Catch Google Cloudcost waste before it ships
Ship faster. Stay optimized. Automatically on each PR.
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Cloud cost waste is committed in code long before it shows up on a billing dashboard. AI-assisted coding makes it worse: more PRs, faster merges, and few guardrails between commit and production.
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Rabbit Agentic shifts automated Google Cloud cost optimization left into your pull requests, IDE, and coding agents. Optimize GCP pricing and usage to catch waste before it's deployed.
Agentic cloud cost optimization with Rabbit
Rabbit Agentic draws from Rabbit's deep Google Cloud knowledge (pricing patterns, resource relationships, and optimization heuristics) to provide 3 key features for visibility and optimization before waste hits production.
Cost-focused code review
Like having a senior GCP architect on every code review, focused on optimizing cloud cost efficiency. Rabbit analyzes the diff, posts inline comments on identified cost issues and proposed optimization, and adds a summary with the rolled-up cost delta.
Severity-rated findings
Cost estimates in specific $ impact
GitHub-native, ready-to-merge suggestions
Fully automatic, with on-demand re-runs
Context enrichment for coding agents
Cost-aware, repo-wide context for Claude Code, Cursor, OpenAI Codex, and GitHub Copilot with GCP optimization knowledge baked in. Established best practices tailored to your environment, within your current agentic workflows.
Agentic optimization plugins with repo-wide context
Reads your entire infrastructure, not just what fits in a chat prompt
Ready-to-apply code blocks your agent can merge directly
Recommendation Applier
Automatically turn Rabbit's recommendations into ready-to-merge pull requests. For Rabbit users, the Recommendation Applier is the proactive counterpart to PR review's reactive analysis, autonomously fixing existing waste while you stay in control.
Automated, ready-to-apply PRs implementing Rabbit recommendations
PRs include estimated savings table, recommendation links, and a clean diff
Actionable, resource-level guidance
No generic spend alerts. Based on a decade of optimization expertise, Rabbit Agentic delivers concrete, resource-level guidance on the GCP services in your stack:
Estimates query costs and flags savings in partitioning, clustering, expiration, materialized views, and billing model choice.
Surfaces autoscaling gaps, oversized workloads, missed Spot, and configurations that keep idle capacity running.
Rightsizes VMs and instance groups to match workloads to the best machine family and size, including custom types.
Tunes CPU, memory, concurrency, and scaling so each service runs lean without hurting latency or reliability.
Checks storage classes, lifecycle rules, and version retention so cold data stops paying hot-data prices.
Flags over-provisioned tiers, unnecessary high-availability configurations in non-production, and node sizing that no longer fits the workload.
Reviews egress patterns, load balancers, CDN coverage, and network tier choices to cut data-transfer costs and unused resources.
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Labels, commitment candidates, and environment-aware sizing so dev doesn't ship with production-scale resources.
Catch and fix cloud cost issues before they reach production.
Integrate in minutes
GitHub App
Automated cost review comments directly on your PRs
2.
Click Add/Install to set up the app
3.
Let us know when you're done so we activate Rabbit on our side