * **Maintain traceability:** Monitor, alert, and audit any real-time changes in your environment to investigate and avoid any suspicious activity. * **Practice protection at all stages:** Apply multiple security controls at all layers such as the edge of the network, VPC, load balancing, every instance and compute service, operating system, application, and code. * **Automate protection practices:** Implement automated protection mechanisms to scale and preserve the safety controls for your environment while being cost-effective. * **Protect data** at rest and in transit: Use measures such as encryption, tokenization, and access control. * **Keep people away from data:** Less exposure, less risk! This principle encourages limiting direct access to your data whenever possible. This reduces the risk of accidental data leaks or errors. * **Prepare for security events:** This principle emphasizes having a plan in place for a security incident. This may include incident management policies and procedures that align with organizational necessities. It's like having a fire drill for your cloud environment. By practicing and using automated tools, you can respond to threats quickly and effectively. ### **Best Practices for Security** The best practices for cloud security focus on seven areas: Security foundations, Identity and access management, Detection, Infrastructure protection, Data protection, Incident response, and Application security. You can simplify getting enhanced security safeguards in place by choosing one of the many reliable cloud resellers for an AWS Well-Architected Framework review on the market right now. In the AWS Well-Architected Review, the below-mentioned specific questions are designed to assess security, focusing on the areas of best practices: For each of these questions, AWS has developed standard best practices that serve as benchmarks for determining if you are managing your cloud security efficiently. ### **Pillar 3: Reliability** The objective of the­ Reliability Pillar is simple: your workloads must be re­ady whenever ne­eded. It centers on designing and running cloud workloads that perform consistently and meet demand. Additionally, it includes the ability to re­cover easily from disruptions and maintain functionality throughout the­ workload's lifecycle. ### **Shared Responsibility for Cloud Resiliency** You must understand that building a resilient cloud environment is a shared responsibility between AWS and you (the customer). AWS's responsibility includes managing the infrastructure that powers its cloud services, including hardware, software, networking, and other facilities. Your (customer) responsibilities are determined by the ### **The design principles for Reliability** * **Automatically recover from failure:** This principle aims to ensure automatic recovery in the event of disruptions. By * **Test recovery procedures:** Unlike traditional IT environments, the cloud allows you to test how your applications fail and how well your recovery plan works. By simulating different failure scenarios, you can identify weaknesses and fix them before a real outage disrupts your business. * **Scale horizontally to increase aggregate workload availability:** This principle focuses on using multiple smaller resources rather than a single large one. This way, if one resource fails, it won't bring your entire application down. By distributing workloads across these smaller resources, you * **Stop guessing capacity:** Running out of resources is a common cause of outages. This principle emphasizes monitoring your workload's demand and automatically scaling resources up or down as needed. This ensures you have enough resources to handle peak periods without wasting money on over-provisioning. * **Manage change in automation:** This principle encourages automating any changes you make to your infrastructure, which then can be tracked and reviewed. ### **Best Practices for Reliability** The best practices for reliability are focused on four major areas: Foundations, Workload architecture, Change management, and Failure management. In the AWS Well-Architected Review, the below-mentioned specific questions are designed to assess infrastructure reliability, focusing on the areas of best practices: ### **Pillar 4: Performance Efficiency** This pillar in the AWS Well-Architected Review focuses on using cloud resources effectively. It's about getting the right amount of power for your applications, without wasting anything. The goal is to be both efficient (avoiding waste) and adaptable (scaling up or down as your needs change). This ensures you're ### **Design Principles for Performance Efficiency** * **Democratize Advanced Technologies:** Make it easier for your team by letting your cloud partner handle complex tasks. Instead of having your IT team learn how to set up and manage new technology. This way, your team can focus on building products rather than worrying about managing resources. * **Go Global in Minutes:** Deploy your * **Use Serverless Architectures:** This design principle focuses on * **Experiment More Often:** Take advantage of virtual and automated resources to try and compare different setups. You can test different types of instances, storage options, or configurations. * **Consider Mechanical Sympathy:** This principle emphasizes selecting technologies that align best with your workload's requirements. For example, think about how your data is accessed when ### **Best Practices for Performance Efficiency** Performance Efficiency pillar in the cloud is based on five best practice areas, which include Architecture selection, Compute and Hardware Design principles, Data management, Networking and Content Delivery, and Process and Culture. In the AWS Well-Architected Review, the below-mentioned specific questions are designed to assess performance efficiency, focusing on the five areas of best practices: For each of these questions, AWS has developed standard best practices that serve as benchmarks for determining the performance efficiency of your cloud infrastructure. ### **Pillar 5: Cost Optimization** The Cost Optimization pillar in AWS Well-Architected Review enables systems to provide business value at the lowest possible cost. It involves carefully managing spending, selecting the most cost-effective resources, and scaling efficiently to meet business requirements without unnecessary expenditures. ### **Design Principles for Cost Optimization** * **Implement Cloud Financial Management:** Think of It as a financial advisor for your cloud spending. Cloud Financial Management helps you track your costs, understand where your money is spent, and identify areas for improvement. It's an investment that pays off in the long run. AWS suggests that an organization should consider _**Actionable Advice:** Cloud Financial Management requires specific expertise and skill sets in the Cloud FinOps domain. A potential alternative could be partnering with a __that can_ _leaving you with more time, money, and resources to dedicate to other critical areas._ * **Adopt a consumption model:** This principle encourages using a consumption model for your cloud resources. In this model * **Measure overall efficiency:** Measuring the value you get from your cloud investment is extremely crucial. This principle emphasizes tracking both the business output your workload generates and the associated costs. By analyzing this data, you can understand how increasing output, functionality, or reducing cloud costs impacts your overall efficiency. * **Stop spending money on undifferentiated heavy lifting:** AWS takes care of complex tasks like data center operations and removes the operational burden of managing operating systems and applications with managed services. This way you free up your team to focus on what matters most – your customers and business projects. * **Analyze and attribute expenditure:** This principle focuses on ### **Best Practices for Cost Optimization** The best practices of the Cost optimization Pillar are focused on the five key areas that include: Practice Cloud Financial Management, Expenditure and usage awareness, Cost-effective resources, Managing demand and supplying resources and Optimize over time. In the AWS Well-Architected Review, the below-mentioned specific questions are designed to assess performance efficiency, focusing on the five areas of best practices: For each of these questions, AWS has developed standard best practices that serve as benchmarks for determining whether your cloud infrastructure is cost-optimized. ### **Pillar 6: Sustainability Pillar** This Sustainability Pillar in AWS Well-Architected Review focuses on minimizing the environmental impact of your cloud workloads, especially energy consumption, and efficiency. ### **Design Principle for Sustainability** * **Understand Your Impact:** This principle guides you in understanding the impact of your cloud workload and its future effects. It is important to consider the entire life cycle of your workload, from customer use to eventual decommissioning. Through this understanding, you can set KPIs and monitor the progress toward a more sustainable cloud environment. * **Establish sustainability goals:** This principle focuses on establishing long-term sustainability goals such as reducing the resources required per transaction. Also, assess the ROI on existing workloads. Identify the resources required to achieve cloud sustainability goals and assign them to the appropriate owner. Plan for growth in a way that reduces impact intensity when assessed against a suitable unit, such as a transaction or user. This way, goal setting helps you visualize a clear picture of how to enhance your overall sustainability efforts and prioritize areas for improvement. * **Maximize Utilization:** This design principle focuses on another important lever for cloud sustainability: right-sizing. AWS recommends implementing an efficient design to enhance the energy efficiency of the underlying hardware. Moreover, minimize or eliminate resource and waste storage usage to further reduce your cloud's impact. * **Anticipate and adopt new, more efficient hardware and software offerings:** Monitor, evaluate, and stay in sync with the * **Use managed services:** An effective way to make the most of resources and move towards sustainability is to share services across a large customer base, maximizing resource usage and minimizing the infrastructure required for cloud workloads. Let’s say multiple customer sets are sharing the load of common data center components, such as power and networking, by migrating workloads to the AWS Cloud and adopting managed services like * **Reduce the downstream impact of your cloud workloads:** As an organization, focus on minimizing the energy and resources your customers need to use your cloud services. Also, minimize the need for clients to upgrade their devices to use your services. * **Sustainability as a non-functional requirement:** AWS suggests that adding cloud sustainability to your business requirements may lead to cloud cost savings by focusing on maximizing resource value and minimizing usage. ### **Best Practices for Sustainability** Best practices for sustainability in the cloud include Region selection, Alignment to demand, Software and architecture, Data, Hardware and services, and Process and culture. In the AWS Well-Architected Review, the below-mentioned specific questions are designed to evaluate your cloud sustainability, focusing on the key areas of best practices: For each of these questions, AWS has developed standard best practices that serve as benchmarks for determining the performance efficiency of your cloud infrastructure. ## **How is an AWS Well-Architected Review conducted?** Let us now understand the step-by-step process of conducting a successful AWS Well-Architected Review. **Step 1: Define Objectives and Scope** The first and foremost step is to be transparent about the objective and scope of your AWS Well-Architected Review. This will include specifying the areas you would like to be assessed and the specific goals you aim to achieve through this AWS WAR process. **Step 2: Identification of Workload** The second step is to define the workload you plan to measure. Understand its components, dependencies, and the business goals it serves. **Step 3: Collaborate with the Right Team** This is one of the most crucial steps. _**Actionable Advice:** The AWS Well-Architected Review process is quite extensive, time-consuming, and requires a specialized skill set. If your organization lacks the time or resources for a thorough review, partnering up with a trusted AWS Well-Architected Partner can be a logical and wise alternative. AWS Well-Architected Review Partners ensure your cloud workloads are evaluated comprehensively and specified objectives are met. It can also be cost-effective, as partners like CloudKeeper offer no-cost AWS Well-Architected Review._ **Step 4: Access the AWS Well-Architected Tool** _**AWS Well-Architected Tool (Source: AWS)**_ The AWS Well-Architected Review Tool helps you assess the current state of your workloads and applications against AWS-defined architectural best practices. A few things to note about the AWS Well-Architected Tool: * The AWS Well-Architected Tool is accessible by logging into the AWS Management Console with your AWS account. * To access the AWS Well-Architected Tool console, you must have a minimum of permissions. * There is no additional cost required for the AWS Well-Architected Tool. You just pay for the underlying AWS resources. **Step 5: Select the Pillars** AWS advises following the pillar order as outlined in the Well-Architected Framework. Select the relevant pillars of the Framework based on your workload. However, in some cases, your business might need to focus solely on one or more pillars. For Example, if you have made changes to your security configurations, you might want to assess them through the Security pillar. Choose the most relevant pillars that you want to focus on throughout the AWS Well-Architected Review for each workload. **Step 6: Answer the Pillar Questions by AWS Well-Architected Tool** As stated above, each pillar in the AWS Well-Architected Review comprises a series of questions aligned with best practices. These questions serve as the foundation for the next steps; thus, answer them honestly. **Step 7: Collect Data and Analyze** It will be easier for your team to assess workloads accurately if they have access to a comprehensive dataset. Compile data about your workload, costs, security rules, architectural designs, configuration details, and documentation. Based on the data gathered, conduct a thorough assessment against the pillars of the AWS Well-Architected Review to identify strengths, weaknesses, and opportunities for optimization. **Step 8: Identify Improvement Opportunities** Based on the analysis, the AWS Well-Architected Tool will offer suggestions and best practices for each pillar. Collaborate with your team or an **Step 9: Create a plan and Implement Changes** Create an action plan that serves as a roadmap for improvements, outlining the steps to manage your workload in line with AWS best practices. Now it's time for action. Decide on the roles and responsibilities, assign action items to your team, and set a deadline for each task. Choosing one out of many reliable cloud resellers for AWS Well-Architected Framework Review partners can be of great help here and ensure that the highlighted upgrades are implemented in accordance with the framework's best practices. Regularly monitor and track the progress of these changes to verify their effectiveness. **Step 10: Re-iterate and Optimize** Once the changes have been implemented, return to the AWS Well-Architected Review Tool to evaluate how the improvements have impacted the architecture as a whole. Remember, AWS Well-Architected Review is not a one-time effort; it’s an iterative process. ## **What should be the frequency of AWS Well-Architected Reviews?** There's no single ‘one-size-fits-all’ answer to the frequency of AWS Well-Architected Reviews. This may depend on various factors and scenarios. The scenarios below demand AWS Well-Architected Reviews to be conducted in a more frequent manner: * If your AWS environment changes rapidly with new deployments and features. * If you are concerned about a particular pillar. * If you are preparing for any major event such as an application launch. In a stable AWS environment with a mature Well-Architected Framework, the frequency of AWS WAR may be lower than in other scenarios. AWS recommends conducting the AWS Well-Architected Review regularly or at major milestones in the workload’s lifecycle, such as moving from Test to Production. Evaluate the criticality of your workloads, the maturity stage of your cloud, the organization's goals, and your specific circumstances, and adjust the frequency of AWS Well-Architected Review accordingly. ## **Conclusion** AWS Well-Architected Review is a great investment for your cloud architecture. The goal here is not only to With the help of AWS WAR and by following established best practices, organizations can avoid common pitfalls and make informed choices when building sustainable cloud systems. Plus, the best part? The framework is constantly updated as AWS learns more from its vast customer base. This ensures you have access to the latest best practices. So, whether you're new to the cloud or a seasoned pro, remember that the AWS Well-Architected Review equips you to build a future-proof cloud environment. Happy Architecting & Reviewing! Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents In the ever-evolving landscape of cloud computing, achieving architectural excellence is paramount for organizations leveraging Azure services. Enter the Azure Well-Architected Review, a meticulous blueprint designed to elevate cloud solutions to unparalleled reliability, scalability, and efficiency. Let's unravel the essence of this review and understand its pivotal role in shaping cloud excellence. ## **What is the Azure Well-Architected Review?** As technology requirements evolve, the deployment of business-critical applications becomes increasingly complex. Microsoft introduced the Azure Well-Architected Framework to assist organizations in managing this complexity. This framework consists of a collection of Azure architecture best practices designed to guide new and existing users through their cloud journey, ensuring maximum cloud ROI. The ## **How does the Azure Well-Architected Review help?** The Azure Well-Architected Review offers several key benefits to organizations: 1. **Enhanced Workload Optimization:** Organizations can optimize and rearchitect workloads to align with business needs, promoting efficiency, productivity, and cost-effectiveness. Secure access enables organizations to customize their approach to adapt to evolving scenarios. 2. **Risk Mitigation:** By designing and building cloud architectures, organizations gain better visibility into data streams, allowing them to analyze and control risks effectively. This enhanced visibility enables proactive threat detection and mitigation actions. 3. **Accelerated Innovation:** With optimized workloads and mitigated risks, organizations can explore new applications and services with agility. The ability to introduce new products and deploy applications without disrupting operations fosters innovation and accelerates development. 4. **Reduced infrastructure costs:** By implementing the recommendations from the review, organizations can streamline their infrastructure, rightsize resources, and eliminate unnecessary expenses, ultimately 5. **Increased scalability:** The review may recommend best practices for designing scalable solutions, such as leveraging Azure services like The Azure Well-Architected Review and Framework are invaluable tools for organizations to assess their cloud architecture and performance. A robust and ## **The five pillars of the Azure Well-Architected Framework** The Azure Well-Architected framework offers a collection of Azure's finest practices to facilitate the development and delivery of exceptional solutions. The Five pillars of the Azure Well-Architected Framework represent a series of guiding principles for constructing and launching top-tier solutions on the Azure platform. The Five Pillars of Azure Well-Architecture Framework are as follows: 1. **Cost Optimization** : With the increasing adoption of cloud solutions, optimizing existing cloud costs is necessary to extract maximum value. * Understanding and forecasting costs * Optimizing workloads * Controlling cloud costs 2. **Operational Excellence** : Operational excellence entails principles to streamline cloud operations and processes to ensure enhanced customer experiences. Azure contributes to successful operational excellence architectures through the following methods: * Implementing modern practices in designing, building, and orchestrating cloud solutions. * Leveraging cloud cost * Utilizing * Incorporating testing practices throughout the application deployment process and ongoing operations to ensure reliability and efficiency. 3. **Performance Efficiency** : The performance efficiency pillar of * Scaling up (add more resources to an instance) and scaling out (add more instances to a service) * Optimizing network performance * Optimizing storage performance * Identifying performance bottlenecks in applications 4. **Reliability** : Businesses today necessitate dependable cloud workloads capable of resilience and continuous functionality even amidst failures. The reliability pillar of principles evaluates the robustness of applications deployed on Azure. With cloud resilience, organizations can: * Design and manage mission-critical systems confidently and effectively. * Establish availability and recovery criteria tailored to workload degradation and business requisites. * Employ architectural best practices to pinpoint potential failure points within existing architecture and assess application responses to failures. * Conduct simulations and forced failovers to evaluate detection and recovery capabilities across diverse failure scenarios. * Ensure consistent application usage through reliable and replicable procedures. * Monitor application health for early failure detection, identification of potential weaknesses, and overall application health assessment. * Respond to failures and disasters by implementing predefined strategies for resolution. 5. **Security** : In today's digital landscape, data is the most invaluable asset for any organization. Hence, ensuring security becomes paramount when constructing cloud architecture. Azure * Identity management * Protect your infrastructure * Application Security * Data sovereignty and encryption * Security Resources ## **How can CloudKeeper help?** As a certified Azure Partner, CloudKeeper leverages its expertise and experience to facilitate organizations in navigating the Azure Well-Architected Review journey seamlessly at no cost. Our seasoned professional team helps you In conclusion, the Azure Well-Architected Review is a cornerstone for organizations embarking on their Azure cloud journey. By embracing this holistic framework, organizations can architect cloud solutions that embody excellence across security, reliability, performance, operations, and Azure cost optimization domains. With CloudKeeper's support, organizations can confidently begin their transformative journey, knowing that their Azure environments are primed for success in the dynamic world of cloud computing. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents Cloud Cost optimization is a critical focus when managing cloud infrastructure on AWS. For EC2, AWS offers various tools to help organizations minimize their cloud spending while maintaining operational efficiency. Two significant strategies are EC2 Reserved Instances (RIs) and Savings Plans, designed to optimize EC2 costs by committing to a specific usage level in exchange for substantial discounts. However, to maximize cloud cost cost savings, it’s essential to understand the concepts of **Coverage and Utilization.** These play a pivotal role in realizing the ## **AWS Reserved Instances: An Overview** AWS Reserved Instances (RIs) allow us to reduce costs by committing to specific EC2 usage for one or three years. AWS RIs can offer up to 72% in discounts compared to AWS On-Demand pricing. However, understanding AWS Reserved Instances pricing options, RI types, and their flexibility is essential for effective cloud cost optimization. **Types of Reserved Instances** **Standard Reserved Instances:** Offer the highest discount of up to 72%, ideal for predictable workloads. However, they lack flexibility in modifying attributes like instance type or operating system and cannot be sold during the term's first and last 30 days. **Convertible Reserved Instances:** Provide discounts up to 54% but offer greater flexibility by allowing changes in attributes such as instance type and operating system. These instances cannot be sold but can be exchanged for others with different attributes. It’s also possible to exchange CRIs with a future expiration date, which, in effect, reduces the point-in-time commitment amount. **RI Payment Options** AWS provides three payment options for RIs: **All Upfront (AURI):** Provides the highest savings by paying the entire term upfront. **Partial Upfront (PURI):** Offers moderate savings with a combination of upfront payment and regular costs. **No Upfront (NURI):** Provides the least savings but offers the flexibility of deferring all payments until they are incurred. **Applying Reserved Instances to On-Demand Instances** Reserved Instances automatically apply to matching On-Demand instances running in our AWS account. To receive the discounted rate, the On-Demand instance must match the following attributes of the Reserved Instance: **Instance Type:** A combination of the instance family (e.g., m4) and size (e.g., large, xlarge). **Region:** The region where the instance is purchased. **Tenancy:** The type of hardware (single or shared) on which the instance runs. **Platform:** The operating system (Windows or Linux/Unix). Because Reserved Instances are discounts applied to On-Demand instances, their prices are tied to the base price of the On-Demand instance. However, the cost of a Reserved Instance is influenced by four key variables: 1. Instance attributes (type, region, tenancy, platform). 2. Term commitment (1 or 3 years). 3. Payment options (All upfront, Partial upfront, No upfront). 4. Offering class (Standard or Convertible). These factors determine the level of savings a Reserved Instance can provide compared to AWS On-Demand pricing. To learn more about Common Pitfalls and Essential Considerations while purchasing AWS Reserved Instance, check out our ## **Key Concepts in Cost Optimization: Coverage, Utilization, and Wastage** **Coverage** Coverage refers to the portion of On-Demand usage offset by Reserved Instances. It ensures that we are covering as much EC2 usage as possible with discounted RIs, a key to cloud cost optimization. **Coverage %** = RI Hours Used / Total On-Demand Hours + RI Hours Used **Example:** If you had instances running for 100 hours in total, and 60 of those hours were covered by Reserved Instances, the RI Coverage would be: This means 60% of your instance usage was covered by Reserved Instances, and the rest was covered by AWS On-Demand pricing. **Utilization** Utilization measures **Utilization %** = RI Hours Used/ Total RI Hours Purchased **Example:** If you purchased 100 hours of RI coverage in a month but only used 70 hours, your utilization would be 70%, which means that 70% of reserved capacity was used, while 30% went unused, resulting in **wastage.** **Wastage** Any time a Reserved Instance is not fully utilized, we are effectively wasting its cost-saving potential. Monitoring wastage is key to cloud cost optimization. We can minimize wastage by modifying or exchanging underutilized Convertible RIs, or by purchasing more suitable RIs based on our workloads. For example, if you have a **Utilization** of 70%, your **Wastage** would be 30%. This means that 30% of the time, your Reserved Instance is not being used even though you are paying for it. Learn more on how to ## **Monitoring RI Utilization and Coverage: Using AWS Tools** AWS provides a range of **RI Utilization Reports** In the AWS Management Console, we can generate RI Utilization reports to: 1. View the combined usage of all your purchased RIs in the chart and the utilization of individual RIs in the table. 2. View the utilization of RIs as the percentage of purchased RI hours in the chart. 3. View the number of RI hours used against the number of RI hours purchased in the table. 4. Select a single RI or a group of RIs in the table to view their respective utilization in the chart. 5. Use the information in the table to track the number of RI hours that are reserved but not used. We can also use **RI Coverage Reports** RI Coverage reports provide insight into how well our instance usage is covered by Reserved Instances. This helps us determine when additional RIs should be purchased or when to modify existing ones to 1. See the number of instance hours covered by RIs in the chart. 2. Track the number of hours that you have totally used and how many of those are covered by RIs. 3. View the number of hours covered by RIs against the On Demand hours in the table. 4. Select a single RI or a group of RIs in the table to view their respective coverage in the chart. We can also view RI recommendations based on historical usage patterns to make informed decisions about future RI purchases. ## **Break-Even Analysis for Reserved Instances - Daily** Performing a Break-Even Analysis helps us understand the minimum level of utilization required to justify purchasing an RI. **For example:** If an RI costs $0.07 per hour and the On-Demand price is $0.10 per hour, the maximum possible discount is 30%. **Explanation:** **100% Utilization:** When the Reserved Instance (RI) is fully utilized, we receive the maximum 30% discount. Over a 24-hour period, the total cost with RI is $1.68 compared to $2.40 for On-Demand instances. This results in a clear cost-saving. **50% Utilization:** If the instance is only used for 50% of the time (12 hours), there is a wastage for the remaining 12 hours where the RI cost still applies. The daily spend for RI remains $1.68, but the AWS On-Demand pricing is reduced to $1.20 for 12 hours. In this case, using an RI results in a negative saving since the total spend is higher than On-Demand. **40% Utilization:** Similarly, for 40% utilization, there are more wasted hours with the RI, increasing the negative savings. **Break-Even Point:** The break-even point occurs when the instance is used for 16.8 hours per day(70% utilization). At this point, the savings from the RI offset the higher cost of not using it fully. This analysis guides our decision on whether to purchase an RI or opt for On-Demand instances based on workload predictability and usage patterns. **What Happens When an RI Expires?** When an EC2 Reserved Instance expires, the associated instances continue to run but revert to AWS On-Demand pricing. To maintain cloud cost savings, it is essential to either renew the RI or evaluate if the instance still requires a long-term commitment. ## **Conclusion** AWS Reserved Instances are a powerful way to achieve cloud cost optimization, but understanding how to monitor and manage Coverage, Utilization, and Wastage is crucial for maximizing savings. By leveraging AWS tools such as Cost Explorer and performing regular break-even analysis, we can ensure we are making data-driven decisions to optimize our EC2 spending. Understanding these critical concepts will enable us to take full advantage of the cost-saving opportunities that AWS EC2 Reserved Instances provide, ultimately aligning our cloud spending with operational requirements and financial goals. _Do you want to switch to a smarter AWS RI Management, and receive benefits like zero-touch RI Management, the flexibility of on-demand for all your Amazon EC2 resources, a buy-back guarantee for unused reserved instances,__, and much more, at no cost from your pocket? If your answer is yes, then_ _is precisely what you're looking for.__today._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Product Manager Atiya brings over 5 years of expertise in product management, specializing in Data & Analytics, AI, and Machine Learning. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents The cloud has become a game-changer for organizations of all sizes, with its enticing blend of cloud cost savings and data-sharing capabilities being prime benefits. Driven by a compelling range of business advantages, enterprises are undergoing a massive cloud migration movement. As IT leaders manage the migration process, achieving a robust cloud environment is challenging. Just like corporate governance is designed to cover corporate strategy, ethical behavior and risk management of the organizations, businesses must have a certain set of rules to handle the overall cloud efficiency and its costs. That is where cloud governance comes into play. Whether it is AWS data governance, Azure governance, or GCP governance, their impact on business efficiency is of supreme importance. ## **What is Cloud Governance?** Cloud policy and cloud governance are like a set of rules and promises that state the intention and the approach to follow the rules of cloud-related activities for process streamlining. According to the FinOps Foundation, a**‘Cloud Policy is a clear statement of intent, describing the execution of specific cloud-related activities in accordance with a standard model designed to deliver some improvement of business value’**. Likewise, as per FinOps Foundation, ‘Cloud Governance is a set of processes, tooling or other guardrail solution that aims to control the activity as described by the Cloud Policy to promote the desired behavior and outcomes.’ FinOps Foundation states that Cloud Governance executes the Policy by the following three methods: 1. **Guidelines** – that set out best practices for policy implementation and how it can be achieved. These are advisory, rather than mandatory. 2. **Guardrails** – formal processes and structures that define mandatory pathways for policy-compliant action, possibly with consequences for non-compliance. 3. **Automation** – processes that automate policy implementation and which therefore control how compliant actions are carried out. Cloud governance helps in maximizing the ROI by aligning the activities within the cloud by supporting the ## **Importance of Cloud Governance** Shifting from traditional data center practices to embracing the Cloud FinOps culture, characterized by specific attitudes and behaviors focused on extracting business value from cloud technology, poses a significant challenge. Policy and cloud governance help in A cloud governance framework is a structured and comprehensive set of policies, procedures, and controls that regulate how users work in cloud environments for consistent performance of cloud services and systems within an organization. It is crafted to ensure system integration, data security and efficient cloud deployment to meet business goals. Implementing and monitoring the cloud governance framework allows businesses to improve oversight and control over cloud operations like data management, data security, risk management, legal procedures, and cloud The cloud governance has a few more advantages as follows: * Reduces time and effort spent on manual tasks. * Optimizes cloud resource management. * Minimizes security risks. * Improves visibility and business continuity. * Regulates and monitors data access. During the early stage of cloud adoption, Cloud Governance plays a crucial role in implementing FinOps personas across the organization. According to the FinOps Walk maturity model, organizations are classified into three categories namely Crawl, Walk and Run. Source: ## **Challenges faced in implementing effective cloud governance** Developing and implementing Cloud Governance in an organization involves a few challenges which need to be addressed. 1. **Cloud adoption:** Transitioning from the traditional data center to cloud infrastructure involves several challenges like skill gaps, lack of metrics for measuring performance and risk, and credential and access management. Understanding the process of migrating from on-premises data centers and 2. **Integration with the existing IT infrastructure:** Many organizations have existing IT infrastructure. For implementing effective cloud governance, a thorough understanding of the existing system, data flows, and dependencies is required. 3. **Balancing between security and compliance with innovation:** Promoting innovation and agility without compromising on security and compliance is a challenge that cannot be overlooked. Cloud security challenges like data breaches and system vulnerabilities require careful planning and designing of policies and controls. Building a strong cloud governance strategy helps in keeping the organization’s cloud environments safe from adversaries. ## **Key components of a robust cloud governance strategy** The following are the key components of the cloud governance strategy: 1. **Data Management:** Data classification according to risk, business value, and compliance requirements provides clear guidance for managing the entire data lifecycle. 2. **Operations Management:** A well-defined cloud governance strategy helps in cloud cost monitoring and performance to detect unusual deployments of cloud resources. It includes how the cloud resources deliver services. 3. **Financial Management:** Cloud governance strategies establish the guidelines and policies to optimize cloud usage and avoid cost overruns. By abiding by the cloud governance framework in an organization, keeping a tab on financial management becomes easy. 4. **Infrastructure and Configurations Management:** By adopting a robust cloud governance strategy, organizations can easily manage configurations allowing them to control the storage and manage dynamic cloud infrastructure. 5. **Security and Compliance Management:** The cloud has made information access and sharing easy. One of the important pillars of cloud governance is the management of security policies to avoid data breaches. Organizations can 6. **Performance Management:** Performance metrics should be regularly monitored to ensure efficient cloud infrastructure usage and cloud service delivery. ## **Best practices for effectively managing multiple cloud service providers** Multiple cloud service providers have benefits if managed by adopting the **The 5 FACES of Good Cloud Policy & Governance:** Source: Multiple cloud service providers can be managed by adopting the following approach: 1. Well-defined objectives and strategies. 2. Choosing the right cloud service providers. 3. Adopting cloud governance in the organization. 4. Cloud cost monitoring. CloudKeeper is a _CloudKeeper delivers instant and guaranteed cloud cost savings, in-depth cost analytics, and expert-backed optimization guidance. Want to learn more? _ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents The shift to cloud computing has revolutionized businesses' operations, providing scalability, flexibility, and efficiency. The global public cloud services market Among cloud service users globally, an average of 30% of cloud spending is wasted. This has become a serious issue among cloud users. As companies embrace cloud services like AWS, the need to streamline expenses and implement cloud cost optimization strategies becomes paramount. Cloud costs often spiral due to three major factors: underutilized resources, complex pricing models, and lack of visibility into spending patterns. Let’s talk about them in detail: * **Complexity in Pricing Models** The complexity in cloud pricing models arises from the diverse range of services, pricing tiers, and billing structures offered by cloud service providers. Understanding and managing these pricing models can be challenging for organizations, making it difficult to predict and optimize cloud costs effectively. * **Lack of Visibility and Transparency** The lack of visibility and transparency in cloud cost management stems from a lack of comprehensive insights into cloud usage, spending patterns, and resource utilization, which impedes accurate tracking and effective expense optimization. Without detailed usage data, organizations struggle to identify where resources are allocated and if they're being utilized optimally. * **Resource Underutilization** Resource underutilization in cloud environments is when cloud resources, such as instances, storage, or databases, are not fully utilized or idle for extended periods, which is precisely what effective cloud cost optimization addresses. This case occurs for the following reasons: 1. Idle Resources. 2. Overprovisioned Resources. 3. Unused Storage & Compute Power. 4. Suboptimal Scaling Strategies. ## **Cloud Cost Optimization** To ### **Step 1: Assess and Analyze** The initial phase of cloud cost optimization necessitates a * Understanding the interplay between different components. * Identifying trends in resource consumption. * Discerning any irregularities or inefficiencies that might contribute to increased cloud costs. This phase sets the groundwork for informed decision-making by providing a clear picture of the existing infrastructure and highlighting areas primed for optimization to drive ### **Step 2: Right-Sizing Resources** One of the most effective strategies to curtail unnecessary expenses in a cloud environment is to By meticulously analyzing usage patterns and performance metrics across resources—such as compute instances, storage volumes, and database configurations—businesses can accurately determine the appropriate size to support their operations and minimize excess cloud allocation & purchase. Right-sizing involves a balance among the below-mentioned conditions: * Avoiding over-provisioning, which leads to idle resources and increased cloud costs. * Preventing under-provisioning, which can lead to performance bottlenecks or inefficiencies. * Right-sizing AWS resources involves strategically matching instance capacity and configuration to the actual workload requirements. * Scheduling resources efficiently ensures they run when needed, reducing overall cloud spend. **Step 3: Automate Cost Management** Automation streamlines and significantly assists with cloud cost optimization by taking over various operational aspects, ensuring that cost-saving measures remain consistent and responsive to the constantly changing cloud environment. By leveraging automation tools and scripts, businesses can orchestrate tasks such as: * Provisioning and de-provisioning resources. * Scheduling instances to operate only during required periods. * Implementing scaling policies in response to workload fluctuations. * Executing cloud cost-monitoring algorithms in real-time. This proactive approach reduces the manual effort involved in managing resources and enhances accuracy and agility in adapting to shifting demands. ### **Step 4: Implement Cost Allocation and Tagging** Tracking expenses at a granular level across cloud infrastructure is essential for gaining comprehensive insights into cloud cost allocation and spending. This approach involves dissecting costs across diverse services, applications, and functionalities within the cloud ecosystem, providing a detailed breakdown of where and how expenses are incurred. Businesses gain a precise understanding of cost distribution by delving deep into the specifics of resource usage, data storage, networking, and various cloud services. This level of scrutiny and understanding of cost attribution aids with the following areas: * Fine-tuning operations. * Maximizing resource efficiency. * Fostering better financial control and planning within the cloud environment​. ### **Step 5: Utilize Reserved Instances and Savings Plans** * #### **Reserved Instances** Cloud service providers offer RIs, a billing option that allows users to reserve capacity for specific instance types in exchange for a significant discount compared to on-demand pricing. Here's how they work: 1. **Cost Savings:** RIs offer substantial discounts (up to 70-75%) compared to on-demand instances. 2. **Term Length and Payment Options:** They are available in various term lengths, such as one-year or three-year contracts, and offer different payment options like all upfront, partial upfront, or no upfront. 3. **Instance Flexibility:** RIs provide flexibility in choosing instance types, availability zones, and platforms. * #### **Savings Plans** Savings plans are another flexible pricing option that offers significant opportunities for cloud cost optimization. Savings plans offer costs up to 72% lower than on-demand pricing for similar resources. They provide similar benefits to RIs but with more flexibility: 1. **Flexibility Across Services:** Unlike RIs, Savings Plans offer flexibility across a broader range of services and instance families within a cloud provider's ecosystem. 2. **Usage Flexibility:** Savings Plans automatically apply savings across a broad set of instance usage, regardless of instance size, region, or operating system. 3. **Pay-As-You-Go Model:** Users commit to a consistent amount of usage (measured in dollars per hour) on a one- or three-year term. Properly strategizing the use of RIs and Savings Plans based on workload patterns and requirements enables organizations to maximize cloud cost optimization and allocate resources more efficiently in the long run. ### **Step 6: Continuous Cloud Cost Optimization through Recommendations** Continuous cloud cost optimization through infrastructure recommendations involves an ongoing process of refining and enhancing resource allocation and usage based on real-time insights and suggestions. These recommendations encompass a wide spectrum of adjustments, from rightsizing instances and storage volumes to suggesting reserved capacity purchases and advising on adopting more cost-effective services or pricing models. The constant analysis of the below-mentioned metrics can ensure cost efficiency: * Usage patterns. * Performance metrics. * Cost data. These recommendations evolve with the changing dynamics of the cloud ecosystem, ensuring that businesses stay ahead in optimizing their infrastructure for cost efficiency. ## **CloudKeeper: A solution to your FinOps challenges** Navigating the intricate web of cloud costs demands a multifaceted strategy, and in this expedition, CloudKeeper emerges as an invaluable ally. Armed with comprehensive analytics, robust automation capabilities, and a continuous stream of cloud cost optimization recommendations, CloudKeeper helps businesses unravel the complexities of cloud costs and extract the utmost value from their cloud initiatives. With its arsenal of Cloud FinOps solutions like: * * * * * Providing a holistic view of cloud expenditures and leveraging automation to streamline processes, CloudKeeper paves the way for businesses to enhance transparency, fine-tune their spending, and align their cloud investments with strategic objectives. As the cloud continues to evolve, CloudKeeper can be a trusted companion, navigating the complexities and guiding businesses toward cost-efficient and optimized cloud operations. _**Experience CloudKeeper firsthand by**_ _**.**_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents In the dynamic realm of cloud computing, cloud cost optimization and cloud cost management are paramount concerns for businesses leveraging AWS services. AWS Cost anomaly detection serves as a compass, guiding your attention to In the context of CCM (Cloud Cost Management), the anomaly detection mechanism acts as a safeguard, allowing organizations to swiftly address deviations and maintain precision in financial planning within their cloud environments. AWS Cost Anomaly Detection emerges as a crucial element in this endeavor. Not only does it provide insights into irregularities and deviations in cloud expenditures, but it also In this step-by-step guide, we will delve into the significance of cost anomaly detection, common anomalies in AWS infrastructure, effective implementation strategies, ## **Why is cost anomaly detection important in AWS?** AWS Cost anomaly detection is a cornerstone for organizations striving to uphold financial transparency and operational efficiency. This crucial mechanism operates proactively, employing advanced algorithms to identify unusual expenditure patterns or deviations swiftly. Cost anomaly in the cloud can be minimized by: ### **1. Preventing budget overruns** One of its primary roles is to prevent budget overruns, acting as a financial safeguard against unexpected spikes in expenditures that could strain allocated budgets. ### **2. Optimizing resource utilization** Anomaly detection ensures that resource utilization remains optimized by identifying inefficient spending or underutilized resources, thereby promoting efficiency in operational workflows. ### **3. Aligning financial objectives** Beyond mere financial oversight, this mechanism aligns financial objectives with operational goals, ensuring that every dollar spent contributes effectively to the organization's overarching mission. ## **Common Cost Anomalies in AWS Infrastructure** Understanding the common anomalies that can arise within AWS infrastructure is crucial for organizations aiming to ### **1. Sudden spikes in data transfer costs** Instances of abrupt increases in data transfer costs often stem from heightened data traffic or unexpected data movements between regions. Identifying and addressing these spikes is essential to ### **2. Unanticipated spikes in compute utilization** Unplanned surges in compute utilization can occur due to unexpected workload increases or inefficient resource allocation. Recognizing these spikes is critical for optimizing resource usage and preventing associated cost escalations. ### **3. Charges from unused or idle resources** Instances or storage that are provisioned but not actively utilized can lead to charges that contribute to unnecessary expenses. Identifying these idle resources is key to implementing ## **Implementing Effective Cost Anomaly Detection in AWS** Implementing a robust AWS cost anomaly detection system is a multifaceted process that combines key steps and systematic approaches such as: ### **1. Setting up anomaly detection alerts** Defining thresholds for spending patterns is the initial step, where predefined limits are established. When these thresholds are breached, the system triggers notifications, serving as an early warning mechanism for potential anomalies. ### **2. Establishing baseline metrics** Creating a baseline for normal behavior is essential. This involves historical cloud cost analytics & spending patterns and identifying standard ranges of expenditure. This baseline becomes a reference point, facilitating the identification of anomalies by contrasting them against established norms. ### **3. Creating notification workflows** To ensure a swift and coordinated response, it's imperative to have well-defined notification workflows. When an anomaly is detected, these workflows ensure that the right personnel are promptly informed, streamlining the process of investigation and resolution. ### **4. A systematic approach for proactive identification** The overall approach is systematic, emphasizing proactive identification and resolution of irregularities. By combining anomaly detection alerts, baseline metrics, and notification workflows, organizations can establish a comprehensive system that actively safeguards against potential disruptions in cost patterns. ## **Tools and Techniques for Monitoring AWS Cost Anomalies** Monitoring cost anomalies in AWS involves a spectrum of tools and techniques, each contributing to a comprehensive strategy. Below are the following tools and techniques: ### **1. AWS Cost Explorer** * **Comprehensive historical view:** AWS Cost Explorer offers a comprehensive view of historical spending patterns, allowing organizations to trace their financial footprint over time. * **Customized reporting:** This tool empowers users to create customized reports, tailoring the analysis to specific needs and gaining deeper insights into expenditure. ### **2. AWS Budgets** * **Custom cost and usage budgets:** AWS Budgets facilitates the establishment of custom cost and usage budgets, aligning financial goals with predetermined thresholds. * **Alert notifications:** The tool comes equipped with alert notifications, ensuring that deviations from set budgets trigger timely alerts for proactive intervention. ### **3. Third-Party Solutions** * **Enhanced cloud cost analytics and visualization:** Third-party solutions extend the capabilities with additional features and integrations. These often include enhanced cloud cost analytics and visualization tools, providing organizations with a more nuanced understanding of their spending patterns. ## **Preventing and Controlling Cost Anomalies in AWS** Preventing and controlling AWS cost anomalies necessitates a combination of proactive measures and strategic interventions: ### **1. Setting up budget alerts** Initiating budget alerts ensures that organizations receive timely notifications as expenditures approach predefined thresholds. This early warning system allows for swift and targeted intervention before costs escalate. ### **2. Resource tagging** Resource tagging is instrumental in enhancing cloud cost visibility and accountability. By providing detailed information about the purpose and owner of each resource, organizations can ### **3. Regular reviews of cost reports** Regular reviews of cost reports serve as a proactive mechanism for identifying potential anomalies early on. These systematic reviews enable organizations to pinpoint irregularities and take corrective actions before they have a significant impact on the budget. ## **How does CloudKeeper help?** Any business’s cloud cost optimization journey needs more than “just savings.” CloudKeeper Lens is a Mastering AWS Cost Anomaly Detection requires a comprehensive understanding of the intricacies involved in cloud expenditure. This guide aims to equip businesses with the knowledge and tools needed to detect, prevent, and control cost anomalies effectively. _If you wish to save more,__with the CloudKeeper team to learn how you can achieve instant & guaranteed savings of up to 25% on the entire AWS Bill._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents Cloud cost optimization has long been a daunting challenge, and as cloud usage continues to surge, it's expected to persist. Enter As businesses expand and innovation continues to drive growth, the Here are some changes that are bound to happen in the Cloud FinOps industry going forward: **AI Dominance in Cloud Cost Analytics:** We witnessed the significant disruption caused by generative AI in 2023, and its integration into **Decentralized FinOps:** The traditional centralization of FinOps and cloud cost management will undergo a shift towards decentralization. Empowering individual teams to control their cloud resource costs promotes better accountability, resource optimization, and ultimately higher cost efficiencies. **Managing Costs Across Diverse Environments:** The existence of multiple cloud providers, each with its unique pricing model and billing system, will push organizations to adopt platforms that offer a unified view of costs across diverse environments, accompanied by enhanced tracking and analytics tools. **Intersection of FinOps and Security:** As Cloud FinOps becomes increasingly complex, the risk of abnormal spending patterns or unauthorized activities will rise. In 2024, Cloud FinOps will focus more on quickly identifying and addressing these **Integration of Sustainability:** Even AWS acknowledges the environmental implications of FinOps by adding sustainability as the sixth pillar of its To unlock a successful career in Cloud FinOps in this changing environment, you’ll not only need to possess technical skills but will also possess a holistic understanding of the product life cycle, efficient resource allocation, focus on relevant KPIs, and even strategic use of automation. Additionally, enrolling in Here are some recommended options along with details on how such courses can benefit you: ## **1.FinOps Certified Practitioner:** **** The FinOps Certified Practitioner certification is designed for professionals in cloud, finance, FinOps consulting, and technology roles, providing validation of FinOps knowledge and enhancing professional credibility. This certification provides fundamental knowledge of FinOps concepts, which is crucial for understanding the lifecycle phases of Inform, Optimize, and Operate. It’ll ensure you have a basic understanding of major cloud providers which is essential in the cloud industry. **Recommended Prerequisites:** * Understand the basics of how cloud computing works and know the key services of your cloud providers. * Be able to describe the basic value proposition of running in the cloud and understand the core concept of using a pay-as-you-go consumption model. * A base level of knowledge of at least one of the three main public cloud providers - AWS, Azure, and Google Cloud. **Who’s it for:** Designed for individuals planning to join a FinOps team, support Cloud FinOps or cloud financial management, or provide support to FinOps teams as consultants, vendors, or trainers. **Cost:** Self-paced - $599 ## **2. FinOps Certified Engineer** **About the Certification:** The FinOps Certified Engineer course delves into FinOps concepts, concluding with a certification exam for Engineer status. This certification emphasizes the role of an engineer enabling them to operationalize cloud infrastructure with FinOps, showcasing their ability to contribute effectively. **Who’s it for:** Engineers handling public cloud solutions and Infrastructure. This course emphasizes operationalizing cloud infrastructure with FinOps, showcasing their ability to contribute effectively to cloud financial management without being the primary FinOps practitioner. **Cost:** $699 ## **3. FinOps Certified Professional** **About the Certification:** The FinOps Certified Professional course is a comprehensive and hands-on FinOps training program that covers building, managing, and evolving FinOps teams. This course aims to advance the careers of an experienced FinOps practitioner, deepen their knowledge, and contribute at an advanced level. Learners will also get a chance to collaborate on a business case to address FinOps challenges in a sample organization. **Required Prerequisites:** * FinOps Certified Practitioner * 6+ months of FinOps work experience **Who’s it for:** Designed for experienced FinOps practitioners aiming to advance their careers, deepen their knowledge, and collaborate with professionals from diverse backgrounds. Ideal for those seeking to enhance their FinOps consulting expertise and contribute at an advanced level. **Cost of the course:** $3,750 ## **4. FinOps Personas courses** **** The FinOps Personas course offers an insightful overview of FinOps, emphasizing collaboration and understanding across various FinOps personas. Dedicated courses are available for each persona, including Engineer, Finance, Procurement, Product Owner, and Leader, promoting collaboration and understanding across different roles. **Cost of the course:** $150 ## **5. FinOps for Containers** **About the Certification:** FinOps for Containers offers a comprehensive review of container environments, catering to engineers engaged with container infrastructures. The course covers effective communication with non-engineers, identifying sources of wasted cost, integrating observability for cost tracking, and managing idle/shared elements within the environment. **Required Prerequisites:** * In-depth practical knowledge of one or more cloud providers. * Recommended: Fundamental certification in one or more cloud providers, ideally an architect-level certification. * Understanding of containerization concepts. * Experience with container services and orchestration environments. * Knowledge of cloud vendor billing, including tagging, account allocation, and spot billing. **Who’s it for:** Engineers or individuals managing container infrastructures, especially those serving multiple users in an organization. The course equips participants to comprehend expenditure across all environment components, communicate cost data effectively, optimize efficiency, and continually enhance Container usage efficiency. **Cost of the course:** $350 ## **6. 2.5.3 Onboarding Workloads** **About the Certification:** The Onboarding Workloads certification, a component of the FinOps Professional course and available separately, focuses on establishing an effective process for migrating and developing applications in the cloud. Through this course, you will gain insights into the importance of involving a FinOps team in the onboarding process, distinctions between onboarding in the cloud and on-premise data centers, identification of key activities, best practices, and a comprehensive understanding of what constitutes a successful workload onboarding process at different stages of FinOps maturity, including measurable success criteria. **Cost of the course** : $100 These certifications will not only equip you with essential skills but also demonstrate your commitment to staying updated in a rapidly evolving cloud landscape. They can be valuable assets in unlocking diverse career opportunities in cloud financial management, The FinOps Foundation even extends financial assistance through its ## **About The FinOps Foundation** _The_ _, under The Linux Foundation, is committed to advancing individuals practicing cloud financial management through best practices, education, and standards. With a community of over 12,000 individuals from 3500+ companies, it offers diverse training and certification programs. The foundation's partner certification programs, such as FinOps Certified Platform and FinOps Certified Service Provider, include numerous major service and platform providers including_ _, reinforcing its industry-wide impact and collaboration._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 8 8 Table of Contents When we talk about modern cloud infrastructure, managing Kubernetes clusters with Amazon Elastic Kubernetes Service (EKS) becomes an essential step. However, EKS cost optimization is not an easy task since EKS workloads are dynamic, making it tough to keep track of and control the costs. To assist the business entities in handling this challenge, we built a dashboard dedicated to tracking EKS costs at the granular level. This gives users transparency in every detail of resource expenditure and assists stakeholders in cloud cost reduction. ## **The Challenge: Monitoring resource level EKS Costs** As resource consumption increases, the cost also fluctuates, for example, CPU, memory, and node usage, which makes it very daunting at times for the stakeholders to get a sense of where the budget is going in reality. If businesses are not provided with granular-level cost insights, then it is very likely that the cost budgets will increase and important cloud cost optimization opportunities will be missed. ## **How the EKS Dashboard assists in data-driven decisions** The EKS cost tracking tool is integrated into CloudKeeper Lens, our proprietary platform for * ### **Previous 3 months of costs** Cost patterns can be identified by comparing the costs of the last 3 months. Historical trends help in finding the rationale behind the dip and rise in the cost. This statistic helps in * ### **CPU and Memory Costs Split** For most of the businesses, it is observed that CPU and memory contribute to the majority of the cost. With the help of this granular information, the user can identify and make a quantitative decision about whether the provisioning of resources is more than required or is appropriate. An e-commerce organization such as Flipkart that is using a platform to track user metrics can identify that around 30% of the overall EKS costs were because of the overallocation of CPU in various clusters. It can right-size the allocation of CPU using the data insights from the EKS dashboard, which can result in approximately 20% cloud cost reduction. **EKS Cost Allocation dashboard on CloudKeeper Lens** * ### **Cluster, Node, and Pod count** This provides a very clear picture of the environmental scale, displaying the clusters, nodes, and pod counts. This in turn ensures that the infrastructure growth is in alignment with the long-term business goals and supports * ### **Costs by Cluster, Namespace, and Region** Identify which particular clusters, namespaces, or regions are resulting in maximum expenses. This ensures that organizations are able to spot resources that result in the highest cost and can make rational calls about re-aligning the resources. A relevant use case for this can be for a telecom organization such as Airtel which provides services in many regions. They can use this granular level cost breakdown to form cost patterns between different regions like the US and Europe regions and make smarter resource deployment choices. For example, they can recognize that if they run certain resources in Europe, they would save 10% of the cost, which would be a better cloud cost optimization choice. * ### **Cost by Instance and Purchase Type** The platform also enables the user to view the breakdown of costs by the kind of EC2 instances utilized in the EKS cluster and also the option for purchase type (On-Demand, Reserved Instances, or Spot). This level of detail helps in overall cloud cost reduction as per the demand of the workload. * ### **Top 20 Node Instance Usage by Total Cost** Most cost-incurring node instances can be recognized using this tabular structure. By performing due diligence on these instances, a lot of costs can be reduced by optimizing usage. Taking a similar example as above, a telecom company could use this level of cost details to check what percentage of their nodes are being used for legacy systems and older workloads, which are not relevant now, and also whether the configurations set are inefficient in nature. As a next step, configuration can be optimized, smaller instances can be used, and overall costs can go down. **Cost breakdown of Top 20 resources** ## **Necessary business needs that can be solved using the EKS dashboard** ### **1. Module-Based Cost Allocation** Assigning and calculating the overall expenditure based on namespace, cluster, and also region enables the organizations to track the expenditure at a team level or module level, this encourages accountability within the teams. An insurance company wherein many technical teams are working together on various modules can use this dashboard to allocate certain percentages of costs to each team so that tracking can be done efficiently. This amount of granularity and transparency encourages the teams to optimize their spending, and this can result in an overall cloud cost reduction of 10-20%. ### **2. Cost Reduction and Optimization** Not just usage transparency, actionable insights pertaining to cost savings are also a feature of this dashboard: * **Accurately sizing the resources:** Optimization of CPU and memory instances can be done by tracking resources that are either under-provisioned or over-provisioned. * **Optimizing the instances:** Look for * **Scaling Adjustments:** Clusters can be scaled up or down, so cost trends can be used to make cloud cost optimization decisions pertaining to scaling. One of our customers, an e-commerce organization, saved $80,000 by transitioning its resources and workloads from OD to spot during fewer traffic hours. This became possible using the detailed cost breakdown from EKS dashboard. ### **3. Geographic Cost Awareness** Companies can get to know the regions where they are incurring the maximum costs and can optimize accordingly; this transparency allows them to make data-driven rational decisions, such as moving non-critical tasks to less cost-intensive regions, resulting in significant cloud cost reduction in the long run. Take an example for the same, a global telecom company with a presence in multiple countries decided to shift 35% of its EC2 workloads from U.S. to South American regions, which resulted in a saving of $12,000 monthly with no major impact on performance. ## **Why you can’t afford to be without the EKS dashboard** Executing plans in the absence of a detailed EKS dashboard can result in missing out on important insights and opportunities for cost optimization. * **Lesser Visibility:** In the absence of granular level spend information, organizations may end up spending more cost on resources that are very less utilized and can often fail to recognize the inefficiencies in the resource allocation. * **Unoptimized Allocation of Funds:** Organizations have to allocate costs and budgets to various teams and modules. But if stakeholders do not have * **Missing Out on Potential Savings:** Due to a lack of spending clarity and having no detailed dashboard such as an EKS dashboard, organizations usually run instances on-demand and overpay, missing out on EKS cost optimization opportunities. ## **The value of the EKS dashboard: Enabling data-driven decisions** The EKS cost tracking dashboard is one of the most powerful tools available that can provide granular level cost insights, which can assist organizations to make better and more rational decisions as far as cost allocation in cloud infrastructure is concerned. * **Accurate Forecasting:** Identify the spending patterns and make data-driven financial calls for allocating resources in the future. * **Align Cloud Costs with Business Goals:** Organizations can align budgets and fixed expenses to each team and features to be developed, which will instill clarity and create accountability. This will ensure alignment with cloud cost optimization strategies and long-term business goals. * **Data-Driven Actions:** EKS dashboard can be utilized for the purpose of resource optimization, reduction in cost wastage, and also assist in overall cloud cost reduction. ## **Conclusion: The Strategic Advantage of EKS Cost Tracking** With the increase in the usage of Kubernetes environments, it is getting difficult to manage and keep track of EKS costs, but keeping track is very crucial for the long-term success of a business. CloudKeeper’s EKS cost-tracking dashboard ensures visibility and transparency for businesses so that they can manage their expenses better. With granular cost information across CPU, memory, regions, clusters, and instance types, organizations are equipped to restructure the usage of their resources and enhance their cloud cost optimization efforts. To conclude, CloudKeeper’s EKS dashboard is not just a cost-tracking tool but an important business asset that can assist companies in staying ahead in the market by making rational, data-driven cost decisions regarding their cloud infrastructure. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Product Manager Harsh is a distinguished Cloud Expert with an extensive background in product management. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents The on-demand characteristic of cloud computing allows users to access computing resources (such as storage, processing power, and applications) without upfront investment in infrastructure. While this flexibility is advantageous, it can also lead to Let’s dig deeper into the cause. ## **Areas of Overlooked Cloud Expenses- A ready checklist for the Finance team** When it comes to keeping an eye on expenses in the context of cloud cost management, organizations often overlook or underestimate several key areas, leading to unexpected costs. Here are some of the areas that are commonly missed: **1. Unused or underutilized Resources:** Failure to monitor and deactivate idle or underused resources, such as instances, storage, or databases, can contribute to a staggering 66% of avoidable cloud spend. Regularly optimizing resource utilization can **2. Data transfer costs:** Many cloud service providers charge for **3. Lack of cost allocation:** Without **4. Unplanned scaling and auto-scaling:** While auto-scaling can be a powerful tool for handling fluctuating demand, it can also result in unforeseen cloud cost spikes **5. Storage costs:** Cloud providers charge for storing data, and over time, if not managed properly, these costs can accumulate significantly. Failure to regularly assess and delete unnecessary or obsolete data can lead to inflated storage expenses. **6. Third-Party services and marketplace costs:** Integration of third-party services or applications from cloud marketplaces may come with additional costs that organizations might not account for initially. **7. Complex pricing models:** Different cloud services often have complex pricing models with various tiers, add-ons, and usage-based charges. Understanding the nuances of these models and accurately predicting costs can be challenging, leading to overspending. **8. Shadow IT or unapproved services:** Shadow IT, where employees procure cloud services independently without IT oversight, can be a major security risk and a hidden source of cloud cost leakage. Implementing strong governance policies and monitoring practices can help identify and eliminate these rogue costs, ultimately improving security and cloud cost savings. **9. Compliance and security costs:** Meeting compliance standards and ensuring data security in the cloud often involves additional costs for specialized services, certifications, or security measures that organizations might not initially anticipate. **Data Points Source:** G2’s Fascinating Cloud Computing Statistics for 2023. To address these areas and prevent overspending, organizations should implement robust cloud cost management practices. This includes regular monitoring and cloud cost optimization of resources, setting budgets and limits, implementing automated cost controls, utilizing cost-tracking & cloud cost optimization tools, educating staff about cloud cost management, and regularly reviewing expenditures against budgets to identify areas for improvement. ## **A cloud cost visibility & recommendation platform is a big “YES”** The realm of cloud computing offers vast potential for optimization to achieve cloud cost savings targets, but without a clear understanding of cloud usage patterns, organizations can easily fall into the cycle of overspending. A Cloud Cost Visibility and Recommendations Platform, designed for various cloud providers, offers organizations visibility and control over cloud expenses. The platform includes the following features, to ensure businesses have a greater view of their spends: * **Granular cloud usage tracking:** It provides a unified view of cloud spending across various cloud providers. This enables tracking expenditure per provider and identifying potential cloud cost-saving opportunities. Users can analyze resource-specific costs, aiding in optimizing cloud spending for better returns. * **Detailed breakdown reports:** The reports provide a visual representation of cost variations on a daily basis, allowing users to delve deeper into specific usage types for different cloud services. For example, identifying a surge in Amazon S3 storage usage on a specific day helps pinpoint areas for cloud cost optimization. * **Cloud cost optimization recommendations:** This functionality analyzes cloud usage patterns to suggest strategies for optimizing resource utilization, thus allowing organizations to enjoy great cloud cost savings, as per their business infrastructure requirement. * **Notifications:** This is one of the highly impactful features that offers concise daily summaries of cloud spending, highlighting breakdowns by provider, service, and resource. Users receive alerts for cost deviations, Reserved Instance (RI) expiry, and utilization. * **RI & savings plan utilization: **This feature helps in providing a consolidated view of active/expired reservations for various services. This overview aids in tracking reservations and identifying opportunities for consolidation and cloud cost optimization. Utilizing such cloud cost analysis platforms empower organizations to gain a clearer understanding of their cloud usage, identify underlying cost factors, and implement effective cloud cost optimization strategies. **A screenshot from the CloudKeeper Lens showing an overview of an AWS cloud billing.** ## **Leveraging cloud cost visibility tools for greater cloud cost savings** In conclusion, unmasking hidden cloud cost savings demands a comprehensive understanding of cloud usage and a proactive approach to managing expenses. CloudKeeper Lens, among other cloud cost management tools, plays a pivotal role in revealing obscured expenses, thereby empowering organizations to optimize their cloud spending effectively. Organizations must prioritize regular monitoring, rightsizing resources, automating workload management, and fostering a culture of cost consciousness to maximize savings opportunities. As businesses navigate the ever-evolving cloud landscape, the ability to uncover hidden costs and harness cloud cost efficiencies will undoubtedly be a defining factor in maintaining a competitive edge while ensuring financial prudence in the digital era. _**Experience CloudKeeper Lens firsthand by scheduling a demo —**_ _**.**_ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Everything You Need to Know About Agentic AI Everything you need to know about Agentic AI—how it works, real-world use cases, and why autonomous agents are the future of AI. By Team CloudKeeper 16 Jan, 2026 Cloud Computing Trends to Watch in 2026 A clear and actionable analysis of the key developments in cloud computing by 2026 and their impact on your bottom line. By Aman Aggarwal 13 Nov, 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents Recent news of Vega Cloud entering receivership has sparked concern across the FinOps community. Once positioned as a strong For many teams, this is the right moment to evaluate whether their current FinOps platform can support continuous optimization as cloud environments grow more complex. ## **When Vendor Uncertainty forces a Replacement Decision** Vega Cloud’s situation reflects a broader reality in the FinOps market. Cloud environments are evolving rapidly, but many cost tools struggle to keep pace. Visibility alone is no longer enough and static recommendations rarely translate into sustained Most importantly, long-term cloud ## **From Tools to Outcomes: Choosing the Right FinOps Partner** Businesses need a solution that not only delivers immediate savings, but also provides visibility, optimization, governance, and financial control as cloud complexity grows. Most providers offer tools, discounts, or consulting in isolation. What organizations should look for instead is a single partner that delivers all three seamlessly and continuously. Key priorities should include: * End-to-end cloud cost optimization, covering rate and usage optimization, * A unified FinOps platform, combining real-time visibility, automated optimization, commitment management, AI-driven insights, and ROI tracking. * Built-in expert support, including WAR, migration and modernization services, and unlimited 24×7 cloud support. * Proven outcomes at scale, with measurable savings, predictable spend, and long-term financial control. CloudKeeper provides just that. The comparison below helps clarify how CloudKeeper supports FinOps at scale. ## **Vega Cloud vs CloudKeeper** **Why CloudKeeper Is Built for your Long-Term FinOps Success** CloudKeeper is a comprehensive cloud cost optimization and FinOps partner built for organizations scaling fast on the cloud delivering guaranteed cloud cost savings from day one, through AI-led platforms and unlimited expert At the core is the CloudKeeper also operates as an authorized cloud reseller and premier partner, enabling access to private pricing agreements, flexible commercial models, and guaranteed savings from day one. With 15+ years of cloud expertise, 150+ certified engineers, 400+ customers globally, #1 rank on G2 for Cloud cost management with 100% Satisfaction Score, and recognition from leading industry analysts, CloudKeeper has proven its ability to deliver measurable, ongoing savings at scale. Disclaimer: This article is based on publicly available information and focuses on broader FinOps best practices rather than individual vendor circumstances. * * * ## **Frequently Asked Questions (FAQs)** **Q1. Why does Vega Cloud’s restructuring matter?** FinOps platforms are central to cost governance. Any disruption increases the risk of visibility gaps, delayed optimization, and cost leakage. **Q2. Should Vega Cloud customers consider switching now?** Yes. Evaluating alternatives early reduces exposure and avoids rushed decisions later. **Q3. What should businesses prioritize when choosing a replacement?** Businesses should look for an end-to-end FinOps partner, not just another tool. The right provider should combine rate and usage optimization, deep cost visibility, and continuous expert support, along with proven experience, delivering real savings for other customers. **Q4.How is CloudKeeper different from Vega Cloud?** Vega Cloud focuses on foundational visibility and recommendations, while CloudKeeper delivers end-to-end cloud cost optimization through a unified platform covering visibility, optimization, commitments management, governance, 24*7 expert and AI-assisted insights. **Q5. What is the safest next step for Vega Cloud customers?** Evaluate alternatives and plan a phased transition to maintain uninterrupted cost control. **Q6. Can migration be done without disruption?** Yes, a phased transition with parallel visibility will help maintain continuity. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents Booking tickets for a concert, building a high-performance game engine, or running AI video generators that go viral worldwide—people and businesses rely heavily on cloud computing to power these experiences. To ensure these services run smoothly, cloud resources must be scalable, cost-effective, and lightning-fast. While an optimal architecture is important, the processors have a massive role in their performance and cost efficiency. In its early days, AWS used x86 processors from Intel and AMD to power EC2 instances. These processors were reliable but not always optimized for the increasingly diverse and demanding workloads customers needed. Recognizing this, AWS set out to build a processor tailored specifically for the cloud leveraging the Arm-based technology. Arm processors, built on Reduced Instruction Set Computer (RISC) architecture, are known for their efficiency, scalability, and energy-saving capabilities. These processors deliver excellent performance at a fraction of the energy cost by stripping out unnecessary instructions and focusing on what truly matters. AWS leveraged this architecture to design and launch the AWS Graviton processor series. This blog will explore AWS Graviton's evolution, its benefits, and the scenarios where it truly shines. We’ll also highlight potential challenges in adoption and how CloudKeeper ensures a smooth migration journey. ## **What is AWS Graviton?** AWS Graviton is a family of server processors designed by AWS to improve the efficiency and performance of its cloud services. First launched in 2018 and built on Arm architecture, these processors are tailored to AWS’s specific needs. Initially, AWS Graviton instance types included EC2 resources for workloads like web servers, caching, and containerized applications. Over the years, AWS released Graviton2, Graviton3, and most recently, Graviton4 in 2023. These processors now power a wide range of AWS services beyond EC2, including databases like Amazon Aurora and RDS, analytics services like OpenSearch and EMR, and ## **What are the benefits of AWS Graviton?** AWS introduced Graviton to offer customers more value from their cloud infrastructure, by ensuring a broader range of cost-effective, high-performance instance types across AWS services. Cloud users tend to gain multiple benefits from leveraging these processors, which include: ### **Cloud Cost Savings** Graviton processors are budget-friendly without compromising power. Since AWS Graviton architecture is based on the Arm framework, they have a System-on-chip (SoC) design, making them more compact, efficient, and cost-effective. They’re known for delivering up to 40% better price performance than x86-based instances, helping businesses ### **Enhanced Performance** These chips handle diverse workloads like app servers, web hosting, and HPC with ease, offering better memory bandwidth and compute capabilities compared to their predecessors. ### **Improved Security** Keeping your data safe is a priority, and Graviton delivers. Features like always-on memory encryption and dedicated vCPU caches make these processors a secure option for critical workloads. ### **Extensive Software Support** AWS Graviton supports a wide range of Linux distributions and open-source tools, as well as many popular operating systems, ISVs, and AWS Partners. This makes it perfect for developers who thrive on flexibility and ### **General Purpose Processors** AWS Graviton servers could be used to improve and optimize server performance, mid-size data-storing processes, microservices, and cluster computing. ### **Burstable Workloads** AWS Graviton processors efficiently handle scalable tasks like microservices, virtual desktops, small and medium database services, and business-critical applications. They excel in managing sudden spikes in resource demands. ### **Compute-Intensive Support** Ideal for workloads requiring significant computational power, including HD video encoding, gaming, and CPU-based machine-learning processes. ### **Superior Networking** Support for C6gn instances offers up to 100 Gbps network bandwidth through the Elastic Fabric Adapter (EFA), ensuring low-latency and high-throughput networking for demanding applications. ### **Reduced Dependency on Third-party Manufacturers** Unlike processors from third parties like Intel or AMD, Graviton is designed by AWS specifically for the cloud. This in-house development allows for tight integration with AWS services, enhancing both efficiency and functionality. ### **Sustainable Computing** The AWS Graviton processors and their architecture are built for sustainability. They use up to 60% less energy than traditional processors, slashing carbon footprint and reducing energy bills. It also aligns with AWS’s vision for a greener future. ### **Availability with Managed AWS Services** AWS Graviton instance types also include a wide range of ## **AWS Graviton Versions Comparison** AWS Graviton architecture has evolved significantly since its debut. Each generation offers better performance, scalability, and efficiency than its predecessor, supporting diverse workloads across AWS services. Here’s a quick comparison of Graviton versions and their key features: AWS Graviton Versions Comparison After the launch of Graviton3, AWS also introduced the Graviton3E, a high-performance variant of the Graviton3 chip. With a 35% better performance for tasks reliant on vector instructions, Graviton3E instances also consume up to 60% less energy for the same work than comparable Amazon EC2 instances, which makes it a more sustainable approach to high-performance computing. Graviton4 stands out as the AWS Graviton family's latest and most advanced server processor, delivering exceptional performance, lower cost, and greater energy efficiency. Additionally, it introduces robust security features, including always-on memory encryption, dedicated vCPU caches, and pointer authentication, ensuring top-tier data protection. ## **Which AWS Services support Graviton Processors?** When AWS Graviton was first introduced, it was designed to deliver cost-effective performance for a limited set of workloads. However, with the release of successive generations like Graviton2, Graviton3, and Graviton4, Graviton processors now support a wide range of AWS services, optimizing performance, cost-efficiency, and energy usage across diverse applications. Here’s a look at some key AWS services powered by Graviton: * **Amazon EC2** - Provides scalable virtual servers for running applications in the cloud. Supports a wide range of applications from * **Amazon Aurora** - A high-performance relational database service compatible with MySQL and PostgreSQL. * **Amazon RDS** - Simplifies relational database setup, operation, and scaling in the cloud. * **Amazon MemoryDB for Redis** - A durable, in-memory Redis-compatible database designed for ultra-low latency workloads. * **Amazon ElastiCache** - Improves database performance by caching frequently accessed data. * **Amazon OpenSearch** - Provides search and analytics services for large datasets. * **Amazon EMR** - Processes large datasets using tools like Apache Spark and Hadoop. * **AWS Fargate** - A serverless compute engine for running containers without the effort of managing infrastructure. * **Amazon EKS** - Manages and orchestrates Kubernetes clusters for containerized applications. * **AWS Lambda** - Runs serverless code in response to events, ### **Amazon EC2 instance types powered by Graviton Processors** Within EC2, various instance types are powered by different generations of AWS Graviton processors, including Graviton 2, Graviton 3, Graviton 3E, and Graviton 4. Each generation offers unique performance and efficiency benefits, catering to different workload requirements. Amazon EC2 instances powered by AWS Graviton AWS Graviton processors are widely used across Amazon EC2 instances for a wide variety of cloud use cases, including application servers, microservices, open-source databases, and high-performance computing. AWS Graviton instance types cost up to 20% less than comparable x86-based EC2 instances, and they are designed to use up to 60% less energy, making them an eco-friendly and cost-effective option for many workloads. ## **What are the use cases of AWS Graviton?** AWS Graviton processors are optimized for specific types of workloads and deliver exceptional cost-performance benefits, but they aren’t a one-size-fits-all solution. Let’s explore where they excel and where alternative solutions might be more appropriate. ### **Microservices** Applications built on microservices that require balanced computing, memory, and networking resources benefit greatly. For instance, streaming platforms with scalable subscriber bases are a perfect fit. ### **Graphics Acceleration and Compute-Intensive Applications** Tasks like video encoding, gaming servers, or computational modeling thrive with AWS Graviton. These processors ensure high performance for latency-sensitive workloads while optimizing costs. ### **Memory-Intensive Workloads** Databases like MySQL, NoSQL, and Redis that require large-scale memory operations see improved performance. For example, supply chain management applications processing extensive datasets find Graviton highly efficient. ### **Accelerated Computing** Ideal for advanced fields like robotics, artificial intelligence, and machine learning inference engines, AWS Graviton architecture and hardware acceleration are perfect for processing complex logic in real-time scenarios. ### **Storage-Optimized Applications** Use cases involving high-frequency read/write operations, such as search engines and streaming services, benefit from Graviton’s ability to handle large data volumes while keeping costs low. ### **Web Servers and App Hosting** AWS Graviton provides cost-efficient and scalable solutions for web hosting and application servers, particularly those relying on Java, Node.js, and PHP. ### **Distributed Computing** Frameworks like Apache Spark and Hadoop see significant performance and cost savings when using Graviton for large-scale data processing tasks. _**(Learn how MobiKwik, India’s leading FinTech player, achieved seamless migration to AWS Graviton and saved 27% of their cloud costs with CloudKeeper -**__**.)**_ ## **Limitations with Graviton** While AWS Graviton delivers exceptional results for many cloud-native and Linux-based workloads, they lack support for some specialized x86 instruction sets and libraries. Hence, they may not be suitable for the following applications. * **Machine Learning Training** :**** Workloads relying on NVIDIA CUDA or requiring extensive GPU acceleration may not benefit from Graviton processors. * **Specialized Engineering Simulations** :**** Tasks with high-precision floating-point computations are better suited to other architectures. * **Windows-Only Applications** : Since Graviton does not support the x86-specific instruction sets, workloads tied to Windows environments may face compatibility challenges. ## **Key considerations before migrating to AWS Graviton** Having explored the benefits, use cases, and limitations of AWS Graviton processors, the next step is understanding how to transition effectively if you decide Graviton is right for your workloads. Migration to Graviton can be straightforward, but planning and preparation are key to ensuring success. * Start by * Conduct comprehensive validation tests to ensure performance, functionality, and compatibility meet your expectations. * Verify whether your existing monitoring and security tools support Arm architecture to avoid surprises post-migration. * Assess if the performance and cost benefits justify migration for each workload, particularly for legacy or highly specialized applications. * Leverage AWS automation tools, such as AWS Systems Manager, to streamline deployment and configuration processes. Transitioning to AWS Graviton can unlock significant cloud cost savings and performance advantages. With a systematic approach, you can ensure a smooth AWS Graviton migration and reap the benefits of this powerful platform. ## **Achieve seamless transition to AWS Graviton with CloudKeeper** AWS Graviton processors offer superior performance and cost efficiency. However, migrating workloads to Graviton requires expertise and meticulous planning. CloudKeeper offers comprehensive AWS Graviton Migration Services, without compromising business continuity. Here’s how CloudKeeper simplifies your migration journey: **Assessment & Workshops**: Gain clarity on Graviton’s potential with tailored workload evaluations and hands-on workshops. We help identify migration opportunities while optimizing for performance gains. **Migration Roadmap** : We create a detailed migration plan, offering end-to-end support to ensure timely execution while adhering to your budget. **Continuity Planning** : Our team develops robust disaster recovery and failover strategies, minimizing risks during and after migration. **Migration & Upgrades**: CloudKeeper manages the technical intricacies of transitioning and upgrading workloads to Graviton, minimizing downtime and disruptions. **Cost & Performance Optimization**: Post-migration, we fine-tune configurations and deliver continuous optimization to maximize the price-to-performance ratio. **Continued Support** : From monitoring and troubleshooting to moving applications to run natively on the AWS Graviton architecture, we provide end-to-end support for your entire migration strategy. With 15+ years of cloud expertise and having worked with 400+ businesses globally, CloudKeeper is a trusted partner for all your cloud migration and modernization needs. Explore our full suite of ## **Conclusion** AWS Graviton is a game-changer in the world of cloud computing, offering impressive cloud cost savings, enhanced performance, and energy efficiency. These processors offer superior price performance in use cases like general-purpose workloads, compute-intensive tasks, and memory-heavy applications, making them a versatile choice for many businesses. However, Graviton isn’t the perfect fit for every scenario. Understanding where AWS Graviton architecture excels—and where it doesn’t—is key to deciding whether it aligns with your needs. That’s why having a trusted partner, like CloudKeeper, can make all the difference. From assessing workloads to managing migrations and ensuring optimal performance, CloudKeeper’s expertise ensures a smooth and stress-free shift to AWS Graviton instance types. Working with the right partner can help you unlock its full potential while minimizing risks and maximizing rewards. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Kubernetes often feels like it’s missing something obvious: where are the groups? You’ll try to _**kubectl create group**_ and — surprise — nothing exists. That’s not a bug. It’s intentional. Kubernetes separates **authentication**(who are you) from **authorization**(what can you do). Kubernetes purposely leaves the authentication step out of the core API so it can integrate cleanly with many identity systems: X.509 client certificates, OIDC/JWTS, This blog explains what that actually means, where groups come from in real life (certificates, tokens, cloud IAM), how groups are used by RBAC, and how a managed Kubernetes service like Amazon EKS maps ## **Where do groups come from in practice?** **1. Client X.509 certificates** When you use client certificates to authenticate to the API server, Kubernetes reads the certificate subject into a username and may extract the Organization (O) fields as groups. In other words, the certificate carries the identity and group information. * CN typically becomes the Kubernetes **username**. * O (Organization) fields are turned into **group** strings. So the group is not a separately created object — it’s baked into the certificate. **2. OIDC / JWT tokens** If your cluster’s API server talks to an OIDC provider (Google, Azure AD, Keycloak, etc.), the token contains claims. A typical claim is groups (an array of strings). Kubernetes trusts the token issuer and uses the groups claim as the set of group names for the authenticated user. **3. Cloud provider authentication (EKS example)** Managed providers often authenticate users via the cloud provider’s identity system (AWS IAM, GCP IAM, Azure AD). They map those cloud identities into Kubernetes username and groups strings — usually through an authenticator that runs during the API server auth step. The important bit: the mapping produces group names (strings) that RBAC later checks. ## **What is a Group in Kubernetes? (short definition)** A group is a string label attached to a user’s identity during authentication. RBAC checks those strings when deciding whether to allow an operation. There is no apiVersion: v1, kind: Group resource that you can kubectl apply. Because groups are just strings, anything that authenticates and produces a group name will work with RBAC. That design is flexible but also means group membership is external — managed by your identity system, not by Kubernetes. ## **How RBAC uses groups — Role and RoleBinding examples** RBAC uses Role/ClusterRole to define permissions and RoleBinding/ClusterRoleBinding to bind those permissions to **Subjects**(users, groups, or serviceAccounts). Here’s a tiny example showing how groups are used: Notice subjects[0].kind: Group — that **name** is just a string. The binding will allow any _authenticated user_ who arrives with the team-a group string to use the **pod-reader** Role in the **team-a** namespace. ## **What happens on Amazon EKS (how EKS ‘abstracts’ authentication and groups)** Amazon EKS provides an authentication bridge between AWS IAM and the Kubernetes API server. This bridge maps an IAM principal (an IAM user or role) to a Kubernetes username and a set of groups. The mechanism works through an authenticator layer that inspects incoming requests, validates AWS IAM credentials, and returns the resolved username and groups to the Kubernetes API server. Traditionally, EKS uses the **aws-auth** ConfigMap in the **kube-system** namespace to define these mappings. Each **mapRoles** or **mapUsers** entry effectively says: “ _When IAM principal X authenticates, treat them as_ _user Y and attach these group strings_.” Conceptually, it looks like this: Key takeaways: * The aws-auth ConfigMap is where **IAM → Kubernetes** identity mapping is configured. * EKS (or the authenticator) produces the Kubernetes username and groups — strings that RBAC later sees. * EKS itself does not auto-create Kubernetes Roles/RoleBindings for you when you update aws-auth. It only maps identity. You still need to create RBAC objects (Role/ClusterRole + RoleBinding/ClusterRoleBinding) that grant permissions to the groups you assigned. * However, many tools (like eksctl or **aws-auth** and simultaneously create ClusterRoleBindings that bind **system:masters** or other groups to the mapped IAM role. It’s also worth noting that **AWS now recommends using EKS Access Entries** as the modern approach to managing cluster access instead of directly editing aws-auth. Access Entries formalize and simplify IAM-to-Kubernetes identity mapping — but that topic deserves its own deep dive for another time. ## **Common gotchas & best practices** * **Don’t expect to kubectl create group** — manage groups in your identity provider. * **Use clear, predictable group names** in your identity mappings (e.g., team-foo, platform-admins) so RBAC bindings are easy to reason about. * **Audit your aws-auth (or cloud equivalent)** whenever you change cloud-side access — identity mappings are what let cloud users become Kubernetes subjects. * **Prefer least privilege:** map IAM roles to narrow groups and write ClusterRole/Role with the minimal verbs/resources needed. * **Service accounts are different** : pods use service accounts for in-cluster auth; you can map IAM roles to service accounts with IRSA (in EKS) so pods get AWS permissions. ## **Example flow: add an AWS IAM role and grant it read-only cluster-wide access** 1. Add IAM role arn:aws:iam::111122223333:role/ReadOnlyK8s to aws-auth with groups: [readers]. 