We usually treat cloud costs as an infrastructure problem - something to be solved with better budgets or Reserved Instances. But in a world of serverless and containers, your bill is a direct reflection of your code's efficiency. A memory leak isn't just a bug anymore; it’s a monthly recurring expense. A "chatty" frontend isn't just slow; it’s a self-inflicted DDoS attack on your own wallet.
This lightning talk shifts the FinOps conversation to where costs actually start: the IDE. We’ll trace a single request through a standard GCP stack—from an Angular frontend, through Java services on GKE, and down into Cloud Spanner.
Instead of high-level theory, we’ll look at the specific code-level anti-patterns that wreck unit economics. You’ll see how "polite" frontend code helps GKE bin-packing density, how Java serialization impacts Dataflow costs, and how specific query patterns can quietly destroy a budget. You'll leave with a developer-centric checklist to stop the bleeding in production.