AI-103 Plan And Manage AN Azure AI Solution Practice Question
You are managing an Azure AI Search service with multiple replicas and partitions. During peak query hours, latency increases significantly, and CPU utilization on the search service hits 95%. You need to scale the service to improve query throughput without altering the index data schema. Which scaling action should you take?
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
✓
Increase the number of search replicas in the Azure portal or via CLI.
Scaling out by adding search replicas increases query throughput and high availability.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the number of search partitions.
Why it's wrong here
Partitions split index storage capacity for large datasets; adding partitions when CPU is bottlenecked by query load is less effective than adding replicas.
- ✗
Disable semantic ranking to reduce compute overhead.
Why it's wrong here
While semantic ranking uses compute, the proper infrastructure scaling path for query latency bottlenecks is adding replicas.
- ✓
Increase the number of search replicas in the Azure portal or via CLI.
Why this is correct
Replicas handle search query load; adding replicas increases query throughput and read capacity.
- ✗
Migrate the service to the Free pricing tier.
Why it's wrong here
The Free tier has lower performance limits and would immediately crash under high traffic.
About these practice questions
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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.