The answer is to deploy at least two replicas and enable autoscaling based on average CPU utilization. Deploying multiple replicas eliminates a single point of failure by distributing inference requests across fault domains, ensuring high availability even if one instance goes down. Autoscaling based on CPU utilization dynamically adjusts the number of active replicas to match variable load, scaling up during traffic spikes to maintain low latency and scaling down during idle periods to reduce costs, directly achieving high availability and cost efficiency with replicas and autoscaling. On the Oracle Cloud Infrastructure Generative AI Professional 1Z0-1127 exam, this pairing tests your understanding of production-grade deployment patterns for real-time inference APIs, where a common trap is choosing a single-replica configuration with manual scaling, which sacrifices either resilience or cost control. Remember the mnemonic “Two for uptime, CPU for dime”—two replicas guarantee uptime, while CPU-based autoscaling saves the dime.
1Z0-1127 Deploying and Managing Generative AI on OCI Practice Question
This 1Z0-1127 practice question tests your understanding of deploying and managing generative ai on oci. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 company is deploying a generative AI model for a real-time inference API. To ensure high availability and cost efficiency under variable load, which two configurations should they implement? (Choose two.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set the number of model deployment replicas to at least 2
Option D is correct because deploying at least two replicas ensures high availability by eliminating a single point of failure; if one replica fails, the other can still serve inference requests. This is a standard best practice for production workloads on OCI, where model deployment replicas are distributed across fault domains to maintain service continuity.
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.
✗
Use a single replica with a larger GPU to handle all traffic
Why it's wrong here
A single replica is a single point of failure and cannot handle high availability.
✗
Deploy the model in a single availability domain to simplify management
Why it's wrong here
Deploying in a single AD increases risk of outage if that AD fails.
✗
Disable connection draining on the load balancer
Why it's wrong here
Disabling connection draining may cause requests to fail during scale-in.
✓
Set the number of model deployment replicas to at least 2
Why this is correct
Multiple replicas provide redundancy and high availability.
Related concept
Read the scenario before looking for a memorised answer.
✓
Enable autoscaling based on average CPU utilization
Why this is correct
Autoscaling adjusts replicas based on load, balancing cost and performance.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Oracle often tests the misconception that a single, powerful GPU instance is sufficient for high availability, but the exam expects you to recognize that redundancy through multiple replicas and autoscaling are required for both availability and cost efficiency under variable load.
Detailed technical explanation
How to think about this question
Under the hood, OCI model deployments use a load balancer to distribute inference requests across replicas, and connection draining (also known as graceful shutdown) ensures that existing connections complete before a replica is taken out of rotation. Autoscaling based on average CPU utilization works well for generative AI models because inference is typically compute-bound; when CPU usage rises above a threshold, new replicas are provisioned to handle the load, and when it drops, excess replicas are terminated, optimizing cost.
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 small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
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.
Deploying and Managing Generative AI on OCI — This question tests Deploying and Managing Generative AI on OCI — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set the number of model deployment replicas to at least 2 — Option D is correct because deploying at least two replicas ensures high availability by eliminating a single point of failure; if one replica fails, the other can still serve inference requests. This is a standard best practice for production workloads on OCI, where model deployment replicas are distributed across fault domains to maintain service continuity.
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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Question Discussion
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