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Plan and manage an Azure AI solutionhardMultiple ChoiceObjective-mapped

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

You are an Azure AI engineer at Contoso Ltd. The company has an Azure AI solution that uses Azure AI Language to analyze customer feedback. The solution is deployed in the East US region and uses the S0 pricing tier. Recently, the volume of feedback has increased significantly, causing the service to throttle requests. The application logs show HTTP 429 (Too Many Requests) errors during peak hours. The development team has already implemented retry logic with exponential backoff, but the errors persist. You need to recommend a solution to handle the increased load without changing the application code. The solution must minimize cost. What should you do?

⚠ Common exam trap

Test-takers frequently think caching (Azure Front Door) or region relocation can solve throttling, but they fail to recognize that throttling is a rate-limit issue tied to the pricing tier, not network latency or content caching.

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

Upgrade the Azure AI Language resource to a higher pricing tier (e.g., S1) or create additional resources and load balance.

Upgrading to a higher pricing tier (e.g., S1) increases the transactions-per-second (TPS) limit, directly addressing the HTTP 429 throttling errors without requiring code changes. Creating additional resources and load-balancing also distributes the request volume, but upgrading the existing resource is the simplest and most cost-effective approach when retry logic already fails.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Upgrade the Azure AI Language resource to a higher pricing tier (e.g., S1) or create additional resources and load balance.

    Why this is correct

    Higher tiers provide higher rate limits and throughput.

  • Use Azure Front Door to cache responses and reduce load on the service.

    Why it's wrong here

    Front Door caches static content, not dynamic API responses.

  • Switch the Azure AI Language resource to the Free tier to reduce costs.

    Why it's wrong here

    Free tier has lower rate limits, increasing throttling.

  • Move the service to a different Azure region with higher capacity.

    Why it's wrong here

    Moving regions does not change the capacity of a single resource.

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