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Deploying and Managing Generative AI on OCIhardMultiple ChoiceObjective-mapped

1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question

A company has deployed a generative AI endpoint using a custom fine-tuned model. They observe that the endpoint is returning 429 (Too Many Requests) errors during business hours. They need to handle this without losing requests. What should they implement?

⚠ Common exam trap

Oracle often tests the misconception that increasing capacity (Option D) or reducing concurrency (Option C) is the primary solution for rate limiting, when in fact the correct answer is a client-side retry mechanism that preserves request integrity.

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

Implement client-side retry with exponential backoff.

Implementing client-side retry with exponential backoff is the standard approach to handle HTTP 429 (Too Many Requests) errors without losing requests. When the OCI Generative AI endpoint returns a 429 status, the client can automatically retry the request after a delay that increases exponentially, reducing the load on the endpoint while ensuring all requests are eventually processed. This pattern is recommended by OCI and follows best practices for rate-limited APIs, as it allows the system to recover from transient capacity issues without manual intervention.

Answer analysis

Option-by-option breakdown

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

  • Increase the endpoint's max tokens limit.

    Why it's wrong here

    Max tokens does not affect rate limiting.

  • Implement client-side retry with exponential backoff.

    Why this is correct

    Retry with backoff is the standard approach to handle 429 errors.

  • Reduce the number of concurrent requests from the application.

    Why it's wrong here

    Reducing concurrency may prevent errors but could also increase latency; retry is more robust.

  • Use a dedicated AI cluster with higher capacity.

    Why it's wrong here

    While this reduces occurrence, it does not handle the immediate error; retry is still needed.

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