Microsoft Azure AI Engineer Associate AI-102 Practice Question
You are designing a multi-team generative AI environment in Azure AI Foundry. All teams must be able to pull the same set of approved foundation models, but each team needs isolated experiment tracking, its own prompt flows, and separate spending limits. According to the Foundry resource hierarchy, which action should you perform first to meet the requirements?
Provision a separate Azure AI Foundry project for each team.
Set up a dedicated Azure AI workspace with per-team cost management tags.
Create an Azure AI Foundry hub in the subscription.
Deploy an Azure OpenAI model deployment in a shared resource group.
In Azure AI Foundry the top-level construct is the hub. A hub is created at the subscription level and defines the catalog of foundation models, centrally managed policy settings, and shared infrastructure budgets for everything that is built beneath it. Individual teams then create one or more projects inside the hub; projects inherit the approved models but have their own prompt flows, experiment artifacts, and cost tracking. Therefore, creating a hub is the necessary first step before the separate team projects can be provisioned. Creating projects, resource groups, or OpenAI deployments can only occur after a hub exists, and none of those actions alone provides the shared model catalog required across teams.
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