Explore Slurm on Kubernetes with dedicated tenant infrastructure. vMetal provisions machines, and vCluster supplies Kubernetes environments with Private Nodes for evaluating upstream Slurm operators.
Most teams underestimate the complexity of running Slurm on Kubernetes at scale.
Namespace isolation exposes cluster-wide agents and other tenants' nodes, making Slurm workloads in shared clusters a security liability.
Integrating Slurm with Kubernetes manually requires months of engineering work before a single tenant workload can run.
AI teams expect cloud-native tooling and self-service environments. A manual provisioning workflow drives them back to hyperscalers.
vMetal provisions infrastructure and vCluster supplies Kubernetes tenant clusters with dedicated Private Nodes. Teams can evaluate upstream Slurm operators inside those environments; a packaged managed Slurm offering remains planned. Lintasarta runs 170+ tenant clusters in production.
Separate Kubernetes tenant environments and dedicated workers support operator evaluation. Packaged managed Slurm remains planned.
Certified Stacks provide versioned application deployments. For Slurm evaluation, distinguish Slinky reference implementations from an available packaged managed service. Validate the selected stack, release and Private Node configuration; packaged managed Slurm remains planned.
Each tenant has an independent Kubernetes API, data store and RBAC boundary. Lightweight control-plane hosting reduces dedicated server requirements for Slurm operator evaluation; Private Nodes keep production workers tenant-specific.
Private Nodes dedicate worker capacity to one tenant cluster, with its own CNI and storage configuration. For Slurm operator evaluation, select physical servers or VMs according to the required infrastructure boundary.
Offer approved Kubernetes evaluation environments through Platform interfaces or your portal. Templates govern access and dedicated worker capacity; Slurm operator setup and validation remain separate from self-service cluster provisioning.
Coordinate tenant environments for Slurm operator evaluation through one UI, CLI and API. Templates, access policies and quotas provide central operator controls while tenant Kubernetes APIs and dedicated production workers remain separate.
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Slurm on Kubernetes uses an operator such as SchedMD’s upstream Slinky to manage Slurm components within Kubernetes. vCluster can provide separate Kubernetes tenant environments with dedicated Private Nodes for evaluation. This is distinct from a packaged vCluster managed Slurm product, which remains planned. Slurm retains job scheduling responsibility; teams must validate operator compatibility, GPU access and operational support.
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.
The public vCluster roadmap still lists the packaged Slurm platform as planned. Upstream Slinky is available separately, but that does not establish a supported vCluster Certified Stack or managed service. Teams evaluating Slurm on Kubernetes must configure and validate the operator, tenant worker model and infrastructure themselves, including scheduling, storage, networking and support responsibilities.
Bare metal Private Nodes can supply dedicated GPU workers to a Kubernetes tenant environment. vMetal orchestrates supported machine provisioning after infrastructure setup. An upstream Slurm operator can then be evaluated within that environment, subject to its own requirements and compatibility. This describes an infrastructure foundation and evaluation path, rather than an available packaged managed Slurm service.
vCluster is a CNCF-certified Kubernetes distribution and exposes standard Kubernetes APIs in tenant environments. This supports familiar clients, Helm charts and cluster-scoped resources such as CRDs. Certification covers Kubernetes conformance rather than an entire AI platform or customer deployment. Validate the selected version, networking, storage, GPU drivers and runtime integrations for the workloads you plan to support.
Readiness depends on dedicated worker capacity, the selected Slurm operator, storage, networking, GPU drivers and validation of job execution. A Kubernetes API becoming available does not mean the Slurm environment is ready. The packaged vCluster managed Slurm offering remains planned, and the approved Boost Run timeline describes managed Kubernetes rather than a Slurm service launch.
Explore dedicated workers and infrastructure requirements for evaluating Slurm on Kubernetes.
