vCluster Labs introduces Infrastructure Tenancy Platform for AI to maximize NVIDIA GPU efficiency on Kubernetes environments. New platform provides a Kubernetes-native foundation for running AI workloads on NVIDIA AI infrastructure, combining advanced isolation, dynamic scaling, and hybrid networking. ATLANTA (KubeCon + CloudNativeCon North America 2025, Booth #421) - November 10, 2025 - vCluster Labs, the company pioneering Kubernetes virtualization, today announced its Infrastructure Tenancy Platform for AI to help organizations build and operate high-performance AI infrastructure on GPU-focused compute clusters, including support for NVIDIA DGX systems. The company's new Reference Architecture for NVIDIA DGX systems is now available, offering architectural guidance for building secure, scalable Kubernetes environments optimized for NVIDIA AI infrastructure. Alongside this, vCluster introduced several new technologies, including vCluster Private Nodes, vCluster VPN, the Karpenter-based vCluster Auto Nodes feature, and direct integrations with NVIDIA Base Command Manager, KubeVirt, and the network isolation controller Netris, all of which form the foundation of the vCluster Infrastructure Tenancy Platform for AI, a unified framework for deploying and managing AI workloads on AI supercomputers in the private cloud as well as on top of hyperscalers and emerging neoclouds. "Our mission is to make AI infrastructure as dynamic and efficient as the workloads it supports," said Lukas Gentele, CEO of vCluster. "With our Infrastructure Tenancy Platform for AI, organizations running NVIDIA AI infrastructure can operate secure, elastic Kubernetes environments anywhere, with the performance, control, and efficiency that AI-scale workloads demand. It feels like getting the most cutting edge public cloud managed Kubernetes but on your bare metal AI supercomputer." Building blocks for the AI infrastructure era. As enterprises race to operationalize AI at scale, platform teams need a Kubernetes foundation that can manage GPU resources efficiently while ensuring workload isolation, mobility, and security. The Infrastructure Tenancy Platform for AI addresses these challenges through the following key innovations: * vCluster Private Nodes & Auto Nodes - Enable virtual clusters to dynamically autoscale GPU and CPU capacity across clouds, data centers, and bare metal environments using Karpenter-based automation. These features help maximize GPU utilization while maintaining full isolation and flexibility. * vCluster VPN - A Tailscale-powered overlay network that establishes secure communication between control planes and worker nodes across hybrid infrastructure. vCluster VPN simplifies burst-to-cloud scenarios, where GPU clusters seamlessly extend from on-premises NVIDIA DGX systems to public cloud environments. * NVIDIA Base Command Manager Integration - Integrates vCluster with NVIDIA Base Command Manager to bring Auto Nodes to NVIDIA DGX clusters, enabling elasticity, GPU lifecycle management, and efficient scaling across on-prem NVIDIA infrastructure. * KubeVirt Integration - Enables the creation of virtual machines on demand as nodes within a virtual cluster using KubeVirt, allowing large bare-metal servers to be partitioned into smaller, isolated compute units. This extends Auto Nodes to on-prem and bare-metal environments, giving platform teams elastic, tenant-aware GPU infrastructure under Kubernetes. * Netris Integration - Provides automated network isolation and lifecycle management for virtual clusters, giving each tenant its own dedicated network path and enabling multi-tenant GPU environments to run securely on shared infrastructure. * vNode Runtime - A secure, Kubernetes-native container sandbox that helps prevent container break-outs, enabling multi-tenant GPU workloads without reverting to VMs. Together, these technologies create the foundation of the vCluster Infrastructure Tenancy Platform for AI - a composable, Kubernetes-native framework purpose-built for running AI, ML, and GPU-intensive workloads anywhere. Industry analysts are increasingly highlighting the urgency of optimizing GPU utilization and simplifying AI infrastructure management. "As AI infrastructure becomes the new competitive frontier, organizations are under immense pressure to operationalize GPUs efficiently while maintaining security and governance across hybrid environments," stated Paul Nashawaty, Practice Lead and Principal Analyst at theCUBE Research. "We find that 71% of enterprises cite GPU utilization inefficiency as a major barrier to scaling AI workloads, and nearly two-thirds are exploring Kubernetes-native approaches to unify AI operations across cloud and on-prem. vCluster Labs' Infrastructure Tenancy Platform for AI directly addresses this gap by enabling dynamic, multi-tenant GPU orchestration with the same elasticity and control enterprises expect from the public cloud, now extended to private NVIDIA-powered AI systems." The new vCluster Reference Architecture for NVIDIA DGX systems outlines best practices for deploying virtual clusters on gpu-centric systems, enabling enterprises to deliver a cloud-like Kubernetes experience on-premises. With vCluster, teams can create lightweight virtual clusters that autoscale GPU resources, integrate securely with both on-prem and cloud networks, and maintain consistent performance across environments. "We've been using vCluster for a while and we love the technology," said Nick Jones, VP of Engineering at Nscale. "We're using vCluster to optimise GPU utilisation and accelerate Kubernetes cluster provisioning - delivering higher performance and efficiency that directly benefit our customers." Enabling cloud agility for NVIDIA GPU infrastructure. From AI factories to private GPU clouds, vCluster brings the scalability and efficiency of public cloud Kubernetes to NVIDIA environments. * Faster cluster provisioning - virtual clusters spin up in seconds with fully declarative provisioning via Terraform and GitOps * Higher GPU utilization - fewer idle GPUs across teams and tenants while ensuring fair use for everyone across the organization * Simplified day 2 operations - automated control plane and node upgrades, automatic backups with vCluster Snapshots and standardized guidance for integration into common cloud-native observability stacks Experience vCluster at KubeCon North America. Be among the first to experience the vCluster Infrastructure Tenancy Platform for AI at KubeCon + CloudNativeCon North America 2025 in Atlanta. Visit Booth #421 for live demos, technical sessions, and book signings. vCluster is also a Diamond Sponsor of Cloud Native + Kubernetes AI Day, where company leaders will present live sessions on GPU-accelerated Kubernetes operations, followed by a fireside chat featuring speakers from NVIDIA, JPMorgan Chase, and vCluster on "The Future of AI and Kubernetes."

