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SPECIFICTION
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Krkn-AI

github.com

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Spec score 8.0 #10 of 25 in Chaos Engineering Platforms

What it is

Krkn-AI is a free, open-source tool for automatically running chaos scenarios and finding experiments to evaluate system resilience. It uses evolutionary algorithms to generate experiments from Krkn scenarios, guided by user-defined objectives such as SLOs and application health checks. Its discover command creates a YAML configuration populated with cluster component information and basic setup. Results show the impact of scenarios on application liveness and include fitness scores; Prometheus metrics can measure system response. An interactive dashboard can monitor experiment results. The project describes testing Kubernetes and OpenShift applications and requires a cluster kubeconfig. Krkn-AI can be installed as a Python CLI or run from a pre-built container image, including on Kubernetes. Listed requirements include Python 3.11 or later, krknctl, oc or kubectl, Podman, Helm 3.x, and a Kubernetes or OpenShift cluster kubeconfig. The repository lists the Apache-2.0 license. Its README describes the tool as under active development and advises users to use it at their own risk. The standard container run example uses host networking and privileged mode, while the guide also documents a FUSE-based option without the privileged flag.

Spec sheet

Purpose
Krkn-AI automatically runs chaos scenarios and discovers experiments to evaluate system resilience.Read 10 Oct 2026 · krkn-chaos.dev
Audience
The project is intended for testing the resilience of Kubernetes and OpenShift applications.Read 10 Oct 2026 · github.com
Deployment
Krkn-AI can be installed as a Python CLI or run from a pre-built container image, including on Kubernetes.Read 10 Oct 2026 · github.com
Integrations
The documented setup uses Krkn scenarios, krknctl, Kubernetes or OpenShift, and Prometheus metrics.Read 10 Oct 2026 · github.com
Security
The project documentation links to a security self-assessment; the repository page does not state a compliance certification.Read 10 Oct 2026 · krkn-chaos.dev
Support
The project documentation links to a community Slack, GitHub issues, and contribution guidelines.Read 9 Oct 2026 · krkn-chaos.dev
License
The public repository is licensed under Apache-2.0.Read 10 Oct 2026 · github.com
Algorithm
It uses evolutionary algorithms to generate experiments from Krkn scenarios and guide testing with user-defined objectives such as SLOs and application health checks.Read 10 Oct 2026 · krkn-chaos.dev
Cluster discovery
The discover command can populate configuration with cluster components, runnable scenarios, health check URLs, and Prometheus-validated fitness queries.Read 10 Oct 2026 · krkn-chaos.dev
Container
A pre-built container image is available on Quay.io, and the container guide documents discovery and run modes.Read 9 Oct 2026 · github.com
Container permissions
The documented standard run example uses host networking and privileged mode; the guide also describes a FUSE-based option without the privileged flag.Read 9 Oct 2026 · github.com
Development status
The repository cautions that the tool is under active development and should be used at the user's own risk.Read 10 Oct 2026 · github.com
Evaluation
User-defined objectives such as SLOs and application health checks guide the algorithm.Read 9 Oct 2026 · krkn-chaos.dev
Installation
The README provides installation from source or directly from the GitHub repository using uv and Python 3.11 or later.Read 9 Oct 2026 · github.com
Metrics
Fitness evaluation can measure system response using Prometheus metrics.Read 10 Oct 2026 · github.com
Monitoring
An interactive dashboard can monitor Krkn-AI experiment results.Read 9 Oct 2026 · krkn-chaos.dev
Project affiliation
The Krkn documentation identifies Krkn as a Cloud Native Computing Foundation Sandbox project.Read 9 Oct 2026 · krkn-chaos.dev
Requirements
The project lists Python 3.11+, krknctl, oc or kubectl, Podman, Helm 3.x, and a Kubernetes or OpenShift cluster kubeconfig as prerequisites.Read 10 Oct 2026 · github.com
Results
Users can analyze scenario impact on application liveness and fitness scores, with an interactive dashboard for monitoring experiment results.Read 10 Oct 2026 · krkn-chaos.dev
Supported environments
The project describes testing Kubernetes and OpenShift applications and requires a cluster kubeconfig.Read 9 Oct 2026 · github.com

Plans and prices

Apache License 2.0 Free Open-source software · No commercial pricing or plan limits stated Read 10 Oct 2026 · github.com

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Strong points and limits

Strong points

  • Generates experiments from Krkn scenarios
  • Uses user-defined objectives such as SLOs
  • Reports liveness impact and fitness scores
  • Monitors results in an interactive dashboard
  • Apache-2.0 licensed

Limits

  • Requires a Kubernetes or OpenShift cluster kubeconfig
  • Requires Python 3.11 or later and other listed tools
  • Project advises using it at your own risk
  • Standard container example uses privileged mode

Who it suits

Krkn-AI is intended for teams testing the resilience of Kubernetes and OpenShift applications. It suits users able to provide the listed cluster tooling and kubeconfig, and who can account for its active-development status.

Verdict

Krkn-AI provides an open-source approach to generating and monitoring chaos experiments against Kubernetes and OpenShift applications. Check the prerequisites and container permissions, and account for the project's stated active-development status.

Where Specifiction places it

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