NCP-GENL Production Monitoring and Reliability Practice Question
A production LLM inference service on NVIDIA Triton Inference Server runs on a multi-GPU node. You observe that one GPU reports ECC XID errors and the model's throughput gradually degrades. Which NVIDIA tool should you use to monitor GPU health and set up alerts for these errors?
⚠ Common exam trap
Many exam-takers confuse profiling tools like Nsight Systems or optimization tools like TensorRT with health monitoring tools.
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)
NVIDIA DCGM is the standard tool for monitoring GPU health in data centers. It tracks ECC and XID errors, temperature, power, and other metrics, and can trigger alerts. For a production LLM service experiencing hardware errors, DCGM provides the necessary observability to detect and respond to GPU failures.
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 Data Center GPU Manager (DCGM)
Why this is correct
DCGM is designed for monitoring and managing NVIDIA data center GPUs. It can detect ECC errors, XID errors, and other health metrics, and can be integrated with alerting systems. In this scenario, DCGM would provide the necessary visibility into GPU health and enable proactive alerts when errors occur, helping maintain reliability.
- ✗
NVIDIA TensorRT
Why it's wrong here
TensorRT is an inference optimization and runtime library, not a monitoring tool. It can improve model performance but does not track GPU health or errors. Using TensorRT would not help detect the ECC XID errors or the gradual throughput degradation caused by hardware issues.
- ✗
NVIDIA Nsight Systems
Why it's wrong here
Nsight Systems is a profiling tool for analyzing application performance and GPU utilization at a detailed level. It is not intended for continuous production monitoring or alerting on hardware errors. While it can help diagnose performance issues, it does not provide the real-time health monitoring and alerting required for ECC and XID errors.
- ✗
NVIDIA Triton Model Analyzer
Why it's wrong here
Triton Model Analyzer is used to profile and optimize model configurations for performance, not for monitoring GPU health. It can help find optimal batch sizes and instance counts, but it does not track ECC errors or XID events. Using it for health monitoring would not provide the necessary error detection or alerting.
About these practice questions
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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.