Azure ML Pipeline Asset Registry Filter
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?
Community Votes
100% of anonymous learners picked answer D. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
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.
Selecting 'azureml' or 'azureml-meta', which refers to global Microsoft-managed registries rather than user-defined workspace assets.
Community Discussion (4 comments)
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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.Official Reference
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.