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Computer VisionhardMultiple ChoiceObjective-mapped

AI-103 Computer Vision Practice Question

You are deploying a Custom Vision object detection model as a Docker container on an Azure Kubernetes Service (AKS) cluster. During load testing, you notice high memory consumption and container restarts. Which configuration setting in the deployment manifest should you review to ensure stability?

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

Kubernetes resource requests and limits for memory and CPU.

Custom Vision container deployments require proper CPU and memory limits/requests configured in the Kubernetes pod spec to prevent Out-Of-Memory (OOM) kills during heavy inference workloads.

Answer analysis

Option-by-option breakdown

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

  • Billing endpoint URL syntax.

    Why it's wrong here

    Billing endpoint affects license validation, not memory usage or container restarts.

  • Azure Blob Storage connection string persistence.

    Why it's wrong here

    Inference containers do not require blob storage connection strings for prediction.

  • Custom Vision iteration publishing name environment variable.

    Why it's wrong here

    Publishing name dictates which model iteration loads, not container resource stability.

  • Kubernetes resource requests and limits for memory and CPU.

    Why this is correct

    Configuring adequate memory and CPU limits prevents OOM termination and CPU throttling for vision containers.

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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-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.