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Answer: Deploy the model to a managed online endpoint. During deployment, set the token_auth_mode parameter of the target configuration object to true.
The question requires deploying a model with two key requirements: (1) monitoring costs at the endpoint and deployment level, and (2) Microsoft Entra ID authentication. Managed online endpoints (Option D) provide built-in cost monitoring capabilities at both endpoint and deployment levels, which AKS deployments (Options A and B) do not offer natively. For authentication, Microsoft Entra ID integration requires token-based authentication, which is configured using the token_auth_mode parameter set to true in managed online endpoints. While Option C also uses managed online endpoints, it incorrectly suggests using the auth_mode parameter instead of token_auth_mode for Entra ID authentication. The community discussion confirms that token authentication is required for Entra ID and that managed endpoints support the necessary cost monitoring features.
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You have an Azure Machine Learning workspace and need to deploy a trained model as an online endpoint. You must monitor costs at the endpoint and deployment level, and users are required to authenticate using Microsoft Entra ID.
What should you do?
A
Deploy the model to Azure Kubernetes Service (AKS). During deployment, set the token_auth_mode parameter of the target configuration object to true.
B
Deploy the model to Azure Kubernetes Service (AKS). During deployment, set the auth_mode parameter to configure the authentication type.
C
Deploy the model to a managed online endpoint. During deployment, set the auth_mode parameter to configure the authentication type.
D
Deploy the model to a managed online endpoint. During deployment, set the token_auth_mode parameter of the target configuration object to true.
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