Chapter 5 of 7 · Databricks Data Engineer Associate

Implementing CI/CD

Git folders branches and commits, bundle variables and targets, deploying bundles and the Databricks CLI.

  • 2topics
  • 10 minfast track
  • 1diagrams and exhibits
  • 10%of the exam
Start with Git Workflow in Databricks Git Folders

Topics in this chapter

Take them in order, or jump to the one you need.

  1. 1Git Workflow in Databricks Git FoldersDatabricks DEA Git folders: clone a repo, create and switch branches, commit and push, pull, resolve conflicts and open pull…5 min
  2. 2Declarative Automation Bundles and the Databricks CLIDatabricks DEA bundles: databricks.yml, variables and target overrides, development and production modes, and bundle validate…Diagram5 min

About this chapter

What this chapter covers

Implementing CI/CD is 10% of the Databricks Data Engineer Associate exam. It covers how code moves from a developer's branch to production without manual copying: working with Git inside the workspace, and packaging jobs and pipelines so the same code deploys to dev, test and prod.

The chapter has two parts: the Git workflow in Databricks Git folders (formerly Repos), and Declarative Automation Bundles (formerly Databricks Asset Bundles) with their variables, targets and Databricks CLI commands.

Questions are mostly short scenarios in which the stated requirement (latency, cost, governance, data volume) decides the answer. They are single-answer multiple choice, with short SQL, PySpark, YAML or CLI commands shown as text. There are no exhibits.

How the topics fit together

Feature branchGit folderCommit and pushPull requestGit providerBundle deploydev, test, prod targetsJobs and pipelinesrunning in each workspace

A developer edits notebooks and files in a Git folder on a feature branch, then commits and pushes. Review and merging happen in the Git provider through a pull request. A CI/CD system then runs the Databricks CLI to validate and deploy the bundle to each target.

  • Git folder questions ask how to create or switch a branch, commit and push, pull changes and where a pull request is opened.
  • Bundle configuration questions ask how variables, target overrides and deployment modes change one codebase per environment.
  • CLI questions ask which databricks bundle command validates, deploys, runs or removes a bundle.
Exam tip

When a scenario says "the same code in dev, test and prod with different settings", the answer is a bundle with targets and variables, not copied notebooks or separate repositories.

How to use these pages

Each topic page has the same shape, so you can skim for what you need.

  • What it is: the idea in plain words.
  • How it works: the mechanism, with tables and examples.
  • What to remember for the exam: the facts to memorize and how questions are phrased.
  • Common mistakes: the classic traps.
  • Check yourself: three questions to test your understanding.

Ready for more practice?

The full Databricks Data Engineer Associate question bank has 598 questions, with timed practice exams and an explanation for every answer.

Get Full AccessTry Sample Exam

This study guide is independent and is not affiliated with, endorsed by, or sponsored by Databricks. Vendor names, certification names and exam codes are trademarks of their respective owners and are used for identification only.