How GPU Clouds can deliver Run:AI via Self Service using Rafay GPU PaaS
As the demand for AI training and inference surges, GPU Clouds are increasingly looking to offer higher-level, turnkey AI services—not just raw GPU instances. Some customers may be familiar with Run:AI from Nvidia as a AI workload orchestration and optimization platform. Delivering Run:AI as a scalable, repeatable SKU—something customers can select and provision with a few clicks—requires deep automation, lifecycle management, and tenant isolation capabilities. This is exactly what Rafay provides.
With Rafay, GPU Clouds can deliver Run:AI as a self-service SKU, ensuring customers receive a fully configured Run:AI environment—complete with GPU infrastructure, a Kubernetes cluster, necessary operators, and a ready-to-use Run:AI tenant—all deployed automatically. This blog explains how Rafay enables cloud providers to industrialize Run:AI provisioning into a consistent, production-ready SKU.
