The answer is that the custom skill must complete within 230 seconds, the API must be accessible from the search service, and data size limits apply with a maximum payload of 16 MB. These three constraints are critical because Azure AI Search enforces a hard timeout on all custom skill executions, and the enrichment pipeline cannot process responses that exceed the payload limit or fail due to network inaccessibility. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your understanding of the operational boundaries when designing custom skills for Azure AI Search that call an external API for specialized data extraction, often appearing as a trap where candidates mistakenly think the skill must be written in a specific language or can only have a single input and output. Remember the mnemonic TAD: Timeout (230s), Accessibility (public or private endpoint), and Data size (16 MB).
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.
Which THREE considerations are important when designing a custom skill for Azure AI Search that calls an external API for specialized data extraction?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The API endpoint must be reachable from the search service
Options B, C, and D are correct. Custom skills must have a timeout of 230 seconds (default), the API must be accessible from the search service (public or via private endpoint), and data size limits apply (payload up to 16 MB). Option A is incorrect because custom skills can be written in any language that supports JSON. Option E is incorrect because the skill can have multiple inputs and outputs.
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.
✓
The API endpoint must be reachable from the search service
Why this is correct
The search service must be able to call the API over the network.
Related concept
Read the scenario before looking for a memorised answer.
✗
The skill can only accept one input and produce one output
Why it's wrong here
Custom skills can accept multiple inputs and produce multiple outputs.
The maximum input size for a custom skill is 16 MB.
Related concept
Read the scenario before looking for a memorised answer.
✓
The skill must complete within 230 seconds
Why this is correct
The default timeout for custom skills is 230 seconds.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Command / output trap
Custom skills can accept multiple inputs and produce multiple outputs.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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: The API endpoint must be reachable from the search service — Options B, C, and D are correct. Custom skills must have a timeout of 230 seconds (default), the API must be accessible from the search service (public or via private endpoint), and data size limits apply (payload up to 16 MB). Option A is incorrect because custom skills can be written in any language that supports JSON. Option E is incorrect because the skill can have multiple inputs and outputs.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which THREE factors should you consider when designing a knowledge mining solution that uses Azure AI Search and custom skills to extract insights from large volumes of documents?
hard
A.The number of knowledge store projections affects indexing speed
✓ B.The maximum execution time of the custom skill must fit within the indexer timeout
✓ C.Incremental enrichment should be enabled to avoid reprocessing unchanged documents
D.Semantic ranking configuration must be included in the skillset
✓ E.The custom skill should be stateless and idempotent to allow parallel execution
Why B: Options A, C, and E are correct. A: Skillset execution time must be within indexer timeout limits. C: Azure Functions can scale to handle concurrent requests. E: Incremental enrichment reduces reprocessing. Option B is wrong because knowledge stores are for structured output, not performance. Option D is wrong because semantic ranking is for search relevance, not extraction.
Variation 2. You are designing a knowledge mining solution that ingests content from SharePoint Online. The solution must index documents and also extract custom metadata such as project name and client ID using a custom skill. The custom skill is an Azure Function that calls an external API. The external API has a rate limit of 100 requests per minute. Your indexer processes 1000 documents per hour. How should you configure the indexer to avoid hitting the rate limit?
hard
A.Use a different custom skill that doesn't call the external API.
✓ B.Schedule the indexer to run every 2 hours with a batch size of 20.
C.Increase the indexer's batch size to 100.
D.Increase the indexer's maximum parallelism to 10.
Why B: Option B uses scheduling to spread the load. Option A increases parallelism, making it worse. Option C increases batch size, causing more requests per batch. Option D uses a different skill but doesn't address rate limit.
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Question Discussion
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