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AI-103 Implement Generative AI And Agentic Solutions Practice Question

You are configuring a Microsoft Foundry project to deploy a multimodal model. You need to ensure that the model deployment scales automatically based on request volume while minimizing management overhead. Which deployment type should you select?

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

Standard deployment

Standard deployment in Azure AI Foundry supports automatic scaling based on traffic volume with managed infrastructure. Provisioned Throughput is for dedicated guaranteed capacity, and Batch deployments are for asynchronous processing.

Answer analysis

Option-by-option breakdown

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

  • Standard deployment

    Why this is correct

    Standard deployment provides auto-scaling and managed infrastructure suitable for dynamic request volumes.

  • Local container deployment

    Why it's wrong here

    Local container deployment requires manual management of the underlying compute infrastructure.

  • Provisioned Throughput deployment

    Why it's wrong here

    Provisioned Throughput is designed for guaranteed throughput units rather than automatic scale-out based on fluctuating web traffic.

  • Batch deployment

    Why it's wrong here

    Batch deployment is intended for asynchronous, high-volume offline scoring jobs rather than real-time API endpoints.

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Senior Network & Security Engineer · founder of Courseiva

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

This AI-103 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-103 exam.