litmuschaos/chaos-charts

Repository to hold chaos experiments resource YAML bundles

Hosted by Cloud Native Computing Foundation · part of Linux Foundation

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litmuschaos/chaos-charts has 90+ stars and 200+ forks on GitHub, is written in Go, and was last pushed on Jul 20, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 13 minutes ago
Type:Curated List / Learning ResourceCategory(s):Alerting, Incidents & SREKubernetes & OperatorsDevOps & Observability
Added to GitGenius on October 15th, 2026
Created on August 9th, 2019
Open Issues & Pull Requests: 32 (+0)
GitHub issues: Enabled
Number of forks: 214
Total Stargazers: 91 (+0)
Total Subscribers: 8 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 408.4 days
Mean response time: 476.5 days
90th percentile: 544.6 days
Tracked items: 2

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Issue Activity (beta)

Open issues: 6
New in 7 days: 1
Closed in 7 days: 0
Avg open age: 600 days
Stale 30+ days: 5
Stale 90+ days: 5

Recent activity

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Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Chaos-Charts is a repository of chaos engineering experiment bundles organized as Kubernetes resources in YAML format.

The project addresses the need to systematically test Kubernetes cluster resilience by providing pre-packaged chaos faults grouped into logical charts. These faults target different layers: Kubernetes resources themselves, applications running on Kubernetes, and the underlying platform infrastructure. Users can deploy these experiment bundles directly into their clusters to validate how systems behave under failure conditions.

Teams adopting this tool should understand that it serves as a curated collection of chaos experiments rather than the orchestration engine itself—it works within the Litmus Chaos ecosystem. The repository is most suitable for organizations running Kubernetes who want to practice chaos engineering with standardized, reusable fault definitions. The YAML-based approach means experiments integrate naturally with Kubernetes workflows and GitOps practices.

The project maintains active development with continuous integration workflows and Docker image builds. Community engagement is supported through Slack channels and social media presence, indicating ongoing maintenance and user interaction.