CheckOps
Chaosd
Chaosd is an Apache-2.0 chaos engineering toolkit from the Chaos Mesh project for injecting faults into physical and virtual Linux hosts via a CLI or HTTP service.
- Open source
- Free
- Chaos Engineering
- Command Line
- Production monitoring & observability
- Integration testing
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Introduction
Chaosd injects faults into Linux hosts through a command-line tool or an HTTP service. It is part of the Chaos Mesh project and covers machines outside Kubernetes, such as virtual machines and bare-metal servers.
The README lists fault types including process failures, network disruption, resource pressure, and faults in files, JVMs and services. Experiments and recovery data are recorded in SQLite so later commands can inspect and recover supported faults. In server mode, Chaos Mesh dashboards can drive Chaosd remotely as part of physical-machine experiments.
In the quality loop Chaosd extends chaos experiments to hosts that Kubernetes tools cannot reach.
The source code is at chaos-mesh/chaosd on GitHub under the Apache-2.0 licence, with about 161 stars; the most recent commit was on 7 November 2026.
Features
- Process faults: Kill or stop processes.
- Network faults: Delay, loss, corruption and partitions.
- Stress: CPU and memory pressure.
- File and disk faults: Disk fill and file faults.
- JVM faults: Java application faults.
- Server mode: HTTP API driven by Chaos Mesh.
Pros
- Fits Chaos Mesh: Same project and dashboard.
- Free to use: Open source under the Apache-2.0 licence, so the core tool costs nothing to use.
- Actively maintained: The repository had commits as recent as 7 November 2026.
Cons
- Linux only: Hosts must run Linux.
- Root required: Many faults need privileges.
- Small community: Fewer users than Chaos Mesh itself.
Usage and Links (Example)
chaosd attack network delay -d eth0 --latency 200ms --percent 50
chaosd search --all
chaosd recover <uid>
Resources:
Pricing
Chaosd is free and open source under the Apache-2.0 licence.
Recommended for?
- Chaos Mesh users with VMs or bare-metal hosts.
Conclusion
Chaosd brings Chaos Mesh-style faults to ordinary Linux hosts.
Use it to include non-Kubernetes infrastructure in game days.
On CheckOps, Chaosd is filed under the Production monitoring & observability and Integration testing stages. Related tools listed here include Chaos Mesh, LitmusChaos, Chaos Toolkit, Gremlin, Steadybit and Toxiproxy. Which one fits best depends mostly on your stack, your team’s size and skills, and whether you prefer to run tools yourself or pay for a managed service. This page reflects the official website, documentation and repository as they stood on 11 November 2026.
Compare
CheckOps pages that put Chaosd next to related tools. There is no paid placement on these lists.
Alternatives
Other tools on CheckOps that cover similar ground. Open a page, or compare one with Chaosd side by side.
CChaos MeshChaos Mesh is a CNCF incubating, Apache-2.0 chaos engineering platform for Kubernetes that defines pod, network, DNS, HTTP, I/O, time, stress, kernel, JVM and cloud faults as custom resources.Compare with Chaosd
LLitmusChaosLitmusChaos is a 100% open-source CNCF chaos engineering platform that uses Kubernetes custom resources to define chaos and steady-state hypotheses, with a hub of experiments and a control-plane UI.Compare with Chaosd
CChaos ToolkitChaos Toolkit is an Apache-2.0 open-source chaos engineering toolkit and orchestration framework for developers, with declarative experiments and extensions for clouds and platforms.Compare with Chaosd
GGremlinGremlin is an enterprise reliability management and resilience testing platform with fault injection, reliability scoring, dependency discovery and Foresight AI agents; custom quotes and a 30-day free trial.Compare with Chaosd
SSteadybitSteadybit is a chaos engineering and reliability platform with a 30-day free trial and an open-source Reliability Hub of 200+ actions for injecting faults and verifying resilience.Compare with Chaosd
TToxiproxyToxiproxy is Shopify's MIT-licensed TCP proxy for simulating network and system conditions such as latency, timeouts and bandwidth limits in chaos and resiliency testing.Compare with Chaosd