2. Create a ClusterRole called cluster-pod-reader that can get/list pods across namespaces. 3. Create a ClusterRoleBinding that binds cluster-pod-reader to Group: readers. After step 1, the IAM principal is authenticated and arrives at the API server carrying groups: ["readers"]. After steps 2–3, RBAC will allow anyone with the readers group to list pods cluster-wide. ## **Final notes** Kubernetes purposely avoids owning authentication and group membership. That avoids reinventing identity systems and gives you freedom to integrate with **groups are an external primitive** — strings declared by whatever authenticates users. Kubernetes RBAC then trusts those group strings, and you must author the Role/RoleBinding objects that reference them. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer Abhay Joshi is a problem solver who enjoys playing with algorithms and building scalable distributed systems. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Why We Looked Beyond Terraform: Crossplane vs Terraform at Scale In this first blog of our five-part series, we dive deeper into the reasons for moving from Terraform to Crossplane. By Neetesh Yadav 20 May, 2026 Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 9 9 Table of Contents Cloud optimization and The year 2026 marks a fundamental turning point where AI becomes essential for driving cost efficiency, performance, governance, and engineering productivity at scale, making cloud cost optimization more critical than ever. Gartner forecasts worldwide public cloud end-user spending to reach $723.4 billion in 2025 (up from $595.7 billion in 2024) as organizations accelerate modernization and AI adoption. IDC projects this trajectory crossing $1.35 trillion by 2027, a scale at which optimization is no longer optional. ## How Is AI Changing the Way Cloud Optimization Works? Artificial intelligence is reshaping cloud optimization because cloud environments now produce far more telemetry than teams can manually analyze. Workloads scale dynamically, distributed microservices shift patterns every hour, and One of the biggest shifts is predictive analytics. Instead of reacting to last month’s overspend, AI forecasts upcoming usage, anticipates cost spikes, and models the impact of architectural decisions. This is especially critical as TD Securities reports that GenAI workloads already account for 12% of cloud spend, rising to 28% by 2028. AI also brings intelligence to ## Why Is AI-Driven Cloud Optimisation Becoming So Valuable? AI-driven cloud cost optimization delivers insights and automation that BCG estimates that enterprises waste up to 30% of cloud spend due to idle or over-provisioned resources. AI identifies optimization opportunities continuously, leading to significant cost efficiencies. Datadog highlights organizations achieving 33% reductions in compute costs using ML-based optimization, proving the impact of AI-powered cloud cost optimization. Performance reliability also improves. Predictive autoscaling, As multi-cloud becomes the norm, 89% of enterprises now operate across multiple clouds, and 90% are expected to adopt hybrid cloud by 2027, the complexity of managing different pricing models, architectures, and governance frameworks increases sharply. AI adds a unifying layer of intelligence that brings consistency to governance, optimization, and operational control across these fragmented environments. Enterprises increasingly expect their ## Why Does 2026 Mark the Inflection Point for Cloud Optimization? Several forces converge in 2026, making it the strategic year for AI-driven cloud optimisation and cloud cost optimization. * AI workload demand is surging - McKinsey notes that * AI-optimized infrastructure spending is expanding rapidly - * Automation is maturing at scale - Gartner forecasts that enterprise These developments position 2026 as the year in which ## How Can Organizations Implement AI-Driven Cloud Optimisation Effectively? Successful AI adoption begins with a clear assessment of current maturity. Organizations evaluate visibility gaps, tagging consistency, rightsizing readiness, FinOps structure, and automation levels, all foundational elements of scalable cloud cost optimization. Initial implementation tends to focus on predictive autoscaling, rightsizing intelligence, anomaly detection, and commitment forecasting, areas where AI provides immediate ROI. As models mature, teams extend AI into architectural planning, workload placement, and governance automation. To support this transition, enterprises increasingly rely on a cloud optimization partner that provides the expertise, modelling capabilities, and Over time, organizations refine KPIs, incorporate predictive insights into planning, and move toward continuous optimization as the baseline operating model. ## Conclusion 2026 marks a structural shift in cloud optimization. With rising cloud consumption, rapid expansion of AI workloads, more distributed architectures, and maturing automation capabilities, enterprises are moving from manual cost checks toward intelligent, AI-driven cloud optimisation. The combination of predictive analytics, autonomous governance, and performance intelligence is redefining how cloud environments are managed. Organizations that embrace this transformation early will be better equipped to navigate the next decade of cloud growth supported by the right cloud optimization partner and a capable cloud optimization platform designed for continuous cloud cost optimisation and enterprise-wide cloud optimization. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Team CloudKeeper is a collective of certified cloud experts with a passion for empowering businesses to thrive in the cloud. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Modern microservices-based applications produce massive volumes of log data. Every API call, container restart, deployment, and authentication event generates logs that are crucial for troubleshooting, monitoring performance, ensuring security, and auditing system activity. In environments running on Many teams rely on Moreover, Amazon CloudWatch has limited search and analytics capabilities, which makes complex queries slow and costly. For organizations dealing with high-volume Amazon ECS workloads, this can become a significant operational and financial burden. ## **Why Amazon OpenSearch Can Be a Better Choice** Amazon OpenSearch is a managed service designed for fast search, analytics, and aggregations. It allows teams to control how logs are indexed, stored, and retained, making it much more cost-efficient at scale compared to Amazon CloudWatch. In AWS OpenSearch, each log is stored as a JSON document, organized into indexes, and distributed across shards for scalability. Properly managing shard sizes, replicas, and storage tiers ensures performance while keeping costs under control. Unlike AWS CloudWatch, OpenSearch allows tiered storage: * **Hot tier:** Fast indexing and querying, ideal for recent logs. * **UltraWarm tier:** Cost-efficient Amazon S3-backed storage for logs that are less frequently accessed. * **Cold tier / Amazon S3 archive:** Long-term storage for historical logs, accessible if needed but at minimal cost. By separating recent, intermediate, and archived data, organizations can prevent unnecessary cluster load and reduce overall storage expenses. ## **Designing a Cost-Efficient Amazon ECS Logging Pipeline** A practical logging architecture for ECS workloads usually looks like this: **AWS ECS Tasks → Fluent Bit / FireLens → Kinesis Firehose → AWS OpenSearch → S3 Archive** Each container produces application logs that Fluent Bit collects and enriches with metadata such as service name, environment, and container ID. Kinesis Firehose acts as a buffer, batching log data to reduce ingestion spikes and prevent overloading OpenSearch. Recent logs are indexed in the hot tier for fast searches, while older logs move to UltraWarm or cold tiers, and logs beyond a defined retention period are archived in Amazon S3. This separation ensures the cluster remains stable, queries remain fast, and storage costs remain predictable. ## **Common Cost Pitfalls in Log Analytics** Amazon OpenSearch costs increase primarily due to architectural choices rather than raw log volume. Common mistakes include: * Retaining excessive logs in the hot tier. * Over-provisioning nodes that remain mostly idle. * Creating too many small shards, which increases JVM heap pressure. * Failing to implement index lifecycle policies. * Using dynamic mappings that generate thousands of fields unnecessarily. By addressing these issues, teams can reduce Amazon OpenSearch costs by 30–60% while improving stability and query performance. ## **Shard Management and Cluster Stability** Shards are the fundamental units of storage in OpenSearch, and mismanagement can lead to resource pressure. Best practices include: * Targeting 20–40 GB per shard for balanced performance. * Avoiding unnecessary daily indexes for small workloads. * Removing replicas for less critical indexes. * Monitoring shard-to-heap ratio before scaling nodes. Many clusters hit JVM heap limits not because of log volume, but due to excessive shards and poorly sized indexes. Proper shard management ensures that the cluster remains responsive even during spikes in log ingestion. ## **AWS CloudWatch vs AWS OpenSearch: A Practical Comparison** While CloudWatch is excellent for small-scale monitoring, OpenSearch offers superior control and cost efficiency for large-scale Amazon ECS workloads. **Amazon CloudWatch Pros:** * Native AWS integration * Simple setup and out-of-the-box dashboards * Easy to use for small workloads and operational alerts **Amazon CloudWatch Cons:** * Costs scale quickly with log volume and retention * Limited search, aggregation, and analytics capabilities * Harder to implement long-term, tiered storage strategies **Amazon OpenSearch Pros:** * Flexible, tiered storage (Hot, UltraWarm, Cold/ AWS S3) * Fine-grained shard and index management * Optimized for complex queries and analytics * Lifecycle policies allow predictable cost management **Amazon OpenSearch Cons:** * Slightly more setup and management effort compared to AWS CloudWatch * Requires careful cluster and shard planning ## **Practical Example of** Imagine a workload generating approximately 500 GB of logs per month. Storing 90 days of logs entirely in Amazon CloudWatch would result in high storage costs and limited querying capability. By contrast, an optimized OpenSearch setup could retain 7 days in the hot tier, 23 days in UltraWarm, and archive logs older than 30 days in Amazon S3. Combined with shard optimization and selective replication, this approach drastically reduces operational costs while retaining analytics capabilities. ## **When to Choose Amazon CloudWatch** Amazon CloudWatch is ideal for smaller workloads, straightforward monitoring, or when organizations require integrated alerts and metrics with minimal setup. However, for Amazon ECS deployments producing large volumes of logs that need advanced search and analytics, OpenSearch is more cost-effective and scalable. ## Conclusion Amazon OpenSearch provides a robust, cost-efficient solution for log analytics in Amazon ECS workloads. By implementing controlled ingestion, tiered storage, lifecycle management, and proper shard sizing, teams can maintain high performance while keeping costs predictable. AWS CloudWatch remains useful for basic monitoring, but for high-volume log analytics, a thoughtful AWS OpenSearch architecture is essential. The most expensive clusters are rarely the busiest—they are typically the ones with poor design, mismanaged storage, and oversized shards. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * DevOps Engineer FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Transitioning to the cloud represents a significant shift for companies looking to improve scalability, lower operational costs, and foster innovation. Nevertheless, the process of migrating to the cloud can be intricate, expensive, and fraught with risks if not approached with a solid strategy. The This blog delves into AWS MAP comprehensively, highlighting its advantages, essential elements, and how it expedites your cloud migration process while guaranteeing sustained success. ## **What is the AWS Migration Acceleration Program(AWS MAP)?** The AWS Migration Acceleration Program (MAP) is an organized initiative for cloud migration that aims to assist companies in transferring their workloads to AWS while minimizing risk, expenses, and downtime. Through AWS MAP, businesses can access expert guidance, industry best practices, and funding to enhance their migration efforts. AWS MAP employs a systematic, three-phase methodology that guarantees organizations can effectively evaluate their readiness for the cloud, mobilize their resources, and carry out a smooth cloud migration process. Whether your goal is to rehost, refactor, re-platform, or modernize your applications, AWS MAP offers a complete framework to facilitate your move to AWS. ## **Key Components of AWS Migration Acceleration Program (AWS MAP)** AWS MAP consists of three essential phases: Assessment, Migration, and Modernization. Each phase aims to facilitate a seamless and effective transition to the cloud for organizations. ### **1. Assessment** The initial phase of AWS MAP assists organizations in analyzing their current infrastructure, evaluating their readiness for the cloud, and crafting a strong business justification for cloud migration. Key tasks in this stage include: * Recognizing existing IT environments, dependencies, and workloads. * Performing a Total Cost of Ownership (TCO) analysis to understand financial advantages. * Evaluating technical preparedness and pinpointing skill shortages. * Developing a ### **2. Mobilization** The Mobilization phase is centered on getting your organization ready for the cloud migration by addressing identified deficiencies and establishing necessary tools and resources. This phase entails: * Establishing AWS Landing Zones and governance structures. * Educating and enhancing team skills through AWS certification programs. * Creating proof-of-concept initiatives for validation purposes. * Collaborating with AWS Partner Network (APN) consultants for planning support. ### **3. Migration & Modernization** The concluding phase involves the execution of the migration and the * Carrying out the cloud migration with AWS-native services such as AWS Migration Hub, AWS Application Migration Service, and AWS Database Migration Service. * Enhancing workloads with AWS cost management solutions. * Modernizing applications using cloud-native offerings like AWS Lambda, Amazon RDS, and Kubernetes. By adhering to this systematic approach, AWS MAP greatly diminishes the challenges and risks tied to cloud migration. ## **The Role of AWS MAP in the Cloud Migration Lifecycle** AWS MAP is essential at every phase of the cloud migration process. Organizations moving to the cloud frequently * A strategic cloud migration approach that reduces downtime and disruptions. * Access to AWS-certified migration specialists and partner consultants. * Proven strategies to enhance performance and cost-effectiveness. * Automated tools that facilitate workload migration and management. By utilizing AWS MAP, companies can greatly speed up their cloud migration while maintaining optimal performance and security. ## **Cloud Cost Savings and Funding Benefits** One of the primary worries for businesses when transitioning to the cloud is the expense involved. AWS MAP offers various funding options to help lower cloud migration costs and facilitate cloud adoption. ### **Available Funding Options in AWS MAP** AWS MAP provides financial assistance through AWS service credits, partner funding, and migration investment programs. These funding mechanisms help organizations mitigate the expenses related to: * Planning and assessing migrations. * Training and developing IT staff skills. * Consulting and implementation services from partners. * Costs associated with using AWS services. Additionally, AWS supplies the Optimization and Licensing Assessment (OLA) to assist businesses in pinpointing cost-saving opportunities through improved license management. ### **Speeding Up Migration Timelines and Reducing Costs** AWS MAP aids organizations in expediting their cloud migration by offering automated tools and expert assistance, thus lessening the time and effort needed for a successful transition. Significant cloud cost-saving advantages include: * **Reduced Operational Interruptions:** By utilizing AWS-native tools such as AWS Migration Hub, businesses can oversee and manage their cloud migration smoothly. * **Preventing Unexpected Expenses:** With AWS MAP, businesses receive a transparent outline of migration costs, ensuring that no unforeseen charges occur. * **AWS Credits and Budget-Friendly Solutions:** AWS MAP supplies businesses with AWS service credits to explore cloud services prior to full implementation. By taking advantage of AWS MAP’s funding benefits, organizations can develop a cost-efficient cloud migration strategy that maximizes their return on investment. ## **Expert Guidance and Cloud Support** Migrating to AWS encompasses more than simply transferring workloads; it necessitates a comprehensive understanding and best practices to ### **AWS-Certified Experts and Cloud Migration Partners** AWS MAP links businesses with AWS-certified migration specialists and leading partners from the AWS Partner Network (APN). These professionals assist in: * Developing tailored cloud migration plans. * Delivering hands-on help for workload transitions. * Ensuring adherence to industry regulations and security best practices. ### **Access to AWS Resources, Tools, and Best Practices** Organizations that utilize AWS MAP benefit from an abundance of resources, including: * The * The AWS Migration Hub for comprehensive migration tracking and supervision. * AWS Training and Certification programs to enhance team skills in cloud best practices. ### **Dedicated Support for Workload Planning and Optimization** AWS MAP offers continuous support even post-migration, ensuring that businesses can refine their workloads for performance, security, and cost-effectiveness. ## **Why Choose CloudKeeper as Your AWS Migration Acceleration Program (AWS MAP) Partner?** When choosing an AWS MAP partner, companies require a reliable advisor who can facilitate a seamless and effective cloud migration. CloudKeeper, an * **Comprehensive Support:** End-to-end guidance throughout the entire AWS MAP journey, from assessment to post-migration optimization. * **Guidance by Cloud Experts:** A team of AWS-certified professionals providing deep expertise and strategic insights. * **Access to Funding Programs:** Helping businesses leverage AWS MAP funding options, AWS credits, and partner investments to reduce migration costs. * **Automated Process:** Leveraging automation tools and best practices to accelerate migration timelines and optimize cloud environments efficiently. By partnering with CloudKeeper for your AWS MAP, you can take full advantage of the AWS MAP benefits while ensuring a cost-efficient, low-risk, and streamlined cloud migration. ## **Conclusion** AWS MAP is an effective initiative that streamlines the process of moving to the cloud while minimizing costs and risks. Through its organized phases, expert advice, and financial assistance, AWS MAP equips businesses with the necessary tools and resources for a seamless cloud transition. Partnering with CloudKeeper allows organizations to further enhance their cloud migration experience, ensuring sustained success within the AWS cloud. If you're contemplating a move to the cloud, AWS MAP is your optimal choice for a smooth, economical, and efficient transition to AWS. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents Cloud has established itself as the standard in business IT. Organizations are not just viewing the cloud as a platform but as an enabler to achieve new business objectives. Cloud has the ability to upscale or downscale resources in real-time as per the requirement of the dynamic business needs. This enables businesses to move quicker, innovate more, and sharpen their competitive edge. As businesses embrace the cloud's numerous advantages, keeping track of cloud spend is a constant struggle. The cloud infrastructure, unlike on-premise technology stacks, is a dynamic environment. The downside of this nature is that things get complicated very quickly. Most public cloud providers use a payment model based on resource usage. This results in a bill with hundreds of line items which is difficult to understand & optimize due to the varying levels of resource usage at different times. However, Some of the cost contributors in the cloud include: Cloud charges become opaque due to the Other challenges that add to the increase in cloud spends: These challenges necessitate the implementation of a company-wide cloud cost management plan. ## **What is Cloud Financial Management and how does it help?** Cloud Financial Management enables businesses to make the most of the cloud infrastructure and keep control on spends while also ensuring that the benefits of the cloud such as scalability, security, and flexibility are available across the organization. It is feasible and crucial to instill a cost-conscious culture across the organization when it comes to cloud infrastructure planning and management. The need of the hour is an organizational planning discipline, a FinOps practice, that enables a business to understand and manage its cloud technology-related costs and needs effectively. This involves finding Optimizing your cloud costs requires a smart cloud strategy right from the resource planning phase. With our Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 6 6 Table of Contents In the business world, the cloud is a necessity for embracing innovation, offering unparalleled opportunities for growth and transformation. For many companies, the decision to embrace the cloud is not just a leap forward – it's a strategic imperative. Yet despite the positive promises of cloud there lies a series of challenges that need to be tackled. Let’s take the example of a fictional company, ABC Solutions, that migrated to the cloud and encountered a familiar obstacle: the need for effective cloud cost management. To efficiently manage the cloud cost they had multiple areas to look after like billing management, ABC Solutions was determined to optimize its cloud cost however, it lacked the resources, tools, and skills to handle the different aspects of cloud cost optimization. Feeling overwhelmed, they considered outsourcing to a third-party vendor. However, they were unsure whether to go for multiple vendors for each aspect of cloud cost optimization. Each vendor will bring its own set of tools, processes, and interfaces, and they were worried if leading to a fragmented approach that might compound the challenges they faced. They realized that a better option might be to find one Cloud FinOps vendor who could handle all their needs, providing a more organized and integrated approach. This example was fictional however the research supports a growing trend of organizations prioritizing end-to-end **-** * _Organizations prefer tools offered by Cloud FinOps solution providers. This preference stems from the underdeveloped Cloud FinOps capabilities in alternative solutions._ * _Scarcity of internal FinOps talent leading to reduced efficacy of homegrown solutions._ * _62% prefer RI management providers as they seek assistance in optimizing Reserved Instances (RIs) across multi-cloud environments, while 56% choose consulting and MSP providers as they are looking for more ongoing support in their FinOps journey._ * _As the market progresses, cloud FinOps providers with end-to-end capabilities across various areas are expected to gain prominence. The future is all-encompassing._ ## **The Limitations of a Point Solutions** Today, your company might have certain challenges and you found a solution that seemed perfect for solving your immediate problems. Because of this, you might tend to overlook its limitations. But as your business grows it automatically leads to new needs and challenges. You end up spending more money on additional solutions to fill the gaps or wasting time transferring data between systems. Looking back, you wish you had invested in a comprehensive platform from the start, rather than a standalone solution. This is a typical scenario that happens in the case of a point solution. **Limited Scope:** Point solution focuses on one specific objective like cost visibility or Reserved Instance Management. This is the strength of point solutions but also its greatest weakness. Point solutions typically address a single problem or process, which means they may not fulfill all the requirements of a complex organization. Users may need to invest in multiple-point solutions to cover all their needs. **Lack of Integration:** Point solutions often work as standalone tools, making integration with existing systems or workflows challenging. This can result in data silos and inefficiencies. When your systems don't work together, you can't see the whole picture of your business. This makes it tough to spot problems and decide what to do next. **Higher Total Cost of Ownership (TCO):** While point solutions may have lower upfront costs compared to comprehensive platforms, the cumulative expenses associated with implementing and maintaining multiple solutions can be higher in the long run. **Scalability Issues:** If you're aiming for fast expansion, relying on separate solutions to manage cloud financial operations is like trying to hold your team together with duct tape. ## **A Closer Look at the Cloud FinOps Partner Ecosystem by ISG & Everest Group** **stated -**_**“A completely cost-optimized cloud deployment, supported by a reliable and experienced partner is the need of the hour.”**_ The Cloud FinOps vendor ecosystem is continuously growing, each one contributing and playing a significant role in Cloud FinOps initiatives and growth. ISG classified the vendors into two categories - Cloud FinOps Vendors by Platform and Cloud FinOps Vendors by Services. ### **1. Cloud FinOps Vendors by Platform** Vendors in this category represent platforms and SaaS solutions for the implementation of cloud FinOps for enterprises, DNBs, & SMEs. Source: ### **2. Cloud FinOps Vendors by Services** Cloud FinOps Vendors in this category represent the solution providers with more focus on the service layer, along with platform and SaaS capabilities. These cloud FinOps consulting partners have expertise in functional areas of activity to support their solutions. Source: **Now let’s understand the cloud FinOps vendor classification through the lens of the survey conducted by Everest Group.** ## **Why end-to-end Cloud FinOps Vendors are trending?** The Everest Group survey found that - The current automation-led FinOps tools are falling short of expectations, prompting a demand for a more holistic approach from Cloud FinOps providers. As you can understand the growing trend toward end-to-end cloud FinOps Service Providers is driven by the need for a holistic approach to cloud cost optimization. By offering comprehensive services, these providers empower businesses to maximize their ROI, streamline operations, and achieve greater success in the cloud. Furthermore, end-to-end Cloud FinOps Service Providers address this demand by offering a complete suite of services that cover every aspect of FinOps, from consultation to implementation. These providers are recognized as one-stop solution providers who offer a comprehensive suite of services that cover Investing in an end-to-end Cloud FinOps partner can offer businesses a range of benefits that include: **Unified Cloud FinOps Strategy:** By providing a single, streamlined platform for all cloud FinOps activities, these providers simplify operations, eliminate the complexity of dealing with multiple vendors, and enhance efficiency. **Comprehensive Insights:** End-to-end Cloud FinOps Service Providers conduct a thorough analysis of cloud expenditure and usage, which helps to uncover in-depth cloud cost optimization opportunities across the entire cloud landscape. **Effortless Integration:** Their Cloud FinOp solutions seamlessly integrate with existing cloud setups, ensuring that enhancements are implemented without disrupting operations. **Strategic Guidance:** End-to-end Cloud FinOps Service Providers offer expert guidance tailored to the unique needs and goals of each organization. They help businesses navigate complex cloud environments and develop customized strategies to **Enhanced Governance and Compliance:** End-to-end FinOps Service Providers implement robust governance frameworks and ensure adherence to industry regulations, ensuring greater **Maximizing ROI:** The ROI of investing in end-to-end cloud FinOps solutions is significant. By leveraging their expertise and comprehensive approach, businesses can unlock hidden savings, optimize resource utilization, and ultimately drive greater returns on their cloud investments. In essence, investing in end-to-end FinOps Service Providers can streamline cost optimization efforts and yield significant returns by maximizing efficiency and ## Why is CloudKeeper an ideal choice for an end-to-end Cloud FinOps partner? Now that you are aware of why it is important to choose a partner that offers comprehensive Cloud FinOps services, let's understand how CloudKeeper fits the bill. With over 15 years of extensive experience and as a certified partner of AWS, Azure & GCP, CloudKeeper has a deep understanding of the cloud ecosystem. We optimize every aspect of your cloud journey by combining rate and usage optimization, providing complete cloud visibility, and offering unlimited cloud support, ensuring unparalleled efficiency and cost savings. If you are interested and would like to explore more on how we can optimize your cloud for long-term efficiency & maximum ROI. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Founder and CEO Deepak is a visionary leader who spearheads the development and execution of long-term business strategies, driving the company's vision to provide world-class cloud engineering services to busines FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents It's Saturday, midnight. While most of the team is off enjoying the weekend, your AWS bill is still hard at work—racking up costs on non-production environments that no one will touch until Monday. QA servers are idling. Dev environments are up and running. Internal tools are consuming compute power, despite zero traffic. Sound familiar? This scenario underscores the everyday That’s where the need for automation becomes crystal clear. ## **Enter CloudKeeper Tuner's Scheduler: Automate, Optimize, and Relax** The key issues typically fall into the following categories: cloud waste, lack of ongoing optimization, cost vs performance trade-offs and overlooked savings. Manual scheduling is error-prone, time-consuming, and often forgotten in the fast-paced cycle of development. But what if you had a smart assistant that could automatically detect idle patterns and shut down your resources—without you lifting a finger? **CloudKeeper Tuner' Scheduler** is that assistant. Integrated directly into your AWS Console via the * Automatically turn off non-prod resources (like EC2 instances, RDS, Auto Scaling Groups, etc.) during nights, weekends, or other inactive hours. * Set custom schedules across dev, QA, staging, and sandbox environments—tailored to your team’s workflow. * Reduce cloud waste and environmental impact by lowering compute usage when it’s not needed. By eliminating the need for manual intervention, the CloudKeeper Tuner's Scheduler helps engineering teams focus on innovation while effortlessly reducing AWS costs. **Scheduler: Intelligent Resource Management** ## **Why CloudKeeper Tuner's Scheduler Stands Out** * **Hassle-Free Setup:** Works seamlessly within your existing AWS infrastructure—no need for architectural changes, and it honors all your predefined constraints. * **Risk-Free Automation:** Shuts down resources safely, ensuring smooth restarts without compromising data integrity or performance. * **Transparent Insights:** Every scheduled action is logged, with clear visibility into the estimated cost savings—so you always know the impact. ## **CloudKeeper Tuner's Scheduler Redefining AWS Resource Management** Cloud resource scheduling is essential for optimizing costs and maintaining operational efficiency. While AWS Scheduler (EventBridge Scheduler) provides robust event and task automation, CloudKeeper Tuner's Scheduler introduces a new paradigm-blending intelligent automation with real-time, actionable cost optimization. Choosing the right scheduler for your AWS workloads can have a significant impact on automation, cost optimization, and operational simplicity. Here are a few technical points highlighting why CloudKeeper Tuner' Scheduler is redefining AWS resource management. ### **1. Purpose and Core Functionality** * **AWS Scheduler:** Automates the execution of AWS resource actions (start, stop, invoke, etc.) based on time or event triggers. Its primary focus is on orchestration and workflow automation across AWS services. * **CloudKeeper Tuner' Scheduler:** Goes beyond simple automation by integrating real-time cost and usage optimization. It analyzes your environment, delivers tailored recommendations, and automates actions specifically to eliminate waste, right-size resources, and modernize workloads. ### **2. Breadth of Optimization** * **AWS Scheduler:** Limited to scheduling actions; does not analyze resource utilization or provide insights into cost-saving opportunities. * **CloudKeeper Tuner's Scheduler:** * Offers 150+ tailored recommendations across 50+ AWS services, covering nearly 90% of a typical AWS bill-an industry first. * Detects and cleans up zombie/unused resources, right-sizes over-provisioned compute and storage, and recommends modernization upgrades for peak efficiency. ### **3. Intelligent, Usage-Based Scheduling** * **AWS Scheduler:** Schedules tasks based on fixed time or event triggers, regardless of actual resource usage or idle patterns. * **CloudKeeper Tuner' Scheduler:** Automatically shuts down idle resources during off-hours. ## **Advantages of Using CloudKeeper Tuner' Scheduler** CloudKeeper Tuner's Scheduler offers a range of advantages that make it a superior choice for organizations focused on AWS cost optimization, operational efficiency, and seamless engineering workflows. Here’s how CloudKeeper Tuner' Scheduler stands out: ### **1. Real-Time, Automated Cost and Cloud Usage Optimization** CloudKeeper Tuner is not just a scheduler-it acts as a real-time assistant, continuously analyzing your AWS environment and delivering actionable recommendations to optimize resources without compromising performance. This proactive approach helps teams ### **2. Effortless Resource Management** Unlike AWS Scheduler, which requires manual input of resource identifiers (like instance IDs or ARNs), CloudKeeper Tuner automatically discovers and fetches resources for start/stop operations, greatly simplifying setup and reducing the risk of configuration errors. ### **3. Intelligent Automation for Idle Resource Shutdown** CloudKeeper Tuner can automatically shut down idle resources during off-hours, helping organizations avoid unnecessary expenses and reduce environmental impact. This goes beyond simple time-based scheduling by leveraging real-time usage data. ### **4. Seamless Integration and Collaboration** CloudKeeper Tuner integrates directly into the AWS Console with a browser extension, providing instant, actionable recommendations where engineers already work. It also connects with Slack and Microsoft Teams, enabling teams to receive and act on recommendations within their existing collaboration tools. ### **5. Transparent, Data-Driven Decision Making** Every recommendation from CloudKeeper Tuner includes an estimated dollar-value savings, giving teams full transparency and helping them prioritize actions for maximum financial impact. ### **6. Backed by AWS-Certified Experts** CloudKeeper Tuner is supported by a team of over 100 AWS-certified engineers, ensuring fast, smooth implementation and expert guidance throughout the optimization process. ### **7. All-in-One Platform for Engineering Teams** CloudKeeper Tuner consolidates optimization, scheduling, and actionable insights into a single interface, making it the **A quick comparison between CloudKeeper Tuner vs AWS Scheduler** ## **Conclusion** CloudKeeper Tuner's Scheduler delivers a smart, automated, and cost-effective approach to AWS resource management, empowering organizations to maximize savings, streamline operations, and make data-driven decisions with ease. Discover how CloudKeeper Tuner' Scheduler can revolutionize your AWS cloud cost optimization journey—just like it has for many other organizations that have unlocked significant cost savings and improved operational efficiency. Curious to see the impact for yourself? Watch Tuner in action to see Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 Why Smart Teams Are Switching to CloudKeeper's Platform Suite for 360° Cloud Management We explore the key features and differentiators of CloudKeeper’s Platform Suite, which are driving intelligent cloud teams to adopt it and augment their end-to-end cloud optimization efforts. By Team CloudKeeper 13 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents _This article is part of a five-blog series where we share a customer use case — how we reimagined their cloud infrastructure strategy with Crossplane, GitOps, and a hybrid Terraform approach._ ## **Setting the Stage** **Terraform got us here. But when our client’s platform grew to 50+ microservices across multiple regions, it started to crack.** State files clashed, ephemeral environments dragged, and drift became a silent enemy. That’s when we looked beyond — and found the missing piece in Crossplane. * **Global reach** across regions * **Microservices sprawl** with dozens of infra stacks * **Ephemeral test environments** spun up at will This speed is powerful — but the wrong tools collapse under scale. That’s exactly what happened in our client’s case. ## **The Customer’s Challenge** A leading **digital commerce platform** , operating across **35+ cities** , was preparing to scale globally. Their platform connected customers and merchants across fine dining, spas, and travel experiences — while also offering merchants a powerful branding channel to reach nearby customers. The platform ran on a **microservices-heavy architecture** with more than **50 services** , each requiring: * An * * **Databases** → PostgreSQL for transactions, MongoDB and Elasticsearch for scale, HBase for personalization. * **Apache Kafka** for event-driven pipelines. The next phase of growth demanded: 1. **Multi-region deployments** to serve global audiences. 2. **Ephemeral environments** so developers could spin up short-lived infra per feature or pull request. 3. **Automation and standardization** to reduce operational overhead and complexity. At first, **Terraform** was the tool of choice. But as the system grew, so did the pain points. **Takeaway** : Terraform handled the first phase well, but scaling exposed cracks. ## **Where Terraform Fell Short** Terraform has proven itself as a **robust tool for building both small and large-scale, complex infrastructure.** However, as our client’s environment grew and became more dynamic, we encountered practical challenges: **State file complexity →** With multiple teams and regions, managing and securing Terraform state files became fragile and error-prone. Ownership disputes and state locking often slowed collaboration. **Slow ephemeral environments →** Developers faced delays when spinning up and tearing down short-lived environments because of state locking/unlocking, which wasn’t designed for high-frequency, Git-driven workflows. **Fire-and-forget model →** Terraform provisions infrastructure and exits. If an AWS resource drifts or is modified outside Terraform, it won’t self-correct until the next apply. In short, Terraform remained excellent for **foundational and static infrastructure** , but it struggled in scenarios demanding continuous reconciliation, rapid ephemeral environments, and high developer velocity — exactly where Crossplane excels. _Terraform automates creation, but Crossplane automates continuity. That shift — from provisioning to reconciliation — made all the difference._ In short, Terraform remained excellent for **foundational and static infrastructure** , but it struggled in scenarios demanding **continuous reconciliation, rapid ephemeral environments, and high developer velocity** — exactly where Crossplane excels. ## **Why Crossplane and Not Others** Before finalizing Crossplane, we evaluated multiple Each had strengths, but none solved the “**always in sync** ” problem: * **Pulumi / AWS CDK →** Great for developers, but tightly coupled with specific programming languages, not Kubernetes-native YAML. * **Terraform Cloud →** Simplified state management but still lacked real-time reconciliation. * **Crossplane →** Runs inside Kubernetes, treating cloud infrastructure as part of the same control loop that keeps pods healthy. ## **Ecosystem Evolution: How Infra as Code Evolved** **Terraform (State File) → Pulumi (Code SDK) → CDK (Language SDK) → Crossplane (Kubernetes-native Reconciliation)** **Takeaway:**_Terraform automates creation, but Crossplane automates continuity. That shift — from provisioning to reconciliation — made all the difference._ ## **Comparative Study: Crossplane vs Terraform at Scale** When we compared Crossplane and Terraform, one distinction stood out: **execution model**. * **Terraform is like a hammer** → strong for building once, but it stops there. * **Crossplane is like a pilot** → always watching, continuously adjusting, keeping the system on course. That continuous reconciliation loop is the **critical advantage** that makes Crossplane ideal for **global, dynamic infrastructures**. ## **Why This Matters** * **No state files →** Kubernetes itself becomes the source of truth. * **Drift prevention →** infra never drifts away from the desired config. * **Auditability & rollbacks →** with GitOps tools like ArgoCD, every change flows through Git. * **Developer velocity →** ephemeral infra can be spun up safely, without affecting shared state. **Takeaway:**_Terraform is a provisioning tool. Crossplane is a management plane. At a global scale, that difference is game-changing._ ## **Continuous Reconciliation: The Missing Piece** The “**aha moment** ” was realizing Terraform lacked **continuous reconciliation**. Kubernetes ensures pods match their declared state. Crossplane extends the same principle to cloud infra: * **Drift prevention →** infra always synced * **Multi-region parity →** manifests apply consistently * **Ephemeral safety →** PR infra managed via Git This was the missing piece in our puzzle. **Takeaway:**_Crossplane brings Kubernetes-style reconciliation to infra — always on, always in sync._ ## **Why We Chose Crossplane Managed Resources Directly** We didn’t start with abstractions (XRDs). Instead, we went straight to **Crossplane Managed Resources (MRs)** : * Faster onboarding for VPCs, EKS, and RDS * Fine-grained transparency * Governance enforced via Kyverno, RBAC, and secure ProviderConfigs. **Takeaway:** Starting with MRs gave us speed without losing control — fast adoption with governance built in. ## **Our Long-Term Hybrid Vision** We didn’t throw Terraform away. Instead, we embraced a **hybrid model** : * **90% Crossplane →** reconciliation, GitOps, ephemeral infra * **10% Terraform →** complex or unsupported resources **Takeaway:** Crossplane powers the **lifecycle** ; Terraform handles the **edge cases**. ## **Conclusion** Looking beyond Terraform wasn’t rejection. It was **recognition of its limits at scale**. For a platform with global reach, 50+ microservices, and ephemeral infra needs, Crossplane’s reconciliation model was the missing piece. With this decision, we laid the foundation for a **GitOps-native infra strategy** that: * Scales globally * Prevents drift * Boosts developer velocity **Next:** _Blog 2 – Designing a Hybrid Crossplane Architecture, where we share the blueprint behind our production-ready hybrid model._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Devops Engineer Neetesh specializes in designing, automating, and managing scalable DevOps pipelines across cloud-native infrastructures. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Kubernetes Cost Optimization: The Complete Guide for High-Growth Companies A comprehensive Kubernetes optimization guide focused on reducing costs without sacrificing performance By Team CloudKeeper 14 Apr, 2026 Graceful Amazon EC2 Shutdowns in Kubernetes with AWS Node Termination Handler This blog covers using Amazon Node Termination Handler to manage Amazon EC2 interruptions, prevent abrupt shutdowns, and apply best practices. By Aamir Shahab 19 Mar, 2026 The Silent Bottleneck: Avoiding Subnet IP Exhaustion in Amazon EKS A practical guide to avoiding subnet IP exhaustion while scaling an Amazon EKS cluster, covering causes, impact, and prevention strategies. By Manish Negi 27 Feb, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents Every digital native business knows the cycle for shipping products: innovate, scale, release, and watch your customer base grow. Then, the cloud bill arrives. It’s a maze of unexpected charges for forgotten instances, underutilized resources, and services that seemed essential during a sprint but now bleed capital. Teams try to trim the spend, but performance suffers, innovation stalls, and the best engineers spend days trying to figure out what caused the incident. Even when teams fully commit to cloud cost optimization, **fragmented tools make the task harder**. One platform shows costs, but can’t fix them. Another tool might focus heavily on cost recommendations - but lacks execution capability. As a result, teams are forced to jump between multiple dashboards, manage different access controls, reconcile conflicting data, and manually piece together insights. Finance teams work in spreadsheets. Engineers dig through usage logs. FinOps teams spend hours translating reports into action. **Each tool solves only a small part of the problem. None delivers the full picture.** This fragmented approach creates blind spots, slows decision-making, and increases the risk of costly mistakes. Optimization becomes reactive instead of strategic. Opportunities for savings are missed. Accountability gets blurred. And instead of simplifying cloud management, these tools add another layer of operational complexity. What should be a streamlined, data-driven process turns into ongoing firefighting - wasting time, draining resources, and holding teams back from real innovation. This is precisely why **a growing wave of forward-thinking & high-growth organizations are integrating CloudKeeper’s ** ## **Three Key Causes of Cloud Inefficiency** ### **1. Lack of Real-Time Visibility into Cloud Infrastructure** Effective Manual cost allocation takes days of engineering time, and by the time you identify the problem, another billing cycle has passed. As a result, cost runaways become frequent, and while you’re fixing previous issues, new inefficiencies keep appearing. ### **2. Failure to Balance Performance and Cost Optimization** Manual optimization requires deep infrastructure knowledge, extensive testing, and constant monitoring. Most teams lack bandwidth, so they choose the safe option of overprovisioning because it's better to waste money than risk downtime. ### **3 Not Sustaining Cost Optimization Efforts Over Time** You run a cloud cost optimization sprint, find savings, implement changes, and call the cloud cost optimization complete. After some time, though, costs creep back up as new services launch without cost controls, and engineers spin up instances they forget about. Nobody maintains cloud optimization discipline because everyone's busy shipping features. One-time cost cuts don't solve ongoing cloud sprawl. You need continuous governance that requires ## **How CloudKeeper Platform Suite Solves All Three Challenges** CloudKeeper Platform Suite is an all-in-one FinOps solution that combines best-in-class automated & AI-led FinOps platforms to provide visibility while optimizing your cloud costs and architecture, along with unlimited 24x7 support & expert services. The architecture follows a proven three-phase approach: Assess, Act, and Sustain. ### **Phase 1: Assess (Lens + Check)** The platform provides hourly cost trends across all services, budget tracking with human-assisted anomaly detection, and deep cost allocation per department, product, and environment. You get OPEX vs CAPEX breakdowns, customizable dashboards, contract tracking, and resource-level details with secure access controls. **CloudKeeper Check** runs customized reviews against the Together, Lens and Check give you complete situational awareness so you're never guessing where money goes or why. ### **Phase 2: Act (Tuner + Commit)** While visibility is the first step toward an optimized cloud infrastructure, acting on those insights is what truly reduces costs, and this is where CloudKeeper Tuner and CloudKeeper Commit come in. * **Cleaner service:** Identifies wastage like unattached volumes, orphaned snapshots, and forgotten resources while showing exact savings for each recommendation. * **Rightsizing engine:** Detects overprovisioned instances and provides targeted recommendations with specific target instances and projected savings. * **Scheduler service:** Automatically shuts down non-production environments during off-hours. With Scheduler, you can set custom uptime and downtime rules so instances run only when needed and turn off outside working hours. * **Architecture modernization:** Recommendations for moving to the latest cloud technologies, improving performance while reducing costs * **Spotbot:** ### Phase 3: Sustain (GenAI + Expert) This is where CloudKeeper separates from every other FinOps tool, because sustaining savings requires ongoing discipline and expertise that automated systems alone can't provide. Questions like "W**hy did our AWS spend spike last week?** " or "S**how me optimization opportunities over $5K monthly" get answered with context-rich insights immediately**. Non-technical stakeholders can self-serve cost information, which democratizes FinOps knowledge across the organization. **CloudKeeper Expert** provides 24/7 unlimited access to 150+ certified cloud professionals who can help whenever you need guidance. Whether you need assistance migrating workloads, optimizing The CloudKeeper Platform Suite delivers end-to-end cloud infrastructure support, including architectural guidance, migration assistance, troubleshooting, and an ongoing optimization strategy. Our **is that we augment our tools with 150+ certified cloud experts** , whose access comes as part of the Platform Suite. CloudKeeper delivers **intelligent automation guided by human expertise** , and this combination drives long-term cloud savings & maximized cloud ROI. ## **CloudKeeper Platform Suite Delivers 20% Average Savings Without Compromising Performance** CloudKeeper's Platform Suite operates on a performance-based model, where you only pay a percentage of the actual savings delivered, meaning the platform literally pays for itself. Here's what customers consistently achieve: * 20% average cost reduction without cutting capacity or compromising performance * $120M+ in total savings delivered across 400+ customers * * Continuous optimization that compounds savings month over month Engineering teams stop chasing idle resources and focus on shipping revenue-driving features. CFOs get predictable, optimized cloud spending without slowing innovation. ## **Why CloudKeeper's Approach Actually Works** Every product in the CloudKeeper Platform Suite traces back to an **actual customer requirement discovered through daily engagement with 400+ companies** solving real cloud management challenges. This customer-centric innovation cycle delivers features that solve actual problems teams face every day. The holistic approach matters too - customers initially come for cost reduction, but they stay because CloudKeeper delivers complete cloud management, including visibility, governance, optimization, architecture improvement, and ongoing support all in one integrated platform. ## **The Bottom Line: An Integrated Solution for Complete Cloud Management** Cloud management involves multiple disciplines working together: FinOps for cost control, Most companies juggle separate tools for each function, which turns integration into a nightmare where teams work in silos, and optimization opportunities get missed in the gaps. **Smart teams already made the switch, and they're scaling confidently, saving 20% on cloud costs, and redirecting engineering effort toward innovation instead of constant bill management.** CloudKeeper's Platform Suite combines best-in-class automated tools with unlimited expert support, delivering complete visibility, automated optimization, and sustained savings without performance compromises. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources From Generative AI to Agentic AI for FinOps: The Leap Towards Autonomous Intelligence Read this blog to discover how Agentic AI transforms cloud cost management from reactive reporting to real-time, autonomous control. By Team CloudKeeper 03 Mar, 2026 GCP Cost Explorer vs CloudKeeper Lens: From Basic Cloud Cost Monitoring to Intelligent Governance Explore how GCP Cost Explorer compares with CloudKeeper Lens for advanced cloud cost monitoring, governance, and smarter Google Cloud optimization. By Sanjeev Mittal 20 Feb, 2026 How 400+ Global Teams Are Solving Cloud Cost Issues & Scaling Efficiently? This blog distills real cloud cost problems, visibility gaps, overprovisioning, storage creep, and AI/Kubernetes sprawl and shows how ownership and CloudKeeper expertise drive lasting savings. By Team CloudKeeper * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 2 2 Table of Contents If you’re using Amazon RDS Performance Insights (PI) today, here’s some big news: AWS is retiring PI on November 30, 2025, and replacing it with ## **What’s New with Database Insights?** AWS launched DBI in December 2024, calling it the “next-generation observability solution” for databases. If you’ve used PI, DBI will feel familiar — but it comes with: * Fleet-wide monitoring instead of just per-instance views * Integration with Application Signals, logs, and events * New troubleshooting tools like lock diagnostics (Postgres) ### Free vs. Paid Here’s how DBI is packaged: * DBI Standard (Free): Enabled by default, 7 days retention (same as PI free tier) * DBI Advanced (Paid): Optional upgrade, 15 months retention, advanced features like log/event correlation, execution plans, and lock analysis ### Pricing: More Power, More Cost Here’s the catch: DBI Advanced costs 6x more than PI. * Performance Insights (PI): ~$1.50/vCPU-month * DBI Advanced: ~$9.00/vCPU-month ### Other gotchas: * Cluster-level billing: You pay for the whole cluster, not just selected instances. * Stopped clusters still bill: Unlike PI, DBI charges don’t stop when the cluster is paused. ### **Migration Timeline** * Now → Nov 2025: Evaluate PI usage, test DBI * Nov 30, 2025: PI End-of-Life * After EOL: Databases automatically roll over to DBI Standard (7 days history) ## **What You Should Do Now** 1. Audit your databases → Identify Amazon RDS/ Amazon Aurora workloads using PI. Learn about the 2. Decide your needs → Is 7 days enough, or do you need 15 months + advanced features? 3. Enable DBI proactively → Don’t wait for PI shutdown, or you’ll lose history ## Bottom Line DBI is the future of database monitoring in AWS. Yes, it’s more powerful — but also more expensive and with shorter retention than PI. The earlier you evaluate and migrate, the smoother your transition will be (and the less surprise billing you’ll face). Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Cloud Engineer Rishabh is a result-driven engineer with expertise in AWS cloud infrastructure, cost optimisation, and secure solution design. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 4 4 Table of Contents When running scaled **prefix delegation.** Instead of a node's Elastic Network Interface (ENI) requesting a single IP for every pod, the ENI is assigned an entire block of addresses, a prefix, typically a /28. This significantly accelerates pod IP assignment and boosts scalability. But what happens when the system fails? We recently encountered a puzzling customer issue where pods could not obtain or **/28 prefix blocks**. Scattered leftover IPs are useless if they cannot form a contiguous block. The pods were stuck in Pending, a classic symptom of IP shortage, yet the numbers contradicted the error. This post details the debugging journey, from understanding the relationship between /25 and /28 subnets to uncovering the hidden root cause: **subnet fragmentation**. ## **The Customer Conundrum: IPs Not Assigning** Here was the setup and the confusing symptoms we faced: * The Amazon EKS cluster was running in a **/25 subnet.** * **Prefix delegation mode** was enabled in the CNI. * The AWS console reported many **free, available IPs** in the subnet. * Despite this, pods were stuck in **Pending** with the error: "**failed to assign IP address**." The immediate conclusion was an IP shortage, but the official metrics suggested otherwise. This meant the visible IP count was a deceptive metric, requiring a deeper look into how prefixes are allocated. ## **Subnet Fundamentals: Why Block Size Matters** To understand the problem, you must think in terms of address blocks, not individual IPs. **The /25 and /28 Interaction** The **CIDR** (Classless Inter-Domain Routing) notation defines the size of an IP address range. A /25 subnet (128 total IPs) can be perfectly divided into eight distinct /28 blocks (16 IPs each). The critical realization here is that prefix delegation does not assign single IPs; it allocates entire, contiguous /28 chunks to the ENIs. This was the key insight: The customer's subnet had many free, scattered individual IPs, but these leftover addresses were useless if a clean, contiguous /28 block was not available. The remaining free IPs were too fragmented to form a full block. ## **Our Debugging Walkthrough** Solving this required a methodical approach to eliminate * **Initial Checks** – Nodes were Ready, ruling out basic kubelet or network configuration failures. * **Subnet IP Deception** – The console's "available IP" count was misleading. We suspected this metric did not reflect the reality of prefix availability. * **CNI Logs** – We confirmed the aws-node DaemonSet logs showed prefix delegation was enabled, ruling out simple configuration errors. * **CloudTrail Investigation** – We searched CloudTrail for prefix assignment API call failures. Finding none ruled out common ## **The Key Hypothesis: Fragmentation** After ruling out the standard culprits, we hypothesized: **The issue isn't the total count of free IPs; it's the availability of contiguous /28 blocks**. The subnet was suffering from fragmentation. **The Script That Revealed the Truth** To prove the hypothesis, we needed to see every IP currently attached to an ENI within the subnet. We used a simple AWS CLI script: Running this script confirmed the hypothesis: The allocated IPs were scattered across the subnet's range, consuming portions of all eight potential /28 blocks. Subnet fragmentation was confirmed. Zero full, intact /28 blocks remained for a new ENI to be allocated. ## **Conclusion and Operator Takeaways** The root cause was definitive: **Subnet fragmentation** had made all remaining IPs unusable for prefix delegation. ### **The Fix** We worked with the customer on two main solutions: * **Free Up Usage** – Releasing full ENIs or workloads to clear an entire /28 block for reuse * **Plan for Scale** – Designing future subnets to be larger than /25 (e.g., /24 or /23) to provide more resilience against fragmentation Once a clean /28 block was made available, the prefix delegation mechanism immediately worked, and pods began acquiring IPs without further issues. ## **Key Takeaways for Amazon EKS Operators** * **Prefix Delegation Works in Blocks** – When prefix delegation is enabled, you must think in terms of /28 blocks. **Scattered free IPs are useless**. You need a **full, contiguous /28 block** for allocation to the node. * **Subnet Design Matters** – A /25 only provides eight /28 chunks. Larger subnets offer greater stability and flexibility as your cluster scales. * **The Console Can Mislead** – The **"available IP"** count is a general metric. To truly diagnose prefix delegation issues, inspect ENI assignments directly to check for fragmentation. If you use prefix delegation in Amazon EKS, your real bottleneck is not "free IP count." It is "available block count." Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior DevOps Engineer Gourav specializes in helping organizations design secure and scalable Kubernetes infrastructures on AWS. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 3 3 Table of Contents If you’ve ever tried to hook up an AWS Simple Notification Service topic to an HTTP or HTTPS endpoint, you probably know the dance: SNS sends a **SubscriptionConfirmation** request, your endpoint is supposed to respond with a 200 OK, and then everything is happy. Except sometimes… it isn’t. The subscription just sits in **“PendingConfirmation”** , retries keep happening, and nothing works. Let’s unpack why that happens and how to fix it. ## **How Amazon SNS Subscription Confirmation Works** Here’s what happens under the hood: 1. You tell Simple Notification Service to subscribe an endpoint (HTTP or HTTPS). 2. SNS sends a **POST request** with a JSON message that includes: * Type: SubscriptionConfirmation * MessageId * SubscribeURL (this is the key) 3. Your endpoint has to: * Respond with**HTTP 200 OK** * (Optionally) validate the signature * And you (or your app) must call the SubscribeURL to confirm If step 3 fails in any way, the subscription won’t confirm. ## **Why Confirmation Fails** Here are the most common gotchas: * **Your endpoint doesn’t return 200 OK** Maybe it returns 302, 403, or times out. Amazon SNS needs a clean 200. * **Firewall or security group blocks SNS** If your service runs in a private * **HTTPS certificate issues** If you’re using HTTPS, Amazon SNS requires a valid, trusted certificate. Self-signed certs usually break it. * **The app doesn’t handle POST** If your endpoint only listens for GET and ignores POSTs, it’ll fail. SNS always sends a POST. * **Confirmation URL never clicked** AWS SNS includes a SubscribeURL in the message. If you don’t hit that URL (either manually or in code), the subscription won’t move past “PendingConfirmation.” ## **How to Debug** When things fail, here’s where to look: * **Check your server logs:** Did it even receive the POST? What status code did it send back? * **Look at the raw SNS message:** Is your handler parsing JSON correctly? Did you miss SubscribeURL? * **Test with curl :** Simulate the SNS POST yourself to verify your endpoint handles it. * **Use VPC Flow Logs or ALB Logs :** See if SNS traffic is even making it to your service. ## **How to Fix** * Make sure your endpoint accepts POST and responds with HTTP 200 OK. * If using HTTPS, ensure the cert is valid and trusted by AWS. * Open up security groups/firewalls to allow SNS IP ranges. * Actually, call the SubscribeURL once you get the message, and automate this in code if possible. * For production: verify the SNS message signature to ensure it’s legit. ## **A Better Flow: Automating Confirmation** In practice, you don’t want to rely on a human clicking SubscribeURL. 1. Receive the SubscriptionConfirmation message. 2. Parse out the SubscribeURL. 3. Make an HTTP GET request to that URL in code. 4. Log the result. That way, every new subscription confirms automatically. ## **Wrapping It Up** AWS SNS subscription confirmation failures almost always boil down to one of two things: 1. AWS SNS can’t reach your endpoint. 2. Your endpoint doesn’t handle the request correctly. The fix is usually straightforward once you know where to look. The hard part is realizing that it’s not SNS being flaky, it’s usually networking, HTTPS, or your handler. Get those pieces right, and Amazon SNS subscriptions just work. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Cloud Engineer Manish is an AWS-focused expert known for optimizing infrastructure performance, controlling costs, and designing secure and reliable cloud solutions. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 7 7 Table of Contents As we approach the International Women’s Day, we take a look at the theme for the year, "**Count Her In: Invest in Women, Accelerate Progress** ". Based on the priority theme for the United Nations 68th Commission on the Status of Women, the theme deeply resonates within the tech and FinOps landscape. Our lives are now completely surrounded by technology, which has completely changed the way we live, work, and interact. The technology sector is always changing, and the emergence of cloud computing has brought about new chances for people to get involved and succeed. Not everyone has, however, had equal access to these opportunities. Significant obstacles have prevented members of marginalized communities and other underrepresented groups from joining the tech sector. Women make up Thankfully, the field of "Cloud FinOps," which blends financial operations and cloud DevOps, is making it easier for members of underrepresented groups to enter and succeed in the digital sector. While traditionally skewed towards male representation, these fields are witnessing a remarkable shift as women take center stage, not just contributing, but leading and inspiring the next generation. ## **Understanding Cloud FinOps** Cloud FinOps, a technique that focuses on optimizing cloud utilization and expenses while setting enterprises for rapid expansion, has gained popularity in recent years. It ## **Why focus on diversity and inclusion in tech?** Diversity and inclusion are the cornerstones of innovation and long-term success in the tech sector, as has been widely reported. Diverse viewpoints, experiences, and ideas are brought together by a diverse workforce, which improves products and services and fosters more creative problem-solving. But historically, there hasn't been much diversity in the tech sector, with major entry barriers facing underrepresented communities. In addition to sustaining inequity, this lack of representation restricts the industry's ability to innovate and thrive. There is more to increased female presence in FinOps and technology than just statistics. The history of technology is intertwined with the accomplishments of incredible women, ranging from **Ada Lovelace** , the first computer programmer in history, to **Grace Hopper** , a pioneer in compiler development. These early pioneers broke over the glass ceiling, proving that brilliance and diversity in thought are essential for tech innovation regardless of gender. It aggressively combats any unconscious prejudice that might exist in organizations. By bringing their distinct experiences and perspectives to the table, women help break down unhelpful preconceptions and establish a more equal workplace. Everyone gains from this, as it promotes creativity and invention and, eventually, organizational success. In addition to other beneficial development results, women's economic empowerment raises productivity, improves economic diversity, and promotes ## **How do challenges impact the marginalized groups in tech?** Disenfranchised groups have encountered several obstacles in their attempts to get into and succeed in the technology sector. Unconscious biases in the recruiting and recruitment procedures, a dearth of mentors and role models, and a lack of networking opportunities are some of these difficulties. The industry also continues to have a gender and racial pay disparity, which exacerbates the injustices experienced by marginalized people. ## **FinOps: A Collaborative Future** There is a significant opportunity for inclusion in the tech sector through Cloud FinOps. Women are becoming more visible in the specialist sector of FinOps, which is centered on optimizing cloud expenses. They currently make up about 26.7% of all IT workers worldwide, and their numbers are continuing to rise. They create creative solutions, hold important positions in cost management teams, and contribute a variety of viewpoints and cooperative methods to the table. This change promotes a more productive and inclusive atmosphere for all parties engaged, which improves decision-making and results. ## **How can marginalized groups benefit by entering Cloud FinOps?** For people from different communities, cloud FinOps has a number of advantages: **Bringing cost optimization and efficiency to businesses** : Cloud FinOps helps businesses to make the most out of their cloud investments by making sure resources are used effectively. Experts in Cloud FinOps can help reduce costs, which makes them an invaluable resource for businesses. **Empowering skill development** : People from different groups can gain useful skills in data analysis, financial management, and cloud computing by working in the field of cloud finance operations. These abilities help them become more marketable and enable them to assume leadership positions in the tech sector. **Leveraging special initiatives:** FinOps Foundation’s special initiatives like the The Women in FinOps **Accessing tech opportunities:** People can obtain a variety of tech opportunities with Cloud FinOps. Professionals with experience in Cloud FinOps are in great demand as more and more firms adopt cloud technology, opening up opportunities for career growth and advancement outside of FinOps. **Making the most of an emerging field** : Cloud FinOps is a relatively new field, even if other disciplines have addressed some of the same concerns, especially in On-Prem systems. It is possible for members of marginalized communities to make a name for themselves in a rapidly expanding and changing field. ## **Improved networking opportunities** The Cloud FinOps community offers a great networking and cooperation platform. Professionals in the industry have access to events, seminars, and a Slack community (FinOps Foundation) to connect with like-minded people and exchange expertise and experiences. In addition to encouraging creativity, networking and collaboration give people from underrepresented groups a solid network of allies that helps them get about the business and take advantage of good possibilities. ## **CloudKeeper: Empowering a Diverse Workforce** Being a leading cloud FinOps and cost optimization solution, CloudKeeper is committed to developing an inclusive and diverse workforce. We are aware that a diverse group of perspectives and experiences makes for a more dynamic and productive team. To enable women to thrive in FinOps and beyond, we offer mentorship programs, flexible work schedules, and career growth opportunities. **Unpause, CloudKeeper by TO THE NEW’s special initiative** , was launched for all the women professionals who pressed pause on their work and want to hit play again. ## **Conclusion** Not only is cloud FinOps transforming the industry's approach to cloud migration, but it's also providing opportunities for members of underrepresented communities. Organizations may maximize their cloud expenditures and advance diversity and inclusion in technology by adopting Cloud FinOps principles. People from underrepresented populations can make a name for themselves in the tech sector and foster innovation and growth by developing their skills, giving them more power, and giving them access to opportunities. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources FinOps is leaving the Dashboard In this blog, Ronak Goyal explores how LensGPT MCP Server enables conversational FinOps with real-time cloud insights within AI tools such as Claude, Cursor, Kiro, and ChatGPT. By Ronak Goyal 26 May, 2026 AI for FinOps and the Future of Cloud Cost Intelligence In this blog, we discuss how AI is emerging as a key driver of cloud cost intelligence and transforming FinOps practices. By Team CloudKeeper 22 May, 2026 How FinOps Teams Can Use AI for Smarter Cloud Cost Control A detailed blog on how FinOps teams can leverage AI to improve cloud cost optimization, visibility, automation, and operational efficiency. By Team CloudKeeper 15 May, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Cloud spending is on track to hit about $700+ billion by the end of 2025, yet more than one in five organizations say they lack clear visibility into what they actually pay for in the cloud. For AWS users, the pressure is even higher: roughly 53% of their bill goes to compute, while an average of 30% of cloud budgets is lost to waste. The numbers add up fast—oversized instances pile up, idle “zombie” resources quietly burn cash, and poor cost allocation erodes accountability. Nearly half of organizations already report cloud costs running higher than planned, and many describe them as far too high, even as only around 64% make use of commitments like Reserved Instances or Savings Plans, leaving easy savings unrealized. What used to be a back-office IT problem is now a boardroom issue, where CFOs demand visibility, CTOs need control, and DevOps teams require actionable, real-time insights rather than more raw data. ## **Why AWS re:Invent 2025 Matters for Cost Management** AWS re:Invent 2025 in Las Vegas presents trusted strategies to convert cloud waste into tangible savings. Explore the key sessions designed to deliver the most value for cost optimization. ### The Foundation: Understanding What's New * **COP203: What's New with AWS Cost Management** Wednesday, Dec 3 | 10:30 AM – 11:30 AM PST | Mandalay Bay, Level 3 South, South Seas E Special guests: Corey Quinn (Duckbill Group) and Matt Cowsert (FinOps Foundation) * **COP202: What's New with AWS Cost Optimization** Thursday, Dec 4 | 2:30 PM – 3:30 PM PST | MGM, Level 3, Chairman's 360 Special guest: Bonnie Firnstahl (Delta Airlines) These breakout sessions reveal the newest features and actionable optimization techniques delivered by AWS experts and seasoned practitioners handling large-scale infrastructures. ### Getting Strategic: Governance and Allocation * **COP309: Establishing Effective Cost Governance (Chalk Talk)** Wednesday, Dec 3 | 3:00 PM – 4:00 PM PST | Wynn, Convention Promenade, Latour 5 Also: Thursday, Dec 4 | 12:30 PM – 1:30 PM PST | Wynn, Convention Promenade, Lafite 1 * **COP339: Developing a Cost Allocation Strategy (Chalk Talk)** Wednesday, Dec 3 | 11:30 AM – 12:30 PM PST | Wynn, Convention Promenade, Lafite 1 These interactive sessions guide you to create automated cost-aware systems and convert cloud invoices into clear, actionable insights through precise cost allocation. ### Going Deep: Technical Implementation * **COP410: Exploring Multi-tenant Cost Allocation for Container Workloads (Workshop)** Thursday, Dec 4 | 12:00 PM – 2:00 PM PST | MGM, Level 3, Premier 318 (Laptop required) * **COP306: Developing Unit Cost Metrics with Cloud Intelligence Dashboards (Builder Session)** Monday, Dec 1 | 5:30 PM – 6:30 PM PST | Mandalay Bay, Lower Level North, Islander H Also: Tuesday, Dec 2 | 11:30 AM – 12:30 PM PST | Mandalay Bay, Level 2 South, Oceanside C (Laptop required) * **COP401: Advanced Analytics with AWS Cost and Usage Reports (Code Talk)** Monday, Dec 1 | 8:30 AM – 9:30 AM PST | MGM, Chairman's 356 Also: Tuesday, Dec 2 | 2:30 PM – 3:30 PM PST | Wynn, Convention Promenade, Margaux 1 * **COP201: Estimating Workload Costs Using AWS Pricing Calculator (Chalk Talk)** Monday, Dec 1 | 5:30 PM – 6:30 PM PST | Wynn, Convention Promenade, La Tache 2 * **COP419: Advanced Multi-cloud Cost Reporting with FOCUS (Code Talk)** Monday, Dec 1 | 4:00 PM – 5:00 PM PST | MGM, Level 3, Chairman's 370 Also: Tuesday, Dec 2 | 2:30 PM – 3:30 PM PST | MGM, Level 3, Chairman's 370 These hands-on sessions cover container cost allocation, building unit cost metric dashboards, leveraging advanced analytics from AWS Cost and Usage Reports, estimating workload costs, and delivering multi-cloud cost reporting. ## Meet CloudKeeper at AWS re: Invent 2025 The CloudKeeper leadership team will be at AWS re:Invent 2025 at The Venetian, eager to share insights gained from delivering significant cloud cost savings across the optimization journey. Whether you’re aiming to boost visibility, automate cost controls, or adopt proven best practices, our experts provide actionable solutions tailored to your needs. Ever tried explaining a 40% cost spike to your CFO with zero visibility into why? Discovered "zombie" resources that have been bleeding money for years? Wondered why your team keeps provisioning resources that never get shut down. We're bringing case studies, best practices, and honest conversations about what actually works. ## Making the Most of re: Invent Cloud cost management is an ongoing process, not a one-time fix. The insights gained at re:Invent 2025 can shape your cloud strategy long-term, shifting cost optimization from reactive fixes to proactive planning. Begin with “What’s New” sessions to grasp the evolving AWS cost management landscape. Participate in governance and allocation sessions to build strong frameworks—without these, even top optimization tactics can falter. Select technical deep-dives aligned with your challenges—be it containers, analytics, multi-cloud, or unit metrics—to gain hands-on knowledge you can apply immediately. Connect with experts like the CloudKeeper team who bring real-world success stories. As the cloud innovator shaping your business, use re:Invent to transform rising AWS costs into controlled, strategic growth opportunities. You’re the one driving innovation in the cloud—architecting, optimizing, and scaling your business every day. Yet, rising AWS costs can feel like a shadow over your success. This year at re: Invent, you have the chance to turn that around. With the CloudKeeper team by your side, you’ll discover the tools, strategies, and community support to conquer your cloud spend and lead your organization toward smarter, cost-efficient growth. **Own your AWS bill. Lead the re: Invent-ion.** Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! Meet the Author * Senior Director Praneet brings over 14 years of experience in building high-growth SaaS companies right from 0$ to IPO. He has held key roles at Udemy, Gainsight, and Deloitte. FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources AWS Savings Plans vs Reserved Instances vs Spot: Which One Is Right for Your Workload? In this blog, learn how to choose the right AWS pricing model for your workloads and optimize cloud costs intelligently. By Team CloudKeeper 27 May, 2026 How Private DNS Resolution Works in AWS Across Accounts A detailed blog exploring private DNS resolution in AWS, covering architecture patterns (before and after), best practices, and centralized vs. decentralized approaches. By Akash Sawan 28 Apr, 2026 Enabling multiple IdPs in AWS IAM Identity Center using Keycloak Guide to integrating AWS IAM Identity Center with Keycloak, covering why it matters, setup steps, and benefits for secure, centralized access management. By Rachana Kumari 22 Apr, 2026 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 5 5 Table of Contents Depending on demand, AWS Auto Scaling dynamically modifies the number of instances running in your AWS environment. Ensuring that you only pay for the resources you use at any given time, can help you reduce your costs. AWS Auto Scaling does not support all AWS resources. It can be used to set up scaling for resources as mentioned below. * Amazon EC2 * Amazon ECS * Amazon DynamoDB * Amazon Aurora * Amazon EC2 Spot Fleets ## **Here are some best practices and strategies for cost optimization with AWS Auto Scaling** **Use spot instances in AWS Auto-Scaling Group** : Spot instances are extra AWS EC2 instance types that are offered at a price that is considerably less than On-Demand instances. You may benefit from the cheaper prices while still making sure you have the necessary capacity to manage traffic spikes by utilizing AWS Auto Scaling with spot instances. Here's an example of how using AWS Auto Scaling with Spot Instances can result in **c5.xlarge** On-Demand instances 24/7, and you're paying $0.17 per hour per instance. This would result in a monthly cost of: Now, let's say you use AWS Auto Scaling with Spot Instances to run the same application. Spot Instances are spare EC2 instances that are available at a much lower cost compared to On-Demand instances, and can be used when the demand is low. For example, let's say you set up your Auto Scaling group to use ten **c5.xlarge** Spot Instances and ten On-Demand instances. The Spot Instance price for **c5.xlarge** in the **us-west-2** region is around $0.057 per hour. Assuming the Spot Instance prices remain similar, your monthly cost would be: That's a savings of over $813.6 per month, or 66% less than the cost of running ten On-Demand instances 24/7! Of course, Spot Instances come with the risk of being interrupted, which means that you need to be able to handle sudden instance termination and ensure that your application can recover quickly. By using AWS Auto Scaling, you can build a resilient architecture that can handle these interruptions and still provide high availability and performance while significantly reducing your costs on EC2 instances. **Utilize predictive scaling:** By using machine learning algorithms to predict future demand, predictive scaling automatically adjusts capacity. Without having to manually change your scaling policies, you can use predictive scaling to make sure you have the appropriate capacity at the appropriate moment. **Recurring monitoring of Auto-scaling policies:** To make sure you're optimizing expenses while achieving your performance needs, it's crucial to **Use CloudWatch alarms according to the need:** Based on particular performance parameters, such as CPU utilization or network traffic, **Use Scheduled Actions with AWS Auto Scaling Groups:** Scheduled actions in AWS Auto Scaling Groups allow you to define a set of scaling actions that are triggered on a schedule, rather than in response to a specific event or performance metric. This can be useful for optimizing costs by scaling up or down based on predictable changes in traffic or demand. For example, you might set up a scheduled action to boost your Auto Scaling group's intended capacity during busy business hours and another to lower the desired capacity during slower periods. Ensuring that you only pay for the resources and AWS instance types that you use at any given time, can help you save expenditures. It's crucial to keep in mind that scheduled activities can take up to 15 minutes to take effect, so make sure to factor that time into your schedules. Also, keep in mind that additional scaling actions outside of those scheduled may be necessary due to unanticipated changes in demand or traffic. Here is a snippet of creating scheduled action. **Use multiple Auto Scaling groups:** You can reduce costs by employing numerous Auto Scaling groups and using separate groups of AWS instance types for various reasons. For instance, you might have one set of instances for dealing with steady-state traffic and another set for dealing with traffic peaks. You may make sure that each Auto Scaling group is optimized for the particular needs of that task by separating the groups for distinct workloads. For instance, you might have two groups, one optimized for memory-intensive tasks, like RDS instance types, and the other for CPU-intensive applications, like the EC2 instance types. By doing this, you may **Use Elastic Load Balancing:** You may equally split your workload by using Elastic Load Balancing (ELB) with Auto Scaling to distribute traffic across several instances. This can assist in avoiding instances of getting overloaded, which could result in worse performance and higher expenses. You may use AWS Auto Scaling to optimize your costs and make sure that you're only paying for the resources you need at any given time by _Like Auto Scaling, multiple other architectural considerations can help you_ _significantly while improving your cloud utilization and performance. With an expert like CloudKeeper by your side, you can rest assured that our team of AWS-certified experts will take care of your AWS Cost Optimization efforts, while you focus on your business.__to learn more._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. Let's discuss your cloud challenges and see how CloudKeeper can solve them all! FOUND THIS USEFUL? SHARE IT No Comments Yet Leave a Comment Related Resources Generative AI Explained: Concepts, Tools & Important Use Cases A clear, practical guide to Generative AI covering core concepts, future trends, leading tools, and real-world industry applications. By Team CloudKeeper 20 Nov, 2025 Automate Beyond Limits with n8n: Your Open-Source Automation Powerhouse This blog will help you gain a working understanding of automating with n8n through a practical example and a comparison with Make and Zapier. By Pratik Singh 04 Nov, 2025 5 Common Mistakes to Avoid in AWS Auto Scaling Groups AWS Auto Scaling Groups (ASG) adjust EC2 capacity automatically, maintaining your infrastructure effectively. Learn here the 5 common mistakes you should avoid. By Rachana Kumari, Aditya Sinha 31 Aug, 2023 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Turn AWS Cost Concerns into Customer Growth Discover how AWS teams turn cost optimization into expansion. Watch the webinar and learn strategies to reopen PPAs and accelerate adoption. Beyond the Dashboard: How Teams Optimized Cloud Usage and Spend? What if your cloud dashboards told you less about what’s happening—and more about what’s working? Live Demo - How can you cut AWS costs by 15% in 15 minutes? Watch our exclusive demonstration of automated AWS cost optimization in action. Learn how businesses like yours can reduce cloud spending without sacrificing performance or security. 2025 Cloud Fitness: 5 Pro-tips for Healthier AWS Infrastructure Watch now to uncover 5 expert-backed tips to reduce costs, enhance performance, and maximize cloud efficiency—without compromising scalability or adding operational complexity. Cut Your Cloud Bill : 10 Actionable Steps Every Business & Tech Team Must Take! Watch an interactive session to learn expert strategies, and get an exclusive & must-have 10-point checklist for cloud cost savings without compromising performance. Considerations for Optimizing Your AWS EDP Investment Watch this exclusive webinar in which our Cloud expert spills the beans on how to optimize your high-volume AWS spending or derive maximum value from your existing EDP program. Fumbles in FinOps Adoption and How to Avoid Them Watch this exclusive panel discussion where our industry experts talk about the common mistakes organizations make in their FinOps adoption journey. Expert Tips to Combat Cloud Waste in 2024 Watch this exclusive webinar in which our FinOps experts will share the time and tested techniques for ensuring minimum cloud waste and maximizing cloud cost savings in 2024. 2024 Essentials: Tactics to Reduce Cloud Waste As per a recent survey, 38% of organizations experience more than 30% of their cloud spend getting wasted. Watch this on-demand webinar to learn more. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Ace your cloud FinOps journey with recommendations from AWS-certified cloud experts If **AWS cloud cost optimization** is your number one priority, watch this exclusive on-demand webinar where you'll hear from a panel of industry experts and cloud FinOps practitioners on ways to save 5-15% on your AWS bill. The diverse audience included: 1. Product Companies - CEO, CFO, Head of Finance & Founders 2. Venture Capitalist Firms - Angel Investors 3. Digital-Native Businesses - CTO, CIO & Head of Engineering Key Takeaways * Best practices to reduce your cloud spend * Cloud cost optimization techniques from industry experts * How CloudKeeper can help optimize cloud spend * CloudKeeper - customer stories * Q&A session with the audience Speakers: 1. Aman Aggarwal - AVP, Cloud & DevOps CloudKeeper AWS Certified Professional with 15+ years of experience. 2. Steven Thurlow - CEO, Singula Decisions A technology leader in the customer subscription Management system. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Achieve sustainable AWS cloud cost savings through cloud cost optimization tips by industry experts Reducing your AWS bill is hard, reducing it further is harder. The 45-minute webinar unravelled the unconventional hacks to cut down the AWS Bill instantly. We discussed various ways to ensure guaranteed reduction on entire AWS bills. The diverse audience included: 1. Product Companies - CEO, CFO, Head of Finance & Founders 2. Venture Capitalist Firms - Angel Investors 3. Digital-Native Businesses - CTO, CIO & Head of Engineering The major takeaways from the session were: * Learnt various unconventional cost optimization hacks * Save further by learning techniques from industry experts * Hear product owners' experiences with using these hacks * Questions & Answer session with the audience Speakers: 1. Aman Aggarwal - AVP, Cloud & DevOps CloudKeeper AWS Certified Professional with 15+ years of experience. 2. Amit Poddar - CTO, eLocal (a HomeServe Company) Technology leader with 30+ years of Industry experience. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Beyond the Dashboard: How Teams Optimized Cloud Usage and Spend? In the final episode of the Cloud Fitness Challenge, we moved beyond theory and tooling into real **AWS optimization outcomes** , shared directly by the engineering leaders who made them happen. Who should watch this? This webinar is especially for, but not limited to: 1. DevOps & Cloud Engineers 2. IT & FinOps Architects 3. Engineering Directors, CTOs & Cloud Leaders 4. Anyone facing scale, sprawl, or spend issues in AWS Key Takeaways * How teams successfully reduced AWS spend * Practical implementation strategies and best practices that worked * Unexpected wins and use cases that emerged post-optimization * How usage insights translated into real efficiency gains Featured speakers: 1. 2. 3. Moderated by These leaders unpacked their stories of navigating AWS complexity, shifting from reactive monitoring to proactive usage strategies, and driving measurable outcomes for both engineering and finance teams. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # AI-Driven AWS RI Management #### Achieving Maximum Coverage with ZERO Commitment Unpredictable workloads and uncertainty in purchase decisions are just a few of the many pressing issues of managing and optimizing AWS Reserved Instances. Sounds familiar? In this webinar, we discussed how you can automate your RI management with zero-touch and no additional commitments. Watch out for our secret sauce on how you can get on-demand EC2 resources at 3-year RI pricing. Learn how to maximize AWS coverage in a risk-free way. The major takeaways from the session were: * Challenges in traditional RI Management * Benefits of having an automated RI Management System * An AI-Enabled Automated RI Management system * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Building a FinOps Culture #### Closing Remarks at FinOps Accelerate TO THE NEW organized **FinOps Accelerate, an AWS FinOps Virtual Conference** , on November 18,2021 with the main objective of creating a discussion forum around FinOps. The conference was graced by some of the most influential CTOs and IT Influencers from leading companies who provided practical and actionable insights for organizations on the FinOps culture. The one-day conference was closed by remarks on FinOps culture by TK Verma, SVP & Head - US Enterprises, TO THE NEW. The closing remarks by TK emphasized the prerequisites of building a FinOps culture like collaboration, value-driven decision making, setting accountability, real-time clean data, embracing variable cost model, and a centralized FinOps team. He also mentioned breaking the cost view down to the three phases of FinOps namely Inform, Optimize and Operate. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Considerations for Optimizing Your AWS EDP Investment Take the first step towards making the most out of the AWS Enterprise Discount Program (AWS EDP), and learn ways to effectively optimize your cloud investment. Watch our on-demand webinar to know: 1. Constructs of AWS Enterprise Discount Program (EDP) 2. If AWS EDP is the right choice for you and how you can get started 3. How to get the best EDP deal with maximum benefits and minimum risks Get insights on how CloudKeeper EDP+ offers additional discounts on your EDP deal at lower annual commits, and the perks we offer which go beyond just discounts. Our Key Takeaways: * The advantages and pitfalls of EDP * Broad contours of EDP construct * How to maximise benefits from EDP * Using CloudKeeper EDP+ for extended gains Speaker: * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Cut Your Cloud Bill : 10 Actionable Steps Every Business & Tech Team Must Take! Join us for an insightful session where our cloud cost experts will share actionable strategies to help you cut costs without sacrificing on performance. Watch our on-demand panel discussion to know: 1. 10 actionable steps to lower your cloud costs 2. Relevant cloud cost optimization insights from top industry leaders 3. Real-world solutions your team can apply right away along with a Speakers: 1. Accomplished tech leader with a passion for programming, architecture design, and product management. He is advancing AI-powered SaaS marketplace solutions for the creator economy & branding innovation. 2. Co-Founder of WiseOps, Ronak brings 11+ years of expertise in AI/ML and data product development. An IIT-BHU alumnus, he has successfully scaled engineering teams at startups like Cogoport, Jugnoo, and Peak AI. 3. Co-Founder of WiseOps, Praneet has 14+ years of experience scaling SaaS companies from startup to IPO. With key roles at Udemy, Gainsight, and Deloitte, he is passionate about coding and mentoring early-stage startups. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Cloud Economics 101: How can you control your AWS Costs to the penny? #### Panel Discussion at FinOps Accelerate TO THE NEW organized **FinOps Accelerate, an AWS FinOps Virtual Conference** , on November 18,2021 with the main objective of creating a discussion forum around FinOps. The conference was graced by some of the most influential CTOs and IT Influencers from leading companies who provided practical and actionable insights for organizations on the FinOps culture. The panelists for this discussion were **Lauren Nelson, VP, Research Director, Forrester, Ashley Hromatko, Director of FinOps, Pearson & Mark Brincat, Chief Technology Officer, SHL**. They discussed measuring the performance of FinOps teams and the processes of forecasting budgets in variable cloud costs. The major takeaways from the session were: * Challenges with managing & tracking Cloud spends * Key metrics & benchmarks to keep an eye on * Budgeting & forecasting Cloud spends * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Ensure Guaranteed AWS cloud cost savings from Day 1 Reducing your AWS bill is hard, reducing it further is harder. The 45-minute webinar unravelled the unconventional hacks to cut down the AWS Bill instantly. We discussed various ways to ensure guaranteed reduction on entire AWS bills. The diverse audience included: 1. Product Companies - CEO, CFO, Head of Finance & Founders 2. Venture Capitalist Firms - Angel Investors 3. Digital-Native Businesses - CTO, CIO & Head of Engineering The major takeaways from the session were: * Learnt various unconventional cost optimization hacks * Save further by learning techniques from industry experts * Hear product owners' experiences with using these hacks * Questions & Answer session with the audience Speakers: 1. Aman Aggarwal - AVP, Cloud & DevOps CloudKeeper AWS Certified Professional with 15+ years of experience. 2. Siddhartha Kongara - Co-founder and CTO, Growsari A Technology Leader with over two decades of experience across various industries. 3. Prateek Baheti - Head of Technology, MoneySmart A Technology Leader with 10+ years of experience. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Expert Tips to Combat Cloud Waste in 2024 A recent survey by Everest Group revealed that most organizations experience more than 30% of their cloud spending getting wasted. So, it is paramount to understand how to effectively manage cloud waste and thereby effectively utilize your IT spending. Ensure maximum savings with minimum cloud waste with helpful insights from our FinOps expert. Watch our exclusive webinar where we unravel top strategies that will have your cloud bills shrinking, not skyrocketing! Our Key Takeaways: * Understanding cloud waste & why is it the top cause of concern in 2024? * Strategies you can use to reduce cloud waste. * Proven solutions that can help you plug cloud waste. * Q&A with FinOps consultant. Speaker: Harsh Agarwal - FinOps Expert, CloudKeeper Expert in optimizing cloud wastage and maximizing savings. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Why bother about FinOps today? #### Keynote Session at FinOps Accelerate TO THE NEW recently concluded **FinOps Accelerate, an AWS FinOps Virtual Conference** , with the main objective of creating a discussion around FinOps and providing practical and actionable insights on the topic. The conference was graced by some of the most influential CTOs and IT Influencers from leading companies. The one-day conference had a keynote address by **Lauren Nelson, VP & Research Director at Forrester Research**. Lauren highlighted how consumer behavior has changed over the course of the past two years and the resulting growth in cloud investments. This has led to rising infrastructure costs opening the way to the practice of FinOps. In this Keynote Session, Lauren will walk you through: * The major challenges an organization faces leading to increased costs * The Best Practices to be followed for Cloud Cost Optimization * Need for the FinOps culture to be inculcated within organizations * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Fumbles in FinOps Adoption and How to Avoid Them In the rapidly evolving landscape of cloud technology, the adoption of FinOps has emerged as a critical practice for organizations worldwide. However, from navigating complex cost structures to overcoming cultural barriers, organizations encounter a myriad of hurdles on their FinOps journey. In our recent episode of FinOps Accelerate, our panelists delved into these challenges. Through insightful discussions and practical strategies, these industry experts talked about the common mistakes organizations make in their FinOps adoption journey and offered actionable insights. Our Key Takeaways: * Equating FinOps solely with cost reduction, overlooking its broader scope * Collaboration across teams * Setting the right KPIs for FinOps implementation and tracking them * Choosing the right FinOps tools and processes Speakers: 1. 2. 3. Watch this exclusive panel discussion and explore the unique insights from the industry experts. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Get insights into FinOps best practices and cloud cost optimization techniques to streamline the AWS infrastructure If **AWS cloud cost optimization** is your number one priority, watch this exclusive on-demand webinar where you'll hear from a panel of industry experts and cloud FinOps practitioners on ways to save 5-15% on your AWS bill. The diverse audience included: 1. Product Companies - CEO, CFO, Head of Finance & Founders 2. Venture Capitalist Firms - Angel Investors 3. Digital-Native Businesses - CTO, CIO & Head of Engineering The major takeaways from the session were: * Best practices to reduce your cloud spend * Cloud cost optimization techniques from industry experts * How CloudKeeper can help optimize cloud spend * CloudKeeper - customer stories * Q&A session with the audience Speakers: 1. Aman Aggarwal - AVP, Cloud & DevOps CloudKeeper AWS Certified Professional with 15+ years of experience. 