Implement knowledge mining and information extraction solutions →hardMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
You are implementing a knowledge mining solution with Azure AI Search that ingests data from Azure Blob Storage. The pipeline includes a custom skill that calls an external API for specialized entity extraction. The custom skill sometimes returns HTTP 429 (Too Many Requests). How should you handle this to ensure reliable indexing?
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
✓
Configure a retry policy on the custom skill
Azure AI Search indexers can be configured with a retry policy for custom skills. When a custom skill returns HTTP 429 (Too Many Requests), a retry policy will automatically retry the skill execution after a backoff delay, helping to handle rate limiting from the external API. Option A is incorrect: reducing the batch size may reduce the number of requests per batch, but if the API rate limit is per request, it may not resolve the 429 error. Option B is incorrect: increasing the skill timeout does not address rate limiting; it only allows more time for a single request. Option D is incorrect: scheduling the indexer less frequently only reduces the frequency of index runs, not the rate of requests during a run.
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 batch size in the indexer
Why it's wrong here
Batch size reduction may not resolve rate limiting if the API is per request.
- ✗
Increase the skill timeout
Why it's wrong here
Timeout increase does not handle 429 errors.
- ✓
Configure a retry policy on the custom skill
Why this is correct
A retry policy with exponential backoff handles 429 errors by retrying after delays.
- ✗
Schedule the indexer to run less frequently
Why it's wrong here
This reduces overall load but doesn't handle bursts.
Visual reference
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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