| name | chaos-experiment-designer |
| description | Design DSDS chaos experiments with deterministic setup, explicit hypotheses, and measurable outcomes. Use when planning failure drills, resilience validation, pre-production risk exercises, and repeatable chaos scenarios for regression testing. |
Chaos Experiment Designer
Overview
Create focused chaos experiments that test one resilience claim at a time. Ensure each experiment is reproducible and has clear pass/fail criteria.
Workflow
- Define the hypothesis
- State one reliability claim in measurable form.
- Identify target metrics and acceptable bounds.
- Define steady state
- Specify baseline workload and expected healthy metric band.
- Establish pre-fault observation window.
- Design fault injection
- Pick minimal fault set to test the hypothesis.
- Set trigger timing and fault duration explicitly.
- Define safeguards
- Add blast radius limits and abort conditions.
- Identify critical user journeys that must stay protected.
- Define evaluation plan
- Add pass/fail rules tied to SLOs and invariants.
- Include recovery expectations (
MTTR, error decay, queue normalization).
- Package experiment
- Return experiment spec, run steps, success criteria, and follow-up checks.
Output format
Hypothesis
Steady-state definition
Fault plan
Safety and abort rules
Pass/fail criteria
Follow-up actions
References
- Read
references/chaos-experiment-template.md for reusable experiment skeletons.
- Use these repo sources:
docs/05-devs-chaos-and-analysis.md (Chapter 27)
canonical-catalogue/DSDS Canonical Catalogue - scenarios to ship.csv
canonical-catalogue/DSDS Canonical Catalogue - Failure modes & propagation semantics.csv