1Z0-1127-25 Using OCI Generative AI Service Practice Question
A company wants to deploy a custom fine-tuned model for retrieval-augmented generation (RAG) using dedicated AI cluster. They need to ensure the model can handle concurrent requests from multiple applications with consistent latency. What should they configure?
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
✓
Increase the number of replicas in the dedicated cluster.
Increasing the number of replicas in the dedicated cluster distributes the load across multiple model copies, improving concurrency and latency stability. This allows the model to handle concurrent requests from multiple applications with consistent latency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set a high temperature to keep responses concise.
Why it's wrong here
Temperature affects randomness, not concurrency.
- ✓
Increase the number of replicas in the dedicated cluster.
Why this is correct
More replicas allow handling more requests concurrently without degradation.
- ✗
Enable auto-scaling on the cluster.
Why it's wrong here
Auto-scaling is not available for dedicated AI clusters.
- ✗
Use the managed serving endpoint instead.
Why it's wrong here
Managed endpoint may not support the custom fine-tuned model.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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