databricks-dabs

databricks-dabs

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Create, configure, validate, deploy, run, and manage Declarative Automation Bundles (DABs, formerly Databricks Asset Bundles). Use when working with Databricks resources via DABs including dashboards, jobs, pipelines, alerts, volumes, and apps.

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Updated 10/2/2026
SKILL.md
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databricks-dabs
description

Create, configure, validate, deploy, run, and manage Declarative Automation Bundles (DABs, formerly Databricks Asset Bundles). Use when working with Databricks resources via DABs including dashboards, jobs, pipelines, alerts, volumes, and apps.

Declarative Automation Bundles (DABs)

Use this skill for any bundle-related request including creating, configuring, validating, deploying, running, and managing Databricks resources through DABs.

Reference Documentation

The following reference files provide detailed guidance for specific bundle tasks:

  • Bundle Structure - Bundle structure, databricks.yml configuration, resource definitions, path resolution, variables, and multi-environment targets
  • SDP Pipelines - Spark Declarative Pipeline configurations for DABs
  • SQL Alerts - SQL Alert schemas and configuration (critical - API differs from other resources)
  • Deploy and Run - Validation, deployment, running resources, monitoring logs, and troubleshooting common issues
  • Resource Permissions - Permission levels and access control for bundle resources, per-resource-type levels, grants vs permissions

When to Use This Skill

Load this skill for any request involving:

  • Creating new bundle projects or resources
  • Configuring databricks.yml or resource YAML files
  • Setting up multi-environment deployments (dev/prod targets)
  • Deploying or running bundle resources
  • Managing permissions for bundle resources
  • Troubleshooting bundle validation or deployment errors
  • Working with specific resource types (dashboards, jobs, pipelines, alerts, volumes, apps)

General Guidelines

  1. Always validate after configuration changes - Use bundle validate --strict --target <target> after any change
  2. Use reference documentation - Consult the appropriate reference file for detailed patterns and examples
  3. Follow naming conventions - Resource files should use <name>.<resource_type>.yml format
  4. Path resolution is critical - Paths differ based on file location (see Bundle Structure reference)
  5. Preserve existing structure - Keep user comments and structure when editing YAML files
  6. Use variables - Parameterize catalog, schema, and warehouse for multi-environment support
  7. Namespace App names - App names are workspace-global and limited to 30 characters. With Databricks CLI 0.270.0 or later, shared-development defaults should include the app and ${workspace.current_user.domain_friendly_name}; override production with a stable name, and persist an explicit local value when the default is invalid, collides, or must distinguish multiple non-production targets in one workspace. On older CLI versions, require an explicit app_name value instead

Documentation