ChaosBlade vs Krkn-AI
ChaosBlade
chaosblade.ioKrkn-AI
github.comSide by side
| Figure | ChaosBlade | Krkn-AI |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Chaos Engineering Platforms | 8.2 (#7) | 8.0 (#10) |
| Deployment | The CLI can be downloaded and unpacked on a host, while the tool and platform also document Kubernetes installation using Helm. | Krkn-AI can be installed as a Python CLI or run from a pre-built container image, including on Kubernetes. |
| Integrations | ChaosBlade-Box uses Helm for deployment management and integrates Prometheus monitoring. | The documented setup uses Krkn scenarios, krknctl, Kubernetes or OpenShift, and Prometheus metrics. |
| Purpose | The project aims to help enterprises address high-availability problems during cloud-native adoption through chaos engineering. | Krkn-AI automatically runs chaos scenarios and discovers experiments to evaluate system resilience. |
Plans
In their own words
ChaosBlade
ChaosBlade is a free, open-source chaos engineering project comprising the ChaosBlade experiment tool and the ChaosBlade-Box platform. Its stated aim is to help enterprises address availability problems during cloud-native adoption. Experiments cover CPU, memory, network, disk, processes, kernels, and files, as well as multilingual applications and Kubernetes resources. They can run through the command-line interface, Kubernetes YAML and CRDs, HTTP server calls, or the Box interface. ChaosBlade-Box provides a shared experiment interface, automates deployment of experiment tools, and can host ChaosBlade and LitmusChaos. It uses Helm for deployment management and integrates Prometheus monitoring. Safety policies support manual stopping or automatic stopping after a configured timeout. Users can download and unpack the CLI on a host, or install the tool and platform on Kubernetes with Helm. The host installation guide lists Java and MySQL requirements; automatic probe installation also needs Ansible and expect. The project supports Kubernetes and is identified as a Cloud Native Computing Foundation sandbox project.
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.