chaosd vs Krkn-AI
chaosd
github.comKrkn-AI
github.comSide by side
| Figure | chaosd | Krkn-AI |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Chaos Engineering Platforms | 7.9 (#11) | 8.0 (#10) |
| Deployment | Chaosd is downloaded and deployed separately from Chaos Mesh. | Krkn-AI can be installed as a Python CLI or run from a pre-built container image, including on Kubernetes. |
| License | The GitHub repository identifies its license as Apache-2.0. | The public repository is licensed under Apache-2.0. |
| Purpose | Chaosd is a Chaos Engineering tool for injecting and recovering faults in physical machine environments. | Krkn-AI automatically runs chaos scenarios and discovers experiments to evaluate system resilience. |
| Security | The PhysicalMachineChaos guide shows Chaosd configured with TLS certificates and says running the service without generated certificates is not recommended for cluster security. | The project documentation links to a security self-assessment; the repository page does not state a compliance certification. |
Plans
In their own words
chaosd
Chaosd is free Apache-2.0 software for injecting and recovering faults on physical machines. It can create process, network, CPU or memory pressure, disk, and host faults. Use it as a command-line tool or run it as a background service controlled through HTTP requests. Chaosd is deployed separately from Chaos Mesh; PhysicalMachineChaos experiments require service mode on each targeted physical or virtual machine. The documented environment requires glibc 2.17 or later, and the binary download described is a Linux amd64 tarball. Network experiments using tc or iptables require sudo or root privileges. Deployment prerequisites include tc, ipset, and iptables; source builds additionally list stress-ng and byteman. Experiments can be searched and recovered by UID. TLS certificates are shown for service security, and running without generated certificates is not recommended.
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.