Kubernetes GPU Cluster
GPU workload orchestration on Kubernetes. NVIDIA GPU Operator, Volcano scheduler and container-based HPC workload management.
What is Kubernetes GPU Cluster?
Kubernetes GPU Cluster is the industry-standard solution for orchestrating AI and HPC workloads in a container-based, scalable and multi-tenant environment. Mevasis installs and configures Kubernetes clusters equipped with NVIDIA GPU Operator and Volcano scheduler end-to-end, from requirements analysis through to production deployment.
Kubernetes is the most mature way to manage GPU infrastructure as code; with the right components, bringing HPC workloads into the container era has become standard practice.
— Mevasis HPC Engineering Team
How Does a Kubernetes GPU Cluster Work?
Mevasis delivers a Kubernetes GPU Cluster ready for production through a four-phase deployment process, from requirements analysis to validation.
Requirements Analysis and Design
GPU model selection, cluster topology, network architecture and tenant structure are defined specifically for your organization.
Installation and Integration
Kubernetes, GPU Operator, Volcano, the monitoring stack and high-speed networking (InfiniBand/RoCE) are configured in the field.
Validation and Training
Performance tests are run with real workloads; team training and technical documentation are delivered.
Frequently Asked Questions
When should this solution be chosen?
A Kubernetes GPU Cluster should be chosen in environments where multiple teams share the same GPU infrastructure and workloads are container-based. It is ideal for scenarios where CI/CD pipeline integration is expected and centralized monitoring of resource utilization is desired.
How does Mevasis deliver this solution?
Mevasis provides end-to-end service for Kubernetes GPU Cluster deployment, from hardware selection through software configuration. We deploy all components in the field — NVIDIA GPU Operator integration, Volcano scheduler setup, network configuration (InfiniBand or RoCE), multi-tenant namespace isolation and monitoring infrastructure (Prometheus, Grafana). Post-installation management, monitoring and update support are also provided.
How is pricing structured?
Kubernetes GPU Cluster pricing varies by cluster size, GPU model and count, network infrastructure preferences and managed service scope. To receive an organization-specific quote, you can fill in the request form. After the Mevasis team completes a needs analysis, a detailed price proposal will be provided.