Automated root cause analysis that reads logs, metrics, and traces together and cites every claim to its source, so you cut MTTR instead of hopping tabs.
It's 2:11am. Checkout is throwing 500s and compose-post-service is screaming, seven times its normal error volume, top of every dashboard you own. So you start there. Twenty-five minutes in, someone asks the question that ends the incident: "is the auth service even up?" It isn't. user-service let a TLS cert expire and logged almost nothing on the way down. The loudest service was the victim. The quiet one was the cause.
That gap, between the service with the most errors and the service that actually broke, is where most of your mean-time-to-resolution goes. Real root cause analysis isn't "find the noisiest service." It's reading logs, metrics, and traces together to find who everyone else is pointing at, then proving it. Epok does that automatically and cites every claim back to the exact log line, span, or metric, so you cut MTTR instead of assembling the answer across six tabs at 2am.
Why the loudest service is rarely the root cause
We ran this as a controlled experiment because the pattern is so consistent. Twenty services, steady traffic, mature baselines. Then we injected a cascade.