vCluster and Netris partner to bring cloud-grade Kubernetes to AI Factories & GPU Clouds with strong network isolation requirements. vCluster's virtual cluster technology and Netris's network automation enables AI operators to launch secure, multi-tenant Kubernetes environments faster - maximizing GPU utilization and scaling seamlessly across cloud, private data centers, and the edge. SAN FRANCISCO - October 28, 2025 - vCluster Labs (formerly LoftLabs), the company pioneering Kubernetes virtualization, today announced a strategic partnership with Netris, the leading NVIDIA-validated Network Automation and Multi-Tenancy Platform trusted by leading GPU cloud operators. As enterprises race to build and scale GPU-powered AI infrastructure, they increasingly face the challenge of running Kubernetes clusters outside of public clouds without losing agility. This partnership combines vCluster's lightweight, isolated virtual clusters with Netris's network automation and multi-tenancy, giving organizations the flexibility to run GPU and AI workloads anywhere, with the same speed, security, and simplicity they expect from the cloud. The two solutions address multi-tenancy at different layers: vCluster at the Kubernetes/compute layer and Netris at the network/abstraction layer, creating a complete foundation for secure, multi-tenant AI infrastructure. Now, through a native integration between vCluster and Netris, this multi-layer isolation becomes fully automated and effortless to operate. When new virtual clusters are created, vCluster can seamlessly connect to Netris networks, ensuring each tenant's Kubernetes environment has its own isolated data plane and network path. This enables operators to deliver cloud-grade security and automation on shared GPU infrastructure. "Our mission has always been to make Kubernetes tenancy simple, efficient, and secure," said Lukas Gentele, CEO and Co-Founder of vCluster. "With Netris, we extend that simplicity with built-in automation and hard multi-tenancy to the networking layer. vCluster ensures isolation at the Kubernetes and compute level, while Netris enforces it at the network and abstraction layer. Together, that's a full-stack approach to multi-tenancy for AI operators. This is especially critical for teams building GPU-based AI factories where strict tenant isolation is a hard requirement." Cloud-Grade Kubernetes for AI infrastructure. Traditionally, running Kubernetes outside the cloud has meant trade-offs. Developers lacked on-demand clusters, while operators had to manually configure load balancers, VPNs, and ACLs. Businesses faced costly sprawl and slowed delivery cycles. Issues are magnified in GPU and AI infrastructure, where utilization and performance directly impact economics. With the vCluster's new Netris integration, organizations can now: * Launch GPU-ready virtual clusters on demand with networking, load balancers, ingress, ACLs, and network isolation automatically configured by Netris through the vCluster integration. * Maximize utilization by securely running multiple tenants on shared clusters, with vCluster providing Kubernetes-level isolation and Netris providing network-level isolation. * Scale AI workloads to the edge with lightweight clusters seamlessly meshed back to central data centers via Netris's secure Site Mesh. Under the hood, the integration allows vCluster environments to attach directly to dedicated Netris networks, giving each tenant its own isolated data plane and Layer 2 connectivity. This eliminates manual Day-2 network configuration and simplifies ongoing operations for shared GPU infrastructure. Future enhancements will extend this integration to automate network creation during cluster provisioning, delivering full end-to-end lifecycle automation. The result: a developer-friendly, operations-ready Kubernetes platform that supports GPU workloads consistently across environments, from public cloud to bare-metal infrastructure to edge sites. Enabling cloud agility, anywhere AI runs. "Netris helps AI operators run like hyperscalers with automation, abstraction, and true multi-tenancy from day one," said Alex Saroyan, CEO and Co-Founder of Netris. "Partnering with vCluster delivers cloud-grade automation and multi-tenancy for Kubernetes, giving AI operators the foundation to run securely, onboard tenants instantly, and monetize GPUs faster." This partnership reflects a broader industry trend where enterprises seek the flexibility of the cloud for AI but increasingly need to run GPU workloads outside of hyperscalers due to cost, control, and performance requirements. With vCluster and Netris, they can finally achieve both. About vCluster. vCluster Labs is virtualizing Kubernetes to enable advanced tenancy models that increase utilization, reduce costs, and make Kubernetes more dynamic. vCluster allows platform and infrastructure teams to create virtual Kubernetes clusters that are as scalable and isolated as traditional clusters but far more lightweight and flexible. Trusted by companies like CoreWeave, Nscale, Adobe, and Deloitte, vCluster powers fully isolated tenant environments across public cloud, private data centers, and GPU-powered AI infrastructure. To learn more, visit www.vcluster.com About Netris. Netris is the leading Network Automation, Abstraction, and Multi-Tenancy (NAAM) Platform purpose-built for GPU Clouds and Enterprise AI Factories. NVIDIA-validated and trusted by the world's most demanding AI cloud operators, Netris provides the essential foundation for transforming GPUs from idle capital expense into sustainable revenue. By automating complex multi-fabric environments across Ethernet, InfiniBand, NVLink, and DPUs, Netris helps operators maximize GPU utilization, accelerate ROI, and scale with confidence. Unlike fragile in-house scripts or legacy enterprise tools, Netris delivers proven cloud-grade automation and true network-level multi-tenancy - enabling AI infrastructure operators to safely run multiple tenants, reduce downtime risk, and launch AI clouds in weeks instead of years.