2. Alan Lai - Head of Engineering, Fave An expert in Mobile Android Development, recognised as the Best Leader of the Year. 3. Ben Trigger - CTO, Qoria A seasoned professional with 25+ years of experience as a technology consultant. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Learn how to get a streamlined and cost optimized AWS infrastructure from industry experts Reducing your AWS bill is hard, reducing it further is harder. The 45-minute webinar unravelled the unconventional hacks to cut down the AWS Bill instantly. We discussed various ways to ensure guaranteed reduction on entire AWS bills. The diverse audience included: 1. Product Companies - CEO, CFO, Head of Finance & Founders 2. Venture Capitalist Firms - Angel Investors 3. Digital-Native Businesses - CTO, CIO & Head of Engineering The major takeaways from the session were: * Learnt various unconventional cost optimization hacks * Save further by learning techniques from industry experts * Hear product owners experiences on using these hacks * Questions & Answer session with the audience Speakers: 1. Aman Aggarwal - AVP, Cloud & DevOps CloudKeeper AWS Certified Professional with 15+ years of experience. 2. Arif Shanji - Senior VP - Engineering, Wahed A Technology Leader with over two decades of experience across various industries. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Learn unconventional techniques to save big on your AWS bills Reducing your AWS bill is hard, reducing it further is harder. The 45-minute webinar unravelled the unconventional hacks to cut down the AWS Bill instantly. We discussed various ways to ensure guaranteed reduction on entire AWS bills. The diverse audience included: 1. Product Companies - CEO, CFO, Head of Finance & Founders 2. Venture Capitalist Firms - Angel Investors 3. Digital-Native Businesses - CTO, CIO & Head of Engineering The major takeaways from the session were: * Learnt various unconventional cost optimization hacks * Save further by learning techniques from industry experts * Hear product owners experiences on using these hacks * Questions & Answer session with the audience Speakers: 1. Aman Aggarwal - AVP, Cloud & DevOps CloudKeeper AWS Certified Professional with 15+ years of experience. 2. Amit Poddar - CTO, eLocal (a HomeServe Company) Technology leader with 30+ years of Industry experience. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Live Demo - How can you cut AWS costs by 15% in 15 minutes? Watch our exclusive demonstration of automated AWS cost optimization in action. Learn how businesses like yours can reduce cloud spending without sacrificing performance or security. Who is it for This webinar is especially for, but not limited to: 1. DevOps & Cloud Engineers 2. IT & Cloud Architects 3. CTOs & Tech Leaders Key Takeaways from the webinar were: * How engineering teams saved without disrupting performance * How to validate cost recommendations and track real-world impact * Handling cost savings at scale across regions, teams, and workloads * Ways to automate actions despite time and resource constraints Speakers 1. 2. 3. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Optimize the AWS cloud spends using best practices and techniques discussed by Cloud leaders Reducing your AWS bill is hard, reducing it further is harder. The 45-minute webinar unravelled the unconventional hacks to cut down the AWS Bill instantly. We discussed various ways to ensure guaranteed reduction on entire AWS bills. The diverse audience included: 1. Product Companies - CEO, CFO, Head of Finance & Founders 2. Venture Capitalist Firms - Angel Investors 3. Digital-Native Businesses - CTO, CIO & Head of Engineering The major takeaways from the session were: * Learnt various unconventional cost optimization hacks * Save further by learning techniques from industry experts * How CloudKeeper can help optimize cloud spend * Hear product owners experience with using these hacks * Questions & Answer session with the audience Speakers: 1. Aman Aggarwal - AVP, Cloud & DevOps CloudKeeper AWS Certified Professional with 15+ years of experience. 2. Dipesh Garg - DevOps Lead, upGrad A senior technologist with extensive experience in DevOps, Infrastructure, and Security. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Optimizing Cloud Spends with little or no efforts #### Panel Discussion at FinOps Accelerate TO THE NEW organized **FinOps Accelerate, an AWS FinOps Virtual Conference** , on November 18, 2021 with the main objective of creating a discussion forum around FinOps. The conference was graced by some of the most influential CTOs and IT Influencers from leading companies who provided practical and actionable insights for organizations on the FinOps culture. The panelists for this discussion were **Nausheen Moulana, Chief Technology Officer, Glytec, Narinder Kumar, Co-Founder & COO, TO THE NEW, Jason Shah, Chief Technology Officer, Mediafly & Rick Triana, Senior Manager, Accenture**. They emphasized a holistic view of speed and quality while focusing on resource optimization. The major takeaways from the session were: * Usage optimization & RI Management * Cloud cost optimization techniques * Choosing the right FinOps tools & services * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # 10 Best Practices to reduce your AWS Cost by upto 24% #### A Webinar by Cloud & DevOps Experts Any organization using the AWS Cloud should have a cloud cost management plan in place. It is important to identify the scope of increasing cost efficiencies on AWS and the best time to do that is now. However, finding ways of how to reduce AWS costs may not be that simple. ##### In this webinar, our experts will walk you through: * Most common mistakes that lead to an increased AWS bill * Best practices to run a cost-effective AWS set up * How to make your team accountable for every penny spent on AWS * Automation techniques to reduce the AWS cost management efforts * Understand if your workload has ‘Provision-based’ or ‘Consumption-based’ pricing * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # 2024 Essentials: Tactics to Reduce Cloud Waste As per a recent survey, 38% of organizations experience more than 30% of their cloud spend getting wasted. With the sheer magnitude and the accelerated use of the cloud as a business enabler, Cloud waste is the next big problem companies are looking to combat in 2024 and beyond. Ensure minimum cloud waste and maximum savings this year. In this exclusive on-demand webinar our experts shared top strategies that will have your cloud bills shrinking, not skyrocketing! Our Key Takeaways: * What is cloud waste & why is it the top cause of concern in 2024? * What are the strategies you can use to reduce it? * Solutions that can help you plug cloud waste. * Q&A with FinOps consultants for your specific questions. Speaker: Harsh Agarwal - FinOps Expert, CloudKeeper Expert in optimizing cloud wastage and maximizing savings. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Turn AWS Cost Concerns into Customer Growth Many AWS deals slow down when customers push back on cost. The best account teams know how to turn those objections into expansion opportunities. In this session, AWS and CloudKeeper leaders shared the insights used to drive **31% YoY growth for PPA customers** , reopen stalled conversations, and accelerate cloud adoption. Watch the webinar on-demand to learn how top AWS teams convert cost optimization discussions into long-term customer growth. Who should watch this? This webinar was designed for: 1. AWS Account Managers driving consumption growth 2. AWS Solutions Architects supporting customer expansion 3. AWS Partner Sales Managers managing strategic accounts 4. Sales leaders focused on increasing PPA coverage and pipeline Key insights include: * Reopening stalled or rejected PPAs * Turning optimization requests into expansion opportunities * Accelerating POCs and service adoption * Using SA-as-a-Service programs to support customer growth Featured speakers: 1. 2. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Understand the cloud cost optimization techniques by AWS-certified experts and combat various cost optimization issues like a pro Reducing your AWS bill is hard, reducing it further is harder. The 45-minute webinar unravelled the unconventional hacks to cut down the AWS Bill instantly. We discussed various ways to ensure guaranteed reduction on entire AWS bills. The diverse audience included: 1. Product Companies - CEO, CFO, Head of Finance & Founders 2. Venture Capitalist Firms - Angel Investors 3. Digital-Native Businesses - CTO, CIO & Head of Engineering The major takeaways from the session were: * Learnt various unconventional cost optimization hacks * Save further by learning techniques from industry experts * Hear product owners experience with using these hacks * Questions & Answer session with the audience Speakers: 1. Aman Aggarwal - AVP, Cloud & DevOps CloudKeeper AWS Certified Professional with 15+ years of experience. 2. Ben Rhodes - Program Director, Next Practice A Senior HealthTech Leader with 20+ years of experience. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 08/October/2025 38 minutes Cloud Cost Optimization: From Brake to Accelerator in 2025 Host Praneet Chandra sits down with Stephen J. Barr, Chief Evangelist at CloudFix, to explore how cloud cost optimization can shift from cutting spend to unlocking innovation. Stephen shares why value over savings matters and how automation enables teams to experiment with confidence. +3 26/September/2025 29 minutes AI Cloud Costs: GPU Economics, Unit Pricing & Developer Ownership Host Praneet Chandra sits down with Kartik Gupta, President at Spyne, to unpack the real cost of scaling AI workloads — where every GPU dollar counts. From choosing between managed services and self-hosting to building a culture of Transparency, Visibility & Communication (TVC), Kartik shares how to balance rapid innovation with disciplined cloud spending. +3 03/September/2025 45 minutes Value-Driven FinOps: Moving Past the Cost Reduction Myth Host Praneet Chandra sits down with Ben de Mora — a FinOps leader with experience at GitLab, IBM— for a grounded, real-world look at cloud cost optimization at scale. From the realities of multi-cloud to the cultural challenges of tagging, tooling, and commitments, Ben shares what actually works inside large engineering organizations. +3 14/August/2025 48 minutes From Chaos to Clarity - The FinOps Balancing Act Host Praneet Chandra sits down with Dvir Mizrahi, VP of FinOps at Wiv.AI, for an unfiltered conversation on the balancing act every cloud leader faces today. From scaling cloud costs to AI’s real impact on FinOps, Dvir shares stories and strategies from the frontlines +3 15/July/2025 48 minutes Rethinking Cloud Costs: From Dashboards to Decisions In this episode, +3 01/July/2025 32 minutes Beyond Lift-and-Shift: The Cloud Cost Maturity Playbook In this episode, +3 17/June/2025 46 minutes The Cloud Cost Playbook: Forecasting, FinOps, and Flawed Assumptions In this episode of The Latte on Cloud Costs, we sit down with +3 03/June/2025 50 minutes The FinOps Reboot: AI, Decentralization, and What’s Next In this episode, Praneet Chandra and +3 21/January/2025 23 minutes Navigating team dynamics for success We invited +3 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close What’s New with Cloud Cost Optimization in 2025? A research-backed report built on 500+ cloud environments to uncover trends, inefficiencies, and a new framework to measure cost maturity. 05/September/2025 Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this report based on a survey by Everest Group. 07/June/2024 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Best Practices to Slash Your GCP Spend by Up to 20% Instantly A detailed GCP cost optimization guide that explores the root causes of runaway cloud spend, six quick fixes for immediate cost reduction, and sustainable practices to keep your GCP setup optimized long term. Unlocking 10–25% Savings from Kubernetes Without Slowing Innovation Kubernetes brings speed and scalability but it also introduces hidden inefficiencies. From overprovisioned pods to misconfigured autoscaling, clusters often consume more than they should. The AWS Fitness Plan: 30 Days to a Stronger, Leaner Cloud Learn about our exciting Cloud Fitness Challenge to uncover optimization blindspots, hidden savings & achieve peak performance in just 30 days. A practical guide to AWS EDP Learn how AWS EDP helps businesses save on cloud costs, scale efficiently, and unlock growth. Discover strategies, use cases, and expert insights. The 4 Pillars of Cloud Cost Optimization Gain insights into the four fundamental pillars of an effective cloud cost optimization strategy, and the best practices to maximize your cloud savings. 5 Reasons Why a Comprehensive Cloud Partner is Necessary Discover why partnering with a comprehensive cloud provider is critical for optimizing your cloud strategy. Download our whitepaper to learn how expert guidance, cost efficiency, security, and scalability can transform your business with Azure. The Complete Guide to Cloud Cost Optimization A step-by-step guide to help you take control of your cloud cost, eliminate waste, manage multi-cloud expenses, improve efficiency, and secure sustainable savings. A Customized & Smarter Approach to AWS Well Architected Review Tired of one-size-fits-all Well Architected Reviews? It’s time to opt for a tailored approach with automated reviews, custom recommendations, & implementation support, all at no cost. Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # The 4 Pillars of Cloud Cost Optimization As the world enters the age of Generative AI, which is quoted as the next big thing after the internet, the need for scalable and robust supporting infrastructures has increased. That’s why in 2024, every $8 out of $10 spent on enterprise IT goes to cloud computing. (Source: McKinsey). But here’s the twist: almost 50% of cloud-based businesses struggle to control cloud costs, with an average of 30% of these cloud budgets going to waste. (Source: State of the Cloud Report, 2024) These numbers indicate a heightened importance of robust cloud cost optimization strategies - the foundation of efficient and sustainable cloud operations. This whitepaper takes you through the fundamentals of cloud cost optimization with a 4-pillar analogy - Rate Optimization, Usage Optimization, Cloud Cost Visibility, and CloudOps Augmentation and Support. Here’s what you’ll learn from the Whitepaper * Best practices for cloud rate optimization * Techniques to minimize waste through usage optimization * Challenges to cloud cost visibility and how to tackle them * Our unique approach towards CloudOps to maximize its benefits Grab your copy today and take your first step towards a sustainable cloud cost strategy. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # 5 Reasons Why a Comprehensive Cloud Partner is Necessary Overcoming cloud challenges demands the right tools, technologies, and a trusted, expert partner. This whitepaper explores five key areas where a comprehensive cloud partner is indispensable, utilizing the Continuous Assess, Review, Act (CARA) framework to guide organizations on their cloud journey and drive success. In this whitepaper, we will cover: * Strategizing cloud consulting * Assessing cloud architecture * Seamless cloud optimization * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # The AWS Fitness Plan: 30 Days to a Stronger, Leaner Cloud **Think you’ve nailed Cloud Usage Optimization? Let’s put it to the test.** **In our analysis of 2000+ AWS accounts, we found 97% of teams were still missing critical savings.** They thought their cloud setup was “fully optimized” until we highlighted a six-figure savings gap. You might feel confident that your team is catching every savings opportunity & the AWS setup feels under control. But what if your **“optimized” cloud also has blind spots** —and you don’t even know it? Thus, **we challenge you** to take the **30-day risk-free, no-cost Cloud Fitness Test** to prove our point! Cloud Fitness Challenge is a **step-by-step, time-bound action** plan to identify the optimization blind spots, tune cloud performance, and maximize savings. Think of it as a 30-day fitness plan for your AWS infrastructure. **Bonus:** Complete the challenge & if your AWS bill is over $10K/month, get a $50 Amazon voucher as a thank-you! Download the whitepaper to see how the challenge works, what to expect, and the kind of results you can achieve. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Acing the Cloud Optimization by choosing the right services, pricing & best practices In the fiercely competitive cloud infrastructure services market, Amazon Web Services continues its domination with an overall share of a whopping 32% as of 2021. This means that nearly one-third of the internet runs on AWS. With an unmatched set of 200+ tools and frameworks and the integrations with technologies like AR, VR, Machine Learning and Blockchain, AWS attracts businesses of all shapes and sizes. But from a business perspective, effectively utilizing the ease-of-use, flexibility and the rich set of offerings from AWS depends on selecting the right instance type and pricing models, adopting best practices and continuously monitoring their cloud infrastructure for corrective actions. Thus, a Cloud Optimization Strategy plays a significant role in enabling organizations to make the most out of the cloud. This whitepaper takes you through some of the crucial considerations in * Choosing the Right AWS Service for your Business * Understanding AWS Pricing Principles * How to Select the Ideal Cloud Optimization Solution * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Best Practices to Slash Your GCP Spend by Up to 20% Instantly Is your GCP infrastructure a cost center instead of a growth engine? Many organizations spend heavily on GCP but still overlook cost-optimization opportunities. This whitepaper compiles the common mistakes and cost-saving techniques we've identified while helping customers optimize their Google Cloud environments. In this whitepaper, you’ll discover: * Why GCP costs spiral out of control * Fast remediation moves for instant savings * How to keep your environment optimized after the quick wins * Costly pitfalls most companies make and how to avoid them * How a partner like CloudKeeper can unlock consistent GCP savings Download the whitepaper now and start saving on GCP today! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Best practices to cut down your AWS spend by 5-15% The shift from an on-premise datacenter to AWS Cloud allows companies to scale their business while simultaneously reducing their overall costs. Furthermore, the sheer scale at which AWS operates brings in economies of scale which in turn benefits companies with reduced services pricing. Any organization using the AWS Cloud should have a cloud cost management plan in place. However, finding ways of how to reduce AWS costs may not be that simple. This whitepaper talks about the common mistakes AWS users make in their setup that results in paying more than they need to. It would dive deeper into some short and long-term best practices, as well as some lesser-known facts and quick-fixes, to optimize your AWS spend as per your business-specific needs. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Cloud infrastructure done right with the AWS Well-Architected Framework With growing workloads & data in the cloud, enterprises are running into the challenge of optimization. As of 2021, about 50% of all enterprise-level data in the world was stored in the cloud, as found by data aggregator Statista. IT leaders have also critically prioritized cloud security enhancement, cloud native design adoption, workload adjustment with changing business priorities & cloud costs control. To achieve optimized cloud availability & meet the requirements of organizations, AWS has introduced the AWS Well-Architected Framework that helps organizations build the most secure, high-performing, resilient, and efficient infrastructure possible for their applications. Along with risk reduction, the framework also helps in increasing business value and managing costs. In this whitepaper, you will learn about the Six Pillars of the framework - operational excellence, security, reliability, performance efficiency, cost optimization and sustainability. It will walk you through the design principles of each of these pillars and will also have the best practices for benchmarking against the six pillars. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # A complete guide to Public Cloud Security If you look at every top-performing enterprise around the world, you’ll quickly find they all have one thing in common: They’re on the cloud. By 2018, 96% of business leaders were already leveraging the cloud in some capacity — today, that number hovers even closer to 100%, as reported by CIO Magazine. Public cloud services offer several major benefits, including a reduced need for on-premise hardware, improved scalability, robust security, reliable business continuity, and enhanced resource allocation & capacity planning. However, when making a shift to a hybrid cloud environment, it's all too common for leaders to overlook one major consideration: security. In this whitepaper, we talk about the role of an enterprise, addressing how to protect data when on Public Cloud, as well as a proactive approach to Cloud workload protection. Whether you’re getting started with public cloud security, or are already familiar with security on Cloud, this whitepaper aims to give you an in-depth view of how to go about making your workloads on Cloud more secure. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # A Customized & Smarter Approach to AWS Well Architected Review Are you stuck with traditional one-size-fits-all Well Architected Reviews that fail to consider your company’s specific objectives & maturity level? Those lengthy questionnaires, generic suggestions, & unclear action plans can leave you with more questions than answers. It’s time for a better approach. CloudKeeper, a certified AWS WAR Partner, offers a smarter approach to Well Architected Reviews - all at no cost! Download our whitepaper to understand in detail about: * The limitations of traditional AWS WAR and why it falls short. * CloudKeeper’s tailored WAR approach and its unique value proposition. * Customer-centric engagement model that delivers 10% average savings within the first 90 days. * Proven results & success story of a business that reduced their AWS costs by 25% within a week. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # The Complete Guide to Cloud Cost Optimization Are you overwhelmed by rising cloud expenses and generic cost-cutting strategies that don’t align with your company’s needs or goals? Traditional approaches often provide vague recommendations and lack actionable insights, leaving you unsure about your next steps. It’s time for a more effective solution. CloudKeeper, a leader in cloud cost management, offers an in-depth guide to Cloud Cost Optimization – completely free! Download our comprehensive guide to learn about: * Understanding cloud cost metrics, eliminating cloud waste, and implementing resource optimization strategies. * Strategic pricing model selection, reserved capacity planning, and automation vs. manual optimization. * Multi-cloud cost optimization, data cost management, and ensuring cost visibility and monitoring. * **Well-Architected Review** implementation and effective cost management practices for sustained savings. * A **personalized “Continuous Assess Review Act Checklist”** to understand your own cloud cost visibility and optimization level. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Demystifying AWS Data Transfer Charges Data transfer cost forms a critical component while saving cloud cost. Majority of organizations have data transfer costs anywhere between 10%-15% of their total bill and any cost higher than this must be reviewed in detail. This whitepaper will discuss the different cost levers associated with data transfer charges in the AWS cloud with a closer look at all the scenarios in which these charges are applicable. It will also mention various architectural pitfalls which can lead teams to incur huge data transfer charges and how to avoid them. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Autoscaling doesn’t lead to cost-saving, unless done right Increasing number of organizations are now adopting and migrating to the cloud for a faster time to market, scalability, availability, reachability and to adopt a pay-as-you go- model. To reap all the benefits of cloud computing, organizations use different architectural models (Serverless, Microservices, and Monolithic) to deploy their workloads. The right use of auto-scaling in any of these models can result in efficient use of cloud resources & significant cost savings. This whitepaper will discuss common mistakes that the cloud teams make and best practices that must be followed while implementing auto-scaling on the AWS cloud. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # FinOps: Challenges, Remedies & Ecosystem It is an indisputable fact that Cloud- an emerging technology a decade ago, is now a part of the very fabric of any business in this connected world. Cloud has become a necessity for the survival of businesses and is a key aspect for their digital transformation, both to innovate and maintain a competitive edge. Nevertheless, Cloud introduces a variety of complexity and challenges to traditional IT financial management. For optimum utilization of Cloud infrastructure, companies require the right financial governance, processes, and partnership. In this whitepaper, cloud infrastructure and finance teams will learn more about the discipline of FinOps, understand the value companies can derive from adopting this practice, and the various kinds of FinOps Services providers in the market. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How to maximize the benefits of the AWS Enterprise Discount Program (EDP) Cloud service providers like AWS offer commitment-based pricing programs, with discounted pricing on AWS services in exchange for annual spending or volume commitments. This helps enterprises scale economically and benefit from predictable pricing. However, without the right usage commitments and contracting terms, EDP could lead to wastage, excessive costs, and poor user experiences. It is crucial to strategize EDP agreements early on, to achieve the desired savings. In this whitepaper, we will cover: * The fundamental pricing principles of AWS * Insights into the EDP Program * AWS Discount Programs that Complement EDP Savings * Lesser-known Hacks to Maximize your ROI * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # FinOps Vendor Ecosystem you should know before nailing your Cloud Optimization Strategy Moving workloads to cloud environments offers greater agility, scalability, flexibility and more. But, this also brings in challenges associated with monitoring and tracking cloud resources, increased cloud bills and a lack of clear cost visibility - one of the most prominent concerns for almost all CFOs, CIOs and CTOs. As per ISG’s estimates, cloud spending is predicted to surpass US$350 billion by 2022, and continue to grow to US$500 billion by 2025. Hence, the traditional consumption-based IT services model for cloud budgeting might not be the right approach to follow. Implementing FinOps principles will help in establishing a granular transparency in cloud assets, gaining actionable insights for strategic investments and thereby reducing cloud bills significantly. However, since each FinOps vendor has their own unique capabilities and features, whom would you choose to address the requirements specific to your organization? This white paper sheds light on the dynamics of the FinOps market and gives a comprehensive understanding of the FinOps Vendor Ecosystem that could help you choose the right FinOps Partner and implement an effective Cloud Optimization Strategy. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Maximizing AWS Cost Savings with Serverless Architecture As cloud computing evolves, Serverless Architecture stands out as a potent tool for achieving cost-effective and innovative solutions. In this model, developers can concentrate on building applications, while the cloud provider handles infrastructure provisioning and ensuring availability. One of the major advantages of serverless cloud computing is its cost optimization capabilities. The stateless architecture, auto-scaling features, and specialized pricing models empower engineers to create cost-savvy cloud solutions. This whitepaper provides a comprehensive overview of serverless technology and also explores- * Common use cases * Key benefits of the model * Application fundamentals * Cost-saving strategies and best practices * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Navigating the FinOps Landscape: A Comprehensive Market Analysis This **exclusive whitepaper is based on the survey conducted by the Everest Group** across 450 organizations globally and acts as your guide through the FinOps landscape. It offers detailed insights on Global FinOps statistics, growth trajectory, key drivers & trends, third-party FinOps providers’ offerings, and more. Why Download? * **Strategic Advantage:** Align your strategies with the latest FinOps industry trends, and understand what your competition might be doing right. * **Informed Decision-Making:** Equip yourself with invaluable insights to address cloud cost challenges. * **Future-Proof Your FinOps Strategy:** Anticipate what the market demands and how it's evolving. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Choosing the Right AWS Service to Optimize Your Cloud and Beyond The race to cloud adoption is gaining pace in its ardor. Gartner forecasts end-user spending on public cloud services will reach $482 billion in 2022. The prediction further adds, by 2026, public cloud spending will exceed 45% of all enterprise IT spending, up from less than 17% in 2021. Cloud-based apps are also on the rise and a growing number of workloads are being hosted on the cloud. The increasing adoption of cloud services will increase the need for additional IT infrastructure. Amidst the fervor of cloud adoption, its proponents have realized the problems posed by wasted or mismanaged cloud estate. The wastages, if not contained, offset the gains from cost reduction - a key business driver motivating cloud adoption. Hence, cloud financial management has emerged as vital for cost-effectiveness while maintaining the integrity of the cloud infrastructure. Seasoned practitioners realize the need for FinOps, bringing financial accountability to the variable spend model of cloud, as their organization’s increasing structural complexity - number of teams, workloads, and clouds - fuels cloud usage. AWS has the largest cloud computing market share at 32% and enables you to take control of cost and continuously optimize your IT spending, while building modern, scalable applications to meet your needs. In this whitepaper, learn how you can choose the right AWS service to optimize your cloud spends. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Overcoming Challenges in RI Management through AI-driven Automated Solution Cost efficiency is critical to successful cloud operations in today’s competitive landscape. Organizations strive to optimize their cloud spending while maintaining high-performance levels. However, effectively managing AWS RIs can be a complex and time-consuming task. The dynamic nature of cloud environments, coupled with the frequent changes in workload demands, requires constant monitoring and optimization of RI utilization to maximize cost efficiency. In this white paper, we will cover: * The pain points in RI/SP management * The potential of an automated RI management solution * How CloudKeeper Auto can help maximize AWS savings * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # A practical guide to AWS EDP Struggling to control your cloud costs while scaling your business? AWS Enterprise Discount Program (EDP) is a great opportunity for organizations seeking substantial savings on AWS. However, navigating its complexities can be challenging without the right guidance. That’s where this whitepaper comes in—a comprehensive guide to simplifying your EDP journey and unlocking its full potential. What you’ll discover: * Insights into how EDP helps businesses save while scaling efficiently * Case studies from leading brands leveraging EDP for growth * Key strategies for successful EDP negotiation and implementation * How partner-led EDP/PPA can maximize savings and simplify the process * Practical tools and steps to optimize cloud investments Download now to make your AWS cost-saving journey smarter and easier! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Unlock the Ultimate Guide to FinOps Strategy & Implementation Cloud adoption has become an integral part of the digital transformation of organizations. They look forward to remaining scalable and resilient with changing business priorities. As per a forecast by IDC, the worldwide spending on public cloud services will reach $809 billion by 2025. To control these cloud investments, organizations are turning towards adopting the FinOps culture. To build cloud financial accountability within the organization, one has to understand the guiding principles of FinOps implementation that can help achieve results that last. In this strategic guide explaining the process FinOps implementation, you can understand the following in detail - * What is needed to build the FinOps culture within the organization * The process of implementing FinOps and the best practices for an efficient implementation * How to make your team accountable for every penny spent on AWS * How AWS helps in building the culture of financial accountability within the organization Download this detailed guide to devise your FinOps strategy and the implementation process to build a sustainable FinOps culture within your organization. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Unlocking 10–25% Savings from Kubernetes Without Slowing Innovation If Kubernetes scales automatically, why do cloud bills keep rising? Kubernetes brings speed and scalability but it also introduces hidden inefficiencies. From overprovisioned pods to misconfigured autoscaling, clusters often consume more than they should. This whitepaper breaks down a practical framework to improve Kubernetes efficiency without impacting reliability. What You'll Learn: * Why Kubernetes cost behavior is fundamentally different * Six pillars of cluster efficiency and governance * A 30-day optimization playbook you can act on now * Practical Kubernetes cost optimization case studies from leading organizations Get strategies that engineering and cloud leaders trust to cut costs without compromising velocity. Download the whitepaper now! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Unlocking Cost benefits in the AWS ecosystem As CIOs ramp up investments, the budgets must be allocated wisely keeping in mind the bigger impact it may have should things go wrong. The businesses of tomorrow are in a digital transformation race to move faster, innovate more, and sharpen their competitive edge. The cloud makes this happen - enabling businesses to scale resources up or down depending on the changing requirements in real time. The shift from an on-premise datacenter to a hyperscaler like AWS cloud allows companies to scale their business while simultaneously reducing their overall costs, replacing up-front IT infrastructure purchases with the more efficient pay-as-you-go model. The sheer scale at which AWS operates brings in economies of scale which in turn benefits companies with reduced services pricing. In this whitepaper, learn how to unlock true cost benefits for your AWS infrastructure. Cloud finance management is about more than just driving down costs. It is about how to embrace the agility, innovation, and scale of AWS to maximize the value that the Cloud provides your business. Download your copy today! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close FinOps is an operational framework and cultural practice In this insightful interview, Dieter Matzion, Sr. Cloud Governance Engineer at Roku, discusses cloud cost strategies, challenges, and real-world FinOps experiences. 04/April/2024 Artificial Intelligence & large language models might shape FinOps in 2024 Dieter Matzion, Sr. Cloud Governance Engineer at Roku, talks about how to tackle your FinOps challenges and why keeping your cloud continuously optimized is vital. 08/February/2024 FinOps is not limited to tools; it extends to organizational support Ermanno Attardo, CPO & Head of AI at Cypher AI, talks about creating a successful FinOps strategy while moving away from the traditional approach of cost reductions. 06/February/2024 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 08 Feb, 2024 | 4 Min read Artificial Intelligence & large language models might shape FinOps in 2024 Interview with Dieter Matzion FinOps Spotlight: An interview series, Chapter 2 FOUND THIS USEFUL? SHARE IT Dieter Matzion Sr. Cloud Governance Engineer, Roku Inc. The cloud computing landscape has been changing over the years & consequently, the concept of FinOps has also been evolving. New technology & innovations are being added to the existing FinOps ecosystem. There are doubts about how best one can implement FinOps in their organization. In our **second chapter of FinOps Spotlight, we talk to Dieter Matzion** , Sr. Cloud Governance Engineer at Roku, about some quick takeaways for someone embarking on their FinOps journey. Dieter Matzion is a member of Roku's Cloud Technology and Infrastructure team, supporting Cloud FinOps across AWS, GCP, and Azure. He has over 30 years of technical expertise working with companies like Google, Netflix, and Intuit. In his line of work, he has supported the AWS cloud cost optimization program, the development of Netflix's rhythm and active management of AWS, and capacity planning and resource provisioning for the Google Cloud offering.He also developed demand-planning models and automation tools for capacity management at Google. Dieter holds an M.S. in computer science. Read his interview and learn more about how to tackle your FinOps challenges from Dieter himself. ## **Q1. What are your suggestions for someone who is beginning their FinOps journey?** For someone new to the FinOps journey, get FinOps Practitioner Certificate from the FinOps Foundation. This step will ensure that people know your skills. ## **Q2. Can you highlight key strategies or shifts in mindset that you believe have been instrumental in FinOps evolution?** Looking around today, we see that most IT is still in data centers. As more organizations migrate to the cloud, we will see a constant stream of people new to FinOps. On the other hand, we see more FinOps experts advancing with technology and automation. ## **Q3. What features should one look for while selecting from the available FinOps tools in the market?** Prepare a list of all the FinOps requirements for your organization. Then, you look at multiple vendors for each requirement and select the best fit for your organization. > _**Without executives understanding, many of your FinOps activities will be performed in a void.**_ ## **Q4. What, in your opinion, is the key to successfully implementing cloud FinOps in a business?** Executive support within your organization is a must. Without executives understanding that the cloud needs to be continuously optimized, many of your FinOps activities will be performed in a void. ## **Q5. Are underutilized resources also a challenge for your business? How do you tackle it?** They are not a challenge for us. When I started, we had less than 1% of cloud waste. However, we see cloud waste of up to 30% across industries. To address this issue, ask your cloud account management team for a waste report to get an initial idea of where you are with cloud waste. You can then build a few waste sensors and small scripts that collect waste data and expand from there. ## **Q6. What are the most common things that engineers overlook in the context of cloud cost optimization?** The data transfer charges are at the top. Following that are the production configurations used in Dev, QA, & Staging environments, which overprovision these further. ## **Q7. Could you suggest low-hanging fruits for cloud cost optimizations and Finops?** For immediate cloud cost savings, businesses can centrally manage the Savings Plans (AWS), Reserved Instances (AWS), Committed Use Discounts (GCP), and Reservations (Azure). ## **Q8. What are the KPIs you track to keep a check on the Cloud FinOps health?** The KPIs we track are Cost per vCPU per hour, Cost per GB stored, and Cost per Streaming Hour. ## **Q9. What are the new FinOps trends you are most excited to see in 2024?** The FinOps trend of 2024 that I am looking forward to is how artificial intelligence and large language models will change how we do FinOps. _At CloudKeeper, we share knowledge, best practices, and lessons learned to empower our readers to make informed decisions, overcome challenges, and achieve their cloud goals._ _Focusing on practical strategies and real-world insights from FinOps practitioners & influencers, our interview series explores the evolving role of FinOps in today's cloud-centric ecosystem and helps our audience navigate changes and adapt to evolving cloud landscapes proactively._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 06 Feb, 2024 | 4 Min read FinOps is not limited to tools; it extends to organizational support Interview with Ermanno Ettardo FinOps Spotlight: An interview series, Chapter 1 FOUND THIS USEFUL? SHARE IT Ermanno Ettardo CPO & Head of AI, Cypher AI Did you know that lacking organizational buy-in and well-defined roles, can turn even the best reports & recommendations from FinOps tools useless? In chapter one of our interview series bringing the FinOps perspectives from across the industry, Ermanno Attardo, CPO & Head of AI at Cypher AI, talks about creating a successful FinOps strategy while moving away from the traditional approach of cost reductions. Apart from leading the product at Cypher AI, he is also an Ambassador of FinOps Foundations and a FinOps Certified Working Group Lead with 15+ years in tech. He holds several AWS certifications, including DevOps Professional and Solutions Architect. An engineering expert in product and finance, he excels in UX, AI, IoT, and 3D programming. Ermano helps teams multiply output through focused strategies, values diverse perspectives, and fosters critical thinking. Read the entire interview & know the intricacies of cloud cost management from Ermanno himself. ## **Q1. What are your suggestions for someone who is beginning their FinOps journey?** Ensure to have full executive support on the work that needs to be done. Then, you should propagate this buy-in to the team of executioners from that stage onwards. To strengthen it further, the certification of FinOps Practitioner from FinOps Foundation would be another pillar. > _**FinOps is not about saving money. FinOps is about making money.**_ ## **Q2. Can you highlight key strategies or shifts in mindset that you believe have been instrumental in FinOps evolution?** It's best summarized in the sentence, "FinOps is not about saving money. FinOps is about making money." However, many companies (and vendors) equivocate FinOps despite the warnings. The framework will evolve again to gain further clarity and push in the right direction. The strategy is to consider the owners of the organizations (who may be different people than the executives who run them) and their interests. Any FinOps operation must reflect this consideration. ## **Q3. What features should one look for while selecting from the available FinOps tools in the market?** Most platforms & tools are great at visualizing and giving recommendations but it cannot be limited to these. It's also about taking action. If you lack organizational buy-in and well-defined roles, even the best reports & recommendations might not be very useful. ## **Q4. What, in your opinion, is the key to successfully implementing cloud FinOps in a business?** Organizational culture is a distillation of what the leadership considers a priority. If this includes FinOps practice, everyone will get on the same page. Only then you can define a clear RACI (responsible, accountable, consulted, and informed). A group differs from a team because of well-defined roles. ## **Q5. Are underutilized resources also a challenge for any/your business? How do you tackle it?** If you plan, everything will be under control & underutilized resources will not be a challenge really. You can keep the ‘Drift’ in check with proper planning and operationalization with automation. ## **Q6. What are the most common things that engineers overlook in the context of cloud cost optimization?** It is the opportunity cost. Sometimes, spending time to fix something that is not worth it will cost more man hours. That same effort can go towards increasing the revenue. Leadership should give engineers clear guidance on what guardrails the decisions should be based on to avoid any wastage of engineers’ man hours. ## **Q7. Could you suggest low-hanging fruits for cloud cost optimizations and FinOps?** The only suggestion I have is to move away from seeking cost reduction and create new products & revenue streams. ## **Q8. What are the KPIs you track to keep a check on the Cloud FinOps health?** Create KPIs that make sense for a product and the value that the business achieves. For example, the cost to serve one customer "unit" and revenue per same unit. All KPIs, including the technical ones, should be driven by business value, or you're wasting time. ## **Q9. What are the new FinOps trends you are most excited to see in 2024?** Sustainability. Aside from the greenwashing fad, there's a legitimate case. We are running out of certain materials, which is limited on Earth. For example, lithium, which is used to make batteries, or gold, which has become more convenient to salvage from old phones than it is to mine. As the FinOps Foundation expands on sustainability, electronics used in cloud hardware will eventually be considered part of a circular economy or sustainability. This is not a green fad but a business consideration. We need more building materials for electronics. _At CloudKeeper, we share knowledge, best practices, and lessons learned to empower our readers to make informed decisions, overcome challenges, and achieve their cloud goals._ _Focusing on practical strategies and real-world insights from FinOps practitioners & influencers, our interview series explores the evolving role of FinOps in today's cloud-centric ecosystem and helps our audience navigate changes and adapt to evolving cloud landscapes proactively._ Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 04 Apr, 2024 | 1 Min read FinOps is an operational framework and cultural practice Interview with Dieter Matzion FinOps Spotlight: An interview series, Chapter 3 FOUND THIS USEFUL? SHARE IT Dieter Matzion Sr. Cloud Governance Engineer, Roku Inc. Welcome to FinOps Spotlight, an exclusive interview series where we dive deep into the world of FinOps by engaging with industry experts and thought leaders. In this dynamic series, we aim to uncover the latest trends, best practices, and insights shaping the rapidly evolving landscape of FinOps. In this episode, we invited Dieter Matzion. He is a member of Roku's Cloud Technology and Infrastructure team, supporting Cloud FinOps across AWS, GCP, and Azure. He has over 30 years of technical expertise working with companies like Google, Netflix, and Intuit. Through FinOps Spotlight, we had the privilege of sitting with Dieter to explore the challenges and strategies driving innovation in cloud financial management. From cost optimization techniques to AI in FinOps and beyond, this interview aims to provide valuable perspectives and actionable advice for organizations navigating the complexities of cloud economics. Watch the full video interview for a more comprehensive view of the discussion and gain additional insights. Be the first to know the latest FinOps insights and news! ### You may also like 99% of companies saved up to 15% monthly with this plan & achieved peak performance. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close From Concept to Completion: Customized action plan to achieve your goal faster with ISV Accelerate! * Initial Assessments and Migrations * Expert guidance to evaluate architecture readiness * Migration planning, scheduling, and implementation * Technical Guidance and Support * Workload and Application Modernization * Infrastructure Audits and Technical Reviews * Seamless Marketplace Integration * Complete action plan for marketplace integrations * Guidance and recommendations for best practices * GTM Enablement and Scaling * Strategic Insights and Resources * Sales Enablement and Industry Partnerships AWS Foundational Technical Reviews for SaaS Products As an AWS Premier Consulting Partner, CloudKeeper helps SaaS companies navigate their AWS architecture complexities with Foundational Technical Reviews (FTR). * Well-Architected Reviews * Automated Issue Discovery and Resolution * Access to Partner Benefits including AWS Funding * “Qualified Software” badge and AWS Partner Solutions Listing We goes above & beyond to fuel your long-term growth on the cloud ## Proactive Support & Consulting Our team of certified experts address any challenge & provide ongoing support and guidance. ## Dedicated Account Management Receive personalized attention and support from a dedicated manager committed to your success. ## Cloud Cost Visibility Get free access to a comprehensive cloud visibility platform for granular insights & informed decision-making. ## Well-Architected Reviews Our cloud-certified experts assess the infrastructure against the latest cloud best practices and frameworks. Your one-stop destination for Cloud Cost Optimization * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud. * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure. **Related Resources** * Fumbles in FinOps Adoption and How to Avoid Them Watch this exclusive panel discussion where our industry experts talk about the common mistakes organizations make in their FinOps adoption journey. On-Demand Webinars * The Growing Need for Multi-Cloud FinOps Solutions to Reduce Cloud Costs Learn key strategies for multi-cloud cost management and discover how FinOps can help you achieve significant savings. Blog * Top Cloud FinOps KPIs you must measure to drive success: A Complete Guide Explore essential Cloud FinOps KPIs that supercharge your cloud management. Achieve optimized cloud costs, improved visibility, and seamless governance. Blog Frequently Asked **Questions** * ### Arrow 1.What is the ISV Accelerate Program? Q1. What is the ISV Accelerate Program? The ISV Accelerate Program is a global co-sell initiative designed to help Independent Software Vendors (ISVs), offering solutions that run on or integrate with leading cloud platforms. It empowers Independent ISVs to expand their reach, optimize their offerings, and drive sales through cloud marketplaces. * ### Arrow 2. What are the benefits of the CloudKeeper ISV Accelerate Program? Q2. What are the benefits of the CloudKeeper ISV Accelerate Program? The CloudKeeper ISV Accelerate Program is designed to help Independent Software Vendors (ISVs), SaaS providers, and software-driven businesses expand their global reach, optimize their offerings, and drive sales through cloud marketplaces. This program offers a range of benefits, including- * Strategic & technical guidance * Foundational Technical Reviews * Seamless Marketplace integration * CPPO Partnerships, * GTM Enablement and Scaling * ### Arrow 3.Is the CloudKeeper ISV Accelerate Program applicable to all cloud platforms? Q3. Is the CloudKeeper ISV Accelerate Program applicable to all cloud platforms? Our ISV Accelerate program is for all major cloud providers, including AWS and Google Cloud Platform (GCP). * ### Arrow 4.Can the ISV Accelerate Program help me scale my SaaS product globally? Q4. Can the ISV Accelerate Program help me scale my SaaS product globally? Yes, the ISV Accelerate Program is designed to support the global scaling of your SaaS product through co-sell opportunities. This significantly expands your potential customer base across the globe. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Trusted by 400+ Global Customers ‹› The Major Kubernetes Challenges that Hold you Back * Over/under-provisioned resources at the node, pod, and volume level. * DevOps inefficiencies from manual scaling and performance tuning. * Limited cost visibility across workloads, namespaces, & clusters. * Security & compliance risks from unmanaged access and outdated components. * Blind spots due to missing metrics and monitoring tools. * Managing tools & integration in Kubernetes can be overwhelming. The CloudKeeper Approach: **Expert-led Kubernetes services + Powerful Toolkit** * **** * **Right-size resources across nodes, pods, and volumes.** * **Automate performance tuning to reduce DevOps effort.** * **Balance performance with cost using real-time insights.** * **** * **Break down costs by workload, namespace, and labels.** * **Identify key spend drivers and inefficiencies.** * **Use historical trends for smarter resource planning.** * **** * **Designated and certified cloud expert for 24*7 personalized support.** * **Well-Architected Reviews and cloud cost audits.** * **Cloud Architectural consulting and migration support.** Our 3-Step **Kubernetes Optimization Framework** **We use a 3-phase model to drive ongoing Kubernetes optimization and long-term, sustained benefits.** * **1. Audit Your Kubernetes Footprint** **With read-only access, we conduct a thorough analysis of your setup, versions, scaling, and workloads to gather critical metrics and identify optimization potential.** * **** * **2. Tune for Performance & Efficiency** **Based on our findings, we provide data-driven recommendations and implement best practices for cost, performance, reliability, and security.** * **3. Measure Results & Refine** **We continuously monitor the impact of changes, analyze results, and refine strategies to ensure your Kubernetes environment always performs at its best.** Kubernetes Cost Optimization Built for Smarter Decisions * **CPU & Memory Cost Overview** **Gain visibility into CPU and memory usage across nodes and pods to rightsize workloads and reduce waste.** **01** **** **** **** * **In-Depth Cost Analysis** **Drill down into costs by cluster, namespace, label, or team to uncover usage patterns and optimization opportunities.** **02** **** **** **** * **Proactive Alerts & Recommendations** **Stay ahead with proactive alerts for budget breaches, anomalies, and inefficiencies - plus tailored recommendations to fix them.** **03** **** **** **** * **Account-Wise Cost Breakdown** **View granular cost distribution across different accounts to identify high spenders and optimize resource allocation.** **04** **** **** **** **** **** **We Work Across** * **Amazon EKS** * **Google Kubernetes Engine** * **Self-hosted (on-prem or hybrid)** Ready to Optimize Your Kubernetes at Scale? Whether you're just getting started or already running production clusters, CloudKeeper helps you achieve better performance, more control, and a lot of savings. Frequently Asked **Questions** * ### Arrow 1.What is Kubernetes? Q1. What is Kubernetes? Kubernetes (K8s) is an open-source container orchestration platform designed to automate the deployment, scaling, and management of containerized applications. **High-Level Kubernetes Architecture** * **Control Plane** : The brain of Kubernetes, consisting of components like API Server, etcd (distributed storage), Scheduler, and Controller Manager. * **Nodes** : Worker machines that run the containerized applications, each containing a Kubelet (node agent), container runtime (like Docker), and kube-proxy for networking. * **Pods** : The smallest deployable units in Kubernetes, consisting of one or more containers that share storage, network, and a specification on how to run. * ### Arrow 2.What is Kubernetes used for? Q2. What is Kubernetes used for? Kubernetes is used to **automate the deployment, scaling, and management** of containerized applications. Instead of managing each container manually, Kubernetes helps teams. * Run applications reliably across environments. * Scale up or down automatically based on demand. * Ensure high availability and fault tolerance. * Optimize infrastructure usage to reduce waste and cost. * ### Arrow 3.Why do companies need Kubernetes management services? Q3. Why do companies need Kubernetes management services? Managing Kubernetes at scale is complex. Companies often struggle with configuration, resource optimization, cost tracking, and ongoing maintenance. Expert-led Kubernetes management helps streamline operations, reduce DevOps burden, and avoid performance or cost issues. * ### Arrow 4.What is Kubernetes optimization, and how does it help? Q4. What is Kubernetes optimization, and how does it help? Kubernetes optimization involves right-sizing workloads, fine-tuning autoscaling policies, improving observability, and controlling costs. It ensures your clusters are efficient, high-performing, and cost-effective, without sacrificing reliability. * ### Arrow 5.Do you support both cloud-managed and self-hosted Kubernetes? Q5. Do you support both cloud-managed and self-hosted Kubernetes? Yes. CloudKeeper supports all major Kubernetes environments, including**AWS EKS, GCP GKE, and self-hosted clusters** , offering consistent optimization and cost visibility across all platforms. * ### Arrow 6.What access does CloudKeeper need to start the optimization process? Q6. What access does CloudKeeper need to start the optimization process? We only require **read-only access** to your Kubernetes environment during the assessment phase. This ensures a secure and non-intrusive review of your cluster setup, workloads, and configurations. * ### Arrow 7.How often should Kubernetes optimization be performed? Q7. How often should Kubernetes optimization be performed? We recommend running a full optimization cycle every **3 to 6 months**. This ensures that changes in workload patterns, scale, or cloud pricing are regularly addressed to maintain cost efficiency. * ### Arrow 8. Can I get customized cost dashboards for my teams or business units? Q8. Can I get customized cost dashboards for my teams or business units? Yes. CloudKeeper creates**custom cost dashboards** segmented by **namespace, label, cluster, or team** , so you can track spending across different departments or projects with clarity. * ### Arrow 9.What makes CloudKeeper’s Kubernetes services different? Q9. What makes CloudKeeper’s Kubernetes services different? Unlike generic MSPs, CloudKeeper combines deep Kubernetes expertise with a **proprietary cost optimization platform** , tailored dashboards,and a structured 3-step framework (Assess → Optimize → Review) for ongoing efficiency and performance gains. * ### Arrow 10.What is the difference between Kubernetes and Docker? Q10. What is the difference between Kubernetes and Docker? **Docker** is a platform used to create and run containers—lightweight, portable units that package applications and their dependencies. **Kubernetes** , on the other hand, is a system that manages and orchestrates those containers across multiple machines. * ### Arrow 11.How to use Kubernetes in AWS? Q11. How to use Kubernetes in AWS? You can run Kubernetes in AWS in two ways: 1. **Self-managed** on EC2 instances. 2. **Managed service** using Amazon EKS, which handles setup and scaling for you. * ### Arrow 12.How to use Kubernetes in Google Cloud? Q12. How to use Kubernetes in Google Cloud? * **Self-managed on Compute Engine instances:** You set up and manage Kubernetes clusters yourself on virtual machines. * **Managed service using Google Kubernetes Engine (GKE):** GKE automates cluster provisioning, upgrades, scaling, and security, making it easier to run Kubernetes at scale. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 06 Apr, 2026 CloudKeeper Achieves AWS AI Services Competency, Reinforcing Its Role In Scalable AI Adoption 10 Mar, 2026 CloudKeeper Certified as a Great Place to Work for the Second Consecutive Year 19 Feb, 2026 CloudKeeper named Authorized Anthropic Reseller 11 Feb, 2026 CloudKeeper Launches LensGPT, Agentic FinOps Consultant combining Multiple AI Tools 15 Jan, 2026 CloudKeeper Earns #1 Position in G2 Winter 2026 Report for Cloud Cost Management Worldwide 06 Jan, 2026 CloudKeeper Accelerates Global Momentum in 2025 with New Leadership and New Platform Suite 24 Dec, 2025 CloudKeeper appoints former AWS and Google Cloud leader Deepak Singh as Senior Advisor 18 Dec, 2025 CloudKeeper Appoints Gaurav Barman as Chief Revenue Officer (CRO) for India 12 Dec, 2025 CloudKeeper named a Major Contender in Everest Group FinOps Cost Management Products PEAK Matrix® Assessment 2025 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 04 Jun, 2026 As cloud bills surge, CFOs are stepping in to drive AI-led decisions Deepak Mittal, CEO, CloudKeeper, shares his perspective on why cloud cost optimization now requires tighter alignment between finance and engineering, as AI adoption increases. 29 May, 2026 The real infrastructure challenge behind generative AI adoption Aman Aggarwal, COO at CloudKeeper, explores how organizations can approach AI-driven cloud cost management with better observability, workload-aware optimization, and continuous governance. 21 May, 2026 The Hidden Cost of AI Adoption: Why Most Enterprises Are Flying Blind on Cloud Spend In this article, Naman explores how rapid AI adoption is driving hidden cloud costs across enterprises and why organizations need stronger FinOps, governance, and cloud cost visibility to scale AI sustainably. 29 Apr, 2026 Rethinking Cloud Cost Governance in the Age of AI Sanjeev Mittal, CPTO, CloudKeeper, shares how the AI-led transition is playing out across FinOps, from multi-cloud optimization and real-time decisioning. 23 Apr, 2026 Why Cloud Efficiency Is Emerging as the Next Profit Lever for India Inc. Gaurav Barman, CRO, CloudKeeper, explores cloud cost optimization, AI-driven workloads, and why cloud efficiency is key to margins for Indian enterprises. 02 Apr, 2026 How AI-Powered Optimization Can Define The Next Phase Of Cloud And AI Maturity Deepak Mittal explains how AI is reshaping cloud cost dynamics and why intelligent optimization is critical for managing AI-driven cloud spend. 23 Mar, 2026 Agentic AI in FinOps: LensGPT reimagining cloud cost visibility and optimization This article explores how conversational and agentic AI is transforming data interaction and cloud cost management through intelligent, real-time insights. 16 Mar, 2026 Cloud Infrastructure in the AI Era: Managing Performance Without Compromising Margins Sanjeev Mittal, CPTO, CloudKeeper, explains how inference and agentic workloads are driving AI cloud costs, and what organisations must change in their cloud strategy. 12 Mar, 2026 AI Workloads Are Shaping FinOps Priorities: Redefining Cloud Economics in 2026 Deepak Mittal, CEO, CloudKeeper, explores how AI is transforming cloud economics, why AI workloads create cost volatility, and how enterprises can manage AI-driven cloud spending. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 23 Mar, 2026 | 6 Min read # Agentic AI in FinOps: LensGPT reimagining cloud cost visibility and optimization Magazine Contributor Conversational and agentic AI is transforming how organizations interact with data and make decisions. These intelligent systems can reason, plan, and respond to queries in natural language, creating new possibilities and new challenges for IT and finance teams. This evolution parallels a broader shift in how people seek information: AI-powered search and conversational interfaces are rapidly altering user behavior and reducing reliance on traditional keyword-based search engines. For example, This rise of conversational AI has also changed how people interact with technology. Users now expect to ask questions in natural language and receive direct, contextual answers rather than navigate complex dashboards or query systems. This trend is also beginning to reshape cloud cost visibility. . Instead of relying solely on static reports and historical data, teams are starting to use AI-driven systems to interpret spending patterns, identify anomalies, and surface optimization opportunities. The goal is continuous, intelligent decision support. ## Rethinking cloud cost management For years, As cloud architectures become increasingly integrated with AI-driven workloads, these traditional methods fall further behind. These services operate continuously, scale dynamically, and generate cost patterns that are not always transparent through static reporting. FinOps teams are now expected to interpret complex relationships between these workloads, consumption trends, and business outcomes. LensGPT changes that rhythm. Users can ask simple questions in natural language and get instant, context-aware responses. It applies multi-step reasoning to identify cost drivers, linking spending patterns to actual cloud infrastructure: services, regions, accounts, and environments are considered together rather than in isolation. The platform delivers responses that combine clarity with guidance, helping teams move from understanding spend to taking action. “AI has changed how people look for information. Large Language Models (LLMs) have made it natural to ask questions and expect direct answers,” said Deepak Mittal, CEO, CloudKeeper. “LensGPT brings that experience to FinOps. Instead of spending time assembling reports, teams can ask a question and get a clear response, along with guidance on what to do next.” The design also reflects a deep understanding of operational reality: cloud costs rarely arise from a single decision. A spike can stem from overlapping services, experimental deployments, or configuration choices made weeks earlier. LensGPT traces these patterns, surfacing actionable insights without requiring users to navigate layers of raw data. ## Designed for cross-functional cloud teams LensGPT is built to support the wide range of stakeholders involved in cloud financial management. While every organization structures responsibilities differently, the platform adapts to multiple roles across finance, engineering, operations, and product. For example, a Chief Financial Officer may use it to understand cost drivers, budget trends, and overall financial impact. An Engineering Manager might focus on workload efficiency and optimization opportunities. A FinOps Analyst can accelerate deep cost investigations, while a Product Owner may explore how infrastructure spending aligns with product growth and usage patterns. Rather than delivering generic dashboards, LensGPT provides context-aware insights tailored to the questions each role is trying to answer. This flexibility enables organizations to extend intelligent cost visibility across teams – while keeping decision-making structured and aligned. ## Access control designed for multi-team governance LensGPT is built with role-based access controls, ensuring that data visibility matches responsibility. Finance teams, engineering teams, and leadership can all access the insights they need without risking governance or security. Encryption and compliance features are integrated, making the platform suitable for complex, multi-team operations. Agentic AI is often discussed in theoretical terms, but LensGPT applies it practically. In contrast to traditional conversational tools that simply retrieve information, LensGPT is designed to reason across datasets and suggest next steps. It helps explain why it is happening and what actions can be taken to address it. This marks a shift from passive reporting to active, AI-assisted decision-making. “Agentic AI represents a step ahead from generating responses to enabling guided decision-making,” said Sanjeev Mittal, Chief Product and Technology Officer, CloudKeeper. “At CloudKeeper, we’re investing deeply in applied AI through our AI Center of Excellence. LensGPT is one outcome of that effort, with more AI-powered solutions in development to address real-world cloud operations challenges.” LensGPT connects existing processes. It is designed to turn insight into action faster, reducing the friction of traditional cloud cost workflows. ## Scaling without losing control As organizations scale AI and GenAI initiatives, keeping cloud costs under control is getting harder. AI workloads bring dynamic usage patterns, heavy compute requirements, and pricing structures that aren’t always straightforward. In this environment, basic visibility isn’t enough. Cloud teams need context-aware insights and practical recommendations that help them act before costs spiral. LensGPT is designed to address this challenge. Instead of jumping between dashboards, filters, and exports, teams receive actionable cost insights, suggested optimization steps, and clear reasoning that explains what’s happening and what to do next. LensGPT fits naturally into CloudKeeper’s broader All-in-One FinOps Platform Suite – a comprehensive mix of visibility tools, optimization capabilities, and ongoing expert support that helps organizations manage cloud spend with confidence and precision. For companies operating across multi-cloud environments, LensGPT simplifies complexity without sacrificing control. It translates detailed cost data into clear next steps while maintaining role-based governance and security – helping teams move from questions to decisions faster. CloudKeeper has built its reputation by delivering measurable cloud cost optimization for more than 400 organizations, driving average savings of 20 percent based on its customer data. The company is uniquely positioned as an end-to-end cloud cost optimization partner which combines platforms, expertise, and structured FinOps execution. With LensGPT, that foundation now extends into a conversational, reasoning-driven experience aligned with how modern teams interact with intelligent systems. For teams seeking to manage cloud costs with precision and confidence, and for those scaling AI initiatives without clear financial guardrails, CloudKeepeer’s LensGPT is a new point of clarity amid the noise. The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 28 Oct, 2025 | 5 Min read # AI in the Cloud: Cost-Saving Game-Changer or Overhyped? Deepak Mittal Founder and CEO Like in any other Industry, AI is considered the next big thing in cloud computing too, which is why Cloud providers are baking AI into their cost tools. At AWS re:Invent 2024, Amazon unveiled a host of AI-based features - updates to Cost Explorer, better commitment analyzers, and consolidated savings recommendations. In addition, they also launched features to reduce operational costs in generative AI workloads Google Cloud is pushing AI cost recommendations too. Their Cloud “Cost Management” tools include AI-powered cost anomaly detection and “intelligent recommendations” based on usage patterns. In the Azure has also begun weaving AI into cost governance. They talk about using Azure Machine Learning models to forecast spending, automate rightsizing, and tie predictions to policies. Their Cost Management updates for mid-2025 include better logging, filtering of ingestion costs, and support for tighter access to cost data. All these announcements suggest AI in cost-optimization is a hot frontier. But we’ve seen cycles of hype before - DeFi, NFTs, blockchain for everything. So the real question: will AI in the cloud deliver measurable cost savings in real systems or will it become just another buzzword? ## **What AI can bring to cost control** Here are some real ways AI helps cut cloud costs. No, these aren’t possibilities or promises - these are effective levers in many systems. **Predictive scaling & load forecasting** Instead of fixed rules (“if CPU > 70%, spin up”), AI models can forecast load a few minutes or hours ahead. Then you scale resources proactively. You avoid overprovisioning. You avoid sudden spikes. Using usage data, you match capacity more closely to demand. In fact, academic work shows that reinforcement-learning based resource allocation in hybrid clouds can reduce costs by 25-35% compared to static rules. **Anomaly detection & cost guards** AI can **Rightsizing & instance recommendations** AI tools analyze historical usage and suggest smaller or more appropriate instance types. They also suggest when to move workloads into reserved instances, spot instances, or savings plans. These suggestions can be automated or presented to engineers for review. **Automation & continuous tuning** A key shift is from “recommend and review” to “automate changes.” Some platforms continuously adjust parameters (CPU, memory, autoscaling limits) without human input. That keeps waste low. Cloud optimization vendor claims suggest users find 30–50% cost savings using such autonomous methods. **Usage optimization platforms** AI-based usage optimizer works by collecting usage data across your cloud assets, building models, and then ## **Where AI may fall short or be overhyped** While AI in the cloud has genuine benefits, there are risks and gaps. It’s not a silver bullet. **High cost & complexity of AI itself** Running AI models, training them, maintaining them - all incur costs. **Lack of measurable ROI in many cases** Many firms adopt AI tools, but can’t tie savings to a clear gain. Sometimes, AI suggestions aren’t adopted. Or they conflict with operational priorities (latency, availability). If you can’t track ROI, you risk spending more on optimization than you recover. **Integration & data readiness issues** AI tools need high-quality data: usage logs, timestamps, resource metadata. In many orgs, this data is fragmented, inconsistent, delayed, or missing. Without good data, the insights are weak. Also, **Overtrust & “black box” risk** Engineers may not accept opaque AI suggestions. If an AI optimizer scales down a service and something breaks, trust erodes. You need explainability, safety checks, overrides. AI errors or mispredictions are possible in spikes, attacks, or unmodeled workloads. **One-size-fits-all is dangerous** Every workload is different. What works for batch processing won’t work for real-time apps. Some AI tools promise universal optimizations; in truth, you must tune per workload. Also, some “AI” cost tools are just heuristic rule engines dressed as models - they may underdeliver. ## **What to watch out for if you adopt AI in the cloud** When adopting Monitoring ROI continuously is another essential aspect. Track metrics like cost saved, performance impact, and errors prevented to ensure the AI is delivering tangible benefits. As workloads evolve, models must be updated and retrained to stay effective. Guardrails are also important - don’t let AI operate without limits or oversight. Finally, embed a ## **Necessary, but use carefully** AI in the cloud is definitely not just hype or a passing trend - it is becoming essential. But like any technology that has caused disruptions used properly. If your AI tool is well built, data mature, processes solid, then you likely will see savings, better allocation, more agility. But beware: AI is not magic. It carries cost, complexity, and risks. It won’t replace good architecture, good engineers, or a culture that respects cost. In short: AI is necessary and can help - but only if you use it in the right way. The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 12 Mar, 2026 | 4 Min read # AI Workloads Are Shaping FinOps Priorities: Redefining Cloud Economics in 2026 Deepak Mittal Founder and CEO Almost every CXO I have spoken to this year shares a similar story. An AI initiative begins with one team, one use case and a clearly defined budget. It looks structured and manageable. Then other teams get interested. More models are deployed. More experiments are run. Infrastructure expands quietly in the background. Before long, the AI footprint spreads across the organization and the cloud bill grows faster than anyone expected. No one makes a single bad decision. Many small decisions get made across teams. In AI, that is enough to create financial complexity. In 2026, your cloud bill has become the clearest indicator of how disciplined your AI strategy really is. ### **The rules of cloud economics have changed** For years, cloud cost management followed a stable model. Companies tracked compute, storage and networking. They AI workloads have changed this pattern. AI model training runs create sudden bursts of GPU intensive spend. Inference demand changes based on user behavior rather than engineering plans. When your AI product succeeds and usage grows, your infrastructure cost grows alongside it. This creates a direct link between product success and cost volatility. At the same time, AI workloads cut across data science teams, ML engineers, product owners and finance. Shared infrastructure with distributed ownership makes cost visibility far more complex. Traditional FinOps practices were not built for this level of dynamic demand. ### **From 31% to 98% in a whim** The scale of this shift is reflected in the data. Just two years ago, only 31 percent of FinOps teams were actively managing AI spend. Today that number stands at 98 percent. According to the latest State of FinOps report published by the FinOps Foundation, This was not a gradual increase. AI spend expanded quickly and organizations had to respond quickly. Another important trend is that many enterprises are now being asked to self fund their AI initiatives through Cloud economics has therefore moved from being a technical function to a leadership level discussion. The same report highlights that in organizations where FinOps reports closer to the C suite, influence over technology decisions increases by two to four times. When cloud spend becomes a boardroom conversation, infrastructure decisions improve. ### **What leading organizations are doing differently?** Companies that are handling AI driven cloud growth well have updated their approach in four key areas. **1. Smarter capacity commitments** Earlier, reserved capacity was planned annually based on predictable workloads. AI demand does not behave in that way. It is bursty and often linked to product experiments or market events. Leading organizations are maintaining a core layer of reserved compute for stable workloads and using spot or on demand capacity for variable AI demand. Deciding what to reserve and what to keep flexible is now a financial strategy decision. **2. Governance before deployment** In the past, cost governance was often reactive. Teams deployed workloads first and optimized later. With AI, by the time optimization begins, significant spend may already have occurred. Stronger organizations now embed financial checkpoints before deployment. Architecture approvals include cost estimates. Budget owners are clearly defined. Engineers have **3. Multi-cloud as commercial leverage** Multi-cloud used to be justified mainly for resilience and flexibility. In 2026, it is also a negotiation tool. Enterprises that can operate across providers such as Amazon Web Services, Microsoft Azure and Google Cloud are in a stronger position during commercial discussions. When AI infrastructure spend runs into large numbers, even partial workload mobility strengthens pricing conversations and commitment structures. Multi-cloud today is both a technical architecture choice and a commercial strategy. **4. Budgeting by business outcome** The most mature organizations are changing how they frame cloud budgets internally. Instead of allocating budgets only by team or infrastructure category, they When cloud spend is connected to outcomes, finance and engineering start speaking the same language. Leadership gains clarity on why costs increase and whether that increase aligns with revenue or strategic impact. ## **The Bottom Line** Every other post on LinkedIn right now is either about which AI model wins, or how someone automated their entire team before lunch. Fair enough. AI is loud. But there's a quieter story that matters more. Worldwide AI spending is set to hit $2.5 trillion in 2026. That's not a number that leaves much room for financial ambiguity. The enterprises that will look back on this year with confidence are not the ones who spent the most - they're the ones who knew exactly what they were spending, why, and what came back. Cloud economics is no longer a support function. It's the difference between AI that compounds and AI that just costs. The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 03 Oct, 2025 | 5 Min read # Beyond Automation: Why DevOps Transparency Is the Real Enabler of Scalable Cloud Aman Aggarwal Chief Operating Officer Ask a developer, a DevOps engineer, and a security analyst, and you might get three different answers for “What’s being deployed right now?” - none fully accurate. This isn’t a sign of poor tooling or talent. It’s a natural consequence of how fast and fragmented modern cloud-native environments have become. DevOps and cloud computing have grown hand in hand. Cloud infrastructure gives teams the flexibility to automate workflows, spin up resources on demand, and scale fast. With containers, CI/CD, and Infrastructure as Code, delivering features is faster than ever. But this speed brings complexity. While cloud systems get more dynamic, deployment cycles get shorter, and infrastructure becomes more distributed, one key element often gets overlooked: transparency. Without it, teams fly blind. With it, they move faster, collaborate better, and build more resilient systems. As services and teams multiply, misalignment creeps in. Logs get siloed, costs spike, and ownership becomes unclear. Delays in resolving issues or spotting security gaps often stem from a deeper issue: lack of visibility. ## What Transparency in DevOps Really Means Transparency isn’t about tracking individuals or overwhelming teams with dashboards. It’s about making the right information visible to the right people at the right time. True transparency means teams can see what’s happening in their systems, understand why it’s happening, and take action without guesswork. This includes having real-time awareness of code changes and deployments, clearly defined ownership of services, and access to logs, metrics, and cost data across teams. It also means fostering collaboration that moves beyond siloed ticket queues and reactive processes. One emerging solution enabling this kind of visibility is the rise of Internal Developer Platforms (IDPs). These platforms bring together tools, documentation, and infrastructure access in one place, giving teams a single source of truth. Alongside this, GitOps practices,which manage infrastructure using version-controlled repositories,help ensure that system changes are both traceable and auditable by default. ## Why It Matters More as You Scale As the number of services, environments, and engineers grows, lack of transparency becomes a serious concern. When transparency is prioritized: * Engineers see how their changes impact performance and cost * Security teams can identify and address risks earlier * Operations teams can manage infrastructure more predictably * Business and tech teams align better around delivery goals In other words, transparency makes scaling possible - without sacrificing control or quality. ## Security Needs Visibility Too Security has often lagged behind in the DevOps lifecycle, acting as a gatekeeper rather than a partner. But that’s changing. With the rise of DevSecOps and CloudSecOps, organizations are moving to integrate security checks throughout the software development lifecycle - not just at the end. Transparency here involves: * Making vulnerabilities and risks visible early * Sharing threat models and benchmarks across teams * Ensuring compliance controls are understood by all stakeholders For example, generating and sharing a Software Bill of Materials (SBOM) allows security teams and developers to work from the same data when evaluating dependencies and potential exposure. This builds trust and better security outcomes. ## Practical Ways to Build DevOps Transparency Organizations don’t need to overhaul their stack to improve transparency. Here are a few high-impact changes: **1. Use Open Communication Tools** Enable real-time collaboration with ChatOps, standups, and integrated notifications. Make deployments and incidents visible to all stakeholders, not just the on-call team. **2. Bring Cloud Cost Data to Developers** Use FinOps dashboards or alerts within development tools. Help engineers understand how architecture choices affect cost in real time. **3. Standardize Change Tracking** Adopt Git-based workflows and infrastructure as code. Use audit trails and logs that are accessible across teams for accountability. **4. Centralize Documentation and Metrics** Avoid team-specific silos by using unified dashboards and repositories for performance data, documentation, and alerts. **5. Lead with Psychological Safety** Encourage learning from failure, not blame. Transparency only works when teams feel safe surfacing issues and taking ownership. ## AI-based DevOps Observability Guilty as charged - it’s another AI mention. AI-powered observability tools are becoming more common in modern DevOps workflows, especially as systems generate massive volumes of telemetry data. These tools can help detect anomalies, predict incidents, and surface insights before they become outages. But there’s a tradeoff. As AI models grow more complex, they can become harder to interpret - introducing new opacity just as they aim to improve clarity. To keep DevOps transparent, it’s important that AI observability solutions remain explainable. Teams need to understand not just that a warning was raised, but why it was raised and what patterns led to the conclusion. Fan of fiddling with open source tools? (Like me?) Try out projects like Opni, Prometheus paired with anomaly detection libraries like Prophet or PyOD, and ML-enhanced ELK stack implementations - these offer visibility while maintaining control over how AI decisions are made. AI-powered insights can be powerful, but they’re only useful when teams can trust and understand the “why” behind them. ## Bring in the Right Expertise Working with experienced DevOps consulting partners could really be the game-changer here. These third-party experts often bring structured frameworks, proven playbooks, and advanced visibility tools that may not exist in-house. From streamlining CI/CD pipelines to integrating observability platforms and security checks, they can help teams untangle complex workflows and establish cleaner, more transparent processes. Many also embed cost optimization as a core part of delivery, aligning engineering efforts with business goals. When internal bandwidth is limited or in-house practices have become too fragmented, bringing in an external lens can help organizations get back to a more consistent and scalable DevOps model. ## Final Thoughts Transparency is not a one-time tool you install. It’s a practice, a mindset, and a key enabler of scalability in cloud-native environments. When teams can see clearly, they work better across roles, tools, and time zones. They fix problems faster, spend smarter, and ship with greater confidence. While cloud computing and DevOps expand use cases across the horizon, the organizations that invest in visibility, alignment, and trust will be the ones best prepared for what comes next. **The article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 19 May, 2025 | 3 Min read # Burn Cloud Costs, Not Cash: How the 30-Day Challenge Is Making AWS Leaner in 2025 AWS bills continue to climb for companies worldwide despite existing ## **The Myth of the Optimized AWS Environment** Most The problem stems from fragmented visibility. Traditional tools analyze costs but fail to address real-time usage patterns or engineering workflows. Teams juggling deployment deadlines and incident management often lack the bandwidth to audit resources continuously, allowing idle instances and outdated configurations to drain budgets silently. ## **CloudKeeper Tuner: The Real-Time Optimization Engine** At the core of the The platform’s SpotBot feature dynamically switches Meanwhile, its “Optimization is not just about savings, but rather about aligning cloud spend with actual business needs,” says Deepak Mittal, CEO of CloudKeeper. ## **Engineering Teams Stretched Beyond Limits** Cloud engineers face relentless demands: building features, ensuring uptime, and responding to outages while expected to “optimize costs without compromising performance.” This tension creates optimization fatigue. “CloudKeeper Tuner is designed for engineering teams drowning in competing priorities,” Mittal explains. “It integrates directly into their existing workflows, surfacing savings opportunities without adding administrative overhead.” The platform’s browser extensions embed recommendations within the AWS Console, displaying estimated dollar savings beside each resource. For example, a development team might see a $1,200/month savings suggestion for replacing outdated ## **From Skepticism to Savings: The 30-Day Proof** The challenge begins with a five-minute setup granting read-only access to AWS accounts, post which, companies receive a Cloud Fitness Score detailing optimization potential. CloudKeeper reports that 99% of challenge participants achieve at least 10% savings within 30 days. These gains come not from risky cost-cutting but from smarter resource alignment-upgrading instances, removing redundant backups, and applying ## **The New Optimization Standard** The 30-Day Challenge exposes a harsh truth: static optimization strategies fail in dynamic cloud environments. As Mittal notes, “You wouldn’t drive a car with last month’s GPS data. Why manage your cloud that way?” For companies hesitant to commit, the risk-free model resonates. With no upfront costs and read-only access, the challenge removes traditional barriers to third-party tools. The $50 Amazon coupon incentive for accounts over $10,000/month of spending further drives participation. In an era where every dollar counts, CloudKeeper’s blend of automation and expertise offers a clear path to smarter, leaner cloud operations. It proves that the right tools and guidance can turn cloud complexity into clarity and control. This article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 04 Jun, 2026 | 3 Min read # As cloud bills surge, CFOs are stepping in to drive AI-led decisions Deepak Mittal Founder and CEO Cloud was meant to make technology spending more flexible. Instead, for many organizations, it has become one of the fastest-growing and least predictable costs on the balance sheet. Global public cloud spending has crossed the $700 billion mark, growing at over 20% annually in recent years, as enterprises This is where CFOs are stepping in more actively. Until recently, cloud decisions were largely driven by technology teams, with success measured in ## **Cloud costs challenge** One of the core challenges is the way cloud costs behave. Unlike traditional infrastructure, spend is tied to usage and moves with it. A change in workload, a new deployment, or even inefficient architecture can quickly push costs up. For many organizations, this The growing use of AI is adding to this pressure. Data-heavy workloads, ## **Tracking costs with AI** In response, many organizations are starting to look at AI not just as a driver of cost, but also as a way to manage it better. With the right data and context, AI can help teams For CFOs, this creates a more direct role in cloud governance. Finance teams are working more closely with engineering and operations to bring greater discipline to spending and improve visibility across environments. As cloud and AI investments continue to grow, this alignment becomes critical to ensure that spending translates into measurable business outcomes. Approaches aligned with FinOps are gaining ground, but their effectiveness depends on shared accountability across teams. Without that alignment, even the best systems struggle to deliver meaningful control. AI workloads are scaling rapidly across cloud environments, bringing finance leaders closer to technology decisions than ever before. Managing cloud spend has become a core business priority with a direct impact on profitability and growth. In an AI-driven environment, growth without visibility is expensive. The organizations that bring discipline to spending, improve visibility, and act on it consistently will be better placed to stay in control and make sharper, more informed decisions. The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 22 Jul, 2024 | 3 Min read # Cloud FinOps evolves: The state of FinOps 2024 report shows it’s more than cost reduction Cloud FinOps will be leveraged beyond cost savings evolving into a comprehensive business enabler, say prominent industry analysts. The data from the State of FinOps Report 2024, paints a clear picture: FinOps is not a one-time fix, but an essential practice for continually aligning cloud spending with evolving business goals. This short-sighted view of cost-cutting hinders the true value of cloud computing and overlooks the true potential of FinOps. Let’s delve deeper and explore why FinOps is an ongoing process that ensures your cloud spending aligns with your evolving business needs, promotes responsible innovation, and ultimately fuels growth. **Cloud environments are dynamic:** Your cloud usage evolves as your business grows. A one-time cost fix won’t address new resources, changing workloads, or emerging technologies like AI. FinOps, however, is an ongoing process that adapts to these changes, ensuring your cloud spending aligns with your evolving needs. **Business goals are fluid:** What’s cost-effective today may not be tomorrow. A startup, for instance, prioritises rapid innovation, requiring readily available, scalable cloud resources. As it matures, cost-efficiency might become more crucial. FinOps ensures your cloud spending reflects these shifting goals, allowing you to strategically scale up or down. **Innovation is a new Vitamin for businesses:** A major misconception is that FinOps teams stifle innovation. However, the truth is that FinOps promotes responsible spending, not frugality. By optimising costs, FinOps frees up resources for innovation, empowers experimentation and also offers a faster time to market for these offerings. **New project launches:** FinOps helps you “right-size” resources from the beginning. It analyzes your project needs and recommends the most appropriate cloud resources, preventing unnecessary costs and ensuring your project starts with a sound financial foundation. **Scaling existing services:** As workloads fluctuate, FinOps identifies opportunities to optimize resource allocation, recommending services like auto-scaling, which automatically adjusts cloud resources based on real-time demand. Additionally, FinOps helps you leverage cost-saving features like committed use discounts, ensuring you only pay for the resources you consistently use. **Emerging technologies:** While emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML), offer immense potential, their cloud costs can be unpredictable. FinOps provides insights into AI resource consumption, enabling you to experiment responsibly without exceeding budgetary constraints. ## **Beyond cost savings** FinOps offers a treasure trove of benefits beyond simple cost savings: **Improved forecasting:** FinOps practices enhance your understanding of cloud costs, providing clear visibility into your cloud spending. With this financial intelligence, you can create more accurate forecasts and budget plans. **Empowered teams:** FinOps fosters collaboration between finance, engineering, and business teams, breaking down silos and creating a productive working relationship. Finance provides budgetary constraints and cost insights, engineering leverages this knowledge to optimise cloud usage while business teams leverage reports to get assurance that cloud investments are aligned with business objectives. **Sustainability:** In today’s environmentally conscious world, FinOps plays a vital role. By right-sizing resources, FinOps helps reduce your cloud footprint and energy consumption. These advantages all tie back to a core truth: FinOps is a continuous practice that ensures your cloud spending aligns with business goals, promotes responsible resource management, and ultimately fuels innovation and growth. By embracing FinOps as an ongoing journey, businesses can understand cloud spending better and learn how to profit by deriving business value from cloud investments, instead of just focusing on reducing costs. **This article was originally published on** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 16 Mar, 2026 | 5 Min read # Cloud Infrastructure in the AI Era: Managing Performance Without Compromising Margins Sanjeev Mittal Chief Product and Technology Officer Here is a question many technology leaders are starting to ask. When did running AI become more expensive than building it? For years, most AI investment went into training models. Companies focused on building the model, running experiments, and improving its accuracy. Deployment was seen as the final step, where the heavy lifting was already done. That thinking is now changing. In 2026, inference workloads, which are the systems that run AI models in production, account for more than half of AI cloud infrastructure spending. In simple terms, many companies now spend more on running AI than on building it. This is where the real cloud infrastructure challenge begins. The conversation is no longer only about models or data. It is about the workloads running behind them and whether the ## Not all AI workloads are the same One common mistake organizations make is treating all AI infrastructure the same way. In reality, AI workloads have very different characteristics and cost patterns. Training is the process of building a model from scratch. It requires large amounts of compute power, usually GPUs, for a limited period of time. Training jobs often run for days or weeks and then stop. Because of this temporary nature, public cloud environments work well for training. Teams can scale resources up for the training run and release them once the job finishes. Fine-tuning is a lighter version of training. Instead of building a model from the beginning, companies adapt an existing model using their own data. Fine-tuning still requires GPUs but for a shorter duration. A well fine-tuned model can also reduce the cost of inference later because it may run efficiently on smaller infrastructure. Inference is where most long term costs appear. This is the stage where AI models respond to real users. Every chatbot reply, recommendation engine, document summary, or search result relies on inference. Unlike training, inference runs continuously. As the number of users grows, the compute requirements grow as well. Over time, inference usually represents the majority of A newer category is agentic workloads. AI agents do more than answer a single prompt. They plan tasks, perform multiple steps, interact with systems, and maintain context across sessions. These workloads can run continuously and trigger several processes in the background. This creates a different cost pattern where compute usage is tied to business workflows rather than individual user requests. ## The performance and cost balance Engineering teams naturally want the fastest and most reliable infrastructure. However, the most powerful AI hardware is also the most expensive. Delivering low latency responses and high model accuracy often increases cloud costs quickly if infrastructure choices are not carefully planned. There is some good news. The hardware market is improving rapidly. GPU supply has increased and competition among cloud providers has pushed prices down compared to the peak demand period during the early AI boom. But lower prices alone do not guarantee controlled spending. Organizations that manage AI infrastructure well make careful decisions about where each workload should run. Training workloads that run occasionally are well suited to public cloud environments and spot instances. Teams can access large clusters when needed and release them