Exam Databricks-Machine-Learning-Professional Topic 10 Question 121 Discussion

Actual exam question for Databricks's Databricks-Machine-Learning-Professional exam
Question #: 121
Topic #: 10
A Machine Learning Engineer wants to implement MLOps. They currently have three environments: dev, stage, and prod. They have many private PyPI packages that they use to train their models, and they are concerned that their environments will not be consistent between dev, stage, and prod. The engineer needs to follow enterprise scaling and CI/CD best practices to ensure that their environments are consistent. Which approach will do this?

Suggested Answer: B Vote an answer

Defining dependencies at the job or task level using Databricks Asset Bundles or Terraform aligns with enterprise MLOps and CI/CD best practices. This approach makes environment configuration declarative, version-controlled, and reproducible across dev, stage, and prod, ensuring consistent use of private PyPI packages without relying on mutable clusters or manual installation steps.

by Harvey at Jun 28, 2026, 06:13 AM

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