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Creates and configures Databricks Declarative Automation Bundles for multi-environment CI/CD deployments of dashboards, pipelines, jobs, alerts, with permissions and resource definitions.
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Create DABs for multi-environment deployment (dev/staging/prod).
Create, configure, validate, deploy, run, and manage Databricks Declarative Automation Bundles (DABs) for resources like dashboards, jobs, pipelines, alerts, volumes, and apps.
Deploys Databricks jobs, DLT pipelines, and ML models using Declarative Automation Bundles for multi-environment IaC management.
Manages Databricks Jobs: create, list, run, update, delete multi-task DAG workflows with schedules, notifications using Python SDK, CLI, or Asset Bundles.
Share bugs, ideas, or general feedback.
Create DABs for multi-environment deployment (dev/staging/prod).
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"
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: ${var.schema} # Default schema used by all datasets in the dashboard if not otherwise specified in the query
permissions:
- level: CAN_RUN
group_name: "users"
Permission levels: CAN_READ, CAN_RUN, CAN_EDIT, CAN_MANAGE
See SDP_guidance.md for pipeline configuration
See alerts_guidance.md - Alert schema differs significantly from other resources
resources:
jobs:
job_name:
name: "[${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
⚠️ 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 ./
resources:
volumes:
my_volume:
catalog_name: ${var.catalog}
schema_name: ${var.schema}
name: "volume_name"
volume_type: "MANAGED"
⚠️ Volumes use grants not permissions - different format from other resources
Apps resource support added in Databricks CLI 0.239.0 (January 2025)
Apps in DABs have a minimal configuration - environment variables are defined in app.yaml in the source directory, NOT in databricks.yml.
# Generate bundle config from existing CLI-deployed app
databricks bundle generate app --existing-app-name my-app --key my_app --profile DEFAULT
# This creates:
# - resources/my_app.app.yml (minimal resource definition)
# - src/app/ (downloaded source files including app.yaml)
resources/my_app.app.yml:
resources:
apps:
my_app:
name: my-app-${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"
| 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
DABs supports schemas, models, experiments, clusters, warehouses, etc. Use databricks bundle schema to inspect schemas.
Reference: DABs Resource Types
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 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)Key log patterns to look for:
Deployment successful - Confirms deployment completedApp started successfully - App is runningInitialized real backend - Backend connected to Unity CatalogError: - Look for error messages and stack tracesRequirements installed - Dependencies loaded correctlydatabricks bundle destroy -t dev
databricks bundle destroy -t prod --auto-approve
| 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 |
../src/ in resources/*.yml, ./src/ in databricks.ymldevelopment for dev/staging, production for prod"users" for all workspace users