ai-cloud
GPU Node Lifecycle Management for AI Clouds
Track GPU machines from provisioning through release. vMetal manages the infrastructure lifecycle, while vCluster assigns worker capacity to production tenants through Private Nodes.
Trusted by the fastest-growing AI cloud providers
Problem
GPU Lifecycle Operations Need Consistent Ownership
GPU node operations become fragmented when provisioning, cluster attachment, and inventory use different lifecycle models.
Manual Provisioning Kills Margins
Manual provisioning delays the point when GPU servers can accept workloads.
No Unified API Across Hardware
Different infrastructure drivers expose different mechanics and operational states.
Released Servers Get Stranded
Without a clear reclaim workflow, released servers can remain stranded outside the available capacity pool.
Solution
One API for the Full GPU Node Lifecycle
vMetal tracks Machines through provisioning, attachment, release and driver-supported cleaning. vCluster assigns dedicated Private Nodes to tenant environments, keeping capacity ownership visible through the machine lifecycle. vCluster Labs software powers 100K+ GPUs.
Full GPU Node Lifecycle in One Platform
vMetal provides a consistent Machine lifecycle across requests, drivers, tenant cluster attachment, release, and inventory reuse.
Bare Metal Ops
GPU Machine Provisioning
vMetal exposes one Machine API above bare metal and VM provisioning drivers. Registered inventory, images and credentials enable repeatable machine lifecycle workflows for GPU machine lifecycle operations. Network automation uses supported integrations such as Netris.
- Stable Machine API
- Bare metal and VM provisioning
- Driver-specific lifecycle automation
Dynamic Scaling
Private Node Capacity Requests
Karpenter-based Auto Nodes requests worker capacity according to configured policies. With the vMetal provider, Machine requests provision available infrastructure for GPU machine lifecycle operations; inventory, driver readiness and release rules determine actual capacity.
- Karpenter-based node management
- Supported infrastructure provider integration
- Inventory-aware capacity policies
Tenant Isolation
Dedicated Tenant Capacity
Private Nodes dedicate worker capacity to one tenant cluster, with its own CNI and storage configuration. For GPU machine lifecycle operations, select physical servers or VMs according to the required infrastructure boundary.
- Dedicated worker nodes per tenant
- Tenant-owned CNI and storage configuration
- Physical servers or supported VMs
Network Isolation
Network Configuration by Driver
Tenant-owned CNI configuration and supported Netris integrations provide separate network controls for GPU machine lifecycle operations. Ethernet segmentation can use VLANs, VRFs and ACLs; InfiniBand isolation uses fabric partitions rather than Ethernet constructs.
- Tenant-owned worker network configuration
- Netris integration for supported fabrics
- Explicit segmentation and access policies
Operational Recovery
Tenant Operations and Recovery Workflows
Combine tenant observability with control-plane snapshots and documented recovery workflows. GPU monitoring and infrastructure tools supply hardware diagnosis and repair; protect workload data separately and test restores before relying on a recovery procedure.
- Tenant observability and recovery context
- Control-plane snapshots and restore workflows
- External hardware diagnosis and repair
Why vCluster
This isn’t a side project. Behind every vCluster deployment is 5+ years of deep K8s engineering, security hardening, and battle-tested infrastructure work at massive scale.
100K+
GPUs Powered
50+
GPU Clouds & F500s
<45
Days to Launch
30K
GitHub Stars
Get Started in 3 Steps
1
Schedule a Demo
Talk to our team about your stack
2
Deploy vCluster
Deploy vCluster on your infra in minutes
3
Onboard Your Tenants
Go live with a hyperscaler-grade tenant experience in days
FAQs
What does GPU node lifecycle management cover in vMetal?
vMetal exposes a stable Machine API above infrastructure-specific drivers for bare metal and VMs. Drivers handle supported provisioning mechanics such as imaging, registration and cleaning. Operators configure inventory, credentials and images before automation runs. vCluster can then use provisioned machines as dedicated Private Nodes, connecting the infrastructure lifecycle to the tenant cluster that needs the capacity.
How does vMetal handle node lifecycle management across different hardware vendors?
vMetal requires vCluster Platform and a connected Kubernetes cluster for its Metal3/Ironic provisioning components. If you are starting without Kubernetes, vCluster Standalone can bootstrap that foundation as a binary on Linux. Once infrastructure drivers, hardware inventory, images and credentials are configured, vMetal can automate supported provisioning workflows and supply machines for tenant Private Nodes.
Can vMetal automatically scale GPU nodes based on tenant workload demand?
Auto Nodes uses Karpenter-based node management, with vCluster Platform handling infrastructure provisioning through a configured node provider. Providers include vMetal and other supported integrations. On the vMetal path, Machine requests allocate and provision available inventory as tenant Private Nodes. Scaling depends on configured policies and usable capacity; it does not create physical inventory or automatically diagnose hardware failures.
How does GPU node lifecycle management integrate with tenant cluster orchestration?
vCluster gives each tenant an independent Kubernetes API, data store and RBAC scope. Private Nodes dedicate worker capacity to that tenant, including its own CNI and storage configuration. vMetal orchestrates the machines underneath. This separates tenant administration and worker placement; shared infrastructure, application permissions and network policies still require an explicit security design.
What network automation is included in GPU node lifecycle management?
Private Nodes give a tenant its own worker networking configuration. Supported Netris integrations can add Ethernet segmentation through VLANs, VRFs and ACLs on compatible infrastructure. These controls require explicit setup and do not reserve all fabric bandwidth. InfiniBand uses partition keys and fabric management rather than Ethernet segmentation; design the relevant fabric controls alongside tenant cluster access policies.
Is vMetal GPU node lifecycle management suitable for sovereign AI cloud environments?
Supported plans include air-gapped deployment and FIPS features. Private Nodes, tenant-scoped access and optional network segmentation provide controls you can include in a regulated deployment. Select supported images and configurations, and validate the full environment against your requirements. These capabilities do not establish certification of the customer's service, application, hardware or operational procedures.
Automate Your GPU Node Lifecycle Today
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