afterwards. Inference workloads tell a different story. If a model runs continuously and serves a high number of users, ## The role of multi cloud Another clear trend in 2026 is the growing use of multi cloud strategies for AI workloads. Earlier, multi cloud was mainly discussed as a way to improve reliability. Today, it also provides financial flexibility. AWS, Azure, and Google Cloud price AI infrastructure differently. When organizations can Different cloud platforms also have strengths in different areas such as GPU availability, specialized hardware, or AI services. Using multiple providers allows organizations to match workloads to the most suitable environment rather than relying on a single platform for everything. ## What cloud governance looks like today Companies that manage AI infrastructure costs effectively tend to follow a few common practices. First, they address cost planning early in the architecture stage rather than after the infrastructure is already deployed. Second, they give engineering teams Third, they evaluate cloud spending based on business outcomes instead of only tracking infrastructure categories. Another important practice is separating training and inference costs. Training is a periodic investment while inference is a continuous operational cost. Treating both as a single budget makes financial planning more difficult. Industry data from the FinOps Foundation also shows that ## The bottom line Most AI conversations today focus on models, automation, or the latest breakthroughs. Those topics attract attention, but there is a quieter challenge behind them - AI systems depend on infrastructure that runs continuously and at scale. Cloud costs can grow just as quickly as AI adoption if the infrastructure strategy is not carefully designed. The organizations that will succeed in balancing cost and performance will be the ones that understand their workloads, choose the right infrastructure for each stage, and maintain financial discipline as they scale. Cloud infrastructure decisions are no longer purely technical choices. They directly affect margins, budgets, and long term sustainability of AI initiatives. In 2026, performance and cost management must go hand in hand. The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 25 Nov, 2025 | 5 Min read # The Cloud Profit Paradox: Why Growing Faster Often Means Paying More Naman Jain Chief Growth & Marketing Officer When cloud computing first took center stage, it promised a future of boundless scalability, instant innovation, and freedom from capital expenditure. For startups and new projects, the cloud was (and still is) a game-changer - a platform where ideas could scale faster than ever before. But as organizations grow and their cloud footprints expand, many encounter an unexpected reality: the more efficient they become, the more they end up spending. This contradiction, often called the Cloud Profit Paradox - or as some call it, the Trillion Dollar Paradox - captures a hard truth about In other words, the cloud accelerates innovation, but without discipline, it can quietly erode profit margins. ## **From Steam Engine to the Cloud Server: The Modern Jevons Paradox** To understand why this happens, let’s look back to 1865, when economist **William Stanley Jevons** made a startling observation. As steam engines became more efficient, Britain should have used less coal - but it used far more. Efficiency had made coal cheaper and more accessible, leading to greater overall consumption. Fast-forward to today, and history is repeating itself in the cloud. Enterprises are finding that while their per-unit cloud costs drop - thanks to automation, cheaper infrastructure, and advanced services - their total cloud bills continue to rise. Developers launch more workloads, AI pipelines spin up more compute resources, and new digital initiatives are initiated across teams. A recent survey of 300 enterprise CIOs revealed this paradox vividly: while 80% reported ## **How the Cloud Profit Paradox Plays Out** **1. The Early Advantage** In the beginning, the cloud’s pay-as-you-go model eliminates the need for expensive hardware. It’s perfect for innovation - enabling startups and teams to move fast and experiment freely. **2. The Flexibility Tax** As usage grows, however, the same flexibility that fuels agility starts to strain finances. Teams overprovision “just to be safe,” forget idle resources, and accumulate zombie workloads that quietly drain budgets. **3. The Jevons Effect** The cloud keeps getting cheaper per unit, but because it’s so easy to deploy, organizations consume more. Efficiency itself becomes the accelerant for higher spend. **4. The Profit Squeeze** Eventually, large enterprises find their cloud bills rising faster than revenue growth. The pressure on operating margins can outweigh the innovation benefits if cost governance lags behind consumption. ## **Beyond Cost Control: Turning Insight into Action** The cloud paradox doesn’t mean companies should abandon the cloud. It means success now depends on how intelligently the cloud is managed. The real winners are the ones who Here’s how leading organizations are doing it. **1. Make Cloud Optimization a KPI** Cloud costs should be used outside finance dashboards. To be more specific, they deserve a place **2. Build Cost Awareness Across Teams** The people who deploy resources often aren’t the ones reviewing invoices. That disconnect breeds inefficiency. Empowering engineers and product owners with **3. Optimize Usage Continuously** Cloud optimization should be a habit - a part of daily business processes. From optimizing workloads and leveraging spot instances to storage tiering and scheduling, small actions add up to big savings. Many organizations see 10-40% annual savings just by Adopting FinOps practices formalizes this discipline, creating cross-functional collaboration between finance, operations, and engineering to ensure cloud usage aligns with business value. **4. Leverage AI and Automation** Manual cost management simply can’t keep up with the current state of complex cloud architectures, given the needs of AI-driven demands. Predictive analytics can even flag when costs deviate from expected business performance, letting teams act before overruns occur. Automation control costs, accelerates efficiency and helps teams in shifting focus towards innovation. **5. Foster a Cloud-Smart Team Culture** Cloud success is as much about mindset as it is about tooling. Encouraging collaboration between engineering, finance, and product teams ensures cost-efficiency becomes everyone’s responsibility. This **6. Partner with Cloud Experts to Unlock Time for Innovation** Even the most capable internal teams can find it difficult to balance cloud cost optimization with product and business demands. This is where By working with a trusted cloud partner, organizations free up valuable time and resources - allowing internal teams to focus on innovation, customer experience, and long-term cloud strategy, while the partner ensures continuous cost savings behind the scenes. ## **Turning the Paradox into Progress** The Cloud Profit Paradox isn’t a sign of a failed cloud strategy, but it shows that cloud maturity demands smarter economics. As AI intensifies demand, businesses must focus more on spending intelligently rather than spending less. By treating cloud optimization as a KPI, fostering cost awareness, using AI and automation, and partnering with FinOps experts, enterprises can strike the right The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 13 Nov, 2024 | 3 Min read # From Cloud Waste to Cloud Efficiency: Navigating the Path to Cost Optimization When groundbreaking technologies like Generative AI and Blockchain are reshaping how businesses and industries operate, cloud computing has emerged as the backbone supporting their widespread adoption. This, in turn, enhances the importance of ## **The Pay-as-you-go Myth** There could be a common misunderstanding about the concept of “you pay for what you use”. Cloud providers charge based on the resources you provision and reserve, not just actual usage. Over-provisioning and under-utilization of resources are hence the major contributors to unnecessary cloud costs. No wonder why cloud waste is the top concern for businesses in the ## **An Ocean of Services and Pricing Models** As businesses bring up new use cases, cloud providers respond with a broader array of services. While businesses adopt these offerings rapidly, it often results in a complex infrastructure with fragmented resources and inefficient architecture. Adding to the complexity, ## **Knowing Where Your Money Goes** ## **Less-obvious Cloud Cost Pitfalls** There are certain hidden cost drivers that quietly accumulate significant cloud costs and impact a company’s bottom line. For example, ## **Multi-cloud Comes into Play** According to the recent State of the Cloud Report, almost 89% of organizations have a Without extensive expertise and cloud-agnostic tools they could also lead to unexpected data transfer costs, security risks, and service compatibility issues. ## **The Right Way Ahead** While these challenges may seem familiar, overcoming them requires up-to-date strategies and expertise. **In-depth Cost Visibility** – First and foremost, you need to deploy * **Cloud Governance Policies** – Use robust cloud governance policies to streamline resource management. This ensures that cloud usage aligns with your organization’s strategic objectives. * **Power of Automation** – Utilize automation to streamline tasks like provisioning and reservation management. Some solutions help perform multiple * **Refine KPIs and Metrics** – Your * **Build Cost Optimization into the Culture** – Fostering a culture of cost consciousness is essential for effective cloud cost management. This starts with enhancing collaboration between finance and engineering teams. * **Multi-Cloud/Hybrid Cloud Expertise** – For those unable to build and sustain an internal team, partnering with specialized cloud cost optimization service providers offers access to the latest expertise and multi-cloud strategies. ## **Conclusion** With cloud cost optimization, the core challenges have always remained the same—cloud waste, lack of visibility, and governance. But with relevant expertise and a culture where everyone’s a cloud cost evangelist, businesses can harness the full power of the cloud while keeping their finances happy and healthy. This article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 20 Aug, 2025 | 5 Min read # The Dual Role of AI in Cloud Cost Management: Driving Demand and Offering Solutions Aman Aggarwal Chief Operating Officer ChatGPT, Midjourney, Automated Workflows, MCP, Agentic AIs - Artificial Intelligence is flipping the script, how things get done, how we interact with customers and pushing us to redesign core business processes. But as AI expands to new frontiers, it’s also reshaping one of the most foundational layers of modern enterprises: cloud computing. The cloud is shouldering this weight of AI’s rise and businesses are feeling it. On the flip side, AI and ML also offer the best tools available to manage those costs intelligently - quite a paradox. This makes it all the more important for cloud leaders to make the most of AI to stay competitive, efficient, and sustainable. ## **AI is driving up Cloud Consumption and Complexity** AI is one of the most compute-hungry technologies in use today. Training large language models, running real-time personalization engines, and operating ML pipelines across workflows - all these require enormous resources, especially for GPUs, high-throughput storage, and low-latency networking. McKinsey estimates that global demand for data center capacity could triple by 2030, with 70% of that demand tied to AI infrastructure. Out of this, Generative AI is expected to account for nearly 40% of the total, and most of this will be hosted on hyperscaler platforms like AWS, Google Cloud, and Azure. This isn’t the only concern. AI models require continuous retraining, real-time data feeds, and fine-tuning which requires a persistent volume of cloud usage. And, unsurprisingly, this surge isn’t without consequences. Public cloud prices are rising. Data center supply in markets like Northern Virginia, USA has dipped below 1% vacancy, while colocation prices have seen double-digit increases year-over-year, according to This scenario of scarce GPU availability and soaring energy consumption has given rise to a new kind of inflation: AI-driven cloud inflation. ## **AI is also the Solution** These statistics might seem concerning - but they’re only half the story. Experts recommend turning to AI itself to solve the very challenges it creates. The result will be a more intelligent approach to cloud cost management - proactive, automated, and sustainable. **Data-Driven Forecasting** By analyzing historical consumption patterns and operational rhythms, AI could help businesses anticipate demand before it happens. This allows cloud teams to plan and provision resources more precisely, minimizing idle infrastructure and avoiding last-minute scrambling. In fact, research shows that AI/ Gen-AI powered forecasting tools can reduce over-provisioning costs by up to 23%. That’s because teams no longer rely on assumptions or overestimate “just in case”. They act on precise, actionable insights. **Smarter Scaling, Greater Efficiency** AI-based usage optimization tools help scale your workloads dynamically, rather than keeping them running at the peak capacity 24/7. When demand rises, these ramp up automatically and scale back down when usage scales down with almost zero manual intervention. This level of agility has immense financial impact. According to studies, organizations using AI and automated scaling mechanisms have seen almost 30% improvement in resource efficiency and cloud spend savings - that’s a third of your cloud spend saved with very little effort. This also means that AI-based optimizations help operational performance and financial responsibility go hand-in-hand - finding that perfect balance. **Simplifying Cost Control and Oversight** Whether it’s spotting unusual spikes in spend or flagging services running longer than needed, AI-powered cloud visibility tools can proactively alert teams to take action before these small cost centers snowball into large expenses. Unlike traditional budget reviews, these insights arrive in real time, allowing for quick corrections. **Sustainability, Optimized with AI** AI is also helping businesses meet sustainability goals in smarter ways. Google Cloud’s Carbon Footprint API and Microsoft’s Sustainability Calculator use AI to recommend workload placement based on renewable energy availability. Meanwhile, AWS supports similar goals using its Gen AI agent Amazon Q integrated into its Well-Architected Framework reviews. ## **The Limitations: AI Isn’t a Silver Bullet** Despite its capabilities, AI has limitations in cloud cost management that have both enthusiasts and regulators talking: **Data Privacy Risks** AI thrives on data - but when deployed in public cloud environments, the lines around data ownership, access, and compliance could become blurry. Without clear boundaries , these AI algorithms could pose a risk to organizations, exposing sensitive data to unauthorized access or third-party breaches. **Internet Dependency** Cloud-based AI solutions require stable, high-speed connectivity. For use cases involving real-time analytics or continuous model updates, any interruption in connectivity can result in downtime or performance degradation. And the latency could affect alerts and recommendations mechanisms. **Skill Gaps and Implementation Hurdles** While companies and their tech teams are still catching up with cloud innovations, AIOps adds another layer of complexity on top of it. From integrating predictive models with Kubernetes to interpreting real-time cost insights from Gen AI-powered dashboards, the technical lift can be substantial. **Model Transparency** One major barrier to AI adoption in cloud cost governance is trust in the AI algorithms and reasoning. AI models often operate as black boxes, making decisions hard to interpret. This could create a gap in understanding why or how certain optimizations were made. Although there have been innovations like the Explainable AI (XAI), which aims to bridge the gap between automation and human understanding - it’s still maturing. **Infrastructure Constraints** Data centers are being pushed to the limit. Even if demand projections hold steady, the U.S. could face a 15+ GW deficit in data center capacity by 2030. This constraint may eventually limit how far and fast organizations can scale AI workloads ,unless of course, tackled by innovations. ## **Moving Forward with Clarity** Like every major shift in technology, AI comes with its own set of challenges. It adds pressure on infrastructure, increases energy use, and raises new concerns around cost visibility and governance. These are valid points. But they are not reasons to step back, but to plan better. Cloud computing faced similar doubts when it first emerged. So did containers, microservices, and even SaaS platforms. Over time, the advantages became clear and more profound - I guess the same will be true for AI, especially when we apply it with discipline. The reality is, the advantages of AI in CloudOps already outweigh the disadvantages. Businesses can now forecast usage with more accuracy, automate scaling, reduce waste, and make smarter decisions in real time. The tools are ready and available across almost all infrastructures. What’s lacking could be the right mindset towards approaching and integrating these solutions, or AI/ML in general. The companies that succeed will be the ones that use AI to build better foundations - cost-efficient, flexible, and ready to scale. Because the cloud is not meant to limit AI, it should help unleash its full potential. **The article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 31 Aug, 2024 | 3 Min read # FinOps paves new avenues to ease economic pressure globally, by prioritising cloud optimisations The World Bank’s latest “Global Economic Prospects” report predicts that global growth will slow to 2.4% in 2024 before increasing to 2.7% in 2025. Rising costs, inflation, and supply chain disruptions force companies to tighten their belts and focus on cost reduction. Every avenue for savings is being scrutinised, and one area ripe for optimisation is cloud spending. More than half of organisations are either hiring or re-training their workforce to better optimise their cloud spend. In this economic tempest, FinOps emerges as a beacon of hope. FinOps is a practice that fosters collaboration between finance, IT, and business teams to optimise cloud financial management. It operates on several key pillars, to bring financial stability: **Transparency:** Clear visibility into cloud costs, empowering informed decision-making. **Governance:** Guardrails and policies to prevent cloud waste and ensure responsible spending. **Chargeback:** Fair allocation of cloud costs across different business units, fostering accountability. **Optimisation:** Continuous monitoring and right-sizing of cloud resources to eliminate inefficiencies. ## **Prioritising cloud optimisations, reducing cloud waste: A step towards establishing FinOps culture.** A 2023 Report by FICCI & EY says that 78% of companies have more than 30% of data on the cloud. Many of these companies try to control cloud spending with one-time fixes, like short-term analysis or patching problems, but they often need to be repeated since the root cause isn’t addressed. A single cost-cutting software might not be able to deliver long-term value. Studies have also revealed that Cloud cost wastage is a significant concern globally with 38% of organisations worldwide wasting more than a third of their cloud spending. That’s where FinOps comes in. Going beyond just throwing new tools at the problem, FinOps helps organisations get the most out of their cloud investment. It starts with forming a clear picture of your current infrastructure and software to develop a solid strategy for optimising costs and maximising benefits. Here is a list of key FinOps metrics tracked by organisations in the order of their importance: **Cloud cost per application:** Tracks the cloud expenses incurred by a specific application. **Cloud optimisation ratio:** Measures the efficiency of cloud resource utilisation relative to costs. **Cloud cost per user:** Indicates the average cloud expense allocated to each user. **Savings plan coverage:** Represents the percentage of cloud spending covered by pre-paid commitments. **RI coverage:** Shows the portion of cloud compute costs covered by Reserved Instances (RIs). Building a FinOps team can further enhance this approach. This team fosters a culture where everyone understands the importance of responsible cloud spending. A successful FinOps program doesn’t just keep costs under control, it also helps identify areas where you can invest your cloud resources more effectively, especially when your internal resources are limited. ## **A Rising Tide: The Positive Growth of FinOps Adoption** The positive impact of FinOps is reflected in its growing adoption rate. The FinOps Foundation reports a significant increase in the number of certified FinOps practitioners globally. This surge in adoption signifies a collective recognition of the cost-saving potential that FinOps offers. Businesses are embracing FinOps as a strategic weapon in their arsenal for navigating economic challenges. FinOps isn’t just about numbers; it’s about aligning financial discipline with business agility. This translates to greater resilience in the face of economic pressures empowering businesses to emerge stronger and more competitive. Remember, every dollar saved counts—whether it’s in the cloud or elsewhere. **This article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 Nov, 2025 | 4 Min read # The Future of FinOps: How AI is Making Cloud Cost Management Predictive and Proactive Deepak Mittal Founder and CEO You know how every cloud bill feels like a mystery novel: plot twists, unexpected characters, and that one villainous workload you forgot existed? AI promises to end that story by thoroughly explaining the past and smartly predicting what’s next. ## **The AI Race: More Than Just Model Supremacy** The past year has felt like a global AI sprint. New models emerge every few weeks, benchmarks shatter almost as soon as they’re created, and industry leaders champion AI as the defining force of this decade. But beneath the spectacle, a quieter transformation is reshaping the foundation of modern computing. AI models are being integrated into cloud infrastructure for They decide where workloads should run, how resources should scale, and when costs are about to drift off target. The same intelligence that powers chatbots and image generators now powers the unseen machinery that keeps our digital world running. ## **From Reactive to Predictive and Proactive** For years, cloud management was a cycle of reaction. Identify an issue, fix it, and prepare for the next one. AI is changing that rhythm entirely. Modern AI systems analyze usage data in real time, detect irregularities before they impact performance, and recommend optimizations almost instantly. They learn how applications behave, forecast traffic patterns, and The result is near-accurate foresight! Cloud systems are starting to think ahead, transforming daily firefighting into deliberate, data-driven decisions. ## **Turning Data into Decisions** FinOps teams today are surrounded by a flood of cloud data: invoices, utilization charts, and performance metrics. AI acts as the bridge between that raw data and real business insight. Instead of waiting for cost anomalies to show up in monthly reports, AI algorithms highlight them the moment they start forming. They ## **Simplifying Multi-Cloud Complexity** Managing multi-cloud or hybrid environments has become a puzzle of pricing models, performance variations, and billing formats. AI thrives in such complexity. Machine learning tools can analyze cross-cloud data, recommend where workloads perform best, and identify underused or overpriced resources. They can even estimate the long-term financial impact of ## **Where AI Still Falls Short** As promising as AI-driven cloud management sounds, it comes with its own set of challenges. AI models rely heavily on the quality of data they are trained on. Poor or incomplete data can lead to inaccurate predictions, misguided scaling actions, or false cost alerts. Moreover, AI-based recommendations often lack context. A model might suggest shutting down resources for cost efficiency, overlooking that they support critical backup operations. There’s also the issue of transparency. Many AI systems operate as black boxes, offering outcomes without clear reasoning. For organizations making high-stakes infrastructure decisions, that lack of explain-ability can be unsettling. And of course, automation without oversight can introduce risk. A wrong algorithmic decision, multiplied across a large infrastructure, can amplify problems rather than solve them. This is why experts increasingly stress a “human-in-the-loop” approach, where AI provides insights, but ## **The Human + AI Partnership** The goal of AI in the cloud is not replacing human expertise but reinforcing the impact. By taking over repetitive and time-sensitive tasks, AI allows engineers and FinOps professionals to focus on strategy, innovation, and architecture. A Together, they can achieve something neither could accomplish alone: a cloud environment that runs efficiently, adapts intelligently, and supports business growth responsibly. ## **The Bigger Picture** AI’s growing role in cloud management is also redefining governance and reshaping how FinOps operates. It’s enabling smarter policy enforcement, predictive capacity planning, and more sustainable energy use by identifying and minimizing idle or redundant resources. Forward-looking enterprises are embedding AI into their cloud governance frameworks to make FinOps more collaborative and proactive. Instead of isolated finance and engineering efforts, AI helps teams share real-time insights, align cost decisions with business priorities, and continuously learn from past trends. When used responsibly, AI has the potential to turn cloud management into a continuous cycle of learning, where every action feeds intelligence back into the system and strengthens the next decision. Cloud automation is now the primitive layer of progress. AI in the cloud is emerging into an ecosystem of intelligence - one that learns, adapts, and collaborates with humans to drive real business value. The smartest companies who leverage AI as a living system of intelligence, collaboration, and continuous learning will lead the next wave of cloud computing. **The article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 30 Apr, 2025 | 4 Min read # The Hidden Cloud Costs Draining Startup Budgets When people talk about cloud costs, it usually revolves around **compute, storage, and networking.** But if you're a startup founder or part of an early-stage tech team, here's a truth bomb: Those numbers on your cloud bill? They're just the tip of the iceberg. In reality, the**real cost** of running on the cloud often comes from something much less visible - your own team’s time and energy spent wrangling infrastructure. Startups adopt the cloud because it’s fast, flexible, and low-cost upfront - industry research says 68 percent startups cite affordability as the top driver. In fintech, 75 percent use it to speed up time-to-market. But once you're past the initial setup, costs shift from infrastructure to the people keeping it running. Every hour your engineers spend restarting containers, fixing CI pipelines, or And when things break , it's never the junior team that jumps in - it's your most experienced engineers. Suddenly, your best talent becomes full-time firefighters. And while all this is happening, cloud costs continue climbing in the background. Why? Because you're over-provisioning to avoid downtime. You're keeping idle resources running “just in case.” You're not auditing usage regularly because the team is too stretched. Startups often underestimate cloud operations time by 50–60 percent, and that doesn't even account for the real dollars lost to unused resources, zombie workloads, misconfigured autoscaling, or inefficient architectures. The result? You're not just burning time. You're burning your budget. And for a startup, that means burning the runway. ## **5 Hidden Cloud Cost Traps and Smarter Ways to Beat Them** Most startups don't overspend on cloud because they’re careless. They do it because cloud complexity snowballs fast - and what seemed efficient at Series A becomes a budget sinkhole by Series B. Here's a breakdown of 5 often-overlooked cost traps and what you can do about them. 1. **You’re Not Paying for the Cloud. You’re Paying for People :** It’s easy to blame AWS or Azure for a rising bill, but often the biggest cost isn't the infra - it’s your team managing it. Engineers spend hours maintaining flaky CI/CD pipelines, provisioning resources manually, tweaking IAM roles, or debugging failed deployments. This eats into both your budget and product velocity. **What to do:** 2. **Infra Sprawl - Idles, Zombies and more:** Left unchecked, cloud environments accumulate junk - idle VMs, orphaned disks, outdated snapshots, unused IPs. With every team spinning up resources and no one tearing them down, you end up with a slow leak that becomes a flood. **What to do:** Run regular infra audits. Set up resource tagging from day one, enforce lifecycle policies, and schedule automated cleanups. Tools like 3. **Scaling Usage, But Not Commitments:** Startups often stay on-demand “just in case” - which is great for flexibility but terrible for your budget. As your workloads stabilize, you miss out on **What to do:** Once you know your steady-state workloads (databases, core services, etc.), commit to them. Use a mix of Reserved Instances and Savings Plans. Monitor usage trends to commit smartly, and review these commitments quarterly. Partnering with cloud cost optimization experts can also unlock 4. **When Moving Data Steals Money:** Cloud providers love to tout storage and compute prices, but quietly rake in cash from data transfer. Cross-region traffic, external egress, even inter-AZ chatter - it all adds up. At scale, it can become one of your top 3 spend categories. **What to do:** Architect for data locality. Keep services and databases in the same region and zone. Use 5. **Over-Engineering Too Early:** It’s tempting to build “like the big guys” - multi-region failover, microservices everywhere, **What to do:** Stay lean. Choose simplicity over theoretical scale. Adopt opinionated PaaS offerings or serverless where it makes sense. Build for resilience, not perfection - and optimize only when real usage data demands it. A simpler architecture keeps both costs and cognitive load down. ## **Final Thought** Cloud gives startups speed, scale, and optionality - but only if you treat it like a product, not a utility. Monitor early, automate aggressively, and architect intentionally. Spending smarter doesn’t mean cutting corners, it means making room to grow. And you don’t have to go it alone. Working with expert consultants or third-party This article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 21 May, 2026 | 6 Min read # The Hidden Cost of AI Adoption: Why Most Enterprises Are Flying Blind on Cloud Spend Naman Jain Chief Growth & Marketing Officer Over the past decade, enterprises have invested heavily in building mature cloud environments. Cloud adoption brought flexibility, scalability, and speed, but it also introduced a new financial challenge. Organizations had to learn how to manage rising cloud costs while maintaining operational efficiency. That is where FinOps became critical. Enterprises spent years building governance models, Now, AI adoption is changing that equation again. Across industries, organizations are rapidly integrating AI into everyday business operations. Customer support platforms are becoming AI-enabled. Developers are using AI coding assistants. Internal workflows are being automated with generative AI tools. Teams across departments are experimenting with AI-powered applications to improve productivity and accelerate decision-making. While this momentum is creating new business opportunities, it is also introducing a new layer of complexity inside cloud environments. Many enterprises are discovering that the cloud ecosystems they spent years optimizing are becoming difficult to manage again. The challenge is not simply that AI increases cloud usage. The larger issue is that AI workloads behave very differently from traditional enterprise applications. As a result, cloud spending becomes harder to predict, harder to optimize, and in many cases, harder to even identify properly. This is creating a growing visibility problem for enterprises. ## **AI workloads do not behave like traditional applications** Traditional enterprise applications usually follow relatively stable usage patterns. Businesses can forecast traffic, estimate infrastructure needs, and optimize resources over time with reasonable accuracy. AI workloads are far less predictable. A single AI-enabled feature can dramatically increase infrastructure consumption based on how employees or customers interact with it. Usage patterns can fluctuate daily. Teams continuously test models, prompts, and workflows. Experiments scale rapidly once adoption begins. In many cases, enterprises launch AI initiatives as pilots, only to discover that infrastructure consumption rises much faster than anticipated. This becomes especially difficult because AI adoption is often happening across multiple teams simultaneously. Engineering, marketing, customer support, HR, and operations teams may all be using different AI services, tools, or cloud resources independently. As AI adoption expands across the organization, cloud consumption grows in parallel. The problem is that many enterprises still lack the visibility needed to understand how much of their cloud spend is directly tied to AI workloads. Leadership teams can see overall cloud costs increasing, but identifying exactly which AI initiatives are driving that growth is becoming increasingly difficult. ## **Standard cloud cost models are struggling to keep up** For years, cloud optimization strategies focused on improving efficiency across relatively predictable workloads. Enterprises became better at rightsizing infrastructure, eliminating idle resources, and improving resource utilization. AI introduced a very different operational model. Unlike traditional workloads, AI environments involve continuous experimentation. Teams constantly test new models, run training workloads, evaluate outputs, and integrate new capabilities into applications and workflows. This creates a cloud environment where consumption changes rapidly, and forecasting becomes less reliable. A company may begin with a limited AI deployment for internal users, but as adoption spreads across teams, infrastructure usage can scale quickly within a short period of time. In many cases, cloud costs rise gradually at first and then accelerate faster than expected. That unpredictability is creating pressure for both technology and finance teams. Engineering leaders want flexibility to experiment and innovate quickly. Finance teams want clearer forecasting and stronger cost visibility. The difficulty is that many existing cloud governance models were not designed for this type of constantly evolving workload behavior. As a result, enterprises are finding themselves in a position where cloud spending becomes reactive instead of controlled. This is one of the biggest operational challenges emerging from enterprise AI adoption today. ## **AI spend is often fragmented across the organization** Another reason cloud visibility is becoming more difficult is the fragmented nature of AI adoption itself. In many organizations, AI usage is not centralized. Different business units adopt different tools, vendors, and platforms based on their own operational needs. Some teams may rely on cloud-native AI services, while others use external AI platforms or subscription-based tools. This creates multiple layers of spending across the enterprise. Some costs appear under cloud infrastructure usage. Others appear through API consumption, third-party AI subscriptions, storage expansion, or supporting data services. Over time, these expenses become distributed across departments and cost centers. The result is a growing visibility gap. Many enterprises can see that cloud spending is increasing. Fewer can clearly explain which AI workloads are responsible. This becomes even more concerning when organizations begin scaling AI initiatives without clear measurement frameworks around business value or operational efficiency. Projects that begin as experimentation can continue consuming cloud resources long after their practical impact becomes unclear. Duplicate tools may emerge across teams. AI services may remain active without regular optimization reviews. Without proper visibility, enterprises risk creating a cloud environment where AI-related spending grows faster than governance practices can adapt. ## **Cloud optimization is becoming more complex** AI adoption is also changing the nature of cloud optimization itself. Traditional cloud optimization practices still matter. Rightsizing infrastructure, eliminating waste, and improving utilization remain important. But AI introduces new operational considerations that many enterprises are still learning to manage effectively. Organizations now need deeper visibility into how AI workloads consume cloud resources over time. They need a better understanding of which workloads create the highest operational costs, which applications drive the largest usage spikes, and which AI deployments deliver measurable business value. This requires a more continuous approach to optimization. Cloud teams can no longer rely only on periodic cost reviews or static optimization models. AI workloads evolve too quickly for that approach to remain effective. As adoption expands, enterprises need ongoing monitoring, stronger workload-level visibility, and tighter collaboration between engineering, finance, and operations teams. The goal is not to slow down AI adoption. Most enterprises understand that AI will continue becoming a core part of business operations. The real objective is ensuring that cloud environments remain financially sustainable as AI usage scales. ## **Businesses need an AI-aware FinOps approach** The rise of AI is pushing enterprises into a new phase of cloud financial management. Organizations that successfully manage this transition will be the ones that build stronger visibility around This requires closer alignment between cloud teams, finance teams, and business leaders. Enterprises need clearer ownership structures, better workload attribution, and stronger operational accountability around AI consumption. More importantly, they need a better understanding of how AI adoption changes cloud economics over time. Many enterprises already spent years building mature cloud governance frameworks. AI is now testing the limits of those frameworks. Cloud spending will continue growing across industries. For leadership teams, the challenge is no longer whether AI should become part of enterprise operations. In many organizations, that transition is already well underway. The bigger challenge is ensuring that AI-driven growth does not reduce the financial visibility and operational control enterprises worked years to build across their cloud environments. FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 01 Apr, 2025 | 4 Min read # High-tech and digital native businesses need a strategic approach to manage multi-cloud cost Multi-cloud isn’t just an option anymore—it’s how modern high-tech companies operate. 90% of tech innovators have already adopted it, and 76% of technology organizations run a mix of public and private clouds, as per recent industry reports. High-tech businesses with substantial cloud expenditures see multi-cloud as a way to enhance resilience, optimize their significant spending, and leverage the best features of different cloud providers. In fact, more than half of CTOs and tech leaders (53%) believe multi-cloud helps them achieve their ambitious growth and innovation goals. While multi-cloud unlocks flexibility and resilience, it also brings a fair share of challenges—especially when it comes to managing costs for high-volume cloud users. A staggering 70% of tech companies struggle with the complexities of multi-cloud, from lack of visibility into their substantial cloud bills to resource sprawl, where engineering teams spin up expensive workloads without proper oversight. For high-tech companies running compute-intensive workloads, managing resources across different cloud providers means dealing with inconsistent APIs, fragmented security policies, and varying cost structures at scale. Synchronizing demanding workloads isn’t always seamless, and without proper visibility, costs can spiral out of control, especially for AI, machine learning, and big data applications. The skills gap hits tech companies particularly hard—finding DevOps talent who can efficiently manage sophisticated multi-cloud setups for high-performance environments is increasingly competitive and expensive. So, how do high-spending tech companies navigate these challenges and make the most of their substantial multi-cloud investments? Here are some best practices that can help navigate the chaos and optimize multi-cloud costs for organizations with significant cloud budgets. ## **Make cost management everyone’s job** For tech companies with seven or eight-figure cloud bills, cost management isn’t just an IT problem—it’s a company-wide responsibility that impacts the bottom line. That’s where Industry benchmarks suggest dollar savings through ## **Stop paying for resources you don’t need** Over-provisioning is one of the biggest money drains for tech companies with extensive cloud usage. Many high-performance workloads run on oversized GPU instances that just sit there eating up cash. ## **Get a single view of cloud spending** If your development teams are using multiple cloud providers for different aspects of your tech stack, ## **Don’t settle for the sticker price** Cloud pricing isn’t set in stone—it’s highly negotiable, especially for high-tech companies with significant spending power. Long-term commitments like ## **Let AI handle the heavy lifting** For tech companies with complex infrastructure, manually tracking costs is a nightmare, and mistakes can be expensive at scale. AI-powered usage and cost management platforms can ## **Final thoughts** For high-tech and digital native businesses with significant cloud spending, multi-cloud could be challenging, but it’s definitely not just a fad—95% of technology organizations now consider multi-cloud architectures critical to business success. However, with more choices and flexibility come more moving parts and complexity in your already sophisticated tech stack. A well-thought-out strategy, combined with these best practices, can make all the difference for companies with substantial cloud budgets. By automating cost controls, optimizing usage of specialized resources, and leveraging smart pricing strategies, you can create a well-oiled machine that’s powerful, cost-efficient, and resilient—even as your technology needs continue to scale. That said, managing a sophisticated multi-cloud environment requires specialized skills, which can be a hurdle even for technically advanced organizations. This is where working with expert partners in cloud cost optimization can bridge the gap, bringing in deep expertise, automation, and proven strategies to ensure your significant cloud investments deliver maximum ROI and support your company’s ambitious technology goals. This article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 02 Apr, 2026 | 5 Min read # How AI-Powered Optimization Can Define The Next Phase Of Cloud And AI Maturity Deepak Mittal Founder and CEO Global IT spending has crossed the But beneath the momentum, there lies a structural tension of AI dramatically increasing cloud cost complexity. More than 80% of organizations cite The state of cloud and AI might just have shifted its focus from the number of model deployments to how intelligently those workloads are optimized. ## The New Cost Problem: AI at Scale AI changes cloud economics in three fundamental ways. First - infrastructure intensity. GPU-backed instances are significantly more expensive than traditional compute instances and are often capacity constrained. Utilization inefficiencies compound quickly in such environments. Second - pricing volatility. Token-based consumption models, dynamic inference workloads and multi-cloud AI deployments introduce variability that traditional static budgeting cannot handle. Third - operational speed. AI teams iterate rapidly. Experiments scale quickly. Traditional FinOps approaches - manual reviews, static dashboards and periodic rightsizing - were not built for autonomous, self-scaling workloads. AI is increasing both the scale and unpredictability of cloud consumption. The solution, increasingly, must also be AI. ## AI Optimizing AI Workloads One of the most important but under-discussed inflection points is that of AI beginning to optimize itself. Model compression techniques can reduce parameter sizes without materially affecting accuracy, lowering training and inference costs. Inference batching and workload shaping improve throughput efficiency, especially in high-volume environments. Dynamic model selection ensures that not every query is routed to the most expensive model - matching cost to required precision. Token efficiency strategies, including prompt refinement and adaptive context management, can meaningfully reduce per-interaction spend in large language model deployments. AI is also accelerating code modernization. AI-assisted refactoring and workload redesign help legacy applications operate more efficiently in cloud-native environments, In this sense, optimization has an added layer of architectural intelligence along with infrastructure tuning. ## AI for Cloud Cost Optimization While AI can optimize workloads themselves, the broader opportunity lies in applying AI to cloud financial governance. AI-powered cloud optimization typically operates across four capability layers: ### 1. Predictive Cost Intelligence AI systems analyze historical consumption patterns, forecast future demand and simulate spend scenarios before new workloads are deployed. This enables proactive financial planning rather than reactive cost correction. ### 2. Intelligent Resource Scheduling AI can dynamically allocate workloads across regions and clouds, optimize GPU cluster utilization and balance spot versus reserved capacity. In high-cost AI environments, utilization precision directly impacts economic performance. ### 3. Autonomous FinOps Instead of relying on quarterly reviews, AI agents continuously evaluate commitment strategies, detect anomalies in real time and trigger corrective actions automatically. This is one of the most needed evolutions of static oversight to adaptive control. ### 4. Conversational AI and Agentic Optimization A particularly transformative development is the emergence of conversational AI interfaces and autonomous agents in cloud cost management. In traditional workflows, teams pull reports, filter dashboards and manually analyze cost drivers across multiple tools. This process slows decision-making and limits responsiveness. With Conversational AI, teams can query cloud financial data using natural language, receive real-time analysis and obtain guided recommendations instantly. More advanced agentic systems go further - applying ## Drive Cloud Cost Efficiency with Native Capabilities While external platforms accelerate optimization, significant gains can be achieved by leveraging native cloud services, engineering practices and FinOps discipline without introducing additional operational overhead. ### Instrumentation and Cost Attribution Establish granular tagging across compute, GPU workloads, models, endpoints and teams. Build metrics such as cost per inference, token and training job to enable precise visibility and accountability. ### GPU and Workload Efficiency ### Cost-Aware AI Architecture Implement model routing, inference batching and caching strategies. Match workload complexity to model size to balance accuracy, latency and cost per request. ### Native Automation and Guardrails Use built-in policies for budget controls, anomaly detection and idle resource shutdown. Enforce limits on experimental environments to prevent uncontrolled spend. ### Governance and Organizational Policies Define clear ownership of AI spend across teams, with approval workflows for high-cost workloads and experiments. Establish budget thresholds, usage policies and ### Integrated FinOps and Engineering Workflows Embed cost monitoring into CI/CD pipelines and operational dashboards. Align engineering, finance and operations teams through shared KPIs and continuous optimization cycles. ## From Cost Control to Economic Performance Cloud cost optimization is often framed defensively - as a way to prevent overspending. But in an AI-driven world, optimization is strategic. Two organizations may deploy similar AI models. The one that achieves higher GPU utilization, smarter model routing, tighter token efficiency and automated financial governance will operate at a materially lower cost per outcome. That organization can reinvest savings into innovation, scale faster and price more competitively. AI is both increasing the complexity of cloud economics and providing the mechanism to manage it. Enterprises that embed In the coming years, competitive advantage will belong not just to those who build the most advanced models, but to those who operate them most intelligently. A successful AI-powered optimization strategy can define that difference.​​ The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 06 Feb, 2026 | 5 Min read # How To Optimize Cloud Costs In 2026 Deepak Mittal Founder and CEO After years of rapid scaling fueled by digital transformation and AI-driven workloads, organizations in 2026 are under pressure to become more financially disciplined. Cloud spending continues to increase - especially with the surge in GPU-heavy AI training and inference workloads - yet financial leaders are demanding more predictable budgets and stronger ROI. This doesn’t imply a slowdown in innovation. Instead, companies need a smarter, more data-driven model to align engineering velocity with financial outcomes. Below, we unpack five practical cloud cost challenges most companies face and explain how modern approaches can mitigate them without compromising performance or customer experience. ## **1. Cloud Waste** Cloud waste remains one of the biggest contributors to overspending, largely due to idle resources, oversized infrastructure, zombie assets, and insufficient provisioning strategies. According to 2025 industry estimates from ByteIota, organizations waste nearly 30 - 32% of their total cloud spend, amounting to $200–230 billion annually - largely due to idle resources, over-provisioning, and inefficient pricing decisions. ## **Solution** Organizations must rely on real-time cost visibility and automated remediation to control waste. Advanced AI-powered cost analytics platforms can provide resource-level insights, predict right-sizing opportunities, detect anomalies instantly, and automatically shut down idle workloads. Combined with consistent tagging standards and clear team ownership models, these capabilities enable engineering teams to ## **2. Difficulty in Predicting Long-Term Cloud Requirements** Forecasting cloud requirements has become even more challenging in 2026 as workloads grow more dynamic, AI models introduce unpredictable GPU needs, and architectures evolve across multi-cloud, hybrid, and edge environments. Even sophisticated forecasting models cannot This uncertainty often leads to over-buying commitments, under-utilizing Savings Plans, relying on expensive on-demand pricing, or making architecture decisions based on assumptions rather than data. ## **Solution** The better approach is to shift from long-term forecasting to smarter and more controlled provisioning. Organizations should begin by establishing a ## **3. Choosing the Right Cloud Services** With hundreds of different options, even experienced cloud practitioners often find it difficult to Choosing the wrong combination of instance types and sizes can easily introduce persistent cloud cost inefficiencies and business risks. ## **Solution** Organizations need a balance of business context and technical intelligence when selecting services. Decisions should take into account deployment goals around latency, reliability, and performance; cost-to-value metrics such as cost per transaction, inference, or customer; the operational capability needed to manage the chosen service; and the long-term implications of pricing models and vendor lock-in. ## **4. Lack of Performance Tracking and Benchmarking** Without performance benchmarking, it becomes nearly impossible to understand how resources are being consumed or whether the associated costs are justified. Tracking only CPU and memory is no longer sufficient in 2026. Modern cloud environments demand broader visibility that includes GPU utilization, cost per workload unit, storage access patterns, ## **Solution** Organizations must adopt real-time monitoring and centralized dashboards that consolidate performance, cost, and utilization metrics. Native tools like AWS Cost Explorer, Azure Cost Management, or GCP Billing offer foundational insights, but they should be supplemented with continuous logging, audit trails, and Kubernetes cost monitoring tools such as Kubecost or ## **5. Lack of Organizational Alignment** FinOps is a collaborative discipline, yet many organizations continue to operate in silos. When engineering, finance, and procurement teams work independently, communication gaps widen, cost decisions become reactive, and architectural choices often conflict with budget expectations. The FinOps Foundation continues to identify this cultural misalignment as one of the most significant challenges in ## **Solution** To overcome this, organizations must cultivate shared responsibility for cloud spend. This begins with bringing finance, engineering, procurement, and leadership together under a unified FinOps framework based on the Inform, Optimize, and Operate phases. Teams should follow consistent reporting practices, rely on showback dashboards, and participate in regular cross-functional FinOps reviews. ## **Harnessing the Power of Collaboration** Cloud cost optimization is not a one-time project but an ongoing discipline that evolves with workloads, business needs, and industry innovation. Every organization has unique priorities, making it essential to adopt an approach that combines real-time visibility, automation, governance, and cross-team collaboration. A well-structured FinOps function - whether built internally or supported by an experienced external partner - can help organizations navigate complex pricing models, manage commitments effectively, **This article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 26 Aug, 2025 | 5 Min read # How Startups Can Keep Cloud Costs from Wrecking Their Budget Naman Jain Chief Growth & Marketing Officer As a startup, you are already juggling product development, investor expectations, and the pressure to grow fast. Cloud costs may not feel like the top priority, until a sudden costly bill creates tough discussions in the boardroom. According to Gartner, by 2025 almost 60% of cloud spending could be wasted. I have seen many startups shocked when their cloud costs jump by 30 - 40% in a single month, eating into the cash that was meant for growth. For example, if a startup spends $50,000 a month on cloud, nearly $30,000 can go waste due to inefficiencies. That same money could have been used to hire people or extend the runway. If not controlled, these costs hurt investor confidence and slow down execution. This is why Cloud Cost Management should be among the top three priorities for any startup - because in addition to saving money, it also helps build a strong base for growth and manage expenses without sacrificing innovation. ## Why Cloud Costs Spiral Cloud expenses are often unpredictable, or you could even say sneaky, as they catch even experienced teams by surprise. Studies show that almost 27% of cloud budgets are wasted on idle resources - like servers left running after a sprint or test environment. Many startups end up losing 20 - 50% of their cloud spend simply due to poor monitoring, which can be a big blow for early-stage companies. Another issue is the complex pricing models of cloud providers. Platforms like AWS, Azure, and Google Cloud follow a pay-as-you-go method, but their pricing comes with multiple tiers, add-ons, and hidden charges. For example, Egress Fees - the cost of moving data out - can take up nearly half of your bill, especially for data-heavy applications. Reserved Instances or Savings Plans look attractive with their discounts, but they demand long-term commitments. This is risky for startups where usage is uncertain. If you miscalculate, you may end up with costly unused resources or sudden bill spikes. Vendor lock-in makes it worse, since moving away from one provider becomes expensive and complicated, forcing you into a cycle of rising expenses. Operational habits also add to the waste. In the rush to launch features quickly, efficiency often gets ignored. Developers over-provision resources to avoid performance issues, while finance teams set strict budgets without fully knowing technical needs. This lack of alignment creates friction and results in wasted spending. ## The Cloud Cost Control Playbook Here are some practical steps to bring discipline to your spending while keeping your startup ready to scale: ### **1. Establish Clear Accountability** A lot of money is wasted on unclaimed resources like servers, storage, or databases that are left running without any workloads. To avoid this, make sure every resource is tagged and assigned to someone. Use ### **2. Streamline with Automation** Making infrastructure changes manually is slow and often leads to mistakes. As a result, teams keep using oversized setups instead of adjusting them. Automated CI/CD pipelines help scale resources up or down as per demand. Many startups have reduced costs by up to 20% by using automation for scaling, as it matches infrastructure with real usage. Automation keeps things efficient and prevents unnecessary spending. ### **3. Foster Team Alignment** Keeping costs under control depends on collaboration. FinOps as a practice is still new, and most startups cannot afford full-time specialists. Finance teams understand money but not cloud architecture, while engineers know the cloud but rarely look at costs. This gap often leads to issues being noticed only after a high bill arrives. Regular _**Community Insight:** _ _is doing rounds in the startup communities, where a founder explained how getting finance and engineering to work together saved them more than any tech tweak. It turned into a goldmine of tips, with other founders chiming in on tricks for taming cloud bills and scaling smarter. It’s a great thread to pick up practical ideas from startups hurdling with the same issues - definitely worth a quick scroll._ ### **4. Make the Most of Free Credits** Cloud providers give huge credits for startups - for example, AWS offers up to $100,000, Microsoft $150,000, and Google $350,000. But many founders use these credits too early or without a plan. The smart way is to use them at the right time, especially during growth stages, so they help reduce costs when spending is high. By carefully spreading these credits across key milestones, startups can extend their runway. Think of credits as a financial tool, not just a freebie. ### **5. Leverage Partner Expertise** Enterprise-level cloud support usually comes at a high cost. However, AWS, Azure, and Google have special startup programs where partners provide support at a much lower price. These partners offer ### **6. Combine Technical and Financial Tactics** Technical steps like rightsizing instances, using spot pricing, or optimizing storage are important, but they are not enough on their own. The real impact comes when you combine these with financial practices like proper visibility, team alignment, and smart credit usage. Together, this approach can save up to a third of your costs while still supporting growth. It helps you balance both performance and savings as your user base expands. ## **The Stakes and the Opportunity** Uncontrolled cloud costs affect more than just your budget. They can lower team morale and even shake investor confidence. Studies show that when cloud bills suddenly rise by 50% or more, almost 75% of employees start worrying about job security. By managing costs proactively, startups can save up to 25% almost immediately. This extra money can be used to support your existing team, hire more talent, extend your runway, or invest in new growth plans Beyond savings, disciplined cloud management enables sustainable scaling. For cloud leaders, this shift in how you go about leveraging cloud could be the core driver of success. Start now: tag resources, automate scaling, align teams, and tap into credits and partner support. Check out that reddit thread for real-world insights from founders. This could very well give you the one superpower every startup needs - the ability to innovate without fear of financial instabilities. **This article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 13 Nov, 2024 | 4 Min read # How to tackle the impact of inflation & energy costs on cloud pricing The global economy has been on a rollercoaster over the past few years, navigating through challenges like the pandemic and geopolitical conflicts. These disruptions have triggered inflationary pressures and soaring energy costs, leaving businesses to adapt to an unpredictable landscape. Although inflation is showing signs of easing—projected to fall from 6.8% in 2023 to 5.9% in 2024 and down to 4.5% by 2025—the overall growth outlook remains tepid, particularly for emerging markets. The energy sector tells a similar story. Despite some relief in global energy prices, electricity demand is expected to rise by about 4% in 2024, contributing to sustained pressure on industries worldwide. Among the most affected sectors is cloud computing, where inflation and rising energy costs are the major factors driving operational expenses and ultimately, cloud service pricing. ## The Cloud Impact Cloud data centres require vast amounts of energy to power and cool their infrastructure. While inflation and energy costs have slightly eased, cloud providers may not experience the same relief as other industries due to the long-term contracts they often sign for energy and resources. These contracts can lock providers into higher expenses, leading to elevated operational costs that are passed on to customers. Labour costs have also surged, driven by a shortage of skilled talent in critical IT roles. Additionally, the costs of producing CPU and memory chips have faced spikes, further increasing cloud prices. Cloud providers have been forced to adjust their pricing structures to offset these rising expenses. Gartner reports that for the first time, price hikes—rather than increased usage—are driving cloud cost inflation. This reduces the funds that companies might otherwise allocate to innovation projects. A recent survey revealed that three out of five businesses saw their cloud spending rise, with nearly 40% experiencing cost increases of over 25%. The growing demand for AI technologies has also significantly contributed to these price surges. Cloud cost management has become a top priority for IT leaders, pushing enterprises to adopt cloud optimization strategies to remain competitive amidst financial pressures. PS: You might have noticed 'shrinkflation' hitting tech services too. Ever seen SaaS providers offering fewer features for the same price? Rising cloud costs could be part of the reason behind this trend. ## **Your Move Now** While many of the factors that cause the cloud cost surge would be beyond our control, what we can do is optimize our cloud infrastructure for better cost-to-performance numbers. Here are some strategies to reduce cloud costs: **Architectural Changes** By optimizing how workloads are deployed, stored, and scaled, businesses can make significant savings. This might include refactoring applications to be more cloud-native, using containerization, or adopting technologies like serverless computing models. Another cost-saving strategy is switching from traditional x86 processors to ARM-based alternatives. Cloud providers like **Discount Programs** Most cloud providers offer various volume and usage-based discounts that can significantly reduce your costs for a certain commitment. Take advantage of these discount programs to ensure you’re not overspending on the pay-as-you-go models. **Prioritizing Cloud Economics** Cost management should be an organization-wide discipline. **Continuous Optimization** Regularly monitoring your cloud infrastructure helps you find multiple opportunities for cost and performance optimization. By fostering a culture of continuous optimization, you can eliminate wasted resources, reduce underutilization, and maximize the value of your cloud investments. **Optimizing Cloud Usage for AI** To efficiently strike a balance between cloud costs and AI innovations, organizations should focus on right-sizing resources and selecting the right instance types for model training. Efficient data management, selection of appropriate AI services, and careful GPU usage are also crucial strategies for minimizing expenses. **Conclusion** Global forces are significantly shaping the business landscape, making it essential for organizations to innovate, especially as AI and other technologies become more prominent. By effectively managing your cloud costs, you can save both time and money, allowing for a more streamlined strategy Whether you choose to build an in-house FinOps team or partner with a cloud cost optimization expert, implementing a robust cloud FinOps strategy will enable you to navigate these troubled waters. Striking the right balance between innovation and costs is the best way to tackle "cloud-flation." **This article was originally published on** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 29 May, 2026 | 5 Min read # The real infrastructure challenge behind generative AI adoption Aman Aggarwal Chief Operating Officer Then Generative AI arrived - and the whole thing got a lot more interesting. ## **The Numbers Tell the Story** The scale of what's happening to cloud infrastructure is hard to overstate. According to Synergy Research Group, global cloud infrastructure revenues hit $106.9 billion in Q3 2025 alone - a 28% year-on-year increase and the first time quarterly cloud spend ever crossed the $100 billion mark. And the fuel behind this surge? Gen AI. GPU-as-a-Service revenues alone grew more than 200% year-on-year in that same quarter. On the hardware side, the numbers are even more striking. IDC's Worldwide Quarterly AI Infrastructure Tracker found that organizations increased By 2029, IDC forecasts the global AI infrastructure market will hit $758 billion. Gartner projects that Gen AI model spending is expected to grow 80.8% this year alone. This is a huge step-change in how cloud infrastructure gets used, while most cost management practices haven't caught up yet. ## **Why Gen AI Breaks the Old Playbook** The challenge with Gen AI infrastructure isn't just that it's expensive. It's that it's expensive in ways that are hard to predict and harder to control with traditional approaches. For years, cloud cost optimization was built around fairly well-behaved workloads. A web server has stable CPU needs. A database scales in line with transactions. You could model it, budget for it, and manage it with the FinOps tools that existed at the time. Most AI infrastructure today also runs in cloud environments. In fact, cloud and shared infrastructure account for about 84% of global AI infrastructure spending, with hyperscalers driving the majority of it. For most enterprises, the question is no longer whether ## **The Paradox: The Same Technology Is Also the Solution** Here is where the story takes a turn I find genuinely exciting - not as a talking point, but based on what we're seeing in practice. The same AI technology that is increasing infrastructure complexity is also becoming one of the most effective tools to control it. Instead of analyzing last month’s bill, these systems can observe workloads in real time and recommend or trigger corrective actions. However, organizations that manage AI infrastructure costs effectively combine this capability with the right tooling and operational practices. ### **Observability and Monitoring** * GPU utilization monitoring at the workload level, not just the instance level, using tools such as Grafana, AWS CloudWatch, or Google Cloud Monitoring configured for accelerator metrics. * Real-time spend dashboards that surface idle or underutilized capacity before it compounds into a large invoice. * ### **Infrastructure and Workload Optimization** * Traffic-aware autoscaling on Kubernetes based on actual workload patterns rather than static provisioning. This approach can significantly reduce infrastructure usage for agentic workloads. * Model routing that * Spot and preemptible instance strategies for bursty training workloads, while reserving committed capacity for stable inference demand. ### **Financial Governance** * Continuous commitment optimization using AI to evaluate whether * Workload tagging and ownership assignment before deployment so cloud costs can be traced to teams and business outcomes. * Multi-cloud cost comparison across AWS, Azure, and Google Cloud to identify pricing advantages and improve negotiating leverage. What makes this different from earlier generations of cloud optimization tools is the move from advising to acting. An AI agent that flags an idle GPU cluster can also take action, shift workloads, or trigger a response with enough context to make the fix immediate. IDC forecasts that AI platforms spending will grow at a 48.5% CAGR through 2027, driven largely by the rise of Agentic AI systems and their ability to orchestrate complex infrastructure decisions autonomously. ## **What This Means Right Now** The old model of cloud cost management - periodic reviews, manual rightsizing, static budgets - is not built for this environment. It's not wrong, it's just too slow. The right response isn't to pump the brakes on The organizations that pair Gen AI or Agentic AI with intelligent infrastructure management are the ones that will actually see returns from it. Those that don't will find their cloud bills growing faster than their business outcomes. The feedback loop - AI managing the cost of running AI - is where the next generation of cloud efficiency gets built. The companies that figure this out early will spend smarter, scale faster, and turn infrastructure discipline into a genuine competitive advantage. The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 29 Apr, 2026 | 5 Min read # Rethinking Cloud Cost Governance in the Age of AI Sanjeev Mittal Chief Product and Technology Officer Cloud spending rarely becomes a challenge because of the lack of data. It becomes a challenge because decisions lag behind usage. By the time teams identify a spike, the cost has already been incurred. Visibility exists, but often too late to influence outcomes. This is where AI is starting to make a measurable difference. Instead of only explaining what has already happened, it allows teams to anticipate patterns, detect deviations earlier, and act before inefficiencies compound. ## **AI moves closer to core CloudOps** The pace of AI innovation continues to accelerate, with AI is becoming embedded within cloud operations themselves. It is increasingly influencing how workloads are placed, how resources are allocated, and how cost deviations are identified. In many environments, these decisions are no longer entirely manual. A growing class of systems now allows teams to interact with cloud cost data more intuitively, shifting from static dashboards to more dynamic, conversational ways of understanding spend and performance. ## **From reactive management to sustainable control** For a long time, cloud cost management has been reactive. Teams would spot an issue, fix it, and then move on to the next one. That approach is beginning to transition. AI systems today can It doesn’t eliminate the need for human oversight but it does reduce the constant firefighting. ## **Translating data into timely action** Most FinOps teams are already dealing with huge volumes of data like billing reports, usage dashboards, and performance metrics. The challenge has always been making sense of it quickly enough to act. This is where AI helps in a practical way. Instead of waiting for monthly reviews, teams can start spotting cost anomalies much earlier. Often, these insights are tied back to actual business activity, which makes them more useful. In practice, this means decisions can be taken faster, and with more context. Rather than exporting reports and stitching insights together, teams can ## **Optimizing multi-cloud environments** As more organizations move toward multi-cloud or hybrid setups, things naturally get more complicated. Different providers, different pricing models, different performance benchmarks, it adds up quickly. AI is particularly useful in handling this kind of complexity. It can compare environments, suggest where workloads might run more efficiently, and point out resources that are either underused or too expensive. Increasingly, these decisions go beyond cost alone, incorporating It’s not a one-time fix. In most cases, it becomes an ongoing process of small, continuous optimizations. ## **From insights to execution** One of the more important changes is not just how insights are generated, but how quickly they can be acted upon. Modern FinOps practices are moving toward continuous loops where inefficiencies are identified, evaluated, and addressed with minimal delay. AI enables faster detection and recommendation, but sustained impact depends on consistent execution. Organizations are increasingly building systems that ## **Challenges in AI-Driven FinOps** The effectiveness of AI-powered cloud optimization systems depends heavily on the quality of data. Incomplete or inconsistent inputs can lead to unreliable recommendations. There’s also the issue of context - AI might suggest cutting costs somewhere without fully understanding how critical that workload is. Another concern is transparency. Many AI systems don’t clearly explain how they arrive at certain decisions, which can make teams hesitant to rely on them completely. Over-automation also carries risk, where incorrect decisions can scale quickly if left unchecked. And of course, over-automation can backfire. If something goes wrong, it can scale quickly. This is why most organizations are still leaning toward a balanced approach - using AI for insights, but keeping humans in the loop for final decisions. ## **The Human–AI collaboration** AI works best when it complements human expertise, not replaces it. By taking over repetitive and time-sensitive tasks, it gives teams more space to focus on planning, optimization, and larger strategic decisions. At the same time, human judgment helps ensure that decisions actually make sense in a real business context. It’s this combination that tends to deliver the best outcomes. Many organizations are also combining AI-driven systems with ## **Closing the Loop: From Visibility to Governance** AI is changing how teams manage cloud costs in a very practical way. What used to be a monthly review is now becoming something more continuous and hands-on. This matters even more as AI workloads grow. Their costs don’t behave like traditional infrastructure. They fluctuate with usage, depend on model choices, and often tie directly to performance decisions. Managing them requires faster feedback loops and better coordination between teams. Many organizations are responding by simplifying how they operate. Instead of juggling multiple tools and reports, they are moving toward connected systems that bring visibility, insights, and action closer together. AI is helping make that possible. Teams can explore cost data more easily, understand what is driving spend, and act sooner. At the same time, experienced judgment still plays a key role in deciding what to change and when. And in the long run, the organizations that get this balance right, between AI capabilities and human judgment are likely to be the ones that extract the most value from their cloud investments. This article was originally published on**** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 14 Jan, 2025 | 3 Min read # Six Trends to Watch Out in the Cloud Cost Optimization Space in 2025 According to Gartner, end-user spending on cloud services is expected to skyrocket from $595.7 billion in 2024 to an astounding $723.4 billion in 2025 - a staggering 21.5% increase. Simultaneously, the importance of cloud financial management is on the rise. A recent Everest Group survey reveals that the FinOps market, valued at $5.5 billion, is set to grow at an impressive CAGR of 34.8% through 2025. This article explores six future trends set to shape the cloud cost optimization space, helping businesses prepare for what’s ahead. ## **1. Focus on Long-term Cost Optimization Goals** As cloud adoption matures, organizations are shifting their priorities from short-term savings to a more sustainable and strategic approach i.e. Short-term cost-saving measures often lack scalability and limit investments in new technologies. By adopting a long-term mindset, businesses can unlock greater operational efficiency and scalability. ## **2. Rise of Multi-Cloud and Hybrid-Cloud Setups** Businesses seem to be moving towards having ## **3. Intelligent Resource Allocation with AI and ML** ## **4. Serverless Computing and Cost Efficiency** Serverless computing, with its pay-as-you-go model, is revolutionizing cost efficiency by eliminating server management and cutting overhead costs. Emerging trends include event-driven architectures for dynamic scaling, advanced monitoring tools for granular cost insights, and hybrid serverless solutions that combine on-premises and cloud services. ## **5. Sustainable Cloud Computing** ## **6. Demand for End-to-End Cost Optimization Providers** An Everest Group survey reveals that many automation-driven FinOps tools fall short of expectations, fueling the demand for more integrated solutions. Businesses are increasingly turning to end-to-end cloud cost optimization providers who offer a complete suite of services across the FinOps lifecycle. These comprehensive partners are becoming essential for organizations seeking a holistic approach to managing and ## Conclusion The future of cloud cost optimization is shifting towards long-term savings rather than quick fixes. Trends like the integration of Generative AI into workflows, serverless computing, and hybrid cloud strategies will play a key role in reducing costs while supporting sustainability goals. Additionally, the growing demand for end-to-end cloud cost optimization providers reflects the need for comprehensive solutions that cover every stage of the FinOps lifecycle. By adopting these trends, businesses can not only optimize cloud costs but also align their operations with environmental and business goals, preparing for a more resilient and efficient future. By Deepak Mittal, CEO and Founder of CloudKeeper. This article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 30 Jul, 2025 | 4 Min read # Startups Chasing Growth? Don’t Let Cloud Waste Undermine Valuations A recent analysis by Andreessen Horowitz, a prominent Silicon Valley VC firm, revealed something surprising – infrastructure costs have quietly climbed to become one of the largest expenses in modern startups. In some cases, cloud spending was eating up over 50 per cent of the cost of goods sold (COGS). Now combine that with this: Investors have pulled back. Capital isn’t as cheap as it was. Valuations are under pressure. And in boardrooms, every rupee spent on infrastructure is being scrutinised. As a founder chasing growth, the last thing you want is to lose investor confidence over something as fixable as cloud waste. But it happens. All the time. There was a popular case not long ago where a startup accidentally ran up a **$450,000 GCP bill overnight** due to a misconfigured script. They caught it late. The business had to halt new hires and product releases for a quarter. Sounds dramatic? It’s not rare. Startups often begin with a “move fast” mindset, which is essential in the early stages. But when growth starts compounding, so do infra bills. Without proper checks, your cloud spend quickly moves from being a small line item to a valuation-dragging liability. VCs today don’t just look at the ARR. They look at gross margins, burn multiples, and cloud economics. Poor infra hygiene is now a red flag. Earlier, startups could afford to be inefficient for longer. Raise, spend, scale, and worry about profitability later. But the market has changed. Investors now expect lean growth. John Curtius, ex-Tiger Global partner, said it best: _“Every startup I talk to now wants to cut infra. It’s the first thing they look at after headcount.”_ And this shift is healthy. Infrastructure is not just a technical concern anymore. It directly influences financial metrics and strategic flexibility. Especially for industries like SaaS or HealthTech, where infrastructure usage can grow exponentially. So if your cloud is growing faster than your business, there’s a problem. Here’s what smart startups are doing to stay lean, improve margins, and make their infra spending investor-friendly: ## **1. Start with the architecture discipline** Use the right services, right instance types, and align your infra to actual workload needs. Overengineering early leads to cost sprawl. Get expert guidance, even if it’s on demand. ## **2. Build FinOps from Day 1** FinOps is not just for big enterprises. Even seed-stage startups benefit from visibility into cloud spend, unit economics, and usage patterns. Use tools or experts to track and report regularly. ## **3. Right-size and autoscale aggressively** Avoid fixed-size provisioning. Use autoscaling, spot instances, and serverless where possible. It’s better to pay for usage than for idle capacity. ## **4. Set up budgets, alerts, and spend policies** Don’t wait to be surprised. Create cost boundaries and alert systems across teams. Involve developers in infra costs to drive accountability. ## **5. Don’t oversubscribe to cloud discounts** Committed use discounts (like AWS Savings Plans or GCP CUDs) can help, but only if used carefully. Overcommitments can become sunk costs when workloads change. ## **6. Enable multi-cloud optionality** You don’t have to go multi-cloud early, but build portable architectures. Avoid provider lock-in, which can reduce your negotiation power and impact future infra decisions. ## **7. Work with cloud cost optimisation partners** Third-party cloud experts can help you across all 3 layers – usage optimization, rate optimisation and visibility & reporting. Many also offer CloudOps support to handle day-to-day operations and infra governance while your team focuses on shipping features. Here’s a simple math: If your gross margin drops from 80% to 60% because of infra bloat, your valuation could fall 30 – 40% in the next round. Not because your product is bad. But because your cost structure is broken. **Investors will ask: Why didn’t you catch this earlier?** The hard truth? No one gives you extra credit for using the cloud. But you’ll definitely lose points for using it poorly. Cloud adoption continues to grow, with global public cloud spending forecasted to hit $723.4 billion in 2025. But this growth comes with a caveat: nearly 30–34% of cloud budgets go to waste. That’s not a margin early-stage startups can afford to ignore. The good news? Startup funding is showing signs of life again. According to Tracxn, the first half of 2025 saw a 4% increase in global VC funding compared to H1 of 2024 – the first uptick in two years. AI, digital health, SaaS, and fintech are leading the charge. This means the runway is opening up, but only for those who manage their fuel wisely. Avoiding cloud waste is no longer about saving money. It’s about building valuation, improving capital efficiency, and preparing to scale on solid ground. **This article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 29 May, 2025 | 4 Min read # Sustainable Cloud Computing Isn’t Just Greener - It’s Cheaper! Aman Aggarwal Chief Operating Officer Imagine this: Right now, as you read this page, you're contributing to carbon emissions - simply by being online. A single webpage visit can emit up to 2 grams of CO₂, depending on the content and hosting infrastructure. Over the course of a year, that adds up enough to melt a few ice cubes off a distant glacier (and yes, it adds up faster than you’d think). But here’s the twist: If the cloud system hosting this page is powered by green cloud computing, those emissions can drop dramatically, in some cases by up to 98%. No melted glaciers. Minimal emissions. Now you understand the effect. ## Why Sustainable Cloud Strategy Matters More Than Ever Let’s be real - cloud isn’t the new kid on the block anymore. From powering AI models to handling global e-commerce traffic, the cloud’s scale has exploded. But so has its environmental footprint. By now, most of the big cloud providers have made bold climate pledges. Microsoft plans to be carbon negative by 2030, Google’s gunning for 24/7 carbon-free energy by the same year, and Amazon wants to hit net-zero emissions by 2040. These are ambitious, game-changing goals — but they only get us part of the way there. The rest? That depends on how you use the cloud. Because even the greenest datacenter can’t help if your workloads are inefficient, your resources are overprovisioned, or your teams aren’t optimizing usage. Sustainable cloud computing isn't just the provider’s job, it's a shared responsibility. And the good news? There are smart, proven ways to do your part and save costs while you’re at it. Here are some best practices you can implement for ‘green computing’ while optimizing your cloud usage * **Start with the right cloud partner** AWS, Azure, and Google Cloud aren’t just competing on uptime anymore - they’re racing to decarbonize. From 100% renewable matching to carbon-negative goals, your choice of provider now plays a starring role in your sustainability journey. Start here. Pick a cloud that walks the talk. * **Go beyond virtualization - think Containers** Virtual machines laid the groundwork. Containers take it further. By packing applications into lighter, * **Embrace Serverless for leaner operations** Serverless computing eliminates the always-on infrastructure trap. You only run code when it's needed, which slashes idle time and energy waste. Bonus: It also simplifies ops and accelerates dev cycles. * **Let Automation do the scaling** Auto-scaling - especially when driven by real-time data or AI - ensures you're not overprovisioning. No more spinning up resources “just in case.” You scale only when demand spikes, keeping both emissions and bills in check. * **Optimize what you build, not just where you run it** Software matters. Lightweight code. Efficient algorithms. Clean architecture. All of it reduces compute strain. Instead of throwing more cloud at a performance problem, smart teams are optimizing their apps to do more with less. * **Process data where it happens (Hello, Edge Computing)** Why send terabytes to a data center when you can process it closer to the source? Edge computing trims latency, boosts responsiveness, and reduces the energy footprint of data transport — especially useful in IoT, manufacturing, and retail. * **Make data your superpower** By ## **The Double Win** Cloud sustainability isn’t just about doing the right thing for the planet. It’s also about building smarter, more efficient businesses. Thus, the right green practices help you hit two birds with one cloud strategy: **Financial Sustainability** When you trim the excess - unused instances, overprovisioned storage, and idle compute, your cloud bills shrink fast. With tools like auto-scaling, serverless, and containerization, you’re essentially minimizing cloud waste. And that means more room in the budget for innovation. **Operational Sustainability** Cleaner, optimized workloads run faster, fail less, and adapt better. Dynamic resource allocation, virtualization, and energy-aware development practices give your systems the agility they need to scale without burning through energy or engineering hours. ## Final Thoughts: Embrace Green Computing for a Better Future Globally, 25% of physical servers and 30% of virtual servers are considered “zombie” - inactive for at least 6 months. That’s an estimated 10 million idle servers, costing businesses around $30 billion - not including energy and operational costs. Think about that - billions lost in cloud spend and massive energy waste, just because resources weren’t monitored or optimized. The point? Optimization is sustainability. And again, sustainability and profitability aren’t at odds - they’re part of the same conversation. The teams that get this right won’t just reduce emissions; they’ll build stronger, more future-ready cloud foundations. In a world where every byte has a footprint, the smartest cloud strategies are the greenest ones. Let’s course correct towards the right direction - by minimizing cloud waste and smarter provisioning. **The article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 01 Jun, 2025 | 4 Min read # Unlock Hidden Cloud Savings with CloudKeeper’s 30-Day Cloud Fitness Challenge Magazine Contributor What if your "fully optimized" AWS environment is leaking six-figure sums annually? With a five-minute setup and zero financial risk, this initiative isn’t just another optimization pitch; it’s a wake-up call for enterprises who are convinced they have maximized their cloud efficiency. For engineering leaders balancing innovation with fiscal responsibility, the challenge offers a no-strings audit that could rewrite their cloud cost narrative overnight. “We’ve worked with 2000+ AWS environments, and even the ones labeled ‘fully optimized’ had six-figure savings left untouched. This challenge is our way of helping teams uncover what they’ve been missing, while keeping the process fun and engaging.” said CloudKeeper’s CEO Deepak Mittal. "I am excited to see what results they’ll unlock along the way." ## The Myth of “Good Enough” Optimization Most cloud teams operate under a dangerous assumption: Don't fix it if it ain’t broke. But CloudKeeper’s analysis reveals that the majority of businesses miss nearly a quarter of potential cloud savings. These are not theoretical gaps. The root cause lies in competing priorities. DevOps teams juggle feature launches, incident response, and security patches while tasked with cost oversight. "Startup founders often tell me they budgeted for infrastructure but didn’t anticipate the operational tax of constant optimization," shares Mittal. This friction creates optimization fatigue, where teams settle for “good enough” rather than pursuing peak efficiency. ## Five Minutes to Fiscal Clarity CloudKeeper sets itself apart through its exceptional speed. While traditional audits can take weeks, CloudKeeper delivers a detailed cost analysis just minutes after connecting an AWS account. Its read-only access model ensures no security risks during the scan, covering over 50 resource types, from overlooked Elastic Block Store volumes to incorrectly configured Lambda functions. The entire process flows through three distinct phases. It begins with discovery, where the platform automatically identifies idle resources, overprovisioned instances, and inefficient pricing models. This is followed by diagnosis, using a proprietary scoring system that evaluates each resource’s cost efficiency, alignment with performance goals, and environmental sustainability. The final stage is prescription, during which CloudKeeper generates custom optimization playbooks. These recommendations prioritize both rapid, high-impact changes like removing unattached storage and longer-term strategies such as planning reserved instances. ## The Engine Behind the Challenge A key component behind the 30-Day Cloud Fitness Challenge is CloudKeeper Tuner, the automated platform for identifying and enabling ongoing Tuner continuously analyzes AWS resource usage, looking for patterns such as underutilized instances, redundant storage, or missed opportunities for rightsizing. Rather than relying on periodic checks, it supports a real-time, iterative approach, helping teams make small, incremental adjustments that compound over time into significant savings. The platform integrates directly with AWS accounts using read-only access, allowing organizations to assess their infrastructure without interrupting day-to-day operations. Over time, Tuner helps establish a culture of continuous optimization by reducing reliance on ad hoc reviews and offering clear, data-driven recommendations for cost and performance improvements. In early usage, many organizations have reported finding additional savings opportunities, even after implementing standard optimization practices, highlighting the platform’s ability to surface issues that may not be immediately visible through conventional methods. ## Proof Over Promises Skepticism is natural when it comes to cloud cost management - but CloudKeeper is addressing it straight forward. Through the challenge, the company aims at least 10% additional savings on the total cloud bill. Participants not only stand to reduce costs but also receive exciting rewards just for registering. CloudKeeper backs its claims with a track record of Mittal summarizes the ethos: "This is all about revealing what’s humanly impossible to track at cloud scale. Even our engineers are surprised by the findings." ## The New Optimization Mandate As cloud environments grow in complexity, static audits become obsolete. CloudKeeper’s challenge introduces the continuous optimization concept, gaining traction among FinOps practitioners. Participants receive real-time alerts for new inefficiencies, turning cost management from a quarterly chore into an always-on discipline. The stakes have never been higher. With AWS dominating 32 percent of the cloud market and workloads multiplying, unchecked spending threatens to derail innovation budgets. For teams ready to confront their blind spots, the 30-Day Challenge provides more than savings- it offers a blueprint for sustainable cloud growth. Registrations for the challenge remain open, but the clock ticks louder than any of those budget alerts. The article was originally published on **.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 21 Jul, 2025 | 4 Min read # Why 400 Global Companies Trust CloudKeeper's No-Commitment Savings Model CloudKeeper has quickly become a game-changer for organizations struggling with the ever-growing challenge of cloud cost management. Serving over 400 clients across 15 countries, the company's success is rooted in its unique approach: combining group purchasing power, proprietary optimization tools, and expert advisory services to deliver end-to-end cloud cost optimization. With an average reduction of 20 percent in cloud spending for a wide range of customers, from startups to enterprises, CloudKeeper has demonstrated that cost optimization doesn't need to involve binding contracts or major operational disruptions. ## **Breaking Free from Traditional Cost-Cutting Constraints** Traditional cloud optimization models often lock businesses into rigid contracts or demand extensive access to their systems, presenting significant obstacles. The effectiveness of this model is evident in CloudKeeper's impressive growth. The company has seen more than 50 percent compound annual growth over four years, culminating in $200 million in annualized revenue in the last fiscal year. CloudKeeper's CEO Deepak Mittal shares, _"Our no-lock-in model is convenient and transformative. Customers retain full control while we optimize rates through aggregated purchasing power. The results speak for themselves."