1Z0-1127-25 Deploying and Managing Generative AI on OCI Practice Question
During deployment of a generative AI model, the inference endpoint returns high latency and timeouts. The model is deployed on a dedicated AI cluster with multiple nodes. What is the most likely cause?
⚠ Common exam trap
Oracle often tests the misconception that high latency is always due to insufficient resources (e.g., memory or batch size), but the real trap here is that candidates overlook the critical role of parallelization configuration in distributed inference—assuming that simply adding more nodes automatically distributes the workload.
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
✓
The cluster nodes are configured with insufficient parallelism or the model is not properly parallelized across nodes
High latency and timeouts in a distributed AI inference deployment typically indicate that the model workload is not efficiently distributed across the cluster nodes. Option C is correct because insufficient parallelism—either due to misconfigured node resources (e.g., insufficient vCPUs, GPU cores, or memory bandwidth) or improper model sharding/parallelization—causes some nodes to become bottlenecks while others remain underutilized, leading to queuing delays and eventual timeouts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The inference request batch size is too small
Why it's wrong here
Incorrect: Small batch sizes typically reduce latency.
- ✗
The model is too large for the cluster memory
Why it's wrong here
Incorrect: This would cause out-of-memory errors, not latency.
- ✓
The cluster nodes are configured with insufficient parallelism or the model is not properly parallelized across nodes
Why this is correct
Correct: Without proper model parallelism, nodes may be underutilized leading to high per-request latency.
- ✗
The client-side network is slow
Why it's wrong here
Incorrect: While possible, the cluster is the shared environment; latency is more likely from cluster configuration.
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