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Chaos Toolkit

Chaos Toolkit is an open-source chaos engineering toolkit for developers exploring systems to find weaknesses.

Place
#1 of 25
Score
7.4
Chaos Toolkit's website

What Chaos Toolkit is

Chaos Toolkit is an open-source chaos engineering toolkit for developers exploring systems to find weaknesses. An experiment defines a steady-state hypothesis and probes to check it, alongside a method made of actions and probes. If the system does not meet the steady state, the method is not applied and the experiment must bail out. Experiments can be declared and saved as JSON or YAML, 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 free 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 add extensions after installing the CLI and core library. Reliably is described separately, with SaaS, private SaaS and on-premises options.

Good

  • Free standalone CLI under Apache License 2.0.
  • Experiments can be stored as JSON or YAML.
  • Can be embedded in a CI/CD chain.
  • A failed steady-state check prevents the method.

Watch out

  • Officially supports Python 3.8 and later.
  • Only tested against CPython.
  • Extensions must be installed separately.

Who it suits

Chaos Toolkit suits developers who want to define and run system experiments in code or CI/CD workflows. Its Python CLI and installable extensions are relevant for teams working with supported systems and integrations.

Verdict

Chaos Toolkit offers a free CLI for defining experiments and connecting them to development workflows. Check its Python runtime requirements and available extensions against your environment.

Plans and prices

From Chaos Toolkit's own pricing page, checked 15 Oct 2026.

All about pricing
PlanPriceWhat it gives you
Chaos ToolkitFreeopen-source CLI · free forever · standalone toolkit

The facts

Each one read from Chaos Toolkit's own pages, with the date it was checked.

What it does

Automation
The toolkit is designed to run inside CI/CD workflows.checked 15 Oct 2026
Community
The project invites contributions through issue reports, issue voting, project stars, community Slack, pull requests and extension proposals.checked 28 Sep 2026
Community support
The project directs users to community Slack, Stack Overflow, GitHub issues and a project email address.checked 15 Oct 2026
Container architectures
Docker Hub lists official images for linux/amd64 and linux/arm64.checked 15 Oct 2026
Containers
Official container documentation lists latest, basic and full images, with Alpine and Debian-based variants.checked 15 Oct 2026
Core projects
The project includes separate CLI, core-library, Kubernetes, addons, reporting and bundler projects.checked 15 Oct 2026
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.checked 28 Sep 2026
Discovery
The chaos discover command can inspect an integration and produce a discovery report used to bootstrap experiments.checked 15 Oct 2026
Experiment as code
Experiments can be stored as JSON or YAML files so teams can review, version and orchestrate them like code.checked 15 Oct 2026
Experiment execution
A basic experiment is run with the command chaos run experiment.json.checked 15 Oct 2026
Experiment format
Experiments can be declared and stored as JSON or YAML files for collaboration and orchestration like other code.checked 28 Sep 2026
Experiment model
Experiments use probes to collect system information and actions to perform operations against the system.checked 15 Oct 2026
Experiments
An experiment declares a steady-state hypothesis and probes to validate it, plus a method made up of actions and probes.checked 28 Sep 2026
Extension methods
Extensions can be implemented as Python functions, external processes or HTTP endpoints.checked 15 Oct 2026
Extensions
After installing the CLI and core library, users can install extensions for different facets of chaos engineering.checked 28 Sep 2026
Independent limit: extension dependency
Hysen Labs says platform-specific actions depend on separately installed extensions and that extension maintenance can become a compatibility risk.checked 15 Oct 2026
Independent limit: interface
Gremlin reports that the toolkit is CLI-only, which makes multi-system execution difficult without suitable cloud or orchestration drivers.checked 15 Oct 2026
Independent limit: missing features
Gremlin’s comparison lists no native scheduling, GUI or REST API in the core toolkit.checked 15 Oct 2026
Independent praise: control
Gremlin highlights the toolkit’s user-defined experiments and native rollback capability as strengths.checked 15 Oct 2026
Independent praise: portability
Gremlin’s comparison says Chaos Toolkit lets users define their own experiments and supports Docker, Kubernetes, bare-metal and cloud platforms.checked 15 Oct 2026
Installation
The documented installation method is pip install -U chaostoolkit inside a Python environment.checked 15 Oct 2026
Integrations
The extension directory lists integrations including AWS, Azure, Google Cloud Platform, Kubernetes, Kafka, Slack, Datadog, Grafana, OpenTelemetry and Prometheus.checked 28 Sep 2026
Kubernetes operator
A Kubernetes operator can watch experiment resources and launch Chaos Toolkit jobs to execute them.checked 15 Oct 2026

Money

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.checked 15 Oct 2026
The full review of Chaos Toolkit

Chaos Toolkit is an open-source toolkit for developers who want to probe systems for weaknesses through structured experiments. It is best suited to teams comfortable with a Python CLI and self-managed deployment. Its code-based experiments and steady-state safety gate are useful strengths, but it is not a managed chaos engineering service.

Overview

Experiments are saved as JSON or YAML, allowing teams to keep them alongside other code and use familiar collaboration and orchestration practices. Each combines a steady-state hypothesis and validating probes with a method of actions and probes. If the steady state is not met, the method is withheld and the experiment must bail out. That precondition is a meaningful guardrail for teams injecting faults, though it does not replace careful experiment design.

