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Chaos Toolkit vs Krkn

Chaos Toolkit

chaostoolkit.org

Krkn

krkn-chaos.dev

Side by side

FigureChaos ToolkitKrkn
Price fromFreeFree
Free planYesYes
Free trial——
Open sourceYes—
WebYesYes
WindowsYes—
macOSYes—
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published11
Spec score · Chaos Engineering Platforms8.8 (#3)8.5 (#5)
Deployment optionsThe offering page describes a standalone open source CLI; it distinguishes Reliably as a separate platform with SaaS, private SaaS and on-premises options.Krkn offers a CLI, pre-built container images, a browser-based dashboard, and a standalone Python program.
IntegrationsThe extension directory lists integrations including AWS, Azure, Google Cloud Platform, Kubernetes, Kafka, Slack, Datadog, Grafana, OpenTelemetry and Prometheus.The documentation describes integrations with Prometheus, Elasticsearch, Grafana, Slack, S3, and CI/CD systems such as Jenkins and GitHub Actions.
PurposeChaos Toolkit is a chaos engineering toolkit for developers to explore and test systems to discover weaknesses.Krkn injects deliberate failures into Kubernetes clusters to test their resilience.

Plans

Chaos Toolkit

  • Chaos ToolkitFree

Chaos Toolkit pricing →

Krkn

  • KrknFree

Krkn pricing →

In their own words

Chaos Toolkit

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.

Visit chaostoolkit.org

Krkn

Krkn injects deliberate failures into Kubernetes clusters so teams can examine resilience under disruption. Its 20-plus scenarios cover pods, containers, nodes, networks, applications, resources, storage and time. The recommended krknctl command-line tool discovers, runs and coordinates scenarios; other choices include pre-built containers, a browser dashboard and a standalone Python program. Krkn evaluates Prometheus metrics against SLO pass/fail criteria and can review metrics during and after scenarios. Dashboard integrations include Elasticsearch and Grafana, and telemetry can be sent to S3 or Elasticsearch. Cerberus monitors Kubernetes and OpenShift health, providing a go/no-go signal, reports and a metrics API; it can also report failures in Slack. Krkn-AI uses evolutionary algorithms against user-defined objectives to identify experiments. Krkn says it saves recovery state and can restore a cluster, but some disruptive scenarios may leave the target unrecoverable. It is intended for resilience measurement, not security provision, and does not currently adhere to compliance standards. Requirements include Kubernetes or OpenShift 1.21+, cluster-admin kubeconfig access, and Docker 20.10+ or Podman 4.0+.

Visit krkn-chaos.dev