Can I implement zero-downtime deployments with this skill?

Yes, the skill includes specialized patterns for Blue-Green and Canary deployments to ensure high availability during updates.

Does this skill support Databricks Asset Bundles (DABs)?

Yes, it provides specific implementation patterns for validating and deploying Databricks Asset Bundles across various environments.

How does it handle deployment failures?

It includes a standardized rollback strategy that allows you to revert to a specific commit SHA or tag via GitHub Actions.

What testing frameworks are included in these workflows?

The workflows integrate popular Python tools including pytest for unit testing, Black and Ruff for linting, and MyPy for type checking.

Are security checks part of the CI/CD pipeline?

Absolutely. It features quality gates for security vulnerability scanning using Bandit and dependency safety checks.

Databricks CI/CD Workflows

Name: Databricks CI/CD Workflows
Author: vivekgana

byvivekgana

•

部署与 DevOps

Automates Databricks deployment cycles using GitHub Actions and robust quality gates for data engineering pipelines.

关于

The Databricks CI/CD Workflows skill provides comprehensive, production-ready patterns for managing the lifecycle of Databricks assets. By leveraging GitHub Actions and Databricks Asset Bundles (DABs), it enables teams to implement automated testing, security scanning, and multi-environment promotion strategies. This skill is ideal for data engineering teams looking to reduce manual errors, enforce code quality through automated gates, and implement advanced deployment strategies like Blue-Green or Canary rollouts within their Lakehouse architecture.

主要功能

Multi-environment deployment workflows for Dev, Staging, and Production
Automated rollback strategies for rapid recovery from failed deployments
Advanced rollout patterns like Blue-Green and Canary deployments
Comprehensive quality gates including linting, security scanning, and coverage checks
2 GitHub stars
Automated validation using Databricks Asset Bundles (DABs)

使用场景

Reducing production risk through environment promotion and mandatory approval gates
Standardizing Databricks project deployments across distributed engineering teams
Implementing automated data quality and security audits within the release pipeline

关于

主要功能

Multi-environment deployment workflows for Dev, Staging, and Production
Automated rollback strategies for rapid recovery from failed deployments
Advanced rollout patterns like Blue-Green and Canary deployments
Comprehensive quality gates including linting, security scanning, and coverage checks
2 GitHub stars
Automated validation using Databricks Asset Bundles (DABs)

使用场景

Reducing production risk through environment promotion and mandatory approval gates
Standardizing Databricks project deployments across distributed engineering teams
Implementing automated data quality and security audits within the release pipeline