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Nutanix NCP-AI Exam Syllabus Topics:

Section	Objectives
Topic 1: Configure a Nutanix Enterprise AI Environment	- Import models (LLMs) - Create and configure endpoints - Manage users and access control - Manage API keys
Topic 2: Perform Day 2 Operations	- Review performance details for tuning - Monitor usage for anomalies or outliers - Monitor performance and activity - Select the appropriate LLM for tasks
Topic 3: Connect Applications to a Nutanix Enterprise AI Environment	- Monitor endpoint-level metrics related to usage - Test and validate integration - Configure applications to use NAI endpoints
Topic 4: Deploy a Nutanix Enterprise AI Environment	- Identify prerequisites for NAI deployment - Perform installation and initial configuration
Topic 5: Troubleshoot a Nutanix Enterprise AI Environment	- Troubleshoot model deployment and serving issues - Resolve model downloading and import failures - Diagnose performance and health issues - Correct endpoint configuration errors

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Nutanix Certified Professional - Artificial Intelligence v6.10 Sample Questions (Q55-Q60):

NEW QUESTION # 55
The administrator observes a "Pod Network Unreachable" health check failure in the NAI, specifically affecting several application pods on a newly added worker node. Existing pods on other nodes are functioning normally.
Upon initial investigation, kubectl get pods -o wide shows the affected pods stuck in ContainerCreating or Pending status, and kubectl describe pod <pod-name> events include messages, such as:
"FailedCreatePodSandBox: failed to create sandbox: rpc error: code = Unknown desc = failed to set up network for sandbox..." or "network is not ready" What is the reason for this error and the appropriate next step that the administrator should take?

A. The NKP CNI plugin on the affected worker node is not functioning correctly; inspect the logs of the CNI poD.
B. The kube-proxy service is misconfigured; restart all kube-proxy pods on the cluster.
C. The Docker/containerd runtime on the worker node is corrupted; reinstall the container runtime.
D. The underlying Nutanix network segmentation is incorrect; verify VLAN or IP pool configurations are correct in Prism Central.

Answer: A

NEW QUESTION # 56
What is the minimum number of supported GPUs required to deploy Google pre-validated LLMs?

A. 0
B. 1
C. 2
D. 3

Answer: D

NEW QUESTION # 57
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?

A. Disable logging temporarily to reduce resource consumption during peak load periods.
B. Scale out the number of instances and allocate additional CPU and memory resources.
C. Restart the model container to clear memory cache and allow the system to rebalance performance.
D. Increase the number of API keys assigned to the endpoint to allow more concurrent access.

Answer: B

NEW QUESTION # 58
What does the Sample Request code include?

A. GPU type and max_tokens
B. User credentials and API key
C. Endpoint URL and API key
D. Endpoint URL and GPU type

Answer: B

NEW QUESTION # 59
Corporate policy says that API keys should be deactivated, not deleted, when a compromise is suspected, but may need to be restoreD.
Which new status will the key display after the one-click Deactivate action?

A. Inactive
B. Pending
C. Expired
D. Failed

Answer: A

NEW QUESTION # 60
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