1Z0-1127 Using OCI Generative AI Service Practice Question
This 1Z0-1127 practice question tests your understanding of using 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 company runs batch inference jobs daily using the OCI Generative AI service. The current cost is higher than expected. Which change would most effectively reduce cost while maintaining throughput?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Switch from on-demand to dedicated AI cluster with batch endpoint.
Switching from on-demand to a dedicated AI cluster with a batch endpoint reduces cost because dedicated clusters provide reserved capacity at a lower per-token rate compared to on-demand pay-per-token pricing, and batch endpoints allow you to process multiple inference requests in a single job, amortizing overhead and reducing idle time. This combination directly addresses the high cost of per-request on-demand pricing while maintaining the same throughput for daily batch jobs.
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.
✓
Switch from on-demand to dedicated AI cluster with batch endpoint.
Why this is correct
Dedicated clusters provide lower cost per token for batch workloads and avoid contention.
Related concept
Read the scenario before looking for a memorised answer.
✗
Reduce the max token limit for all requests.
Why it's wrong here
Reducing tokens may affect output quality and does not address cost structure.
✗
Use a larger model to reduce retries.
Why it's wrong here
Larger models cost more per token, not less.
✗
Increase the number of parallel requests to improve efficiency.
Why it's wrong here
More parallel requests may increase cost due to higher throughput, not reduce it.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Oracle often tests the misconception that reducing token limits or increasing parallelism is the most effective cost-saving measure, when in fact the pricing model change from on-demand to dedicated infrastructure yields the greatest savings for predictable batch workloads.
Trap categories for this question
Command / output trap
Reducing tokens may affect output quality and does not address cost structure.
Detailed technical explanation
How to think about this question
Dedicated AI clusters in OCI Generative AI are provisioned with a fixed number of GPU nodes (e.g., A100 or H100) and billed hourly, making them cost-effective for predictable batch workloads where utilization is high. Batch endpoints queue requests and process them in a single job, reducing the overhead of individual API calls and allowing you to leverage lower batch pricing tiers. Under the hood, OCI uses a token-based billing model where on-demand requests incur a premium for elasticity, while dedicated clusters offer a flat-rate compute cost that becomes cheaper per token at scale.
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.
Using OCI Generative AI Service — This question tests Using 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: Switch from on-demand to dedicated AI cluster with batch endpoint. — Switching from on-demand to a dedicated AI cluster with a batch endpoint reduces cost because dedicated clusters provide reserved capacity at a lower per-token rate compared to on-demand pay-per-token pricing, and batch endpoints allow you to process multiple inference requests in a single job, amortizing overhead and reducing idle time. This combination directly addresses the high cost of per-request on-demand pricing while maintaining the same throughput for daily batch jobs.
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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