Kubernetes Service
Production-grade Kubernetes for AI workloads — fully managed end-to-end
Overview
A managed Kubernetes control plane engineered for GPU workloads — from single-node tests to multi-region training clusters.
Technova Kubernetes Service (TKS) provides a hardened, GPU-aware Kubernetes control plane with built-in multi-tenant isolation and automated lifecycle management. Clusters launch in minutes via standard manifests, then scale from a single node to federated multi-region deployments. Pre-configured defaults for GPU partitioning, gang scheduling and model serving operators let teams focus on applications rather than cluster administration.
Capabilities
Rapid cluster provisioning
New clusters — production or ephemeral — are ready in minutes through standard Helm charts, Kustomize or Argo applications. No protracted procurement or manual setup cycles.
Tenant isolation
Namespace-scoped RBAC, network policies and resource quotas ensure each team sees only its own workloads and data. Isolation is enforced at both the orchestration layer and the network layer.
Federated multi-region scaling
Grow from a single test node to federated clusters spanning UK and US regions, all managed through one kubectl context and a unified control plane.
GPU partitioning & sharing
First-class support for NVIDIA MIG, MPS and time-slicing lets a single RTX PRO 6000 or MI300X be safely shared across tenants, with per-namespace quotas and access controls.
All-or-nothing gang scheduling
Volcano-based gang scheduling and topology-aware placement ensure distributed training pods launch together and co-locate on the same fabric — no partial starts or stranding.
Pre-installed ML operators
KServe, Kubeflow, Argo Workflows and the NVIDIA/AMD GPU device plugins ship pre-configured and version-pinned — managed upgrades included, no manual operator wrangling.
Benefits
Integrations
How it works
Define
Declare your workload via Helm, Kustomize or Argo. RBAC roles and resource quotas are scoped to your organisations and projects.
Deploy
The cluster boots in minutes. Platform operators map your spec to the right GPU pool, node topology and autoscaler profile.
Serve
KServe autoscales model servers to zero when idle. Blue/green and canary rollouts are available through GitOps pipelines.
Iterate
Roll back, upgrade or extend across regions — all through kubectl or GitOps, backed by full observability and audit logs.
Pricing
Ready to put Technova to work?
Talk to our team about a custom GPU cluster, managed Slurm or one of our vertical AI solutions.