What's New with CloudKeeper?

Migrate eligible standalone Intel-based Compute Engine VMs to their AMD-based equivalent machine types across all GCP projects. The AMD-based equivalent preserves the same vCPU count and memory while running at a lower price point.

This recommendation identifies Google Cloud Storage buckets that contain incomplete multipart uploads.

This recommendation identifies BigQuery tables that have remained inactive for extended periods and may be suitable for deletion or lifecycle management. 

This recommendation focuses on identifying stale AlloyDB backups and recommending their deletion to reduce unnecessary storage costs

Securely access CloudKeeper Tuner insights directly from AI assistants like Cursor, Claude, Kiro, and VS Code Copilot using natural language—without leaving your workflow. 

App Engine support to the Scheduler, enabling automatic start and stop scheduling for App Engine versions to reduce compute costs during off-hours.

We've extended the GCP Resource-Based Scheduler on CK Tuner to support Stateless Managed Instance Groups (MIGs). Customers can now automate Stop/Start actions on their MIGs to reduce compute costs during off-hours or low-traffic windows.

Label-Based Scheduler is now available on GCP Tuner, enabling customers to automate start and stop actions for GCP resources using labels and recurring schedules to reduce compute costs.

Create and track Jira tickets directly from Tuner recommendations to accelerate resolution and streamline cost optimization workflows.

Automatically run workloads on Spot Instances with intelligent interruption handling and On-Demand fallback for maximum savings and reliability.