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Chaos Toolkit

chaostoolkit.org

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Spec score 8.8 #3 of 25 in Chaos Engineering Platforms

What it is

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.

Spec sheet

What it does
Chaos Toolkit is a command-line tool for defining and running controlled chaos-engineering experiments against infrastructure and applications.Read 15 Oct 2026 · chaostoolkit.org
Purpose
Chaos Toolkit is a chaos engineering toolkit for developers to explore and test systems to discover weaknesses.Read 28 Sep 2026 · chaostoolkit.org
Integrations
The extension directory lists integrations including AWS, Azure, Google Cloud Platform, Kubernetes, Kafka, Slack, Datadog, Grafana, OpenTelemetry and Prometheus.Read 28 Sep 2026 · chaostoolkit.org
License
The software is released under the Apache-2.0 license.Read 15 Oct 2026 · github.com
Automation
The toolkit is designed to run inside CI/CD workflows.Read 15 Oct 2026 · chaostoolkit.org
Community
The project invites contributions through issue reports, issue voting, project stars, community Slack, pull requests and extension proposals.Read 28 Sep 2026 · chaostoolkit.org
Community support
The project directs users to community Slack, Stack Overflow, GitHub issues and a project email address.Read 15 Oct 2026 · github.com
Container architectures
Docker Hub lists official images for linux/amd64 and linux/arm64.Read 15 Oct 2026 · hub.docker.com
Containers
Official container documentation lists latest, basic and full images, with Alpine and Debian-based variants.Read 15 Oct 2026 · chaostoolkit.org
Core projects
The project includes separate CLI, core-library, Kubernetes, addons, reporting and bundler projects.Read 15 Oct 2026 · chaostoolkit.org
Deployment options
The offering page describes a standalone open source CLI; it distinguishes Reliably as a separate platform with SaaS, private SaaS and on-premises options.Read 28 Sep 2026 · chaostoolkit.org
Discovery
The chaos discover command can inspect an integration and produce a discovery report used to bootstrap experiments.Read 15 Oct 2026 · chaostoolkit.org
Experiment as code
Experiments can be stored as JSON or YAML files so teams can review, version and orchestrate them like code.Read 15 Oct 2026 · chaostoolkit.org
Experiment execution
A basic experiment is run with the command chaos run experiment.json.Read 15 Oct 2026 · github.com
Experiment format
Experiments can be declared and stored as JSON or YAML files for collaboration and orchestration like other code.Read 28 Sep 2026 · chaostoolkit.org
Experiment model
Experiments use probes to collect system information and actions to perform operations against the system.Read 15 Oct 2026 · chaostoolkit.org
Experiments
An experiment declares a steady-state hypothesis and probes to validate it, plus a method made up of actions and probes.Read 28 Sep 2026 · chaostoolkit.org
Extension methods
Extensions can be implemented as Python functions, external processes or HTTP endpoints.Read 15 Oct 2026 · chaostoolkit.org
Extensions
After installing the CLI and core library, users can install extensions for different facets of chaos engineering.Read 28 Sep 2026 · chaostoolkit.org
Independent limit: extension dependency
Hysen Labs says platform-specific actions depend on separately installed extensions and that extension maintenance can become a compatibility risk.Read 15 Oct 2026 · hysenlabs.com
Independent limit: hosted control plane
Zaira Labs says the file-driven CLI lacks the centralized scheduling, multi-tenant isolation and web UI associated with hosted chaos platforms.Read 15 Oct 2026 · zairalabs.ai
Independent limit: interface
Gremlin reports that the toolkit is CLI-only, which makes multi-system execution difficult without suitable cloud or orchestration drivers.Read 15 Oct 2026 · gremlin.com
Independent limit: missing features
Gremlin’s comparison lists no native scheduling, GUI or REST API in the core toolkit.Read 15 Oct 2026 · gremlin.com
Independent praise: control
Gremlin highlights the toolkit’s user-defined experiments and native rollback capability as strengths.Read 15 Oct 2026 · gremlin.com
Independent praise: portability
Gremlin’s comparison says Chaos Toolkit lets users define their own experiments and supports Docker, Kubernetes, bare-metal and cloud platforms.Read 15 Oct 2026 · gremlin.com
Installation
The documented installation method is pip install -U chaostoolkit inside a Python environment.Read 15 Oct 2026 · chaostoolkit.org
Kubernetes operator
A Kubernetes operator can watch experiment resources and launch Chaos Toolkit jobs to execute them.Read 15 Oct 2026 · chaostoolkit.org
Maker team
The same LinkedIn article characterizes ChaosIQ as a very small team.Read 15 Oct 2026 · linkedin.com
Maker transition
A September 18, 2023 LinkedIn article says ChaosIQ, the company behind the product platform, retired the ChaosIQ brand in favor of Reliably while continuing to use Chaos Toolkit.Read 15 Oct 2026 · linkedin.com
Open API
The project describes an open API intended to support chaos engineering across different systems.Read 15 Oct 2026 · github.com
Provider types
The experiment API defines Python, HTTP and process providers for actions and probes.Read 15 Oct 2026 · chaostoolkit.org
Python SDK pattern
Python extensions conventionally expose actions in actions.py and probes in probes.py.Read 15 Oct 2026 · chaostoolkit.org
Release
PyPI lists Chaos Toolkit 1.21.4 uploaded on October 5, 2026, with a Python 3 universal wheel.Read 15 Oct 2026 · pypi.org
Reporting
The chaostoolkit-reporting plugin can create PDF or HTML reports from executions.Read 15 Oct 2026 · chaostoolkit.org
Repository activity
The verified GitHub organization lists roughly 2,000 stars for the main repository and identifies the project as Python and Apache-2.0 licensed.Read 15 Oct 2026 · github.com
Runtime
Official installation documentation says the CLI requires Python 3.8 or newer and has been tested against CPython.Read 15 Oct 2026 · chaostoolkit.org
Safety gate
If the steady state is not met, the method is not applied and the experiment must bail out.Read 28 Sep 2026 · chaostoolkit.org
Secrets API
The experiment specification supports named secrets and lets providers reference the secrets required by an action or probe.Read 15 Oct 2026 · chaostoolkit.org
Security practice
The contribution guide suggests contributor accounts enable 2FA to reduce security risks if an account is breached.Read 28 Sep 2026 · chaostoolkit.org
Security signal
Zaira Labs reports an OpenSSF Scorecard result of 3.7 out of 10 and zero listed security advisories for the project snapshot it reviewed.Read 15 Oct 2026 · zairalabs.ai
Self-hosting
The standalone toolkit runs locally or in user-managed environments, while the separate Reliably product provides hosted and private deployment options.Read 15 Oct 2026 · chaostoolkit.org
Supported runtime
The CLI is implemented in Python 3, officially supports Python 3.8+, and has only been tested against CPython.Read 28 Sep 2026 · chaostoolkit.org

