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. 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.
Refer to the exhibit. You are reviewing a content safety policy for an Azure AI Foundry deployment. The policy rate limits to 20 requests per minute. A user submits 50 requests in one minute. How many requests are allowed?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
20
The content safety policy enforces a rate limit of 20 requests per minute. When a user submits 50 requests in one minute, the rate limiter allows only the first 20 requests and blocks the remaining 30. This is a standard token-bucket or sliding-window rate-limiting behavior in Azure AI Foundry, where exceeding the limit results in HTTP 429 (Too Many Requests) for excess requests.
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.
✓
20
Why this is correct
The rate limit policy sets 20 requests per minute.
Related concept
Read the scenario before looking for a memorised answer.
✗
50
Why it's wrong here
The limit is 20 per minute, not 50.
✗
100
Why it's wrong here
100 is the hourly quota, not the per-minute limit.
Common exam trap: answer the scenario, not the keyword
Microsoft often tests the misconception that exceeding a rate limit blocks all requests, when in fact the limit is a threshold that allows the first N requests and denies the rest.
Detailed technical explanation
How to think about this question
Azure AI Foundry rate limiting uses a sliding window algorithm that tracks request timestamps. The first 20 requests within a 60-second window are accepted; subsequent requests receive a 429 response with a Retry-After header. This prevents resource exhaustion and ensures fair usage across tenants, similar to Azure API Management's rate-limit policy.
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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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.
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: 20 — The content safety policy enforces a rate limit of 20 requests per minute. When a user submits 50 requests in one minute, the rate limiter allows only the first 20 requests and blocks the remaining 30. This is a standard token-bucket or sliding-window rate-limiting behavior in Azure AI Foundry, where exceeding the limit results in HTTP 429 (Too Many Requests) for excess requests.
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.
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Question Discussion
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