On Distributed Failure

The first time you watch a service cascade fail, it's humbling. Not in the way that textbooks describe it — "cascading failures" sounds tidy, academic. The real thing is watching dashboards turn red in sequence, like a row of dominoes that you inadvertently nudged. You scroll through logs fast enough that the timestamps blur, and somewhere in the back of your mind you're running a different process: tracing back to the commit, the config change, the assumption that turned out to be wrong.

Distributed systems have a way of exposing every assumption you ever made. Network partitions don't care about your deadlines. A thread that blocks forever will block forever. The CAP theorem isn't a theoretical curiosity — it's something you feel when you're paged at 2am and have to make a real tradeoff between consistency and availability in the span of five minutes, with incomplete information, while someone on the other end of a Slack thread is asking for an ETA.

What I learned, slowly, is that failure is information. A system that has never failed is a system you don't fully understand. Every incident is a probe into the true behavior of your architecture — the latent bugs, the wrong assumptions baked into your retry logic, the service that everyone assumed was stateless but quietly wasn't. The postmortem isn't a blame session; it's the closest thing you have to a spec for how the system actually behaves under pressure.

The goal isn't to build systems that never fail. It's to build systems where failure is bounded, observable, and recoverable. That's a much more achievable target, and it changes how you write code. You start designing for the failure path first — treating the happy path as the special case rather than the default. You add circuit breakers not because you expect the downstream to go down, but because you accept that it will.

There's something clarifying about that shift. Once you stop trying to prevent failure entirely and start engineering around its inevitability, the work gets less anxious and more precise.