vCluster Adds Auto Nodes to Bring Karpenter-Based Dynamic Autoscaling to All Environments: Public Cloud, Private Cloud, and Bare Metal

September 09, 2025 at 12:00 PM EDT

New release empowers platform engineering teams to deliver scalable, isolated Kubernetes workloads across any infrastructure, eliminating resource waste, cloud lock-in, and complex provisioning.

vCluster Labs (formerly LoftLabs), the company pioneering Kubernetes virtualization, today announced the newest capability for vCluster, Auto Nodes. This powerful feature enables node autoscaling for virtual clusters across any environment, including public cloud, private cloud, hybrid infrastructure, and even bare metal, using Karpenter, the open source autoscaler created by Amazon Web Services (AWS).

Auto Nodes is infrastructure-agnostic and extensible by design. Platform teams can use Terraform or OpenTofu to declaratively define infrastructure and even build custom providers for any non-standard environments. Besides Terraform and OpenTofu, vCluster’s Auto Nodes also ships with native support for tools like NVIDIA Base Command Manager (BCM) and KubeVirt which make it easy to autoscale workloads across bare metal private clouds and AI clusters with NVIDIA GPUs in particular.

“With Auto Nodes, we’re unlocking Karpenter-powered dynamic autoscaling across any infrastructure,” said Lukas Gentele, CEO of vCluster. “It’s not just about autoscaling, it’s about doing it anywhere, with full isolation and flexibility - all based on a proven open source technology. That’s a superpower no other K8s distro has across private cloud and bare metal environments.”

While Karpenter is widely adopted in managed Kubernetes offerings like EKS and AKS, Auto Nodes marks the first time this autoscaling capability is available in a fully portable, environment-agnostic form, enabling organizations to scale Kubernetes workloads anywhere without being locked into a single vendor or cloud provider.

“The ability of Auto Nodes to instantly provision and decommission capacity on Kubernetes clusters based on resources from any cloud or on-premises data center infrastructure elevates auto scaling to a new level. Organizations can now scale or burst their workloads anywhere based on cost, compliance, or other considerations, without being tied to a single platform vendor,” said Torsten Volk, principal analyst, application modernization at Enterprise Strategy Group. "vCluster’s Auto Node feature is an advancement because it allows organizations to fully leverage modern hybrid and multi-cloud resources, whether in a regulated private cloud, a hyperscaler, or bare metal. This is significant because it provides exactly the flexibility that enterprises need to future-proof their infrastructure strategy."

Unlock Dynamic Kubernetes Clusters with Hard Isolation

vCluster recently introduced Private Nodes, allowing users to join dedicated Kubernetes nodes directly into a virtual cluster. This made it possible to run workloads in fully isolated, single-tenant environments while retaining the lightweight benefits of vCluster’s containerized control plane.

Now with Auto Nodes, isolation no longer comes at the risk of losing scalability or increasing infrastructure waste. Each virtual cluster can now scale its Private Nodes automatically, on any cloud, in any environment, using a built-in Karpenter integration.

The Flexibility of Auto Nodes and How They Work

Auto Nodes builds on the Private Nodes tenancy model by embedding a Karpenter operator directly into each virtual cluster. The Karpenter operator:

Monitors pods (including unschedulable ones) inside the virtual cluster;
Dynamically provisions new nodes that match specific constraints;
Automatically removes unused nodes again once workloads terminate and load reduces;
Works with a range of node providers, including Terraform, BCM, KubeVirt, and custom environments; and,
Supports GPU and CPU-based workloads across diverse hardware types.

With Karpenter’s just-in-time autoscaling and vCluster’s multi-provider support, each virtual cluster becomes its own fully isolated autoscaling unit, able to request exactly the compute it needs, when it needs it, from whatever infrastructure is available. This unlocks hybrid and multi-cloud architectures where virtual clusters can elastically scale GPU or CPU workloads without sacrificing isolation or duplicating clusters.

Auto Nodes makes it possible to shift workloads between cloud providers or data centers dynamically, enabling cross-cloud cost optimization based on real-time pricing, availability, or policy constraints, without changing application code or infrastructure setup.

Key Use Cases

Auto Nodes can be incredibly powerful when used for AI Workloads, CI/CD Pipelines, Secure Multi-Tenancy, and Hybrid Clusters. Benefits include:

AI Workloads – Autoscale GPU nodes across cloud and on-premise environments.
CI/CD Pipelines – Launch burst compute for test jobs without paying for idle capacity.
Secure Multi-Tenancy – Deliver isolated, production-grade environments that scale independently.
Hybrid & Multi-Cloud Infrastructure – Scale Kubernetes workloads across cloud providers and datacenters without rearchitecting.

Product Availability

Auto Nodes is now available as part of the vCluster v0.28 and vCluster Platform v4.4 release. It supports static and dynamic node pools, fine-grained constraints via NodeTypes, and can target specific instance shapes, GPUs, and architectures.

With the release of Auto Nodes, Private Nodes now scale like the cloud across any infrastructure and with full tenant isolation. For more information, visit vcluster.com/launch.

Supporting Resources

About vCluster Labs

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