Can we run chaos engineering in regulated environments (SOC2, PCI)?

Yes. Treat experiments as change-managed work with tickets, approvals, and auditable Git history. Use staging with prod-like load first, time-bounded prod windows, documented abort conditions, and evidence (dashboards, reports). We’ve implemented this with risk/control mappings for SOC2 and PCI DSS.

How do we avoid data loss when testing databases?

Prefer read replicas, followers, or shadow traffic. Test network faults and failover logic rather than destructive writes. If you must test primary failure, do it with snapshot/point-in-time restore rehearsals and explicit data validation checks post-run.

We’re not on Kubernetes—does this still apply?

Absolutely. Use `Gremlin`, `AWS FIS`, or `Toxiproxy` at the VM/app layer. The principles—SLOs, guardrails, small blast radius, scoring—are platform-agnostic.

What’s the minimum viable chaos program?

Two SLOs per critical service, one guardrail PR (timeouts + circuit breaker), one latency experiment per week, scored and reported. In a month you’ll have findings that justify deeper investment.

How do we get executive buy-in?

Tie experiments to error budget burn, MTTR, and change failure rate. Show a before/after dashboard and one story where chaos prevented an incident. Frame it as risk reduction with auditability, not cowboy testing.

Guides · Oct 31, 2025 · 10 minute read

The Chaos Engineering Playbook We Actually Run: Resilience Tests That Don’t Torch Prod

Practical, low-blast-radius chaos engineering for teams that ship. Metrics, guardrails, configs, and tooling that hold up under fire.

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The Chaos Engineering Playbook We Actually Run: Resilience Tests That Don’t Torch Prod

Key takeaways

Implementation checklist