A "push code → deploy" pipeline is a demo, not a production strategy. What separates a toy CI/CD setup from one that survives a real data platform is the gates — the checkpoints that stop bad code, bad data, and bad permissions from ever reaching production. This post covers the actual strategy mature Databricks teams run, with full implementation using Asset Bundles, GitHub Actions, and a Service Principal.
1. The environment & branching strategy
Map Git branches → Databricks Asset Bundle targets → physical workspaces. Never deploy dev code straight to prod — always promote through a fixed path.
Git branch
Bundle target
