Microsoft Azure AI Engineer Associate AI-102 Practice Question
You need to create an Azure AI Foundry hub that will be used by multiple generative-AI projects in your organization. The hub must meet the following requirements:
Be provisioned by using infrastructure as code so it can be deployed to multiple subscriptions.
Automatically create the minimum set of dependent Azure resources that any project inside the hub will need.
Which deployment approach should you use first to be sure that both requirements are satisfied?
Create the hub manually in the Azure portal and then export a template for reuse in other subscriptions.
Use an Azure PowerShell script that calls New-AzResourceGroupDeployment with inline parameters to provision only the hub.
Run an Azure CLI command that creates an Azure AI Foundry project and hub in a single step.
Deploy the hub by using an Azure Resource Manager (ARM) or Bicep template that defines the Azure AI Foundry hub resource and its dependencies.
Deploying the hub with an Azure Resource Manager (ARM) or Bicep template meets both requirements. A template is fully declarative, so you can repeatedly deploy the same hub definition to any subscription. The template can include the hub plus its dependent resources (Azure Storage account, Azure Key Vault, Azure Application Insights, and optionally an Azure Container Registry and Azure AI Services account). When the hub is created with these dependencies, every new project you create under the hub automatically reuses those resources. Creating the hub manually or by using an ad-hoc PowerShell script is not idempotent across subscriptions, and project-level CLI commands cannot run until a hub already exists.
Ask Bash
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What is an ARM template and how does it ensure consistent deployment?
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What is the difference between Bicep and ARM templates?
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What does 'idempotent' mean in the context of Azure deployments?
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Microsoft Azure AI Engineer Associate AI-102
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