- A
Configure the custom skill to execute in batch mode and set a retry policy on the indexer
Batch mode reduces API calls, and retry policy handles transient failures.
- B
Increase the number of partitions in the Azure AI Search service
Why wrong: Partitions affect indexing throughput, not custom skill execution.
- C
Enable indexer error handling to skip failed documents
Why wrong: Skipping documents loses data, which is not acceptable.
- D
Scale out the Azure Function to multiple instances
Why wrong: Custom skills run in the context of the indexer; the indexer controls concurrency.
Question 99 of 993
Implement knowledge mining and information extraction solutions →hardMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
This AI-102 practice question tests your understanding of implement knowledge mining and information extraction solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Your team is implementing a knowledge mining solution using Azure AI Search with custom skills. The custom skill, deployed as an Azure Function, calls a third-party API to enrich documents. You notice that some documents fail enrichment with HTTP 429 (too many requests) errors. You need to ensure all documents are enriched without losing data. What should you do?
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 the custom skill to execute in batch mode and set a retry policy on the indexer
Option A is correct because configuring the custom skill to execute in batch mode reduces the number of HTTP requests to the third-party API by processing multiple documents per invocation, while setting a retry policy on the indexer ensures that failed documents due to transient HTTP 429 errors are automatically retried. This combination prevents data loss by not skipping documents and by handling rate-limiting gracefully.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure the custom skill to execute in batch mode and set a retry policy on the indexer
Why this is correct
Batch mode reduces API calls, and retry policy handles transient failures.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the number of partitions in the Azure AI Search service
Why it's wrong here
Partitions affect indexing throughput, not custom skill execution.
- ✗
Enable indexer error handling to skip failed documents
Why it's wrong here
Skipping documents loses data, which is not acceptable.
- ✗
Scale out the Azure Function to multiple instances
Why it's wrong here
Custom skills run in the context of the indexer; the indexer controls concurrency.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse scaling the Azure Function (Option D) as a solution for rate limiting, when in fact it increases the problem, or they assume skipping errors (Option C) is acceptable, missing the requirement to not lose data.
Detailed technical explanation
How to think about this question
Under the hood, the indexer's retry policy uses exponential backoff (default up to 3 retries) for transient failures like HTTP 429, while batch mode in custom skills (using the 'batchSize' property in the skill definition) groups multiple documents into a single function call, reducing the total number of API calls. In a real-world scenario, if the third-party API enforces a rate limit of 10 requests per second, batching 5 documents per call effectively reduces the request rate by 5x, and the retry policy handles any remaining throttling without data loss.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement knowledge mining and information extraction solutions — This question tests Implement knowledge mining and information extraction solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure the custom skill to execute in batch mode and set a retry policy on the indexer — Option A is correct because configuring the custom skill to execute in batch mode reduces the number of HTTP requests to the third-party API by processing multiple documents per invocation, while setting a retry policy on the indexer ensures that failed documents due to transient HTTP 429 errors are automatically retried. This combination prevents data loss by not skipping documents and by handling rate-limiting gracefully.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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