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Deploying and Managing Generative AI on OCIeasyMultiple ChoiceObjective-mapped

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

Your organization uses OCI Data Science to train a generative AI model for code generation. After training, you want to deploy it as a REST API. You create a model deployment using the OCI console, but after 30 minutes the deployment status is still 'Creating'. You check the logs and see the message: 'Insufficient capacity for shape VM.GPU.A10.1 in availability domain AD-1'. The deployment is configured with a single replica. You have verified your tenancy has sufficient service limits for GPU instances. What should you do to resolve this issue quickly?

⚠ Common exam trap

Test-takers frequently confuse service limits with capacity availability, assuming a limit increase will fix the issue, when in fact the error explicitly states 'Insufficient capacity' for the shape, not a limit breach.

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

Change the deployment to use a different GPU shape, such as VM.GPU.A10.2

The error indicates that the specific GPU shape VM.GPU.A10.1 lacks capacity in the current availability domain. Switching to a different GPU shape, such as VM.GPU.A10.2, which uses a different instance configuration, can bypass the capacity constraint without requiring a region change or service limit increase. This is the fastest resolution because it directly addresses the availability domain capacity issue while keeping the deployment in the same region and AD.

Answer analysis

Option-by-option breakdown

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

  • Change the deployment to use a different GPU shape, such as VM.GPU.A10.2

    Why this is correct

    A different GPU shape may have available capacity in the same availability domain.

  • Delete the deployment and create it in a different region with more GPU capacity

    Why it's wrong here

    This is a drastic step and may introduce latency; not the first action.

  • Request a service limit increase for GPU shapes

    Why it's wrong here

    Service limits are not the issue; the error is about capacity, not limits.

  • Wait for 1 hour and check again; capacity may become available

    Why it's wrong here

    Capacity shortages may persist; waiting is not a reliable solution.

Visual reference

Client Recursive Resolver Root DNS (13 root servers) TLD DNS (.com, .org, …) Authoritative example.com query IP addr answer

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