Plans and prices

Chaos Toolkit Free open-source CLI · free forever · standalone toolkit Read 15 Oct 2026 · chaostoolkit.org

Every Chaos Toolkit plan and price →

Strong points and limits

Strong points

  • Free CLI under Apache License 2.0
  • Experiments can be stored as JSON or YAML
  • Can be embedded in a CI/CD chain
  • Includes a safety gate for unmet steady state

Limits

  • Requires Python 3.8 or later
  • Tested only against CPython
  • Extensions require the CLI and core library

Who it suits

Chaos Toolkit suits developers who want to describe and run system experiments alongside code. Its API, CI/CD embedding, and listed integrations are relevant to teams working with cloud, container, or observability systems.

Chaos Toolkit in depth

Read the full write-up

Chaos Toolkit is a free, open-source chaos engineering CLI for developers who want to express system experiments as code. It is best suited to teams comfortable with Python and self-hosting; its defining strength is a steady-state gate that stops an experiment’s method from running when its precondition fails.

Overview

Experiments are declared in JSON or YAML, which lets teams keep them alongside other code and use familiar collaboration and orchestration practices. Each experiment sets a steady-state hypothesis, uses probes to validate it, and defines a method of actions and probes. If steady state is not met, the method is withheld and the experiment must bail out. That is a useful safeguard for teams injecting faults, though it does not replace careful experiment design.

The offering is a standalone CLI, not the separate Reliably platform. Teams choosing Chaos Toolkit take responsibility for installing and operating it in their own environment rather than selecting Reliably’s SaaS, private SaaS or on-premises options.

