Implement knowledge mining and information extraction solutions →easyMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
Your company uses Azure AI Search to power a customer support portal. The search index includes product documentation and known issues. Recently, the portal's search performance has degraded, and users report slow response times. You need to identify the cause of the performance issue. What should you check first?
⚠ Common exam trap
It's easy for candidates to confuse indexing-related metrics (like skillset execution or index size) with query performance metrics, leading them to check storage size or schema complexity instead of the direct performance indicators of query latency and CPU usage.
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
✓
Review the search service metrics for high query latency and CPU usage.
High query latency and CPU usage are direct indicators of performance bottlenecks in Azure AI Search. The search service metrics in the Azure portal provide real-time data on query execution time and resource consumption, which are the first signals to investigate when users report slow response times. Checking these metrics helps identify whether the issue stems from excessive query load, insufficient replicas, or inefficient 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.
- ✓
Review the search service metrics for high query latency and CPU usage.
Why this is correct
Metrics help identify performance bottlenecks.
- ✗
Check the size of the index storage in the Azure portal.
Why it's wrong here
Storage size alone does not cause slow queries.
- ✗
Ensure the index schema does not have too many fields.
Why it's wrong here
Number of fields is not a typical cause of slow queries.
- ✗
Verify that the skillset is not running during peak hours.
Why it's wrong here
Skillsets run during indexing, not querying.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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