Implement knowledge mining and information extraction solutions →mediumMultiple ChoiceObjective-mapped
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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Senior Network & Security Engineer · founder of Courseiva
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