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Kubernetes HPA Calculator & Simulator

Calculate CPU and memory utilization recommendations with replica bounds, stabilization windows and scaling policies. Replay CSV observations locally and export autoscaling/v2 YAML.

Your configuration stays in this browser
No cluster access, kubectl execution or configuration uploads. Anonymous operation events contain only operation types and size/time buckets, never input values.
Advanced scaling behavior

Scale up

Scale down

Start with a sample or enter your configuration, then run the tool.

Model boundaries
Deterministic aggregate CPU/memory utilization model, not a Kubernetes controller replica. Assumes all Pods ready with requests set. Does not model per-Pod missing metrics, readiness delays, scheduling, custom/external metrics or prehistory before the first row. Bounds, windows and policy event history are modeled.

About Kubernetes HPA Calculator & Simulator

Calculate replicas, replay utilization and generate HPA YAML. Calculate CPU and memory utilization recommendations with replica bounds, stabilization windows and scaling policies. Replay CSV observations locally and export autoscaling/v2 YAML. The core workflow is designed to run in your current browser.

Key capabilities

  • Process inputs locally without connecting to a cluster
  • Start with a sample and review each result
  • Explain modeled rules and unsupported behavior
  • Export reviewable configuration and analysis

Useful for

  • Review a proposed configuration before applying it
  • Understand a result using a reproducible offline example

Frequently asked questions

Is Kubernetes HPA Calculator & Simulator free to use online?

Yes. Kubernetes HPA Calculator & Simulator opens in a modern browser and does not require desktop software installation.

What is Kubernetes HPA Calculator & Simulator useful for?

Common use cases include Review a proposed configuration before applying it; Understand a result using a reproducible offline example.

Is my input or file uploaded?

The core processing workflow is designed to run locally in the browser. Key capabilities include Process inputs locally without connecting to a cluster, Start with a sample and review each result, Explain modeled rules and unsupported behavior; account, comments, and anonymous analytics may still create normal site requests.

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