Chaos Monkey for Spring Boot vs Krkn-AI
Chaos Monkey for Spring Boot
codecentric.github.ioKrkn-AI
github.comSide by side
| Figure | Chaos Monkey for Spring Boot | Krkn-AI |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Linux | — | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 1 |
| Spec score · Chaos Engineering Platforms | 7.4 (#16) | 8.0 (#10) |
| Integrations | The documentation describes using Unleash to control feature toggles and springdoc-openapi to show Chaos Monkey endpoints in Swagger UI. | The documented setup uses Krkn scenarios, krknctl, Kubernetes or OpenShift, and Prometheus metrics. |
| Purpose | Chaos Monkey for Spring Boot tests Spring Boot applications by injecting failures during operation. | Krkn-AI automatically runs chaos scenarios and discovers experiments to evaluate system resilience. |
| Support | The project directs bug reports and feature requests to GitHub Issues and general usage questions to Stack Overflow with the spring-boot-chaos-monkey tag. | The project documentation links to a community Slack, GitHub issues, and contribution guidelines. |
Plans
In their own words
Chaos Monkey for Spring Boot
Chaos Monkey for Spring Boot has no write-up on Specifiction yet; its figures are above.
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.