NCP-GENL Production Monitoring and Reliability Practice Question
An LLM inference service on NVIDIA Triton Inference Server is experiencing occasional out-of-memory (OOM) errors on the GPU. The team wants to monitor GPU memory usage to predict and prevent OOM conditions. Which NVIDIA tool provides real-time GPU memory metrics that can be integrated with Prometheus for alerting?
⚠ Common exam trap
Test-takers frequently confuse profiling tools or basic command-line utilities with a production-grade monitoring solution that integrates with Prometheus for alerting.
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
✓
NVIDIA Data Center GPU Manager (DCGM)
DCGM is designed for data center GPU monitoring and provides comprehensive metrics, including memory usage. With DCGM Exporter, these metrics can be scraped by Prometheus, enabling real-time alerts when memory usage approaches limits. This proactive monitoring allows the team to adjust batch sizes or resource allocation before OOM errors occur, ensuring reliable LLM inference.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
NVIDIA Nsight Systems
Why it's wrong here
Nsight Systems is a profiling tool for analyzing application performance, not for continuous production monitoring. It can capture GPU memory usage during profiling sessions but does not provide real-time metrics or Prometheus integration for alerting. It is unsuitable for ongoing monitoring of OOM conditions in a live service.
- ✗
NVIDIA Triton Inference Server metrics endpoint
Why it's wrong here
Triton's metrics endpoint exposes inference-specific metrics like request counts and latencies, but it does not provide detailed GPU memory usage metrics. While it can indicate OOM errors via error counts, it does not offer the granular memory utilization data needed to proactively monitor and prevent OOM conditions.
- ✗
NVIDIA System Management Interface (nvidia-smi)
Why it's wrong here
nvidia-smi provides GPU memory usage but is a command-line tool that outputs snapshots. It lacks a native Prometheus exporter and is not designed for continuous metric collection and alerting. While it can be scripted, it is not the optimal tool for real-time monitoring and integration with Prometheus in a production monitoring stack.
- ✓
NVIDIA Data Center GPU Manager (DCGM)
Why this is correct
DCGM is a suite of tools for managing and monitoring NVIDIA GPUs in clusters. It provides detailed metrics including GPU memory usage, and DCGM Exporter can expose these metrics in Prometheus format. This integration enables real-time monitoring and alerting on memory usage, helping predict and prevent OOM conditions in production LLM inference.
About these practice questions
This NCP-GENL question is part of Courseiva's 352-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official NVIDIA exam blueprint
This NCP-GENL practice question is part of Courseiva's free NVIDIA 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 NCP-GENL exam.