[InfiniBand Security] You are concerned about potential security threats and unexpected downtime in your InfiniBand data center. Which UFM platform…

The NVIDIA UFM® (Unified Fabric Manager) Cyber-AI platform is the correct solution. It extends the capabilities of the UFM Enterprise platform by applying artificial intelligence and machine learning to telemetry data. This enables it to learn the unique operational rhythm or "heartbeat" of an InfiniBand data center. By analyzing this baseline, it can detect security threats like abnormal system behavior, identify performance degradations, and provide predictive analytics to forecast potential network failures, thus minimizing unexpected downtime.

A. Host Agent: This is a software component (e.g., HCA agent) that runs on hosts to gather data; it is not the central analytics platform itself.

B. Enterprise Platform: UFM Enterprise is the foundational management platform for provisioning and monitoring, but the specific AI-driven security and predictive analytics are features of the Cyber-AI extension.

D. Telemetry Platform: The UFM Telemetry platform is responsible for collecting granular, real-time monitoring data. This data is the input for the Cyber-AI platform, which performs the actual analysis and prediction.

1. NVIDIA UFM Cyber-AI Platform Product Brief (PB-10198-001v02), Page 1, "Overview": "The NVIDIA UFM® Cyber-AI platform extends the benefits of the UFM Enterprise platform by using AI to detect security threats and operational issues, as well as to predict network failures."

2. NVIDIA UFM User Manual (v6.12.0), Chapter 1.1, "Introduction to UFM": This section describes the different UFM platforms, clearly distinguishing the role of UFM Enterprise as the management tool, UFM Telemetry as the data collection tool, and UFM Cyber-AI as the analytics and security platform that builds upon them.

3. NVIDIA UFM Appliance Datasheet (DS-09206-001v04), Page 1, "UFM Cyber-AI": "UFM Cyber-AI adds a layer of security to the data center, using AI to learn the fabric’s operational cadence and identify performance degradations, component failures, and abnormal usage patterns."