services you can launch with the rafay platform

Rafay-powered SLURM-as-a-Service

Rafay-powered SLURM as a Service delivers fully managed, multi-tenant SLURM environments for high-performance computing workloads as a cloud-like, on-demand service. Through automated, BCM-based cluster bring-up with secure per-tenant separation and governance built in, tenants request a cluster and Rafay provisions, schedules, and governs it.

  • Self-Service Access: Tenants launch SLURM clusters on demand through the portal or API.
  • Multi-Tenant Isolation: Automated BCM-based bring-up with secure per-tenant separation and operational control.
  • HPC and AI/ML on One Platform: A single offering serves research, engineering, and AI teams without separate environments.
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HPC Meets Cloud-Native Agility

Familiar HPC scheduling, delivered as a governed, on-demand service

Simplified Deployment

Automated BCM-based bring-up removes manual cluster management

Ready-to-Use Access

Login nodes let users submit jobs immediately

Multi-Tenant Isolation

Multiple tenants or teams with full isolation and operational control

Full Automation

Provisioning, scaling, and teardown handled automatically

Break Free from HPC Silos

Expand into HPC and research markets on existing GPU infrastructure

Automated BCM-based bring-up removes manual HPC cluster management

Per-tenant metering and billing turn HPC scheduling into a priced service

Serve traditional HPC and modern AI/ML workflows on shared infrastructure

“We are able to deliver new, innovative products and services to the global market faster and manage them cost-effectively with Rafay.”

Joe Vaughan
Joe Vaughan
Chief Technology Officer
,
MoneyGram
Whitepaper

Hybrid Cloud Meets Kubernetes

Learn how to Streamline Kubernetes Ops in Hybrid Clouds with AWS & Rafay

Start a conversation with Rafay

Talk with Rafay experts to assess your infrastructure, explore your use cases, and see how teams like yours operationalize AI/ML and cloud-native initiatives with self-service and governance built in.