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ML Model Lifecycle And OperationshardMultiple ChoiceObjective-mapped

AI-300 ML Model Lifecycle And Operations Practice Question

You need to ensure that your Azure ML models are deployed with high availability across multiple regions. Which deployment strategy should you configure?

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

Managed Online Endpoints with multiple deployments

Managed Online Endpoints support multi-region traffic distribution by using managed deployments behind a single endpoint.

Answer analysis

Option-by-option breakdown

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

  • Kubernetes Online Endpoints

    Why it's wrong here

    Requires manual cluster management and is not the native managed high-availability solution.

  • Managed Online Endpoints with multiple deployments

    Why this is correct

    Managed Online Endpoints allow splitting traffic across multiple deployments in different regions.

  • Batch Endpoints

    Why it's wrong here

    Batch endpoints are designed for asynchronous processing, not real-time high-availability requests.

  • Azure Container Instances (ACI)

    Why it's wrong here

    ACI is deprecated for production scale and does not support native multi-region traffic routing.

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JA

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.