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AI-102 Practice Question: Implement knowledge mining and information extraction solutions

Exhibit

Refer to the exhibit.
{
  "skillset": {
    "name": "demo-skillset",
    "description": "Custom skillset for enrichment",
    "skills": [
      {
        "@odata.type": "#Microsoft.Skills.Custom.WebApiSkill",
        "name": "custom-skill",
        "description": "Calls external API for entity extraction",
        "uri": "https://myfunctionapp.azurewebsites.net/api/extract",
        "context": "/document",
        "inputs": [
          {
            "name": "text",
            "source": "/document/content"
          }
        ],
        "outputs": [
          {
            "name": "entities",
            "targetName": "extractedEntities"
          }
        ],
        "httpMethod": "POST",
        "timeout": "PT30S",
        "batchSize": 5,
        "degreeOfParallelism": 3
      }
    ]
  }
}

You have defined the custom WebApiSkill shown in the exhibit. The skill calls an Azure Function that can process up to 10 documents per second. However, you notice that the skill is failing with 429 errors. What is the most likely cause?

⚠ Common exam trap

The trap here is that candidates often focus on the batch size as the sole cause of rate limiting, overlooking that `degreeOfParallelism` multiplies the effective request rate, which is the actual trigger for 429 errors.

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 of 3 causes too many concurrent requests, exceeding the function's capacity

The `degreeOfParallelism` of 3 causes the AI Search enrichment pipeline to invoke the Azure Function with up to 3 concurrent batches, each of size 5, resulting in up to 15 documents per second. Since the function can only handle 10 documents per second, this exceeds its capacity and triggers HTTP 429 (Too Many Requests) errors.

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 timeout of 30 seconds is too short for the function to respond

    Why it's wrong here

    The function processes quickly; timeout is not the issue.

  • The batch size of 5 is too large, causing the function to receive too many documents at once

    Why it's wrong here

    Batch size of 5 is fine; the issue is concurrency.

  • The context '/document' is incorrect, causing all documents to be processed as one

    Why it's wrong here

    Context is correct for per-document processing.

  • The degreeOfParallelism of 3 causes too many concurrent requests, exceeding the function's capacity

    Why this is correct

    With batchSize 5 and degreeOfParallelism 3, up to 15 documents are sent concurrently.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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