Mastering CI/CD for Azure Databricks

End-to-End Deployment with Azure DevOps & Asset Bundle

What you'll learn
- Set up and configure Azure DevOps pipelines for automating Databricks deployments.
- Create and manage Databricks Asset Bundles to structure and version your deployment assets.
- Deploy notebooks, jobs, and workflows to Development, Test, and Production environments using CI/CD
- Handle environment-specific configurations with variables, secrets, and conditional logic.
- Validate deployments and implement rollback strategies for reliable and secure automation
- Build a complete end-to-end CI/CD pipeline for Azure Databricks with real-world, hands-on demonstrations

Requirements
- Basic familiarity with Azure Databricks — including notebooks, jobs, and workspace navigation.
- Working knowledge of Azure DevOps and Git — especially using repositories and version control
- Access to an Azure subscription — with permissions to use Azure DevOps and Databricks services for hands-on practice

Description
Course Overview

Welcome to one of the most practical and hands-on courses on CI/CD deployment for Azure Databricks using Azure DevOps pipelines and Databricks Asset Bundles. This course is designed for data engineers, DevOps professionals, and cloud developers who want to automate and streamline their Databricks workflows across multiple environments — Development, Test, and Production.

In today’s data-driven world, deploying notebooks, jobs, and workflows manually is not scalable or reliable. This course teaches  you how to build a robust CI/CD pipeline that automates deployments, ensures consistency, and accelerates delivery using modern DevOps practices.

Whether you're working in a small team or managing enterprise-scale data platforms, this course will equip you with the tools and techniques to confidently implement CI/CD in your Databricks projects.

What You Will Learn

By the end of this course, you will be able to:

Understand the fundamentals of CI/CD in the context of Azure Databricks.

Set up and configure Databricks Asset Bundles for structured deployments.

Build and manage Azure DevOps pipelines tailored for Databricks workflows.

Automate deployments to Development, Test, and Production environments.

Integrate version control, environment isolation, and deployment validation.

Apply best practices for collaboration, scalability, and maintainability.

Course Structure

This course is 100% demonstration-based, meaning you’ll be able to watch and practice along with every step. Each module is carefully designed to build on the previous one, ensuring a smooth learning curve and practical understanding

What You’ll Need

To get the most out of this course, you’ll need:

An active Azure subscription with access to Azure DevOps and Databricks.

Basic knowledge of Git and YAML (we’ll cover the essentials).

A willingness to learn by doing — this course is hands-on!

What You’ll Achieve

By the end of this course, you’ll have:

A fully functional CI/CD pipeline for Azure Databricks.

The ability to deploy notebooks, jobs, and workflows automatically.

Confidence in managing deployments across multiple environments.

Skills that are highly valuable in modern data engineering and DevOps roles.

Instructor Support

Throughout the course, you’ll have access to Q&A forums, where you can ask questions, share insights, and get help from the instructor and fellow learners. We’re here to support your learning journey every step of the way.

Let’s Get Started!

If you're ready to take your Databricks deployment skills to the next level and build production-grade CI/CD pipelines using Azure DevOps, then enroll now and start your journey toward mastering automated data workflows.

Let’s build something powerful — together!

Who this course is for:
- Data Engineers who want to automate and streamline Databricks deployments across environments.
- DevOps Professionals looking to integrate Databricks into their CI/CD workflows using Azure DevOps.
- Cloud Developers and Architects working with Azure-based data platforms and seeking scalable deployment strategies
- Technical Learners and IT Professionals interested in hands-on experience with modern data engineering and DevOps practices.
More Info