1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question
A data scientist fine-tunes a model using OCI Data Science and wants to deploy it as a managed endpoint in OCI Generative AI. What must they do first?
⚠ Common exam trap
Watch out — candidates often assume they can directly create an endpoint using CLI or SDK without first registering the model in the Model Catalog, overlooking the mandatory registration step that links the artifacts to the serving infrastructure.
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
✓
Upload model artifacts to Object Storage and register in Model Catalog
To deploy a fine-tuned model as a managed endpoint in OCI Generative AI, the model artifacts must first be uploaded to Object Storage and registered in the Model Catalog. This is a prerequisite because OCI Generative AI endpoints pull model artifacts from the Model Catalog, which references the storage location. Without registration, the service cannot locate or serve the model.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Upload model artifacts to Object Storage and register in Model Catalog
Why this is correct
This is the required first step to deploy a custom model.
- ✗
Write a custom container
Why it's wrong here
A custom container is optional and not the first step.
- ✗
Create a dedicated AI cluster
Why it's wrong here
The cluster is created after the model is registered.
- ✗
Use OCI CLI to create an endpoint
Why it's wrong here
The CLI is used after the model is registered.
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