Chaos Experiment

SkillMedia

Use when the user asks to create, edit, update, design, or configure a Harness Chaos Experiment — including faults, probes, actions, experiment YAML, fault injection, pod-delete, or resilience tests. Do not use for Chaos steps inside a pipeline or a DRTest stage; use chaos-dr-test for those. Do not

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Chaos Experiment skill

What this skill tells your AI

The instructions your AI receives, as published by harness/harness-skills in skills/chaos-experiment/SKILL.md and read by ahel’s review.

Create and manage chaos experiments using Harness Chaos Engineering via MCP.

Instructions

Step 1: Check Infrastructure

Call MCP tool: harness_list
Parameters:
  resource_type: "chaos_infrastructure"
  org_id: "<organization>"
  project_id: "<project>"

Step 2: Browse Templates

Call MCP tool: harness_list
Parameters:
  resource_type: "chaos_experiment_template"
  org_id: "<organization>"
  project_id: "<project>"

Step 3: List Existing Experiments

Call MCP tool: harness_list
Parameters:
  resource_type: "chaos_experiment"
  org_id: "<organization>"
  project_id: "<project>"

Step 4: Create Experiment

Call MCP tool: harness_create
Parameters:
  resource_type: "chaos_experiment"
  org_id: "<organization>"
  project_id: "<project>"
  body: <experiment definition>

Step 5: Run Experiment

Call MCP tool: harness_execute
Parameters:
  resource_type: "chaos_experiment"
  action: "run"
  resource_id: "<experiment_id>"
  org_id: "<organization>"
  project_id: "<project>"

Step 6: Monitor Results

Call MCP tool: harness_list
Parameters:
  resource_type: "chaos_experiment_run"
  org_id: "<organization>"
  project_id: "<project>"

Get specific run details:

Call MCP tool: harness_get
Parameters:
  resource_type: "chaos_experiment_run"
  resource_id: "<run_id>"

Step 7: Check Probes

Call MCP tool: harness_list
Parameters:
  resource_type: "chaos_probe"
  org_id: "<organization>"
  project_id: "<project>"

Common Experiment Types

  • Pod Delete - Kill pods to test recovery
  • Pod CPU Hog - Stress CPU to test throttling
  • Pod Memory Hog - Consume memory to test OOM handling
  • Pod Network Loss - Simulate network failures
  • Pod Network Latency - Add artificial latency
  • Node Drain - Drain K8s nodes
  • EC2 Stop - Stop AWS EC2 instances
  • ECS Task Stop - Stop ECS tasks

Chaos Resource Types

Resource TypeOperationsDescription
chaos_experimentlist, get, create, update, delete, runExperiments
chaos_experiment_runlist, getRun history/results
chaos_experiment_templatelist, getPre-built templates
chaos_infrastructurelist, getTarget infrastructure
chaos_probelist, getHealth probes

Examples

  • "Show me all chaos experiments" - List chaos_experiment
  • "Create a pod-delete experiment for checkout-service" - Create chaos_experiment
  • "Run the weekly resilience test" - Execute run action
  • "What were the results of the last chaos run?" - Get chaos_experiment_run

Performance Notes

  • Review existing experiments before creating duplicates. Check for similar fault types targeting the same service.
  • Wait for experiment completion before analyzing results. Do not draw conclusions from partial runs.
  • Verify the target infrastructure and service are healthy before running chaos experiments.

Troubleshooting

Experiment Won't Run

  • Verify chaos infrastructure is connected and active
  • Check target application/namespace exists
  • Ensure RBAC permissions for chaos operations

Probes Failing

  • Check probe endpoints are accessible
  • Verify probe timeout settings
  • Review probe type matches expected behavior

Signals

GitHub stars
106
Forks
18
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
chaos-experiment-harness
Source
github.com/harness/harness-skills