試験AI-300 トピック1 問題47 スレッド
Microsoft AI-300のリアル試験問題集
問題 #: 47
トピック #: 1
問題 #: 47
トピック #: 1
An Azure Machine Learning workspace contains multiple registered versions of a model that is used in production.
An older model version must no longer be deployable, but it must remain available for compliance review and potential rollback.
You need to change the state of the model version to meet the requirements.
What should you do?
An older model version must no longer be deployable, but it must remain available for compliance review and potential rollback.
You need to change the state of the model version to meet the requirements.
What should you do?
おすすめの解答：C 解答を投票する
To ensure that older Azure Machine Learning model versions are no longer deployable but remain available for reference or historical tracking, you should archive those specific versions.
How to Archive Model Versions
Archiving a model version effectively hides it from standard list queries and management interfaces, preventing accidental deployment while maintaining its metadata and files in the workspace.
Behavior of Archived Models:
Hidden by Default: They will no longer appear in the Azure Machine Learning Studio model list unless you explicitly filter for archived assets.
Referenceable: You can still reference and use an archived model version in existing workflows if you have its specific version number.
Restoreable: If you need to redeploy the model in the future, you can use the restore command to make it active again.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-models
How to Archive Model Versions
Archiving a model version effectively hides it from standard list queries and management interfaces, preventing accidental deployment while maintaining its metadata and files in the workspace.
Behavior of Archived Models:
Hidden by Default: They will no longer appear in the Azure Machine Learning Studio model list unless you explicitly filter for archived assets.
Referenceable: You can still reference and use an archived model version in existing workflows if you have its specific version number.
Restoreable: If you need to redeploy the model in the future, you can use the restore command to make it active again.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-models
Konishi 2026-07-07 04:15:03
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