Managed GPU Kubernetes Cluster
Run AI, HPC, and ML workloads on a fully managed Kubernetes cluster powered by GPU Bare Metal or GPU VMs, with high-performance shared storage
Everything your GPU workload demands
Flexible GPU Deployment
Run Kubernetes on GPU Bare Metal for peak performance or scale with GPU VMs for on-demand workloads
High-performance Shared Storage
NVMe block storage up to 50 GB/s throughput for training and distributed file storage with a unified namespace across all nodes
Production-Ready Under 30 Minutes
Pre-configured clusters with everything you need to launch your first GPU job in under 30 minutes
Fully Managed Control Plane
The Kubernetes control plane is fully managed with automated updates, high availability, and a 99.99% SLA
Why Choose GPU Cluster?
Scalable infrastructure designed to power next-generation AI workloads
Fully Managed AI Infrastructure
No setup burden with fully pre-configured stack (GPU drivers, InfiniBand, Kubernetes, monitoring)
Instant Workload Recovery
Reschedule workloads in seconds with automated health checks and self-healing
Real-Time Data Synchronization
Sync instantly across all nodes through a shared distributed file system
Dynamic Auto Scaling
Autoscale Kubernetes nodes to match capacity to workload in real time
Use Cases
Designed for High-Performance and AI-Driven Workloads
Scale LLM & Foundation Model Training
Run distributed training at full GPU speed, with fast communication and storage that avoid performance bottlenecks
Production-Ready Model Serving
Serve AI models on GPU VMs with autoscaling that adapts to demand, ensuring efficiency without over-provisioning or dropped requests
HPC & Scientific Computing
Run HPC workloads and ML pipelines in one cluster, with seamless integration that supports existing workflows without disruption