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Most teams that move to Databricks get the hard part right. They migrate the processing engine, rebuild the transformation logic, and stand up Unity Catalog. Then they leave Azure Data Factory running in the background: connected to everything, owned by nobody, and quietly accumulating cost and complexity. In this entry, that’s the gap we address.

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Databricks Docker: From runtime CI/CD to compliance
Databricks Docker: From runtime CI/CD to compliance
Unity Catalog commits: Make your managed delta layer safer and more performant
Unity Catalog commits: Make your managed delta layer safer and more performant
Global Job Parameters, Thanks To DABs Mutators
Global Job Parameters, Thanks To DABs Mutators

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Databricks Docker: From runtime CI/CD to compliance

Databricks now supports 12 official Docker base images, and you can build your own on top of them. Custom containers let data engineering teams control the full runtime (including native binaries, enterprise certificates, internal packages, and offline environments) not just Python dependencies. This post walks through how to build, test, and deploy a custom Databricks container, with nine production use cases from compliance runtimes to DuckDB integration.

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