Which NVIDIA solution is specifically designed to accelerate data analytics and machine learning workloads, allowing data scientists to build and deploy models at scale using GPUs?

Your team is running an AI inference workload on a Kubernetes cluster with multiple NVIDIA GPUs. You observe that some nodes with GPUs are underutilized, while others are overloaded, leading to inconsistent inference performance across the cluster. Which strategy would most effectively balance the GPU workload across the Kubernetes cluster?

A large enterprise is deploying a high - performance AI infrastructure to accelerate its machine learning workflows. They are using multiple NVIDIA GPUs in a distributed environment. To optimize the workload distribution and maximize GPU utilization, which of the following tools or frameworks should be integrated into their system? (Select two)

You are managing the deployment of an AI - driven security system that needs to process video streams from thousands of cameras across multiple locations in real time. The system must detectpotential threats and send alerts with minimal latency. Which NVIDIA solution would be most appropriate to handle this large - scale video analytics workload?

A data center is running a cluster of NVIDIA GPUs to support various AI workloads. The operations team needs to monitor GPU performance to ensure workloads are running efficiently and to prevent potential hardware failures. Which two key measures should they focus on to monitor the GPUs effectively? (Select two)