1Z0-1127-25 Using OCI Generative AI Service Practice Question
A multinational corporation plans to deploy OCI Generative AI in multiple OCI regions for disaster recovery. They have fine-tuned a custom model in the primary region. What is the recommended approach to make the fine-tuned model available in the secondary region with minimal manual effort?
⚠ Common exam trap
OCI often tests the misconception that cross-region replication of storage automatically makes the compute service (like a dedicated AI cluster) available in the secondary region, but in reality, the cluster is a separate resource that must be explicitly created and configured to use the replicated artifact.
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
✓
Copy the model artifact to the secondary region's object storage bucket and create a new dedicated endpoint there.
The recommended approach to make a fine-tuned custom model available in a secondary OCI region with minimal manual effort is to copy the model artifact (the trained weights and configuration files) to the secondary region's object storage bucket and then create a new dedicated endpoint there. This avoids re-running the expensive fine-tuning job and leverages OCI's object storage cross-region copy capabilities, while the dedicated AI cluster in the secondary region can serve the model directly from the copied artifact.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create an IAM policy to allow cross-region access to the model from the secondary region.
Why it's wrong here
Policies can grant access but the model artifact must be physically present in the region.
- ✗
Use OCI Cross-Region Replication for the model's underlying object storage bucket and the dedicated AI cluster.
Why it's wrong here
CRR replicates objects but does not automatically replicate the dedicated cluster configuration.
- ✗
Redeploy the fine-tuning job in the secondary region using the same training data.
Why it's wrong here
This is inefficient and duplicates effort; the model can be copied.
- ✓
Copy the model artifact to the secondary region's object storage bucket and create a new dedicated endpoint there.
Why this is correct
This leverages existing model artifacts and can be automated with OCI CLI or SDK.
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