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 state
Databricks