NCP-AIO Installation and Deployment Practice Question
Which action is required when updating the NVIDIA driver on a node managed by the GPU Operator to ensure that running workloads are not interrupted abruptly?
⚠ Common exam trap
Candidates often suggest manually stopping pods or deleting the node, forgetting that the GPU Operator provides automated rolling update capabilities that handle pod draining and cordoning safely.
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
✓
Use the operator to perform a rolling update.
The GPU Operator supports seamless driver upgrades by cordoning and draining nodes. When an update is initiated, the operator gracefully moves workloads to other available nodes before updating the driver. This process prevents application crashes, ensures data integrity, and maintains cluster stability during maintenance windows, which is a key responsibility for AI operations professionals managing production-grade, long-running AI training or inference tasks on shared GPU resources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Manually stop all running pods.
Why it's wrong here
Manual intervention is unnecessary and prone to human error. The GPU Operator is designed to handle lifecycle management automatically. Forcing manual stops disrupts the automated workflow and fails to leverage the operator's built-in capability to perform safe, coordinated node drains, which are necessary for maintaining cluster state consistency.
- ✓
Use the operator to perform a rolling update.
Why this is correct
The GPU Operator automates the rolling update process, which includes cordoning and draining nodes to move workloads before applying driver upgrades. This ensures that the maintenance happens without unexpected service outages, fulfilling the requirement to manage infrastructure updates safely while maintaining high availability for the dependent AI workloads.
- ✗
Reboot the entire cluster simultaneously.
Why it's wrong here
Rebooting the entire cluster at once would cause a total service outage. This is a destructive practice that violates high-availability best practices. Updates must be applied incrementally to keep a portion of the cluster active, ensuring that the AI services remain operational throughout the entire maintenance procedure.
- ✗
Delete the node object from the cluster.
Why it's wrong here
Deleting the node object is an extreme and incorrect method for an update. It would lead to the loss of node configuration and potentially cause persistent resource errors in the cluster. Standard operating procedures dictate that node states should be updated, not deleted, to maintain persistent cluster identity.
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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-AIO 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-AIO exam.