NCP-AI Musterprüfungsfragen & NCP-AI Zertifizierungsfragen

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Die echten und originalen Prüfungsfragen und Antworten zu NCP-AI Zertifizierung (Nutanix Certified Professional - Artificial Intelligence v6.10) bei ExamFragen wurden verfasst von unseren IT-Experten mit den Informationen von NCP-AI Prüfungen (Nutanix Certified Professional - Artificial Intelligence v6.10) aus dem Testcenter wie PROMETRIC oder VUE.

Nutanix NCP-AI Prüfungsplan:

Thema	Einzelheiten
Thema 1	Connect Applications to a Nutanix Enterprise AI Environment: This domain focuses on configuring and validating application connections to endpoints and monitoring endpoint metrics to track application usage and integration performance.
Thema 2	Configure a Nutanix Enterprise AI Environment: This domain focuses on operational setup including onboarding users, importing large language models, creating and securing API endpoints with keys, and delivering these endpoints to consumers.
Thema 3	Perform Day 2 Operations: This domain addresses ongoing management including preparing application integration requirements, interpreting and optimizing performance metrics, monitoring access for anomalies, and selecting appropriate LLMs for optimal output.
Thema 4	Deploy a Nutanix Enterprise AI Environment: This domain covers initial deployment tasks including validating prerequisites, installing Enterprise AI components, and configuring DNS, URLs, and certificates for secure platform operation.
Thema 5	Troubleshoot a Nutanix Enterprise AI Environment: This domain covers diagnosing and resolving performance issues, resource utilization problems, cluster health check failures, and model import or endpoint creation errors.

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Nutanix Certified Professional - Artificial Intelligence v6.10 NCP-AI Prüfungsfragen mit Lösungen (Q17-Q22):

17. Frage
Refer to the exhibit

An administrator needs to troubleshoot an import failure from a AI/ML user and does not have the admin right to try to do a manual upload of LLM.
What is the cause of the import failure?

A. Storage location configuration is not correct.
B. Wrong pre-validated model has been selecteD.
C. Model Instance name test already exists.
D. AI/ML User does not have the proper rights.

Antwort: D

18. Frage
An administrator is deploying the required infrastructure on-premise using NKP on Nutanix to install NAI.
Which type of storage should be created during the deployment process to save the models?

A. CIFS
B. Block
C. NFS
D. Volume

Antwort: C

19. Frage
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. Increase the number of API keys assigned to the endpoint to allow more concurrent access.
C. Restart the model container to clear memory cache and allow the system to rebalance performance.
D. Scale out the number of instances and allocate additional CPU and memory resources.

Antwort: D

20. Frage
What prerequisites must be skipped when adding GPU nodes to a managed Kubernetes service on an Azure AKS cluster using Azure CLI?

A. Install the Worker driver
B. Install the Worker Connector
C. Install the GPU driver
D. Install the GPU Connector

Antwort: C

21. Frage
An administrator observes that inference requests to Nutanix Enterprise AI are experiencing increased latency. After accessing the Infrastructure Usage and Health page, the administrator finds that the Service Health status is marked as Critical, and the GPU utilization on one node is consistently at 100%, while other nodes show moderate usage.
What is the most appropriate next step to resolve the performance issue?

A. Rebuild the endpoint to include multiple instances.
B. Increase the memory allocation for the node with high GPU usage.
C. Restart the Kubernetes cluster to reset all node metrics and clear the Critical status.
D. Disable inference endpoints on the overloaded node.

Antwort: A

22. Frage
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NCP-AI Zertifizierungsfragen: https://www.examfragen.de/NCP-AI-pruefung-fragen.html

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