Proactive Resilience Testing
ChaosOps enables teams to proactively identify system weaknesses through chaos engineering practices, helping prevent outages before they impact production environments.
Automated Chaos Experiments
The platform likely offers automation for running chaos experiments, reducing manual effort and enabling consistent, repeatable testing of system resilience.
Improved Incident Response
By simulating failure scenarios, teams can better prepare their incident response processes and reduce mean time to recovery (MTTR) during real outages.
Visibility into System Weaknesses
ChaosOps provides insights and reporting on system vulnerabilities, helping engineering teams prioritize reliability improvements based on real experiment data.
Integration with DevOps Workflows
The tool is designed to fit into modern DevOps and SRE practices, allowing chaos engineering to become part of continuous integration and deployment pipelines.
ChaosOps combines classic server monitoring and alerting with AI that runs entirely on your own infrastructure (local LLM via Ollama) โ your metrics and incident data never leave your servers. Its self-healing actions are guarded: every automated fix runs through whitelists, snapshots with rollback, and human approval.
Three reasons: (1) Self-hosted by design โ no per-node SaaS pricing and no data leaving your network, unlike Datadog-style tools. (2) AI with a seatbelt โ local root-cause analysis plus self-healing that requires human confirmation at every step, not a blank-check automation. (3) One-time purchase โ the Professional edition is $1,399 perpetual with 90 days of free updates. No subscription.
Small teams, indie developers, and sysadmins running a handful to a few dozen servers who want serious monitoring, alerting, and incident management without enterprise SaaS pricing โ and who prefer keeping their operational data on their own infrastructure.
ChaosOps was built by a solo founder frustrated with two things: monitoring tools that charge per node, and tools that require shipping your operational data to someone else's cloud. It grew from an internal self-healing project into a full self-hosted operations platform, with a free open-source edition (AGPL-3.0) released alongside the commercial one.
Python (FastAPI) backend, Vue 3 web console, lightweight agents for Linux/Windows/ARM hosts, SQLite/InfluxDB for metrics storage, and Ollama for local LLM inference (OpenAI-compatible APIs also supported).
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Check the traffic stats of ChaosOps on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
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