Topics
Databricks, covered in depth, platform and AI.
Free long-form guides on the topics covered across the two volumes. Each page is an opinionated practitioner-level overview, written for engineers who already know the basics and need to understand what actually matters in production.
Volume 3 · Ch 22–37
The Production Lakehouse Playbook
Unity Catalog
The three-level namespace, ABAC, governed tags, lineage, audit, and how UC becomes the platform contract.
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Lakehouse Architecture
Delta Lake (with Iceberg/UniForm interop), Unity Catalog, medallion architecture, the substrate everything else runs on.
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Lakeflow SDP
Spark Declarative Pipelines (formerly DLT), declarative bronze/silver/gold, streaming tables, quality expectations, APPLY CHANGES for CDC.
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Lakeflow Jobs
Orchestration on Databricks, task dependencies, event triggers, retries, parameters, SP execution.
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Asset Bundles (DAB)
Declarative deployment for jobs, pipelines, and ML artifacts. Versioned, environment-aware, CI/CD-ready.
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CI/CD with GitHub Actions + OIDC
Federated identity, no PATs, multi-environment promotion, the testing strategy that actually fits notebooks.
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Performance Tuning
Photon, Liquid Clustering, Predictive Optimization, and the diagnostic loop that finds bottlenecks fast.
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Volume 4 · Ch 38–58
The AI Lakehouse Playbook
RAG on Databricks
Retrieval-augmented generation using Mosaic AI Vector Search, chunking, retrieval evaluation, and production patterns.
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Agent Bricks
Classification, information extraction, auto-tuning, the cost-quality frontier. The declarative path to production agents.
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Multi-Agent Systems
The Multi-Agent Supervisor, MCP, agent evaluation, tracing every hop. When single-agent is still the right answer.
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MLflow 3 on Databricks
Experiments, UC Model Registry, aliases, traces, evaluation. The operating system for ML and GenAI workflows.
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Mosaic AI Vector Search
Delta-sync vs direct-access indexes, embedding models, hybrid retrieval, performance, cost.
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Feature Store on UC
Point-in-time lookups, online serving from Lakebase, and avoiding training-serving skew.
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MLOps & Lakehouse Monitoring
Alias-driven promotion, champion/challenger, traffic splitting, drift detection.
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Two volumes
Get the series.
Volume 3 is the platform foundation. Volume 4 is the AI build-out. Read either standalone, or both for the complete picture.
Volume 3
The Production Lakehouse Playbook
Unity Catalog, Lakeflow, and the Databricks Data Intelligence Platform, the production playbook for engineers who already know Spark.
Buy on Amazon$29.00 Kindle · $39.99 Paperback · 16 chapters
Volume 4
The AI Lakehouse Playbook
Mosaic AI, Agent Bricks, Lakebase, and the production Lakehouse, the 2026 field manual for shipping AI systems on Databricks.
Buy on Amazon$32.00 Kindle · $39.99 Paperback · 21 chapters