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testland/chaos-experiment-author

Use when scoping a chaos engineering experiment before running it: a steady-state hypothesis, real-world faults (latency, node or region failure), blast radius, automation and the verdict, with a five-check validation of the hypothesis and LitmusChaos and Gremlin setup. Chaos Mesh has its own skill.

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Gremlin advanced operations - attacks, Scenarios, Reliability Score, CI, compliance

Deep reference for gremlin.md. Consult when picking a specific attack, chaining attacks into a Scenario, wiring Gremlin into CI, reading the Reliability Score, or satisfying an audit / compliance requirement.

Per gremlin-home:

Full attack table

Per gremlin-home and the broader Gremlin docs, the four attack classes expand into these individual attacks:

Class	Attack	Effect
Resource	CPU	Spike CPU usage
Resource	Memory	Spike memory
Resource	Disk I/O	Spike disk I/O
Resource	Disk space	Fill disk
Network	Latency	Inject latency
Network	Packet loss	Drop packets
Network	DNS	DNS resolution failure
Network	Blackhole	Drop all packets to/from a target
State	Shutdown	Reboot the host
State	Process killer	Kill a specific process
State	Time travel	Skew the system clock
Request	Request injection	Modify HTTP requests in flight

Running an attack via the web UI

Web UI workflow:

Select target (host / container / service / Lambda).
Pick attack type.
Configure (e.g., latency 500ms; duration 5min).
Optionally schedule.
Click "Unleash."

The UI provides safety: blast-radius scoping, abort button, notifications.

Authoring a Scenario

A Scenario chains multiple attacks:

# Pseudo-Scenario config (Gremlin's UI exports JSON; this approximates)
scenario:
  name: "Checkout resilience test"
  attacks:
    - type: latency
      target: { service: checkout }
      length: 5min
      latency: 500ms
    - type: packet-loss
      target: { service: payment }
      length: 5min
      loss-percent: 10
      delay-after-previous: 1min
  abort_conditions:
    - "Sentry error rate > 2%"
    - "Manual abort"

Scenarios match per the chaos-experiment-author "vary real-world events" principle - combinations approximate real incidents.

Reliability Score

Per gremlin-home, Gremlin's differentiator is the "Reliability Score" - "individual services" get scores "based on dependency mapping, risk detection, and failure testing."

Score components (per Gremlin docs):

Resilience tests passed: % of attacks the service survived
Dependency map: service-to-service relationships
Detected risks: configuration drift, hidden dependencies

A service moving from "untested" to "score 80" via passing attacks creates an objective improvement signal.

API + CI automation

Trigger an attack directly from the API:

curl -X POST "https://api.gremlin.com/v1/attacks/new" \
  -H "Authorization: Key $GREMLIN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "command": {
      "type": "latency",
      "args": ["-l", "300", "-m", "500", "-c", "5", "-h", "^api\\.example\\.com$"]
    },
    "target": {
      "type": "Random",
      "containers": { "labels": { "app": "checkout" } }
    }
  }'

The API enables CI integration - trigger a saved Scenario, wait for it to run, then evaluate a monitoring-driven verdict:

- name: Trigger Gremlin scenario
  run: |
    curl -X POST "https://api.gremlin.com/v1/scenarios/${{ vars.SCENARIO_ID }}/runs" \
      -H "Authorization: Key ${{ secrets.GREMLIN_API_KEY }}"
- name: Wait + verdict
  run: sleep 600 && ./scripts/datadog-verdict.sh

Compliance + audit

Gremlin's enterprise tier (per gremlin-home's positioning) provides:

Audit logs (who triggered what, when).
RBAC at organization / team / role level.
SOC 2 / FedRAMP / etc. compliance posture.

Important for regulated industries where audit is non-negotiable.

References

gh - Gremlin overview: enterprise reliability platform, reliability scoring, multi-platform fault injection.
chaos-experiment-author - methodology Gremlin Scenarios implement.