NCP-AIO Installation and Deployment Practice Question
A financial services company is deploying NVIDIA AI Enterprise on a Kubernetes cluster with strict security policies. They need to ensure that GPU workloads are isolated and that the NVIDIA GPU Operator components are deployed with least privilege. Which feature of the NVIDIA GPU Operator allows administrators to define granular permissions for its components?
⚠ Common exam trap
The trap here is assuming that PodSecurityPolicy or Network Policies can restrict API permissions; only RBAC governs what actions components can perform on Kubernetes resources.
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
✓
Role-Based Access Control (RBAC)
RBAC is the Kubernetes mechanism for defining granular permissions. The NVIDIA GPU Operator deploys components with specific ServiceAccounts and RBAC roles that grant only the permissions needed to perform their functions. This aligns with least-privilege principles and is critical for security-sensitive deployments. Other options are either deprecated, network-focused, or platform-specific.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Security Context Constraints
Why it's wrong here
Security Context Constraints (SCCs) are an OpenShift-specific feature that controls pod security contexts. They are not part of the NVIDIA GPU Operator's permission model and are not applicable to standard Kubernetes clusters. They do not provide granular permissions for the Operator's components.
- ✗
PodSecurityPolicy
Why it's wrong here
PodSecurityPolicy is a Kubernetes admission controller that controls pod security settings, but it is deprecated and not specific to the GPU Operator. It does not provide granular permissions for the Operator's components; it only enforces cluster-wide pod security policies.
- ✓
Role-Based Access Control (RBAC)
Why this is correct
RBAC in Kubernetes allows administrators to define roles and role bindings that specify which actions are permitted on which resources. The GPU Operator uses RBAC to grant its components the minimum necessary permissions. This enables least-privilege access and is essential for strict security environments.
- ✗
Network Policies
Why it's wrong here
Network Policies control traffic between pods, not permissions for API actions. They are important for network segmentation but do not define granular permissions for the GPU Operator's components. They operate at the network layer, not the authorization layer.
Quick reference
Access Control Model Comparison
| Model | Acronym | Who Controls Access? | Best For |
|---|---|---|---|
| Discretionary Access Control | DAC | Resource owner | Small teams, file shares |
| Mandatory Access Control | MAC | System / security labels | Classified govt / military |
| Role-Based Access Control | RBAC | Administrator (via roles) | Enterprise environments |
| Attribute-Based Access Control | ABAC | Policy engine (user + resource attributes) | Fine-grained, dynamic policies |
| Rule-Based Access Control | RuBAC | System rules / ACLs | Firewall rules, network ACLs |
About these practice questions
Courseiva writes every NCP-AIO question from scratch — 309 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or 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-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.