You train and register an Azure Machine Learning model You plan to deploy the model to an online endpoint You need to ensure that applications will…

The solution is incorrect because it proposes using amltoken authentication. Azure Machine Learning tokens (amltoken) are time-bound security artifacts that expire, requiring clients to periodically request a new token. The goal explicitly requires a non-expiring artifact. The appropriate authentication method for this requirement is key-based authentication (authmode = 'key'), which provides static primary and secondary keys that do not expire unless they are manually regenerated by the user. Since the proposed solution uses an authentication method with an expiring artifact, it does not meet the stated goal.

A. Yes: This is incorrect. The amltoken authentication method uses tokens that expire, which directly contradicts the requirement for a non-expiring artifact for application access.

1. Microsoft. (2023). Authenticate clients for online endpoints. Microsoft Learn. Retrieved from https://learn.microsoft.com/en-us/azure/machine-learning/how-to-authenticate-online-endpoint.

Section: Authenticate with keys: This section states

"Authentication with a key is common for existing clients and is a simple approach... Keys don't expire

but they can be regenerated." This confirms that keys are non-expiring artifacts.

Section: Authenticate with tokens: This section explicitly states

"Azure Machine Learning tokens (amltoken) and Azure Active Directory tokens (aadtoken) both have an expiration." This confirms that amltoken is an expiring artifact

making it unsuitable for the stated goal.