_ ## **Precision Engineering Meets Financial Visibility** CloudKeeper's technological ecosystem addresses all three critical pillars of cloud cost management: rate optimization, usage efficiency, and cost visibility. As an end-to-end cloud optimization provider, CloudKeeper goes beyond fragmented solutions by combining software, services, and savings into a unified offering. ## **Scaling Trust Through Transparent Economics** CloudKeeper's SaaS-like model ensures a combination of light-touch service delivery and deep technical expertise. A team of over 100 certified cloud specialists diligently supports clients, driving exceptional operational efficiency that propels the company toward its ambitious financial goal of tripling its revenue by the fiscal year 2027. CloudKeeper continues to earn strong validation from both customers and industry analysts. With a 4.7/5 rating on G2 and 4.2/5 on Gartner Peer Insights, users consistently highlight the platform's effectiveness and ease of use. CloudKeeper has also been recognized for its leadership in cloud cost optimization across multiple 2024 industry assessments by leading analyst firms like IDC, ISG, Everest Group, and Forrester. ## **Adapting to Industry-Specific Cloud Demands** Although CloudKeeper serves clients across various industries, the company has also developed tailored solutions for sectors with particularly demanding cloud requirements. For example, "No two industries use the same cloud model—their architectures, workloads, and compliance needs all differ. That's why our solutions are designed to be flexible, adapting to what each business actually needs," says Mittal. ## **A Future Driven by Innovation and Efficiency** With its proprietary tools serving CloudKeeper's relentless focus on innovation, transparency, and customer-centricity drives the company's impressive growth and positions it as a leader in the evolving world of cloud cost optimization. Looking ahead, the company is doubling down on future-focused initiatives with a dedicated AI Center of Excellence exploring the use of Gen AI in cloud optimization. It is also investing heavily in Kubernetes and container management to unlock the next level of performance and efficiency. With this relentless focus on innovation and adaptability, CloudKeeper is not just solving today's cloud challenges—it's building the foundation for future-ready cloud computing. **This article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 29 May, 2025 | 4 Min read # Why Automation Is the Linchpin of Cloud Cost Optimisation Cloud spending continues its upward trajectory, with Gartner projecting global end-user spending on public cloud services to reach $723.4 billion in 2025, up from $595.7 billion in 2024. (Fun fact: Studies say – there will be 200 zettabytes (a trillion gigabytes) of data in the cloud in 2025). This surge is largely driven by the increasing adoption of AI and hybrid cloud strategies . Small and medium-sized businesses are also contributing to this growth, with projections indicating that over half of their technology budgets will be allocated to cloud services in 2025 . However, this rapid expansion brings challenges. The FinOps Foundation’s Our own research among customers echoes this sentiment. In a study of over 400 global cloud practitioners, spanning 2000+ cloud accounts, 97% of respondents were missing out on at least 23% of cloud savings due to inefficiencies, manual processes, and ## **Cloud Waste: The Hidden Drain on Enterprise Budgets** Let’s break it down: cloud waste refers to anything you pay for but don’t fully utilize- idle VMs, unused storage snapshots, overprovisioned compute, and Common culprits include: * Incorrect sizing of resources * Outdated instance types * Development environments running after hours * Excessive log or data retention Industry experts estimate that 30 – 40% of cloud resources are typically overprovisioned. That means for every $1 spent, $0.30–$0.40 is wasted. Idle resources alone are projected to account for $14.5 billion in global waste this year. And it’s not just inefficiency – it’s expensive. These errors are often the result of manual interventions, lack of ## **Why Manual Optimization Just Can’t Keep Up** The increasing complexity of cloud operations – fueled by the rapid integration of AI – has made manual In large enterprises with hundreds of accounts and services, relying on cloud teams to manually detect zombie resources, track cost spikes, and reconfigure infrastructure is a losing battle. It results in a reactive rather than proactive approach – one where optimization comes after the invoice shock. ## **Enter Automation: The Catalyst for Smarter Cloud Usage** Here’s how * **Zombie Resource Cleanup** : Automation engines scan for unattached volumes, idle * **Over-Provisioning Fixes** : Instances and volumes with excessive CPU or memory are resized based on usage patterns, helping rightsize infrastructure without compromising performance. * **Modernization:** When newer, more efficient instance types become available, the system identifies outdated ones and migrates workloads with minimal disruption. * **Scheduler-Based Shutdowns** : Automation helps enforce work-hour-based uptime for dev, test, or staging environments, ensuring off-hours don’t accumulate unnecessary costs or emissions. * **Spot Instance Automation** : For container workloads like These are all repeatable, scalable actions that would be nearly impossible to execute manually in a large, multi-account cloud landscape. ## **Rate Optimization: Let the System Do the Math** It doesn’t stop at usage. Automated platforms also bring intelligence to rate optimization – handling the complexity of This ensures that you’re not just consuming the right amount of cloud, but also paying the right rate for it. ## **From Dashboards to Autonomous Action** A lot of enterprises stop at visibility. Dashboards are great, but visibility without action is just observation. And perhaps most importantly, engineers finally get to spend less time firefighting and more time building. ## **Final Thoughts: Optimization Is No Longer Optional** The convergence of cloud sprawl, rapid AI adoption, and fluctuating pricing models has made manual cost optimization virtually obsolete. As a result, enterprises are bleeding billions in avoidable cloud spend, often repeating the same costly mistakes month after month. Recent research shows that organisations leveraging AI-driven resource allocation frameworks are achieving up to 40% cost savings over traditional approaches. Full-featured solutions now offer intelligent resource cleanup, dynamic provisioning, and real-time cost controls—embedded directly into engineers’ existing workflows. For today’s business leaders, the takeaway is clear: automated This article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 23 Apr, 2026 | 4 Min read # Why Cloud Efficiency Is Emerging as the Next Profit Lever for India Inc. Gaurav Barman Chief Revenue Officer - India For a long time, cloud decisions in Indian enterprises were driven by straightforward priorities such as pricing, performance, and scalability. That logic worked when workloads were predictable and growth was easier to model. Today, that equation is under pressure. AI adoption is accelerating across sectors, and with it comes a very different cost structure. Cloud is no longer a background enabler. It is increasingly tied to margins, pricing decisions, and the pace at which businesses can scale. As a result, leadership conversations are moving closer to a fundamental question: how effectively is ## India’s cloud momentum is unmatched India’s cloud momentum is undeniable. Estimates suggest cloud could contribute close to 8 percent of GDP, or roughly $380 billion, by 2026. At the same time, more than 75 percent of enterprises expect AI to reshape their business models. This combination of scale and ambition is pushing organizations to expand their cloud footprint rapidly, often across hybrid and multi-cloud environments. The opportunity is massive, but so is the responsibility to ## AI is making cloud economics harder to predict This growth is not coming with predictable economics. AI workloads behave differently from traditional applications. They rely on large volumes of data, require high-performance compute, and continue to incur costs long after deployment through ongoing inference. What appears manageable at the pilot stage can expand quickly when deployed at scale. Many organizations are already encountering unexpected spikes in their monthly bills, especially as usage patterns fluctuate. ## From tracking costs to measuring business value Cloud efficiency is gaining importance in this environment. The conversation is no longer limited to reducing waste after the fact. There is a growing focus on understanding the return generated by each unit of cloud consumption. Instead of tracking cost in isolation, enterprises are beginning to connect it with metrics such as revenue per transaction, cost per customer, or This approach brings cloud decisions into direct alignment with business performance. It allows leadership teams to identify which workloads are contributing to growth and which ones are quietly eroding margins. ## Margin leak inside cloud environments Inefficiencies within cloud environments continue to add up, often without immediate visibility. * 30 to 40 percent of cloud costs are often unoptimized * Up to 83 percent of * Network-related expenses, including data egress, can increase by around 20 percent annually These numbers reflect structural issues such as limited visibility, fragmented ownership, and delayed decision-making. In many cases, teams only get a clear picture of spending after the costs have already been incurred. ## Governance is becoming a competitive edge Governance is becoming a critical factor, particularly in India. With regulations such as the Digital Personal Data Protection framework, enterprises are required to maintain tighter control over how data is stored, processed, and used. AI adds another layer of complexity, as models evolve continuously and generate risk in real time. This has led to a greater emphasis on building governance directly into cloud environments. Instead of relying on periodic reviews, organizations are working toward systems that provide ## Why cloud efficiency should matter The financial implications of these changes are significant. From a revenue leadership perspective, cloud efficiency is closely linked to margin expansion and sustainable growth. Decisions around infrastructure, model deployment, and data movement influence not only cost but also pricing strategies and customer experience. For instance, the If inference costs are not managed effectively, they can reduce the profitability of otherwise high-value offerings. Efficient architectures, on the other hand, improve margins without limiting scale. ## Breaking silos There is a growing need for alignment across teams. Finance, engineering, and business units must operate with a shared understanding of how cloud resources are being used and what they deliver. This requires moving beyond siloed reporting toward Many organizations are adopting real-time monitoring, AI-driven anomaly detection, and automated optimization to manage this complexity. Some are also introducing controlled automation, where cost decisions can be executed within predefined limits. ## Designing for efficiency from Day 1 Another important development is the focus on designing for efficiency from the outset. Instead of treating cost as an afterthought, enterprises are incorporating it into architecture decisions, development processes, and deployment strategies. This ensures that efficiency is built into the system rather than applied later as a corrective measure. ## Efficiency will shape India’s next phase of growth India’s position as a growing cloud and AI hub adds urgency to this conversation. With increasing investments in data centers, a strong digital talent base, and supportive regulatory frameworks, the country is well placed to lead in cloud-driven innovation. At the same time, the scale of adoption means inefficiencies can have a much larger financial impact if left unaddressed. Cloud efficiency plays a direct role in determining ## Final thoughts With cloud and AI becoming central to business operations, how well organizations balance cost, control, and value will directly impact long-term performance. Cloud efficiency is ultimately about ensuring that growth is supported by systems that are financially sustainable, operationally transparent, and aligned with business goals. The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 11 Mar, 2026 | 8 Min read # Why Cloud Efficiency Will Matter More Than Cloud Scale in the Next Phase of Digital Growth Naman Jain Chief Growth & Marketing Officer For most of the past decade, cloud strategy had one dominant measure of success: scale. How many workloads were migrated. How many data centers were retired. How quickly legacy infrastructure could be replaced. Bigger footprint, faster migration, more compute on demand - these were the metrics that defined cloud maturity, and the organizations that moved fastest were celebrated for it. That logic made sense when the primary constraint was access. But the constraint has changed. In 2026, the organizations that will lead the next phase of digital growth are not the ones with the largest cloud footprints. They are the ones that have learned to The question at the center of cloud strategy has shifted. It is no longer “how do we scale faster”. It is “why are our cloud costs rising faster than the value we are creating”. ## **The scale-first era left a costly legacy.** Cloud migration delivered real and meaningful advantages. It reduced time-to-market, enabled elastic capacity, and gave organizations access to modern platforms without the capital burden of on-premises infrastructure. These gains were genuine. But migration was designed around speed, not sustainability - and that trade-off is now showing up on the balance sheet. The most visible symptom is cost visibility. In traditional infrastructure environments, costs were relatively predictable. Cloud computing changed that entirely. Spend became variable, distributed across hundreds of services and teams, and often invisible until the bill arrived. Without consistent tagging standards, it became impossible to attribute costs to specific teams, products, or business outcomes. Engineering decisions - made quickly, under delivery pressure - created financial obligations that nobody was tracking. Tagging, in particular, became one of the most widespread and underappreciated failure points. Resources deployed without proper tags cannot be traced to a cost center, a product line, or an owner. At scale, this means a significant portion of cloud spend becomes unaccountable - visible in aggregate but opaque in detail. Optimization efforts stall because teams cannot identify what they own, let alone whether it is being used effectively. Architecture compounded the problem. The dominant migration pattern - lift and shift - moved workloads from data centers into the cloud without rethinking how they were built. Monolithic systems that scaled inefficiently. Always-on resources running continuously where event-driven models would have sufficed. Poor separation between critical production workloads and lower-priority systems, meaning everything was resourced as if it were mission-critical. Reservations and commitments added another layer of complexity. Organizations purchased reserved capacity to reduce costs, which made sense in principle. But Governance rarely kept pace. Approval processes either did not exist or were too slow to be useful, so teams provisioned resources informally and at speed. By the time finance or FinOps teams reviewed spending, the patterns were already embedded. Changing them required engineering effort, organizational alignment, and often difficult conversations about who owned the problem. The scale era produced extraordinary capability. It also produced cloud environments that were architected for movement, not for efficiency - and those two things are increasingly in conflict. ## **Generative AI arrives into an already inefficient estate** The arrival of The compute requirements of AI are categorically different from traditional web applications. A single large model training run can exhaust the budget faster than dozens of conventional services combined. GPU instances are significantly more expensive than standard compute, and demand for them has outpaced supply in most cloud regions. Inference costs at scale are not trivial. And unlike predictable application workloads, AI experimentation is iterative - teams run multiple training jobs, evaluate outputs, adjust parameters, and repeat, often without clear cost accountability at each stage. According to the FinOps Foundation's latest State of FinOps report, 98% of organizations now actively manage AI spend - up from just 31% two years ago. That shift happened in a compressed timeframe, and most organizations were not prepared for it. AI cost management has become the number one skillset that FinOps and engineering teams need to develop, precisely because existing frameworks were not built with GPU economics in mind. The pressure on engineering leaders is significant. Boards and executive teams expect AI capabilities to be delivered at pace. At the same time, many organizations are being asked to self-fund AI investments through Scale without efficiency does not fund AI growth. It competes with it. ## **Optimization has matured and so has the cloud cost challenge** For many engineering and FinOps teams, cloud optimization is already a familiar discipline. The challenge is that the straightforward opportunities have largely been addressed. Teams have eliminated the most obvious waste: idle instances, dramatically overprovisioned storage, redundant services running in parallel. What remains is harder. FinOps practitioners describe hitting the big rocks of cloud waste - the high-value, relatively low-effort improvements that produced meaningful results early in the optimization journey. What follows is a high volume of smaller, more complex opportunities that require deeper architectural knowledge, broader organizational coordination, and more sustained effort to capture. The returns are diminishing, and the work is getting harder. The FinOps Foundation's data reflects this maturity shift. Governance, forecasting, organizational alignment, and scope expansion now collectively outweigh pure optimization as strategic priorities for advanced practices. The center of gravity is moving from cost reduction towards value creation - unit economics, AI value quantification, and influencing technology selection decisions before they are made. Mature organizations are no longer asking how to spend less on the cloud. They are asking whether the cloud spend they have is producing the outcomes it was intended to produce - and building the capabilities to answer that question with real data. ## **Architecture is the lever that contracts cannot reach** When cloud costs rise faster than expected, the instinct for many leaders is to address the commercial relationship first - renegotiating enterprise agreements, extending reserved instance commitments, or evaluating alternative providers. These actions can provide relief at the margin. They rarely solve the underlying problem. The most significant cost drivers in cloud environments are architectural decisions, and they compound over time. A workload that was designed to scale horizontally without intelligent limits will consume resources proportionally to traffic, whether or not that traffic is generating business value. An always-on service that could be redesigned as event-driven carries a continuous cost regardless of utilization. Monolithic systems that cannot separate high-criticality components from low-criticality ones end up resourced for the worst case across the entire application. For AI and GPU workloads specifically, the architectural decisions are even more consequential. Intelligent scheduling, spot instance strategies, and optimized inference paths can significantly reduce spend while maintaining performance - but only if cost-awareness is built into how teams design and operate systems from the beginning. Retrofitting cost efficiency into AI infrastructure after the fact is substantially more difficult and expensive than designing for it upfront. The FinOps Foundation data shows this shift is already underway. Pre-deployment architecture costing has emerged as one of the most in-demand capabilities among practitioners. Teams are embedding financial requirements earlier in the engineering and product lifecycle - a discipline known as shift left - recognizing that decisions made at the design stage have far greater leverage over costs than decisions made after systems are in production. ## **Efficiency is now a leadership concern** Perhaps the most significant structural change in cloud economics over the past two years is where accountability now sits. According to the FinOps Foundation, 78% of FinOps teams now report directly to the CTO or CIO. That shift reflects a broader recognition that cloud spend is a strategic question, not just an operational one. Teams with C-suite engagement demonstrate two to four times more influence over technology selection decisions compared to those with director-level engagement only - including cloud architecture direction, provider selection, and build-versus-buy tradeoffs. The organizations that manage cloud most effectively are those where finance understands technical cost drivers, engineering understands financial impact, and leadership aligns spending with strategic priorities. Cloud strategy can no longer exist independently of business strategy. Growth plans, customer experience goals, and AI investment roadmaps all have direct implications for cloud architecture and cost structure. Organizations that optimize cloud costs in isolation - without reference to where the business is going - often find themselves solving the wrong problem. ## **The next phase runs of cloud efficiency** Cloud scale was the right priority when access and speed were the binding constraints. That problem has largely been solved. The constraint now is sustainable, value-generating operations - and that requires a fundamentally different discipline than the one that defined the migration era. The organizations that will lead the next phase of digital growth are building cloud estates that are intentional by design: architecturally sound, cost-attributed at the resource level, governed without friction, and aligned tightly to business outcomes. They are treating cloud spend as a strategic investment that must justify itself in measurable terms - not as infrastructure overhead that scales automatically with ambition. Cloud migration defined the last decade. Cloud efficiency will define the next one. The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 05 Mar, 2025 | 3 Min read # Why Real-time Monitoring is Critical for Cloud Management Budget Do your Cloud costs often surprise you? By the time most companies notice a spike in their Cloud bill, it’s already too late. Unlike traditional IT expenses, cloud costs are highly dynamic, changing daily or even hourly. But without A recent study found that nearly 50% of technology leaders struggle with cloud cost control. Despite this, companies continue scaling their cloud environments without clear insight into where their money is going. Without real-time visibility, cost overruns can accumulate unnoticed, leaving businesses scrambling to fix budget leaks. But what does real-time cost monitoring really mean? Cloud providers don’t always offer truly real-time data, as billing updates can lag. The key is to access the most recent and granular cost data possible, ensuring teams can make informed decisions before costs spiral out of control. ## **The High Cost of Poor Cloud Cost Visibility** A lack of cost visibility isn’t just an inconvenience—it directly impacts engineering, finance and leadership teams. According to surveys, nearly 90% of professionals say poor cost visibility hinders their work. * **For engineers** this means inefficient resource allocation and unexpected cost spikes. * **Finance teams** struggle to track spending trends and stay within budget. * **Leadership** faces uncertainty when making strategic decisions, as fluctuating cloud costs make financial forecasting difficult. Venture-backed companies, in particular, feel the pressure. With investor expectations to optimise every penny, unchecked Cloud costs can erode profitability and burn rates faster than expected. ## **Why Real-Time Cloud Cost Monitoring Matters** The sooner you detect anomalies and trends; the better control you have over your cloud budget. Here’s how real-time monitoring helps – * **Avoiding Waste** – Identify unused or underutilized resources before they drain your budget. * **Smarter Resource Allocation** – Ensure teams use the right resources at the right time. * **Better Budgeting & Forecasting** – Understand cost trends early to prevent any surprises. ## **Five Ways to Improve Cloud Cost Visibility** Tracking cloud costs effectively isn’t just about checking your invoices. It’s about having the right strategy, tools, and collaboration in place. Here are five practical ways to improve cloud cost visibility - ### **Make Cloud Costs a Shared Responsibility** Cloud spending isn’t just an IT problem. ### **Let AI and Automation Do the Heavy Lifting** Cloud usage fluctuates constantly, and manual tracking just isn’t practical. ### **Get Granular with Your Cost Data** Visibility starts with accurate, detailed data. Cloud providers offer cost breakdowns, but they can be overwhelming. A clear, structured approach to collecting and analyzing this data - across multiple providers - makes it easier to track trends, allocate budgets, and cut waste. ### **Use a Smart Tagging System** ### **Invest in a Comprehensive Cloud Cost Visibility Platform** While cloud providers offer built-in cost tracking, ## **Final Thoughts** Cloud cost visibility isn’t a one-time fix - it’s an ongoing process that requires continuous monitoring and optimisation. By adopting a real-time approach and leveraging the right tools and strategies, businesses can prevent unnecessary spending, improve budgeting accuracy and ensure cloud investments align with business goals. Investing in cost visibility solutions today means fewer cloud budget surprises tomorrow. This article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 04 May, 2026 How AI is Closing the Loop Between Cloud Visibility, Insight and Action Sanjeev Mittal, CPTO, CloudKeeper, discusses cloud cost optimization, FinOps trends, AI workloads, real-time cost monitoring, and governance. 27 Apr, 2026 CloudKeeper Drives Smarter AI Adoption with FinOps Excellence for Enterprises Aman Aggarwal, COO, CloudKeeper, shared his insights on scaling AI adoption, FinOps, and optimizing Claude usage on AWS. 12 Feb, 2026 How Startups Can Optimize Their Cloud Infrastructure More Effectively Aman Aggarwal, COO at CloudKeeper, talks about the common cloud cost mistakes startups make and the practical steps founders can take to stay ahead of runaway cloud spending. 14 Oct, 2025 CloudKeeper: Driving cloud cost optimisation and FinOps maturity across enterprises Aman Aggarwal, COO, CloudKeeper, discusses the evolving FinOps ecosystem, the company’s innovation in cost optimization, and the revolution of AI and automation. 08 Oct, 2025 Deepak Mittal: The Making of a Global FinOps Leader Deepak Mittal discusses what drives success at CloudKeeper - from sustainable cloud savings to customer-first execution - and his vision of expanding across the world. 19 Sep, 2025 Rethinking Cloud Cost Optimization: Deepak Mittal’s Vision for Developers, Startups, and Enterprises Deepak Mittal on CloudKeeper’s $200M journey - bootstrapped, product-led, and reshaping cloud cost optimization for startups and enterprises alike. 25 Aug, 2025 Cloud Cost Optimization: Deepak Mittal at the Helm of CloudKeeper’s Global Journey Deepak Mittal, CEO, CloudKeeper, shares insights on AI-driven FinOps, multi-cloud adoption, and the company’s vision for the future of cloud optimization. 27 Jun, 2025 Cloud Cost Optimization: In Conversation with Deepak Mittal, CEO of CloudKeeper In this insightful interaction, Deepak Mittal, CEO of CloudKeeper, talks about best practices in cloud cost management, cloud security, the future of cloud computing, and the growing role of AI and automation. 20 May, 2025 Cloud costs spiral as decentralized access fuels uncontrolled resource use Deepak Mittal, CEO of CloudKeeper, shares with TechCircle how GenAI is reshaping cloud spend and why cost optimization is now a key enterprise strategy. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 26 Jun, 2025 | 10 Min read # Cloud Cost Optimization: In Conversation with Deepak Mittal, CEO of CloudKeeper Magazine Contributor As more organizations rely on the cloud for their operations, managing cloud costs becomes increasingly important. Efficient cloud cost optimization helps reduce expenses and improve operational efficiency, freeing up IT budgets for strategic projects rather than maintenance and basic operation costs. Moreover, companies that manage their cloud expenses well can invest more in innovation and customer experience, positioning themselves ahead in their respective markets. All in all, cloud cost optimization translates into a competitive advantage. However, this practice involves understanding the cost implications of cloud resources, then finding and implementing strategies to reduce unnecessary expenses without impacting the system’s performance. In this context, we spoke with **Mr. Deepak Mittal, CEO of CloudKeeper**. In this conversation, Mr Mittal breaks down the key issues enterprises face in cloud cost management and how to overcome them. He highlights how CloudKeeper offers end-to-end cloud support, from consulting and implementation to continuous management and improvement. Likewise, he also gives a clear view of where the future is headed and what leaders can expect in the coming years. **Q. Congratulations on your role as the Founder & CEO of CloudKeeper! What excites you most about this role in the company? And what is your vision for the future?** Mittal: Thank you! What excites me the most is the sheer scope of impact CloudKeeper can have on global businesses. Cloud computing is now the backbone of digital transformation across industries, and yet, every year, we see billions of dollars in unused or inefficiently used resources. CloudKeeper began as a cost optimization service within To The New, and its rapid success proved that this challenge was both real and solvable. Today, we are an independent entity with $200M in annual revenue and 50% YoY growth, working with 400+ global clients. Our journey has only just begun. The vision ahead is to redefine how businesses perceive and manage cloud costs — with intelligence, automation, and flexibility. We’re investing deeply in next-gen solutions like Gen AI and **Q. You have extensive experience in the tech domain. How has your expertise prepared you for this role?** Mittal: I’ve spent over two decades in the tech industry, starting with engineering roles and gradually moving into building and scaling technology businesses. My journey from early roles at Sapient and BayPackets to co-founding TO THE NEW, and now leading CloudKeeper, has given me both the technical depth and business acumen required to solve complex challenges in the cloud space. At CloudKeeper, we blend technical innovation with financial discipline - something I’ve come to value deeply over the years. My role as Co-Chair of the NASSCOM Regional Council in Noida has also been incredibly insightful. It keeps me closely connected with the challenges and aspirations of enterprises across sectors, especially when it comes to cloud adoption and optimization. Being on the Governing Board of the FinOps Foundation also allowed me to collaborate with global leaders in this space and stay aligned with the direction the industry is headed. This constant dialogue with industry peers ensures that our offerings remain relevant, practical, and future-focused. **Q. According to you, what are the best practices for Cloud Cost Optimization?** Mittal: Cloud cost optimization is a vast and evolving discipline, but at its core, it starts with visibility. You can’t optimize what you can’t see. So, Once visibility is achieved, the next steps are fairly strategic - moving from reactive cost savings to proactive cloud financial planning, which involves embedding cost-efficiency into architecture and operations from the ground up. Smarter architectural choices, workload placement, long-term commitment planning, and automation are no longer optional – they’re foundational to sustaining optimization at scale. But beyond the technical levers, one of the most overlooked yet critical aspects is building a strong FinOps culture. Cost optimization isn’t just a finance problem or an engineering task - it’s a shared responsibility. It requires tight alignment between engineering, finance, and leadership. When all three speak the same language around cloud value, the real transformation begins. **Q. What is the impact of under-utilization on cloud costs, and how can it be addressed?** Mittal: If we’re referring to scenarios where resources are provisioned but not fully utilized, then yes, that’s one of the most pervasive and costly inefficiencies in cloud environments. Under-utilization leads to increased costs, as organizations pay for idle or oversized resources that don’t contribute proportional value. This directly impacts the ROI of cloud investments, since you’re not truly leveraging the potential of what you’ve paid for. This typically results from over-provisioning – either due to unclear workload patterns or a cautious approach that leads teams to allocate more than necessary. In many cases, lack of visibility into real-time usage, or poor application optimization, means teams don’t even realize how much is going to waste. The consequences aren’t just financial. Inefficient resource allocation affects overall system performance and operational agility. When resources aren’t optimized, teams may unknowingly leave workloads running at higher specs than needed or duplicate efforts without realizing existing capacity could be reused. Over time, this leads to bloated infrastructure, misaligned forecasts, and fragmented cloud governance. Though often overlooked in the beginning, under-utilization steadily builds up, resulting in meaningful cost and resource inefficiencies. **Q. What are some challenges associated with cloud cost optimization, and how can you overcome them?** Mittal: Cloud cost optimization challenges can range from basic overprovisioning to managing complexities in multi-cloud architectures. Each cloud provider comes with its own pricing models and services, making it difficult for enterprises to adopt a unified cost strategy. This often results in fragmented visibility, inefficiencies, and overspending. Keeping up with constantly changing pricing models is another hurdle. Without real-time visibility, organizations risk falling behind and incurring unnecessary costs. Similarly, A lack of accountability and cost visibility across teams further compounds the issue. Without a culture where teams collaborate on cloud spending, optimization becomes an afterthought. Unexpected cost spikes, compliance risks, and skill gaps in cloud teams only add to the complexity. Overcoming these challenges requires more than just tools – it needs a strong FinOps culture, automation, and continuous education. Real-time visibility, strategic RI management, and proactive governance are critical. Combining technology with expert guidance and cross-functional alignment creates the foundation for lasting, impactful optimization. **Q. How can you balance cost optimization with maintaining high availability and performance?** Mittal: That balance is central to every cloud optimization strategy. The truth is, when done right, cost optimization should never come at the expense of performance or availability. In fact, the very best practices mentioned before – like rightsizing, auto-scaling, and reserved instance planning – are designed to enhance efficiency while maintaining (or even improving) performance outcomes. For example, auto-scaling enables dynamic resource allocation based on demand, ensuring peak performance during high-traffic periods and cost savings during lulls. Similarly, rightsizing ensures you’re not over-provisioning resources that sit idle, while still meeting workload needs. Architectural choices also matter. Serverless functions help eliminate idle compute costs for non-critical processes, and spot instances can deliver savings for flexible workloads. Meanwhile, elastic and cross-zone load balancing enhances both availability and resiliency. It’s also crucial to maintain continuous monitoring and run regular audits. Tagging resources for cost allocation and setting automated alerts for performance anomalies help teams stay proactive. Ultimately, it’s about engineering smarter – not cutting corners. At CloudKeeper, we help businesses implement these practices, ensuring their cloud is always cost-effective and high-performing. **Q. What tools and technologies do you use to manage Cloud infrastructure?** Mittal: At CloudKeeper, we bring a comprehensive suite of solutions that span cost visibility, usage optimization, rate optimization, as well as CloudOps and 24×7 personalized support. Our approach is designed to simplify cloud management while maximizing efficiency and savings. We offer tailored solutions for diverse customer needs: * **CloudKeeper AZ** enables * **CloudKeeper Auto** uses AI to automate Reserved Instances and Savings Plans, delivering on-demand flexibility with RI pricing and even buy-back guarantees. * **CloudKeeper EDP+** helps customers get the most out of their AWS EDP with added discounts, reduced annual commitments, and lowered AWS support costs. * **CloudKeeper Lens** offers deep cloud cost visibility and actionable insights to track and optimize usage. * **CloudKeeper Tuner** is an industry-first usage optimization solution that automatically optimizes 50+ AWS services to improve workload performance while lowering costs. Beyond tools, we offer end-to-end cloud support, from consulting and implementation to continuous management and improvement, all delivered by a team of experienced cloud professionals. **Q. How do you ensure security and compliance in a Cloud infrastructure?** Mittal: Ensuring cloud security and compliance starts with a few universal best practices. These include setting up a robust cloud governance framework, enforcing strict IAM (Identity and Access Management) controls, encrypting data in transit and at rest, regularly auditing resources, and staying updated with the latest compliance standards like ISO 27001, ISO 27701, and SOC 2. It’s also essential to implement real-time monitoring, incident response plans, and clear documentation for audits and risk assessments. At CloudKeeper, we follow these principles rigorously. We never access any customer data—our solutions require only minimal IAM access strictly for optimization purposes. As part of our consulting and support, we conduct detailed Cloud Security Assessments and help clients build governance frameworks tailored to their business and regulatory needs. We also support compliance efforts by helping implement secure architectures, monitoring systems, and offering reporting mechanisms aligned with SOC 2 and ISO standards. **Q. What are some key considerations for choosing a cloud provider?** Mittal: While major cloud providers offer a comparable range of services, the right choice often depends on your organization’s specific needs. It’s important to evaluate providers across a few key dimensions: * Reliability & Performance – Uptime commitments, SLAs, and disaster recovery capabilities play a crucial role. * Security – Look for providers with strong encryption, access controls, and compliance with international standards. * Scalability – Ensure the provider can support your future growth without disruption. * Pricing – Understand their pricing model beyond base rates—especially egress charges, storage costs, and scaling impacts. * Support & Expertise – Consider the availability and responsiveness of their technical support, and their experience in your industry. * Integration & Ecosystem – Compatibility with your current architecture and services matters. * Alignment with Emerging Tech – Choose providers that are cohesive with future-ready technologies like GenAI, Kubernetes, and serverless architectures to future-proof your infrastructure. * Compliance & Data Residency – Check for global data center presence and adherence to regulatory standards. * Flexibility – Assess how easy it is to migrate or switch later, to avoid vendor lock-in. **Q. In your opinion, how do you envision the future of cloud computing?** Mittal: We’re seeing AI and machine learning gaining prominence. Platforms like AWS are now embedding Gen AI into their core services, not just for app development, but also for smarter cloud management. For example, AWS recently introduced Edge computing will also explode, thanks to the rise of IoT. Processing data closer to its source means faster decisions and less latency – something industries like manufacturing and healthcare are already benefiting from. We’re also moving toward a hybrid and multi-cloud future, where businesses combine the best of multiple providers to boost resilience and flexibility – without being locked into one vendor. Security is becoming more automated and proactive, with AI-driven threat detection and faster incident response. At the same time, sustainability is finally becoming a priority with providers investing in green data centers and carbon-aware computing. In the near future, we’ll see a rise in industry-specific cloud solutions, wider adoption of serverless architectures, and might even have quantum-intergated cloud computing resources. Cloud will be smarter, greener, and more tailored - and businesses that embrace this shift early will lead the way. **Q. Any advice you would like to give future tech leaders?** Mittal: Absolutely. One key piece of advice I’d offer is – always stay grounded in customer value. Technology will keep evolving, but the fundamental goal remains the same: solving real problems for real people. Stay curious. The cloud, AI, quantum computing – they’re not just trends. And the best leaders are the ones who don’t just chase hype but understand how to harness these technologies meaningfully. Be open to experimentation but marry it with discipline, especially when it comes to cost, security, and sustainability. Also, never underestimate the power of building strong, cross-functional teams. The most impactful innovations are never built in silos. Cultivate a culture where engineers, product leaders, and business teams speak the same language and that language should be outcomes. And finally, invest in continuous learning for yourself and your teams. The pace of change in tech isn’t slowing down, and the leaders who thrive will be those who learn, unlearn, and relearn faster than the world changes. **This article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 25 Aug, 2025 | 5 Min read # Cloud Cost Optimization: Deepak Mittal at the Helm of CloudKeeper’s Global Journey Magazine Contributor Cloud has become the backbone of modern business, but spiraling costs often undermine its promise. To tackle this challenge, companies are turning to cloud cost optimization strategies that go beyond dashboards, combining tools, services, and expert guidance. At the forefront is Deepak Mittal, CEO of CloudKeeper, who has positioned the company as a trusted cloud cost management platform for enterprises and hypergrowth startups alike. In this interview, Mittal explains how CloudKeeper’s cutting-edge cloud cost optimization tools, from Tuner to Lens, are reshaping FinOps, how multi-cloud adoption is changing strategies, and why practical, predictive innovation is key to the future of AI-powered cloud optimization. ## **CloudKeeper offers products like Tuner, Lens, and Auto. How are these innovations changing cloud optimization?** **Mittal:** AI is not just some fad, something like NFTs or VR that may or may not become mainstream. We genuinely see it changing the way businesses work, not years later, but right now. At CloudKeeper, we’re using AI where it makes a difference. Tuner provides smart, usage-based optimization recommendations and Lens, on the other hand, is evolving into more of a cost visibility assistant, a CloudGPT of sorts. You can simply ask what’s driving your AWS costs this week and get custom dashboards, reports, or insights on demand. Together, these cloud cost optimization tools simplify decision-making and deliver faster, more accurate outcomes. ## **Multi-cloud adoption is growing. What challenges do clients face, and how do you help them?** **Mittal:** The shift to multi-cloud is accelerating, but it’s not easy. The biggest challenge is visibility; when teams are spread across different clouds, it becomes a nightmare to get a unified view of spend, usage, and performance. CloudKeeper Lens helps solve this by giving teams Then there’s the skill gap. Multi-cloud requires specialized knowledge across platforms, and most teams don’t have that luxury overnight. That’s why we provide expert consulting and hands-on support for migrations and modernization. Troubleshooting is another big hurdle. Issues can arise in the middle of the night across time zones, and when you’re juggling multiple clouds, complexity only increases. Our 24×7 support team acts like an extended arm, fast, responsive, and platform-aware. And finally, multi-cloud cost governance can get messy. Choosing which plan works best on which cloud is time-consuming. With CloudKeeper AZ, our clients access savings they usually wouldn’t qualify for, without worrying about complex lock-ins. ## **You support both AWS and Google Cloud. How do companies differ in using and optimizing these platforms?** **Mittal:** The goals are the same: better performance at lower cost, but the approaches differ. AWS is the go-to for enterprises looking for breadth and control. It’s incredibly mature, offers the largest service catalogue, and gives companies deep flexibility. Businesses with complex hybrid environments often gravitate to AWS. Optimization here involves fine-tuning usage across a sprawling set of services, where our AWS cost intelligence and expert advisory make a real difference. Google Cloud, on the other hand, is increasingly popular with organizations pushing the envelope on data, AI, and modern app development. BigQuery, GKE, and Vertex AI are standout offerings. Startups and digital-native businesses often choose GCP for innovation. Optimization here focuses on sustained usage, choosing the right architecture patterns upfront, and From a pricing perspective, GCP’s per-minute billing and automatic sustained use discounts are attractive, while AWS still leads in enterprise-scale discounts and customization options. Our role is to help clients navigate these trade-offs, ensuring their cloud cost optimization strategies align with workloads and business goals. ## **Generative AI is making waves. How is CloudKeeper leveraging AI for smarter outcomes?** **Mittal:** We’re seeing GenAI become a natural part of how cloud teams work. At CloudKeeper, we’ve already built internal GenAI agents for customer success and sales support, making day-to-day operations faster and more efficient. For clients, we’re embedding AI into both Tuner and Lens. Soon, customers will have predictive insights, guided recommendations, and even dedicated services for GenAI-based workloads. The aim is AI-powered cloud optimization that saves time, reduces waste, and enables smarter decisions at scale. ## **CloudKeeper’s product portfolio is expanding rapidly. How do you decide what to build next?** **Mittal:** Our innovation roadmap is shaped by two things, market signals and customer voice. In fact, CloudKeeper itself was born from a customer need. Back when we were offering AWS managed services through TO THE NEW, a client asked us for help Since then, we’ve continued to listen closely to our customers while anticipating where the market is heading. For example, we launched CloudKeeper Auto, an Similarly, when customers asked for Lens insights and support within their workflows, we built a Slack integration to bring FinOps closer to daily operations. Looking ahead, you can expect more innovations that blend proactive market understanding with real customer needs, whether that’s in AI-led automation, deeper integrations, or platform intelligence. ## **With rapid U.S. expansion, how do you see CloudKeeper’s role evolving in the North American market?** **Mittal:** North America is a dynamic and highly competitive cloud market, home to many of the world’s top cloud players, emerging tech innovators, and some of the leading names in our own domain. That makes it both exciting and demanding. For us, it’s a space that keeps us on our toes, driving us to constantly evolve our platforms, deepen our FinOps capabilities, and explore new frontiers in digital transformation through FinOps. With strong local leadership and growing momentum, we’re building meaningful partnerships and delivering tangible impact across the region. **The article was originally published on** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 19 May, 2025 | 6 Min read # Cloud costs spiral as decentralized access fuels uncontrolled resource use The shift to the cloud is reshaping how businesses operate, but managing In a conversation with TechCircle, CEO Deepak Mittal, breaks down the key issues enterprises face in cloud cost management, the growing impact of Generative Artificial Intelligence (GenAI), and how CloudKeeper’s tools and recent acquisition are addressing these challenges. He also offers a clear view of where the cloud industry is headed and what to expect in the coming years. Edited Excerpts: ## **What are the key challenges that enterprises and startups face in managing their cloud spending effectively?** When companies begin their cloud journey, the initial focus is usually on migration, security, reliability, and uptime. These are top priorities. Cost, however, is often overlooked. First, many organisations don’t anticipate how quickly cloud costs can spiral. Second, their traditional IT procurement models, largely CapEx-based and centralised, don’t apply in the cloud, which operates on a flexible, In the cloud, everything is available instantly. Hyperscalers offer hundreds or thousands of services, accessible to anyone in the organisation. That means anyone can deploy high-cost resources like top-tier GPUs or load balancers with a few clicks, often without oversight or approval. This creates major Ultimately, this is a multi-faceted challenge. The existing mindset doesn’t fit, a shift from CapEx to OpEx and from centralised control to decentralised access. There’s a lack of cost awareness, inadequate governance, and missing tooling. It’s a people issue, a cost issue, and a governance issue all at once. ## **How is your company using GenAI to drive innovation and improve offerings?** With the rise of GenAI, the industry is seeing both new opportunities and challenges. For most enterprises and startups, the availability of advanced GenAI tools from cloud providers like AWS, Google Cloud Platform, and Azure is a positive development. These tools offer powerful capabilities, but they also come with increased costs. Currently, most companies, likely over 95%, are still in the early stages of exploring GenAI. They're running pilots or small-scale experiments, often using free credits provided by hyperscalers. Because of this, GenAI-related costs aren’t yet a major concern. However, as GenAI adoption becomes more mainstream, expenses are expected to rise, and companies will need to manage them more closely. At CloudKeeper, we see GenAI as an opportunity. Our customer base has grown from around 300 to over 400 in the past year, and we’re expanding the range of tools and solutions we provide. Internally, we use GenAI to increase operational efficiency and enhance product development. We're also helping our clients identify appropriate use cases for GenAI and navigate the associated cost and implementation challenges. While GenAI has potential, it’s not universally applicable, and we're guiding customers on where and how to apply it effectively. ## **How is the global market responding to AI? Are companies mainly experimenting with it, or have they advanced further?** As of now, many B2B companies have emerged. A large portion of them are essentially wrappers around existing This pattern is seeing widespread adoption. On the consumer side, tools like Perplexity, Anthropic Claude, and OpenAI are also being used heavily. Companies like Indigo, Zepto, and Lenskart, some of our current customers, are also adopting these technologies. However, for them, cost is not yet a major concern. ## **How do your tools address the complexities of cloud cost management?** When we engage with customers, our main objective is to help them reduce their cloud costs. We achieve this through three main strategies. The first is rate optimisation. This involves aggregating cloud usage across multiple customers, which allows us to negotiate better pricing from AWS, similar to how group buying works. We then pass those cost savings to our customers. In addition, we help them make the most of discount programs that cloud providers offer in exchange for usage commitments. We guide customers on the right level of commitment and, in many cases, take on those commitments ourselves. The second strategy is usage optimisation. We use tools like These three approaches, rate optimisation, usage optimisation, and architecture optimisation, form the foundation of our cost-saving efforts. We package them into solutions like ## **CloudKeeper recently acquired WiseOps. What strategic advantages does this acquisition bring to your clients?** We had already developed two software platforms, CloudKeeper Lens and Auto, over the past five years. Building a solution like CloudKeeper Tuner (formerly WiseOps) had been on our roadmap for some time, but our focus remained on improving existing tools. We consistently discussed the need to offer automated infrastructure optimisation features. WiseOps already had those capabilities, along with a strong team and a good product-market fit. However, they were acquiring customers independently, while CloudKeeper already had a customer base of 400 that could immediately benefit from such features. We saw a strategic fit and Customer feedback has been positive. Many recognise it as the missing piece. We’ve also seen faster sales cycles, with prospects appreciating our end-to-end cloud cost optimisation offering, covering rate, usage, and architecture optimisation. This has significantly strengthened our value proposition. ## **How do you assist organisations in achieving scalability without compromising on cost efficiency and environmental considerations?** One way we contribute to reducing carbon emissions is by optimising resource usage. For example, if a customer can run their workloads on 80 servers instead of 100, that directly lowers their cloud consumption and infrastructure cost. This naturally supports sustainability goals. However, in our conversations with stakeholders, typically CTOs, heads of DevOps, or cloud teams, sustainability is rarely a top priority. It may be discussed at the board level, but among those responsible for day-to-day operations, the focus is usually on performance, reliability, and cost. That said, we do highlight environmentally friendlier options when available. For instance, if a hyperscaler offers services with a lower carbon footprint, we ensure our customers are aware of those alternatives. Still, in practice, ## **Cloud adoption is growing fast. Where do you see the industry heading, and what trends do you expect in the next three to five years?** As more data center leases expire, workloads are steadily moving to the cloud. This trend has been ongoing for the past decade and is expected to accelerate in the coming years. Currently, GenAI does not contribute significantly to our overall revenue, which exceeds $200 million. However, we anticipate that GenAI will begin to play a more substantial role over time. Along with this growth, we also expect associated costs to rise. As cloud costs increase, enterprises are becoming more focused on financial operations (FinOps) and cloud cost optimisation. Although these services exist today, the provider landscape is still fragmented. There are over 50 companies globally offering various cloud optimisation solutions. We expect this space to consolidate over the next three to five years. Like other industries, a few dominant players will likely emerge, while many smaller firms will be acquired. This article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 27 Apr, 2026 | 7 Min read # CloudKeeper Drives Smarter AI Adoption with FinOps Excellence for Enterprises Magazine Contributor ### **1. Please briefly introduce CloudKeeper and its core offerings.** CloudKeeper is a comprehensive cloud cost optimization and FinOps partner for companies that are scaling fast on the cloud. We help businesses get more value from what they are already spending, without adding complexity or long-term commitments. Our approach combines guaranteed savings from day one with continuous optimization through our platform-led solutions and expert support. From visibility and automation to commitment management, we cover the full FinOps lifecycle. We also support customers end-to-end, from consulting and migration to ongoing management and 24x7 support. The idea is simple: help teams move fast on the cloud while staying in complete control of cost and performance. CloudKeeper has also We are also equipped to support evolving workloads, including AI, by extending our FinOps and cloud optimization expertise to these environments, helping organizations maintain visibility, control, and efficiency as enterprise AI adoption scales. ### **2. What does the partnership with Anthropic mean for enterprises?** Our partnership with Anthropic is about making AI adoption more structured and easier to operationalize within existing cloud environments. Today, many organizations struggle with fragmentation across model access, infrastructure, billing, and governance. This often slows down real progress. Through this partnership, enterprises can We help organizations introduce visibility into usage, align consumption with business needs, and put guardrails around cost and access. This ensures that as teams start using AI, they do so in a controlled and sustainable way. ### **3. How is demand for Claude AI models evolving in the market?** The conversation has changed completely in the last 12 months. A year ago, most enterprises were asking "should we explore AI?" Today, they're asking "how do we scale this responsibly?". Claude is gaining serious traction because enterprises need more than just a capable model - they need reliability, safety, and the ability to handle complex, context-heavy enterprise workflows. Claude delivers that. What I find interesting is the parallel wave of interest towards cost awareness. Companies are realizing that running AI at scale isn't cheap, and they're actively looking for structured consumption models. That's exactly the intersection where CloudKeeper plays - making sure AI adoption is not just fast, but financially sustainable. ### **4. How does CloudKeeper help enterprises adopt AI while optimizing cloud costs?** We don’t treat AI and cost as separate conversations - they go hand in hand. When organizations begin to run AI workloads, costs can scale quickly without the right visibility and controls. We bring structure into this through real-time insights into usage, cost drivers, and optimization opportunities. With platforms like LensGPT, teams can We also help implement guardrails such as usage controls and budget thresholds, ensuring teams can experiment and scale while maintaining control over costs. Through our Extending FinOps practices to AI workloads is a natural part of this approach, helping organizations manage newer consumption patterns more effectively. ### **5. What opportunities does AI model resale create for AWS partners?** This is a genuine inflection point for the AWS partner ecosystem. For years, the conversation was mostly about infrastructure - compute, storage, networking. AI model resale changes the game entirely. Partners can now offer end-to-end AI solutions - combining model access, deployment, cost optimization, and ongoing support. That's a fundamentally different value proposition, and it creates much deeper customer relationships. But here's my honest take - not every partner will succeed at this. The ones who will are those who bring ### **6. How do you ensure secure and compliant AI adoption for enterprises?** Security and compliance remain central to how we approach any workload. Since models like Claude are accessed through Amazon Web Services, enterprises can continue leveraging their existing security frameworks, identity controls, and compliance structures. On top of that, we add The focus is on enabling adoption while ensuring that security, compliance, and risk management are not compromised. ### **7. How can FinOps help manage the cost of AI workloads?** AI workloads introduce new and often unpredictable consumption patterns, which makes cost management more challenging. FinOps provides the structure needed to manage this effectively. It enables real-time visibility into usage, clear cost allocation, and the ability to implement guardrails around consumption. By CloudKeeper supports this through a combination of platforms and expertise. LensGPT allows teams to interact with their cloud and cost data conversationally, helping them quickly identify inefficiencies and optimization opportunities. CloudKeeper Tuner At the same time, our Generative AI Launchpad helps organizations adopt AI in a structured way from the outset, with the right architecture, governance, and cost controls already in place. Backed by our AWS AI Services Competency, we bring proven expertise in building and scaling production-grade AI solutions, ensuring cost optimization is built into the foundation itself. Overall, FinOps helps ensure that evolving workloads, including AI, remain efficient, controlled, and aligned with business outcomes. ### **8. Can you share a recent success story or case study?** We work with both traditional enterprises and new-age AI-powered platforms, helping them scale efficiently while keeping infrastructure costs under control. In one case, we supported an AI-driven document processing platform on Google Cloud that was facing cost spikes and limited visibility across APIs, BigQuery, and compute. By implementing a We also worked with an AI-powered energy intelligence platform running on Kubernetes, where infrastructure instability was impacting operations. By In another engagement, with an AI-native platform scaling ML workloads, we addressed deep infrastructure inefficiencies - from slow GPU startup times to upgrade bottlenecks. By Across these engagements, applying FinOps principles to evolving AI workloads helped drive better efficiency and control. ### **9. What key trends do you see in AI-driven cloud adoption?** AI adoption is becoming more structured. Several converging trends are shaping how enterprises approach it. FinOps for AI is now mainstream - cost governance, token optimization, and financial accountability are no longer afterthoughts. Equally interesting is the rise of AI for FinOps using AI itself to manage cloud costs, which is exactly what LensGPT does. Multi-cloud AI strategies are growing, with organizations distributing workloads across AWS, GCP, and Azure based on model availability, latency, and cost - making cross-cloud visibility critical. Multi-model approaches are becoming standard, with teams We're also seeing agentic AI move into production, data sovereignty becoming a procurement filter, and above all a relentless push toward measurable business outcomes over experimentation. ### **10. What is CloudKeeper’s future roadmap?** Our focus is on becoming the go-to partner for AI and cloud - not as separate disciplines, but as one integrated capability. We're expanding the Generative AI Launchpad to support more industries and faster time-to-production, bringing together AI architecture expertise, AWS best practices, managed services, and FinOps governance in one structured engagement. On the platform side, LensGPT will evolve to include deeper AI cost intelligence - model-level spend analysis, proactive anomaly detection, and token consumption optimization to help teams manage prompt efficiency, context window usage, and model-tier selection at scale. CloudKeeper Tuner will take on increasingly complex workload optimization patterns alongside this. Our AWS AI Services Competency and Anthropic reseller partnership underpin everything. But ultimately, sustainable AI adoption requires continuous optimization and a partner accountable for outcomes over time. That's exactly the model we're building toward. The article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 14 Oct, 2025 | 4 Min read # CloudKeeper: Driving cloud cost optimisation and FinOps maturity across enterprises Magazine Contributor Cloud service providers in India have witnessed a steady surge in enterprise cloud adoption. As workloads scale and AI-driven applications expand, cloud cost optimisation has become a top priority for enterprises. This is where FinOps, a discipline combining finance, technology, and operations, plays a defining role. In an exclusive interaction with DQ Channels, **Aman Aggarwal, COO, CloudKeeper,** talks about how the company is empowering organisations to streamline their cloud operations, reduce wastage, and make FinOps a sustainable business practice rather than a one-time project. ## **From TO THE NEW to CloudKeeper: evolving with customer needs** _“We were earlier operating under the brand name TO THE NEW, which continues as a services organisation,”_ recalls Aggarwal. _“It’s an IT services company where we do custom development for web, mobile, and smart TV apps. We became an AWS partner in 2013 and eventually attained premier consulting partner status.”_ Working with global clients, the team realised that cloud cost optimisation was the most common and critical customer requirement. _“We saw that while architects focused on automation, resiliency, and security, cost wasn’t the first thought on everyone’s mind. Only C-level executives and finance teams truly cared about it,”_ he adds. Recognising this gap, the company carved out CloudKeeper in 2018 as a separate business line focused purely on Cloud FinOps._“We started offering_ _to customers,” says Aggarwal. “And since then, the response has been phenomenal.”_ By 2020, amid the pandemic’s financial pressures, cost efficiency became a necessity for all. “ _That was when we began expanding internationally to the US and other geographies. Today, we serve over 400 customers globally, managing an annual run rate of close to USD 230 million, growing at nearly 40% CAGR,”_ he notes. ## **How FinOps is maturing from cost control to business enabler** According to Aggarwal, FinOps is no longer a transactional, one-time activity._“Earlier, customers would optimise costs once, forget about it, and return a year later when bills spiked again,”_ he explains. _“Now, more organisations understand that FinOps has to be a discipline. There has to be real-time tracking, dashboards, and a clear linkage between cloud cost and business KPIs like_ _,”_ he points out. He believes this shift reflects a broader maturity curve. _“Customers today focus on per-unit cost metrics that tie directly to their business outcomes. That’s a big change in mindset.”_ ## **Automation, AI, and human oversight: a balanced approach** CloudKeeper’s FinOps ecosystem combines automation with human validation. _“We work with many listed companies, fintechs, and compliance-driven organisations. They’re cautious about granting external access. So,__,requires no special permissions; it just consumes AWS cost and usage reports,”_ says Aggarwal. For automation, CloudKeeper offers CloudKeeper Auto and CloudKeeper Tuner._“Auto_ _, generating recommendations that are manually validated before execution. Similarly, Tuner helps customers_ _,”_ he explains. _“The goal is to give customers control while reducing effort. We don’t automatically delete resources; instead, we make it a one-click task with full visibility. That’s the balance between AI-driven automation and human judgment.”_ ## **Tackling multi-cloud complexity through standardization** Operating across AWS, Azure, and GCP brings unique challenges. _“The billing models of hyperscalers differ significantly,”_ Aggarwal says. _“That’s why we’re contributing to the FinOps Foundation’s Focus project, which aims to create a unified billing data format across cloud platforms.”_ CloudKeeper’s R&D teams are actively working to _“Our goal is to provide customers a single, consolidated dashboard that reflects their entire cloud cost structure, not just a summary,”_ he elaborates. Customers also prefer cloud-agnostic tools to avoid vendor lock-in._“We see enterprises opting for Terraform instead of cloud-native scripts, or third-party ISVs like Redis Cloud, Databricks, or Snowflake, because they work seamlessly across environments,”_ he observes. ## **India and Southeast Asia: unique dynamics of a price-sensitive market** Discussing regional differences, Aggarwal notes that India and Southeast Asia remain highly price sensitive. _“Hyperscalers recognise this,”_ he says. _“Commitment thresholds and benefits differ widely from North America. In our region, most deals are customised—credits, thresholds, and support mandates vary.”_ Having executed over 75 large commitment deals, CloudKeeper helps clients navigate this complexity. _“_ _based on business projections and technical roadmaps. Our experience helps them secure the best commercial terms,”_ he shares. ## **Future focus: AI, serverless, and next-generation cost visibility** Aggarwal sees rapid evolution ahead. _“Most hyperscalers are introducing private labels like Graviton, Amazon’s chip family, which offers significant cost benefits. We’re helping customers adopt these to optimise workloads.”_ He also points to serverless and containerised workloads, which are growing rapidly. _“Earlier,__required third-party tools. Now, hyperscalers are introducing native analytics, and we’re integrating those updates into our own platforms.”_ And then there’s generative AI, the newest cost challenge. _“GPU consumption is unpredictable. Everyone wants to innovate with AI, but few understand the cost implications. So visibility and control are critical,”_ he says. ## **Conclusion: FinOps as a continuous journey** As cloud adoption deepens, FinOps has evolved from a corrective tool into a strategic discipline. CloudKeeper’s approach, integrating automation, transparency, and human insight, illustrates how enterprises can strike the right balance between innovation and efficiency. _“Our mission,”_ concludes Aggarwal, _“is to make cost optimisation a continuous journey. It’s about building smarter, more accountable cloud ecosystems.”_ **The article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 20 Mar, 2025 | 6 Min read # CloudKeeper's Million-Dollar Cloud Cost Savings Strategy The allure of cloud computing – scalability, flexibility, and on-demand resources – has spurred its widespread adoption. However, this ease of access can quickly translate into uncontrolled spending, making As businesses in India, from unicorns to established enterprises, grapple with ballooning cloud bills, CloudKeeper, led by CEO Deepak Mittal, is emerging as a critical ally. In an exclusive interview, Mittal reveals the secrets behind his company's success, dissecting the common pitfalls of cloud waste, and outlining how CloudKeeper is pioneering a holistic approach to cost optimization, saving clients millions while navigating the complexities of a rapidly evolving digital landscape. Excerpts: ## **Could you start by giving us an overview of CloudKeeper and its business in India?** In India, we have over 150 customers and handle more than ₹1,000 crore in cloud-related business. While we may not have exact competitor figures, we believe CloudKeeper is among the top cloud cost optimization providers in the country. Our client base includes over 25 unicorns and large enterprises such as IndiGo Airlines, Zepto, Lenskart, and CarDekho, alongside numerous mid-sized and emerging businesses. ## **Are there any specific industries that benefit the most from your solutions?** That’s a great question and one that often comes up. While we work with about 35 Fintech companies, For instance, the work we do for a company like Zepto can be just as impactful for a financial institution or a SaaS company. Since our expertise lies in cloud cost efficiency rather than a specific industry vertical, we can seamlessly serve a diverse range of businesses. ## **Cloud cost optimization is a competitive space. What sets CloudKeeper apart?** Cloud cost optimization is evolving, especially in the U.S., with three main approaches: rate optimization (buying cloud at the best price), usage optimization (eliminating waste), and architecture optimization (building cost-efficient infrastructure). What makes CloudKeeper unique is that we cover all three aspects as a Total Savings Partner. Unlike others who focus solely on software, consulting, or procurement, we combine all three—proprietary technology, expert advisory, and procurement expertise— ## **What are the biggest challenges organizations face in managing cloud costs?** The biggest issue is that cost has always been an afterthought—companies first focused on cloud migration and security, leaving cost optimization behind. Now, with rising cloud bills, they’re realizing the need for better control. **Challenges include:** * **Lack of expertise—** Most IT professionals specialize in cloud deployment, not cost management. * **Complex pricing** —Millions of cloud SKUs make it hard to pick the right options. * **No real-time visibility** —Companies often overspend without knowing it. CloudKeeper tackles these with ## **Many businesses struggle with cloud waste. What are the most common inefficiencies in cloud spending, and how can they be mitigated?** Cloud inefficiencies primarily arise from Another major factor is the lack of awareness regarding cost implications. Cloud providers offer various pricing tiers, but businesses often select higher-end configurations without evaluating their needs, leading to unnecessary expenses. Additionally, cloud platforms rapidly introduce new, more cost-effective solutions. For instance, AWS launched its ## **How do you ensure tangible savings and ROI for your customers?** We embed cost savings directly into our contracts, which is one of our key differentiators. Our approach consists of two types of savings: The type 1 is, Guaranteed Savings, these savings require no changes to a customer’s existing cloud setup. They are realized from the start, with typical savings ranging from 7–10%. Then type 2 is, Optimization-Based Savings, these require minor adjustments to configurations or usage patterns. Through detailed audits, we identify areas of overprovisioning or inefficient resource allocation. These savings generally materialize within 60–90 days. On average, our customers achieve 20–26% savings, demonstrating the effectiveness of our optimization strategies. ## **Cloud computing is evolving rapidly with AI, multi-cloud, and sustainability trends. How are you adapting to these changes?** To be candid, sustainability is widely discussed, but it is not a primary focus for most customers. Businesses care more about tangible outcomes. If sustainability initiatives align with cost savings—such as reducing energy consumption by optimizing cloud workloads—then they resonate. However, presenting sustainability as a standalone pitch often fails to gain traction. AI adoption is increasing, but ## **You have a presence in multiple countries. How do you tailor your services to different regions and industries?** The core cloud platforms—AWS, Google Cloud, and Azure—remain largely uniform across regions. However, the speed of adoption and priorities differ. In India, Additionally, cloud providers often launch new features in the US first before rolling them out to other regions. This creates a gap where global companies operating in multiple markets may have access to cost-saving features in one region but not in another. Our role is to bridge this gap and ensure clients leverage the best available options wherever they operate. ## **How do you see cloud cost optimization evolving?** The market is consolidating—too many niche providers have emerged, but businesses prefer end-to-end solutions. In the next few years, we’ll likely see five to seven dominant players offering comprehensive cloud cost management. Right now, Kubernetes cost optimization is a hot topic, but AI workloads will take center stage soon. ## **What’s your advice for businesses starting their cloud cost optimization journey?** Make cost efficiency a **top-down priority**. If leadership drives it, teams will follow. My key tips: 1. **Think financially**. Treat cloud costs as a business metric. 2. **Set KPIs.** Track and optimize cloud spending regularly. 3. **Embed cost awareness.** Make it part of your cloud strategy, not an afterthought. ## **What’s your vision for CloudKeeper in the next 3-5 years?** We’ve been growing at nearly 50% annually for the past few years, and we aim to sustain that momentum. More importantly, our vision is to become the go-to partner for businesses looking to optimize multi-cloud environments and drive cloud cost efficiency at scale. Currently, the cloud cost optimization space is still evolving, with only a few major players. Our goal is to be among the top three companies in this domain, setting industry benchmarks for cost intelligence and optimization. ## **As a founder and CEO, what is the most important lesson you have learned?** The biggest lesson I’ve learned is**never take shortcuts** —whether in product development, customer relationships, or business strategy. It’s tempting to go for quick wins, but sustainable growth comes from long-term thinking. Investing in robust solutions, maintaining transparency with customers, and focusing on lasting value always pay off. This article was originally published on FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 07 Oct, 2025 | 4 Min read # Deepak Mittal: The Making of a Global FinOps Leader Magazine Contributor ## How CloudKeeper scaled globally with resilience, customer trust, and cloud cost innovation Behind every fast-scaling company is a story of vision, resilience, and leadership. For Deepak Mittal, Co-founder and CEO of CloudKeeper, building a hypergrowth cloud startup has been as much about discipline as it has been about innovation. Today, CloudKeeper serves more than 400 clients across industries and geographies, helping them achieve sustainable cloud cost savings through its FinOps solutions. In this exclusive interview, Mittal shares his leadership journey, from lessons learned during the 2008 financial crisis with TO THE NEW to scaling CloudKeeper into a global FinOps leader with $20 million EBITDA. He also reflects on building diverse teams, expanding into North America, and why customer-first execution always trumps vanity metrics. ## CloudKeeper now serves over 400 global clients and delivers an average of 20% savings. What has been the biggest driver behind this impact? **Mittal:** The universality of the problem we solve. Cloud is the backbone of digital infrastructure, and every business, whether a Gen AI startup or a Fortune 500, wants better performance at lower cost. Our edge lies in delivering not just savings, but ## CloudKeeper recently expanded into North America, with 35% of your client base now in the U.S. How do you adapt across markets? **Mittal:** While cloud cost challenges are consistent globally, the way organizations approach them varies. In some markets, engineering teams lead optimization; in others, finance takes charge. Some customers prioritize long-term sustainability, while others seek immediate savings. ## CloudKeeper is trusted by leaders like eLocal, HackerEarth, Recruit CRM, Appsmith, Moneysmart, and InterGlobe Aviation. Which client stories stand out to you? **Mittal:** Every client story matters, but a few are special. With eLocal, we drove ## Profitability is rare for a fast-growing SaaS company, yet CloudKeeper reported $20M EBITDA. How did you achieve this balance? **Mittal:** Growth and profitability rarely go hand in hand in SaaS. We focused on value, not vanity metrics. Our solutions directly save customers money, which made revenues sticky and trust-driven. We also stayed disciplined on unit economics, lean teams, frugal operations, and efficiency-first practices. Combined with a committed team, this approach helped us scale without compromising profitability. ## Your FinOps model combines platforms, expert advisory, and procurement. Why does this resonate with both startups and enterprises? **Mittal:** Because it’s complete. Startups get FinOps capabilities out of the box, without hiring teams, freeing them to focus on product and growth. Enterprises benefit from our certified FinOps experts and automation that help teams make better decisions without slowing down. ## With your rapid U.S. expansion and new local leadership, how do you see CloudKeeper’s role evolving in the North American cloud ecosystem? **Mittal:** North America is a dynamic and highly competitive market, home to hyperscalers, emerging innovators, and some of the leading names in our own domain. It keeps us on our toes, driving us to constantly evolve our solutions, deepen our FinOps capabilities, and explore new frontiers in ## What lessons from TO THE NEW shaped your leadership at CloudKeeper? **Mittal:** TO THE NEW was built during the 2008 financial crisis, and it taught me resilience and long-term thinking. At CloudKeeper, I’ve applied those lessons by hiring carefully, focusing on execution, and building sustainable products. Listening to customers and staying disciplined has mattered more than chasing buzzwords or short-term growth. ## As you expand globally, what lessons have you learned about managing cultural differences and teams across regions? **Mittal:** Context matters. What works in one region doesn’t always work elsewhere, whether it’s communication styles, expectations, or service levels. Building high-performing global teams requires embracing diversity, empowering local leadership, and aligning everyone on shared outcomes. ## CloudKeeper is targeting 3× revenue growth by FY2027. What are your strategic priorities? **Mittal:** We’re doubling down on high-potential markets like North America, investing in ## What advice would you give to founders seeking to turn cloud into a driver of growth? **Mittal:** Treat cloud like any critical investment. Track it with the same intent as R&D or talent. Build a FinOps culture early, where finance, engineering, and product teams share ownership. And while trends like GenAI and serverless are exciting, focus on what moves the needle for your business. Surround yourself with people who understand both tech and economics. **The article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 04 May, 2026 | 5 Min read # How AI is Closing the Loop Between Cloud Visibility, Insight and Action Magazine Contributor Cloud spending is at an inflection point. Artificial intelligence workloads are now central to enterprise strategy, and organizations are grappling with costs that are more dynamic, unpredictable, and harder to govern than ever before. Traditional tools built for simpler cloud environments are struggling to keep pace, and the gap between innovation and financial control is widening. To address this challenge steps a new generation of AI-powered FinOps platforms that promise to transform how enterprises understand and manage their cloud spend. In an exclusive interview with **Sanjeev Mittal, CPTO of CloudKeeper** , Analytics Insights explores how agentic AI, natural language interfaces, and real-time intelligence are rewriting the rules of cloud cost governance. Here are the excerpts: ## Cloud spending has grown significantly with the rise of AI workloads. What are the biggest challenges enterprises face today in managing cloud costs effectively? AI has fundamentally changed how the cloud is consumed. The entire There is also a gap between innovation and control. Teams are moving fast with AI, but cost governance is still catching up. This makes it difficult for organizations to scale AI confidently without overspending. ## Traditional cloud cost management relies heavily on dashboards and manual analysis. What limitations do these approaches create for modern enterprises? Dashboards were designed for a simpler cloud environment. They provide visibility, but they still depend heavily on manual effort and user expertise. Teams often spend hours pulling reports, applying filters, and trying to interpret data across multiple tools. Developing meaningful insights requires database knowledge and technical skills that not everyone on the team has. And by the time a pattern is identified, the cost has already been incurred. It is fundamentally a reactive process. Another limitation is accessibility. Not every stakeholder is comfortable navigating dashboards — especially finance or leadership teams who often need ad-hoc analysis and real-time answers, not another tool to learn. This creates silos where cost data exists but doesn't reach the people making spending decisions. What modern enterprises need is a more intuitive and proactive way to understand and act on cloud cost data. ## CloudKeeper recently launched LensGPT. Could you explain how an agentic AI approach changes the way organisations interact with cloud financial data? With LensGPT, we are moving from dashboards to conversations. Instead of navigating filters and reports, users ask questions in plain language — "Why did my S3 cost spike last Tuesday?" or "What's my cost per EKS cluster deployment?" — and The agentic approach means the system does more than just respond. It understands the context, analyzes patterns, and guides the user toward the next step. Instead of spending time figuring out what happened and what to do next, teams can directly ask and get both the insight and the recommended action. We are also launching LensGPT as an MCP server, which means it connects directly into tools teams already use — Claude, ChatGPT, Cursor, or internal AI assistants. Cost intelligence meets users where they work, not in another dashboard they have to learn. This makes FinOps faster, more accessible, and much more aligned with how teams actually work today. ## How does LensGPT use natural-language queries and AI reasoning to help teams identify cost drivers and optimisation opportunities in real time? LensGPT sits on top of our Lens Analytics Engine, which The reasoning layer is what sets it apart. A question like "Why did my costs spike last week?" is not a simple lookup. LensGPT decomposes it into multiple sub-queries — checking service-level changes, regional shifts, configuration modifications, and usage anomalies — then synthesizes a single, explained answer. It attributes the spike to specific resources, tags, or events, not just a service total. On optimization, LensGPT draws from our recommendation engine which today covers 44 recommendation types across AWS and GCP. When it identifies a cost driver, it can immediately surface the relevant optimization. Because Lens processes data at hourly granularity, these insights reflect what is happening now, not what happened last month. Teams can catch anomalies within hours rather than discovering them in a monthly review. ## In your view, how will AI-powered FinOps platforms reshape cloud cost governance for enterprises over the next few years? AI-powered FinOps platforms will shift cost governance from reactive to continuous. Instead of periodic reviews, organizations will have Another key shift will be speed. Decisions that used to take hours or days will happen in minutes, supported by real-time insights.Overall, governance will become more embedded, proactive, and aligned with how modern cloud environments operate. ## With organisations increasingly prioritising cost efficiency in cloud adoption, what trends do you expect to see in the evolution of FinOps and cloud optimisation tools? The biggest shift we see is FinOps moving from a reporting function to an intelligence layer that is embedded directly into engineering and business workflows. Today, cost insights sit in dashboards that a small team reviews. Tomorrow, they will be delivered through the same AI tools teams already use. The second trend is the emergence of FinOps for AI as a distinct discipline. AI workloads account for 8-10% of cloud spend today, but that is projected to exceed 40%. GPU utilization averages just 20-50% across enterprises — there is enormous waste being created at scale. Organizations will need We also expect FinOps to shift left in the lifecycle. Cost awareness will become part of architecture and deployment decisions, not something reviewed after the bill arrives. At CloudKeeper, we are already building in this direction — integrating optimization recommendations into DevOps workflows through ITSM integrations, infrastructure-as-code tools, and MCP-based AI assistants. Ultimately, the tools that win will be the ones that close the loop — from visibility to insight to action — without requiring a human to manually connect the dots at every step. The article was originally published on Published in * * FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 12 Feb, 2026 | 6 Min read # How Startups Can Optimize Their Cloud Infrastructure More Effectively Aman Aggarwal Chief Operating Officer ### **Why is the lack of cloud cost visibility one of the biggest growth risks for startups today?** A few years ago, cloud costs were treated almost like background noise. Today, they are front and centre. A recent VC analysis showed infrastructure costs quietly becoming one of the largest expense lines for modern startups, sometimes consuming over 50% of COGS. That is a big shift - and a dangerous one if founders don’t have visibility. What makes a cloud tricky is that it doesn’t fail loudly. Bills creep up week after week. Auto-scaling works, new services get added, logs and data pile up and suddenly, the infra line item starts growing faster than revenue. I have seen startups shocked by a 30 - 40% jump in cloud costs in a single month, not because of growth, but because nobody was watching closely. This lack of visibility directly affects investor confidence. VCs now scrutinize gross margins, burn multiples, and cost discipline just as much as ARR. Poor infra hygiene has become a red flag. One well-known case involved a misconfigured script that ran up a six-figure cloud bill overnight, forcing the company to freeze hiring and delay product plans. Earlier, inefficiency could be masked by easy capital. That cushion is gone. Infrastructure influences runway, valuation, and strategic flexibility. If your cloud costs are growing faster than your business, that’s a risk. ### **How can startups identify hidden cloud costs before they impact runway and margins?** Hidden cloud costs usually come from places no one owns. Idle servers left running after sprints, over-sized databases “just to be safe”, test environments that never shut down - these are extremely common. Studies suggest nearly a third of cloud spend is wasted this way, and I have seen similar numbers on the ground. The first step is breaking the bill into understandable pieces. Instead of one large monthly number, startups should look at costs by service, environment, and team. Production vs. non-production is often eye-opening. In one case, nearly 20% of spend was tied up in unused development environments that no one had touched for weeks. Another area founders underestimate is data movement. Egress fees, especially for data-heavy applications like analytics or streaming, can quietly take up a massive chunk of the bill. Many teams only realize this after costs spike. Weekly reviews matter. Not finance-only reviews, but joint conversations between engineering and finance. When engineers see cost data alongside performance metrics, inefficiencies surface quickly. Finally, alerts and anomaly detection are critical. A sudden spike should never be a month-end surprise. Catching issues early protects margins, preserves runway, and avoids uncomfortable boardroom conversations later. ### **What cloud cost metrics should founders and CTOs track weekly and not just quarterly?** Quarterly reviews are too slow for cloud. Costs change daily, sometimes hourly. Founders and CTOs don’t need dozens of metrics, but a few weekly signals can prevent major surprises. First, track weekly cloud spend trends, not just the total bill. Is spend increasing faster than users, transactions, or revenue? If yes, dig deeper. Second, monitor cost by service category - compute, databases, storage, and data transfer behave very differently. Egress and storage growth often go unnoticed until they become painful. Third, keep an eye on cost per user or cost per transaction. This ties the infrastructure directly to business outcomes. If this metric worsens as you scale, something is off in architecture or usage. CTOs should also track utilisation ratios. Low CPU or memory usage with high spend is a clear sign of overprovisioning. Kubernetes clusters are especially prone to this. Finally, review waste indicators weekly - idle instances, unattached volumes, unused reservations. These are quick wins. Waiting for a quarterly review often means money already lost. ### **How does real-time cloud cost visibility improve infrastructure and scaling decisions?** Real-time visibility changes behaviour. When teams see the cost impact of their decisions instantly, they stop over-engineering “just in case.” Scaling becomes intentional instead of reactive. I have seen startups plan aggressive infra upgrades ahead of campaigns, only to rethink once they saw the real-time cost spike. In many cases, small optimizations - better caching, query tuning, or autoscaling - delivered the same performance without the extra spend. Cost visibility also makes experimentation safer. Teams can test new services or architectures, measure impact, and roll back quickly if costs outweigh benefits. Without visibility, fear creeps in - either teams overspend to stay safe, or hesitate to scale at all. For leadership, this connects tech choices to financial outcomes. Scaling stops being a pure engineering call and becomes a business decision balancing performance, customer experience, and margins. This feedback loop is a powerful framework for startups. It ensures infrastructure grows with demand - not ahead of it - and supports sustainable scale instead of expensive mistakes. ### **Which common cloud usage mistakes lead to overspending in early-stage startups?** The biggest mistake is overprovisioning early. Startups design for future scale instead of current needs, leading to oversized instances and underutilized clusters. This is especially common in Kubernetes environments. Another major issue is ignoring non-production environments. Dev and QA setups often run 24/7 with production-level configurations. Over time, these quietly burn cash without adding value. Data-related costs are also underestimated. Logs, backups, analytics pipelines, and cross-region traffic accumulate rapidly. Egress fees, in particular, catch teams by surprise. There’s also the commitment trap. Discounts like Savings Plans, including the recent Database Savings Plans, look attractive, but committing too early can backfire when workloads change. I’ve seen startups locked into unused capacity while still paying the bill. Finally, lack of ownership. When cloud costs belong to “everyone”, they belong to no one. Without clear accountability, waste becomes normalized. ### **How can startups balance performance, scalability, and cost optimization in the cloud?** This balance isn’t about choosing one over the other - it’s about timing and discipline. Early on, speed matters. But speed without awareness leads to inefficiency that compounds as you scale. Smart startups design architectures that scale horizontally and elastically, rather than vertically and permanently. Autoscaling, serverless, and managed services help match cost with real demand. Performance should be driven by actual usage patterns, not assumptions. Many performance issues are solved through better design, not bigger machines. Cost optimization should be continuous, not a panic response. Small, regular adjustments prevent painful corrections later. When teams review reliability, performance, and cost together, decisions naturally become more balanced. In practice, startups that treat cost as a core engineering metric don’t slow down - they scale with confidence and clarity. ### **What tools and practices deliver the fastest ROI for cloud cost optimization?** The fastest ROI usually comes from fundamentals. Native cloud tools for budgets, alerts, and cost breakdowns are simple but powerful, and often underused. Automated scheduling of non-production environments delivers immediate savings. Rightsizing based on actual utilization is another quick win, especially early on. From a process perspective, weekly cost reviews involving engineering make a bigger impact than dashboards alone. When developers see cost tied to their services, behaviour changes. Cloud credits should be treated strategically not burned early. Used wisely during growth phases, they can significantly extend the runway. Finally, many startups benefit from working with cloud optimization partners. They bring expertise across usage optimisation, rate optimisation, and governance - without the cost of building an in-house FinOps team too early. In today’s environment, cloud cost discipline isn’t about cutting corners. It’s about building a scalable, investor-ready business. **The article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 19 Sep, 2025 | 6 Min read # Rethinking Cloud Cost Optimization: Deepak Mittal’s Vision for Developers, Startups, and Enterprises Magazine Contributor CloudKeeper’s achievement of reaching $200 million in annualized revenue, without raising any venture capital, highlights a distinct and disciplined path to growth in the cloud cost optimization sector. Rather than relying on aggressive funding, the company has focused on building scalable, outcome-oriented solutions rooted in deep technical expertise. Leading this effort is **Founder and CEO Deepak Mittal** , whose background in engineering and commitment to delivering tangible value have shaped CloudKeeper’s trajectory from day one. In this interview, Mittal shares the core principles behind the company’s product-first philosophy, detailing how it built trust with both cloud providers and customers through consistent delivery and innovation. The conversation also sheds light on CloudKeeper’s approach to developer adoption, its disruption of traditional pricing expectations, and how it maintains credibility and adaptability across a diverse client base, from early-stage startups to complex, global enterprises. ### Q: CloudKeeper achieved 50% revenue growth and $200 million in annualized revenue without venture funding. What strategic decisions enabled this capital-efficient scaling while competing against well-funded FinOps rivals? **Deepak:** CloudKeeper was born out of To The New, a bootstrapped company I co-founded with a strong cloud and DevOps foundation. CloudKeeper followed the same principles from the start, focusing on delivering real customer outcomes through a highly skilled engineering team and a product-first mindset. Instead of chasing growth through capital, we built scalable, innovative solutions that addressed core cloud cost challenges supported by a team of experts. Our consistent delivery earned us trust not just from customers, but from cloud providers like AWS and GCP, who now actively recommend us. That ecosystem support, combined with disciplined execution, has helped us scale without raising a single dollar. ### Q: Your AWS console-integrated Tuner platform fundamentally changes developer workflows. How did you identify this niche opportunity and convince engineers to adopt optimization tools within their existing processes? **Deepak:** One of the consistent challenges highlighted by the FinOps Foundation is getting engineering teams to own cloud cost decisions. It’s understandable as engineers are measured on delivery and performance, not cost. So we knew any solution we built had to align with that reality, not fight it. CloudKeeper Tuner has been designed with that philosophy in mind, an There were no blueprints for this, we were stepping into uncharted territory. But that gave us the freedom to innovate on our own terms. It was a leap of faith, and it paid off because we put the developer experience at the heart of it. ### Q: CloudKeeper offers savings without long-term commitments. How does this model challenge traditional cloud providers' lock-in strategies, and what pushback have you encountered? **Deepak:** CloudKeeper AZ aims to ### Q: With 100+ AWS-certified engineers, how do you maintain technical depth while expanding into multi-cloud optimization and AI workload management? **Deepak:** We have over 100 certified cloud experts across AWS and Google Cloud, many of whom also hold FinOps Foundation certifications. Their deep expertise spans cloud, DevOps, FinOps, and cost optimization. We began integrating AI well before it was mainstream, launching CloudKeeper Auto in 2022, an We’ve built a strong culture of continuous learning through dedicated cloud learning paths, full certification sponsorships, and internal hackathons to foster innovation. Engineers are incentivized to experiment, upskill, and contribute to technical breakthroughs. A dedicated Center of Excellence now drives our multi-cloud and AI workload strategy forward. ### Q: Your Well-Architected Reviews are funded entirely by CloudKeeper - what measurable business outcomes justify this investment compared to paid consulting models? **Deepak:** Our fully-funded Well-Architected Reviews deliver immediate, tangible outcomes - unlike generic trials or passive demos. They allow us to dive deep into a customer’s actual cloud environment, identify inefficiencies, and Moreover, these reviews generate high-value insights that inform our roadmap and strengthen our optimization models. Even in cases where a customer doesn’t immediately convert, the goodwill and referrals we earn create a strong organic growth channel, making the ROI of these funded reviews far superior to traditional paid consulting approaches. ### Q: As you expand in North America, how will CloudKeeper's approach differ when advising cost-conscious startups versus Fortune 500 enterprises with complex cloud estates? **Deepak:** Our approach remains consistent: anchored in personalized engagement – but it flexes to match the scale and needs of each business. We’ve worked with both large enterprises like FranConnect and AMI Strategies, and nimble startups like Appsmith and Chain.io, delivering tailored cost optimization outcomes across industries such as SaaS, FinTech, Healthcare, and Retail. Our team of experts performs in-depth evaluations, aligning Well-Architected Reviews with business goals to uncover savings and eliminate waste. Startups often look for quick wins, such as the immediate savings offered by CloudKeeper AZ, while enterprises tend to focus on modular services like usage optimization, ### Q: With AI infrastructure costs projected to triple, what architectural principles is CloudKeeper advocating to prevent a new wave of cloud waste in generative AI deployments? **Deepak:** Generative AI workloads are extremely resource-hungry, and without the right guardrails, they can lead to massive cloud waste. At CloudKeeper, we promote building cost-aware architectures, choosing the right compute options, isolating workloads smartly, and using flexible pricing models like spot instances wherever possible. We also guide teams to Our platforms like CloudKeeper Tuner and Lens are evolving to bring visibility and control to AI-specific spending, right from the start. The goal is simple: help businesses scale AI with confidence without the budget surprises. CloudKeeper’s evolution reflects a rare mix of engineering precision, product insight, and commercial focus. Through embedding optimization within developer workflows, funding hands-on reviews, and staying ahead of multi-cloud and AI workload needs, the company has set itself apart in the FinOps space. Deepak Mittal’s perspective reveals a founder deeply rooted in technology, yet sharply attuned to business impact. As cloud costs rise and architectures grow more complex, CloudKeeper offers more than just savings, it provides strategic guidance for companies aiming to scale with control and clarity. Its ability to adapt across startup and enterprise environments, while maintaining measurable outcomes, positions it as a trusted partner for organizations rethinking how they manage cloud efficiency and long-term growth. **The article was originally published on****.