Chaos Engineering

End-to-end chaos engineering: experiment design, fault injection catalog, gameday execution, and the maturity model that turns one-off "let's break stuff" exercises into a reliable discipline. Provider-agnostic — works whether you use Litmus, Chaos Mesh, AWS FIS, Gremlin, ChaosToolkit, or hand-rolled scripts.

This skill answers four questions: what to inject, where to inject it, how to size the blast, and how to extract durable learning from each run.

Core Capabilities

• Principles & maturity — the five Principles of Chaos and a four-level maturity model (L0 none → L4 always-on production chaos) with level-up criteria.
• Experiment design loop — a nine-step loop (steady state → hypothesis → variables → blast radius → abort → run → analyze → act → document) with worked good/bad examples.
• Fault catalog — what to inject per layer: pod/host, network, dependency, resource, state, and traffic, with tool mappings.
• Blast-radius sizing — quantify worst-case affected users and recommended caps; experiments start tiny (1 pod / 1% / 1 min) and grow only after passing.
• Gameday execution — scheduled multi-scenario exercises with roles, agendas, scenario selection, and debrief templates.
• Discipline — anti-patterns to avoid, the "first five experiments" for new teams, and end-to-end workflows (single experiment, gameday, kill-switch verification, post-incident verification).

When to Use