project/
├── databricks.yml           # Main config + targets
├── resources/*.yml          # Resource definitions
└── src/                     # Code/dashboard files

bundle:
  name: project-name

include:
  - resources/*.yml

variables:
  catalog:
    default: "default_catalog"
  schema:
    default: "default_schema"
  warehouse_id:
    lookup:
      warehouse: "Shared SQL Warehouse"

targets:
  dev:
    default: true
    mode: development
    workspace:
      profile: dev-profile
    variables:
      catalog: "dev_catalog"
      schema: "dev_schema"

  prod:
    mode: production
    workspace:
      profile: prod-profile
    variables:
      catalog: "prod_catalog"
      schema: "prod_schema"

resources:
  dashboards:
    dashboard_name:
      display_name: "[${bundle.target}] Dashboard Title"
      file_path: ../src/dashboards/dashboard.lvdash.json  # Relative to resources/
      warehouse_id: ${var.warehouse_id}
      dataset_catalog: ${var.catalog} # Default catalog used by all datasets in the dashboard if not otherwise specified in the query
      dataset_schema: ${var.schema} # Default schema used by all datasets in the dashboard if not otherwise specified in the query
      permissions:
        - level: CAN_RUN
          group_name: "users"

resources:
  jobs:
    job_name:
      name: "[${bundle.target}] Job Name"
      tasks:
        - task_key: "main_task"
          notebook_task:
            notebook_path: ../src/notebooks/main.py  # Relative to resources/
          new_cluster:
            spark_version: "13.3.x-scala2.12"
            node_type_id: "i3.xlarge"
            num_workers: 2
      schedule:
        quartz_cron_expression: "0 0 9 * * ?"
        timezone_id: "America/Los_Angeles"
      permissions:
        - level: CAN_VIEW
          group_name: "users"

resources:
  volumes:
    my_volume:
      catalog_name: ${var.catalog}
      schema_name: ${var.schema}
      name: "volume_name"
      volume_type: "MANAGED"

# Generate bundle config from existing CLI-deployed app
databricks bundle generate app --existing-app-name my-app --key my_app --profile DEFAULT

# This creates:
# - resources/my_app.app.yml (minimal resource definition)
# - src/app/ (downloaded source files including app.yaml)

resources:
  apps:
    my_app:
      name: my-app-${bundle.target}        # Environment-specific naming
      description: "My application"
      source_code_path: ../src/app         # Relative to resources/ dir

command:
  - "python"
  - "dash_app.py"

env:
  - name: USE_MOCK_BACKEND
    value: "false"
  - name: DATABRICKS_WAREHOUSE_ID
    value: "your-warehouse-id"
  - name: DATABRICKS_CATALOG
    value: "main"
  - name: DATABRICKS_SCHEMA
    value: "my_schema"

bundle:
  name: my-bundle

include:
  - resources/*.yml

variables:
  warehouse_id:
    default: "default-warehouse-id"

targets:
  dev:
    default: true
    mode: development
    workspace:
      profile: dev-profile
    variables:
      warehouse_id: "dev-warehouse-id"

databricks bundle validate                    # Validate default target
databricks bundle validate -t prod           # Validate specific target

databricks bundle deploy                      # Deploy to default target
databricks bundle deploy -t prod             # Deploy to specific target
databricks bundle deploy --auto-approve      # Skip confirmation prompts
databricks bundle deploy --force             # Force overwrite remote changes

databricks bundle run resource_name          # Run a pipeline or job
databricks bundle run pipeline_name -t prod  # Run in specific environment

# Apps require bundle run to start after deployment
databricks bundle run app_resource_key -t dev    # Start/deploy the app

# View logs for deployed apps
databricks apps logs <app-name> --profile <profile-name>

# Examples:
databricks apps logs my-dash-app-dev -p DEFAULT
databricks apps logs my-streamlit-app-prod -p DEFAULT

databricks bundle destroy -t dev
databricks bundle destroy -t prod --auto-approve