Nutanix NCP-AI Practice Test Questions Answers

Comprehensive and Detailed Explanation From Exact Extract of Nutanix Artificial Intelligence documents knowledge without any external URL or links:

To successfully configure and validate the integration, the administrator needs to utilize the connection details provided by the NAI platform.

Validation Workflow:The correct procedure is to retrieve theEndpoint URLand the uniqueAPI Keyfrom the NAI Endpoint details page (often via the "View Sample Request" or "Sample Code" feature).

Configuration:The administrator or developer must then configure the application to send HTTP requests to this specific URL with the API Key included in the header (e.g., as a Bearer token).

Testing:Sending a test request using these exact credentials allows the administrator toconfirm the response meets requirements(schema and content) and validates that the application can successfully authenticate and communicate with the inference service before production rollout.

Comprehensive and Detailed Explanation From Exact Extract of Nutanix Artificial Intelligence documents knowledge without any external URL or links:

According to the "Large Language Models in Nutanix Enterprise AI" documentation regarding model management, administrators have specific options when importing models that are not pulled directly from Hugging Face or NVIDIA NGC.

Supported Import Sources:For custom LLMs or pre-validated models in "Dark Site" (air-gapped) scenarios, the platform supports importing models fromLocal Storage,S3-compatible Object buckets, orNetwork File System (NFS) file shares.1

Protocol Specifics:Among the file-based protocols listed (SMB, SFTP, FTP, NFS),NFSis the only one explicitly supported for mounting or accessing external file shares to ingest model weights and configuration files into the NAI cluster. This aligns with standard Kubernetes ReadWriteMany (RWX) volume requirements often used in NAI backends.

Comprehensive and Detailed Explanation From Exact Extract of Nutanix Artificial Intelligence documents knowledge without any external URL or links:

To successfully configure a custom domain with a corporate CA-signed certificate in Nutanix Enterprise AI, the administrator must ensure the following two external prerequisites are met:

DNS Configuration (Option A):AnA recordmust be created in the corporate DNS server that points the fully qualified domain name (FQDN) ai.company.com to the external IP address assigned to the NAI Ingress Gateway (LoadBalancer IP). This ensures that traffic destined for the custom URL reaches the cluster.

Certificate Provisioning (Option C):A validCA-signed TLS certificate(and its corresponding private key) matching the FQDN ai.company.com must be obtained from the corporate Certificate Authority. This certificate is then stored as a Kubernetes Secret (e.g., nai-letsencrypt-certificate or similar custom secret) and referenced by the Ingress Gateway to enable secure HTTPS termination.

Comprehensive and Detailed Explanation From Exact Extract of Nutanix Artificial Intelligence documents knowledge without any external URL or links:

A400 Bad Requesterror typically indicates a client-side issue where the request sent to the server is malformed, has invalid syntax, or is missing required headers. Since the administrator has verified the endpoint is in theActivestate and internal testing via the NAI console returnsSucceeded, the server-side infrastructure and model are functioning correctly.

The most effective resolution is to provide the developers with the exactSample Requestcode generated by the platform.

View Sample Request:In the Endpoint details page, the administrator can click "View Sample Request" (or "View Code").

Content:This feature generates a precise code snippet (often in cURL or Python) that includes the correctly formatted Endpoint URL, the specific API Key, and the required JSON payload structure.

Result:By using this validated code, developers can identify syntax errors in their own code (such as incorrect header formatting or JSON structure) that are causing the 400 error, ensuring immediate connectivity.

Comprehensive and Detailed Explanation From Exact Extract of Nutanix Artificial Intelligence documents knowledge without any external URL or links:

According to the endpoint creation workflow in the Nutanix Enterprise AI documentation, an endpoint is essentially a deployment of a specific model. Therefore, the prerequisite for creating an endpoint is having a model available in the local registry.

Model Status:The system explicitly requires that the imported Large Language Model (LLM) be in theActive(or Ready) state before it can be selected in the "Create Endpoint" wizard.

Workflow:When an administrator imports a model (whether from Hugging Face or manually), it transitions through statuses like "Processing" (downloading) or "Pending" (waiting for resources). It is only when the status reachesActivethat the model is fully validated, stored, and available to be served as an endpoint. An "Uploaded" status typically refers to a manual file transfer that has not yet been processed or validated for deployment.