** FOUND THIS USEFUL? SHARE IT * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 06 Jan, 2026 | 4 Min read # CloudKeeper Accelerates Global Momentum in 2025 with New Leadership and New Platform Suite **New York, USA, 6th January 2026** - CloudKeeper marked 2025 as one of its most consequential years since inception, driven by strategic expansion into the North American market, significant leadership additions, major industry recognitions, and the launch of its flagship CloudKeeper Platform Suite. The company’s growth trajectory reflects strong demand for comprehensive cloud cost management and FinOps solutions that help businesses manage cloud spend with precision and depth. CloudKeeper’s A central milestone for CloudKeeper in 2025 was the launch of two industry-first product innovations, signaling a decisive shift toward intelligent, outcome-driven cloud financial management. The company introduced CloudKeeper Tuner, the industry’s first In parallel, CloudKeeper unveiled its Strengthening its GenAI capabilities was another major focus area in 2025. The company launched the CloudKeeper GenAI Launchpad to CloudKeeper also continued to strengthen its leadership throughout the year. Key appointments included **Sanjeev Mittal as Chief Product and Technology Officer; Kenneth Ziegler and Deepak Singh as Senior Advisors and Board Members; Gaurav Barman as Chief Revenue Officer, India; Ryan Frielino as Chief Revenue Officer, North America; and Kirti Sharma as Chief People Officer**. These leadership additions have played a critical role in shaping product strategy, accelerating go-to-market execution, and supporting the company’s expanding global operations. The company 2025 reinforced CloudKeeper’s strong growth trajectory. In addition to its $220 million annualized revenue milestone, AWS recognized the company for driving the highest-value new launches during the year, while within the Google Cloud ecosystem, CloudKeeper was named Northern Titan at the Redington - Google Cloud Shatakoti event - recognizing its rapid growth and growing regional impact. These accomplishments underscore CloudKeeper’s expanding influence across both AWS and Google Cloud ecosystems. _“2025 marked a defining chapter in CloudKeeper’s journey from our independence to our rapid scale in revenue, products, people, and markets,”_ **said Deepak Mittal, CEO of CloudKeeper.** _“Our expansion in North America, our industry-first platform launches, and our deep investments in GenAI reflect a clear commitment to helping companies manage cloud complexity with intelligence, automation, and confidence.”_ CloudKeeper’s achievements in 2025 illustrate its growing role as a Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 06 Apr, 2026 | 2 Min read # CloudKeeper Achieves AWS AI Services Competency, Reinforcing Its Role In Scalable AI Adoption **New York, USA - 6th April 2026** - CloudKeeper, an end-to-end cloud & AI cost optimization and FinOps company, today announced that it has achieved the Amazon Web Services (AWS) AI Services Competency, recognizing its expertise in building and scaling production-grade AI solutions on AWS. With this recognition, CloudKeeper has validated its capabilities in supporting businesses to move beyond experimentation and deliver measurable outcomes from AI investments. This includes demonstrated expertise in building production-grade AI solutions, integrating AI services within existing enterprise environments, and deploying them in alignment with _“Achieving the AWS AI Services Competency validates our execution-first approach to AI,”_ **said Deepak Mittal, CEO, CloudKeeper.**_“Enterprises today are looking for AI that works beyond controlled environments. This recognition reflects our ability to help customers build solutions that are scalable, secure, and grounded in real business impact.”_ The competency is awarded through a rigorous evaluation of technical expertise, architectural excellence, and demonstrated customer success. It also reflects CloudKeeper’s ability to _“Building AI is only half the job. Running it efficiently is where most teams struggle,”_**said Aman Aggarwal, COO, CloudKeeper.**_“As usage grows, costs and complexity can spiral quickly. We help organizations stay in control while continuing to scale.”_ CloudKeeper has been actively expanding its AI portfolio to support enterprise adoption at scale. This includes its role as an**LensGPT** , further strengthens this approach by bringing With this milestone, CloudKeeper is set to deepen its collaboration within the AWS ecosystem and expand its ability to support organizations across industries. The focus is on enabling enterprises to operationalize AI in a way that is structured, responsible, and aligned with long-term business outcomes. Read the Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 24 Dec, 2025 | 2 Min read # CloudKeeper appoints former AWS and Google Cloud leader Deepak Singh as Senior Advisor **New Delhi, India, 24th December 2025** - CloudKeeper, a global FinOps and cloud cost optimization company, has announced the appointment of Deepak Singh, veteran enterprise technology leader and former senior executive at AWS and Google, to its Board of Advisors. This appointment aligns with CloudKeeper’s broader strategy of strengthening leadership capabilities and reinforcing its position as a leading player in the Currently serving as the Senior Director for Enterprise Business - India & SAARC at Palo Alto Networks, Deepak brings more than two decades of experience across cloud computing, AI ecosystems, and cybersecurity. He has also held leadership roles at Google, AWS, VMware, HP, and Intel and has contributed significantly to the early build-out of _“Deepak brings a rare blend of technical depth, platform insight, and enterprise leadership. His experience shaping cloud, AI, and cybersecurity ecosystems globally gives him a clear understanding of where the market is headed.”_ **said Deepak Mittal, CEO, CloudKeeper**. _“CloudKeeper is at an important point in our expansion across the international markets, and Deepak’s guidance will be valuable as we strengthen our product strategy and scale our global operations.”_ _“CloudKeeper has consistently stood out in industry conversations as a company for their impressive work in_ _. Over the past year, I’ve observed their work closely, and the momentum is clearly building. I’m glad to join the Board and look forward to contributing to CloudKeeper’s next phase of growth.”_ **said Deepak Singh**. Beyond his corporate career, Deepak is an active industry advisor and early-stage investor supporting builders and entrepreneurs across India. Outside work, he is rooted in his family’s farming legacy and actively supports community cricket through “Krickshetra Sports,” along with initiatives that uplift women in leadership. At CloudKeeper, Deepak Singh will focus on guiding the company’s strategic direction across India and global markets. Based in New Delhi, he will work closely with the leadership team to strengthen CloudKeeper’s product innovation, expand strategic partnerships, and support Read the Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 18 Dec, 2025 | 2 Min read # CloudKeeper Appoints Gaurav Barman as Chief Revenue Officer (CRO) for India **New Delhi, India, 17th December 2025** - CloudKeeper, a global FinOps and cloud cost optimization company, has announced the appointment of Gaurav Barman as its Chief Revenue Officer (CRO) for India. This marks an important step in strengthening the company’s leadership team as it continues to expand its presence in the Gaurav brings over 21 years of experience across the cloud, SaaS, and data platform ecosystem. In his previous roles at companies such as AWS and Cloudera, Gaurav led go-to-market programs, built strategic alliances, and managed engagements with a range of startups, digital natives and enterprise customers. His stint as a founder of a technology venture, gave him hands-on exposure to the operational and strategic aspects of building and scaling businesses. An IIT-IIM alumnus, Gaurav has worked with customers across multiple industries, including BFSI, Healthcare, Retail, CPG, and Manufacturing, with experience in developing new markets and executing channel sales programs. His background spans cloud infrastructure, data analytics, **Deepak Mittal, CEO of CloudKeepe** r, said: _“Finding the right leader for a role as critical as the CRO is never easy - you look for someone who understands the pace of the cloud industry and who has operated at scale in environments like AWS, brings deep customer insight, and can scale sustainably. With Gaurav, we’ve found exactly that. We are thrilled to welcome him and are excited for the impact he will create.”_ Sharing his thoughts on joining CloudKeeper, **Gaurav Barman said** : _“CloudKeeper is at a pivotal point in its journey, and the opportunity ahead is tremendous. Over the past couple of weeks, I’ve been on the ground meeting customers, partners, and teams, and the energy has been incredible. I’m truly excited to help shape the next phase of growth and deliver even greater value to customers across India.”._ In his new role at CloudKeeper, Gaurav will lead revenue strategy, enterprise expansion, and strategic partnerships in India further solidifying CloudKeeper’s position as the preferred Read the Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 Mar, 2026 | 2 Min read # CloudKeeper Certified as a Great Place to Work for the Second Consecutive Year **New Delhi, India, 9th March 2026** - CloudKeeper, a The certification is based entirely on employee feedback captured through the Great Place to Work® Trust Index Survey, where CloudKeeper achieved a strong score of 87. Recognized globally as the gold standard for assessing workplace culture, the certification reflects high levels of trust, fairness, pride, and camaraderie experienced by employees. Commenting on the recognition, Deepak Mittal, CEO of CloudKeeper, said: “Earning the Great Place to Work certification for the second year in a row is deeply meaningful because it comes directly from our people. At CloudKeeper, we focus on building trust, encouraging ownership, and creating an environment where learning and innovation happen naturally. This recognition truly belongs to every CKer.” CloudKeeper’s people practices are rooted in continuous learning, innovation, and shared ownership. To support a future-ready workforce, the company has established an AI Center of Excellence and launched CKers Sidekick, an internal AI-powered platform that helps employees AI adoption is reinforced through internal learning sessions, peer-led knowledge sharing, and governance frameworks that encourage responsible and practical usage. To further build AI fluency, CloudKeeper introduced CK AI Exchange, a people-driven initiative where employees propose topics, lead sessions, and shape the learning agenda based on shared interests and business relevance. For early-career talent, a structured six-month BootCamp blends classroom learning with hands-on projects and behavioral training. Employee engagement is also driven by the CK Fun Fam, a volunteer-led team that fosters connection and belonging across locations. What sets strong workplaces apart is how intentionally they invest in their people,” said Saloni Jain, Sr. Customer Success Analyst , Great Place to Work ® ️ India. “CloudKeeper's strong scores in Leadership, Camaraderie, and Justice reflect a people-centric culture, one that supports performance while ensuring employees feel valued, trusted, and treated fairly.” As CloudKeeper continues to expand its business globally, the company remains committed to nurturing a culture built on trust, collaboration, and shared responsibility - where people feel empowered to do their best work and grow together. Read the Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 15 Jan, 2026 | 3 Min read # CloudKeeper Earns #1 Position in G2 Winter 2026 Report for Cloud Cost Management Worldwide ## **With a back-to-back 100% customer satisfaction score, CloudKeeper has outperformed 60+ platforms.** **New York, USA, 14th January 2026** - CloudKeeper, a leading cloud cost optimization company, has been recognized as the #1 globally ranked solution in G2's Winter 2026 Grid Report for Cloud Cost Management, outperforming 60+ competitive platforms in the category. This marks its 12th recognition as a global leader in cloud cost management. This season, CloudKeeper's exceptional performance is underscored by The company has secured the #1 position across 20 G2 reports, including the Asia Regional Grid, Momentum Grid, Mid-Market Grid, India Regional Grid, and the Relationship Index for In addition to its top global ranking, CloudKeeper earned 39 prestigious G2 awards, including Momentum Leader, Regional Leader(Asia), High Performer, Best Results, Best Meets Requirements, Best Usability, _“We’re incredibly proud of this milestone. Seeing our customers consistently rate CloudKeeper at the top and achieving 100% satisfaction again tells us we’re solving real problems in these increasingly complex cloud environments and delivering meaningful value at scale,”_ **said Deepak Mittal, Founder & CEO at CloudKeeper.** _"These G2 recognitions motivate us to keep raising the bar for what customers should expect from a_ _.”_ _"CloudKeeper achieved what no other cloud cost management partner could - a perfect 100% satisfaction score in G2's Fall 2025 Reports, followed by the #1 global ranking across 60+ competitors in our Winter 2026 Report. With 99% of users giving 4 or 5 stars, the message from customers is clear: they want_ _, and CloudKeeper is setting that standard,"_ **said Chris Perrine, Vice President & Managing Director, G2 Asia Pacific.** ## **The Real Validation: Customer Voices** _"Exceptional AWS Support with Lightning-Fast Issue Resolution. CloudKeeper’s responsiveness and expertise stand out the most."_ **- Pradeep Goswami** **DevOps Engineer - Freight Tiger** _"With CloudKeeper, we_ _, and get insight into where we can optimize — something we previously missed."_ **- Arun Kumar M G** **Senior DevOps Engineer** _"The support from the Cloudkeeper team is unparalleled. They even go the extra mile of explaining the "how" and not only the "what" should be done."_ **- Verified G2 Review** _"They act like an extension of our own team,__. A truly valuable partner for AWS cost management."_ **-Palani E** **Principal Technical Architect** _"I am really impressed by their responsiveness and commitment._ _I highly recommend them to any organization looking for a trusted partner in cloud transformation."_ **- Verified G2 Review** CloudKeeper has been named a Leader based on receiving a high customer satisfaction score and having a large market presence, along with 99% of users rating it 4 or 5 stars. Rankings on G2 reports heavily rely on verified and authentic reviews provided by real software buyers. Read the Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 18 Nov, 2025 | 3 Min read # CloudKeeper launches industry-first all-in-one FinOps Suite delivering guaranteed results **New York, USA, 17th November 2025** - CloudKeeper, a leading provider of comprehensive cloud cost optimization and FinOps solutions, today announced the launch of the The new suite unifies CloudKeeper’s proven FinOps platforms, AI capabilities, and expert-led services to help organizations achieve continuous visibility, control, and savings across their cloud environments. At the core of the CloudKeeper Platform Suite are three platforms: * **CloudKeeper Lens** – offers * **CloudKeeper Tuner** – drives usage optimization through * **CloudKeeper Commit** – enables rate optimization by In addition, the Platform Suite includes several value-added services that enhance end-to-end cloud management: * **CloudKeeper Check** – * **CloudKeeper Expert** – 24x7 access to * **CloudKeeper GenAI** – an The Platform Suite reflects CloudKeeper’s three-phase strategy for sustainable cloud optimization, blending visibility, automation, and intelligence to drive measurable ROI within 30 - 90 days. _“Even when we introduced our first solution, CloudKeeper AZ, our vision was to make_ _easily accessible to every business,”_ said **Deepak Mittal** , **CEO, CloudKeeper**. _“With the CloudKeeper Platform Suite, we’re expanding that vision through an integrated ecosystem that helps organizations achieve control, efficiency, and lasting value from their cloud investments.”_ The Platform Suite is available in two flexible deployment models: * **SaaS Deployment** - hosted securely on CloudKeeper’s infrastructure and accessible over the internet. * **Private Cloud Deployment** - hosted within the customer’s environment with CloudKeeper-managed setup, support, and upgrades. This flexibility allows enterprises to adopt the platform in alignment with their security, compliance, and operational preferences. _“Cloud optimization has often evolved in silos across tools and processes,”_ said **Sanjeev Mittal** , **Chief Product and Technology Officer at CloudKeeper**._“With the Platform Suite, we wanted to build an integrated environment where automation, AI, and expert support work together. The GenAI component adds contextual intelligence,__make smarter, faster decisions.”_ The CloudKeeper Platform Suite is backed by a results-based pricing model, no lock-ins, and the assurance of guaranteed results. CloudKeeper partners with enterprise customers through a structured ‘Assess’ phase to identify guaranteed cost-saving opportunities, followed by an accelerated ‘Optimize’ phase where those savings are realized within just a few weeks. This structured approach - combining the Platform Suite with expert-led services - enables performance-based engagements to deliver business outcomes that consistently drive value. CloudKeeper recently strengthened its leadership team with several key appointments, including Sanjeev Mittal as the Chief Product and Technology Officer. The launch of the Platform Suite builds on this momentum and further positions the company at the forefront of FinOps innovation. Explore the Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 11 Feb, 2026 | 3 Min read # CloudKeeper Launches LensGPT, Agentic FinOps Consultant combining Multiple AI Tools **New York, USA, 11th February 2026** - CloudKeeper, a global FinOps and cloud cost optimization company, today announced the launch of **CloudKeeper LensGPT** , an Built to support AWS and Google Cloud environments, the platform provides In traditional cloud cost management workflows, teams often need to pull reports, apply filters, and perform follow-up analysis across multiple tools before arriving at a decision. CloudKeeper positions LensGPT as a streamlined alternative to this problem with its unique agentic AI approach. Rather than limiting output to static insights, the platform applies multi-step reasoning to identify cost drivers and propose practical actions for optimization. Recommendations take into account how cloud infrastructure is set up, including the services being used, regions, accounts, and environments, helping teams move from _“AI has changed how people look for information. Large Language Models (LLMs) have made it natural to ask questions and expect direct answers,”_ **said Deepak Mittal, CEO, CloudKeeper**._“LensGPT brings that experience to FinOps. Instead of spending time assembling reports, teams can ask a question and get a clear response, along with guidance on what to do next.”_ LensGPT is _“Agentic AI represents a step ahead from generating responses to enabling guided decision-making,”_ **said Sanjeev Mittal, Chief Product and Technology Officer, CloudKeeper**. _“At CloudKeeper, we’re investing deeply in applied AI through our AI Center of Excellence. LensGPT is one outcome of that effort, with more AI-powered solutions in development to address real-world cloud operations challenges.”_ Ahead of its public launch, CloudKeeper made LensGPT available to a select group of customers as part of a pre-launch feedback program. According to the company, the response has been strong, with several customers opting to continue using the platform beyond the initial access period. Early feedback highlighted faster access to FinOps data, reduced dependency on manual reporting, and improved clarity for both business and engineering teams. “ _Early feedback has been one of the strongest indicators of product–market fit for us,”_**said Naman Jain, Chief Growth and Marketing Officer, CloudKeeper.** _“CFOs have shared that they can now get clear answers on cloud spend without looping in multiple teams, and engineering teams have told us they’re spending far less time building reports and dashboards. That feedback reinforces that LensGPT is solving a very real, everyday problem.”_ The launch of LensGPT follows a year of significant growth and innovation for CloudKeeper, including the introduction of its **To learn more, visit:****.** Read the Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 05 Jul, 2023 | 2 Min read # CloudKeeper named a Key Player in IDC Market Glance: FinOps Cloud Transparency, 2Q23 CloudKeeper, a leading AWS FinOps and cost optimization solution, has been named a key player in the IDC Market Glance: FinOps Cloud Transparency, 2Q23. This Market Glance examines how cloud cost transparency software and service providers support enterprise FinOps teams. CloudKeeper's inclusion in the report demonstrates its expertise and contribution to the competitive cloud cost transparency market. The IDC Market Glance highlights the prominent FinOps cloud cost providers and vendors in the cloud cost transparency market, including FinOps software companies, hyper scalers, service providers, and niche vendors. The report maps out the five main segments of the market: Cloud Iaas Resource Optimization, Reporting and Pricing Analytics/Recommendations, Cloud Software as a Service Management, FinOps Service Providers, and Container Optimization. The report identifies CloudKeeper as a leading provider in three out of the five key segments: Cloud Iaas Resource Optimization, Reporting and Pricing Analytics/Recommendations, and FinOps Service Providers. **Deepak Mittal - CEO, CloudKeeper** , said, "We are honored to be featured in the IDC Market Glance: FinOps Cloud Transparency. This acknowledgment solidifies our position as a trusted FinOps partner in helping organizations optimize their cloud costs and drive significant ROI from their cloud investments.” He further added, “The market is continuously evolving and growing, and CloudKeeper is well-positioned to capitalize on this growth with its customer-centric FinOps offerings which have already benefited over 300+ global customers." Each segment mentioned in the report signifies essential capabilities provided to the FinOps teams by the vendors. CloudKeeper’s mention in the Cloud Iaas Resource Optimization segment showcases its ability to streamline and optimize cloud resources to achieve maximum efficiency and cost savings. With a focus on Reporting and Pricing Analytics/Recommendations, CloudKeeper offers comprehensive solutions tailored to meet the specific FinOps needs and customer segments. The FinOps solutions by CloudKeeper include Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 14 Oct, 2025 | 3 Min read # CloudKeeper Named a Leader in G2 Fall 2025 - Only Partner to Achieve 100% Satisfaction Score **New York, USA, 14th October 2025** - CloudKeeper, the comprehensive cloud cost optimization company, has once again been **recognized as a Leader in G2’s Fall 2025 Reports** , marking its 11th recognition as a global leader in cloud cost management. This season, CloudKeeper achieved a **remarkable 100% satisfaction score** , making it **the only partner in its category to reach this milestone**. It is rated **#1 for user satisfaction, competitive pricing, cloud optimization, proactive assistance & multiple crucial categories**. It holds a rating in the Top 3 for more than 25+ categories. In addition, it is **ranked #1 across 19 G2 reports, including the Enterprise Usability Index, Asia Regional Grid®, the Momentum Grid®, and the Mid-Market Grid® for Cloud Cost Management** , establishing its dominance across key markets and business segments. CloudKeeper proudly **earned 36 G2 awards, including Momentum Leader, Best Results, Best Meets Requirements, Best Support, Best Usability, Best Relationship, and more**. _“Every G2 badge is an honor, but achieving a 100% satisfaction score makes this recognition truly special."_ said **Deepak Mittal, Founder & CEO of CloudKeeper**. "_When someone takes time to write a review saying we've genuinely helped their business, that means everything to us. It shows our customers feel heard, supported, and genuinely better off with us by their side - and that’s exactly the kind of partner we want to be.”_ _“CloudKeeper has once again delivered outstanding results in G2’s Fall 2025 Reports, building on its success in our_ _categories. Their commitment to making solutions simple to implement, easy to use, and delivering rapid ROI is evident in both their customer reviews and our data. CloudKeeper strikes a great balance by taking complex platforms and making them accessible, while helping businesses achieve meaningful results with ease,”_ said **Chris Perrine, Vice President & Managing Director, G2 Asia Pacific.** The G2 reviews that earned CloudKeeper this recognition tell the same story & support the satisfaction score it achieved. _“Any challenges or questions were addressed promptly, showcasing their dedication to customer satisfaction. It's clear that they prioritize building long-term relationships based on trust and mutual growth. The CloudKeeper team has been an extended arm for us to streamline cloud infra management.”_ - **Verified G2 Review** _“The ease of use stands out - it’s simple enough_ _. The implementation was quick, with great onboarding support. Their customer support team is highly responsive and consistently helpful.”_ - **Senior DevOps Engineer, Verified G2 Review** _"We have been using CloudKeeper for quite some time and are happy to say that we no longer worry much about our AWS costs because CloudKeeper handles it for us.__, and the platform is very user-friendly. Overall, we are very satisfied with CloudKeeper!"_ - **DevOps - Technical Lead, Glider.ai** _“The support team at CloudKeeper is outstanding. They're always available for meetings, providing proactive recommendations.”_ - **Co-Founder & CTO, Verified G2 Review** ## **Looking Forward** CloudKeeper’s 11th recognition marks another step in its continued focus on advancing cloud optimization. The company remains invested in enhancing automation, These initiatives reflect CloudKeeper’s commitment to delivering measurable value to its customers and driving innovation in the cloud cost optimization space. CloudKeeper has been named a Leader based on receiving a high customer satisfaction score and having a large market presence, along with 99% of users rating it 4 or 5 stars. Rankings on G2 reports heavily rely on verified and authentic reviews provided by real software buyers. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 12 Dec, 2025 | 2 Min read # CloudKeeper named a Major Contender in Everest Group FinOps Cost Management Products PEAK Matrix® Assessment 2025 **New York, USA, November 25, 2025** - CloudKeeper, a global FinOps and cloud cost optimization company, has been recognized as a Major Contender in the Everest Group FinOps Cost Management Products PEAK Matrix® Assessment 2025. The annual assessment is one of the industry’s most respected benchmarks, evaluating leading FinOps platforms on their capabilities, innovation maturity, and ability to deliver measurable value to customers. CloudKeeper has shown substantial improvement in its position from last year’s assessment, the FinOps Cloud Cost Management Product PEAK Matrix® Assessment 2024 report, reflecting the strong progress they have made in their _“Being named a Major Contender in the Everest Group PEAK Matrix® is a proud milestone for us,”_ said **Deepak Mittal, CEO of CloudKeeper**._“With AI adoption accelerating across modern cloud stacks, companies need FinOps frameworks that are smarter, faster, and more adaptive. This recognition validates our focus on helping customers achieve continuous optimization through_ _and engineering excellence.”_ Everest Group acknowledged CloudKeeper for its platform depth, ease of use, strong customer outcomes, and a CloudKeeper has recently launched the This recognition from Everest Group further underscores CloudKeeper’s strong momentum in delivering next-generation FinOps capabilities to enterprises across the world. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 13 Aug, 2025 | 2 Min read # CloudKeeper Once Again Named a Leader in G2's Summer 2025 Report, Backed by 99% User Satisfaction ## The company outperformed industry benchmarks in key satisfaction metrics **New York, 13th, August, 2025** - CloudKeeper, a comprehensive cloud cost optimization company, has once again been recognized as the leader in the G2 Summer 2025 Grid® Report, marking its 10th recognition as a global leader. CloudKeeper stands strong in the second position as the best cloud cost management solution worldwide. The platform also secured the first position in the **Asia Pacific Regional Grid®, Mid-Market Grid®, India Regional Grid®, and the Enterprise Usability Index** , further establishing its dominance across key markets and business segments. **Highlights:** * Rated #1 for Quality of Support, Competitive Pricing & Ease of Admin * Backed by a remarkable 99% Satisfaction Score * Rated in the Top 3 in more than 25+ categories CloudKeeper bagged an impressive 32 G2 badges this season, including **Momentum Leader, Best Results, Best Meets Requirements, Best Support, Best Usability, Best Relationship, Easiest Admin** and many more. “This recognition from G2 is a reflection of the trust our customers place in us and the real, measurable impact CloudKeeper brings to their cloud journeys. In a crowded market, our end-to-end approach continues to set us apart. We're proud to be the go-to partner for teams looking to simplify and optimize their cloud costs”, said **Deepak Mittal, Founder & CEO of CloudKeeper.** "CloudKeeper once again saw amazing results in G2's reports. We saw their enterprise strategy really bearing fruit as our research showed them delivering Best Usability, Easiest Admin, Best Meets Requirements, and Best Results amongst their peers, said **Chris Perrine, Vice President & Managing Director - APAC of G2**. He further added, "It was not just another solid quarter for CloudKeeper, but a quarter where they continued to solidify their leadership across their categories." From DevOps Heads to CTOs, from CFOs to CEOs, CloudKeeper remains a preferred choice. **Aakash Sharma, Lead CloudOps at Seclore** , said in a G2 review, “CloudKeeper is a game-changer for cloud cost management. It is essential for controlling cloud spend and making the most out of the infrastructure.” While **Ajay Yadav, a DevOps leader from GirnarSoft** , shared, “CloudKeeper acts as our FinOps vertical and helps us with cloud financial management, ensuring that we can focus on our delivery expertise.” CloudKeeper has been named a Leader based on receiving a high customer satisfaction score and having a large market presence, along with 99% of users rating it 4 or 5 stars. Rankings on G2 reports heavily rely on verified and authentic reviews provided by real software buyers. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 09 Sep, 2025 | 3 Min read # CloudKeeper Welcomes Sanjeev Mittal as Chief Product and Technology Officer **New York, USA, 9th September 2025** - CloudKeeper, a leading provider of end-to-end cloud cost optimization solutions, today announced the appointment of Sanjeev Mittal as Chief Product and Technology Officer (CPTO). Sanjeev will lead CloudKeeper’s product and technology strategy, strengthening its product capabilities in cloud optimization and accelerating innovation to meet the evolving needs of global businesses. Based in London, Sanjeev brings over two decades of global leadership experience in enterprise software, cloud solutions, and product-led growth. Most recently, he led a successful turnaround of a SaaS APM company with 800+ customers. After a successful acquisition of Stackify by BMC Software, he continued with the PE firm to repeat the GTM playbook across its portfolio companies. Prior to this, he held senior roles at global enterprises like Amazon Web Services (AWS), Oracle, Nokia and Sapient. At AWS, Sanjeev played a pivotal role in growing ISV sales by developing robust go-to-market strategies, and product innovations - working closely with enterprise ISVs to co-create cloud-based solutions. His expertise with cloud-native offerings comes at a time when CloudKeeper is building solutions to help organizations navigate the shift driven by technologies like AI and get more value from cloud. Commenting on the appointment, **Deepak Mittal, CEO of CloudKeeper said,** _"We are excited to welcome Sanjeev as our Chief Product and Technology Officer (CPTO). His extensive experience with global technology firms and deep understanding of the cloud ecosystem will be invaluable as we continue to strengthen the growth of our products.On a personal note, Sanjeev and I started our careers around the same time, and it’s amazing to team up with him again to shape CloudKeeper’s future. Having used CloudKeeper’s services himself, he truly understands what our customers need."_ Sharing his thoughts on the new role, **Sanjeev Mittal** **said,** _"CloudKeeper has established itself as a trusted partner in cloud cost optimization and FinOps, and I am excited to help expand its impact. With cloud and AI evolving hand in hand, businesses need products that deliver efficiency while enabling innovation. I look forward to contributing to CloudKeeper’s mission of empowering customers to realize the full potential of their cloud investments."_ CloudKeeper is one of the world’s most trusted providers of cloud cost optimization and FinOps solutions, helping businesses simplify cloud management and unlock sustainable savings. Always at the forefront of innovation, CloudKeeper has introduced platforms like CloudKeeper Tuner, the industry’s first With Sanjeev’s appointment, CloudKeeper is set to build on this momentum - strengthening its product portfolio and delivering solutions that align with evolving market needs and the opportunities shaping the future of cloud. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close At CloudKeeper, great work begins with happy people and ends with happy customers. We consider ourselves more than just a company; we are a close-knit family of like-minded CKers who love to collaborate and make a real impact in the cloud industry. Let’s e-meet our team! * * * * * * Deepak Mittal Chairman, Founder & CEO Deepak is a visionary leader who spearheads the development and execution of long-term business strategies, driving the company's vision to provide world-class cloud engineering services to businesses globally, enabling them to achieve their technological goals and drive innovation. * Kenneth Ziegler Senior Advisor & Board Member Ken is a seasoned leader in the technology and cloud services industry. As the former President and CEO of Logicworks (now RapidScale), Ken played a pivotal role in transforming the company into a trusted partner for AWS and Azure customers. * Deepak Singh Senior Advisor and Board Member Deepak has held leadership roles at Google, AWS, VMware, HP, and Intel, playing a key role in the early build-up of the cloud computing and AI ecosystem at Google and AWS. Beyond this, he is an active industry advisor and early-stage investor, supporting entrepreneurs across India * Deepak Mittal Chairman, Founder & CEO Deepak is a visionary leader who spearheads the development and execution of long-term business strategies, driving the company's vision to provide world-class cloud engineering services to businesses globally, enabling them to achieve their technological goals and drive innovation. * Aman Aggarwal Chief Operating Officer Aman spearheads business operations, strategic execution, and cross-functional alignment to drive sustainable growth. With deep expertise in the Cloud space, Aman blends deep domain expertise with leadership to enhance customer value, foster innovation, and scale CloudKeeper’s impact globally. * Naman Jain Chief Growth & Marketing Officer Naman is a seasoned GTM leader with deep expertise in technology sales, marketing, & strategic planning. Recognized for his strategic vision, operational rigor, and results-driven mindset, he has played a pivotal role in accelerating the company’s growth & market success. * Ryan Freilino Chief Revenue Officer (North America) Ryan brings over a decade of leadership experience in building high-performing teams & driving revenue growth. He drives our expansion across North America, leading GTM strategy, growing partnerships, & helping businesses maximize cloud value. * Sanjeev Mittal Chief Product & Technology Officer Sanjeev Mittal is a seasoned product leader with over two decades of global leadership experience in Cloud, SaaS, and Software Development. He has driven product innovation, delivery, GTM, and scalable growth at AWS, Stackify, Oracle, and Sapient. He's obsessed with delivering cost efficiency, customer adoption, and real business impact. * Gaurav Barman Chief Revenue Officer - India Gaurav Barman is an IIT-IIM alumnus with over two decades of leadership in cloud and SaaS revenue growth. He leads revenue strategy, enterprise expansion, & partnerships, strengthening the CloudKeeper’s leadership in cloud cost optimization. * Kirti Sharma Chief People Officer With deep expertise across Organizational Development, Talent Enablement, & Product Management, Kirti combines people-first leadership with HR tech innovation. She has spearheaded multiple strategic initiatives to elevate organizational culture, strengthen employee engagement, & drive meaningful business impact. * Neeraj Gupta Senior Director - Customer Success Neeraj excels at leading end-to-end infrastructure projects. Specializing in AWS cloud solutions since its inception, Neeraj possesses extensive expertise in optimizing cloud spend and ensuring compliance with WAR standards for customers. * Vikram Singh Jain Director DevOps Vikram is a customer-obsessed technology leader with expertise in Global DevOps, SRE, and GenAI automation across multi–cloud-native environments. He excels at fostering cross-functional collaboration to deliver secure, resilient, and cost-optimized platforms. * Vivek Vinod Sinha Director - Customer Success Vivek brings leadership experience in AWS cloud growth, customer success, and strategic partnerships. An IIM alumnus, he is passionate about building strong customer-focused teams and delivering meaningful results for clients. * Amit Raturi Senior Technical Manager Amit is part of the platform and data teams at CloudKeeper, managing end-to-end technology ecosystems. He specialises in building scalable solutions for SaaS platforms, complex data systems, and modern search and data discovery platforms. * Kushagra Sahni Associate Director - Product Kushagra is passionate about solving complex problems through simple solutions. He is an engineer at heart who loves transforming ideas into meaningful innovations that balance simplicity and effectiveness. * Ronak Goyal Senior Director - Product Ronak has extensive expertise in building AI/ML and data products and scaling engineering teams at various startups. He was part of the early teams at Cogoport, Jugnoo, and Peak AI. Ronak is an alumnus of IIT-BHU. * Tejprakash Sharma Associate Director - DevOps Tej specializes in Cloud Cost Optimization, helping businesses gain visibility into their cloud spend and maximize savings. With expertise in AWS Cloud and DevOps, he focuses on driving cost-efficient and scalable cloud operations. * Aman Dixit Associate Director - EDP+ Sales Aman comes with an experience of over a decade in the IT/ITeS industry, managing roles across technology sales, presales, and business strategy. Currently managing EDP+ engagements for CloudKeeper, Aman has played a pivotal part in driving the company's exponential growth across global markets. * Anu Priya Lal Senior Manager - Marketing Anu Priya Lal is a seasoned marketing professional with a decade of experience in the technology sector. She has a strong background in demand generation and corporate branding, with an eye to creating targeted campaigns for relevant stakeholders & decision-makers. * Ben Frank Friedman Associate Director - Sales Ben brings over two decades of experience helping organizations optimize technology strategy through FinOps, cost governance, and advisory-led partnerships. He has led successful sales and strategy efforts across AWS, Azure, and SaaS, working to solve real cloud challenges. * Danil David Senior Manager - Sales Danil is a dynamic sales leader who has been driving strategic growth across cloud and IT solutions. Proven expertise in Public Cloud and IT Infrastructure sales, with a strong focus on revenue generation, client engagement, and leading high-performing teams across diverse markets. * Danish Khan Manager - Sales With over a decade of experience in technology and cloud sales consulting, Danish helps organizations adopt AWS with confidence, guiding them through the right service selection to drive significant savings. He is passionate about building strong, growth-oriented customer relationships. * Eugene Clay Associate Director - Sales Eugene brings deep AWS consulting expertise to help organizations design secure, efficient, and cost-effective cloud solutions. He’s passionate about guiding customers on their cloud journey and driving long-term value through smart architecture and cost optimization. * Kumaresh Das Associate Director - Inside Sales Kumaresh is a dynamic leader known for his expertise in market demand analysis, developing effective sales methodologies, and leading high-performing teams. He plays a crucial role in advancing CloudKeeper's sales strategies. * Nikita Khripunov Associate Director - Sales With over a decade of experience in IT sales and business development, Nikita helps businesses to embrace cloud solutions, foster strategic partnerships, and align technology with growth - enabling them to thrive in the ever-evolving cloud landscape. * Nitish Bisht Associate Director - Inside Sales Nitish is a results-driven, enthusiastic sales professional with expertise in technology sales, demand generation, sales strategies, and team management. His contributions have played a significant role in the immense growth of CloudKeeper's sales team. * Puneet Malhotra Senior Manager - GCP Sales Puneet comes with a decade of experience in technology sales, consulting & strategy, primarily driving cloud adoption & FinOps for customers on Google Cloud Platform. * Ross Lian-Thornton Associate Director - Sales With a decade of experience in the tech industry, including Salesforce and as an AWS partner, Ross brings a deep understanding of cloud ecosystems and customer-focused solutions. He plays a key role in strengthening CloudKeeper’s U.S. expansion. * Sahil Jangam Associate Director - Sales Sahil is an experienced sales leader with over a decade of success driving revenue growth and consistently surpassing targets. He builds strong customer relationships, identifies new opportunities, and delivers tailored, high-impact solutions aligned with customer needs. * Saloni Phutela Director - Marketing With experience across high-growth startups and large enterprises, Saloni specializes in developing successful GTM strategies. Her expertise lies in driving 360-degree integrated marketing initiatives aimed at lead generation and elevating brand presence in global markets. * Shyamanta Sharma Associate Director - AWS Sales (ANZ & UK) With a strong track record, Shyam has orchestrated growth strategies across India, ANZ, and America. His passion lies in empowering organizations to thrive in the digital age. Shyam has navigated complex landscapes as a trusted advisor, forging alliances with Fortune 500 companies and startups. * Stephanie Sanchez Manager - AWS Alliance Stephanie leads strategic alignment with AWS and drives high-impact GTM initiatives. Known for building partnerships rooted in trust, she brings a proven ability to accelerate joint growth, pipeline generation, and shared success across the AWS ecosystem. * Suraj Rajagopalan Associate Director - AWS Sales (India) Suraj is a seasoned sales professional with a demonstrated history of working in the IT industry. He is highly skilled in negotiation, market research, business development, and driving digital transformation initiatives that help solve real problems. * Viraesh Salooja Manager - Sales A seasoned, result-oriented professional in consultative tech sales, Viraesh has driven business growth across various industries. With expertise in scaling initiatives from 0 to 1 and 1 to 10, he excels at driving client success and delivering measurable outcomes. We would love to connect with you! Take the next step. This could be the start of something special. More to Explore * Who We Are? Learn more about our milestones and journey so far. * What's in the news? Stay updated with the latest and greatest happenings at CloudKeeper! * Thought Leadership! Read the latest and exclusive content curated by FinOps and cloud professionals. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Here’s what all you get with our Partner-Led AWS Enterprise Support (PLS) Never let pricing be a barrier to accessing AWS Enterprise Support. CloudKeeper offers the same expertise, guidance, and assistance at a fraction of the cost. **Features** Open Cases with AWS Support AWS Service Guidance AWS Account Manager and Solution Architect Billing Support Technical Account Manager (TAM) Architecture Reviews Business Reviews Application Guidance TAM Assisted Case Escalation Infrastructure Event Management 24*7 Technical Support Case Severity / Response Times Training Pricing **AWS Developer Support** System impaired: < 12 hrs Tiered Pricing (>3% of Monthly Bills Avg) **AWS Business Support** Business-critical system down: < 60 mins Tiered Pricing (>10% of Monthly Bills Avg) **AWS Enterprise On Ramp Support** From TAM Pool Max 1 Per Year Max 2 Per Year Max 2 Per Year Max 1 Per Year Business-critical system down: < 30 mins Tiered Pricing (>10% of Monthly Bills Avg) **AWS Enterprise Support** Designated TAM from AWS Unlimited Unlimited Unlimited Unlimited Business-critical system down: < 15 mins 500 Training Credits Per Year Tiered Pricing (> $15,000 Monthly Avg) **CloudKeeper Partner-Led Support** Designated TAM from CloudKeeper (Certified Cloud Expert) Unlimited Unlimited Unlimited Unlimited Business-critical system down: < 15 mins Custom Discounted Pricing **Enjoy the enhanced AWS Enterprise Support at a much lower cost.** There’s more! With our Partner-led Support (PLS) framework, you also get a comprehensive suite of services to streamline your day-to-day cloud management at no extra costs! Here's how CloudKeeper goes above and beyond: * DevOps Support Extensive support for adopting and optimizing DevOps practices and cloud-native technologies. * Cloud Automation Tailored cloud automation solutions that enhance efficiency, reduce manual interventions and minimize errors. * Performance Optimization Continuous monitoring and optimization strategies that ensure your applications deliver peak performance and superior user experiences. * Adoption of New AWS Services Guiding you through the latest AWS innovations ensuring smooth integrations and maximum benefits. * Consulting and Advisory Benefit from tailored consulting and advisory services designed to address your unique requirements and optimize your workload modernization strategies. CloudKeeper brings you comprehensive cloud management services, at a fraction of the costs you would incur with a direct AWS Enterprise Support plan. Not on AWS Enterprise Support? No Problem! Enjoy a full suite of cloud management services with 24*7 support and a designated account manager, all at no cost! Sign up for our Personalized Cloud Support services today and optimize your cloud journey for maximum efficiency. We are on Your one-stop destination for Cloud Cost Optimization * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud. * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure. **Related Resources** * Maximizing AWS Enterprise Support Benefits with a Partner-led Strategy AWS Enterprise Support offers a wide range of support services to organizations, but the pricing could be a barrier. Learn how you can access the same level of cloud support at a fraction of the cost with the AWS Partner-led Support Program. Blog * Why are end-to-end Cloud FinOps Partners leading the way? (Research Backed) Learn about the significance of comprehensive Cloud FinOps solutions and why CloudKeeper stands out as an ideal partner. Streamline cost optimization & maximize efficiency. Blog * 20 Tips and Tricks to Make AWS Work to Your Advantage Tap into the true potential of AWS Services with some cool hacks to save your cloud costs and to manage your cloud infrastructure effectively. Blog Frequently Asked **Questions** * ### Arrow 1.What are the AWS Support Plans? Q1. What are the AWS Support Plans? AWS offers four main support plans: Developer Support, Business Support, Enterprise On-ramp, and Enterprise Support. Each plan is designed to cater to different organizational needs, with increasing levels of support and guidance as you move from Developer to Enterprise Support. * ### Arrow 2. Does AWS provide 24*7 Support? Q2. Does AWS provide 24*7 Support? Yes, 24*7 support is available with the AWS Enterprise Support plan. This includes round-the-clock access to AWS Cloud Support Engineers, enabling critical issue resolution at any time. * ### Arrow 3.What is AWS Enterprise Support? Q3. What is AWS Enterprise Support? AWS Enterprise Support is a premium support plan that offers proactive planning, advisory services, automation tools, 24/7 support and a designated Technical Account Manager (TAM). This level of cloud support is essential for organizations with large infrastructures, complex workloads, and substantial budgets at stake, to ensure seamless, uninterrupted cloud performance. * ### Arrow 4.What are the top features of AWS Enterprise Support? Q4. What are the top features of AWS Enterprise Support? The most important features of AWS Enterprise Support are * 24x7 Technical Support - Round-the-clock access to AWS support engineers with technical assistance for troubleshooting issues or answering service-related questions. * Technical Account Manager (TAM) - Personalized support with a designated Technical Account Manager (TAM) who acts as a bridge between you and AWS, ensuring you get to leverage the AWS support services to the maximum. * Case Severity / Response Times - Some of the fastest SLAs and response times in the industry, including a 15 minute response time for critical issues. * Expert Guidance - Proactive guidance and recommendations by certified cloud experts on maximizing AWS services, architectural improvements, cloud cost optimization and more. * Third-party Application Guidance - Assistance with specific application workloads, fine-tuning them to run efficiently on the cloud. * ### Arrow 5. How much does AWS Enterprise Support cost? Q5. How much does AWS Enterprise Support cost? AWS Enterprise Support follows a tiered pricing model, with charges based on a percentage of your monthly AWS usage: * 10% of the first $150,000 in monthly AWS charges * 7% of monthly charges between $150,000 and $500,000 * 5% of monthly charges between $500,000 and $1 million * 3% of monthly charges over $1 million If these thresholds aren’t met, there’s a minimum monthly fee of $15,000, regardless of usage. * ### Arrow 6.What factors influence AWS Enterprise Support pricing? Q6. What factors influence AWS Enterprise Support pricing? AWS Enterprise Support pricing depends on several factors: * **AWS Usage:** Support fees increase with higher AWS usage based on a tiered percentage model. * **Contract Terms:** Custom support agreements or long-term commitments like AWS Enterprise Discount Programs (EDPs) may influence costs. * **Regional Variations:** AWS usage costs vary by region, impacting support costs accordingly. * **Additional Services:** Specialized services like migration assistance or managed services may come at additional costs based on the service complexity. Learn more about AWS Enterprise Support pricing with * ### Arrow 7.What is AWS Partner-led Support? Q7. What is AWS Partner-led Support? AWS Partner-led Support is an option where certified AWS partners, like CloudKeeper, provide AWS Enterprise Support-level services at a reduced cost. This support plan allows businesses to work with certified AWS Solution Provider partners, receiving extensive support and additional benefits without the higher cost of AWS direct support. * ### Arrow 8.What is AWS Partner-led Support pricing? Q8. What is AWS Partner-led Support pricing? AWS Partner-led Support offers custom discount pricing which varies according to the business needs and cloud setup. With CloudKeeper, for example, customers have saved up to 40% on their monthly cloud costs while retaining the full features of AWS Enterprise Support. * ### Arrow 9.What features are available with AWS Partner-led Support? Q9. What features are available with AWS Partner-led Support? AWS Partner-led Support includes nearly all features of AWS Enterprise Support, such as: * 24*7 technical support via email, chat, and phone * Proactive architectural and operational guidance * Fast response times for critical issues However, some add-on features like Training Credits and Incident Detection and Response are typically excluded. With CloudKeeper, you get a range of additional benefits at no cost, including: * Support for DevOps & Cloud-native Technologies * Assistance with adopting new AWS services * Workload Modernization support * Cloud Automation solutions * Cloud Cost Optimization insights * Performance Optimization techniques * Consulting and Advisory Services for cloud innovation * ### Arrow 10.Will Partner-led Support affect my relationship with AWS? Q10. Will Partner-led Support affect my relationship with AWS? No, Partner-led Support won’t impact your AWS relationship. Certified AWS Solution Provider partners who meet the AWS standards are allowed to offer Partner-led Support. These partners become your primary contact for support, while you continue to receive the full benefits of AWS services. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close #### CloudKeeper Platform Suite # From Visibility to ROI : All-in-One FinOps Suite for Guaranteed Results * $120M+ Total savings delivered * 400+ Happy customers * 100% G2 Satisfaction Score ## The Platform suite that pays for itself! The CloudKeeper platform suite goes far beyond providing tools. It’s a powerful blend of best-in-class automated FinOps platforms that provide visibility while optimizing your cloud costs and architecture, along with unlimited 24x7 support & expert services. CloudKeeper Lens ## Visibility & Governance CloudKeeper Tuner ## Usage Optimization CloudKeeper Commit ## Rate Optimization ## CloudKeeper Lens Real‑time cost analytics, hourly trends, budgets, tagging, and anomaly detection - secure access to resource‑level details. ## CloudKeeper Tuner Automated optimization across 20+ most used services, fully covering AWS Trusted Advisor recommendations & beyond: right‑sizing, auto‑spotting, off‑hours scheduling, and unused resource cleanup. ## CloudKeeper Commit Zero‑touch, AI-driven Reserved Instanced/Savings Plan management with automated buying/selling. With our Platform Suite, you also gain access to a set of **powerful value-adds for** **end-to-end smarter cloud management.** * Architecture Reviews CloudKeeper Check Unlimited Personalized Architecture Reviews with remediation plans delivered by certified experts. * Unlimited 24x7 Services CloudKeeper Expert Access to certified architects, FinOps practitioners, and pre-committed consulting hours included. * AI Assistant for FinOps CloudKeeper Gen AI Interactive AI agents that answer spend questions, suggest optimizations, and provide real-time guidance. ### Flexible Deployment Options Choose between **SaaS or Private deployment to match your infrastructure** preferences and security requirements. * #### SaaS - The products are hosted in CloudKeeper’s infrastructure, available to users over the internet. * #### Private Cloud - The products are hosted in the customers’ own cloud, available to users over the corporate intranet. CloudKeeper provides expert managed services for set-up, support, and performing ongoing upgrades of products in customers’ cloud. The CloudKeeper’s 3-phase proven path to Sustainable Cloud Optimization Your **Always-On Engine** for everything you need to control your cloud * **Lens + Check** **Spot immediate cost savings and architecture gaps with real-time visibility and expert reviews.** **01** **** **** **** * **Tuner + Commit** **Automatically optimize workloads, right-size resources, and maximize Reserved Instance/Savings Plan efficiency.** **02** **** **** **** * **GenAI + Expert** **Maintain continuous savings, enforce policies, and get 24x7 expert guidance for long-term efficiency.** **03** **** **** **** * ## The CloudKeeper Advantage * Guaranteed outcomes backed by expertise * Zero lock-ins * Results-based pricing model * Automation + AI + 24x7 certified support * Fast, Sustained Impact in 30–90 days * 20% Average Savings ## Why choose CloudKeeper as your Cloud Optimization Partner? * 15+ Years of AWS expertise * 150+ certified cloud professionals * 4.7 out of 5 stars on G2 Discover how CloudKeeper drives success for businesses across all industries. ‹› **Pioneering end-to-end cloud management** **Ranked #1** in User Satisfaction based on 100% genuine customer reviews for Cloud Management * CloudKeeper is a game-changer for cloud cost management. It is **essential for controlling cloud spend** and making the most out of the infrastructure. It’s become a **vital part of our cost management toolkit**. Aakash Sharma Lead CloudOps at Seclore * We have been using CloudKeeper for quite some time and are happy to say that **we no longer worry much about our AWS costs because CloudKeeper handles it for us**. Their support team is very responsive, and the platform is very user-friendly. Overall, **we are very satisfied with CloudKeeper!** Nikhil. DevOps - Technical Lead, Glider.ai * CloudKeeper Tuner not only **saved us thousands by removing unused resources but also helped modernize our architecture for better performance**. Our engineers now get live, in-console savings opportunities—like having an **always-on assistant built for scale and speed**. Pratish Arora. Principal DevOps Engineer, NetRoadshow * I would consider it as a **One-stop solution** for my cloud spending/ reservations/ saving recommendations and optimisation efforts. Their Tuner **tool has been a great addition** to our account, helping us with real-time saving opportunities. Sunny Chhatija. Engineering Manager * The **platform delivers comprehensive visibility** into our cloud usage patterns and identifies actionable savings opportunities that would be **nearly impossible to detect through native AWS CloudWatch** monitoring alone. Mahesh V. CTO * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 17 Jun, 2025 | 3 Min read # CloudKeeper Achieves $200M Revenue with 50% Year-over-Year Growth, Eyes 3x Surge by 2027 CloudKeeper, a leading cloud cost optimization and FinOps company, today announced that they have exited the last fiscal year with an annualized revenue of $200 million and EBITDA of $20 million, marking a 50% year-on-year growth. With this milestone, the company has cemented its position as one of the fastest-growing players in the global cloud ecosystem. The company's rapid growth is fueled by strong customer acquisition and strategic expansion into international markets, particularly North America. CloudKeeper onboarded 101 new customers worldwide in the past year, with 26 added in the final quarter alone. Its client portfolio includes prominent names like eLocal, HackerEarth, Recruit CRM, Appsmith, Moneysmart, and Interglobe Aviation. To accelerate its North American presence, the company has established a local office and made key leadership appointments. Seasoned industry expert Ryan Freilino has been hired as the Chief Revenue Officer (CRO) for the region, and Chief Growth & Marketing Officer (CGMO) Naman Jain has relocated to spearhead market strategy. They are backed by a growing team of local cloud professionals dedicated to accelerating user acquisition and ensuring seamless customer assistance. Building on this strong momentum, CloudKeeper has set an ambitious goal to triple its revenue by the end of 2027. To power this next phase of growth, the company plans to double its global workforce from 250 to 500 employees by next year. It is actively hiring for strategic leadership positions, including a Chief Revenue Officer (CRO) for India and a global Chief Product & Technology Officer (CPTO), while scaling its Sales, DevOps, and Engineering teams. “Our vision is to become the go-to partner for businesses navigating multi-cloud complexity, driving cloud cost efficiency at scale,” said Deepak Mittal, CEO and Founder of CloudKeeper. “As the cloud cost optimization space continues to evolve, we aim to be among the top three global players, setting new benchmarks in cost intelligence and operational excellence for our customers.” CloudKeeper’s success is also driven by relentless product innovation. The company has evolved from a single AWS savings solution to a comprehensive portfolio of platforms and services. Its most recent offering, Its broader suite of offerings includes FinOps and DevOps consulting, well-architected reviews, migration support, and 24x7 personalized cloud support. The company has also successfully expanded its services to Google Cloud, onboarding over 20 GCP customers within the first six months. Exploring the use of Gen AI in cloud optimization, CloudKeeper has established a dedicated AI Center of Excellence. The company is further investing in Kubernetes and container management innovations to drive the next wave of cloud cost and performance optimization. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 28 Jun, 2023 | 3 Min read # CloudKeeper achieves first spot in G2 Summer 2023 Grid® Report; recognized as a leader for the third time in the cloud cost management category CloudKeeper, a leading AWS FinOps and cost optimization solution, has been ranked **#1** among the cloud cost management solutions, worldwide. For the third consecutive time, **CloudKeeper has been recognized as the leader in the G2 Summer 2023 Grid® Report** , solidifying its position as the industry's preferred choice for cloud cost management. CloudKeeper is also ranked #1 in the “Easiest To Use” category in cloud cost management software. In addition, CloudKeeper has also earned several badges that include Leader Enterprise, Most Implementable, High Performer, Best Usability, Easiest To Do Business With and Best Relationship, showcasing CloudKeeper's comprehensive suite of features and the ability to cater to diverse business needs. Deepak Mittal, CEO - CloudKeeper, said - "We are humbled to maintain our top position in the G2 Report. This consecutive recognition reflects our customer-centric approach. We are deeply grateful to our customers for their continued support and confidence in CloudKeeper. The positive feedback and appreciation we receive from our customers inspire us to continue growing and remain the preferred choice in the FinOps space.” He further added, “We are incredibly proud of our team at CloudKeeper, whose hard work and dedication have been remarkable." "Cloudkeeper saw another impressive quarter of results, both in becoming the #1 ranked provider of Cloud Cost Management software and being named a G2 Leader overall and for the Enterprise and Mid-Market. We also saw Cloudkeeper really differentiating themselves against their competitors for Quality of Support, Meeting Requirements, Ease of Use, and Product Moving In The Right Direction, where they saw top marks in their category.", says **Chris Perrine, Vice President & Managing Director - G2 Asia Pacific.** CloudKeeper has always been driven by customer satisfaction and ensures maximum benefits on cloud investments for their customers. In line with this commitment, CloudKeeper has recently enhanced and expanded its offerings that can address a wide range of FinOps challenges as well as meet the unique needs of different customer segments. With a growing base of 300+ customers, already benefiting from instant and guaranteed savings, they can now leverage CloudKeeper Auto for AI-based RI management and CloudKeeper EDP+ for maximized ROI on AWS EDP. CloudKeeper has been rated 4 stars or more by 98% of users, with 92% expressing their willingness to strongly recommend CloudKeeper. The solution also garnered users’ love and is named a leader in the mid-market and enterprise space. CloudKeeper's consistently high performance demonstrates its unwavering dedication to customer success and the value it brings to the FinOps landscape, worldwide. **About G2** G2 serves as the most trusted platform for businesses to review and evaluate software and service providers. Products in the leader’s quadrant earn this esteemed recognition due to their exceptional ratings, impressive customer satisfaction levels, and substantial market presence. **About CloudKeeper** CloudKeeper is a comprehensive AWS Cost Optimization and FinOps solution that offers instant & guaranteed savings of up to 25% on your entire AWS bill at no lock-in or commitment, no efforts, no cost, and no access. As an AWS Premier Consulting Partner and Member of FinOps Foundation, CloudKeeper helps 300+ businesses with cloud cost optimization and has successfully helped save more than $100 million+ in AWS billings. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 17 Oct, 2023 | 2 Min read # CloudKeeper achieves rank #1 in G2 Fall 2023 Grid® Report for Cloud Cost Management CloudKeeper, a cloud FinOps and cloud cost optimization solution, has been ranked #1 in the Cloud Cost Management category in the G2 Fall 2023 Grid® Report. The accomplishment marks CloudKeeper's fourth consecutive recognition as a leader and second consecutive top ranking in the cloud cost management category. This remarkable feat, along with its recognition as a Leader in the Enterprise, Mid-Market, and Small Business segment, validates the impact of CloudKeeper's CloudKeeper has also garnered a host of prestigious badges in the G2 Fall 2023 Grid® Report. These accolades encompass recognition as a leader in Cloud Cost Management for India and the Asia Pacific, leadership status in Mid-Market Cloud Cost Management and Cloud Management Platforms, the highly coveted 'Best Usability' badge, acknowledgment for 'Best Relationship in Mid-Market,' and the distinction of being a 'High Performer' in Asia Pacific Cloud Management Platforms. These badges collectively underscore CloudKeeper's versatility, user-friendliness, and unwavering dedication to lowering cloud costs for its clients. **Deepak Mittal, CEO - CloudKeeper,** said, “We are elated to be recognized once again as the leader in cloud cost management by G2 in their Fall 2023 Grid® Report. This achievement is a testament to our team's dedication to delivering excellence and driving value for our customers. We remain committed to innovation, helping businesses optimize their cloud costs and enabling them to focus on their core business operations.” “CloudKeeper had another tremendous quarter, and they are performing incredibly well in both our Cloud Cost Management and Cloud Management categories,” said **Chris Perrine, Vice President and Managing Director, APAC at G2.** “Seeing them be recognized and rated so highly across the metrics we measure, like Best Usability, Best Results, and Best Relationship shows the value they are delivering to their customers. CloudKeeper also ranked #1 for 16 different attributes G2 measures in the categories they are listed in”. **About G2** G2 serves as the trusted platform for businesses to review and evaluate software and service providers. Products in the leader’s quadrant earn this esteemed recognition due to their exceptional ratings, impressive customer satisfaction levels, and substantial market presence. The G2 Fall 2023 Grid® Report is a prestigious industry benchmark that evaluates and ranks software solutions based on genuine user reviews, product capabilities, and market presence. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 17 Jan, 2024 | 2 Min read # CloudKeeper awarded the AWS APN Certification Distinction for achieving 100 AWS Certifications CloudKeeper, a leading provider of cloud cost optimization solutions, announced today that it has collectively achieved 100 Amazon Web Services (AWS) Certifications and has been awarded the This distinction recognizes AWS Partners that have achieved 50 or more AWS Certifications within their organization, providing them the opportunity to showcase their customer obsession through AWS Certification achievement, and highlight the value that AWS Certifications brings to their customers. “We are proud to achieve this significant milestone and earn the AWS APN Certification Distinction,” said **Deepak Mittal, CEO at CloudKeeper**. “This recognition is a testament to our team’s dedication to continuous learning and growth, and our commitment to providing our customers with the highest level of expertise and support with AWS experts to assist our customers migrating to, and optimizing their use of, AWS.” AWS Certification validates cloud expertise to help professionals highlight in-demand skills and organizations build effective, innovative teams for cloud initiatives using AWS. CloudKeeper’s team of AWS Certified professionals have the skills and knowledge to help customers with a wide range of services, including Amazon Elastic Compute Cloud (Amazon EC2), Amazon Simple Storage Service (Amazon S3), and Amazon Relational Database Service (Amazon RDS), a collection of managed services that makes it simple to set up, operate, and scale databases in the cloud. “We are grateful for our relationship with AWS and for the support they have provided us on our journey to achieving this milestone,” said Deepak. “We look forward to continuing to work with AWS. Together, we will provide a complete cloud services and cloud management portfolio that will give customers fast, flexible access to the cloud.” Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 08 Aug, 2024 | 2 Min read # CloudKeeper acquires WiseOps to strengthen its position as a leading Full-Service Cloud Cost Optimisation Partner CloudKeeper, a leading cloud cost optimization partner, is excited to welcome WiseOps, a cutting-edge platform specializing in AWS cost and usage optimization, into its family. This integration marks a significant step forward for CloudKeeper, enhancing its commitment to delivering superior cloud optimization solutions. CloudKeeper has established itself as a comprehensive partner for cloud cost optimization, offering guaranteed cost savings, unlimited expert consulting, and a robust analytics platform. With a proven track record of helping over 350 global businesses save an average of 20% on their cloud bills, CloudKeeper excels in maximizing value across AWS, Microsoft Azure, and Google Cloud. WiseOps has distinguished itself in AWS cost optimization with its engineering-centric approach. Its suite of intelligent tools seamlessly integrates into the flow of work, offering actionable, one-click implementations of cost-saving measures across AWS services. WiseOps stands out for its AI-driven recommendations, and automated optimizations, enabling teams to continuously reduce cloud spend without compromising performance or workflow efficiency. "WiseOps was the missing piece of the puzzle," said **Deepak Mittal, Founder and CEO of CloudKeeper**. "By joining forces with them, CloudKeeper has become a truly comprehensive cloud cost optimization solution. It will enable us to cater to a broader range of clients, address more complex use cases, and help businesses optimize and engineer their cloud environments more effectively.” **Praneet Chandra, CEO & Co-founder of WiseOps**, commented: “Our commitment to using cloud cost optimization as a pathway to sustainable cloud usage aligns perfectly with CloudKeeper's vision. We are thrilled to collaborate with a leader in the field to advance our shared goals and deliver impactful results for our clients.” **Ronak Goyal, CTO and Co-founder of WiseOps** , also shared his excitement: “This represents a significant opportunity for both WiseOps and CloudKeeper to drive innovation and deliver exceptional value. We look forward to integrating our technologies and expertise to offer even more powerful solutions for cloud cost optimization.” WiseOps' solutions will now be integrated into CloudKeeper's extensive suite of offerings, enhancing CloudKeeper’s overall portfolio. This powerful combination is set to transform the cloud cost optimization landscape, empowering businesses to fully realize their potential in the cloud. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 20 May, 2021 | 2 Min read # CloudKeeper, an AWS FinOps solution, aims to onboard 150 new customers in 2021 in the US CloudKeeper, a FinOps solution by TO THE NEW - an AWS Premier Consulting partner, targets to onboard 150 customers in the USA. CloudKeeper helps companies with a guaranteed saving of anywhere between 5% to 15% on monthly AWS bills with immediate effect, with no pre-payments or volume commitments, and without root, PEM files, or password access. Moreover, customers get free access to an AWS Cloud analytics & optimization platform for resource monitoring and management. CloudKeeper currently helps more than 200 companies across the globe with guaranteed cost savings and cloud cost management. Some of the marquee customers of Cloudkeeper in the US include CellTrak, AllyO, FEN Learning, Mediafly, IMPLAN, and many other Enterprises, ISVs, and consumer tech companies. According to **Deepak Mittal, CEO & Co-Founder, TO THE NEW Pvt. Ltd**, "We have seen an increasing demand for CloudKeeper, our AWS Cloud FinOps solutions. CloudKeeper has been successfully helping many organizations by enhancing their operational efficiency, controlling their growing cloud costs, and allowing them to make smart business decisions by making use of valuable data insights. We are seeing very high interest from our existing and potential customers as no other solution currently offers guaranteed savings on the entire AWS bill with immediate effect and without any cost or lock-in." CloudKeeper has been helping customers navigate the complexities of the cloud by offering them transparency, visibility, and cost-savings all bundled in one unique offering while keeping the AWS account security safely in customer's hands. ### About TO THE NEW TO THE NEW is a technology services company that designs, builds & runs digital products and platforms for enterprises, SaaS, and consumer tech companies. It has been recognized by global analyst firms like Gartner, Everest, ISG, and Zinnov for its capabilities in Digital Engineering, Cloud, Data & Analytics. See the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 04 Oct, 2023 | 2 Min read # CloudKeeper Becomes a Premier Member of the FinOps Foundation CloudKeeper, a leading FinOps & cost optimization solution, has become a Premier Member of the FinOps Foundation. The FinOps Foundation is the global community for those who manage the value of the cloud, promoting collaboration, knowledge sharing, and best practices among professionals in this burgeoning field. As a Premier Member, CloudKeeper will provide support and resources to the FinOps community, and promote the adoption of FinOps best practices. CloudKeeper has solidified its dedication to fostering responsible and efficient cloud spending practices across the globe. Concurrently, **Deepak Mittal, CEO of** **Deepak Mittal** expressed his enthusiasm for this collaboration, stating, "Becoming a Premier Member of the FinOps Foundation and joining its Governing Board is a significant milestone for CloudKeeper. We are delighted to deepen our involvement with the FinOps community and contribute to the evolution of Cloud FinOps practices. This aligns perfectly with our mission to empower organizations with cost-effective cloud cost management & optimization solutions & services." "We are pleased to welcome CloudKeeper as a Premier Member, and we look forward to leveraging their expertise in cloud cost optimization to enhance the community's best practice. Deepak’s presence on our Governing Board will undoubtedly bring valuable insights to our strategic initiatives,” said **J.R. Storment, Executive Director of the FinOps Foundation**. CloudKeeper's commitment to optimizing cloud costs and helping organizations manage their cloud expenses aligns seamlessly with the FinOps Foundation's mission to help advance individuals from organizations of all sizes to best manage the value of their cloud spend. As a Premier Member and Deepak’s participation on the Governing Board, CloudKeeper and the FinOps Foundation are poised to continue driving innovation and best practices in FinOps. For more information about CloudKeeper and its cloud cost optimization solutions, please visit Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 19 Mar, 2024 | 2 Min read # CloudKeeper completes audit for AWS MSP Program with 100% compliance score CloudKeeper, a leading provider of cloud cost optimization and FinOps solutions, is pleased to announce the **successful retention of its Amazon Web Services (AWS) Managed Service Provider (MSP) designation for the fourth consecutive year.** We have successfully completed an extensive independent audit to ensure that our business health and technical capabilities meet a high standard, and were able to achieve a 100% compliance score. This achievement builds confidence among AWS customers seeking qualified MSP Partners, offering them an independent assessment of our capacity to drive continuous innovation, support AWS adoption, ensure security, embrace DevOps, and excel in customer management. This assessment included discussions and a review of selected processes, procedures, and records. The audit specifically mentioned a number of our strengths, including: * AWS Premier Tier Consulting Partner with AWS Migration Consulting and AWS DevOps Consulting competencies. * Good practice around optimizing workload placement to increase energy efficiency. * Implementation of security best practices adhering to the AWS Guardrails. * Provision of comprehensive cost optimization reporting to customers. **Narinder Kumar, COO and Co-Founder, TO THE NEW and CloudKeeper,** expressed, "We are proud to maintain and continue our membership in the AWS MSP Program. The assessment was extensive, but our Newers demonstrated and built upon best practices. Passing the audit process is a validation of the continued evolution of our Managed Services and Cloud capabilities that have been delivering value to customers across the globe for over 15 years. We are enthusiastic about continuing to help them achieve their cloud transformation goals by leveraging the passion for innovation and breadth of services that AWS and CloudKeeper bring to each customer’s cloud journey." As an AWS MSP Partner, we provide customers with full lifecycle solutions in cloud infrastructure and application migration. Read Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 05 Mar, 2025 | 2 Min read # CloudKeeper Earns 2025 Great Place To Work Certification™ New Delhi, India — CloudKeeper is proud to be Certified™ by Great Place To Work®. This marks their first certification as an independent company after spinning off from TO THE NEW, a 9-time consecutive Great Place To Work® Certified™company. This recognition is based entirely on what current employees say about their experience working at CloudKeeper. Great Place To Work® is the global authority on workplace culture, employee experience, and the leadership behaviors that drive revenue growth, employee retention, and innovation. Learn more at _“Being recognized as a Great Place To Work® is a moment of pride for all of us at CloudKeeper. I’m incredibly proud of every CKer who has contributed to creating a workplace rooted in trust, transparency, and collaboration”,_ said Deepak Mittal, Founder & CEO - CloudKeeper. _“At CloudKeeper, we are dedicated to creating an environment where every CKer thrives, feels valued, and is empowered to make a meaningful impact. We believe that when our team feels valued, extraordinary things happen.”_ ## **Investing in Employee Growth and Development** CloudKeeper is dedicated to nurturing talent and fostering continuous learning. Recently, the company onboarded 50+ new graduates through its Freshers’ Boot Camp - a comprehensive program designed to equip them with the knowledge, skills, and confidence needed to excel in the industry. This immersive initiative ensures a seamless transition from academia to the real-world with hands-on experience, setting freshers up for long-term success. Throughout the program, freshers engage in hands-on technical training, collaborative projects, and team-building activities. Guided by experienced mentors, they gain exposure to industry-leading technologies and best practices. CloudKeeper regularly organizes knowledge sessions to enhance both technical and soft skills, while also sponsoring industry certifications to help employees stay ahead of evolving industry trends. Beyond skill development, CloudKeeper places a strong emphasis on recognizing and celebrating individual contributions, creating an environment where employees feel valued and motivated. This commitment to growth, learning, and recognition makes CloudKeeper an exciting and rewarding place to build a career. According to ## **WE ARE HIRING!** Looking to grow your career at a company that puts its people first? Visit our careers page at: Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 08 Jul, 2025 | 4 Min read # CloudKeeper Expands to North America, Strengthens Leadership, Accelerating Global Momentum **New York, USA, 8th June 2025** - CloudKeeper, a leading provider of comprehensive cloud cost optimization solutions and services, has announced its strategic expansion into North America. The move signals the company’s commitment to deepening customer engagement and delivering tailored FinOps and cloud cost optimization solutions to businesses in the region. This expansion follows a year of exceptional growth for CloudKeeper, which closed the previous fiscal year with $200 million in annualized revenue and $20 million in EBITDA, reflecting a 50% year-over-year increase. The company added 101 new customers globally, with momentum continuing to build across industry verticals. To accelerate its North American expansion, CloudKeeper has strengthened its leadership team with key appointments.**Kenneth Ziegler** , current CEO of Leapwork and former CEO of Logicworks, has joined as Senior Advisor and Board Member. With decades of experience in scaling cloud and managed service businesses, Ken will work closely with the leadership team to guide strategic initiatives and support CloudKeeper’s growth in the region. Joining him is **Ryan Freilino** , a seasoned industry veteran, who has been appointed as Chief Revenue Officer for North America. Ryan will lead regional revenue growth and retention strategies across the U.S. market, and will be driving alliances & partnerships with hyperscalers. In addition, CloudKeeper has onboarded several experienced cloud, DevOps, and sales professionals to enhance regional outreach and strengthen customer engagement. Supporting these developments, **Naman Jain** , CloudKeeper’s Chief Growth & Marketing Officer, has recently relocated to the United States as part of the company’s strategic efforts to expand its footprint in the region. With this, Naman will focus on strengthening CloudKeeper’s brand presence across the U.S. and will lead the development and execution of the go-to-market strategy tailored to the region’s unique dynamics. His relocation underscores CloudKeeper’s commitment to building a stronger local presence, fostering closer relationships with customers and partners, and accelerating growth in one of its most critical markets. The company has also realigned its internal sales leadership to focus on the unique dynamics of the U.S. cloud ecosystem, ensuring its offerings are deeply aligned with local customer needs and regulatory requirements. CloudKeeper already serves over 150 customers in North America, representing nearly 35% of its global customer base and 42% of worldwide revenue share, across industries such as technology, retail, healthcare, and financial services. The region has emerged as one of CloudKeeper’s fastest-growing markets, with an 80% year-over-year increase in revenue, underscoring the company’s rising momentum and relevance in the market. _“Expanding into the U.S. has always been a key objective for us, and we believe the timing is just right. With the global expertise we've built over the years, we’re now well-equipped to bring our solutions closer to a market that’s leading the charge in cloud innovation,”_ said **Deepak Mittal, CEO and Founder, CloudKeeper**. _“Having a local presence will allow us to better understand regional challenges, work more closely with our customers, and tailor our offerings to their needs. It’s exciting to be here - right in the middle of some of the most revolutionary businesses in the world.”_ **Ryan Freilino, Chief Revenue Officer, North America** , added: _“Having worked in the U.S. cloud space for years, I see CloudKeeper as the missing piece in the cloud optimization puzzle many businesses deal with. I’m excited to help these companies adopt smarter, sustainable cloud practices and bring innovation and efficiency together in a way that truly scales.”_ Sharing his perspective, **Naman Jain** , **Chief Growth & Marketing Officer**, said: _“We’ve already seen strong success in the U.S. market, working with a wide range of businesses across industries. Being on the ground now helps us to better understand local needs, offer more customized solutions, and build deeper relationships with the customers and the hyperscalers. It’s an exciting step toward unlocking new opportunities and delivering even greater value in the region.”_ CloudKeeper has grown into a comprehensive suite of cloud cost optimization solutions, including FinOps and DevOps consulting to automated optimization tools, well-architected reviews, cloud migration support, and The company has also extended its services to Google Cloud, onboarding over 20 GCP customers within six months. As North American businesses rapidly adopt AI, scale digital infrastructure, and embrace multi- and hybrid-cloud strategies, CloudKeeper aims to be the trusted partner helping them achieve greater efficiency, performance, and savings in the cloud. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 04 May, 2023 | 3 Min read # CloudKeeper continues to be a leader in Spring 2023 G2 Grid® Reports in the Cloud Cost Management Category CloudKeeper, an AWS premier partner and a comprehensive FinOps solution has once again been recognized as the leader in G2 Spring 2023 Grid® Report. It is the second consecutive recognition and CloudKeeper stands strong in the third position as the best cloud cost management solution worldwide. The first and second position is held by AWS Cloudwatch and IBM Turbonomic respectively. Furthermore, CloudKeeper also earned a leader’s spot in the cloud management platforms’ grid. We are proud to have received multiple badges including Best Support, Easiest to Use, Easiest To Do Business With, Best Usability, Easiest Admin, and Easiest Setup. Furthermore, we have earned a spot in the top 3 rankings for multiple categories like - User Satisfaction, Compliance, Ease of Use, Spend Forecasting and Optimizations, and Market Presence. Cloud cost management has become a critical priority for businesses seeking to enhance profitability, efficiency, and sustainability. With more than a decade of experience in the cloud, CloudKeeper possesses an in-depth understanding of the FinOps ecosystem, enabling us to provide targeted solutions that effectively address each FinOps challenge and scale cloud cost optimization efforts for organizations. This achievement underscores the hard work and dedication of the CloudKeeper team and reinforces our commitment to providing customers with unparalleled cloud cost management solutions. Subsequently, CloudKeeper has been rated 4 stars or more by 98% of users, with 91% expressing their willingness to strongly recommend CloudKeeper. The solution also garnered users’ love across mid-market and small business space, showcasing its unwavering commitment to providing a seamless FinOps experience to a wide range of businesses. CloudKeeper expressed heartfelt gratitude to all its valuable customers for trusting them as their growth partners in the journey of cloud cost management. **Deepak Mittal, CEO - CloudKeeper** , says, ”Our customers are at the heart of everything we do at CloudKeeper. We have been on a mission to simplify cloud cost management, and this consecutive recognition as a leader in G2 Spring 2023 reports validates that we are on the right path. We thank our valuable customers for trusting us as their growth partners in the journey of cloud cost management.” He further added, “As we eye an exciting year of growth & advancement, CloudKeeper is committed to being one of the most trusted partners for everything FinOps and help customers achieve instant & guaranteed savings on their cloud bills.” “CloudKeeper achieved outstanding results in G2's Spring 2023 reports, being named a Leader in both our Cloud Cost Management and Cloud Management Platforms categories. Remarkably, CloudKeeper ranked either #1 or #2 for 22 key attributes we measure in these categories. They also demonstrated exceptional performance in the Mid-Market segment, garnering accolades for Easiest Admin, Easiest Set-Up, Best Usability, and Easiest To Do Business With”, says **Chris Perrine, Vice President & Managing Director - G2 Asia Pacific**. G2 is a widely recognized platform for unbiased ratings and reviews of various software products and platforms. Rankings on G2 reports heavily rely on verified and authentic reviews provided by real software buyers, making it the most trustworthy source for potential buyers researching and selecting software solutions. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 16 May, 2025 | 3 Min read # CloudKeeper Launches 30-Day Challenge to Help Businesses Slash AWS Costs New York (USA), May 16, 2025 - This is a challenge to every AWS team confident that they've already done enough cost optimization. After analyzing over 2,000 AWS accounts, CloudKeeper found that 97% of teams were still missing critical savings opportunities, some as high as six figures. Even the most meticulous teams left an average of 23% in savings on the table. Through this 30-day, expert-guided journey, CloudKeeper invites AWS users to take the Cloud Fitness Test and prove just how lean, efficient, and cost-smart their cloud can be. Participating organizations undergo a comprehensive evaluation of their AWS environments, culminating in a tailored action plan designed to optimize resource utilization, minimize unnecessary expenditures, and boost overall performance. Central to this initiative is CloudKeeper Tuner, an industry-first AWS usage optimization platform recently launched by CloudKeeper. This innovative solution underpins the challenge by delivering automated scans, detailed usage analytics, and actionable recommendations across over 50 AWS services. _“We’ve worked with 400+ businesses in the past 15 years, and a majority of them had almost a quarter of their cloud savings untouched. Sometimes, even the best of the teams need a fresh pair of eyes to uncover what’s missing, and this challenge is our way of helping them, while keeping it fun and engaging,_ ” said **CloudKeeper’s CEO** **Deepak Mittal**. _"Think your AWS setup is fully optimized? There’s one way to find out - take up the challenge._ ” Inspired by intensive fitness programs, the Cloud Fitness Challenge enables daily usage and savings recommendations, dynamic instance management, automated scheduling, and expert support, helping teams build everyday cloud discipline. The Challenge follows a structured three-step journey, beginning with secure AWS account integration using read-only IAM roles to ensure complete data privacy. Participants then receive a personalized Cloud Fitness Score, generated through automated scans that reveal usage patterns, inefficiencies, and untapped savings opportunities. With these insights, teams apply tailored optimization strategies guided by CloudKeeper’s experts, turning recommendations into measurable cost reductions and performance gains. CloudKeeper emphasizes that this challenge isn’t about questioning capabilities, but about pushing the boundaries of what’s possible in cloud optimization. The program incentivizes progress through milestone-based rewards, recognizing achievements in resource optimization and savings realization while maintaining a gamified, engaging experience throughout the 30-day journey. The challenge is open to all organizations operating active AWS environments. CloudKeeper has emphasized that no application data or customer information will be accessed throughout the assessment process, ensuring full data privacy and compliance. To sign up for the Cloud Fitness Challenge, visit - Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 18 May, 2023 | 3 Min read # CloudKeeper launches CloudKeeper Auto, an AI-powered RI Management Platform CloudKeeper, a global leader in AWS FinOps and Cost Optimization space, has announced the launch of Businesses can save significant costs on AWS through its offerings like Reserved Instances (RIs) and Saving Plans that require a 1-year or 3-year commitment. But, it is often difficult for businesses to predict their usage and make such long-term or large-volume commitments. Striking a balance between the cost of obtaining new resources and maintaining operational flexibility, while minimizing cloud waste, has always been a challenging trade-off. CloudKeeper Auto helps tackle this challenge by combining the flexibility of On Demand instances and the cost-effectiveness of Reserved Instances. Using CloudKeeper Auto, organizations can buy AWS compute instances on-demand, at 3-Year Reserved Instance pricing, which is the highest discount tier for reservations. Notably, the solution does not require any type of volume or term commitment from the user. The proprietary AI engine automatically buys/sells RIs on behalf of the organization, with just a simple IAM access to their AWS account. CloudKeeper charges only 18% of the total EC2 savings as a platform fee, which is one of the most competitive fees in the market. CloudKeeper Auto completely takes away all manual dependencies on RI management and delivers substantial savings with - * Automated buying/selling of RIs on the secondary marketplace * Guaranteed buyback of RI reservations made through the platform * Risk-free coverage with no commitments and no billing transfer The company also offers However, not all AWS users could benefit from CloudKeeper AZ due to concerns with billing transfer, their own contractual obligations towards programs like AWS EDP, and more. CloudKeeper Auto, however, resolves these concerns with no requirements for billing transfer or commitment, and a zero-touch, AI-driven RI management system. With two distinct solutions tailored to meet various objectives of cloud cost optimization, CloudKeeper has now carved a niche for itself as a unique FinOps Solution Provider. “At CloudKeeper, we have always been committed to solving cloud cost challenges. Our new solution is a direct response to the market feedback from those who could not leverage the potential of CloudKeeper AZ, due to multiple reasons. We hope to expand our reach to a broader set of AWS consumers, with a stronger arsenal of features,” said Deepak Mittal, CEO, CloudKeeper. “CloudKeeper Auto is capable of delivering superior and sustainable cost savings to all kinds of businesses across the world, completely risk-free!” Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 29 Jan, 2025 | 2 Min read # CloudKeeper Launches Industry’s First Automated AWS Usage Optimization Platform Covering 50+ Services DOVER, Del., USA , Jan 29, 2025 - CloudKeeper, a leader in cloud cost optimization, announced the launch of **real-time assistant** for smarter AWS cost and usage optimization while seamlessly integrating with the **flow of work across multiple AWS accounts**. Achieving the lowest possible cost without compromising performance has been a longstanding challenge for engineering teams. CloudKeeper Tuner addresses this with advanced optimization algorithms rooted in AWS Well-Architected Framework principles. The platform provides **150+ tailored recommendations for 50+ AWS services** , driving an average of 10% cost savings. To streamline workflows for engineers’, CloudKeeper Tuner features **user-friendly browser extensions** , enabling them to **access instant, actionable recommendations directly within the AWS Console** with just a few clicks. Each recommendation comes with estimated savings, offering complete transparency on what, when, and why to optimize. Deepak Mittal, CEO - CloudKeeper, expressed, “ _At CloudKeeper, we actively listen to our customers and understand the challenges faced by their engineering teams. With the launch of CloudKeeper Tuner, we’re setting a new benchmark in the AWS cost optimization space.”_ He added: _"CloudKeeper Tuner is a breakthrough solution, offering optimization across 50+ AWS services which covers 90% of the typical AWS bill—an industry first. It empowers engineering teams to make smarter, data-driven decisions while achieving measurable savings and maintaining peak performance, all through a single platform."_ **Key Features at a Glance** CloudKeeper Tuner delivers precise and effortless optimization through three core features: **1. Recommendations Actionable insights categorized into key areas:** * **Cleaner:** Identifies zombie and unused resources. * **Over-Provisioned:** Detects and optimizes over-allocated compute and storage resources. * **Modernization:** Upgrades resources to the latest AWS instances for improved performance and savings. **2. SpotBot:** Saves up to 65% by dynamically switching ECS Fargate tasks between Spot and On-Demand instances. **3. Scheduler:** Automatically shuts down idle resources during off-hours, reducing costs and environmental impact. Backed by over 100 AWS-certified engineers, CloudKeeper Tuner ensures smooth deployment and rapid results. Its smart data ingestion feature collects real-time usage and cost telemetry from AWS accounts, keeping recommendations up-to-date with ongoing changes. Seamless integrations with Slack and Microsoft Teams further enhance collaboration and streamline workflows for the teams. **Try CloudKeeper Tuner Today** Experience the power of CloudKeeper Tuner with a free trial. Discover how it can revolutionize the way you manage your cloud resources. Read full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 04 Aug, 2025 | 2 Min read # CloudKeeper Named a Major Player in IDC MarketScape: Worldwide FinOps Cloud Costs Optimization Multicloud 2025 Vendor Assessment **New York, USA – August 4th, 2025** - CloudKeeper, a global FinOps and cloud cost optimization company, has been recognized as a**Major Player in the IDC MarketScape: Worldwide FinOps Cloud Costs Optimization Multicloud 2025 Vendor Assessment (Doc #US52991225, July 2025).** Only six vendors have been listed in this IDC MarketScape based on rigorous prequalification criteria. “ _Being named a Major Player by the IDC MarketScape is a proud milestone for us,_ ” said **Deepak Mittal, CEO of CloudKeeper.