LitmusChaos runner

Deep dive for chaos-experiment-author Step 4. Configures LitmusChaos for Kubernetes-native chaos engineering. Prefer over chaos-mesh when the team wants a ChaosCenter web UI for workflow scheduling and ChaosHub catalog browsing; use chaos-mesh for fine-grained network-fault policies via its own CRD family.

Overview

Per litmus-home:

"LitmusChaos is a CNCF-hosted, open-source Chaos Engineering platform that helps teams identify infrastructure weaknesses through safe, controlled chaos tests."

"Kubernetes developers & SREs use Litmus to manage chaos in a declarative manner." (litmus-home)

The architecture: Litmus runs as a Kubernetes operator; experiments are CRDs; results export to Prometheus.

When to use

• The platform is Kubernetes (Litmus is K8s-native).
• The team wants CNCF / open-source chaos tooling (vs commercial Gremlin).
• A chaos experiment's outcome should integrate with existing K8s observability (Prometheus, Grafana).

Step 1 - Install

Per litmus-home:

helm repo add litmuschaos https://litmuschaos.github.io/litmus-helm/
helm install litmuschaos litmuschaos/litmus -n litmus --create-namespace

The Litmus operator + ChaosCenter (web UI) deploy.

Step 2 - Pick a ChaosExperiment from the Hub

Per litmus-home, the ChaosHub is "a repository hosting most of the chaos experiments that are needed for a quick start in Chaos Engineering." Common experiments:

Install per-experiment:

kubectl apply -f https://hub.litmuschaos.io/api/chaos/2.14.0?file=charts/generic/pod-delete/experiment.yaml

Step 3 - Author a ChaosEngine

The ChaosEngine CR runs an experiment against a target:

apiVersion: litmuschaos.io/v1alpha1
kind: ChaosEngine
metadata:
  name: checkout-pod-delete
  namespace: app
spec:
  appinfo:
    appns: app
    applabel: 'app=checkout'
    appkind: deployment
  chaosServiceAccount: pod-delete-sa
  experiments:
    - name: pod-delete
      spec:
        components:
          env:
            - name: TOTAL_CHAOS_DURATION
              value: '60'      # seconds
            - name: CHAOS_INTERVAL
              value: '20'       # seconds
            - name: PODS_AFFECTED_PERCENTAGE
              value: '50'
        probe:
          - name: 'check-checkout-availability'
            type: httpProbe
            httpProbe/inputs:
              url: 'http://checkout.app.svc:8080/health'
              insecureSkipVerify: false
              method:
                get:
                  criteria: '=='
                  responseCode: '200'
            mode: 'Continuous'
            runProperties:
              probeTimeout: 5
              interval: 2
              retry: 3
              probePollingInterval: 1

Per litmus-home, probes "create complete chaos scenarios close to the real application experience upon failure." The probe is the steady-state check per the chaos principles.

Step 4 - Run

kubectl apply -f checkout-pod-delete.yaml

Litmus runs the experiment for TOTAL_CHAOS_DURATION seconds, checking the probe continuously. The verdict (Pass / Fail) lands in chaosengine.status.experimentStatus.verdict.

Step 5 - Read the verdict

kubectl get chaosengine checkout-pod-delete -o jsonpath='{.status.experimentStatus.verdict}'
# Output: Pass | Fail

Step 6 - Probe types

Probes can run in different modes: SOT (start of test), EOT (end of test), Edge (both), Continuous (every N seconds during the experiment).

Step 7 - Observability

Per litmus-home: "chaos observability by exporting Prometheus metrics that highlight and quantify the impact of chaos on the applications or infrastructure in real time."

Key metrics:

• litmuschaos_passed_experiments
• litmuschaos_failed_experiments
• litmuschaos_awaited_experiments

Wire to Grafana for dashboards.

Step 8 - CI integration

- name: Run chaos experiment
  run: |
    kubectl apply -f experiments/checkout-pod-delete.yaml
    kubectl wait --for=condition=Complete chaosengine/checkout-pod-delete --timeout=10m
    VERDICT=$(kubectl get chaosengine checkout-pod-delete -o jsonpath='{.status.experimentStatus.verdict}')
    echo "Verdict: $VERDICT"
    [ "$VERDICT" = "Pass" ]

Anti-patterns

Limitations

• Kubernetes only. No native non-K8s support (vs Gremlin's multi-platform).
• ChaosHub experiments need vetting. Community experiments vary in quality.
• Cluster overhead. Litmus operator + per-experiment pods consume resources.
• Per-tool incompatibility. Litmus ChaosEngines aren't Chaos-Mesh CRDs; experiments don't port.

References

• lh - LitmusChaos overview, CNCF-hosted, ChaosExperiments
  • ChaosEngine + ChaosHub + probes, Prometheus metrics export.
• chaos-mesh - sibling K8s-native alternative.
• gremlin.md - commercial multi-platform alternative.
• The host chaos-experiment-author SKILL.md - methodology this tool implements.