QumulusAI has partnered with vCluster, the team behind virtual Kubernetes cluster technology, to help developers rapidly and affordably build secure, isolated Kubernetes environments for AI development.
The companies have also established the vCluster AI Lab, a new environment that enables vCluster to accelerate product innovation for the rapidly evolving AI ecosystem. The AI Lab runs on QumulusAI’s distributed GPU infrastructure, providing the vCluster team with direct access to scalable GPU resources that enable vCluster engineers to rapidly prototype new product features, experiment with emerging AI workloads, and refine orchestration capabilities as GPU architectures and AI frameworks continue to evolve.
With the rapid adoption of generative AI, enterprise development teams face a familiar dilemma. They must choose between waiting weeks to provision dedicated infrastructure, or piling teams into shared Kubernetes environments with no real isolation, creating security, governance, and resource contention problems. The result is delayed projects and GPU capacity that sits underutilized while teams wait for access. What organizations need is a way to instantly provision secure, isolated Kubernetes environments on top of existing GPU infrastructure, giving each team dedicated access without the overhead of standing up entirely separate clusters.
Through the partnership, QumulusAI will offer a managed Kubernetes solution powered by vCluster technology, enabling enterprises and AI developers to deploy isolated Kubernetes environments on shared GPU infrastructure. The solution enables AI development at hyperspeed by allowing teams to rapidly spin up development, testing, and production environments without duplicating infrastructure while maintaining secure separation and optimal utilization of GPU resources at scale.
The environments run on QumulusAI infrastructure powered by NVIDIA’s Blackwell based B300 and RTXPRO 6000 platform, designed to support modern AI training, inference, and experimentation workloads.
“AI teams need infrastructure that moves as fast as their ideas,” said Ryan DiRocco, CTO of QumulusAI. “By combining vCluster’s trusted Kubernetes virtualization technology with QumulusAI’s distributed GPU cloud, organizations can spin up isolated environments in minutes and begin building quickly. We believe this partnership will give enterprises the flexibility, access, and speed required to move AI from experimentation to production.”
“AI infrastructure is evolving at an extraordinary pace, and platform tooling must evolve with it,” said Lukas Gentele, CEO of vCluster. “Our new AI Lab, powered by QumulusAI infrastructure, gives us the ability to test new ideas quickly and ensure our platform is ready for the next generation of AI workloads. At the same time, customers benefit from enterprise-grade Kubernetes environments optimized for GPU-accelerated development.”
“This partnership reflects a broader shift in the market toward more flexible and efficient AI infrastructure models,” said Steven Dickens, CEO and Principal Analyst, HyperFRAME Research. “The ability to rapidly spin up isolated environments on shared GPU resources addresses a real gap for enterprises trying to move from experimentation into production.”
To learn more about how this partnership is transforming AI infrastructure, explore the latest innovations with vCluster.
Related News:
QumulusAI Secures $500M Financing to Accelerate AI Infrastructure Growth
Zero Networks Debuts Kubernetes Access Matrix to Reduce Risk at Scale
