Question 235 of 988

Plan and manage an Azure AI solution →easyMultiple ChoiceObjective-mapped

Quick Answer

The answer is that the degreeOfParallelism is set too high, overwhelming the Azure Function. When a custom skill timeout occurs in Azure AI Search, the degreeOf parallelism parameter controls how many concurrent requests the indexer sends to your skill endpoint. A value of 10 means ten documents are processed simultaneously, and if your Azure Function lacks sufficient resources or suffers from cold starts, it cannot keep up, causing requests to queue and eventually time out. On the AI-102 exam, this scenario tests your understanding of how custom skill execution scales—many candidates mistakenly blame the indexer batch size or document size, but the core issue is concurrency throttling. Remember the memory tip: “Parallelism is power, but too much power causes a timeout shower.” Lowering the degreeOfParallelism spreads the load, giving each request a fair chance to complete without overwhelming the function.

AI-102 Plan and manage an Azure AI solution Practice Question

This AI-102 practice question tests your understanding of plan and manage an azure ai solution. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.

Exhibit

{
  "properties": {
    "description": "My custom skill",
    "type": "Custom.WebApiSkill",
    "context": "/document",
    "inputs": [
      {
        "name": "text",
        "source": "/document/content"
      }
    ],
    "outputs": [
      {
        "name": "entities",
        "targetName": "entities"
      }
    ],
    "uri": "https://myfunctionapp.azurewebsites.net/api/extract-entities",
    "httpMethod": "POST",
    "timeout": "00:00:30",
    "batchSize": 1,
    "degreeOfParallelism": 10
  }
}

Refer to the exhibit. You have an Azure AI Search skillset with the custom skill shown. When you run the indexer, you notice that many documents fail with a timeout error. What is the most likely cause of the timeouts?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

Question 1easymultiple choice

Full question →

Exhibit

{
  "properties": {
    "description": "My custom skill",
    "type": "Custom.WebApiSkill",
    "context": "/document",
    "inputs": [
      {
        "name": "text",
        "source": "/document/content"
      }
    ],
    "outputs": [
      {
        "name": "entities",
        "targetName": "entities"
      }
    ],
    "uri": "https://myfunctionapp.azurewebsites.net/api/extract-entities",
    "httpMethod": "POST",
    "timeout": "00:00:30",
    "batchSize": 1,
    "degreeOfParallelism": 10
  }
}

A
The HTTP method should be GET instead of POST.
Why wrong: POST is the correct method for sending input data; GET would not work.
B
The timeout value is too short for the function to complete.
Why wrong: 30 seconds is the maximum allowed; increasing it is not possible beyond that limit.
C
The degreeOfParallelism is set too high, overwhelming the Azure Function.
High parallelism can cause the function to throttle, leading to timeouts.
D
The batch size is too large, causing each request to process too many documents.
Why wrong: Batch size is 1, so each request handles a single document.

Full breakdown with real-world context →

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

✓

The degreeOfParallelism is set too high, overwhelming the Azure Function.

The custom skill in Azure AI Search is configured with a `degreeOfParallelism` of 10, meaning up to 10 concurrent requests are sent to the Azure Function. If the function cannot handle this level of concurrency (e.g., due to limited resources or cold starts), requests will queue up and eventually time out. Reducing the `degreeOfParallelism` would throttle the load and prevent the function from being overwhelmed.

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 HTTP method should be GET instead of POST.
Why it's wrong here
POST is the correct method for sending input data; GET would not work.
✗
The timeout value is too short for the function to complete.
Why it's wrong here
30 seconds is the maximum allowed; increasing it is not possible beyond that limit.
✓
The degreeOfParallelism is set too high, overwhelming the Azure Function.
Why this is correct
High parallelism can cause the function to throttle, leading to timeouts.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The batch size is too large, causing each request to process too many documents.
Why it's wrong here
Batch size is 1, so each request handles a single document.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Microsoft often tests the misconception that timeouts are always caused by a short timeout value or large batch size, but here the trap is that the `degreeOfParallelism` setting is the hidden culprit that overwhelms the function, not the batch size or timeout duration.

Detailed technical explanation

How to think about this question

Under the hood, Azure AI Search sends batched documents to a custom skill via HTTP POST. The `degreeOfParallelism` controls how many of these batches are sent concurrently. If the Azure Function is on a Consumption plan, it has a limited number of concurrent executions (e.g., 200 by default), but if the function is slow (e.g., due to cold starts or heavy computation), even a small number of concurrent requests can exhaust its capacity, causing subsequent requests to wait and eventually exceed the 230-second timeout. This is a common scaling issue where parallelism must be tuned to match the function's throughput.

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

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this AI-102 question test?

Plan and manage an Azure AI solution — This question tests Plan and manage an Azure AI solution — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: The degreeOfParallelism is set too high, overwhelming the Azure Function. — The custom skill in Azure AI Search is configured with a `degreeOfParallelism` of 10, meaning up to 10 concurrent requests are sent to the Azure Function. If the function cannot handle this level of concurrency (e.g., due to limited resources or cold starts), requests will queue up and eventually time out. Reducing the `degreeOfParallelism` would throttle the load and prevent the function from being overwhelmed.

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.

Are there clue words in this question I should notice?

Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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