The answer is to implement client-side throttling and retry logic, use Azure Queue Storage to decouple ingestion from processing, and select the S0 pricing tier for Azure AI Language. This combination is correct because Azure Queue Storage acts as a cost-efficient buffer that absorbs bursts of up to 500 requests per second, allowing the AI service to process at its average 50 requests per second without over-provisioning. The S0 tier provides sufficient throughput for sustained loads, while client-side retry logic handles transient throttling from the queue, ensuring no data loss during spikes. On the AI-102 exam, this scenario tests your understanding of asynchronous processing patterns and tier selection for cost optimization—a common trap is choosing a higher tier to handle bursts directly, which wastes money. The key insight is that queues smooth traffic spikes without scaling the AI resource. Memory tip: think “Queue, Throttle, S0” as the three pillars of burst handling.
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.
You are architecting an Azure AI solution that uses Azure AI Language to analyze text for sentiment and key phrases. The solution must handle bursts of up to 500 requests per second but average only 50 requests per second. You need to ensure cost efficiency while meeting performance requirements. Which THREE actions should you take?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use Azure Queue Storage to buffer requests during spikes
Option A is correct because Azure Queue Storage can decouple the ingestion of requests from processing, allowing the solution to buffer bursts of up to 500 requests per second while the Azure AI Language service processes at a lower sustained rate. This prevents request throttling and enables cost-efficient scaling by using a lower-cost queue to absorb spikes rather than over-provisioning the AI service tier.
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.
✓
Use Azure Queue Storage to buffer requests during spikes
Why this is correct
Decouples ingestion and processing, smoothing out bursts.
Related concept
Read the scenario before looking for a memorised answer.
✗
Select the Free tier and implement queuing
Why it's wrong here
Free tier limited to 20 requests per minute, cannot handle 500 RPS.
✓
Use the S0 pricing tier
Why this is correct
S0 tier supports up to 1000 requests per second, sufficient for bursts.
Related concept
Read the scenario before looking for a memorised answer.
✓
Implement client-side throttling and retry logic
Why this is correct
Helps manage rate limits gracefully.
Related concept
Read the scenario before looking for a memorised answer.
✗
Deploy the service in multiple regions
Why it's wrong here
Not needed for burst handling; increases cost.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume a higher pricing tier (like S0) alone can handle bursts, but without queuing and retry logic, the service will still throttle requests, leading to failures or the need for costly over-provisioning.
Detailed technical explanation
How to think about this question
Azure Queue Storage uses a simple REST API to store messages up to 64 KB each, with a maximum queue size of 500 TB, making it ideal for buffering high-frequency bursts. The client-side retry logic (Option D) with exponential backoff is essential to handle transient failures when the AI Language service returns HTTP 429 (Too Many Requests) or 503 (Service Unavailable) during peak load, ensuring reliability without requiring a higher-cost tier.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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: Use Azure Queue Storage to buffer requests during spikes — Option A is correct because Azure Queue Storage can decouple the ingestion of requests from processing, allowing the solution to buffer bursts of up to 500 requests per second while the Azure AI Language service processes at a lower sustained rate. This prevents request throttling and enables cost-efficient scaling by using a lower-cost queue to absorb spikes rather than over-provisioning the AI service tier.
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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