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Canonical Chaos Engineering Platform vs Krkn-AI

Both stand on chaos engineering platforms. Which one you can start free with, which one lets you read the code, and what each costs once you pay.

Canonical Chaos Engineering Platform

Free plan LinuxSelf-hostedWeb

Teams focused on Kubernetes chaos experiments should consider the platform for its open source model and documented recovery checks. Teams needing charmed VM cloud testing should look elsewhere for those capabilities.

Visit Canonical Chaos Engineering Platform

Krkn-AI

Free plan LinuxSelf-hosted

Krkn-AI provides a way to automate resilience experiments and monitor their results in Kubernetes and OpenShift environments. Review its prerequisites and development-status warning before adopting it.

Visit Krkn-AI

The facts

Canonical Chaos Engineering PlatformKrkn-AI
Free planYesYes
Open sourceNot publishedNot published
Runs onLinux, Self-hosted, WebLinux, Self-hosted
Lowest paid planNot publishedFree or on request
Plans publishedNone1
MakerNot publishedNot published
Websitecanonical-chaos-engineering.readthedocs-hosted.comgithub.com
On chaos engineering platforms#7 of 25#11 of 25

Canonical Chaos Engineering Platform: what it does well

  • Free and open source, with community contributions welcomed.
  • Tutorial demonstrates a pod deletion and recovery probe.
  • Supports Kubernetes chaos testing.
  • Experiment scheduling and blast-radius controls are listed.
  • Documentation describes TLS for internal and external connections.

What to know first

  • The current scope excludes charmed VM cloud chaos testing.
  • Charmed Litmus currently wraps only the control plane.
  • A documented upstream bug leaves control-plane to MongoDB traffic unencrypted.
  • A forgotten changed admin password may require manually deleting database tables or redeploying MongoDB to reset.

Krkn-AI: what it does well

  • Free and open source under Apache-2.0.
  • Generates experiments from Krkn scenarios.
  • Uses user-defined objectives such as SLOs and health checks.
  • Reports liveness impact and fitness scores.
  • Offers CLI and pre-built container deployment.

What to know first

  • Requires a Kubernetes or OpenShift cluster kubeconfig.
  • Requires Python 3.11 or later and several tools.
  • The project is under active development and advises caution.

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