Classic change data feed saves an extra copy of every change, which adds storage and slows updates. Hubert Dudek benchmarks the automatic alternative on a 5-million-row table and walks through how it works.

Bronze, Silver, and Gold are a great starting point, but real projects rename layers, split them, and stack them. Here’s how to decide what each layer is responsible for, and when a separate one earns its place.

Every CI/CD pipeline eventually needs something to run after deployment: initial setup, config syncs, validation checks. job_runs in Databricks Asset Bundles handles all of it natively, and you can use it to block a production update when validation fails.