Why Your Chaos Experiments Are Probably Wasting Time (and How to Fix It)

You have 20 microservices. You want to run chaos experiments. Where do you start? If your answer is "the payment service" — why? Because it feels important? Because it failed last week? Because LitmusChaos defaulted to it? Most teams pick chaos targets the same way they pick where to eat lunch — gut feel, recent memory, or whoever spoke loudest in the meeting. That's fine when you're running 2 services. It breaks down fast when you're running 20. The actual problem Chaos engineering has a prioritization gap. The tooling is excellent at how to break things — LitmusChaos, Chaos Mesh, Gremlin all do this well. None of them tell you what to break next. The result: teams either test the same high-visibility services repeatedly, or they run random experiments and hope they hit something real. Both approaches leave systematic gaps. The framing that fixed this for me came from fault tree analysis: risk = impact × likelihood Impact — if this service degrades, how many others are affected? Likel