NVIDIA Run:ai for Platform Administrators

Welcome to the "NVIDIA Run:ai for Platform Administrators" lab, a hands-on lab designed to help you explore the architecture and operational workflows behind NVIDIA Run:ai. Whether you're a platform engineer, systems administrator, or just someone interested in the NVIDIA Run:ai platform, this lab will walk you through the core concepts that power NVIDIA Run:ai and give you the practical skills to deploy and manage the NVIDIA Run:ai platform.

NVIDIA Run:ai is a GPU orchestration and optimization platform that helps organizations maximize compute utilization for AI workloads. By optimizing the use of expensive compute resources, NVIDIA Run:ai accelerates AI development cycles, and drives faster time-to-market for AI-powered innovations.

Built on Kubernetes, NVIDIA Run:ai supports dynamic GPU allocation, workload submission, workload scheduling, and resource sharing, ensuring that AI teams get the compute power they need while IT teams maintain control over infrastructure efficiency.

The goal of this lab is to introduce platform administrators to the core concepts and architecture of NVIDIA Run:ai. By the end of this lab, users will have hands-on experience configuring and managing NVIDIA Run:ai's core components; from cluster setup to workload scheduling and organizational management.

The lab walks the user through accomplishing the following:

1. Explore the Architecture
2. Manage users, roles, and permissions
3. Create Projects and Departments
4. Define scheduling rules and policies
5. Create workloads and explore workload assets
6. Navigate key NVIDIA Run:ai Analytics

This lab consists of the following hardware and software:

• Windows 11 Jumpbox
• 3 x Ubuntu 2204 Server
• Vanilla Kubernetes
• NVIDIA Run:ai v2.23.10