Microsoft Certified: Azure AI Engineer AssociatePlan and manage an Azure AI solutionEasy
A research institution is developing an Azure AI solution to analyze large datasets from scientific experiments. The solution uses Azure Machine Learning for model training and inference. To ensure reproducible deployments and consistent environments across development, testing, and production, the institution wants to automate the provisioning and configuration of all Azure resources. Which approach should they use for this automation?
- AManually create and configure resources through the Azure portal.
- BImplement a GitOps workflow with direct API calls.
- CWrite PowerShell scripts for each resource deployment.
- DUse Azure Resource Manager (ARM) templates or Bicep.
Show answer & explanationAnswer & explanation
Correct answer: D. Use Azure Resource Manager (ARM) templates or Bicep.
Azure Resource Manager (ARM) templates and Bicep are declarative infrastructure as code (IaC) tools that allow you to define and deploy Azure resources consistently and reproducibly across different environments. This is the standard and recommended approach for automated provisioning.
Why the other options are wrong
- A. Manual creation is not reproducible, consistent, or scalable for automated deployments.
- B. While GitOps is a good practice, direct API calls for provisioning are low-level and less efficient than using declarative ARM/Bicep templates for IaC.
- C. PowerShell scripts are imperative and can be prone to inconsistencies, making them less ideal than declarative IaC for reproducible deployments.
Infrastructure as Code (IaC)
Managing and provisioning infrastructure through code instead of manual processes, enabling consistent, repeatable, and version-controlled deployments.
- Defines infrastructure declaratively (e.g., ARM templates, Bicep).
- Ensures consistency across environments.
- Enables version control and automated deployments.
Memory trick: ARM/Bicep builds AI infrastructure like code.