Krkn-AI vs kube-monkey
Krkn-AI
github.comkube-monkey
github.comSide by side
| Figure | Krkn-AI | kube-monkey |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Linux | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Chaos Engineering Platforms | 8.0 (#10) | 7.2 (#19) |
| Installation | The README provides installation from source or directly from the GitHub repository using uv and Python 3.11 or later. | The README provides Helm installation instructions for deploying kube-monkey into the kube-system namespace. |
| License | The public repository is licensed under Apache-2.0. | The repository is distributed under the Apache License 2.0. |
| Metrics | Fitness evaluation can measure system response using Prometheus metrics. | The project documentation lists a Prometheus metrics endpoint. |
| Purpose | Krkn-AI automatically runs chaos scenarios and discovers experiments to evaluate system resilience. | Implements Netflix’s Chaos Monkey for Kubernetes by randomly deleting pods to help develop and validate failure-resilient services. |
| Support | The project documentation links to a community Slack, GitHub issues, and contribution guidelines. | The README directs contributors to the Kubernetes Slack #kube-monkey channel and project contribution guidance. |
Plans
In their own words
Krkn-AI
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.
kube-monkey
kube-monkey has no write-up on Specifiction yet; its figures are above.