Key features

Experiments as code

The CLI can be embedded in a CI/CD chain, making it a fit for teams that want experiments in their delivery workflow. Its Open API supports extensions for different systems. After installing the CLI and core library, users can add extensions for the facets of chaos engineering they need. The extension directory includes AWS, Azure, Google Cloud Platform, Kubernetes, Kafka, Slack, Datadog, Grafana, OpenTelemetry and Prometheus.

Fault injection and controls

Chaos Toolkit supports Kubernetes, cloud and network fault injection, experiment scheduling and blast-radius controls. That combination gives teams several ways to scope and automate experiments, rather than limiting them to writing definitions. The toolkit’s extension model is also relevant to teams working across different systems, but using it means managing the CLI and extensions themselves.

Open source and community

Apache License 2.0 and an invitation to contribute through issue reports, voting, stars, Slack, pull requests and extension proposals make the project suitable for teams that value an open development model. Its contribution guide recommends enabling two-factor authentication on contributor accounts as a measure against account compromise.

Pricing

Chaos Toolkit — free. The plan is an open-source CLI, free forever under Apache License 2.0. There is no paid plan in this offering; it is a strong fit for teams that want to run the toolkit themselves without a software charge, but it is not a substitute for a managed service.

Platforms

The deployment model is self-hosted, with platform coverage listed for API, Linux, macOS, web and Windows. The CLI is implemented in Python 3, officially supports Python 3.8 and later, and has been tested only against CPython. Installation instructions cover Python setup on macOS, Debian or Ubuntu, and Windows, followed by installation of the CLI with pip. That gives teams several supported setup paths, while making Python runtime management part of adoption.

Who it's for

Choose Chaos Toolkit if your team wants code-defined experiments, a safety condition before fault-injection methods run, and the ability to add system integrations or place experiments in CI/CD. It is less suitable if you want a managed service, or if your team does not want to operate a Python CLI and its extensions.

Pros and cons

Useful precondition for experiments: a failed steady-state check prevents the method from running, reducing the chance of proceeding when the declared hypothesis is not satisfied.

Works with code-based workflows: JSON or YAML experiment files and CI/CD embedding suit teams that want experiments treated like other code.

Extensible across systems: the Open API and integrations for cloud, orchestration, messaging and observability systems give teams options to adapt the toolkit to their environment.

Free and open source: the CLI costs nothing and uses Apache License 2.0.

Requires self-management: users install the Python CLI and extensions themselves; teams looking for an operated platform should consider a separate offering.

Python constraint: the CLI officially supports Python 3.8+ and has only been tested against CPython, which may narrow runtime choices.

Alternatives

Chaos Engineering Platforms is the broader category to browse when comparing options.

Reliably is worth considering if you want a separate platform and a free plan capped at one team member; it describes itself as open source and says its approach avoids lock-in.

ChaosBlade is another free, open-source chaos engineering tool, with support for three system platforms, four programming-language applications and more than 200 experiment scenarios.

FaultMesh may suit teams seeking a hosted option with a free Starter plan for up to three services, core fault types, basic resilience scoring and community support, or a Growth plan priced at $49 a month.

Krkn is another free option if you want a tool with no stated pricing or usage limits.

Toxiproxy is a free, open-source TCP proxy under the MIT license, an alternative for readers looking specifically for that kind of tool.

Chaos Mesh is a free, open-source, cloud-native chaos engineering platform that runs on Kubernetes, making it a natural alternative for Kubernetes-focused teams.

Gremlin is an option if you prefer a paid platform and want to evaluate it through its 30-day free trial, which requires no credit card and does not auto-convert.

Steadybit is another paid option; its Enterprise plan includes on-prem installation, SAML, audit log and enterprise support.

Verdict

Chaos Toolkit is a good choice for developers who want a free, code-oriented way to run scheduled chaos experiments with a steady-state gate and self-hosted control. Choose it for its open, extensible CLI and workflow fit; look elsewhere if you want a managed platform rather than a Python tool your team operates.

Verdict

Chaos Toolkit gives developers a code-oriented way to define experiments, with a safety condition that prevents the method from running when steady state fails. It is a standalone CLI rather than the separate Reliably platform.

Where Specifiction places it

Alternatives to Chaos ToolkitAll alternatives →