An administrator is deploying a customer support chatbot that needs to integrate with a large language model hosted in the Nutanix Enterprise AI platform. The goal is to enable real-time inference while following best practices for security and scalability. Which action should the administrator perform to meet these requirements?

The standard and most secure method for an application to consume a model hosted on the Nutanix Enterprise AI (NAI) platform is by creating a dedicated API endpoint. The NAI Dashboard provides the interface to deploy a model and then expose it via a REST API endpoint. Generating an API key for this endpoint ensures that only authorized applications, like the chatbot, can send inference requests. This approach is inherently scalable as the platform manages the backend model instances and provides a stable, secure, and high-performance interface for real-time communication.

A. Prism Central application profiles are used for application lifecycle management and network policy definition within Nutanix Calm or Flow, not for creating inference API endpoints for AI models.
C. Using SSH and raw sockets is a significant security vulnerability and an operational anti-pattern. SSH is for administrative access, not application integration, and this method lacks standard security and management features.
D. Nutanix Flow provides network-level security (microsegmentation), which is a recommended practice. However, it only controls network traffic; it does not create the application-level API needed for the chatbot to communicate with the model.

1. Nutanix GPT-in-a-Box 2.0 User Guide: Chapter 5, "Using a Deployed Model for Inference," Section: "Creating an Inference Endpoint." This section details the procedure for making a deployed model accessible. It states, "To use a deployed model for inference, you must create an inference endpoint... The system generates an API key that you must use to access the endpoint." This directly supports the creation of an API endpoint and key for secure access.

2. Nutanix GPT-in-a-Box 2.0 User Guide: Chapter 5, "Using a Deployed Model for Inference," Section: "Sending an Inference Request." This section provides examples of how to make API calls to the endpoint using the generated API key in the authorization header. It demonstrates that the API endpoint is the designated method for application integration.