Designing and Implementing a Data Science Solution on Azure — Question 183

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You have an Azure Machine Learning workspace that includes an AmlCompute cluster and a batch endpoint.

You clone a repository that contains an MLflow model to your local computer.

You need to ensure that you can deploy the model to the batch endpoint.

Solution: Add a compute resource to the workspace.

Does the solution meet the goal?

Answer options

Correct answer: A

Explanation

The proposed solution is indeed correct because adding a compute resource to the workspace is essential for deploying the MLflow model to the batch endpoint. Without a compute resource, the batch endpoint would not have the necessary infrastructure to run the model. The other option, which states 'No,' is incorrect as it overlooks the requirement for compute resources in the deployment process.