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Question 109 - DP-100 discussion

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HOTSPOT

You have an Azure Machine Learning workspace named workspace1 that is accessible from a public endpoint. The workspace contains an Azure Blob storage datastore named store1 that represents a blob container in an Azure storage account named account1. You configure workspace1 and account1 to be accessible by using private endpoints in the same virtual network.

You must be able to access the contents of store1 by using the Azure Machine Learning SDK for Python. You must be able to preview the contents of store1 by using Azure Machine Learning studio.

You need to configure store1.

What should you do? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.


Question 109
Correct answer: Question 109

Explanation:

Box 1: Regenerate the keys of account1.

Azure Blob Storage support authentication through Account key or SAS token.

To authenticate your access to the underlying storage service, you can provide either your account key, shared access signatures (SAS) tokens, or service principal

Box 2: Update the authentication for store1.

For Azure Machine Learning studio users, several features rely on the ability to read data from a dataset; such as dataset previews, profiles and automated machine learning. For these features to work with storage behind virtual networks, use a workspace managed identity in the studio to allow Azure Machine Learning to access the storage account from outside the virtual network.

Note: Some of the studio's features are disabled by default in a virtual network. To re-enable these features, you must enable managed identity for storage accounts you intend to use in the studio.

The following operations are disabled by default in a virtual network:

Preview data in the studio.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/how-to-access-data

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asked 02/10/2024
Youssef El Akhal
39 questions
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