Train Your AI Model Once and Deploy on Any Cloud with NVIDIA and Run:ai

Started a first new and realistic application.

Train Your AI Model Once and Deploy on Any Cloud with NVIDIA and Run:ai

Jul 07, 2023,  By Guy Salton and Abhishek Sawarkar

Organizations are increasingly adopting hybrid and multi-cloud strategies to access the latest compute resources, consistently support worldwide customers, and optimize cost. However, a major challenge that engineering teams face is operationalizing AI applications across different platforms as the stack changes. This requires MLOps teams to familiarize themselves with different environments and developers to customize applications to run across target platforms.

NVIDIA offers a consistent, full stack to develop on a GPU-powered on-premises or on-cloud instance. You can then deploy that AI application on any GPU-powered platform without code changes.

Introducing the latest NVIDIA Virtual Machine Image

The NVIDIA Cloud Native Stack Virtual Machine Image (VMI) is GPU-accelerated. It comes pre-installed with Cloud Native Stack, which is a reference architecture that includes upstream Kubernetes and the NVIDIA GPU Operator. NVIDIA Cloud Native Stack VMI enables you to build, test, and run GPU-accelerated containerized applications orchestrated by Kubernetes.

The NVIDIA GPU Operator automates the lifecycle management of the software required to expose GPUs on Kubernetes. It enables advanced functionality, including better GPU performance, utilization, and telemetry. Certified and validated for compatibility with industry-leading Kubernetes solutions, GPU Operator enables organizations to focus on building applications, rather than managing Kubernetes infrastructure.

NVIDIA Cloud Native Stack VMI is available on AWS, Azure, and GCP. ... '