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AI-300 Mlops Infrastructure Practice Question

You are creating a CI/CD pipeline in Azure DevOps. Which extension is essential to integrate Azure ML tasks into your build/release pipeline?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Azure Machine Learning extension

The Azure Machine Learning extension provides the necessary tasks to interact with the Azure ML CLI from DevOps pipelines.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Visual Studio Code extension

    Why it's wrong here

    This is for local development, not server-side CI/CD automation.

  • Terraform extension

    Why it's wrong here

    Terraform is for infrastructure provisioning, not ML model lifecycle orchestration.

  • Azure Machine Learning extension

    Why this is correct

    This extension enables native tasks like model registration, training runs, and deployment.

  • Kubernetes extension

    Why it's wrong here

    While useful for AKS, it does not provide Azure ML-specific model lifecycle tasks.

Visual reference

Client DHCP Server 1 Discover (broadcast) 2 Offer (IP: 192.168.1.10) 3 Request (I accept) 4 Acknowledge (lease confirmed) DORA — the four-step DHCP lease process

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Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Microsoft exam blueprint

This AI-300 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-300 exam.