An open-source chaos engineering platform for SREs and developers to test cloud-native system resilience.
LitmusChaos is an open-source chaos engineering platform that helps SREs and developers practice chaos engineering in cloud-native environments. It allows teams to inject controlled faults into their systems to identify weaknesses and improve resilience. The platform is built around Kubernetes custom resources and provides a centralized hub for sharing and managing chaos experiments.
Site Reliability Engineers (SREs), DevOps engineers, and developers working with Kubernetes who want to proactively test and improve their system's resilience against failures.
Developers choose LitmusChaos because it's a CNCF-graduated, Kubernetes-native solution that integrates seamlessly with existing cloud-native workflows. Its open-source nature, extensive community-contributed experiment library, and support for custom chaos integrations make it a flexible and powerful tool for resilience testing.
Litmus helps SREs and developers practice chaos engineering in a Cloud-native way. Chaos experiments are published at the ChaosHub (https://hub.litmuschaos.io). Community notes is at https://hackmd.io/a4Zu_sH4TZGeih-xCimi3Q
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Uses custom resources like ChaosExperiment and ChaosEngine, making it seamlessly fit into existing K8s workflows and tooling, as highlighted in the README's architecture overview.
ChaosHub provides a centralized library of pre-built, community-contributed experiments, accelerating adoption and sharing best practices, evidenced by hub.litmuschaos.io integration.
BYOC (Bring-Your-Own-Chaos) support allows integrating third-party tools for custom chaos, offering extensibility beyond built-in faults, as noted in the ChaosExperiment CR description.
Built-in probes enable defining and checking system health constraints during experiments, reducing risk of unintended damage, detailed in the ChaosEngine section of the README.
The platform is tightly coupled to Kubernetes, making it irrelevant for non-K8s environments and limiting use in hybrid setups without K8s components.
Managing the chaos control and execution planes adds infrastructure overhead, and workflow setup can be intricate, as implied by the detailed installation and contribution guides.
Creating custom experiments requires deep understanding of chaos engineering principles and Kubernetes CRDs, which may deter teams new to the practice, despite community resources.