Databricks-DE-Assoc Implementing CI/CD Practice Question
A data engineering team stores its Databricks notebooks and Python files in a Git repository. They want to avoid manually copying files into the workspace and ensure that the production workspace always runs the exact code version that passed tests. Which approach should they use?
⚠ Common exam trap
The trap here is assuming that any file transfer method (like .dbc export or DBFS mount) is equivalent to Git-based deployment, when only Databricks Repos provides commit-level traceability and native execution.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use Databricks Repos to clone the Git repository into the production workspace and check out the tested commit.
Databricks Repos provides native Git integration, enabling teams to clone repositories and check out specific commits. By checking out the tested commit in the production workspace, the team ensures that the deployed code matches what passed tests, eliminating manual copying and reducing drift. This is a core practice for implementing CI/CD with Databricks.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Schedule a Databricks Job that runs a notebook which pulls the latest code from Git at runtime.
Why it's wrong here
Pulling code at runtime from a notebook adds complexity and potential failure points, such as network issues or authentication errors. It also means the job may run untested code if the branch changes. Databricks Repos is the native, supported way to manage Git-backed code in the workspace.
- ✗
Mount the Git repository as a DBFS mount point and reference notebooks directly from the mount.
Why it's wrong here
DBFS mounts are designed for data storage, not for executing notebooks or Python modules. While you could store files there, you cannot run notebooks directly from a mount, and you lose Databricks Repos features like visual Git integration and per-user credentials. This approach is not a supported CI/CD pattern.
- ✓
Use Databricks Repos to clone the Git repository into the production workspace and check out the tested commit.
Why this is correct
Databricks Repos integrates directly with Git, allowing the workspace to clone a repository and check out a specific commit or tag. This ensures the production workspace executes exactly the code version that passed tests, without manual file copying. It also provides version traceability and supports CI/CD automation through the Repos API.
- ✗
Export notebooks as .dbc files and import them into the production workspace using the Databricks CLI.
Why it's wrong here
.dbc files are proprietary archive formats that are not human-readable or version-controlled in Git. Exporting and importing them manually defeats the purpose of CI/CD because it bypasses Git history and introduces manual steps. It also makes it difficult to verify that the imported code matches the tested commit.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Databricks exam blueprint
This Databricks-DE-Assoc practice question is part of Courseiva's free Databricks certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Databricks-DE-Assoc exam.