Welcome to the Databricks for Practitioners blog
Short field notes between book updates, releases, patterns, and the parts of Databricks platform + AI that change too fast for a book to keep up with.
This is the blog companion to the Databricks for Practitioners series, two volumes covering the platform foundation (V3) and the AI build-out on top (V4), and a place for shorter pieces that don’t fit between book updates.
The books cover the durable architecture and the patterns that hold up. The blog covers everything else: new Databricks releases worth noticing, things I learn the hard way, and the parts of production data + AI that change too fast for any book to keep up with.
What to expect
A few pieces a month, focused on:
- New Databricks releases, what changes in Mosaic AI, Agent Bricks, MLflow, Lakeflow, Unity Catalog, and Lakebase, and which changes you actually care about.
- Production patterns, RAG, agents, MLOps, governance, CI/CD. Things that worked. Things that didn’t.
- Cost surprises, where the bill comes from, and how to bring it down without losing functionality.
- Migration notes, moving from Pinecone to Vector Search, from external orchestrators to Lakeflow Jobs, from Hive Metastore to Unity Catalog, from manual deploys to Asset Bundles.
If you want the long-form deep dives, those are in the topic pages and the books themselves.
Subscribe
The RSS feed is the simplest way to keep up. The Kindle editions of both volumes also include major-release addendums for free, so if you’re already a reader, you don’t have to remember to check.
Ritesh