chaos-engineering
结构化实验与自动中止门控，适合在受控环境验证系统鲁棒性。
执行故障注入有造成服务中断的高风险，需在受控环境并有回滚策略
基于假设驱动对系统进行可控故障注入与弹性验证（网络、服务、基础设施）。
在受控环境里按假设往系统里注入网络、服务或基础设施级别的故障，验证系统在异常下还能不能恢复。常用于做 game day、演练故障恢复或评估关键依赖（用 LitmusChaos/Chaos Mesh/AWS FIS/Gremlin/toxiproxy 等工具）。特别之处是按假设设计、可控回滚（abort gating）并逐步放量，不是随意破坏，目标是提前发现薄弱环节。
▸ 展开 SKILL.md 英文原文
Validate system resilience through controlled fault injection. Covers hypothesis-driven chaos experiments, failure injection types (network, service, infrastructure, dependency), LitmusChaos/Chaos Mesh/AWS FIS/Gremlin/toxiproxy tooling, automated abort gating, game day planning, and progressive chaos adoption. Use when: "chaos engineering," "fault injection," "resilience test," "game day," "failure recovery," "system reliability," "blast radius." Not for: safe rollout flags/canary/dark launch during a release — use testing-in-production; designing new tests from production telemetry — use observability-driven-testing. Related: testing-in-production, observability-driven-testing, performance-testing, release-readiness, test-environments.
帮我安装这个 skill：https://raw.githubusercontent.com/petrkindlmann/qa-skills/main/skills/chaos-engineering/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/petrkindlmann/qa-skills/main/skills/chaos-engineering/SKILL.md"<objective> Chaos engineering is the discipline of experimenting on a system to build confidence in its ability to withstand turbulent conditions. It is not random destruction -- it is hypothesis-driven, controlled experimentation that reveals weaknesses before they cause outages. A retry that "works in the demo" silently double-charges customers when the payment API times out; the only way to know is to inject the timeout and watch. </objective> ## Quick Route | Situation | Go to | |-----------|-------| | First experiment ever, team is new | Starting Small → First Three Experiments | | Designing one experiment | Chaos Experiment Workflow (5 steps) | | Picking a tool for your environment |