Answer-first summary for fast verification
Answer: Model files, Compute target
For deploying an MLflow model for batch inference in Azure Machine Learning, the two required components are the model files (B) and a compute target (E). The model files contain the trained MLflow model, which includes all necessary artifacts and the MLmodel file that describes the environment and dependencies. The compute target (E) is needed to execute the batch inference job. Environment (A) is not required because MLflow models automatically define their own environment through the MLmodel file. Online endpoint (C) and Kubernetes online endpoint (D) are for real-time inference, not batch inference, making them incorrect for this scenario. The community discussion, with 86% selecting BE and upvoted comments referencing Microsoft documentation, confirms that MLflow models do not require specifying an environment separately, as it is self-contained.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
No comments yet.
You have an MLflow model that you need to deploy to Azure Machine Learning for batch inference.
You must create the batch deployment.
Which two components are required? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A
Environment
B
Model files
C
Online endpoint
D
Kubernetes online endpoint
E
Compute target