Databricks Asset Bundle (DABs) Writer

Overview

Create DABs for multi-environment deployment (dev/staging/prod).

Reference Files

• SDP_guidance.md - Spark Declarative Pipeline configurations
• alerts_guidance.md - SQL Alert schemas (critical - API differs)

Bundle Structure

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

Main Configuration (databricks.yml)

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"

Dashboard Resources

Support for dataset_catalog and dataset_schema parameters added in Databricks CLI 0.281.0 (January 2026)

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"

Permission levels: CAN_READ, CAN_RUN, CAN_EDIT, CAN_MANAGE

Pipelines

See SDP_guidance.md for pipeline configuration

SQL Alerts

See alerts_guidance.md - Alert schema differs significantly from other resources

Jobs Resources

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"

Permission levels: CAN_VIEW, CAN_MANAGE_RUN, CAN_MANAGE

⚠️ Cannot modify "admins" group permissions on jobs - verify custom groups exist before use

Path Resolution

⚠️ Critical: Paths depend on file location:

File Location	Path Format	Example
resources/*.yml	../src/...	../src/dashboards/file.json
databricks.yml targets	./src/...	./src/dashboards/file.json

Why: resources/ files are one level deep, so use ../ to reach bundle root. databricks.yml is at root, so use ./

Volume Resources

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

⚠️ Volumes use grants not permissions - different format from other resources

Apps Resources

Apps resource support added in Databricks CLI 0.239.0 (January 2025)

Apps in DABs have a minimal configuration - environment variables are defined in app.yaml in the source directory, NOT in databricks.yml.

Generate from Existing App (Recommended)

# 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)

Manual Configuration

resources/my_app.app.yml:

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

src/app/app.yaml: (Environment variables go here)

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"

databricks.yml:

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"

Key Differences from Other Resources

Aspect	Apps	Other Resources
Environment vars	In app.yaml (source dir)	In databricks.yml or resource file
Configuration	Minimal (name, description, path)	Extensive (tasks, clusters, etc.)
Source path	Points to app directory	Points to specific files

⚠️ Important: When source code is in project root (not src/app), use source_code_path: .. in the resource file

Other Resources

DABs supports schemas, models, experiments, clusters, warehouses, etc. Use databricks bundle schema to inspect schemas.

Reference: DABs Resource Types

Common Commands

Validation

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

Deployment

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

Running Resources

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

Monitoring & Logs

View application logs (for Apps resources):

# 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

What logs show:

• [SYSTEM] - Deployment progress, file updates, dependency installation
• [APP] - Application output (print statements, errors)
• Backend connection status
• Deployment IDs and timestamps
• Stack traces for errors

Key log patterns to look for:

• ✅ Deployment successful - Confirms deployment completed
• ✅ App started successfully - App is running
• ✅ Initialized real backend - Backend connected to Unity Catalog
• ❌ Error: - Look for error messages and stack traces
• 📝 Requirements installed - Dependencies loaded correctly

Cleanup

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

---

Common Issues

Issue	Solution
App deployment fails	Check logs: databricks apps logs <app-name> for error details
App not connecting to Unity Catalog	Check logs for backend connection errors; verify warehouse ID and permissions
Wrong permission level	Dashboards: CAN_READ/RUN/EDIT/MANAGE; Jobs: CAN_VIEW/MANAGE_RUN/MANAGE
Path resolution fails	Use ../src/ in resources/*.yml, ./src/ in databricks.yml
Catalog doesn't exist	Create catalog first or update variable
"admins" group error on jobs	Cannot modify admins permissions on jobs
Volume permissions	Use grants not permissions for volumes
Hardcoded catalog in dashboard	Use dataset_catalog parameter (CLI v0.281.0+), create environment-specific files, or parameterize JSON
App not starting after deploy	Apps require databricks bundle run <resource_key> to start
App env vars not working	Environment variables go in app.yaml (source dir), not databricks.yml
Wrong app source path	Use ../ from resources/ dir if source is in project root
Debugging any app issue	First step: databricks apps logs <app-name> to see what went wrong

Key Principles

1. Path resolution: ../src/ in resources/*.yml, ./src/ in databricks.yml
2. Variables: Parameterize catalog, schema, warehouse
3. Mode: development for dev/staging, production for prod
4. Groups: Use "users" for all workspace users
5. Job permissions: Verify custom groups exist; can't modify "admins"

Related Skills

• databricks-spark-declarative-pipelines - pipeline definitions referenced by DABs
• databricks-app-apx - app deployment via DABs
• databricks-app-python - Python app deployment via DABs
• databricks-config - profile and authentication setup for CLI/SDK
• databricks-jobs - job orchestration managed through bundles

Resources

• Databricks Asset Bundles Documentation
• Bundle Resources Reference
• Bundle Configuration Reference
• Supported Resource Types
• Examples Repository 1
• Example Repository 2