- A
Create an endpoint, deploy the model, then provision a Dedicated AI Cluster
Why wrong: Cannot deploy without a cluster.
- B
Deploy the model to a shared endpoint, then provision a Dedicated AI Cluster for scaling
Why wrong: Shared endpoint cannot host fine-tuned models; dedicated cluster is needed first.
- C
Create an endpoint, then provision a Dedicated AI Cluster, then deploy the model
Why wrong: The cluster must exist before deploying the model and creating the endpoint.
- D
Provision a Dedicated AI Cluster, deploy the model to the cluster, then create an endpoint
The correct order: allocate cluster, deploy model, then expose via endpoint.
Question 980 of 991
1Z0-1127 OCI Generative AI Service Practice Question
This 1Z0-1127 practice question tests your understanding of oci generative ai service. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A team fine-tuned a Cohere Command R model in OCI GenAI and validated it. They now need to deploy it for production inference with a dedicated endpoint. What is the correct sequence of steps?
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
✓
Provision a Dedicated AI Cluster, deploy the model to the cluster, then create an endpoint
Option D is correct because in OCI Generative AI, the correct sequence for deploying a fine-tuned model to a dedicated endpoint is: first provision a Dedicated AI Cluster (which provides the isolated compute infrastructure), then deploy the model to that cluster, and finally create an endpoint that exposes the deployed model for inference. This ensures the model is hosted on dedicated resources before the endpoint is created.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 endpoint, deploy the model, then provision a Dedicated AI Cluster
Why it's wrong here
Cannot deploy without a cluster.
- ✗
Deploy the model to a shared endpoint, then provision a Dedicated AI Cluster for scaling
Why it's wrong here
Shared endpoint cannot host fine-tuned models; dedicated cluster is needed first.
- ✗
Create an endpoint, then provision a Dedicated AI Cluster, then deploy the model
Why it's wrong here
The cluster must exist before deploying the model and creating the endpoint.
- ✓
Provision a Dedicated AI Cluster, deploy the model to the cluster, then create an endpoint
Why this is correct
The correct order: allocate cluster, deploy model, then expose via endpoint.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the order of provisioning infrastructure versus deploying the model, mistakenly thinking the endpoint can be created first and then attached to a cluster later, but OCI GenAI requires the cluster to exist and the model to be deployed before the endpoint can be created.
Detailed technical explanation
How to think about this question
Under the hood, a Dedicated AI Cluster in OCI GenAI is a set of GPU-backed compute instances (e.g., using A100 or H100 GPUs) that are provisioned in a specific OCI compartment and region. Deploying the model to the cluster involves loading the fine-tuned Cohere Command R model artifacts into the cluster's inference runtime, which then exposes an internal inference API. The endpoint creation step binds a public or private HTTPS endpoint (with OCI IAM authentication) to that internal API, enabling production traffic to reach the model. In real-world scenarios, this order prevents orphaned endpoints and ensures that billing and scaling policies are correctly applied to the cluster before any inference requests are accepted.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the 1Z0-1127 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this 1Z0-1127 question test?
OCI Generative AI Service — This question tests OCI Generative AI Service — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Provision a Dedicated AI Cluster, deploy the model to the cluster, then create an endpoint — Option D is correct because in OCI Generative AI, the correct sequence for deploying a fine-tuned model to a dedicated endpoint is: first provision a Dedicated AI Cluster (which provides the isolated compute infrastructure), then deploy the model to that cluster, and finally create an endpoint that exposes the deployed model for inference. This ensures the model is hosted on dedicated resources before the endpoint is created.
What should I do if I get this 1Z0-1127 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This 1Z0-1127 practice question is part of Courseiva's free Oracle certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the 1Z0-1127 exam.
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