Databricks Dabs

databricks/databricks-agent-skills/plugins/databricks/codex/skills/databricks-dabs

by databrickse3df77b3f0eb5d70392eb35c6761ca0f2929a4f6No license345 starsListed Oct 9, 2026Updated Oct 9, 2026Repository updated today

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.

Instructions onlyDevOps & Cloud
AI-generated overview

Guides creating, configuring, validating, deploying and managing Databricks Declarative Automation Bundles.

What it does
This skill provides instructions and reference material for working with Databricks Declarative Automation Bundles (DABs). It covers bundle structure and databricks.yml configuration, resource definitions, variables, multi-environment targets, Spark Declarative Pipeline settings, SQL alert schemas, deployment and run workflows, and resource permissions. It also defines validation and App naming completion checks to run before deploying.
When to use it
Use it when creating or configuring bundle projects and resources, setting up dev/prod targets, deploying or running bundle resources, managing permissions, or troubleshooting bundle validation and deployment errors. It also applies to specific resource types such as dashboards, jobs, pipelines, alerts, volumes and apps.
Requirements
Requires the Databricks CLI (version 0.270.0 or later is referenced for App naming defaults) and access to a Databricks workspace for validation, deployment and running resources. It ships no scripts; it is instructions plus reference documents and image assets.

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 [blocked] - Bundle structure, databricks.yml configuration, resource definitions, path resolution, variables, and multi-environment targets
  • SDP Pipelines [blocked] - Spark Declarative Pipeline configurations for DABs
  • SQL Alerts [blocked] - SQL Alert schemas and configuration (critical - API differs from other resources)
  • Deploy and Run [blocked] - Validation, deployment, running resources, monitoring logs, and troubleshooting common issues
  • Resource Permissions [blocked] - 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

Required App Completion Contract

Before validating any bundle that creates or changes an App, re-read the final bundle YAML and confirm all of the following structural requirements:

  • Each App resource uses a dedicated name variable, such as name: ${var.app_name}, while preserving an existing equivalent variable when present.
  • For Databricks CLI 0.270.0 or later, each App name variable defaults to a recognizable App prefix plus ${workspace.current_user.domain_friendly_name} for development, and the production target overrides it with a stable name. On older CLI versions, App name variables have no default and each developer must provide values.
  • No development App name uses ${workspace.current_user.short_name}, a bare ${bundle.target}, or a hardcoded value.

Only after this check, run databricks bundle validate --strict --target <target> --output json and inspect each resolved resources.apps.<key>.name. Each name must contain only lowercase letters, digits, and hyphens and be at most 30 characters. If a resolved name is invalid, collides after normalization, or multiple non-production targets share a workspace, persist a shorter, distinct value in the uncommitted .databricks/bundle/<target>/variable-overrides.json file and validate again. Successful validation alone does not satisfy this contract because validation does not catch every invalid or non-namespaced App name.

Documentation

Source and attribution

Source:databricks/databricks-agent-skillsinplugins/databricks/codex/skills/databricks-dabsat commite3df77b

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

Report or request removal