FaultMesh
7.2#1 in chaos engineering platformsFrom $49 a monthFree planWebAPISelf-hosted
VisitFaultMesh vs Krkn-AI
What both publish
| Fact | FaultMesh | Krkn-AI |
|---|---|---|
| Audience | Starter is described for small teams beginning chaos engineering, Growth for teams making it routine, and Enterprise for organizations running FaultMesh inside their own perimeter. | The project is intended for testing the resilience of Kubernetes and OpenShift applications. |
| Deployment | FaultMesh is available as managed SaaS or as a Kubernetes Operator deployed in the customer's cluster, where data stays inside the perimeter. | Krkn-AI can be installed as a Python CLI or run from a pre-built container image, including on Kubernetes. |
| Purpose | FaultMesh injects controlled failures, detects anomalies in real time, remediates automatically and scores system resilience on a Kubernetes-native platform. | Krkn-AI automatically runs chaos scenarios and discovers experiments to evaluate system resilience. |
FaultMesh plans
- StarterFree
- Growth$49 a month
- EnterprisePriced on request
Krkn-AI plans
- Apache License 2.0Free
Pick FaultMesh if…
Starter is described for small teams beginning chaos engineering, while Growth suits teams making it routine. Enterprise is aimed at organizations that want to run FaultMesh inside their own perimeter.
Pick Krkn-AI if…
Krkn-AI suits teams evaluating the resilience of Kubernetes or OpenShift applications. It requires a cluster kubeconfig and the listed command-line and container tooling.