NCP-AI 試験問題を無料オンラインアクセス
| 試験コード: | NCP-AI |
| 試験名称: | Nutanix Certified Professional - Artificial Intelligence v6.10 |
| 認定資格: | Nutanix |
| 無料問題数: | 77 |
| 更新日: | 2026-07-19 |
An administrator logs onto the Nutanix Enterprise AI Dashboard and notices that all current GPU and non-GPU Endpoints are marked as HibernateD. After reviewing the Audit Events section, the administrator notes that no anomalous behavior events have occurred since the day before.
What is the most likely cause as to why all of the current Endpoints are hibernated seemingly at random?
An administrator is monitoring the performance of a deployed Large Language Model within the Nutanix Enterprise AI platform. After initial deployment, users report slow inference response times and occasional timeouts when accessing the model through its API endpoint.
The administrator reviews the performance metrics available in the NAI Dashboard and notes the following:
CPU usage is consistently high across all inference-serving containers.
Memory utilization is nearing the allocated limits for the model service.
The request latency graph shows increasing average inference times during peak usage.
Which action should the administrator take to improve performance and reduce latency?
When manually importing pre-validated or custom LLM Models from existing storage, which protocol is supported?
When preparing an NAI deployment using NKP, which Infrastructure OS should be used to support AI compatible GPUs?