databricks-deploy-integration

# Databricks Deploy Integration ## Overview Deploy Databricks jobs, DLT pipelines, and ML models using Declarative Automation Bundles (DABs, formerly Asset Bundles). Bundles provide infrastructure-as-code with `databricks.yml` defining resources, targets (dev/staging/prod), variables, and permissions. The CLI handles validation, deployment, and lifecycle management. ## Prerequisites - Databricks CLI v0.200+ (`databricks --version`) - Workspace access with service principal for automated deploys - `databricks.yml` bundle configuration at project root ## Instructions ### Step 1: Initialize a Bundle ```bash # Create from a template databricks bundle init # Available templates: # - default-python: Python notebook project # - default-sql: SQL project # - mlops-stacks: Full MLOps template with feature engineering ``` ### Step 2: Configure `databricks.yml` ```yaml # databricks.yml — single source of truth for project deployment bundle: name: sales-etl-pipeline workspace: host: ${DATABRICKS_HOST} variables: catalog: description: Unity Catalog name default: dev_catalog alert_email: description: Alert notification email default: dev@company.com warehouse_size: default: "2X-Small" include: - resources/*.yml targets: dev: default: true mode: development # dev mode auto-prefixes resources with [username] and enables debug workspace: root_path: /Users/${workspace.current_user.userName}/.bundle/${bundle.name}/dev variable...