SYSTEM Cited by 1 source
Databricks Asset Bundles¶
Databricks Asset Bundles (DABs) are the deployable packaging unit for Databricks projects — a declarative, version-controlled bundle of notebooks, jobs, ML pipelines, dashboards, and configuration that can be deployed, updated, and run with a single command.
Stub page. One ingested source so far — used as the packaging-unit that lets the MapAid groundwater pipeline ship as a self-contained artifact a non-Databricks-expert partner organization can operate.
Architectural role in the MapAid groundwater pipeline¶
"The entire system is packaged as a Databricks Asset Bundle, meaning it can be deployed, updated, and run with a single command. MapAid received a self-contained solution that can be maintained without expertise across multiple cloud services. Because the pipeline logic is decoupled from the specific archive it processes, the same system could be adapted to other water archives, other regions, or other domains." (Source: sources/2026-05-11-databricks-unlocking-the-archives)
The architectural value is decoupling pipeline logic from the archive it processes. The bundle bundles the Lakeflow Job topology, the AI Functions calls, the schema definitions, the Unity Catalog Volume references, and the Delta table targets — but the input archive is a configuration parameter. Pointing the same bundle at a different archive is a deploy parameter, not a code change. See patterns/asset-bundle-single-command-deployment.
This is the pattern that makes pro-bono / partner-operated AI
pipelines tractable: hand a domain partner a databricks bundle deploy
command instead of a multi-service architecture diagram.
Seen in¶
- sources/2026-05-11-databricks-unlocking-the-archives — canonical wiki instance. The whole document-classification + extraction + judge pipeline ships as one bundle; one-command deploy explicitly called out as the operating-handoff feature for a non-Databricks partner organization.