After years of building data pipelines on Google Cloud Platform, I’ve learned fault tolerance isn’t optional; it’s essential from day one. What sets a production-ready pipeline apart isn’t the architecture diagram but how it handles out-of-order changes, backlog, crashes, and quota limits.

This article distills lessons from real-world challenges: debugging issues at 3 a.m., handling unexpected load, and ensuring pipelines keep running through failures. The advice here is practical, not theoretical.