** “ _We believe this recognition reflects our commitment to solving real-world cloud challenges for businesses through automation, expert guidance, and an unwavering focus on delivering savings. It’s an exciting time for cloud innovations, and we’re proud to be among the frontrunners helping businesses stay in control and ahead of the curve._ ” CloudKeeper offers a comprehensive range of platforms, solutions and support to optimize cloud costs and streamline operations across AWS and Google Cloud. CloudKeeper’s unique approach of combining usage optimization, rate optimization, in-depth visibility and CloudOps augmentation, enables FinOps teams to simplify cloud complexity while driving consistent value. Its flagship products include CloudKeeper AZ, a **About IDC MarketScape** IDC MarketScape vendor assessment model is designed to provide an overview of the competitive fitness of technology and service suppliers in a given market. The research utilizes a rigorous scoring methodology based on both qualitative and quantitative criteria that results in a single graphical illustration of each supplier’s position within a given market. IDC MarketScape provides a clear framework in which the product and service offerings, capabilities and strategies, and current and future market success factors of technology suppliers can be meaningfully compared. The framework also provides technology buyers with a 360-degree assessment of the strengths and weaknesses of current and prospective suppliers. Read the Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 16 Aug, 2022 | 2 Min read # CloudKeeper by TO THE NEW joins FinOps Foundation as a new member company CloudKeeper, a turnkey AWS Cost Management solution by TO THE NEW, has joined the FinOps Foundation, a part of The Linux Foundation’s non-profit technology consortium and focused on advancing the people and practice of cloud financial management, as a new member company. CloudKeeper’s objective is to provide an end to end solution to its customers which provides guaranteed 5-15% savings on cloud bills. CloudKeeper has helped more than 250 global customers with guaranteed savings up to 15% of the entire AWS bill at no extra cost and no inventory commitment. Furthermore, customers get free access to CloudKeeper’s AWS Cloud analytics & optimization platform. With this on the membership, Deepak Mittal, CEO & Co-founder, TO THE NEW says, “CloudKeeper by TO THE NEW is delighted to join the FinOps Foundation in their mission of advancing people through FinOps education. From startups to global enterprises, companies are widely embracing FinOps practices to optimize their cloud transformation journey. As an organization, we have always invested in the area of Cloud FinOps and by being part of this community we can expand our capabilities to better serve our customers with greater savings, flexibility and value in Cloud Financial Management. We look forward to interacting and sharing experiences with like-minded organizations, while upskilling and contributing to the future of FinOps.” Kevin Emamy, Partner Program Advisor for the FinOps Foundation says, “We’re excited to welcome CloudKeeper to our growing community of leading organizations and practitioners at the forefront of the FinOps movement. Our research continues to show more companies devoting even more resources to manage their cloud spend. By expanding our ecosystem of members, as well as our vendor community, we hope to fuel this growth by providing the widest set of resources and tooling available today.” CloudKeeper has helped customers navigate the complexities of cloud cost management by offering them savings, transparency, and visibility all bundled in one unique offering while keeping the account security safely in customers’ hands. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 04 Jan, 2023 | 2 Min read # CloudKeeper ranks in the Top 3 Cloud Cost Management Providers in G2 Winter 2023 Grid® Reports CloudKeeper, by TO THE NEW, is proud to be among the Top 3 Cloud Cost Management Providers in the Inclusion in the G2 Winter 2023 Grid® reports is based on CloudKeeper receiving a high volume of positive reviews from actual solution users. G2 rating algorithm also considers additional metrics from publicly available information and third-party sources. CloudKeeper has been ranked 1st in terms of User Satisfaction and has also earned a spot in the top 3 rankings for multiple categories like - Compliance, Ease of Use, Dashboards and Visualizations, Spend Forecasting and Optimizations, Market Presence, Ease of Setup, Ease of Admin, Best Support and Spend Tracking. The solution has been rated 4 stars or more by 97% of users, with a vast majority of them (92%) expressing their willingness to strongly recommend CloudKeeper to others. "CloudKeeper is a unique solution that offers guaranteed savings on the entire AWS bill. We are very excited and proud to be in the Leaders quadrant along with the likes of AWS and IBM. Unbiased user reviews are what every organization longs for, as they contribute immensely to the creation of intuitive, resilient and sustainable products. I would like to thank each and every one of our customers for helping us achieve this incredible feat.We look forward to providing improved, seamless experiences to our customers and empower them to drive their cloud journeys further ahead" said Deepak Mittal, Co-Founder & CEO, TO THE NEW. "G2 saw very strong results from CloudKeeper in our Winter 2023 Cloud Cost Management Software category. CloudKeeper had the highest satisfaction score in the category, besting both AWS and IBM, and were rated #1 or #2 across 14 different attributes G2 measures. CloudKeeper also saw a lot of success in the Mid-Market space, being named #1 for Compliance, Ease of Setup, and Spend Tracking.” said Chris Perrine, Vice President - Asia Pacific, G2. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 30 Nov, 2022 | 2 Min read # CloudKeeper ranks in the top 5 partners globally in the Well-Architected Challenge conducted by AWS CloudKeeper, by CloudKeeper successfully conducted 131 well-architected reviews and remediated 419 high-risk issues, which made them one of the top 5 partners of AWS in the Platinum category - the highest category in the contest. The AWS Well-Architected Framework Review is a systematic approach that helps competitively benchmark an organization's cloud infrastructure and workloads against the AWS best practices. The review leverages a set of foundational practices based on the six conceptual pillars of the framework laid out by AWS. "It's a proud moment for us to be recognized as a top player in this category. It speaks volumes about our core capability in understanding well-architected frameworks. It acknowledges our ability to work with varied clients, understand their current environment, and share our recommendation basis the principles laid by AWS methodology," said **Deepak Mittal, Co-founder & CEO, **. "By understanding the demands of our customers' industries, clubbed with our premier partnership with AWS, we help them accelerate their digital transformation journeys." "We congratulate CloudKeeper on receiving the Platinum award and appreciate their effort in driving extra reviews and identifying high-risk items for immediate remediation," said **Jodie Wong, Program Manager APJC, AWS Well-Architected Program**. CloudKeeper by TO THE NEW is a one-stop FinOps solution that provides savings, software, services, and support, all bundled into a single solution. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 26 Aug, 2024 | 2 Min read # CloudKeeper recognized in the Cloud Cost Management And Optimization Solutions Landscape Report, 2024 CloudKeeper, a leading provider of cloud cost optimization solutions, has been identified as a **Key Vendor** in the **Cloud Cost Management And Optimization Solutions Landscape Report, 2024**. This recognition highlights CloudKeeper's commitment to delivering cutting-edge solutions that empower businesses to optimize their cloud spending and maximize ROI across AWS, Microsoft Azure, and Google Cloud platforms. According to a Forrester report, "Despite an economic downturn, the annual average enterprise cloud spend has continued to grow to $35 Million which is an increase of $2 Million year over year." It highlights increasing executive pressure for enhanced value from cloud investments. Companies are also finding it difficult to establish an organization-wide governance framework and attain cross-functional buy-in for this plan. Organizations are placing greater emphasis on Cloud Cost Management and Optimization (CCMO) as a solution. Businesses have saved between 20% and 30% of their cloud spending, on average, just by leveraging CCMO solutions. The CCMO market has evolved significantly, with vendors now focusing heavily on automation and rightsizing resources. Forrester has identified the top use cases for these solutions to be cloud cost waste identification; cloud cost sizing/type optimization; and cloud cost commitment term optimization. The landscape report comprehensively analyzes 32 CCMO vendors, applying rigorous selection criteria and detailed vendor differentiation. This approach assists companies in identifying the most suitable cloud cost optimization partner tailored to their specific needs. CloudKeeper has emerged as a strong contender in the report, demonstrating exceptional capabilities and expertise across various categories. CloudKeeper combines advanced group buying strategies, tailored resource provisioning, and enhanced analytics to help organizations achieve significant cost savings while enhancing operational efficiency in the cloud. With a track record of saving 350+ global companies an average of 20% on their cloud bills, CloudKeeper continues to innovate and set benchmarks in the FinOps and Cloud Cost Optimization space. "Happy and proud of this recognition, which underscores our drive to innovate and our commitment to delivering substantial value to our clients," said **Deepak Mittal, Founder & CEO of CloudKeeper**. "Our mission is to be the go-to solution for all cloud needs, and this acknowledgment has further fueled our drive to lead the industry in cloud cost optimization and holistic cloud management solutions." Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 17 Jan, 2025 | 2 Min read # CloudKeeper recognized at the 2024 AWS MPPO Awards by AWS Startup Team, India **New Delhi, 15th January 2025** – CloudKeeper, a leading provider of comprehensive cloud optimization platforms and services, is thrilled to announce its recognition as a**Debutant ISV Partner** as a part of the **AWS Marketplace Private Pricing Offer (MPPO) Awards by AWS Startup Team, India**. This award highlights CloudKeeper’s exceptional contribution to driving customer success and innovation within the AWS ecosystem. The AWS MPPO Award celebrates partners who have demonstrated outstanding performance in leveraging AWS Marketplace’s private pricing feature to deliver tailored cloud solutions. Deepak Mittal, CEO of CloudKeeper, shared his excitement about the recognition. “This award is a testament to our unwavering focus on our customers. At CloudKeeper, we have always aimed to simplify cloud operations and deliver maximum value. A big thank you to the India AWS Start Up Team for their ongoing support and incredible opportunities!” A leader in the cloud cost optimization space, **CloudKeeper is an****and a top AWS reseller**. Ranked among the **top 5 AWS Well-Architected Review partners** globally, CloudKeeper is also an AWS-qualified provider that delivers With its suite of different products available on AWS marketplace, CloudKeeper helps in better management & visibility of cloud through AWS Marketplace Partner Private Offers (MPPO) is a program that enables ISV users on the AWS Marketplace to sell their products with custom terms, including End User Licensing Agreements (EULAs) and tailored pricing. This program helps businesses streamline procurement processes, leverage flexible pricing options, and better meet their specific needs. Additionally, MPPO enables buyers to access AWS resources, which can help accelerate deal closures and enhance collaboration between ISVs and customers. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 15 Apr, 2025 | 2 Min read # CloudKeeper welcomes Kenneth Ziegler as Senior Advisor and Board Member New York (USA), April 14, 2025 - CloudKeeper, a leading provider of comprehensive cloud optimization platforms and services, announces the joining of Kenneth Ziegler ("Ken") as a Senior Advisor and Board Member. Based in New York, Ken brings over 25 years of experience in the technology and cloud services industry, with a proven track record of driving growth and innovation in the sector. As the former President and CEO of Logicworks (now RapidScale), Ken played a pivotal role in transforming the company into a trusted partner for AWS and Azure customers before being acquired by Cox Communications in 2023. At CloudKeeper, Ken will focus on accelerating the growth journey and expanding the footprint in the U.S. market. He will collaborate closely with the Deepak Mittal, CEO of CloudKeeper, expressed his enthusiasm about the new appointment: "Ken’s extensive experience in scaling technology organizations, combined with his deep understanding of the cloud business, will be invaluable to CloudKeeper as we continue to grow. We are thrilled to have him on board to support our continued success." Ken Ziegler added: "CloudKeeper is well-positioned in the cloud optimization space, helping organizations manage costs and improve operational efficiency. I’m excited to work with the team to drive growth and amplify CloudKeeper's impact both in North America and globally!" In addition to his role at CloudKeeper, Ken serves as an Advisory Director at Charlesbank Capital Partners (USA) and sits on the Board of Directors for Maltego Technologies (Germany) and Quorum Cyber (UK). Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 15 Dec, 2021 | 2 Min read # TO THE NEW launches CK Lens™, an AWS Cost Management platform on AWS Marketplace AWS Marketplace is a curated digital catalogue that makes it easy for organizations to discover, procure, entitle, provision, and govern third-party software. With TO THE NEW’s analytics platform, CK Lens™, organizations can effectively manage their cloud resources and optimize their AWS spending instantly in a single place. The solution provides a complete view of infrastructure consumption costs, identifies areas for optimization, billing breakdown, daily cost usage, and much more. CK Lens™ is a part of TTN’s proprietary solution, CloudKeeper, an in-house cloud FinOps solution that ensures a 5-15% reduction of your AWS expenses. TTN also offers a 90-days free CK Lens™ trial period to customers, to help kick-start their journey to monitor and analyze their usage to ensure efficient AWS deployment at all times. **Deepak Mittal, CEO & Co-Founder, TO THE NEW** said, “We’ve seen a surge in demand for cloud-based Cost Management platforms recently as companies rush to move to the cloud. CK Lens will improve businesses’ operational efficiency, streamline cloud costs, and allow them to make better business decisions by leveraging important data insights. Migration to the cloud is expected to continue in the future, and CK Lens will evolve to keep up with the pace of digital transformation requirements.” CK Lens™ serves over 200+ customers globally and has been developed as a result of TO THE NEW’s decade-long experience working with AWS. TO THE NEW has also been an AWS Premier Consulting Partner since 2018. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 10 Mar, 2021 | 2 Min read # TO THE NEW launches CloudKeeper, reduces AWS spends by 15% TO THE NEW announced the launch of its cloud spend optimization solution - **‘CloudKeeper’, which guarantees to cut down AWS bills by 5-15% without any volume commitment**. The solution provides customers with the flexibility to move across Instance family or size as well as operating systems and regions. As a premier consulting and authorised reselling partner of AWS, TO THE NEW has empowered 200+ companies around the world to cut down AWS costs. The solution provides customers with complete flexibility to move across Instance family or size as well as operating systems and regions. TO THE NEW’s marquee customers including Abbott, CreditSense, FEN Learning, In-flight Dublin Tata Sky, and other clients across Enterprises, ISVs, eCommerce, and FinTechare are saving millions of dollars with CloudKeeper. **TO THE NEW offers freedom from all long-term planning & commitments by billing one year reserved like pricing while customers run all their workloads on-demand**. This leads to direct guaranteed savings in their AWS cost from Day 1 without any commitment /upfront payment or lock-in. It also provides its customers with valuable insights into their cloud usage and helps them make intelligent data-driven decisions by providing real-time dashboarding and analytics while managing their AWS billings. With CloudKeeper, customers also get quarterly cost optimization audits and recommendations on how to save costs further. According to **Deepak Mittal, CEO & Co-Founder, TO THE NEW Pvt. Ltd.**, “As businesses walk through difficult times, we have witnessed an increased demand for a cost spend optimization solution on Cloud. CloudKeeper has been successfully helping many organizations by enhancing their operational efficiency, controlling their growing cloud costs, and allowing them to make smart business decisions by making use of valuable data insights. We expect this trend to continue in times to come, with CloudKeeper emerging even more powerful in the future.” TO THE NEW’s CloudKeeper has been helping customers navigate the COVID crisis by offering them transparency, visibility, and cost-savings all bundled in one unique offering while keeping the AWS account security safely in customer’s hands. See the media coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 12 Sep, 2023 | 2 Min read # TO THE NEW recognized in the 2023 Gartner® Magic Quadrant™ for Public Cloud IT Transformation Services We believe this recognition underscores TO THE NEW’s expertise in harnessing the power of public cloud technologies and its commitment to reshaping industries in a cloud-first world by delivering specialized cloud transformation journeys. The evaluation was based on TO THE NEW’s ability to execute and completeness of vision. TO THE NEW helps businesses design, build, and maintain their multi-horizon cloud transformation journeys, with end-to-end cloud engineering services including, implementation, modernization, 24x7 managed services, DevOps, and cost optimization. Its proprietary solution on AWS cost optimization and FinOps services, Commenting on this recognition, **Deepak Mittal, CEO & Co-founder at TO THE NEW**, said, "We are honored to be acknowledged in the Gartner Magic Quadrant for Public Cloud IT Transformation Services. This recognition validates our relentless dedication to delivering exceptional cloud-native solutions and transformational services. We are committed to making investments in our in-house IP’s and, most importantly our global talent, which have been the cornerstone of our success. We remain committed to driving innovation, providing valuable services, and being a trusted partner in our clients' digital transformation journeys.” With its deep domain expertise and engineering mindset, TO THE NEW strives to benefit organizations in their different stages of the cloud journey. This research can help global enterprises trust TO THE NEW to be among the 21 distinguished providers dedicated to cloud transformation services. For more information, view the report **Gartner Disclaimer** Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s Research & Advisory organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. GARTNER and MAGIC QUADRANT are registered trademarks and service marks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 22 Jan, 2021 | 2 Min read # TO THE NEW recognized by ISG for its strong competencies in Public Cloud TO THE NEW, a leading provider for digital transformation and technology services has been recognized by ISG Provider LensTM for its capabilities on Cloud, Application Development services as well as an AWS Ecosystem Partner in their recently published analyst quadrant reports for 2020. TO THE NEW has made its debut in ISG ratings this year and been named as a “Product Challenger” for its **Data Analytics & ML capabilities** along with being a “Contender” for **Cloud Consulting, Managed Services & Agile Development**, amongst others. ISG Provider Lens™ is a unique evaluation of market players with empirical, data-driven research and market analysis in light of the observation of ISG’s global advisory team. ISG evaluated multiple vendors with a global presence based on customer portfolio, innovation capabilities, performance & growth, experience and case studies. “This is a truly remarkable achievement. It is a result of our agility and focus on building new-age capabilities, to provide high-quality transformation-services to our fast-growing customer base. It is heartening to see TO THE NEW increasingly being recognised across the industry to laud our growth and achievements.”, said **Deepak Mittal, Co-founder & CEO, TO THE NEW**. ISG has attributed TO THE NEW’s positioning to its DevOps focused approach, robust and long-standing AWS partnership, extensive Cloud Consulting experience and strong Product Engineering & Quality Engineering expertise. “TO THE NEW is a fast-growing provider that offers high-quality transformation services by leveraging its strong partnership and DevOps styled approach in migration of workloads to the public cloud.", said **Shashank Rajmane, Lead Analyst, ISG**. “ISG sees TO THE NEW as a strong competitor in our AWS Data Analytics and Machine Learning Partner quadrant with robust core capabilities and an aggressively expanding portfolio. ISG also sees To The New as one of the most aggressive providers in our AWS Consulting Services Partner quadrant. The company demonstrates excellent foundational capabilities & a competitive services portfolio, while also demonstrating superb client relationship management and support.", said **Bruce Guptill, U.S. Principal Analyst, ISG**. See the media coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 26 Dec, 2023 | 2 Min read # TO THE NEW Recognized as a “Product Challenger” Under 3 Categories in the ISG Provider Lens Report for AWS Ecosystem Partners 2023 **‘Product Challenger’ in 3 categories - Consulting Services, Managed Services, and Data Analytics & Machine Learning, in the ISG Provider Lens™ for AWS Ecosystem Partners 2023 Report.** In this quadrant, ISG highlights the current market positioning of AWS partners and how they address the critical challenges of offering managed services in the AWS ecosystem. ISG’s assessment is based on the expanse of providers’ service offerings and market presence. This recognition underscores TO THE NEW’s expertise in providing comprehensive cloud solutions that help organizations maximize their AWS investments and reflect the company's strong capabilities across the full spectrum of cloud services. Furthermore, "We are thrilled to be recognized as a Product Challenger by ISG" said **Deepak Mittal, CEO at TO THE NEW.** "This recognition is a testament to our team's commitment to providing our customers with the best possible cloud solutions and also help them in embracing FinOps principles to enhance cost efficiency and optimize cloud utilization." ## **About ISG Provider Lens™** The ISG Provider Lens™ Quadrant research series is a leading source of independent market evaluation for service providers. The reports provide detailed data and market analysis to help enterprises select appropriate sourcing partners. The research currently covers providers offering their services across multiple geographies globally. See the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 23 Jan, 2024 | 3 Min read # TO THE NEW Recognised by ISG in 2023 Multi Public Cloud Services Provider Lens™ "This recognition in the three key categories of ISG's 2023 Multi Public Cloud Services Provider Lens report is a true honor," says **Deepak Mittal, CEO of TO THE NEW**. "It signifies our commitment to staying at the forefront of the multi-cloud landscape, offering customers access to the latest tools, technologies, and best practices.” He further added, “ This Provider Lens™ evaluates providers offering public cloud services, including consulting and transformation, managed services, public cloud infrastructure, and specialized services like FinOps and SAP HANA environments, across multiple major public cloud platforms, like AWS, Azure, and GCP, helping businesses choose the right partner for their multi-cloud strategy. The consulting and transformation quadrant of the report evaluates providers that assist enterprises in modernizing, optimizing, and transforming their IT operations to achieve greater efficiency, agility, and security. The managed services for Midmarket quadrant assesses managed service providers who adopt DevOps-centric approach to support robust CI/CD pipelines with strong container management capabilities, offer expertise in site reliability engineering (SRE) and business resiliency, cloud infrastructure lifecycle management and real-time multicloud monitoring with predictive analytics to maximize performance, reduce costs and ensure compliance and security. The FinOps and cloud optimization quadrant assesses service providers who offer expertise in workload assessment, cloud governance, and FinOps, utilizing AI/ML analytics to predict costs and identify savings opportunities. Leaders actively manage FinOps tools for clients, automate resource utilization, and even handle resource transactions while streamlining workflows for swift budget management. In essence, these providers become expert partners in navigating the complexities of multi-cloud cost optimization. ISG's independent validation provides assurance that TO THE NEW possesses the necessary expertise and capabilities to deliver value, optimize cloud investments, and drive business transformation.Being named in ISG's Provider Lens is a significant milestone on this journey, and TO THE NEW remains dedicated to continuously enhancing its offerings and exceeding customer expectations. Furthermore, CloudKeeper, its proprietary solution, empowers organizations using multi -cloud services by delivering guaranteed cost savings and comprehensive FinOps services. ## **About ISG** ISG Analyst firm, also known as Information Services Group, Inc., is a leading global technology research and advisory firm based in Stamford, Connecticut. It specializes in providing expert guidance and market insights to help businesses, service providers, and technology vendors navigate the ever-changing world of information technology. The ISG Provider Lens™ Quadrant research series is their leading source of independent market evaluation for service providers. The reports provide detailed data and market analysis to help enterprises select appropriate sourcing partners. The research currently covers providers offering their services across multiple geographies globally. Read the full coverage Published in * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Our Platforms * ## What’s **included** Pricing Lock-In or Commitment Available on Marketplace 24*7 Personalized Cloud Support Well-Architected Reviews * ### CloudKeeper **Lens** Cloud Cost Visibility and Recommendations 2% of the monthly cloud bill Month-on-Month agreement **Yes** **Yes** **Yes** * ### CloudKeeper **Tuner** Automated Usage Optimization & Recommendation Platform 2% of the monthly cloud bill Month-on-Month agreement **Yes** **Yes** **Yes** * ### CloudKeeper **Commit** Zero-touch, AI-based Platform for AWS RI Management 18% of the savings delivered Month-on-Month agreement **Yes** **Yes** **Yes** * CloudKeeper Lens * Resource-level cost visibility. * Hourly dashboards and heat maps. * Advanced cost-clarity dashboards. * Cloud cost optimization recommendations. * CloudKeeper Tuner * 150+ Recommendations across 50+ AWS Services. * Integrates with AWS Console via an extension. * Fits into the flow of work across multiple accounts. * Backed by 100+ AWS-certified engineers for faster implementation. * CloudKeeper Commit * Automated AWS RI management. * RI/Savings Plans-like pricing for on-demand compute instances. * No commitment and risk-free 100% coverage. * Buy-back guarantee of unused RIs. Our Solutions ### CloudKeeper **AZ** One-stop solution addressing the A to Z of cloud cost optimization Our customers achieve an average of 20% savings on the entire cloud bill * Instant & Guaranteed Savings of up to **15% on your cloud spend**. * No commitment or Lock-in. * On-demand instances at commitment-based pricing. * Discounted rates for top-tier AWS & GCP support. * Access to volume-based pricing & unified billing. * 24*7 personalized cloud support & Well-Architected Reviews. ### Exclusive access you unlock **@1% of monthly bill** **(for each platform)** ### CloudKeeper Lens Cloud Cost Visibility Platform ### CloudKeeper Tuner Usage Optimization Platform Up to 10% additional savings ### CloudKeeper **PPA+** Gain additional benefits while lowering commitment on AWS PPA * Bigger discounts compared to standard PPA agreements. * Lower Annual Commitments compared to standard PPA agreements. * Discounted Price on AWS Support. * 24*7 personalized cloud support from certified experts. * Well-Architected Reviews & Audits at frequent intervals. ### Exclusive access you unlock **@1% of monthly bill** **(for each platform)** ### CloudKeeper Lens Cloud Cost Visibility Platform ### CloudKeeper Tuner Usage Optimization Platform Up to 10% additional savings Our Capabilities Certified experts ensuring your cloud is always optimized, cost-efficient, and future-proof * 24*7 Personalized Cloud Support Comprehensive Suite of Services by Certified Cloud Experts * Designated Account Manager * Architecture and Business Reviews * DevOps and Automation Support * Cost and Performance Optimization * Adoption of New Cloud Services * Migration Support & POC * Third-Party Tech Stack Guidance * Partner-Led Support AWS Enterprise Support Benefits + 24*7 Support * Open Cases with AWS Support * AWS Service Guidance & Billing Support * AWS Account Manager & Solution Architect * Unlimited Architecture & Business Reviews * Unlimited TAM Assisted Case Escalation * Unlimited Infrastructure Event Management * 24*7 Technical Support & Application Guidance * Well-Architected Reviews Customized WAR Assessments, delivering 10% savings within the first 90 days * Designated Account Manager * Architecture and Business Reviews * DevOps and Automation Support * Cost and Performance Optimization * Consultation & implementation support * Engagement until cloud optimization achieved Need help in deciding the best solution for you? Schedule a call with our team and we’ll help you out. Trusted by 400+ Global Customers Our customers saved an average of 20% on their monthly AWS and GCP spend through CloudKeeper We have expertise across leading cloud platforms * * Frequently Asked **Questions** * ### Arrow 1.How much can I potentially save with CloudKeeper AZ? Q1. How much can I potentially save with CloudKeeper AZ? With CloudKeeper AZ, you get instant & guaranteed savings of up to 15%. Plus, you can unlock additional savings using CloudKeeper Lens and Tuner. On average, our customers save 20% on their entire cloud bill. * ### Arrow 2.How much can I potentially save with CloudKeeper Tuner? Q2. How much can I potentially save with CloudKeeper Tuner? With CloudKeeper Tuner, you can achieve an average savings of 10% within the first 30 days of onboarding. * ### Arrow 3.Is there any long-term commitment or lock-in? Q3. Is there any long-term commitment or lock-in? No, all CloudKeeper solutions and platforms come with no lock-in except CloudKeeper EDP+. You have the flexibility to scale up or opt-out anytime, ensuring complete control over your cloud cost optimization journey. * ### Arrow 4.Will I be charged separately for 24*7 support or Well-Architected Reviews? Q4. Will I be charged separately for 24*7 support or Well-Architected Reviews? No, both are included at no additional cost in all CloudKeeper solutions and platforms. * ### Arrow 5.Can I use CloudKeeper Lens & Tuner across different cloud providers? Q5. Can I use CloudKeeper Lens & Tuner across different cloud providers? Yes, CloudKeepers Lens is available for AWS & GCP. CloudKeeper Tuner is currently available for AWS, with plans to launch on GCP. * ### Arrow 6.What level of support is included with CloudKeeper solutions and platforms? Q6. What level of support is included with CloudKeeper solutions and platforms? CloudKeepers offers 24/7 personalized cloud support, including a designated account manager, architectural reviews, anomaly detection, hands-on implementation assistance, and much more. * ### Arrow 7.Are your platforms available on the marketplace? Q7. Are your platforms available on the marketplace? Yes, CloudKeeper Lens, Tuner, and Auto are all available on the marketplace. * ### Arrow 8.Can I use CloudKeeper platforms with multiple cloud accounts? Q8. Can I use CloudKeeper platforms with multiple cloud accounts? Yes, our platforms support multi-account management. * ### Arrow 9.How long does onboarding take? Q9. How long does onboarding take? Just a few minutes! Our simple and hassle-free process gets you up and running in no time. * ### Arrow 10.Is CloudKeeper a certified cloud partner? Q10. Is CloudKeeper a certified cloud partner? Yes, CloudKeeper is a certified AWS and Google Cloud Partner. With 15+ years in business, CloudKeeper has delivered over $120 million in cloud cost savings. * ### Arrow 11.How do I know if CloudKeeper is right for my business? Q11. How do I know if CloudKeeper is right for my business? No worries! We offer a **free cloud savings assessment and expert consultation** to show you exactly how much you can save and maximize your ROI with CloudKeeper. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Information We Collect * ### Our Services We may collect personally identifiable information about you through our website when you register for an account, such as your email. We also collect data through our partners (customers) who use our Service (including by embedding our code on their websites) to analyze usage of their websites. When you visit such websites, your browser may send us certain information about you as described below. We do not send any promotional emails, however we may send you service-related emails related to your account. * ### Cookies Information We may send one or more cookies - a small text file containing a string of alphanumeric characters - to your computer that uniquely identifies your browser and lets learn about your behavior and usage patterns when you are on our site. A cookie may also convey anonymous information about how you browse a partner website to us. A cookie does not collect personal information about you. A persistent cookie remains on your hard drive after you close your browser. Persistent cookies may be used by your browser on subsequent visits to the site. Persistent cookies can be removed by following your web browser's directions. A session cookie is temporary and disappears after you close your browser. You can reset your web browser to refuse all cookies or to indicate when a cookie is being sent. * ### Log File Information Log file information is automatically reported by your browser each time you access a web page on our site. When you access the Service, our servers automatically record certain information that your web browser sends whenever you visit any website. These server logs may include information such as your web request, Internet Protocol ("IP") address, browser type, referring / exit pages and URLs, number of clicks, domain names, landing pages, pages viewed, and other such information. * ### Clear Gifs Information When you access the Service or are on our website, we may employ clear gifs (also known as web beacons) which are used to track the online usage patterns of our users anonymously. No personally identifiable information from your CloudKeeper account is collected using these clear gifs. The information is used to enable more accurate reporting, improve the effectiveness of our Service, and make CloudKeeper better for our users and partners. These technologies mentioned above do not collect personal information about you and only collect data in the aggregate. How we share Your Information * ### Personally Identifiable Information CloudKeeper will not rent or sell your personally identifiable information to others. We may store personal information in locations outside the direct control (for instance, on servers or databases co-located with hosting providers). As we develop our business, we may buy or sell assets or business offerings. Customer, email, and visitor information is generally one of the transferred business assets in these types of transactions. We may also transfer or assign such information in the course of corporate divestitures, mergers, or dissolution. * ### Non-personally Identifiable Information We may share non-personally identifiable information (such as anonymous usage data, referring/exit pages and URLs, platform types, number of clicks, etc.) with interested third parties to help them understand the usage patterns for certain CloudKeeper's services and those of our partners. Non-personally identifiable information may be stored indefinitely. * ### How We Protect Your Information CloudKeeper is concerned with protecting your privacy and data, but we cannot ensure or warrant the security of any information you transmit to CloudKeeper or guarantee that your information on the service may not be accessed, disclosed, altered, or destroyed by breach of any of our industry standard physical, technical, or managerial safeguards. * ### Compromise of Personal Information In the event that personal information is compromised as a result of a breach of security, CloudKeeper will promptly notify those persons whose personal information has been compromised, in accordance with the notification procedures set forth in this Privacy Policy, or as otherwise required by applicable law. * ### Your Choices About Your Information You can review and correct the information about you that CloudKeeper keeps on file by logging into your account to update your password and billing information. Alternatively, you can contact us directly at * ### Children’s Privacy Protecting the privacy of young children is especially important. For that reason, CloudKeeper does not knowingly collect or solicit personal information from anyone under the age of 13. If you are under 13, please do not send any information about yourself to us, including your name, address, telephone number, or email address. No one under the age of 13 is allowed to provide any personal information to CloudKeeper. In the event that we learn that we have collected personal information from a child under age 13 without verification of parental consent, we will delete that information as quickly as possible. If you believe that we might have any information from or about a child under 13, please contact us at * ### Notification Procedures It is our policy to provide notifications, whether such notifications are required by law or are for marketing or other business-related purposes, to you via email notice, written or hard copy notice, or through conspicuous posting of such notice on the Service, as determined by CloudKeeper in its sole discretion. We reserve the right to determine the form and means of providing notifications to you, provided that you may opt out of certain means of notification as described in this Privacy Policy. * ### Features on Our Site If you use a bulletin board or chat room on this site, you should be aware that any personally identifiable information you submit there can be read, collected, or used by other users of these forums, and could be used to send you unsolicited messages. We are not responsible for the personal information you choose to submit in these forums. We also have testimonials on our site, for which users have given permission to have their personal information posted on our site with their testimonial. * ### Links to Other Web Sites Our Site includes links to other websites whose privacy practices may differ from those of other sites. If you submit personal information to any of those sites, your information is governed by their privacy statements. We encourage you to carefully read the privacy statement of any Web site you visit. * ### Changes to Our Privacy Policy If we change our privacy policies and procedures materially, we will post those changes on the Service to keep you aware of what information we collect, how we use it and under what circumstances we may disclose it. Changes to this Privacy Policy are effective when they are posted on this page. If you have any questions about this Privacy Policy, the practices of this site, or your dealings with this website, please contact us at * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Cloud has demonstrated a clear ability to impact the bottom line. Managing a portfolio of companies with diverse cloud needs can be challenging for Private Equity firms. CloudKeeper understands this and has been a strategic partner for leading Private Equity firms to tackle the cloud challenges head-on. We offer comprehensive solutions and services, to maximize savings while ensuring optimal cloud performance across the entire portfolio. The CloudKeeper Effect: Value Delivered Right from Day One Our partnership provides holistic support covering everything from immediate cost savings to long-term growth enablement. * Results from Day 1 Begin achieving cloud cost savings from Day 1 following a few minutes of seamless onboarding process. * Improved Financial Performance Significant savings directly contribute to higher margins and improved financial performance across your portfolio companies. * We own commitment risk Don't be held back by commitment. Run everything on-demand at commitment-based pricing with 100% coverage. * Efficiency & risk management Our proactive approach to cost management mitigates potential overruns and cloud sprawl risks within your portfolio. * Focus on Strategic Growth We handle end-to-end cloud needs, empowering your portfolio companies to focus on core business initiatives that drive long-term success. * Competitive Differentiation Reduced cloud costs allow your portfolio companies to invest in innovation and stay ahead of the competition. A custom-built cloud cost optimization roadmap for each portfolio company Our certified cloud experts create structured roadmaps with short, medium, and long-term cloud strategies, ensuring that cloud ROI is maximized and specific cloud challenges are addressed. * Identify & remediate critical issues * Adoption & integration of new cloud services * Expert support for overall cloud optimization * Proactive outreach for cost optimization * Human-assisted cost anomaly detection * Custom monthly cost analysis reports Here’s how we optimize the entire cloud cost optimization journey of PE-backed companies * Rate Optimization * Guaranteed discounts on the entire bill & access to volume-based pricing. * On-demand instances at commitment-based pricing. * Maximum benefits on AWS EDP, PPA, MAP, & other similar programs. * Usage Optimization * Ensure the cloud resources perfectly match the workload. * Optimize resource efficiency with automated and manual policies. * Identify optimization opportunities across compute, data, and storage. * Cloud Consulting & Support * Designated and certified cloud expert for 24*7 personalized support. * Well-Architected Reviews and cloud cost audits. * Cloud Architectural consulting and migration support. Our Full-Spectrum of Capabilities: The one-stop destination for your cloud success * Consult * FinOps Consulting & Support * Well-Architected Reviews * Implement * Cloud Migration Planning & Implementation * Cloud Modernization Strategies * Manage * 24*7 Personalized Cloud Support * Partner-led Support at a discounted price * Improve * Architecture Guidance & Cost Optimization Support * DevOps Free your team from the responsibility of managing the cloud and allow them to dedicate their time and expertise to driving strategic growth initiatives. A partnership for long-term growth With 15+ years of expertise, CloudKeeper understands the unique challenges private equity firms face. We offer a collaborative partnership approach, providing: * Dedicated Account Management A dedicated account manager will work closely with your portfolio companies to understand the specific needs and offer solutions accordingly. * Regular Reporting & Visibility Actionable insights into cost spending for informed decision-making. Efficient cost allocation, chargeback, & tagging, along with alerts & notifications. * Expertise & Support Our team of certified cloud experts is available 24*7 to provide ongoing support and guidance to your portfolio companies. * Quarterly Business Reviews Meet with our team quarterly to comprehensively review your progress and refine cloud cost optimization strategies. * Well-Architected Reviews Periodically, our cloud-certified experts assess the infrastructure against the latest cloud best practices frameworks. * Leveraging Cloud Partner Network We access the cloud partner network resources, programs, and incentives to further support and meet your specific business goals. Delivered maximum cloud ROI across the portfolio of top private equity firms Your one-stop destination for Cloud Cost Optimization * Highest tier partner with 100+ certifications & expertise in designing, migrating, & managing workloads on the AWS cloud. * Certified expertise & competencies to help businesses maximize the potential of Google Cloud infrastructure. **Related Resources** * Fumbles in FinOps Adoption and How to Avoid Them Watch this exclusive panel discussion where our industry experts talk about the common mistakes organizations make in their FinOps adoption journey. On-Demand Webinars * The Growing Need for Multi-Cloud FinOps Solutions to Reduce Cloud Costs Learn key strategies for multi-cloud cost management and discover how FinOps can help you achieve significant savings. Blog * Top Cloud FinOps KPIs you must measure to drive success: A Complete Guide Explore essential Cloud FinOps KPIs that supercharge your cloud management. Achieve optimized cloud costs, improved visibility, and seamless governance. Blog Frequently Asked **Questions** * ### Arrow 1.How does CloudKeeper help Private equity firms with cloud cost optimization? Q1. How does CloudKeeper help Private equity firms with cloud cost optimization? CloudKeeper’s Private Equity partner program is tailored to help Private Equity firms optimize the cloud costs and performance of their portfolio companies. We offer a comprehensive suite of cloud cost optimization solutions and services that help in cloud cost visibility, cloud resource optimization, cloud billing optimization, and ongoing cost management. * ### Arrow 2.Why is cloud cost optimization important for Private Equity firms? Q2. Why is cloud cost optimization important for Private Equity firms? With portfolio companies increasingly relying on cloud infrastructure, rising costs can erode profitability. CloudKeeper ensures optimal cloud utilization, identifies inefficiencies, and helps improve EBITDA across your portfolio. * ### Arrow 3.Does the program cover multiple cloud platforms? Q3. Does the program cover multiple cloud platforms? Yes, the program supports all major cloud providers, including AWS and Google Cloud Platform (GCP), ensuring comprehensive optimization for multi-cloud portfolios. * ### Arrow 4.How quickly does the savings start with CloudKeeper? Q4. How quickly does the savings start with CloudKeeper? Savings begin on Day 1 with a quick and seamless onboarding process that takes just a few minutes. * ### Arrow 5.How does CloudKeeper address potential cost overruns and cloud cost commitment risks? Q5. How does CloudKeeper address potential cost overruns and cloud cost commitment risks? Our proactive cost management approach includes real-time monitoring, cost anomaly detection, and cloud sprawl mitigation to reduce risks and ensure efficient cloud usage. We take full ownership of commitment risks, allowing your portfolio companies to run everything on demand while benefiting from commitment-based pricing with 100% coverage. * ### Arrow 6.What sets CloudKeeper apart from other cloud cost optimization partners for private equity firms? Q6. What sets CloudKeeper apart from other cloud cost optimization partners for private equity firms? Our certified cloud experts conduct detailed assessments and offer a custom-built roadmap that is tailored to the unique needs of the portfolio company, covering short, medium, and long-term cloud strategies. CloudKeeper acts as a cloud cost management vertical and handles all end-to-end cloud needs, allowing portfolio companies to focus on their core business initiatives that drive innovation and long-term success. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Rate Optimization at no commitment or risk AI-led, Guaranteed, & Ongoing Cloud Cost Savings * **25%** Avg. savings on entire cloud bill * **400+** Companies served globally * **$120+ million** Cloud Cost Savings delivered * **24x7** Unlimited Cloud Support Cloud Costs Are Growing. Your Savings Aren't Most businesses are leaving significant money on the table - because the right rate optimization levers are hard to identify, manage, and execute at the right time. * #### Untapped Hidden Savings Most teams optimize usage but still miss hidden rate advantages across billing, commitments, and commercial constructs. * #### Too much complexity, too little time Reserved Instances, Savings Plans, and AWS commercial agreements require continuous attention, expertise, and fast decision-making. * #### Rigid contracts and risky commitments Many organizations hesitate to commit because they fear lock-ins, overcommitment, and paying for capacity they may not use. * #### Fragmented tools and disconnected outcomes Fragmented tooling, manual spreadsheets, & siloed teams make it impossible to act on rate optimization opportunities. * #### Reactive vs Proactive Savings Most FinOps teams are reactive. Real savings happen upstream, at the rate negotiation & commitment layer, before consumption occurs. * #### PPA Negotiation Gaps Without expert help in negotiations, businesses over-commit, accept suboptimal discounts, and miss add-on benefits they're entitled to. One Solution. Three ways to optimize your cloud rates. CloudKeeper unifies savings expertise, AI-powered intelligence, and continuous optimization in one place - eliminating the need for multiple vendors or fragmented approaches. 01 Instant & Guaranteed Savings on Cloud * Zero cost * Zero lock-in * Zero commitment Average Savings 25% on the entire bill * Cloud Cost Savings start from Day 1 * Best-in-market volume discount rates * Access to Prism & Unlimited 24*7 Support * Dedicated account management * Access to Platform Suite (available at an additional cost) ‹› hbspt.forms.create({ region: "na1", portalId: "47057450", formId: "44723dbb-df78-424c-9c2c-ffdedc29c2d4" }); Cloud Partner Advantage We have direct access to the best pricing tiers, support channels, and negotiation pathways. Why do businesses choose CloudKeeper for rate optimization? AI adoption is accelerating - but costs are becoming harder to predict and optimize. We consistently see the same set of challenges across our customer environments. * ### Fast Onboarding, Faster Impact Get started in minutes - no complex setup. Start seeing savings from Day 1 itself. * ### Anomaly Detection - Human + AI AI catches the spike. A real expert confirms it. No alert fatigue, no false alarms - just actionable insights. * ### No Lock-in. Ever. No long-term commitments, no exit fees, no gotchas. If we don't keep saving you money, you're free to walk away. Your Dedicated FinOps Squad Each customer is backed by a dedicated team that collaborates with you daily through Slack or Teams. * ### FinOps Strategist Guides you towards the right plan selection and ensures seamless onboarding for immediate savings. * ### Solutions Architect Provides ongoing technical support, resolves complex issues, and ensures efficient utilization of cloud resources. * ### Customer Success Partner Tracks progress, shares weekly/monthly reports, and ensures optimization turns into sustained savings. Real Optimization Outcomes with CloudKeeper | Customer Name | Key Challenge | CloudKeeper Approach | Measurable Impact | | --- | --- | --- | --- | | | Limited cost visibility, lack of FinOps practices, and inefficient cloud spend management | CloudKeeper AZ for instant discounts, along with dedicated FinOps support to enable continuous cost visibility and optimization. | Achieved **25% AWS savings on total cloud bill** , with savings active from Day 1 and zero lock-in or upfront commitment | | | Lack of cost visibility, manual RI/SP management, cost attribution issues, and difficulty handling anomalies | PPA+ for savings, implemented RI/SP optimization, tagging, anomaly detection, and architectural improvements | Delivered **~27% total AWS cost savings** (12% instant + additional optimizations) with improved financial transparency | | | High overall cloud spend with inefficiencies and limited optimization across infrastructure | Leveraged CloudKeeper AZ along with dedicated FinOps support and continuous cost visibility. | Reduced **~22% of total cloud spend,** improving overall cost efficiency | * #### KEY CHALLENGE Limited cost visibility, lack of FinOps practices, and inefficient cloud spend management #### CLOUDKEEPER APPROACH CloudKeeper AZ for instant discounts, along with dedicated FinOps support to enable continuous cost visibility and optimization. #### MEASURABLE IMPACT Achieved **25% AWS savings on total cloud bill** , with savings active from Day 1 and zero lock-in or upfront commitment * #### KEY CHALLENGE Lack of cost visibility, manual RI/SP management, cost attribution issues, and difficulty handling anomalies #### CLOUDKEEPER APPROACH PPA+ for savings, implemented RI/SP optimization, tagging, anomaly detection, and architectural improvements #### MEASURABLE IMPACT Delivered **~27% total AWS cost savings** (12% instant + additional optimizations) with improved financial transparency * #### KEY CHALLENGE High overall cloud spend with inefficiencies and limited optimization across infrastructure #### CLOUDKEEPER APPROACH Leveraged CloudKeeper AZ along with dedicated FinOps support and continuous cost visibility. #### MEASURABLE IMPACT Reduced **~22% of total cloud spend,** improving overall cost efficiency Not Sure Which Solution Fits? Our FinOps experts will analyze your current cloud spend and recommend the right combination. **Pioneering end-to-end cloud management** **Ranked #1** in User Satisfaction based on 100% genuine customer reviews for Cloud Management * CloudKeeper has truly been a **game-changer for our cloud cost management.** It is **essential** for anyone who wants to take control of their cloud spending and make the most out of their infrastructure. I **highly recommend** it to any organization looking to get serious about managing its cloud expenses. Aakash Sharma S. Lead CloudOps * We’ve achieved strong savings through their discounts, cost optimization, and technical support. They act like an extension of our own team, proactively flagging cost anomalies and providing detailed follow-ups. A truly valuable partner for AWS cost management. Palani E Principal Technical Architect * The team is super supportive of all our tracks around infra cost optimisation. Overall, we've got a deep discount with our EDP commitment and great support from the team so far. * CloudKeeper's **offering is one of a kind.** It **acts as our FinOps vertical** and helps out in cloud financial management, ensuring that we can focus on our delivery expertise. Ajay Y. DevOps Leader * More than just cost savings, a **business partner I can rely on.** CloudKeeper has proven its deep understanding of the AWS platform. The transition to integrate Cloudkeeper into our AWS account was easy. It made cost management and optimization quite easy. Frank D. DevOps Team Lead * Cost Optimization, Technical assistance, and Resource optimization bundled as one. In short, **an end-to-end FinOps solution.** Praveen K. Senior Cloud Engineer Frequently Asked Questions * ### Arrow 1.What is rate optimization in cloud cost management? Q1. What is rate optimization in cloud cost management? Rate optimization focuses on lowering the unit price you pay for cloud services through better commercial constructs, discount programs, commitments, and negotiated pricing - without relying only on usage reduction. * ### Arrow 2.Is my data and cloud account secure with CloudKeeper? Q2. Is my data and cloud account secure with CloudKeeper? Absolutely. CloudKeeper is an AWS Premier Tier Services Partner with strict security and compliance standards. For Commit, we only request the minimal IAM permissions required for RI management - no access to your data or workloads. All data is encrypted in transit and at rest, and we undergo regular third-party security audits. * ### Arrow 3.We already have an AWS PPA/EDP. Can CloudKeeper help? Q3. We already have an AWS PPA/EDP. Can CloudKeeper help? No worries - we can still add value. Even if your AWS PPA/EDP is active, we help optimize how you use it. From cost-saving recommendations to continuous optimization and usage tracking, we can ensure you get the most from your contract. And when it’s time for renewal, we’ll be right there to help you get a better deal. * ### Arrow 4.How quickly can I start seeing savings? Q4. How quickly can I start seeing savings? For CloudKeeper AZ & PPA+, savings are typically reflected in your next billing cycle. CloudKeeper Commit's AI begins optimizing your RI portfolio immediately upon integration, with measurable impact visible within the first month. * ### Arrow 5.How do I optimize AWS RI and Savings Plans effectively? Q5. How do I optimize AWS RI and Savings Plans effectively? Effective optimization requires: * Continuous tracking of usage patterns * Right-sizing commitments * Buying/selling decisions at the right time Platforms like CloudKeeper Commit automate this process. * ### Arrow 6.What is AWS Private Pricing Agreement (PPA)? Q6. What is AWS Private Pricing Agreement (PPA)? An AWS PPA (formerly EDP) is a custom pricing agreement offering discounts in exchange for committed cloud spend over a period. * ### Arrow 7.Is it risky to commit to AWS Savings Plans or RIs? Q7. Is it risky to commit to AWS Savings Plans or RIs? Yes, if done manually. Over-commitment or misaligned usage can lead to wasted spend. That’s why AI-led automation (like Commit) helps reduce risk. * ### Arrow 8.How does Premier Partnership with hypercalers help with cloud cost savings? Q8. How does Premier Partnership with hypercalers help with cloud cost savings? An AWS Premier Partner has the highest level of AWS accreditation, giving them direct access to better pricing tiers, dedicated AWS support channels, and PPA negotiation pathways that most businesses can't access independently. ## Certified. Trusted. Industry Recognized. ## Stop paying for cloud tools. Start paying for outcomes. close close * * * * * * * # What’s New in **Cloud Cost Optimization** in 2025? The Research Report for Engineering & FinOps Leaders * * × ## About **the Report** This flagship report from CloudKeeper delivers deep insights into cloud cost optimization trends shaping 2025. Built on data from **500+ organizations,** combined with perspectives from **leading FinOps experts,** the report outlines the next era of cloud financial governance. Whether you're an engineering leader, FinOps practitioner, or cloud architect, this is your roadmap to optimizing cloud spend in today’s complex environments. What **You’ll Learn** Real-world data collected from actual organizations. * The biggest inefficiencies draining cloud budgets (and how companies are fixing them) * The impact of Graviton, serverless, and containerization on compute savings * Best practices for sustainable, real-time cost governance * Why multi-cloud visibility & FOCUS are now essential * How human-assisted remediation & automation are transforming cloud financial operations * A data-backed Cloud Cost Optimization Index to guide your next moves Key **Highlights** Data-Backed Trends Shaping Smarter Cloud Spending * 60% of organizations still have idle network resources * 90% can migrate to lower-cost compute (Graviton, AMD) * 20% reduction in cloud bill spikes with AI- driven monitoring * 35% infrastructure cost reduction with serverless & container workloads * 5-25% savings achieved by CloudKeeper customers using automated tools Featured **Contributors** Crafted using proprietary insights from CloudKeeper's cost data from 500+ real-world organizations * ### Pankaj Bajaj FinOps Leader, Mercari * ### Shahnawaz Khan Group PM, HCL Tech * ### Dieter Matzion FinOps Ambassador, Roku * ### Victor Garcia Founder, FinOps Weekly Industry Validation & Trusted Sources Insights aligned with leading research from FinOps Foundation, Gartner & Forrester Inside **the Report** A 5-step approach to smarter cloud cost optimization. * ### 1 1 Trends & Challenges From AI workloads to underutilized RIs * ### 1 2 Tech Drivers AI, automation, and modern compute architectures * ### 1 3 Tools & Innovations Anomaly detection, rightsizing and cost dashboards * ### 1 4 Best Practices FinOps frameworks, storage/network governance * ### 1 5 Cloud Cost Optimization Index 2025 What to prioritize, pilot, and sunset Who Should **Read This Report?** A must-read for cloud, finance, and engineering leaders driving cost efficiency * ### FinOps Teams Building data-driven strategies * ### Cloud Architects Optimizing for performance & cost * ### Engineering Leaders Managing cloud growth * ### Finance Executives Seeking better cost accountability ### Ready to see how your organization stacks up and what you can improve? **Get the Complete Data, Analysis, and Expert Recommendations.** close About CloudKeeper CloudKeeper is a cloud cost optimization partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & usage optimization platform to reduce cloud costs & help maximize the value from the cloud. We have helped **400+ global companies** save an average of **20% on their cloud bills** , all while maintaining flexibility and avoiding any long-term commitments or costs. We have expertise across leading cloud platforms * * close close Are you tired of traditional AWS Well-Architected Reviews (AWS WAR)? Lengthy questionnaires, generic suggestions, and unclear action plans can leave you with even more questions than answers, at the cost of your time, money & resources. Traditional AWS WARs often rely on a generic approach, failing to consider your company’s specific objectives and maturity level. CloudKeeper **exclusively offers a smarter approach to AWS Well-Architected Reviews,** that is tailored to the unique capabilities and maturity level of each organization. Here is why our AWS WAR stands out: An in-depth & automated architectural review Custom recommendations for your cloud environment Structured roadmap with short, medium & long-term strategies Our Proven Capabilities as an AWS WAR Partner An AWS Premier partner with 15+ years of cloud expertise, CloudKeeper stands out as one of the most experienced AWS WAR Partners. * Top 5 Ranked among the AWS Well-Architected Partners * 500+ AWS Well-Architected Reviews completed * 150+ Certified Solutions Architects & Cloud Experts * APN Awarded AWS Partner Network Certification Distinction See the Clear Advantage: CloudKeeper AWS WAR vs. Traditional AWS WAR **Aspect** Approach Audit Method Recommendations Action Plan Implementation Efficiency Results **Traditional AWS WAR** One-size-fits-all Lengthy questionnaire-based Generic & standard for organizations of all sizes Basic feedback No support Time-consuming and resource-intensive Uncertain **CloudKeeper AWS WAR** Tailored to your organization's maturity and capabilities Automated assessment Customized based on your capabilities, challenges, and goals Clear, prioritized action plans with short, medium, and long-term strategy Proactive engagement until cloud efficiency is achieved Streamlined and automated, saving you valuable time (and money) Proven track record of significant savings & infrastructure optimization How do we perform the AWS Well-Architected Reviews? The AWS-Certified Experts from CloudKeeper perform a comprehensive review of your infrastructure using a structured approach. * Step 1 Initial Assessment to Understand the Current State * Step 2 Workload Identification * Step 3 An In-depth & Automated Architectural Review * Step 4 Identification of Potential Risks & Opportunities * Step 5 A Personalized Roadmap for Improvement * Step 6 End-to-end Implementation Support Beyond Basic Assessment: A 90-Day Cloud Transformation Plan Our deliverables go beyond basic assessment & recommendation. We become your partner in implementing actionable strategies that ensure optimization across all facets of your cloud infrastructure. * Identify critical issues & challenges * Tracking & remediation of top pain points * Adoption & integration of new AWS services * Expert consulting for overall cloud optimization * Proactive outreach for cost optimization * Human-assisted cost anomaly detection * Custom monthly cost analysis reports ## **No costs involved.** Completely funded by CloudKeeper! The AWS Well-Architected Reviews are entirely free. Why, you may ask? AWS WAR helps showcase our capabilities and the guaranteed cloud savings we can deliver. And most organizations end up choosing us as their long-term cloud cost optimization partner. We would love to have you onboard as well! AWS WAR Success Story Prodigal reduces monthly AWS costs by 25% Within a week of partnering with CloudKeeper, Prodigal reduced their monthly AWS bill by 25% and resolved many operational issues through AWS Well-Architected Review & Implementation. We are on An Overview of AWS Well-Architected Review (AWS WAR) AWS Well-Architected Reviews benchmark your infrastructure against best practices and design principles, crafted by AWS experts. These reviews focus on the following pillars: Operation Excellence Defining operational standards , monitoring workloads, and enabling continuous improvement. Security Protecting data, controlling access, and managing security events. Reliability Addressing resource availability , disaster recovery, and managing service disruptions. Performance Efficiency Streamlining resource selection , rightsizing, and performance monitoring. Cost Optimization Tracking cloud costs, eliminating waste, and optimizing spend while the business scales. Sustainability Designing the cloud architecture for environmentally conscious resource management. Our AWS WAR Customers **Related Resources** * Understanding AWS Well-Architected Review: Your Ultimate Guide Learn in-depth about AWS Well-Architected Review(AWS WAR) with this definitive guide covering everything you need for comprehensive understanding & implementation. Blog * Cloud infrastructure done right with the AWS Well-Architected Framework A walkthrough of the six pillars of AWS Well Architected Framework, the design principles of the pillars and the best practices for benchmarking against them. Whitepapers * Unlocking Cost benefits in the AWS ecosystem Shifting to AWS cloud allows businesses to scale, while reducing their overall costs. Learn how to unlock the true cost benefits for your AWS infrastructure. Whitepapers Frequently Asked **Questions** * ### Arrow 1.What is an AWS Well-Architected Framework? Q1. What is an AWS Well-Architected Framework? AWS Well-Architected Framework is a set of best practices and guidelines designed to help organizations build secure, high-performing, resilient, and efficient applications on AWS. It provides a structured approach to assess and improve architectures across six key areas, known as pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability. * ### Arrow 2.What is an AWS Well-Architected Review(AWS WAR)? Q2. What is an AWS Well-Architected Review(AWS WAR)? The AWS Well-Architected Review is a systematic assessment based on the AWS Well-Architected Framework. This review helps organizations evaluate their workloads against AWS best practices across six key pillars. The process identifies areas for improvement to enhance the overall architecture, leading to more resilient, secure, and cost-effective solutions​. * ### Arrow 3.How does CloudKeeper AWS WAR differ from traditional AWS WAR? Q3. How does CloudKeeper AWS WAR differ from traditional AWS WAR? As an AWS Certified Well-Architected Partner, CloudKeeper recognizes that every cloud environment has its unique challenges. We understand that no two organizations have the same level of maturity or capabilities. CloudKeeper, offers a smarter approach and a more customized approach to AWS Well-Architected Reviews, addressing challenges such as lengthy questionnaires, generic suggestions, & unclear action plans. Learn more about it * ### Arrow 4.Who should use the AWS Well-Architected Framework? Q4. Who should use the AWS Well-Architected Framework? The AWS Well-Architected Framework is a valuable resource for anyone involved in the design and operation of cloud systems on AWS. This includes professionals like: * Chief Technology Officers (CTOs) * Cloud Architects * Developers * Operations Team Members * ### Arrow 5.What is the AWS well-architected review process? Q5. What is the AWS well-architected review process? AWS suggests a three-phase approach towards the whole AWS Well-Architected Review Process - Prepare, Review, and Improve - which involves thorough preparation for the review, analyzing the current architecture, identifying various risks, and implementing resolutions as per priority. **CloudKeeper follows a six-step AWS well-architected review process. Before diving into the AWS Well-Architected Review we conduct thorough consultations** to understand your unique infrastructure and its gaps, your capabilities, and your desired outcomes from the review. **Pre-WAR Essential:** A 90-minute detailed discussion for a deep understanding of your infrastructure and goals. **Post-WAR Essential:** A 90-minute detailed discussion to finalize actionable recommendations based on your maturity level. * Step 1: Initial Assessment to Understand the Current State * Step 2: Workload Identification * Step 3: An In-depth & Automated Architectural Review * Step 4: Identification of Potential Risks & Opportunities * Step 5: A Personalized Roadmap for Improvement * Step 6: End-to-end Implementation Support * ### Arrow 6.Who should participate in an AWS Well-Architected Review? Q6. Who should participate in an AWS Well-Architected Review? Ideally, a cross-functional team should be involved, including cloud architects, security experts, developers, and key stakeholders from business and financial teams. This ensures that the review comprehensively covers both technical and business objectives​. * ### Arrow 7.What are the costs associated with an AWS Well-Architected Review? Q7. What are the costs associated with an AWS Well-Architected Review? While the AWS Well-Architected Tool itself is free, working with a certified AWS Well-Architected partner may involve costs. However, CloudKeeper offers a zero-cost AWS Well-Architected Review. * ### Arrow 8.How often should I conduct an AWS Well-Architected Review? Q8. How often should I conduct an AWS Well-Architected Review? There isn’t a single answer for how often you should do an AWS Well-Architected Review—it depends on your specific situation. AWS recommends conducting a Well-Architected Review periodically, especially after major updates or changes in your workloads. It’s beneficial to review before significant events, like new product launches or expanding operations, to ensure infrastructure readiness.​ **Here are some cases where more frequent reviews make sense:** * Frequent Changes: If your AWS environment changes a lot with new features or updates, regular reviews help you keep things optimized and secure. * Focused Improvements: If you're especially concerned about one area, like security or cost, reviewing that pillar more often can help address it better. * Major Events or Milestones: Big events, like launching a new application or moving from test to production, are great times for a review. For stable, well-organized environments, you may not need reviews as frequently. Look at how critical your workloads are, how developed your cloud setup is, and your company’s goals to decide the best review schedule for your needs. * ### Arrow 9.How can CloudKeeper help implement the AWS Well-Architected Review findings? Q9. How can CloudKeeper help implement the AWS Well-Architected Review findings? The customized AWS Well-Architected Review by CloudKeeper provides a precise action plan detailing exactly what needs to be done in the next 30, 60, and 90 days. It’s like having a GPS for your cloud journey. Our action plan not only tackles current challenges but also prepares you for ongoing growth and adaptation. CloudKeeper also offers comprehensive support throughout your cloud optimization journey, ensuring that recommendations are implemented correctly and effectively. Our dedicated team of certified experts are with you every step of the way until you achieve cloud efficiency. * ### Arrow 10.Who is an AWS Well-Architected Partner? Q10. Who is an AWS Well-Architected Partner? An AWS Well-Architected Partner is a certified consulting partner recognized by AWS for their expertise in implementing the AWS Well-Architected Framework. These partners have the skills, expertise, and resources to conduct AWS Well-Architected Reviews, helping organizations assess and improve their cloud environments based on best practices across all the key pillars. An AWS Premier Partner, with 15+ years of cloud expertise, CloudKeeper stands out as one of the most experienced AWS Well-Architected Partners. CloudKeeper was ranked in the * ### Arrow 11.How to choose the right AWS Well-Architected Partner? Q11. How to choose the right AWS Well-Architected Partner? Ensure your AWS Well-Architected Partner checks yes to the below questions. * Do they take the time to understand current state & company specifics(needs, challenges, desired outcomes, maturity level)? * Is their process simple, efficient, and streamlined? * Are their recommendations customized to your needs? * Do they provide a clear action plan on how to improve your infra? * Will they guide you on the implementation of the action plan? * Are they certified AWS Well-Architected Partners and have enough experience? * ### Arrow 12.What are the 6 pillars of AWS well-architected review? Q12. What are the 6 pillars of AWS well-architected review? The AWS well-architected review is conducted across 6 pillars: * Operational Excellence * Security * Reliability * Performance Efficiency * Cost Optimization * Sustainability * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close ## Overview CloudKeeper is a leading cloud cost optimization company working with 400+ businesses around the world. As a part of our continued efforts to ensure safe and seamless use of our products and platforms with no exposure to threats, we are inviting security professionals from around the world to test and report any vulnerabilities on our website or products (in scope) and to be a part of our exclusive White-Hat Hall Of Fame. Terms of Engagement CloudKeeper is committed to working with security researchers to verify and address potential vulnerabilities that are reported to us. Irrespective of the severity of the vulnerability, we would be happy to put your name in our Hall Of Fame. We thank all security researchers who are helping us to improve our overall security. ### A submission will qualify for the Hall Of Fame if it includes: * Description of the vulnerability * Steps for reproducing the vulnerability. If we cannot reliably reproduce the issue, we cannot fix it * Impact of the vulnerability with an exploit scenario * Proof of concept (Explain what you have achieved to do. No Attachment needed) In Scope & Out of Scope Targets All parts of our website (https://www.cloudkeeper.com/) available to customers/guests are in scope and are our primary interest. CloudKeeper uses a number of third-party providers and services. Our disclosure program does not give you permission to perform security testing on their systems. Vulnerabilities in third-party systems will be assessed on a case-by-case basis. Not Applicable Vulnerabilities Please refrain from sending us a report on the below issues. Even if they are reproducible, we consider them as informational and not a security vulnerability. * Presence of banner or version information * OPTIONS / TRACE HTTP method enabled * “Advisory” or “Informational” reports such as user enumeration * Vulnerabilities requiring physical access to a system * Missing CAPTCHAs * Default web server pages * Brute-force attacks * Content injection * Hyperlink injection in emails * Missing SPF/DMARC records Content Spoofing * Issues relating to password policy Full-path disclosure * Version number information disclosure * XML.RPC being accessible publicly (Or enumeration using XML.RPC) * CSRF-able actions that do not require authentication (or a session) to exploit * Issues on 3rd-party subdomains/domains of services we use. Please report those issues to the appropriate service. * Reports related to the security-related headers: Strict Transport Security (HSTS) – XSS mitigation headers (X-Content-Type and X-XSS-Protection) – X-Content- Type-Options – Content Security Policy (CSP) settings (excluding nosniff in an exploitable scenario) * Click-jacking (without a valid exploit) * DOS vulnerabilities * Any theoretical issue, which does not seem to be exploitable Let’s work towards a safer internet, one page at a time! * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Are your workloads in Azure infrastructure delivering maximum value? If you are uncertain, Azure Well-Architected Review will help you analyze if your Azure cloud is well-optimized or not and identify the improvement areas and optimization opportunities. Why should you prioritize an Azure Well-Architected Review? Once you've transitioned to the cloud, ensuring a steady ROI from your infrastructure is extremely essential for long-term success and sustainability. To achieve this, it's important to follow the guiding principles and best practices outlined by the Microsoft Azure Well-Architected review framework, structured around five key pillars: * Reliability Ensuring consistent uptime and minimizing downtime risks even in the face of disruptions. * Security Implementing robust measures to safeguard your data and infrastructure. * Cost Optimization Adopting a cost-efficient mindset to optimize cloud spend and resources for maximum value. * Performance Efficiency Enhancing responsiveness and scalability to deliver seamless user experiences. * Operational Excellence Improving workload quality through standardized workflows and team cohesion. Why CloudKeeper for Azure Well-Architected Review? A Microsoft Certified Solution Provider, **with 15+** Years of cloud expertise, CloudKeeper stands out as one of the most experienced Azure Well Architected Review Partners. How do we perform the Azure Well-Architected Reviews? The Azure-Certified Experts from CloudKeeper perform a comprehensive review of your infrastructure using a structured approach. * Initial Assessment We begin by understanding the state of your current cloud environment. This includes discussing your needs, challenges, and desired outcomes for the Azure Well-Architected Review. * Workload Identification Building upon the insights gathered, we proceed to identify the workload within your Azure environment. This could be a single application, a group of related applications, or your entire cloud infrastructure. * An In-depth Architectural Review Our certified Azure experts will then perform a comprehensive review of your chosen workload(s) against the five pillars of the Azure Well-Architected Review framework. * Identification of Potential Risks & Opportunities Based on our thorough examination, we identify strengths, weaknesses, areas for improvement, and opportunities, laying the groundwork for optimization and enhancement. * A Personalized Roadmap for Improvement We share a detailed report outlining our findings and most importantly, a clear roadmap for improvement. This customized roadmap will include recommendations, actionable steps, and strategies. **No costs involved**. Completely funded by CloudKeeper! The Azure Well-Architected Reviews are entirely free. Why, you may ask? These reviews help showcase our capabilities and the guaranteed cloud savings we can deliver. Most organizations end up choosing us as their long-term cloud cost optimization partner. We would love to have you onboard as well! Ready for a health checkup of your Azure cloud? Throughout the Azure Well-Architected Review process, we remain transparent, keeping you informed and involved every step of the way. We would love to provide Our Azure WAR Customers **Related Resources** * A Comprehensive Guide to Azure Cost Optimization Master Azure cost optimization with strategies and best practices. Control spending, maximize value, and ensure long-term success in the cloud. Blog * Navigating the FinOps Landscape: A Comprehensive Market Analysis Future-proof your cloud FinOps strategy by understanding global statistics, market demands, and key FinOps trends, with this whitepaper based on a survey by Everest Group. Whitepapers * Understanding AWS Well-Architected Review: Your Ultimate Guide Learn in-depth about AWS Well-Architected Review(AWS WAR) with this definitive guide covering everything you need for comprehensive understanding & implementation. Blog Frequently Asked **Questions** * ### Arrow 1.What is Azure Well-Architected Framework? Q1. What is Azure Well-Architected Framework? Azure Well-Architected Framework is a design framework comprising a set of best practices, guides, and tools provided by Microsoft Azure to help you build and maintain high-quality workloads in the Azure cloud platform. The Azure Well-Architected Framework focuses on five key pillars: Reliability, Security, Cost Optimization, Performance Efficiency, and Operational Excellence. * ### Arrow 2.What is Azure Well-Architected Review? Q2. What is Azure Well-Architected Review? An Azure Well-Architected Review is a comprehensive assessment of your Azure cloud environment, designed to identify areas for improvement and ensure your business is built on the best architectural principles. Think of it as a health checkup for your cloud infrastructure, conducted by certified experts. * ### Arrow 3.What should be the frequency of Azure Well-Architected Reviews? Q3. What should be the frequency of Azure Well-Architected Reviews? There's no single ‘one-size-fits-all’ answer to the frequency of Azure Well-Architected Reviews. The frequency of Azure Well-Architected Reviews can vary depending on several factors such as the rate of change in your Azure environment, the criticality of your workloads, the maturity stage of your cloud, and your organization's goals and objectives. Evaluate your specific circumstances and adjust the frequency accordingly. * ### Arrow 4.How much does an Azure Well-Architected Review cost? Q4. How much does an Azure Well-Architected Review cost? The cost of an Azure Well-Architected Review can vary depending on multiple factors. This includes the scope of your review, the complexity of the Azure cloud environment, the Azure Well-Architected Review Partner you engage with, and other additional services offered. To get an accurate cost estimate for an Azure Well-Architected Review, reach out to Azure-certified consulting partners. **CloudKeeper offers a zero-cost Azure Well-Architected Review.** * ### Arrow 5.What happens after the Azure Well-Architected Review by CloudKeeper is complete? Q5. What happens after the Azure Well-Architected Review by CloudKeeper is complete? CloudKeeper will provide you with a detailed report outlining the findings, including: * Identified strengths and weaknesses of your Azure environment. * Specific recommendations for improvement. * A customized roadmap with actionable steps for optimization. * ### Arrow 6.How can CloudKeeper help implement the Azure Well-Architected Review findings? Q6. How can CloudKeeper help implement the Azure Well-Architected Review findings? CloudKeeper offers end-to-end * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close 400+ success stories, yours could be next! Explore how we add value to your cloud journey and simplify cloud cost optimization. * $100+ million Cloud Cost Savings delivered * 20% Average Cost Reduction * 15+ Years of experience in cloud * * Select Featured Case Studies Featured Case Studies * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * How Fundamento improved AI reliability, GKE stability & cloud efficiency * How ZenduIT improved cloud visibility, storage governance & monthly cost savings * How Nanonets gained full FinOps visibility & reduced GCP costs with CloudKeeper Our Customers from different Geographies Industries PE/VCs * SaaS & ISVs eCommerce & Consumer Portals Financial Services Education Healthcare Media & Entertainment * * USA Canada India Australia SEA Europe * SaaS & ISVs eCommerce & Consumer Portals Financial Services Education Healthcare Media & Entertainment * * USA Canada India Australia SEA Europe * SaaS & ISVs eCommerce & Consumer Portals Financial Services Education Healthcare Media & Entertainment ‹› Customer Voices: How CloudKeeper makes a difference **Provided detailed information about the spending and helped us identify the bottlenecks** of unused resources. Also, it gives us a fair idea about the projection for the upcoming month's bill. SURENDRA REDDY C V DevOps Tech Lead **Cloudkeeper Lens gives excellent visibility on cost usage** and **360-degree view** of our cloud spend Verified G2 Review CloudKeeper offers a detailed view of historical spending. This allows us to track costs on a day-to-day or week-to-week basis. **This level of visibility is very helpful in identifying potential cost-saving. opportunities** Verified G2 Review * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Scans.AI optimized EKS performance and reduced AWS costs Industry: AI & Automation Headquarters: Johannesburg, South Africa Founded in: 2019 Company Size: 51–200 employees Featured Tags: Overview Scans.AI is an AI-native platform that helps insurers, fleets, and automotive businesses turn complex inspections and claims into fast, reliable, data-driven decisions. It uses advanced automation and intelligent orchestration to simplify high-volume workflows. Powered by cutting-edge AI, Scan.AI delivers 98%+ accuracy in damage detection and enables up to 15% savings per claim. The platform provides real-time orchestration across claims, inspections, and repairs for enterprises operating across Africa, India, and other global markets. Challenges As Scans.AI’s AI/ML workloads scaled on Amazon EKS, underlying platform inefficiencies began impacting performance, cost, and development velocity: * Escalating AWS costs driven by EKS clusters running on outdated Kubernetes versions and incurring Extended Support Charges. * Blocked EKS upgrades due to severe version skew across the control plane, kubelet, and critical add-ons. * Excessive GPU startup latency, with inference and training workloads taking 15–20 minutes to initialize. * Networking instability when enabling modern EKS features like Prefix Delegation, resulting in IP allocation failures. * Slowed experimentation cycles, turning rapid AI iteration into long, inefficient development loops. Scans.AI needed a structured, engineering-led approach to remove technical debt, restore performance, and regain cost efficiency across their EKS platform. The Solution ## Solution: CloudKeeper partnered closely with Scans.AI’s engineering teams to deliver a phased EKS optimization and alignment strategy focused on stability first, followed by performance and efficiency gains. Phase 1: EKS Diagnosis and Upgrade Enablement * Conducted deep diagnostics to identify Kubernetes version skew across the control plane, self-managed node groups, kubelet, and kube-proxy. * Designed and executed a safe, stepwise upgrade path involving controlled downgrades, node rotations, and add-on alignment. * Successfully upgraded EKS clusters from Kubernetes 1.29 to 1.32, restoring upgrade hygiene and eliminating Extended Support risk. Phase 2: Performance and Networking Optimization * Identified subnet fragmentation as the root cause of Prefix Delegation failures. * Guided migration of node groups to clean subnets to enable stable IP allocation and higher pod density. * Realigned GPU node groups post-upgrade, resolving long-standing startup latency issues through EKS and GPU best practices. This approach removed platform bottlenecks while unlocking both performance and cost improvements. ## Impact CloudKeeper’s engagement delivered measurable performance, cost, and platform stability improvements across Scans.AI’s EKS environment. | Metrics | Outcomes | | --- | --- | | GPU Workload Startup Time | Optimized from 15–20 minutes to ~1 minute, delivering a 93% reduction in startup latency. | | EKS Upgrade Readiness | Resolved critical version skew and upgraded clusters to Kubernetes 1.32, restoring upgrade hygiene and reducing operational risk. | | AWS Support Costs | Eliminated Extended Support Charges by aligning clusters with supported Kubernetes versions. | | Pod Density & Networking | Enabled Prefix Delegation through subnet realignment, improving IP allocation stability and node utilization. | With CloudKeeper, Scans.AI achieved: Dramatically faster GPU workload startup and AI experimentation cycles Fully unblocked and future-ready EKS upgrade posture Elimination of unnecessary AWS Extended Support costs Stable, high-density networking through functional Prefix Delegation A clean, maintainable Kubernetes foundation built for scalable AI growth ## Conclusion Scans.AI’s partnership with CloudKeeper transformed their EKS platform from a constrained, high-cost environment into a stable, high-performance foundation for AI innovation. By resolving Kubernetes misalignment, eliminating networking constraints, and restoring upgrade hygiene, CloudKeeper enabled Scan.AI to move faster without compromising reliability or cost control. With predictable infrastructure performance, reduced latency, and improved cost efficiency, Scan.AI is now well-positioned to confidently and sustainably scale its AI workloads. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Fundamento improved AI reliability, GKE stability & cloud efficiency * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How **Bidgely** Unlocked Cloud Savings with CloudKeeper Tuner Industry: Energy Analytics & AI SaaS Headquarters: Mountain View, California Founded in: 2011 Company Size: 51-200 employees Featured Tags: Overview Bidgely, a global leader in AI-powered energy intelligence, runs complex and data-heavy workloads on AWS. Challenges With cloud usage spread across over 20 AWS accounts and critical services like EC2, ASG, RDS, and Redshift, the team faced challenges in: Gaining unified visibility into cloud inefficiencies Identifying unused or underutilized resources at scale Establishing a consistent cost optimization process Reducing manual analysis and guesswork in cloud decisions The Solution ## Solution: **CloudKeeper Tuner** After onboarding, Bidgely immediately unlocked tangible insights and savings opportunities. ~4% monthly recurring savings ~8% EC2 savings by clean-up & right-sizing 100% adoption of browser extension within the SRE team Infra optimization delivered with minimal engineering effort These early results highlight CloudKeeper Tuner’s ability to deliver value **even with partial onboarding** - reinforcing its effectiveness at scale. Values Delivered Description ## Future Roadmap: Automation with CloudKeeper Scheduler Based on current usage trends, **CloudKeeper Tuner’s Scheduler module** is projected to deliver an additional 10–12% in savings across EC2, ASG, RDS, and Redshift services. This roadmap supports Bidgely’s broader objective of **cost optimisation with minimal manual effort** , while maintaining high performance standards. EC2 & ASG Description Instance & scale-in scheduling during non-peak hours RDS Description Stop/start automation for dev/test environments Redshift Description Optimizing inactive clusters and query-based scheduling Key Benefits Delivered Automated identification of infra optimization opportunities Simplified visibility and governance of under-utilized resources Additional 10-12% of savings through dynamic provisioning Infrastructure modernization with zero to low effort CloudKeeper Tuner has become an essential part of our cloud operations—like an extension of AWS itself. It delivers real-time, actionable recommendations right inside our console, saving us time and effort. Month after month, we're discovering new ways to improve our setup and reduce costs. We're steadily progressing toward our savings goals, thanks to a combination of a powerful product and a proactive support team that keeps pushing improvement opportunities Sunny Chhatija DevOps Manager Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How CarDekho seamlessly migrated to AWS CloudFront and achieved huge cost savings with CloudKeeper Industry: Automobiles Headquarters: Jaipur, India Founded in: 2008 Company Size: 1000 - 5000 employees Featured Tags: About CarDekho CarDekho is India’s largest digital automotive solutions provider that supports customers throughout their car purchase journey. With a footprint across 30+ countries, CarDekho has become the bridge between car buyers and all auto stakeholders including OEMs, dealers, sellers, as well as finance and insurance providers. Values delivered * Migrated 400+ domains to AWS CloudFront. * Zero downtime and no data loss. * Eliminated data transfer costs. * Enhanced performance and data security. * Facilitated seamless testing and deployment. Challenges Complex CDN Configuration CarDekho faced challenges with the complex configurations of Akamai CDN. They needed to migrate to AWS CloudFront to simplify content delivery operations, streamline management, and reduce the operational complexities. Complex Configuration Management The migration required custom implementations for features like URL redirection and method blocking. Additionally, configuration mismatches between Akamai and CloudFront posed challenges in optimizing traffic management, security and system alignment. Large-Scale and Secure Migration Migrating over 400 domains from Akamai to AWS CloudFront presented a monumental task. They also needed enhanced security while also maintaining service continuity. Time and Resource Constraints To meet the contract timelines of CarDekho and Akamai, the migration had to be completed within a month, despite the challenge of limited skilled resources. Solution CarDekho leveraged our end-to-end cloud optimization services, capitalizing on CloudKeeper’s Through a combination of technical expertise and cutting-edge AWS tools, CarDekho achieved substantial cloud cost reductions and operational improvements. Seamless Migration Migrated over 400 domains across all of CarDekho's Business Units to AWS CloudFront for improved performance. Additionally, they achieved a substantial reduction in CDN-related costs due to the elimination of data transfer fees. Optimized Performance Employed Lambda@Edge and CloudFront Functions to handle complex business functionalities at the edge, improving processing efficiency and reducing load times, further enhancing user experience. Streamlined Configurations Established a dedicated staging distribution to mirror the production environment, ensuring seamless testing and validation. This setup helped overcome CloudFront's lack of versioning and HTTP/3 support in staging, ensuring a smooth transition for CarDekho. Proactive Security Mechanisms Implemented logging via AWS WAF and stored logs on Amazon S3, utilizing Amazon Athena for efficient log analysis. Additionally, set up Route 53 health checks and CloudFront alarms for continuous monitoring and proactive issue resolution for production domains and AWS Advanced Shield for additional DDoS protection. Uninterrupted Services Achieved seamless service with no disruptions for CarDekho’s users throughout the complex migration, with zero downtime and zero data loss. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How **CEAT** Optimized AWS Costs & Gained Cloud Visibility with CloudKeeper Tuner Industry: Manufacturing (Tyres) Headquarters: Mumbai, Maharashtra Founded in: 1958 Company Size: 5,001-10,000 employees Featured Tags: Overview CEAT is one of India’s leading automobile manufacturers, known for its focus on innovation, quality, and operational excellence. With a growing digital infrastructure on AWS, CEAT sought smarter ways to manage cloud spend and ensure every resource was delivering value. Challenges Despite having a well-managed AWS environment, CEAT faced: Idle resources silently adding to costs Limited visibility into certain underutilized services A need for quick, actionable insights without deep manual analysis They wanted a solution that could not only **highlight cost-saving opportunities** but also **expose blind spots** that might otherwise go unnoticed. The Solution ## Solution: **CloudKeeper Tuner** CEAT deployed **CloudKeeper Tuner** , an AI-powered cloud cost optimization platform. Idle NAT Gateway Detection: The Cleaner module identified NAT Gateways with zero data transfer activity. These were safe to remove, creating an immediate, risk-free saving opportunity. Blind Spot Identification: The platform uncovered areas of AWS usage that weren’t being actively monitored, giving CEAT complete visibility over their environment. Actionable Insights in Real Time: Instead of sifting through AWS data manually, CEAT’s DevOps team now receives precise recommendations that can be implemented instantly. Key Results **4.2% Potential AWS Savings:** achieved without affecting performance **Highest-impact Recommendation:** Remove idle NAT Gateways **Complete Visibility:** Eliminated blind spots in resource usage **Faster Decision-Making:** Real-time, actionable recommendations for cost optimization ## Conclusion With CloudKeeper Tuner, CEAT now runs a **leaner, more transparent AWS environment.** Unused resources are quickly identified and removed, blind spots are closed, and every dollar spent on cloud infrastructure is backed by clear, measurable value. CloudKeeper Tuner didn’t just help us find unused resources - it uncovered blind spots we weren’t even aware of. The recommendations were precise, easy to implement, and made immediate sense. Baskar Rajendran DBA Manager, CEAT Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Damstra reduced their entire AWS spends by 22%, working with CloudKeeper Industry: Enterprise Software Services Headquarters: Melbourne, Australia Founded in: 1998 Company Size: 51-200 employees Featured Tags: About DAMSTRA Damstra Technology is a global leader in enterprise protection software. They provide multiple SaaS offerings which include workforce management, access control, asset management, learning management, and HSE management solutions. Values delivered * Instant savings of 12% on entire AWS costs. * 10% cost reduction through architectural optimizations. * Enhanced cloud cost visibility & reporting. * Proactive anomaly detection & resolution Challenges Complex Workload Distribution They struggled with the intricate distribution of cloud workloads across multiple teams and geographical locations. This complexity hindered efficient resource management and cost optimization, posing operational challenges. Cost Deprioritization The engineering team at Damstra prioritized developing new features, moving cloud cost optimization slightly out of focus. This adversely affected financial efficiency and hindered the company’s efforts to optimize expenditure within their AWS infrastructure. Solution Damstra got onboard **12% of savings** on their entire AWS bills instantly. The solution helped them in optimizing their AWS Reservation Management. Damstra also saved an **additional 10%** on their cloud costs, by the following architectural optimizations - * Moving applications to latest generation instances * Network tuning to reduce data transfer * Architectural changes in load balancer setup Cost Analytics & Reporting With complementary access to Well-Architected Reviews Fine-tuned their cloud infrastructure based on the architectural guidelines of AWS for better performance, scalability and security. Anomaly Detection CloudKeeper enabled Damstra to efficiently detect and address any unusual spikes or dips in cloud spend. