1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question
A developer wants to deploy a custom generative AI model that was trained using OCI Data Science. Which service should they use to expose the model as an API endpoint?
⚠ Common exam trap
Candidates often confuse OCI Generative AI service (a managed service for pre-built models) with the ability to deploy custom models, or they assume API Gateway alone can serve a model without a backend compute service.
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
✓
OCI Data Science Model Deployment
B is correct because OCI Data Science Model Deployment is specifically designed to host and serve machine learning models as REST API endpoints. It directly deploys models trained in OCI Data Science, managing the underlying infrastructure, scaling, and providing a secure HTTPS endpoint for inference requests.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
OCI API Gateway
Why it's wrong here
API Gateway can route to a backend but is not a model hosting platform.
- ✓
OCI Data Science Model Deployment
Why this is correct
This is purpose-built for deploying models as APIs.
- ✗
OCI Functions
Why it's wrong here
Functions are for small code snippets, not for serving models.
- ✗
OCI Generative AI service
Why it's wrong here
This service only hosts models provided or fine-tuned within it.
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