Tutorial: How to ship AI/BI Dashboard changes safely at scale with Databricks Asset Bundles | Endigest
Databricks
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This tutorial demonstrates how to manage Databricks AI/BI dashboards safely using Databricks Asset Bundles (DABs), Git, and CI/CD workflows.
- •Dashboards are added to a Databricks Asset Bundle to version-control them as deployable assets tracked in a Git repository
- •Git branching isolates dashboard development so changes don't affect the production dashboard during authoring
- •Pull Requests provide a structured review and approval step before any change reaches production, with optional auto-deployed test previews
- •Environment-specific .yml configuration files handle differences (catalog, schema, SQL warehouse) across dev, test, and production workspaces
- •Deployment automation runs on PR merge, reusing the same dashboard code with environment-specific overrides applied automatically
•Full Git history enables auditing of what changed, when, and by whom, with rollback capability to any prior stateThis summary was automatically generated by AI based on the original article and may not be fully accurate.