The project is open source under Apache License 2.0, and its community welcomes issue reports, voting, stars, Slack participation, pull requests and extension proposals. Its contribution guide recommends that contributors enable two-factor authentication to reduce account-compromise risk.

Key features

Automation and integrations

Chaos Toolkit can be embedded in a CI/CD chain, making it a fit for teams that want experiments to be part of their development workflow. Its Open API supports extensions for different systems; users install those after the CLI and core library. Integrations include AWS, Azure, Google Cloud Platform, Kubernetes, Kafka, Slack, Datadog, Grafana, OpenTelemetry and Prometheus. That breadth can connect experiments to varied environments, but teams should expect to select and install the extensions they need.

Experiment controls

It supports Kubernetes, cloud and network fault injection, experiment scheduling and blast-radius controls. Those capabilities cover both experiment execution and containment, which is useful for teams seeking a configurable toolkit rather than a narrow fault simulator. The CLI is self-hosted, so teams remain responsible for their own environment and workflow.

Pricing

The Chaos Toolkit plan costs free and is free forever under Apache License 2.0. It provides the open-source CLI without a paid-plan upgrade requirement stated. There are no published seat or usage caps in this plan description, but the free offering is the standalone CLI rather than the separate Reliably platform, which has SaaS, private SaaS and on-premises options.

Platforms

The toolkit is available for API, Linux, macOS, self-hosted, web and Windows environments. Its CLI is implemented in Python 3 and officially supports Python 3.8 and later; it has only been tested against CPython. The installation guide covers Python setup on macOS, Debian or Ubuntu, and Windows, and installs the CLI with pip. Teams using other Python implementations should account for the narrower tested runtime support.

Who it's for

Chaos Toolkit suits development and reliability teams that want experiments stored as code, integrated into CI/CD, and extended to cover their systems. It is especially compelling for teams able to manage Python and self-hosted tooling. Readers looking for a turnkey managed platform should consider a different product.

Pros and cons

  • Pro: JSON or YAML experiment definitions can live with other code, supporting collaboration and orchestration practices familiar to development teams.
  • Pro: A failed steady-state check prevents the experiment method from running, providing a clear safety condition.
  • Pro: The free, Apache-licensed CLI supports scheduling, blast-radius controls, Kubernetes, and cloud and network fault injection.
  • Con: The CLI depends on Python 3.8+ and is tested only against CPython, constraining runtime choices.
  • Con: The standalone CLI is self-hosted; teams seeking SaaS or managed operations need another option.

Alternatives

For a broader comparison, browse Chaos Engineering Platforms.

  • Reliably is worth considering for teams seeking a freemium alternative that describes itself as open source and emphasizes avoiding lock-in.
  • ChaosBlade is another free, open-source chaos engineering tool, with stated support for three system platforms, four programming-language applications and more than 200 experiment scenarios.
  • Chaos Mesh is a free, open-source cloud-native chaos engineering platform that runs on Kubernetes.
  • PowerfulSeal offers self-hosted Kubernetes chaos testing with pip or Docker installation.
  • AWS Fault Injection Service is a paid option billed at $0.10 per action-minute, with an additional $0.10 per action-minute for each additional account; AWS GovCloud (US-East and US-West) is $0.12 per action-minute.
  • Gremlin may suit teams considering a paid platform: its trial is free for 30 days, requires no credit card and does not auto-convert.
  • Steadybit is a paid alternative with Professional and Enterprise plans; Enterprise includes on-prem installation, SAML, audit log and enterprise support.
  • Toxiproxy is a free alternative available for Windows, macOS and Linux.

Verdict

Choose Chaos Toolkit if your team wants a free, extensible way to define experiments as code and bring them into development workflows, while retaining control over a self-hosted Python CLI. Look elsewhere if you need a managed service or cannot accommodate its Python runtime requirements.

Getting started

  1. Open the Chaos Toolkit website
  2. Install Python 3.8 or newer on macOS, Debian or Ubuntu, or Windows
  3. Install the CLI and core library with pip
  4. Add extensions for the systems or services you want to test
  5. Store experiments as JSON or YAML files
  6. Embed the toolkit in a CI/CD chain if needed

Limits worth knowing

The free offering is the standalone open-source CLI. It requires Python 3.8 or newer and is deployed in a self-hosted model.

Questions

What does Chaos Toolkit cost?

The Chaos Toolkit plan is free forever at 0.00 USD, under the Apache License 2.0.

Which platforms does it support?

Listed platforms are API, Linux, macOS, self-hosted, web, and Windows.

Is Chaos Toolkit open source?

Yes. The toolkit is open source under the Apache 2 license.

Which runtime does the CLI use?

The CLI is implemented in Python 3, officially supports Python 3.8 and later, and has only been tested against CPython.

Can it integrate with Kubernetes and cloud services?

Yes. Listed integrations include Kubernetes, AWS, Azure, Google Cloud Platform, Kafka, Slack, Datadog, Grafana, OpenTelemetry, and Prometheus.

Alternatives to Chaos Toolkit

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