Azure ML Pipeline Asset Registry Filter

DP-100 By islever Editorial Last updated

Short answer

D workspace

Question

You manage an Azure Machine Learning workspace named proj1. You plan to use assets defined in proj1 to create a pipeline in the Machine Learning studio designer. You need to set the Registry name filter to display only the list of assets defined in proj1. What should you set the Registry name filter to?
  1. proj1
  2. azureml-meta
  3. azureml
  4. workspace Correct Answer

Key Takeaways

Tests knowledge of asset scoping in Azure ML Designer, specifically how to isolate assets to the current workspace versus global registries.

Configuring the Azure Machine Learning Designer pipeline to use workspace-specific assets by setting the Registry name filter. Community consensus confirms that selecting 'workspace' restricts asset visibility to the current project.

Common mistake: Selecting 'azureml' or 'azureml-meta', which refers to global Microsoft-managed registries rather than user-defined workspace assets.

Expert Analysis

Why the Answer Is Correct

In the Azure Machine Learning Studio Designer, when creating a pipeline using assets (like datasets or models), you can filter the available resources. Setting the Registry name filter to 'workspace' ensures that only assets registered within the current Azure ML workspace (proj1) are displayed. This is crucial for maintaining isolation and ensuring pipelines use the correct, versioned data or models specific to that environment.

Why the Other Options Are Wrong

Options A ('proj1') is incorrect because 'proj1' is the workspace name, not a valid registry filter value in this context. Options B ('azureml-meta') and C ('azureml') refer to global registries managed by Microsoft. These contain public, curated datasets and models, not the custom assets defined by the user in their specific workspace.

Community Comment Notes

All community comments agree on option D. The top-voted comment explains that filtering by 'workspace' displays only assets defined within the current workspace, distinguishing them from other registries. This aligns with official Microsoft documentation on managing assets in the Designer.

Exam Strategy

Focus on understanding the scope of Azure ML resources: Workspace vs. Global Registry. When asked about using your own defined assets, look for options that limit the scope to the current workspace.

Community Votes

D
100%

100% of anonymous learners picked answer D. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 3 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 3

  1. goran74 👍 3
    You should set the Registry name filter to D. workspace. In Azure Machine Learning, setting the Registry name filter to "workspace" ensures that only the assets defined within the current workspace (in this case, proj1) are displayed, rather than assets from other registries.
  2. Sadhak 👍 1 Answered D
    workspace is the right answer.
  3. testgm 👍 1 Answered D
    Workspace

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