Reference Architecture: vCluster on NVIDIA DGX
See how enterprises are extending NVIDIA DGX systems with Kubernetes-native lifecycle management to deliver scalable, isolated, and efficient GPU environments for AI and ML workloads.
Operationalize AI Infrastructure with vCluster
Enterprises are investing heavily in NVIDIA DGX systems to power AI innovation, but operating GPU clusters efficiently at scale is still a major challenge. This Reference Architecture explains how vCluster extends NVIDIA Base Command Manager (BCM) with Kubernetes-native lifecycle management to simplify operations, maximize GPU utilization, and maintain strict tenant isolation.
With this guide, you’ll learn:
- Integrate vCluster with BCM for streamlined DGX lifecycle management
- Improve isolation and GPU utilization with Private Nodes and Auto Nodes
- Enable secure multi-tenancy across AI, data science, and engineering teams
- Follow practical deployment steps and proven DGX architecture patterns
“This reference architecture shows how vCluster helps organizations turn static DGX clusters into dynamic, cloud-like AI environments with stronger governance, higher utilization, and simpler day-2 operations.”
Co-Founder & CEO of vCluster
Deploy your first virtual cluster today.