Microsoft Azure AI Engineer Associate AI-102 Practice Question
You are creating a project inside Azure AI Foundry and must give your team access to GPT-4 Turbo for prompt flow experiments. The solution should avoid distributing secret keys and rely on role-based access that Foundry can automatically enforce across the project's resources. What is the most appropriate way to provision the capability?
Deploy the GPT-4 Turbo container image to Azure Container Instances and point Foundry to the public endpoint.
Register the Microsoft.CognitiveServices provider and submit an access request email; the GPT-4 Turbo model will then appear automatically in the project without further action.
Create a separate Azure OpenAI resource in the portal and send the generated access key to the development team.
Use the Foundry model catalog to add a GPT-4 Turbo deployment to the project; Foundry will create a managed Azure OpenAI connection that is secured with Entra ID and governed by RBAC.
Inside a Foundry project you can add an Azure OpenAI model straight from the model catalog. When you select GPT-4 Turbo and deploy it, Foundry automatically creates or links an Azure OpenAI resource and exposes it to the project through a managed connection secured with Microsoft Entra ID. Because the connection is handled by Foundry, developers authenticate with their Azure AD identities and no secret keys have to be shared. Creating a stand-alone Azure OpenAI resource, running the model in a container, or relying only on provider registration would either require manual key distribution or would not surface the model inside the project automatically.
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