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.

Learn how to configure Databricks all-purpose clusters to reject scheduled jobs, forcing teams to use cost-effective job clusters. Simple setup, big savings.

Learn how Databricks’ policy default values reduce Asset Bundle complexity. Centralize governance and eliminate repetitive cluster configurations.