Chaos Mesh vs Chaos Toolkit

Chaos Mesh is a free, open-source platform for running fault simulations in development, testing, and production environments. It runs on Kubernetes and manages experiments through Kubernetes CustomResourceDefinitions and the Kubernetes API. Fault simulations cover areas including Pods, networks, DNS, HTTP, I/O, time, stress, kernels, block devices, JVMs, physical machines, and AWS, Azure, and GCP. Schedule, Workflow, and StatusCheck resources support recurring experiments, serial or parallel workflows, and application health checks. Selectors and namespace controls help scope experiments to chosen targets. Chaos Dashboard offers a web interface and HTTP API for creating, managing, and observing experiments, with role-based access control enabled by default. Chaos Mesh is licensed under Apache License 2.0 and can be installed from its Helm repository using Helm 3. Compatibility varies by release: version 2.8 supports Kubernetes 1.30 through 1.35, while version 2.7 supports 1.26 through 1.28. Its privileged Chaos Daemon runs as a Kubernetes DaemonSet by default, though that permission can be disabled. Community support is available through CNCF Slack and GitHub Discussions.

Chaos Toolkit is a free, open-source chaos engineering toolkit for developers exploring systems to uncover weaknesses. Experiments define a steady-state hypothesis and probes to check it, along with a method of actions and probes. If the system does not meet the stated steady state, the method is not applied and the experiment must stop. Experiments can be declared in JSON or YAML files, making them suitable for collaboration and orchestration alongside code. The toolkit extends to systems through its Open API and can be embedded in a CI/CD chain. Listed integrations include AWS, Azure, Google Cloud Platform, Kubernetes, Kafka, Slack, Datadog, Grafana, OpenTelemetry, and Prometheus. The standalone CLI is available under Apache License 2.0. It is implemented in Python 3, officially supports Python 3.8 and later, and has only been tested against CPython. Installation instructions cover macOS, Debian or Ubuntu, and Windows; users can install extensions after the CLI and core library. Reliably is a separate platform with SaaS, private SaaS, and on-premises options.