AI-102 Plan and manage an Azure AI solution Practice Question
Your Azure AI Search index contains millions of documents. Users report that search results are slow for complex queries. You need to improve query performance without reducing result quality. Which action should you take?
⚠ Common exam trap
A common mix-up: candidates confuse replicas (which improve query performance and availability) with partitions (which improve indexing speed and storage capacity), leading them to choose options that degrade functionality instead of scaling resources.
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 replicas
Increasing the number of replicas in Azure AI Search distributes query load across multiple copies of the index, enabling parallel processing of complex queries. This directly improves query throughput and latency without altering the index schema or reducing result quality, as replicas provide dedicated resources for query execution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reduce the maximum number of results returned per query
Why it's wrong here
Reducing results may affect user experience but not query performance.
- ✓
Increase the number of replicas
Why this is correct
Adding replicas allows load balancing and faster query responses.
- ✗
Remove all facet fields from the index
Why it's wrong here
Removing facets reduces filtering options but doesn't directly improve query performance.
- ✗
Disable complex query types such as fuzzy and regex
Why it's wrong here
Disabling query types may reduce result quality.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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