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How eLocal is leveraging CloudKeeper to adopt FinOps best practices & reduce their AWS cost by 25% Industry: Advertising Services Headquarters: Pennsylvania, USA Founded in: 2008 Company Size: 51-200 employees Featured Tags: About eLocal eLocal is a dynamic and seasoned marketing company that connects millions of local consumers to the businesses they need. Backed by Homeserve Group, the company has helped boost the revenue and retention rates of thousands of local, regional, and national businesses. They are completely hosted on AWS with a growing footprint due to acquisitions & organic growth. Values delivered * Immediate cloud savings of 10%. * Further cost reduction by 15% through architectural-level optimizations. * Efficient resource allocation and cost savings. * Comprehensive cloud cost visibility. Challenges Lack of Visibility eLocal had an extensive and complex AWS infrastructure distributed across multiple projects which hampered the overall cloud usage visibility. Right-sizing of Instances Due to a large number of AWS instances, they struggled to manage resource provisioning, creating performance bottlenecks and budgetary constraints. Manual RI/SP Management They managed AWS RIs and Savings Plans manually, which led to overcommitments, limited flexibility, and challenges with dynamic workloads. Cost Monitoring Challenges eLocal found it difficult to track and analyze cloud costs due to the complexity of their large AWS infrastructure, which was constantly being scaled up. Solution After eLocal was onboarded to our end-to-end AWS Cost Optimization solution Additionally, they could further reduce their AWS costs by 15%, with the help of architectural-level optimizations which included eliminating cloud waste, right-sizing resources, fine-tuning the system design, and further recommendations around the following services - * EC2 and RDS * Load Balancer * EBS volumes and S3 storage Better Cost Visibility CloudKeeper customers get complimentary access to Well-Architected Reviews CloudKeeper helped them align their cloud setup as per the design principles of AWS, backed by a team of AWS-certified cloud experts. Cost and Usage Anomaly Detection CloudKeeper helped them continuously monitor and address cost anomalies leading to more efficient resource allocation and cost savings. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Eshopbox enabled real-time service-level visibility into their cloud spends with CloudKeeper Lens Industry: Logistics and Supply Chain Headquarters: Gurgaon, India Founded in: 2012 Company Size: 51 - 200 employees Featured Tags: Overview Eshopbox is an e-commerce operations and fulfillment solutions provider that helps D2C brands streamline logistics, warehousing, and multi-channel order management. With a powerful software platform, smart warehouses, and trusted carrier integrations, Eshopbox enables brands to deliver faster, improve accuracy, and scale seamlessly across marketplaces with complete operational visibility. Values delivered * Cloud cost savings exceeding ₹1 million. * Service-level cost visibility with custom dashboards. * Usage optimization resolving cloud wastage. * Guided infrastructure modernization. * Structured support model with faster resolution. Challenges Eshopbox had a complex GCP setup with operations spanning high-scale inventory workflows powered by GCP services like GKE, Cloud SQL, App Engine, and BigQuery. They struggled to maintain precision and scalability while controlling cloud costs. Overprovisioned Infrastructure The dynamic scaling of Eshopbox’s GCP setup often resulted in resources being allocated beyond actual requirements. This overprovisioning inflated costs, created inefficiencies, and made it difficult for the team to strike the right balance between performance and budget. Unclear Usage Patterns Service-level consumption was difficult to interpret due to limited visibility and complex billing structures. Without clarity into usage trends, anomalies often went unnoticed, leading to cost spikes and making it harder to prioritize optimization initiatives effectively. Lack of Structured Support Eshopbox faced delayed resolutions and minimal accountability due to a lack of structured support processes. This not only created bottlenecks in addressing issues but also impacted their ability to respond quickly to business-critical needs. Budgeting Uncertainty Unpredictable workload spikes in ecommerce seasons created challenges in forecasting costs. Budget planning became unreliable, with unexpected bills disrupting financial control and making it difficult to allocate resources for growth initiatives with confidence. Solution Cost Governance Dashboards CloudKeeper implemented governance dashboards using GCP billing exports and CloudKeeper Lens - our Cloud Cost Visibility platform with resource-level insights. These delivered real-time spend visibility, improved accountability across teams, resolved cost anomalies and empowered Eshopbox to monitor resource usage and costs continuously, turning financial data into actionable insights. Integrated Monitoring CloudKeeper embedded monitoring tools into the support framework, enabling proactive anomaly detection and timely resolutions. This integration minimized service interruptions, streamlined troubleshooting, and ensured optimization opportunities were flagged and resolved before escalating into costly issues. Cost Optimization Framework A structured governance framework was established to align financial planning with business goals. This provided predictability in costs, streamlined tracking of anomalies, and offered a sustainable way to manage budgets without compromising scalability or performance. ## **Post-Optimization Impact** * Cloud costs reduced by over ₹1 million * Service-level visibility streamlined forecasting and planning * Cloud waste minimized by reducing overprovisioning * Support model improved resolution time and accountability * Infrastructure modernization completed without disruptions CloudKeeper enabled Eshopbox to balance scale, performance, and cost efficiency with improved visibility, optimized infrastructure and faster support frameworks. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How **FirstHive** Uncovers 9.8% Cloud Savings with CloudKeeper Tuner Industry: MarTech / Customer Data Platform Headquarters: Sunnyvale, California Founded in: 2019 Company Size: 51-200 employees Featured Tags: Overview FirstHive is a global Customer Data Platform (CDP) that enables brands to deliver hyper-personalized engagement at scale. As AWS usage grew, managing cloud costs while maintaining agility and performance became a top priority. To gain better control and long-term cost visibility, FirstHive adopted **CloudKeeper Tuner** Challenges Despite using AWS-native tools and internal monitoring, FirstHive encountered ongoing challenges: Fragmented visibility across multiple accounts Resources running longer than necessary, especially in test and dev environments Unclear financial impact of existing configurations Scattered insights that were hard to prioritize and act upon They required a centralized platform that delivered actionable insights with clarity and historical depth. The Solution ## Solution: **CloudKeeper Tuner** FirstHive onboarded 3 out of 4 AWS accounts onto CloudKeeper Tuner. The platform provided a single pane of glass across environments, uncovering long-standing optimization opportunities and driving deeper cost awareness. ### Impact | Metric | Value | | --- | --- | | Total Identified Savings | 7.3% of the AWS bill | | EC2 Optimization Contributions | 88% of total savings | | Aged Recommendations | From 60+ days to over a year | | Key Findings | **Dormant test setups, oversized instances, legacy configurations** | Recommendations included detailed reasoning, usage metrics, and risk indicators—making it easier for the team to take action without guesswork. Values Delivered Description # Future Roadmap: Automation with CloudKeeper Scheduler With a strong foundation established, FirstHive is exploring the activation of CloudKeeper Scheduler to further enhance savings through automation. Initial insights show clear opportunities across: * EC2 * Auto Scaling Groups (ASG) * ECS * RDS These services—especially in development and staging—exhibit patterns ideal for automated scheduling. Based on current usage trends, enabling Scheduler could drive an additional 10–12% in monthly savings, without manual effort or impact on performance. Outcome Points Description By using CloudKeeper Tuner, FirstHive was able to: Unlock nearly 10% in monthly cloud savings Identify long-standing cost drains across accounts Act with confidence through prioritized recommendations Plan for automation-led optimization Build a scalable and cost-aware cloud strategy ## Conclusion For a growth-focused company like FirstHive, CloudKeeper Tuner has become a strategic ally in cloud cost management. From uncovering long-overlooked savings to mapping a path for intelligent automation, the platform is powering a more cost-effective and agile cloud ecosystem. CloudKeeper Tuner is a very straightforward solution. Earlier, I used 2 to 3 different tools but now, the CloudKeeper Tuner is the one-stop solution for recommendations. I like the way it works. Sathiya Narayanan D Senior Manager- CloudOps, FirstHive Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Foundation AI re-architected and streamlined their Kubernetes environment with an upgrade to EKS v1.30 Industry: Gen AI Headquarters: Irvine, California Founded in: 2019 Company Size: 51 - 200 Employees Featured Tags: Overview Foundation AI is an AI-powered automation company helping enterprises streamline document-intensive workflows across legal, healthcare, and financial services. Their platform leverages machine learning and intelligent document processing to transform unstructured data into actionable insights. Values delivered * Eliminated recurring node failures and NotReady states. * Upgraded 10+ components including EKS add-ons and CSI drivers. * Saved 200+ man hours, enabling seamless upgrades. * Reduced EFS mount failures and pod crash loops. * Restored production stability and reliable infra operations. Challenges Recurring Production Outages Foundation AI faced ongoing disruptions with EKS v1.29, as nodes would frequently become unresponsive and enter a NotReady state, severely affecting business-critical workloads, including Apache Airflow DAGs. Container Runtime and Network Failures Container crashes triggered failures in the aws-node pod responsible for VPC networking, severing communication with the control plane and taking down entire nodes. Outdated CSI Drivers EFS mounts were failing due to an outdated aws-efs-csi-driver, and secrets store mounts failed due to incompatibility between the deployed Secrets Store CSI driver and Kubernetes v1.29’s VOLUME_MOUNT_GROUP enforcement. Add-on Drift and Inconsistent Configuration Kube-proxy and VPC-CNI plugins were misaligned, causing unpredictable behavior. Without uniform configuration management, the cluster became increasingly unstable. Opaque Custom AMIs Custom-built AMIs lacked transparency and versioning, making troubleshooting difficult and consistent patching nearly impossible. Solution To address the persistent instability and operational challenges in their Amazon EKS environment, Foundation AI partnered with **CloudKeeper** for a comprehensive Kubernetes stabilization initiative. Given the complexity of the cluster, an **in-place upgrade** to Amazon EKS v1.30 was chosen. Flawless In-Place EKS Upgrade With minimal disruption as a priority, CloudKeeper supported a zero-downtime control plane upgrade using synthetic probes and live traffic validation. New v1.30 node groups were custom-built to mirror existing taints, labels, and IAM roles. A drain-and-validate process was adopted, gradually decommissioning old nodes while continuously tracking logs using Fluent Bit and OpenSearch for anomalies. Despite the cluster’s deeply embedded dependencies, the upgrade was executed seamlessly. Resolved Node and Network Failures The team upgraded essential EKS components including container runtime, VPC-CNI, kube-proxy, and CoreDNS. Additionally, AWS’s node auto-repair agent was deployed to enhance node self-healing. These upgrades eliminated frequent containerd crashes and fixed the underlying issues causing node disconnections and NotReady states. Upgraded CSI Drivers and Secured Secrets Management Outdated storage and secret drivers were a major source of instability. With specialist guidance from CloudKeeper, Foundation AI team upgraded: * The aws-efs-csi-driver to fix failed volume attachments and EFS socket errors * The secrets-store-csi-driver to align with Kubernetes v1.29’s volume mount requirements. These updates stabilized secret injection and resolved crash loops, ensuring Airflow and other workloads ran smoothly. Improved Observability and Resilience Backed by deep expertise in container orchestration and telemetry, Team CloudKeeper supported the enablement of end-to-end observability using Datadog, CloudWatch alarms, and Route 53 health checks. The EKS Log Collector was deployed to collect diagnostic data, while memory settings were fine-tuned to reduce OOMKill incidents—boosting workload resilience and uptime. ## Post-Upgrade Impact The EKS upgrade restored production stability and confidence across the board. * Airflow DAGs executed without misfires * EFS volumes mounted without delay * Secrets were injected reliably on first attempt Most importantly, the Foundation AI team transitioned from constant firefighting to operating with trust, predictability, and peace of mind in their infrastructure. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Foundation AI optimized Amazon RDS for performance & cost efficiency Industry: Gen AI Headquarters: Irvine, California Founded in: 2019 Company Size: 51 - 200 employees Featured Tags: Overview Foundation AI is an AI-powered automation company helping enterprises streamline document-intensive workflows across legal, healthcare, and financial services. Their platform leverages machine learning and intelligent document processing to transform unstructured data into actionable insights. As a cloud-native company, it relies heavily on AWS services such as Amazon RDS to deliver secure, resilient, and high-performance platforms to its customers. Challenges Foundation AI's mission-critical workloads depend on Amazon RDS for reliable database performance. However, the company’s engineering teams faced recurring challenges in managing production databases effectively. High memory utilization across RDS instances Suboptimal database configurations impacting reliability Cost inefficiencies due to misconfigured instances Performance bottlenecks affecting application responsiveness Instability during peak workloads leading to operational risks Increased risk of downtime and poor customer experience These challenges created unnecessary incidents, reduced customer confidence, and hindered scalability. The Solution ## Solution: **Partner-led Support** Foundation AI partnered with CloudKeeper leveraging the Partner-led Support service to optimize database performance, addressing RDS stability and performance issues. The following measures were taken: Performance Analysis & Monitoring Used **AWS CloudWatch** and custom instrumentation to monitor query patterns, memory consumption, and performance bottlenecks. Database Tuning & Parameter Optimization Adjusted critical database parameters to improve query execution efficiency. Enhanced resource allocation strategies were designed to ensure optimal memory utilization. Instance Right-Sizing & Cost Optimization Recommended and implemented right-sized RDS instances aligned with workload requirements. This reduced the risk of over-provisioning while lowering unnecessary costs. Values Delivered Description # Post Optimization Impact Proactive RDS optimization not only stabilized Foundation.ai’s core infrastructure but also delivered measurable improvements across performance, reliability, and cost efficiency. By addressing configuration gaps, eliminating bottlenecks, and right-sizing resources, the system is now better equipped to maintain consistent performance and offer a more reliable customer experience. Improved Stability Description RDS performance bottlenecks were eliminated, ensuring consistent uptime. Optimized Performance Description Memory utilization dropped substantially, resulting in faster query execution and better customer experience. Reduced Risk Description Prevented downtime and stabilized production workloads. Cost Efficiency Description Achieved savings through smarter resource allocation and right-sizing. Better Customer Experience Description Faster application responsiveness and improved reliability boosted overall user satisfaction. ## Conclusion Through CloudKeeper’s **Partner-led Support** , Foundation AI transformed its Amazon RDS environment into a stable, high-performance, and cost-efficient backbone for its mission-critical workloads. With optimized configurations, improved governance, and proactive performance management, the company strengthened customer trust and operational resilience. By ensuring a faster, more reliable, and scalable database layer, Foundation AI is now better positioned to support its rapidly growing user base and continue delivering intelligent automation solutions with confidence. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Foundation AI scaled their remote workforce with Amazon WorkSpaces Industry: Gen AI Headquarters: Irvine, California Founded in: 2019 Company Size: 51 - 200 employees Featured Tags: Overview Foundation AI is an AI-powered automation company helping enterprises streamline document-intensive workflows across legal, healthcare, and financial services. Their platform leverages machine learning and intelligent document processing to transform unstructured data into actionable insights. To support its globally distributed teams, Foundation.ai required a secure, scalable, and compliant remote desktop infrastructure powered by AWS. Challenges To support its rapidly expanding remote workforce across the world, Foundation.ai required a secure, scalable, and compliant remote desktop infrastructure powered by AWS. They decided to deploy Amazon WorkSpaces but faced several challenges: Designing governance and access controls from scratch Enabling scalable provisioning without compromising security Establishing a secure and reliable end-to-end setup Ensuring alignment with strict enterprise compliance requirements Without a streamlined and secure setup, productivity and business continuity for remote teams were at risk. The Solution ## Solution: **Partner-led Support** Foundation AI leveraged our Partner-led Support service to deploy a secure, scalable, and fully governed Amazon WorkSpaces environment. The goal was to build a remote desktop ecosystem that supported global teams and enforce strict security and compliance controls. To achieve this, the following measures were taken: End-to-End WorkSpaces Deployment Designed and deployed a secure, managed WorkSpaces environment for distributed teams. Identity & Access Management Integration Integrated user directories for seamless identity and access management. Also ensured compliance with enterprise-grade security policies. Scalable & Policy-Driven Provisioning Implemented automated workflows for flexible provisioning of WorkSpaces. This allowed teams to scale quickly without manual overhead. Values Delivered Description # Post Optimization Impact Foundation.ai successfully established a secure, scalable, and compliant virtual desktop environment that enabled global collaboration while maintaining enterprise security standards. Secure Remote Access Description Employees could access corporate resources safely from any location. Unified Governance Description Centralized IAM and security policies minimized unauthorized access risks. Scalable Infrastructure Description On-demand WorkSpaces provisioning enabled rapid team expansion. Operational Resilience Description Remote workforce productivity and business continuity were consistently maintained. Improved Compliance Description The environment aligned with enterprise-grade security and regulatory requirements. ## Conclusion Foundation AI successfully built a secure, scalable, and compliant Amazon WorkSpaces environment that empowers its globally distributed workforce. By strengthening governance, automating provisioning, and implementing enterprise-grade security controls, the company eliminated operational risks while enabling seamless remote access and collaboration. This optimized Amazon WorkSpaces ecosystem now serves as a resilient foundation for Foundation AI continued growth - ensuring their teams can work securely, efficiently, and without interruption, no matter where they are in the world. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How FranConnect seamlessly upgraded MSK Clusters and strengthened AWS SQS expertise Industry: Enterprise SaaS Headquarters: Herndon, Virginia Founded in: 2000 Company Size: 201 - 500 employees Featured Tags: Overview FranConnect is a leading provider of franchise management solutions, trusted by brands worldwide to drive operational efficiency, accelerate growth, and improve governance. As a cloud-first organization, FranConnect relies heavily on AWS services to deliver a reliable, secure, and high-performing platform for its customers. Values delivered * Flawless upgrade to MSK v3.9 with zero downtime * Resolved recurring operational issues * Enhanced security, governance and compliance standards * Customized training workshops on Amazon SQS * Improved system scalability and reliability Challenges FranConnect’s reliance on Amazon SQS made it central to their messaging and workflow architecture. As the company scaled, several issues surfaced: Configuration Ambiguity Unclear SQS best practices caused frequent misconfigurations, performance bottlenecks, and recurring reliability concerns. These issues created operational inefficiencies and made enforcing consistent configuration hygiene increasingly difficult as the platform scaled. Troubleshooting Delays The absence of structured workflows and real-time diagnostics prolonged incident resolution, delaying delivery pipelines. This significantly reduced operational efficiency and affected the speed of product releases across teams. High Dependency on External Support Routine SQS issues often required escalation to external support, slowing resolution times and driving up operational costs. This reliance limited engineering self-sufficiency and distracted teams from innovation-focused initiatives. Frequent Operational Issues Repetitive SQS-related incidents frequently disrupted workflows and drained engineering capacity. The recurring firefighting reduced productivity, increased costs, and impacted morale by keeping teams away from core business priorities. Mission-Critical MSK Upgrade Upgrading to MSK 3.9 was essential for platform resilience but carried risks of downtime, replication errors, and instability. A carefully planned, risk-mitigated migration strategy was required to avoid disruption. Solution CloudKeeper team implemented a multi-faceted approach focusing on targeted training, a critical infrastructure upgrade, and enhanced security governance. The was designed to resolve immediate issues while building long-term resilience. AWS SQS Training Program A tailored training program for 50 engineers focused on best practices, real-world troubleshooting, and interactive sessions. This initiative empowered teams with the expertise to operate SQS confidently and independently. Flawless MSK Upgrade Through impact assessments, rollback planning, replication fine-tuning, and proactive error resolution, Franconnect successfully executed the MSK 3.9 migration. The process delivered zero downtime and no post-upgrade incidents. Security and Governance Enhancements Service Control Policies (SCPs) were implemented to prevent unauthorized changes, enforce compliance, and strengthen governance. These security measures improved operational resilience across Franconnect’s AWS environment. ## Post-Optimization Impact The collaboration empowered the client’s engineering teams with stronger self-sufficiency, stability, and security while eliminating recurring operational hurdles. * Zero SQS-related support tickets raised since the training. * Engineers now independently manage, optimize, and troubleshoot SQS. * Enhanced system scalability and reliability post the upgrade. * SCP implementation reduced misconfiguration risks. FranConnect’s leadership praised the effectiveness of the training and the flawless execution of upgrades. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Fundamento improved AI reliability, GKE stability & cloud efficiency Industry: Software Development Headquarters: San Francisco, California Founded in: 2020 Company Size: 11-50 Employees Featured Tags: Overview Fundamento is an AI and automation company delivering enterprise-grade voice, chat, and analytics solutions.Their platform powers conversational experiences using advanced speech processing, natural language understanding, and real-time analytics, helping enterprises build intelligent, scalable interactions across support, sales, and service channels. To improve AI reliability, stabilize GKE-to-Gemini operations, and build long-term FinOps maturity, Fundamento partnered with CloudKeeper to jointly enhance performance, visibility, and cost efficiency across their GCP ecosystem. Challenges With increasing AI workloads and platform complexity, Fundamento encountered several technical and operational blockers: * GKE → Gemini authentication failures affecting AI workflows. * Uncertainty around Gemini 2.0/2.5 Flash deployment in India, causing latency and rollout gaps. * Vertex AI MAX_TOKEN limits impacting chatbot and GenAI workloads. * RTP traffic failures in the production voice bot due to network issues. * FinOps workflows blocked by IAM and permission gaps They needed a scalable, insight-rich platform to improve reliability and visibility and a collaborative partner to help resolve these blockers quickly and effectively. The Solution ## Solution: **CloudKeeper Lens** CloudKeeper worked closely with Fundamento’s engineering, AI, and FinOps teams to deliver hands-on diagnostics, infrastructure fixes, and real-time visibility: Enabled Gemini 2.5 Flash with correct setup Fixed GKE–Gemini auth and optimized token usage Resolved RTP/SIP issues and corrected firewall/NAT configs Restored missing FinOps permissions Together, this helped Fundamento stabilize AI operations, streamline networking, and build a strong foundation for ongoing FinOps visibility and optimization. Values Delivered Description # Outcome With CloudKeeper, Fundamento achieved: Description Stable, low-latency Gemini 2.5 Flash deployment in India Description Fully restored GKE → Vertex AI authentication Description Reliable voice bot operations through corrected RTP/SIP networking Description End-to-end cost visibility via CloudKeeper Lens Description Higher operational efficiency with clear playbooks and continuous support ## Conclusion Fundamento’s partnership with CloudKeeper transformed their AI and cloud reliability from dealing with recurring authentication, networking, and token issues to operating a streamlined, well-governed, and insight-driven GCP environment. Through a combination of hands-on engineering support, cloud governance fixes, and real-time FinOps visibility, CloudKeeper enabled Fundamento to deliver smoother AI experiences, stronger platform stability, and predictable cloud operations. With enhanced reliability, improved cost governance, and continuous expert support, Fundamento is now positioned to scale its AI workloads with confidence and efficiency. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Helping a Global Energy Intelligence Platform resolve EKS logging issues Industry: Energy Intelligence / SaaS Headquarters: Mountain View, California Founded in: 2011 Company Size: 500+ Employees Featured Tags: Overview The customer is a global leader in AI-powered energy intelligence solutions, helping utilities and energy providers turn smart meter and IoT data into actionable insights. Their platform supports load disaggregation, energy efficiency, demand response, and customer engagement initiatives. Challenges The customer runs backend workloads on Amazon EKS. While spot instances optimized costs, operational and reliability issues began affecting platform stability and daily operations. * Pods frequently crashed due to application logs filling ephemeral storage and triggering disk pressure conditions. * Unexpected pod failures caused permanent log loss, creating auditability gaps and compliance risks. * Limited log visibility slowed incident investigation and increased recovery times during production issues. * Engineering teams spent excessive time firefighting failures, increasing operational overhead and impacting service reliability. The customer needed a scalable, fault-tolerant logging strategy that prevented storage-related crashes, ensured persistent logs, and required minimal or no application code changes. The Solution ## Solution: **Partner-led Support** CloudKeeper partnered with the customer’s engineering teams to design a resilient, low-touch logging architecture that improved platform stability, ensured log durability, and aligned with AWS best practices. Log Offloading via Sidecar Architecture * Implemented Fluent Bit sidecar containers in EKS pods to continuously stream logs independent of pod termination. * Enabled log synchronization at defined intervals without requiring application code changes. * Enforced log rotation policies to prevent ephemeral storage exhaustion and disk pressure issues. Centralized and Structured Log Storage * Offloaded logs to Amazon S3 using a structured, date- and application-based hierarchy. * Enabled clear segregation of logs by workload and time for improved governance. * Simplified log retrieval for audits, investigations, and operational troubleshooting. Stability and Reliability Improvements * Decoupled logging from the application lifecycle to ensure log persistence during unexpected pod failures. * Eliminated disk pressure–related crashes while aligning logging operations with AWS scalability and cost-efficiency best practices. This solution established a stable, scalable logging foundation, reducing operational risk and enabling engineering teams to focus on reliability, performance improvements, and delivering consistent experiences. Values Delivered Description # Post Optimization Impact Description Zero Disk Pressure Failures - Pod crashes due to disk pressure were fully resolved. Description Reliable Log Retention - Logs remained consistently available for audit, even in cases of abrupt pod termination. Description Operational Efficiency - DevOps teams reclaimed time from manual firefighting, redirecting efforts toward innovation Description Improved Customer Experience - Stable backend services significantly reduced disruption and enhanced reliability. ## Conclusion CloudKeeper helped the customer resolve their logging and storage constraints by decoupling log management from pod lifecycles and eliminating storage pressure. The resulting architecture improved fault tolerance and observability, and reduced operational noise across production workloads. With a stable, scalable logging foundation, the customer now operates and scales Kubernetes workloads with greater reliability, control, and confidence. Other Success Stories * Containing an AWS account breach and restoring stability within hours * How Scans.AI optimized EKS performance and reduced AWS costs * How Fundamento improved AI reliability, GKE stability & cloud efficiency * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # Containing an AWS account breach and restoring stability within hours Industry: Food & Beverage Headquarters: Bangalore, Karnataka Founded in: 2014 Company Size: 500+ Employees Featured Tags: Overview The customer is a leading Indian food-tech platform focused on delivering freshly prepared, globally inspired meals. Running production workloads on Amazon Web Services, their infrastructure was built for rapid product development and high-growth operations. However, as the platform scaled, security monitoring and incident response capabilities did not evolve at the same pace. Operating without a defined response framework or proactive alerting, the team lacked the visibility and control required to manage active security threats. Challenges When suspicious activity emerged, the team faced an active account compromise with limited visibility and response mechanisms: * Unauthorized infrastructure provisioning across multiple AWS regions in real time * Rapidly escalating cloud costs due to malicious resource creation * No visibility into access points, affected services, or blast radius * Lack of centralized logging and tooling to investigate account activity * Limited escalation support due to absence of AWS Premium Support Immediate containment and investigation were critical to prevent further impact. The Solution ## Solution: **Partner-led Support** As part of the Partner-led Support program, the Cloud Reliability Engineering team from CloudKeeper initiated a structured, multi-stage response to investigate, contain, and secure the environment. Forensic Investigation * Leveraged AWS CloudTrail logs to reconstruct the sequence of events and identify the source of compromise * Detected exposure of an IAM access key used from unauthorized IP addresses * Mapped API activity to understand how infrastructure was provisioned across regions Blast Radius Identification * Developed automation scripts to scan all enabled AWS regions * Identified unauthorized resources across Amazon EC2, AWS Auto Scaling, and Amazon ECS * Established complete visibility into impacted infrastructure and scope of compromise Containment and Remediation * Revoked compromised IAM credentials immediately * Removed all unauthorized resources after validation * Coordinated with AWS to lift temporary account restrictions * Completed containment and remediation within hours of engagement Security Hardening * Reviewed IAM policies and enforced least-privilege access controls * Improved monitoring and logging visibility for proactive detection * Prepared audit-ready documentation to support AWS refund claims * Strengthened overall security posture to prevent future incidents CloudKeeper executed a rapid, structured incident response to investigate the breach, contain unauthorized activity, and restore full account stability. Values Delivered Description # Values Delivered With CloudKeeper, the customer achieved: Description Rapid containment of active security breach Description Audit-ready documentation for cost exposure and refunds Description Complete removal of unauthorized infrastructure Description Strengthened IAM and monitoring controls Description Restored account stability within hours ## Conclusion CloudKeeper helped the customer contain a live AWS account compromise by combining rapid forensic analysis, automated discovery, and structured remediation. What began as an uncontrolled breach was quickly transformed into a fully contained and stabilized environment. With improved security controls, better visibility, and a hardened cloud foundation, the customer is now better equipped to detect, respond to, and prevent future threats with confidence. Other Success Stories * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * How Fundamento improved AI reliability, GKE stability & cloud efficiency * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Locus improved resource utilization and achieved cost savings with targeted EKS optimization Industry: Logistics Headquarters: Milpitas, California Founded in: 2015 Company Size: 201 - 500 Employees Featured Tags: Overview Locus is a leading logistics automation partner offering a unique order-to-delivery dispatch management platform helping enterprises to optimize supply chain operations through intelligent dispatch planning, real-time tracking, and data-driven optimization. Values delivered * Improved CPU utilization across clusters. * Reduced pod restarts and oversized nodes. * Enabled granular pod cost attribution. * Lowered EC2 costs with optimized instances. * Reduced pod instability with smart scheduling. Challenges Though Locus had a proper EKS foundation, they faced persistent inefficiencies around resource usage, scheduling behavior, and cost visibility - limiting their ability to convert insights into action. Diagnosing Utilization and Instance Fit EC2 nodes showed average CPU utilization under 10% due to memory-heavy but CPU-light workloads. Karpenter’s bin-packing struggled to schedule these efficiently, leading to large, underutilized instances across clusters. Bridging the Observability-to-Action Gap Tools like Kubecost and CastAI provided cost insights, but didn’t align well with internal workflows. The team lacked the clarity and granularity needed to take decisive action on their cost data. Improving Scheduling and Node Pool Strategy Overly aggressive consolidation windows led to frequent pod evictions and churn. While the team had separated workloads by type, scheduling still caused instability and unnecessary overhead. Correcting Oversized Instance Provisioning NodeClaim policies unintentionally allowed provisioning of 32xlarge and 48xlarge instances. These oversized types weren’t regularly used but posed cost risks during burst scenarios or resource crunches. Solution CloudKeeper worked with Locus to implement a targeted optimization strategy covering right-sizing, Karpenter tuning, cost visibility, and infrastructure hardening to improve resource utilization, workload stability, and cloud spend. Right-Sizing Workloads with Better Instance Matching After analyzing underutilized EC2 nodes and misaligned instance choices, we reclassified services based on memory and CPU profiles. A tailored mix of R-series and M-series instances improved bin-packing efficiency and reduced waste, guided by average (not peak) CPU usage. Refining Node Pool Strategy and Scaling Policies We optimized node pool segmentation by isolating workloads based on type and duration, while adjusting consolidation idle timers from 1 to 15 - 30 minutes. This stabilized pods and minimized churn without compromising responsiveness to load changes. Leveraging VPA for Precise Resource Allocation Vertical Pod Autoscaler was introduced in recommendation mode for staging and off-mode for production. Its suggestions helped right-size resource requests, particularly for Java services, resulting in better CPU utilization and less overprovisioning without service disruptions. Restricting Oversized Instances in Karpenter We discovered and removed overly large instances (e.g., 32xlarge, 48xlarge) from autoscaling configurations. Spot-based pools with TTL policies were introduced for short-lived workloads, helping isolate bursty cron jobs from long-running production services to enhance cost control. Boosting Cost Visibility with CloudKeeper Lens Locus switched from Kubecost to CloudKeeper Lens to gain deeper cost attribution across pods, containers, and namespaces. The platform provided clearer insights and required no additional configuration, helping teams tie usage to spend more effectively. Hardening Infrastructure and Streamlining Logging A full cluster audit flagged root-level pods and recommended hardening. All pods used IRSA, and ENI limits were healthy. We also advised moving from sidecar logging to stdout/stderr streams for simpler, more scalable log management. ## Post-Upgrade Impact Within 48 hours of the transformation process, CPU over-allocation dropped and node churn reduced dramatically. * Pod lifetimes increased from hours to days. * EC2 average CPU utilization significantly improved. * Removed idle NodePools and applied VPA-driven rightsizing. * Graviton adoption was added to the roadmap for future savings. Beyond immediate results, Locus committed to a phased rollout of the optimizations across multiple production regions. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Loylogic’s Pointspay successfully transitioned to AWS with minimal disruptions to Live systems Industry: Marketing Services Headquarters: Zurich, Switzerland Founded in: 2005 Company Size: 51 - 200 employees Featured Tags: About Loylogic Loylogic Group is a leading innovation-driven company, focusing on e-commerce and e-payment systems for loyalty programs. They have been helping global brands in transforming loyalty programs by enhancing user journeys and offering attractive rewards options. **Pointspay** - Loylogic Group's loyalty points management solution allows shoppers to earn and redeem loyalty points at checkout, providing merchants with the tools to increase customer engagement and purchasing frequency. Values delivered * Seamless AWS migration for Pointspay. * Minimal disruptions for Live systems. * Achieved full compliance and isolation. * Enhanced scalability and flexibility. * Better cost tracking and resource management. Challenges Infrastructure Migration Pointspay had to be isolated from their shared infrastructure for business requirements, while maintaining clear cost visibility from other services. Configuration and Dependency Issues Entangled configurations of Pointspay resources, along with certain undocumented components and APIs lead to unforeseen debugging and delays. Uninterrupted Operations The migration required seamless execution without disrupting their services, including API-to-API communication and a cross-region Disaster Recovery (DR) setup for databases. DNS Caching and RDS Parameters Migration testing faced delays due to outdated DNS endpoints causing connectivity issues. Setting up an RDS replica was also hindered by parameter group conflicts. Solution Loyalogic Group utilized CloudKeeper’s end-to-end migration and modernization services to transition Pointspay to a dedicated AWS account. This involved careful planning, risk assessment, and execution. The migration process was divided into **three phases** : Pre-Migration * Detailed inventory assessment to identify dependencies and configurations. * Replicated networking, application, database, storage, security, and DNS setups. * Transferred RDS snapshots and backed up DocumentDB data. * Performed a migration dry run and modified AMIs for EC2 for the new account settings. * Adjusted domain settings and mirrored security policies. Migration * Application downtime was managed with a maintenance page. * Migrated RDS and DocumentDB backups; restored EFS data to the new account. * Updated DNS servers for domain routing. Post-Migration * Thorough QA Testing for all configurations, functionalities and edge cases. * Replicated verified firewall settings, and diligently monitored the new infrastructure. * Established cross-region RDS replicas with necessary configurations. Achieving Isolation and Compliance The infrastructure was completely isolated from Loylogic’s, ensuring dedicated resource management. Compliance requirements were met, enhancing flexibility in cost tracking and governance. Ensuring Continuity and Recovery Maintained API integrity between Pointspay and Loylogic Group’s services. Successfully implemented a cross-region disaster recovery setup for robust backup solutions. Comprehensive Planning and Diligent Execution Detailed pre-migration discussions and incremental testing minimized the potential risks and the impact on live systems. Continuous monitoring and proper documentation streamlined migration processes and post-migration audits. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How MaxVal unlocked cloud Savings & visibility with CloudKeeper Tuner Industry: Intellectual Property (IP) Management / LegalTech Headquarters: Los Altos, California Founded in: 2004 Company Size: 501-1,000 employees Featured Tags: Overview MaxVal is a global leader in Intellectual Property (IP) lifecycle management, serving top law firms, enterprises, and innovation-driven organizations. As their cloud infrastructure scaled, the team sought a solution that could surface hidden inefficiencies, optimize provisioning, and simplify cleanup - without adding to their operational overhead. Challenges MaxVal faced growing complexity in managing their cloud environment. Identifying underutilized and over-provisioned resources was becoming increasingly manual and time-consuming, and existing tools lacked the granular visibility they needed. Their key requirements included: Clear insights into resource wastage Actionable recommendations, especially for EC2 and EBS Automation to reduce manual effort A cost-effective solution to support ongoing cloud optimization The Solution ## Solution: **CloudKeeper Tuner** By onboarding to CloudKeeper Tuner, MaxVal was able to quickly gain visibility into inefficiencies and take action through its core features - Cleaner and Over-Provisioned. The platform enabled the team to: Uncover idle and underutilized resources in a few clicks Right-size EC2 instances based on usage trends Clean up unused EBS volumes and snapshots with confidence Access centralized dashboards for streamlined reporting and tracking Results Identified over 4% in potential monthly AWS savings, with EC2 optimization contributing the most Cleaner surfaced resource-level inefficiencies that other tools missed EC2 right-sizing delivered impactful cost optimization Reduced manual effort through automation and intuitive insights Achieved without any additional cost or disruption I would highly recommend CloudKeeper Tuner with the Cleaner and Oversizing features it has. The Cleaner feature of CloudKeeper Tuner gives direct visibility which is not provided in any other tool. That visibility makes CloudKeeper Tuner highly useful. Sudharsanam Dhamodharan IT Solution Architect, MaxVal Group Inc. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How MobiKwik, a major fintech player, is using CloudKeeper EDP+ to reduce their AWS costs by 27% Industry: Financial Services & FinTech Headquarters: Gurugram, India Founded in: 2009 Company Size: 501-1,000 employees Featured Tags: About MobiKwik MobiKwik is the fastest-growing Indian fintech company specializing in digital payments and financial services. Started as a mobile recharge platform, the company has grown into a comprehensive digital wallet offering bill payments, money transfers, loans, insurance, and investments, with 135 million registered users. Values delivered * Instant savings of 12% on entire AWS costs. * 10% cost reduction through architectural optimizations. * Enhance financial transparency & accountability. Challenges Lack of Visibility MobiKwik struggled to see and understand their cloud expenses, leading to financial uncertainties. Cost Attribution Issues Accurately assigning cloud costs to specific applications and teams proved difficult, creating challenges in cost governance and accountability. Manual RI/SP Management The company used labor-intensive processes in managing Reserved Instances and Savings Plans, hampering cost optimization. Challenges with Handling Cost Anomalies MobiKwik encountered difficulties in identifying and addressing unexpected spikes or dips in cloud expenses, which impacted their budgeting. Solution MobiKwik started off their partnership with **12% on their overall AWS costs** almost instantly, without any effort or change in their infrastructure. They leveraged the RI/SP management features and the enhanced savings on AWS Enterprise Discount Program offered by CloudKeeper. Furthermore, CloudKeeper delivered an **additional 15%** using several architectural level optimizations which include - * Downgrading the servers to a lower but optimum configuration * Optimized usage of EBS volumes * Migrating from CLB to ALB * Identifying idle/unused resources Tagging & Cost Allocation CloudKeeper introduced a system for organizing cloud expenses with tag based reports, enhancing financial transparency and resource allocation for MobiKwik. Well-Architected Reviews Backed by AWS-certified cloud experts, CloudKeeper helped them optimize their entire cloud infrastructure according to the AWS design principles. Anomaly Detection CloudKeeper implemented a solution to promptly identify and address unusual cost fluctuations, enhancing financial control at MobiKwik. Graviton Processor Adoption MobiKwik adopted Graviton processors which turned out to be significantly cost-effective compared to other alternatives with the same processing power. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How **MobiKwik** Unlocks AWS Savings of 7–10% every month with CloudKeeper Tuner Industry: Financial Services & FinTech Headquarters: Gurugram, India Founded in: 2009 Company Size: 501-1,000 employees Featured Tags: Overview As one of India’s leading digital financial services platforms, MobiKwik operates a cloud-first infrastructure where cost, performance, and agility are non-negotiable. With growing scale came growing complexity—spread across multiple AWS accounts and services. Despite using internal tools and AWS-native solutions, MobiKwik struggled to maintain a centralized, actionable view of its cloud optimization efforts. They needed a smarter, automated solution to keep cost efficiency in lockstep with growth. That’s when they turned to **CloudKeeper Tuner** Challenges Managing a multi-account AWS environment came with its own set of pain points: Fragmented optimization opportunities across multiple AWS accounts Time-consuming manual effort for identifying right-sizing and cleanup opportunities Limited trust in existing insights, often leading to delayed action MobiKwik needed a solution that was intelligent, reliable, and fast to implement—without disrupting ongoing deployments or business-critical services. The Solution ## Solution: **CloudKeeper Tuner** MobiKwik onboarded their AWS environment to CloudKeeper Tuner.Within days, the platform started delivering granular, real-time recommendations across more than 50 AWS services, including **EC2, EBS, and RDS.** By analyzing actual usage patterns, historical trends, and peak loads, **Tuner provided data-backed suggestions that MobiKwik’s teams could trust—no manual audits, no guesswork.** ### Impact EC2 Right-Sizing Tuner identified ~26% optimization scope in EC2, flagging underutilized instances and helping MobiKwik reallocate resources with zero disruption. EBS Cleanup & Tuning While Mobikwik had already built an in-house utility for EBS cleanup, Tuner complemented it by identifying tuning opportunities to further improve storage efficiency. RDS Optimization Tuner surfaced over 11.7% monthly savings potential in RDS by recommending smarter instance types and reservation strategies—without performance compromise. Overall, Tuner uncovered **7–10% monthly savings potential** across MobiKwik’s AWS environment—backed by **precise insights** and **immediate actionability.** Reduced Manual Effort: Description Automated analysis replaced time-consuming manual tracking across AWS accounts Accelerated Decisions: Description FinOps and DevOps teams could act on recommendations in hours, not weeks Lean Infrastructure: Description Cleanup of idle volumes and resizing instances resulted in tangible cost reduction Full Transparency: Description Every suggestion was backed by usage data and was risk-free to implement Continuous Monitoring: Description Scans the cloud setup 24/7 for fresh optimization scopes and proactively flags cost spikes Scalable Optimization: Description As MobiKwik grows, Tuner scales effortlessly across their architecture Why Tuner Stood Out for MobiKwik **Trusted by FinOps & DevOps:** Recommendations were backed by strong data credibility and quickly adopted across teams. **No Manual Overhead:** No scripts, no spreadsheets—just plug in and optimize. **Unified Visibility:** One dashboard to track cost insights across all integrated accounts. **Backed by Experts:** CloudKeeper’s FinOps team supports every recommendation with clarity. ## Conclusion For MobiKwik, CloudKeeper Tuner became more than just a cost optimization tool—it became a strategic partner in their cloud journey. CloudKeeper Tuner is one of the best tools for identifying underutilized instances and optimization opportunities. We get consolidated views of all cost optimizations in a single console instead of juggling multiple tabs or third-party tools, plus actionable recommendations for potential savings. Dilawar Singh Director of Engineering - DevOps and Infra, MobiKwik Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Nanonets gained full FinOps visibility & reduced GCP costs with CloudKeeper Industry: Software Development Headquarters: San Francisco, California Founded in: 2017 Company Size: 51-200 employees Featured Tags: Overview Nanonets is a leading AI automation platform specializing in Intelligent Document Processing (IDP) and unstructured data extraction. Powered by advanced OCR and deep learning, Nanonets helps enterprises convert invoices, receipts, contracts, and forms into clean, structured, and actionable data fueling automation at scale. As their AI workloads expanded across GCP, rising costs and limited visibility made it difficult to understand usage patterns, optimize heavy workloads, and maintain predictable spending. To strengthen cost governance and gain deep visibility into their AI-driven infrastructure, Nanonets partnered with CloudKeeper to establish a structured, insight-led FinOps framework. Challenges As their AI workloads expanded, Nanonets began facing multiple visibility and cost-efficiency challenges across their GCP environment. Low visibility into Gemini API cost spikes BigQuery and Compute costs lacked query-level clarity Vision API misconfigurations driving high spend No real-time dashboards due to missing log sinks They needed granular, real-time visibility into AI workloads and a partner who could help them understand, optimize, and govern cloud costs effectively. The Solution ## Solution: **CloudKeeper Lens** CloudKeeper worked with Nanonets to implement a strong FinOps visibility and optimization framework across GCP. * Enabled transparent Gemini API cost attribution * Built real-time Looker dashboards for BigQuery and compute insights * Established reliable log sinks and pipelines for continuous governance * Optimized workloads through Vision API tuning, Compute rightsizing, and AMD migration recommendations This helped Nanonets gain clarity into their AI workloads, optimize high-consumption services, and build predictable cost governance. Values Delivered Description # Post Optimization Impact Description Reduced BigQuery and Compute costs via query cleanup and rightsizing Description Achieved transparent visibility across key GCP services Description Enabled real-time dashboards for engineering, finance, and product teams Description Predictable cloud spend and stronger governance supporting scalable AI growth ## Conclusion Nanonets’ collaboration with CloudKeeper transformed their cloud operations from limited visibility and rising costs to a structured, real-time FinOps practice. By enabling transparent attribution for key AI services, optimizing BigQuery, Vision API, and Compute Engine usage, and establishing reliable cost governance pipelines, CloudKeeper helped Nanonets gain clarity, control, and predictability across their GCP environment. With deeper insights, reduced spend, and a stronger FinOps foundation, Nanonets is now better equipped to scale its AI workloads confidently and sustainably Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How **NetRoadshow** Uncovers Long-standing AWS Cost Blind Spots with CloudKeeper Tuner Industry: Financial Services / Investor Communications Headquarters: Atlanta, GA Founded in: 1997 Company Size: 201-500 employees Featured Tags: Overview NetRoadshow, a leading US-based provider of secure online roadshows for investment banks and corporations, operates in a cloud-intensive environment where availability and performance are non-negotiable. However, as their cloud footprint scaled, so did the complexity of managing it efficiently. To gain clarity, control, and cost optimization across their AWS infrastructure, NetRoadshow adopted **CloudKeeper Tuner**. Challenges Despite leveraging native AWS tools and in-house monitoring practices, NetRoadshow encountered: Underutilized resources not flagged by conventional tooling Inactionable recommendations due to lack of prioritization or historical insights Explainability and dollar impact unknown for un-optimized resources They needed a solution that didn’t just surface cost-saving recommendations—but helped **connect the dots across time, accounts, and services.** The Solution ## Solution: **CloudKeeper Tuner** NetRoadshow onboarded 10+ AWS accounts onto Tuner, unlocking centralized governance, real-time recommendations, and visibility into persistent inefficiencies. * **$4,900+ in monthly potential savings identified,** spanning services like EC2, RDS, EBS, and more * **RDS Savings accounted for ~17% of their monthly RDS spend,** spotlighting significant rightsizing opportunities * **60+ day old recommendations** spotlighted long-ignored inefficiencies—offering a backlog of savings ready to be actioned * **1+ year-old suggestions** revealed legacy oversizing and misconfiguration, helping initiate long-overdue cleanup Values Delivered Description # Future Roadmap: Unlocking More with Scheduler As part of their roadmap, they plan to leverage Scheduler’s automation capabilities to optimize non-production workloads—such as development, staging, and testing environments—without impacting performance or availability. **What’s ahead:** * **Projected 10–12% Additional Savings** by automating start-stop cycles across services like EC2, Auto Scaling Groups, RDS, ECS, and Redshift * **Effortless Policy-Based Automation** to reduce cloud wastage and ensure consistent cost control * **Operational Ease at Scale** , allowing engineering teams to focus on innovation while Scheduler handles infrastructure efficiency in the background With Scheduler in the pipeline, NetRoadshow is set to strengthen its FinOps maturity and continue driving measurable cloud savings—month after month. Outcome Points Description CloudKeeper Tuner didn’t just offer NetRoadshow instant savings—it delivered a continuous cost saving platform empowering their teams to: Prioritize long-standing blind spots Strategically plan for future automation through Scheduler and other modules Explainability and dollar value impact of each savings ## Conclusion For a performance-focused organization like NetRoadshow, CloudKeeper Tuner proved to be a **cost governance companion,** not just a recommendation engine. And with forecasted automation-ready opportunities still on the table, the journey to deeper savings has just begun. CloudKeeper Tuner didn’t just help us save thousands by identifying and removing unused resources—it pushed us to rethink and modernize parts of our architecture for better performance. Our DevOps engineers now see live, in-console cost-saving opportunities as they work, like having an always-on assistant. It’s a tool built for scale, speed, and real-world cloud teams. Pratish Arora Principal DevOps Engineer Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Netcore Cloud achieved 25% AWS savings and strengthened cloud security Industry: Automation/AI Headquarters: Mumbai, India Founded in: 1998 Company Size: 1000-5000 employees Featured Tags: Overview Netcore Cloud is a global leader in customer engagement and marketing automation, enabling businesses to deliver personalized, AI-driven experiences at scale. Running extensively on AWS, Netcore’s data-intensive platform supports millions of users worldwide. Values delivered * Reduced costs and modernized workloads * Remediated 15+ security vulnerabilities * Improved infrastructure utilization * Faster issue detection and resolution * Proactive monitoring and governance * Zero disruptions to business operations Challenges As Netcore scaled rapidly, its AWS environment became increasingly complex and harder to manage. The scaling demands brought new financial and operational challenges that required immediate attention. Rising AWS Costs Escalating cloud bills began to impact profit margins, with several non-critical workloads consuming disproportionate costs. The absence of regular spend governance compounded inefficiencies. Underutilized and Over-Provisioned Resources Multiple EC2 instances and workloads were provisioned beyond actual demand, resulting in consistently low utilization and wasted compute capacity across environments. Security Gaps and Compliance Risks Open ports, overly broad IAM permissions, and publicly accessible S3 buckets created potential vulnerabilities. These gaps not only increased exposure risks but also posed compliance challenges in regulated workloads. Limited Optimization Visibility The team lacked consolidated insights into actionable cost and performance improvements. Without a unified optimization framework, identifying high-impact opportunities remained a manual and time-consuming process. Solution CloudKeeper adopted a structured and data-driven strategy combining automation through CloudKeeper Tuner and hands-on optimization via Partner-led Support to help Netcore achieve sustained efficiency gains. In-depth Visibility and Recommendations CloudKeeper Tuner delivered end-to-end visibility across Netcore’s AWS ecosystem - identifying idle resources, underutilized workloads, modernization opportunities, and critical security gaps. The insights provided a clear roadmap for cost, performance, and security optimization. Infrastructure Optimization and Modernization CloudKeeper’s certified experts worked closely with Netcore’s engineering team to translate recommendations into measurable results through: * Right-sizing EC2 instances and workloads for optimal performance and cost balance. * Decommissioning idle and unused resources to eliminate wastage. * Migrating key workloads to AWS Graviton, leveraging its cost-performance benefits. * Tightening security by closing open ports, restricting IAM roles, and securing S3 configurations. Team Enablement through Upskilling Netcore engineers were upskilled in AWS best practices for cost optimization, security, and operational governance. This empowered the team to independently manage, optimize, and troubleshoot their cloud environment, ensuring long-term efficiency and resilience. This coordinated approach ensured zero disruption to business operations while maximizing cost efficiency and compliance alignment. ## **Post-Optimization Impact** Netcore’s cloud efficiency, security, and operational maturity saw drastic improvements: * Significant AWS savings of almost 25% and minimized cloud waste. * 15+ critical vulnerabilities remediated, strengthening security posture. * Infrastructure utilization improved from ~45% to ~78%. * Faster issue detection and resolution with proactive monitoring. Netcore’s engineering team gained greater autonomy, operating with cost awareness, confidence, and optimized performance across their AWS environment. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How **OneAssist** transitioned to AWS CloudFront achieving enhanced content delivery and minimizing data transfer costs Industry: Consumer Services Headquarters: Mumbai, India Founded in: 2011 Company Size: 201 - 500 Employees Featured Tags: About OneAssist OneAssist is a consumer solutions company providing a comprehensive platform for protecting and managing everyday essentials. It offers quick and reliable support to manage issues such as loss, theft, or damage to their gadgets, home appliances, financial products and more. Values delivered * Migrated 25 domains with zero downtime. * 100% traffic redirected with zero data loss. * Significant reduction in CDN costs. * Minimized latency and improved performance. * Proactive monitoring and security protocols. * Innovative configuration management. Challenges Costly CDN and WAF Configuration OneAssist incurred significant costs due to high transfer fees and the complexity of maintaining Akamai’s CDN configuration and Web Application Firewall (WAF). These costs made their existing setup unsustainable. Large-scale Migration As OneAssist’s entire infrastructure was already hosted on AWS, transitioning all the 25 CDN domains to AWS CloudFront offered both savings and simplified management. However, this required a carefully planned migration with minimal disruptions. Timeline and Resource Constraints The migration had to be completed within two weeks before the Akamai contract expired, with limited skilled resources. Extensive testing requirements added to the complexity due to limited familiarity with the domains. Feature Compatibility Challenges Akamai supported features like URL redirection and HTTP method blocking, which CloudFront lacked natively. Mapping these functionalities required careful planning to maintain seamless operations. Security and Configuration Gaps Akamai’s WAF provided rate limiting in 5-second intervals, while AWS WAF supported a minimum threshold of 1-minute intervals. Additionally, CloudFront lacked versioned domain configurations, and HTTP/3 support. Performance and Efficiency Ensuring optimal content delivery speed, strengthening security, and streamlining ongoing management were key priorities calling for thorough planning and a systematic approach. Solution OneAssist leveraged CloudKeeper’s Flawless Migration with Zero Downtime Seamlessly migrated over 25 domains from Akamai to AWS CloudFront, ensuring uninterrupted service, zero downtime, and no data loss throughout the transition. Enhanced Performance and Cost Efficiency Optimized content delivery using CloudFront’s caching and Lambda@Edge, reducing latency while eliminating data transfer costs for significant savings. Strengthened Security and Monitoring Implemented AWS WAF for proactive security, enabled AWS WAF logging via Amazon S3 and Athena, and set up CloudFront alarms for real-time threat detection. Adjustments were made to AWS WAF rate-based rules to align with OneAssist’s specific rate-limiting needs. Streamlined Configuration Management Engineered a dedicated staging distribution to mirror production, overcoming CloudFront’s lack of versioning and HTTP/3 support in staging environments. Continuous Performance Monitoring Deployed Route 53 health checks and CloudFront error alarms, ensuring real-time insights, high availability, and quick issue resolution. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How RevSure achieved in-depth cloud cost visibility and saved 25% on their GCP bill Industry: Gen AI Headquarters: Wilmington, Delaware Founded in: 2021 Company Size: 11 - 50 employees Featured Tags: Overview RevSure is a revenue intelligence platform that helps B2B marketing and sales teams convert leads into qualified pipelines using AI-driven funnel analytics. The company blends full-funnel analytics, predictive intelligence, and proactive recommendations to help B2B businesses optimize every phase of their buyer journeys. Values delivered * Enhanced cloud spend visibility and attribution. * Cumulative GCP savings of around 25%. * Automated cost dashboards with Looker and BigQuery. * Improved budgeting and proactive incident triage. * Seamless adoption of GCP best practices. Challenges RevSure had data-heavy operations relying on real-time processing, predictive modeling, and dashboarding on Google Cloud services including BigQuery, Vertex AI, Compute Engine, Cloud SQL, and Looker. They were scaling rapidly but their complex infrastructure was struggling to keep pace. Fragmented and Overprovisioned Infrastructure The GCP environment - while powerful - had become fragmented and frequently configured manually. This lack of centralized governance resulted in widespread overprovisioning. Resources consumed more capacity (and cost) than their actual usage required, leading to wasted spend across the complex architecture. Limited Cost Visibility and Attribution The challenge of linking spend across these multiple, essential services meant the finance and engineering teams had limited visibility into costs. This resulted in poor cost attribution, making it nearly impossible to accurately map cloud expenses back to specific teams or business units, severely hindering effective budgeting. Lack of Real-Time Analytics Existing reporting methods were reactive, providing little to no real-time analytics on cloud spend. The absence of detailed SKU-level attribution prevented precise forecasting needed to support the scaling of their core product features. Inefficient Manual Incident Resolution The process for identifying, diagnosing, and resolving infrastructure incidents across their complex suite of GCP services was highly manual. This lack of automated workflows resulted in a high Mean Time to Resolution (MTTR) for critical issues, directly impacting platform uptime and agility. Solution To address these issues that troubled RevSure’s scaling efforts, they partnered with CloudKeeper for a comprehensive GCP optimization and governance initiative. The strategy focused on implementing strong FinOps practices supported by enhanced monitoring and observability. Integrated Cost Visibility and Attribution CloudKeeper deployed the CloudKeeper Lens platform to unify RevSure’s GCP billing data, creating a single source of truth with SKU-level visibility. Automated dashboards in Looker and BigQuery eliminated reporting delays, while structured tagging mapped costs to teams and workloads - driving accountability, accurate budgeting, and actionable cost insights across the organization. Targeted Resource Right-Sizing Leveraging utilization insights from CloudKeeper Lens,the Compute Engine and BigQuery resources were optimized, which were critical for predictive modeling workloads. Right-sizing ensured configurations matched actual usage instead of peak assumptions, eliminating waste without performance impact. A GCP best practices framework was embedded to ensure sustainable optimization for future workload provisioning. Operational and Resilience Improvements Manual troubleshooting increased RevSure’s MTTR, impacting efficiency. CloudKeeper implemented a structured support framework, leveraging Cloud Monitoring and Logging for proactive detection and faster incident triage. Defined escalation pathways reduced resolution times, improved workload stability, and freed engineering capacity - allowing teams to prioritize product innovation over repetitive, reactive firefighting. ## **Post-Optimization Impact** The collaboration delivered immediate and transformative outcomes for RevSure: * Cumulative cost savings of around 25%. * Automated dashboards enabled instant financial visibility. * SKU-level attribution improved budgeting precision. * MTTR reduced through proactive incident triage. The RevSure team regained financial control by transitioning from reactive to proactive cost management. They also established a foundation for seamless GCP best practice adoption. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How RippleHire improved GCP stability, visibility, and monthly costs with CloudKeeper Industry: Software Development Headquarters: Mumbai, Maharashtra Founded in: 2015 Company Size: 51-200 employees Featured Tags: Overview RippleHire is a global, AI-powered Applicant Tracking System used by enterprises across 50+ countries to run large-scale, high-velocity hiring. Built on behavioral science, artificial intelligence, and a no-code architecture, RippleHire helps organizations deliver award-winning recruiting experiences and operational efficiency at scale. To stabilize their GKE environment, improve cloud efficiency, and build long-term FinOps maturity, RippleHire partnered with CloudKeeper to jointly optimize cost, performance, and reliability across their GCP ecosystem. Challenges With expanding workloads and increasing scale, RippleHire encountered several critical issues across GKE and GCP cost governance: GKE instability with node pool failures and 12,000+ pending pods No granular Pod/NodePool/cluster cost visibility Full WAR to fix cost, security, and performance gaps Unexpected Cloud SQL and Logging cost spikes They needed a scalable, insight-rich platform to regain control of their cloud costs and a collaborative partner to help them resolve these challenges effectively. The Solution ## Solution: CloudKeeper worked closely with RippleHire across engineering, FinOps, and architecture teams to stabilize clusters, improve cloud hygiene, and unlock operational transparency. Stabilized GKE operations by fixing autoscaling, MIG health, disk saturation, scheduling issues, and quota constraints Built custom dashboards for Pod-, NodePool-, and cluster-level cost visibility Performed a full Well-Architected Review across Compute Engine, GKE, Cloud SQL, Networking, Storage, and Logging Resolved Cloud SQL transfer anomalies and optimized Cloud Logging through exclusion filters, routing improvements, and retention fixes Together, this helped RippleHire restore stability, gain granular visibility, and establish a strong foundation for ongoing FinOps and architectural improvements. | Metric | Value | | --- | --- | | Monthly Savings Identified | $4400 - $4800 | | Cost Optimization Sources | Rightsizing, AMD migration, removing idle resources | | GKE Stability | Predictable autoscaling and healthier NodePools | | Cost Visibility | Pod, NodePool and cluster-level insights | | Logging Optimization | Reduced unwanted logs and corrected retention | RippleHire now has predictable cloud costs, stable GKE operations, and improved architecture hygiene across their GCP environment. Outcome Points Description With CloudKeeper, RippleHire achieved: Stabilized and predictable GKE performance Granular visibility into cloud costs across services $4.4K–$4.8K in recurring monthly savings Resolved Cloud SQL and Logging anomalies A clear roadmap for ongoing FinOps improvements ## Conclusion RippleHire’s partnership with CloudKeeper transformed their cloud operations, from reactive fixes to a structured, data-driven optimization strategy. The combination of deep engineering diagnostics, cost governance, and long-term FinOps planning has enabled RippleHire to operate a more resilient, transparent, and cost-efficient GCP environment. With enhanced visibility, stronger architecture hygiene, and predictable savings, RippleHire is now positioned to scale confidently while making every cloud decision smarter and more sustainable. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How Scrut Automation used CloudKeeper Tuner to unlock 7.3% in AWS savings. Industry: Software Development Headquarters: Palo Alto, California Founded in: 2009 Company Size: 51-200 employees 215 associated members Featured Tags: Overview Scrut Automation is a**high-growth GRC automation platform** that helps businesses stay continuously audit-ready for frameworks like SOC 2, ISO 27001, and GDPR. As a security-focused SaaS provider with a dynamic cloud footprint on AWS, Scrut needed deeper visibility into their usage patterns to control costs without compromising performance. To enhance their cloud efficiency and scale smarter,**Scrut Automation partnered with CloudKeeper** to jointly drive cloud cost optimization using CloudKeeper Tuner. Challenges With cloud infrastructure growing in complexity, Scrut faced common yet critical challenges: Identifying inefficiencies in containerized services like ECS Surfacing overlooked or aged recommendations across environments Prioritizing changes with tangible business value Managing visibility and governance across multiple AWS accounts They needed a scalable, context-rich platform to simplify cloud cost control—and a partner to collaborate closely on solving these problems. The Solution ## Solution: **CloudKeeper Tuner** Scrut onboarded one of their two AWS accounts to CloudKeeper Tuner. Even with partial onboarding, the insights were powerful—particularly within their ECS usage. The DevOps team at Scrut worked steadily on CloudKeeper Tuner’s recommendations, swiftly implementing them to unlock both performance efficiencies and tangible cost savings. ### Impact | Metric | Value | | --- | --- | | Monthly Savings Identified | 7.3% of the AWS bill | | ECS Optimization Impact | 88% of total savings | | Aged Opportunities Detected | From 60+ days to over a year | | Recommendation Quality | Clear, contextual, and actionable | CloudKeeper Tuner highlighted underutilized containers and aged inefficiencies in both staging and production environments—most of which had remained undetected in internal reviews. Values Delivered Description # Future Roadmap: CloudKeeper Scheduler for Scaled Automation Following strong initial results, Scrut is now planning to activate CloudKeeper Scheduler to extend cost automation across its cloud infrastructure. Tuner has already mapped idle patterns in non-production environments, enabling the team to automate off-hour shutdowns for services like ECS, EC2, RDS, and ASG. **Next-phase goals include:** Description Unlocking 8–10% additional savings through automated scheduling Description Reducing manual efforts via intelligent, policy-driven controls Description Enabling engineers to focus on innovation while cost optimization runs in the background Outcome Points Description With just a partial deployment, Scrut Automation achieved: 7.3% in monthly cost visibility 88% of savings driven by ECS optimization Aged inefficiencies brought to light for resolution A clear roadmap for scaling automation through Scheduler Stronger alignment between cloud usage and business goals ## Conclusion This joint initiative between **Scrut Automation and CloudKeeper** helped move from manual cloud cost reviews to a more structured, intelligent approach to optimization. The early savings and deep visibility have laid the groundwork for an expanded, automated cost-efficiency program - **making every cloud decision smarter, scalable** , and more sustainable. The CloudKeeper Tuner helped us in reducing the over-provisioned resources by providing recommendations and identifying how much more we can reduce. The onboarding process is simple, not too much hassle that we have to make on our end. Sanchit Aggarwal Senior DevOps Engineer, Scrut Automation Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close # How ZenduIT improved cloud visibility, storage governance & monthly cost savings Industry: Software Development Headquarters: Mississauga, Ontario Founded in: 2015 Company Size: 11-50 Employees Featured Tags: Overview ZenduIT provides IoT-powered fleet, video, and safety solutions, combining smart devices with cloud software to help enterprises improve safety, efficiency, and data-driven decision-making at scale. To strengthen financial transparency, optimize storage architecture, and improve cloud efficiency, ZenduIT partnered with CloudKeeper to establish end-to-end FinOps clarity and technical governance across their GCP environment. Challenges With growing datasets and evolving IoT/video workloads, ZenduIT faced several cloud visibility and scaling challenges: * Billing gaps from missing data and no SKU visibility * Unclear GCS retention and egress costs * IoT/video scaling issues for 300 devices and 165 TB per month * AI and hygiene issues with Vertex AI blockers, idle spend and Trax spikes They needed a scalable, insight-rich platform to restore financial clarity and a partner who could help them optimize storage, egress, and AI workloads with confidence. The Solution ## Solution: **CloudKeeper Lens** CloudKeeper collaborated closely with ZenduIT’s engineering, cloud, and FinOps teams to restore clarity, optimize storage, and enable AI workflows: Billing Visibility & Governance Deployed CloudKeeper Lens for full billing clarity, SKU-level dashboards, anomaly detection, and restored missing chargeback visibility. Storage, Egress & IoT Architecture Optimization Mapped GCS pricing and lifecycle rules, built an egress exposure model, and created a storage playbook for ~165 TB/month ingest, recommending CDN usage, caching, signed URLs, parallel ingestion, and resumable uploads. AI Enablement & Cloud Hygiene Fixes Enabled governed Vertex AI onboarding with correct IAM roles, resolved permission inconsistencies through WAR, and provided a cleanup workbook highlighting idle/unused resources. These initiatives gave ZenduIT deeper visibility, optimized storage and egress strategies, and a scalable foundation for AI and IoT workloads. Values Delivered Description # Value Delivered With CloudKeeper, ZenduIT achieved: Description Full financial clarity with SKU-level visibility Description Predictable storage and retention costs Description ~$1.8K/month in actionable savings Description Governed and safe Vertex AI experimentation Description Strong FinOps governance with cleanup cadence Description Lower egress risk through optimized architecture ## Conclusion ZenduIT’s partnership with CloudKeeper transformed their cloud operations, from cost blind spots and unpredictable storage behavior to a transparent, well-structured, and scalable FinOps framework. Through a combination of billing analytics, storage governance, AI enablement, and infrastructure cleanup, ZenduIT now operates with stronger financial control, reduced risk, and a clearer roadmap for scaling IoT and video workloads. Other Success Stories * Containing an AWS account breach and restoring stability within hours * Helping a Global Energy Intelligence Platform resolve EKS logging issues * How Scans.AI optimized EKS performance and reduced AWS costs * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close * # Thank you for your interest! Our team will get back to you shortly. About CloudKeeper CloudKeeper is your comprehensive cloud cost optimization partner that combines the power of savings through smarter commitments, expert cloud consulting & support, and an enhanced visibility & usage optimization platform to reduce your cloud cost & help you maximize the value from AWS & Google Cloud. close close **Introduction** As cloud infrastructure becomes increasingly central to product development, deployment, and scaling, tech product companies are faced with the challenge of optimizing and controlling their cloud expenditures. This webinar will address these challenges head-on by focusing on three key pillars: **enhancing cloud cost visibility** , providing **automated recommendations** for optimization, and implementing **effective remediation strategies** to curb overspending. In this session, we will demonstrate how tech product companies can uncover hidden inefficiencies and drive actionable, data-backed recommendations. * **Cost allocation and chargeback strategies** : These enable organizations to allocate cloud expenses accurately across teams, products, or departments, fostering financial transparency and accountability. This helps ensure that the right stakeholders are empowered to manage costs and that cloud spending is aligned with business priorities. * **Tagging best practices and anomaly detection** : By applying consistent tagging to resources and leveraging anomaly detection systems, companies can detect unexpected spikes in cloud usage, track resource utilization more accurately, and reduce the risk of costly surprises. * **Usage Optimization & Remediation**: Some practical steps that companies can take to address inefficiencies once they’ve been identified. Whether it’s rightsizing instances, shutting down unused resources, or utilizing more cost-effective services, attendees will leave with actionable insights to drive real cost savings. Know your**Speakers** * ### Praneet Chandra Senior Director, CloudKeeper * ### Tejprakash Sharma DevOps Lead, CloudKeeper Key**Takeaways** * 1. Best practices for **cost allocation and chargeback** to ensure transparent and responsible cloud spending * 2. Effective **tagging strategies** and tools for **anomaly detection** to identify and address unexpected cost spikes * 3. How to **automate usage optimization** and use recommendations to reduce cloud waste * 4. Real-world **remediation tactics** to optimize cloud infrastructure for maximum cost efficiency About **CloudKeeper** CloudKeeper is a Comprehensive Cloud Cost Partner that combines the power of group buying & commitments management, expert cloud consulting & support, and an enhanced visibility & usage optimization **platform to reduce your cloud cost & help you maximize the value from AWS, Microsoft Azure, & Google Cloud**. We have helped **400+ global companies** save an average of **20% on their cloud bills** , modernize their cloud set-up and maximize value — all while maintaining flexibility and avoiding any long-term commitments or cost. AWS Premier Consulting Partner since 2013 Premier Partner & Governing Member of the FinOps Foundation Leader in the G2 Grid for Cloud Cost Management Microsoft Solutions Partner close close #### Change Log # What's New with CloudKeeper? Discover new features, services, and key improvements across our platform. Latest announcements May 12, 2026 UPDATE Tuner #### Jira (Data Center) Integration Create and track Jira tickets directly from Tuner recommendations to accelerate resolution and streamline cost optimization workflows. May 04, 2026 FEATURE Tuner #### EC2 Spot Protection (AWS Tuner) Automatically run workloads on Spot Instances with intelligent interruption handling and On-Demand fallback for maximum savings and reliability. Apr 30, 2026 UPDATE Tuner #### Auto Remediation Change Logs — “Remediated By” Column Added visibility into who triggered each remediation action with a new “Remediated By” column for improved transparency and auditability. Apr 30, 2026 UPDATE LensGPT #### LensGPT Update – Tag Support and URL-Based Navigation Enhanced LensGPT with tag-based insights and Lens platform URL generation for improved analysis and navigation. Apr 29, 2026 FEATURE LensGPT #### LensGPT- MCP Server Introduced Apr 28, 2026 UPDATE Lens #### LensGPT – Expose APIs for Customer Access (AWS & GCP) APIs have been exposed to enable customers to programmatically interact with LensGPT and retrieve billing insights. This allows seamless integration with external tools, dashboards, and automation workflows. Customers can now leverage LensGPT capabilities beyond the UI for customized use cases. Apr 27, 2026 UPDATE Lens #### Cloud Monitoring Dashboard Revamp (GCP) Revamped Cloud Monitoring dashboard in GCP to improve cost visibility, usability, and monitoring insights. Apr 22, 2026 UPDATE Tuner #### Tag Based Scheduler Enhancements We’ve upgraded the Scheduler experience with several usability and visibility improvements: Apr 14, 2026 UPDATE Lens #### Cloud SQL Dashboard Revamp (GCP) Revamped Cloud SQL dashboard in GCP to enhance cost visibility, usability, and service-level insights. Apr 07, 2026 FEATURE Lens #### Networking Cost Breakup Dashboard (GCP) Introduced Networking dashboard in GCP for detailed visibility into network-related costs and usage patterns. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Wondering what makes CloudKeeper a favourite among **DevOps Heads, CTOs, CFOs, and CEOs?** * **$120+ million** Cloud cost savings delivered * **20%** Average cost reduction * **100%** Satisfaction score on G2 * **400+** Success Stories What makes us truly **unique?** Why **juggle between multiple providers when one partner can do it all?** From rate optimization to usage optimization, granular visibility to cloud management services - we’re the only partner with **end-to-end cloud optimization capabilities.** * CloudKeeper Lens #### Cloud Visibility & Recommendation * Optimize spend, allocation & chargebacks. * Tagging & right-sizing guidance. * Multi-cloud visibility & hybrid cloud visibility. Vendors In this landscape * * * * * CloudKeeper Commit #### Savings & RI Management * Automated SP/RI optimization. * Flexible coverage & precise prediction. * Pay only when you save. Vendors In this landscape * * * * CloudKeeper AZ/EDP+ #### Cloud Reseller * Access to volume-based pricing. * Flexible, better payment terms. * Access to partner programs & incentives. Vendors In this landscape * * * * CloudKeeper Tuner #### Usage Optimization Platforms * Identify & fix cloud inefficiencies. * End-to-end automated process. * Usage insights & expert recommendations. Vendors In this landscape * * * * CloudKeeper Partner Led Support #### MSPs and FinOps Consulting Companies * FinOps consulting & support. * Well-Architected Reviews. * Architectural consulting & migration support. Vendors In this landscape * * * The **CloudKeeper has proven capabilities and scale in providing FinOps solutions** using a combination of platform and cost optimization services. Our unique approach to continuous cloud optimization: **CARA Framework** Maximizing ROI from your cloud investment isn’t a one-time task—it’s a dynamic, ongoing journey. Thus, our team leverages the **Continuous Assess Review Act (CARA)** Framework that combines high-impact optimizations with continuous performance tracking. * Average 20% cost reduction within the first 90 days * Ensures ongoing improvements * Tailored for the unique needs of businesses * Results-as-a-Service approach for measurable outcomes * Adapts to your business priorities and existing flow of work **Pioneering end-to-end cloud management** **Ranked #1** in User Satisfaction based on 100% genuine customer reviews for Cloud Management * CloudKeeper has truly been a **game-changer for our cloud cost management.** It is **essential** for anyone who wants to take control of their cloud spending and make the most out of their infrastructure. I **highly recommend** it to any organization looking to get serious about managing its cloud expenses. Aakash Sharma S. Lead CloudOps * CloudKeeper's **offering is one of a kind.** It **acts as our FinOps vertical** and helps out in cloud financial management, ensuring that we can focus on our delivery expertise. Ajay Y. DevOps Leader * More than just cost savings, a **business partner I can rely on.** CloudKeeper has proven its deep understanding of the AWS platform. The transition to integrate Cloudkeeper into our AWS account was easy. It made cost management and optimization quite easy. Frank D. DevOps Team Lead * **One of the best decisions we made.** CloudKeeper helps to keep track of the cloud usage and reduce the cloud spending. The daily report is especially useful to review the cost and take any necessary action. Keshav Murali Head of Engineering * A Game-Changer for Cloud Management! CloudKeeper has **transformed our cloud management** with its intuitive interface and powerful features. They have an excellent support team that provides timely assistance. Kartik K. Infra Administrator * Cost Optimization, Technical assistance, and Resource optimization bundled as one. In short, **an end-to-end FinOps solution.** Praveen K. Senior Cloud Engineer * We've found the product valuable, both for insights and savings. The **service & support are excellent.** Highly recommended to enhance visibility and savings. Our **Cloud Expertise** Recognized for proven expertise & certifications across leading cloud platforms. * * Trusted by 400+ Global Customers From SMEs, DNBs to ISVs & enterprises, CloudKeeper brings cross-industry expertise in every engagement. **They accomplished it!** Are you ready to take your cloud journey to new heights? **Related Resources** * 5 Reasons Why a Comprehensive Cloud Partner is Necessary Discover why partnering with a comprehensive cloud provider is critical for optimizing your cloud strategy. Download our whitepaper to learn how expert guidance, cost efficiency, security, and scalability can transform your business with Azure. Whitepapers * Why are end-to-end Cloud FinOps Partners leading the way? (Research Backed) Learn about the significance of comprehensive Cloud FinOps solutions and why CloudKeeper stands out as an ideal partner. Streamline cost optimization & maximize efficiency. Blog * FinOps Vendor Ecosystem you should know before nailing your Cloud Optimization Strategy Learn about the dynamics of the FinOps market and the FinOps Vendor Ecosystem to help you choose the right FinOps Partner and implement an effective Cloud Cost Optimization Strategy. Whitepapers * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close Workload Rightsizing & Smart Scheduling Backed by AI + Unlimited Cloud Experts BEFORE Without CloudKeeper COMPARE AFTER With CloudKeeper #### Workload Utilization Right-sized: 95% Utilized #### Runtime Utilization Unused capacity: Near-zero #### Workload Schedule Smart Scheduling • Auto-scaling UPTO3% Potential Savings #### Workload Utilization Right-sized: 25% Utilized #### Runtime Utilization Unused capacity: 12 hrs/day #### Workload Schedule Always On . Manual Scheduling . ### High Costs Cloud wastage 24 x 7 The Hidden Reasons Your Cloud Bill Keeps Growing * #### Over-provisioned instances everywhere CPU and memory stay underutilized, but costs keep running 24×7. * #### Non-prod runs like production Dev/Test/UAT environments stay “always on” even when no one is using them. * #### Too many services, too little time Engineers don’t have the bandwidth to continuously review thousands of resources. * #### Risk of change stops action Fear of performance impact delays rightsizing - even when waste is obvious. * #### Recommendations don’t get implemented Tools show insights, but execution stalls without ownership and follow-through. * #### Shadow IT & Forgotten Resources Forgotten POCs, old sandboxes, and unmanaged spikes quietly drain your cloud budget. The CloudKeeper Solution: **Intelligent Workload Rightsizing + Smart Scheduling** Our * **Intelligent Workload Rightsizing by Tuner** * Detects over-provisioned compute and container workloads * Recommends best-fit sizes using actual utilization trends * Highlights risk level, performance considerations, and expected savings * Prioritizes actions that deliver maximum impact with minimal disruption **** * **Smart Scheduling with Tuner’s Scheduler** * Finds workloads that don’t need 24×7 uptime (Dev/Test/UAT, batch, internal apps) * Enables scheduling by team, tag, environment, or calendar * Eliminates waste during nights/weekends/idle windows * Improves governance with policy + approvals (as needed) **** * **Continuous Optimization, Not One-Time Cleanup** * Regularly refreshes recommendations as usage changes * Prevents “optimization drift” after migrations, releases, or growth spurts * Our team ensures infrastructure stays aligned with real business demand * Keeps savings compounding month after month **** * The CloudKeeper Difference - Your Dedicated FinOps Squad Each customer is backed by a dedicated team that collaborates with you daily through Slack or Teams. * ### FinOps Strategist Drives rightsizing and scheduling decisions based on savings impact & business priorities. * ### Solutions Architect Ensures every resizing and scheduling action is safe, reliable, and performance-ready. * ### Customer Success Partner Coordinates teams, tracks progress, shares weekly/monthly reports, and ensures sustained savings. Real Optimization Outcomes with CloudKeeper | Customer Name | Key Challenge | CloudKeeper Approach | Measurable Impact | | --- | --- | --- | --- | | | Rising AWS costs, resource underutilization, and security gaps | Rightsizing, decommissioning, modernization, and closing security gaps | Achieved **-25% AWS savings** , 15+ vulnerabilities fixed, utilization improved from **-45% to -78%** | | | Multi-account visibility gaps and resource underutilization | Enabled cleanup, right-sizing, and real-time insights | **20% savings** from EC2 cleanup, rightsizing, and dynamic provisioning, along with -4% monthly recurring savings. | | | Over and under-provisioned resources with low visibility | EC2 rightsizing, idle cleanup, and centralized reporting | Identified **over 4% monthly AWS savings** , driven mainly by EC2 optimization | * #### KEY CHALLENGE Rising AWS costs, resource underutilization, and security gaps #### CLOUDKEEPER APPROACH Rightsizing, decommissioning, modernization, and closing security gaps #### MEASURABLE IMPACT Achieved **~25% AWS savings** , 15+ vulnerabilities fixed, utilization improved from **~45% to ~78%** * #### KEY CHALLENGE Multi-account visibility gaps and resource underutilization #### CLOUDKEEPER APPROACH Enabled cleanup, right-sizing, and real-time insights #### MEASURABLE IMPACT **20% savings** — from EC2 cleanup, rightsizing, and dynamic provisioning, along with ~4% monthly recurring savings * #### KEY CHALLENGE Over and under-provisioned resources with low visibility #### CLOUDKEEPER APPROACH EC2 rightsizing, idle cleanup, and centralized reporting #### MEASURABLE IMPACT Identified **over 4% monthly AWS savings,** driven mainly by EC2 optimization **Pioneering end-to-end cloud management** **Ranked #1** in User Satisfaction based on 100% genuine customer reviews for Cloud Management * CloudKeeper Tuner not only **saved us thousands by removing unused resources but also helped modernize our architecture for better performance**. Our engineers now get live, in-console savings opportunities—like having an **always-on assistant built for scale and speed**. Pratish Arora. Principal DevOps Engineer, NetRoadshow * CloudKeeper is a game-changer for cloud cost management. It is **essential for controlling cloud spend** and making the most out of the infrastructure. It’s become a **vital part of our cost management toolkit**. Aakash Sharma Lead CloudOps at Seclore * I would consider it as a **One-stop solution** for my cloud spending/ reservations/ saving recommendations and optimisation efforts. Their Tuner **tool has been a great addition** to our account, helping us with real-time saving opportunities. Sunny Chhatija. Engineering Manager * CloudKeeper Tuner delivers comprehensive **visibility into our cloud usage patterns** and identifies **actionable savings opportunities** that would be **nearly impossible to detect through native AWS CloudWatch** monitoring alone. Its strength lies in **surfacing hidden inefficiencies** across AWS services. For any organization serious about AWS cost governance, **I highly recommend evaluating Tuner.** Mahesh V. CTO Frequently Asked **Questions** * ### Arrow 1.What is cloud workload rightsizing? Q1. What is cloud workload rightsizing? Cloud workload rightsizing is the practice of aligning cloud resources - such as instances, databases, and containers - to the actual performance and capacity needs of applications, instead of overprovisioning “just in case.” It uses utilization and performance data to recommend smaller, cheaper, or more appropriate resource types. * ### Arrow 2.How does rightsizing work with autoscaling? Q2. How does rightsizing work with autoscaling? Rightsizing ensures your instances and containers are correctly sized, while autoscaling adjusts capacity based on demand. Together, they ensure workloads scale efficiently without unnecessary cost. * ### Arrow 3.What is cloud workload scheduling, and why does it matter? Q3. What is cloud workload scheduling, and why does it matter? Cloud workload scheduling is turning resources off - or scaling them down - when they’re not needed, like nights and weekends for non‑production workloads. It matters because many environments do not need to run 24×7, and turning them off during idle periods directly reduces your cloud bill. * ### Arrow 4.How does CloudKeeper keep optimization safe for production workloads? Q4. How does CloudKeeper keep optimization safe for production workloads? CloudKeeper combines data‑driven recommendations with collaborative workflows, approvals, and guardrails. Your teams and CloudKeeper’s experts jointly review changes, start with low‑risk workloads, and only automate what you’re comfortable with. * ### Arrow 5.How quickly can we see savings from rightsizing and scheduling? Q5. How quickly can we see savings from rightsizing and scheduling? Most organizations realize quick‑win savings from scheduling and low‑risk rightsizing within the first few weeks, followed by deeper, policy‑driven gains over the next few cycles as more workloads and environments are brought into scope. * ### Arrow 6.What is CloudKeeper Tuner & Scheduler? Q6. What is CloudKeeper Tuner & Scheduler? CloudKeeper Tuner is our proprietary automated usage optimization & recommendation platform that acts as a real-time assistant and easily fits into your flow of work across multiple cloud accounts. It delivers tailored recommendations and enables you to optimize resources effortlessly while maintaining peak performance for your workloads. * ### Arrow 7.What role does the CloudKeeper Customer Success team play in optimization? Q7. What role does the CloudKeeper Customer Success team play in optimization? Every customer is supported by a dedicated FinOps Strategist, Solutions Architect, and Customer Success Partner. They validate opportunities, align stakeholders, coordinate execution, and ensure savings are implemented and sustained—not just identified. * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * close close