Rafay-powered SLURM as a Service (SLURMaaS) enables organizations to deliver fully managed, multi-tenant SLURM environments for high-performance computing (HPC) workloads.
Traditional SLURM deployments are static, siloed, and resource-intensive to manage. Rafay modernizes SLURM by integrating it with Kubernetes through Project Slinky, allowing providers to expose SLURM job scheduling as a cloud-like, on-demand service.
This approach allows service providers, enterprises, and sovereign cloud operators to offer secure, elastic SLURM environments with built-in governance, visibility, and automation, simplifying access for research and engineering teams.
Self-Service Access: Tenants can launch SLURM clusters instantly through a portal or API.
Kubernetes Integration: Project Slinky bridges SLURM with Kubernetes for containerized HPC workloads.
Lifecycle Automation: Provisioning, scaling, patching, and teardown are fully automated across environments.
Traditional SLURM scheduling with Kubernetes orchestration, dynamic GPU allocation, and multi-tenant security
Launch clusters instantly with Kubernetes integration
Optimize utilization across SLURM jobs automatically
Secure workload separation with per-tenant tracking
Provisioning, scaling, and teardown handled automatically
.svg)
Aviz ONES, NVIDIA Spectrum-X Ethernet, and the Rafay Platform deliver a unified solution turning GPU fabrics into governed, cloud-native environments, instantly consumable.
Enterprises and Cloud Providers leverage the Rafay Platform to deliver self-service consumption of AI and cloud-native infrastructure to developers and data scientists.
Cisco provides AI-optimized infrastructure. The Rafay Platform makes it usable across teams, tenants, and use cases in days.
Learn how the Rafay Platform "allows CIOs to align their AI strategies with national regulatory frameworks while maintaining global scalability and agility" in this analyst report.
The latest Radar Report from GigaOm, the Rafay Platform's "Managed Kubernetes" capability is ranked as an “Outperformer."
CSPs can harness these strategic opportunities to capitalize on the AI-optimized IaaS market, projected at $80 billion in 2028.
.png)
“Rafay’s central orchestration platform facilitates efficient, self-service infrastructure and AI application management” writes Accenture | NVIDIA in 2025 Building AI Value Within Borders paper.
Learn how to accelerate the ROI of your GPU infrastructure by quickly delivering a fully functional GPU Cloud with the self-service workflows and infrastructure orchestration of the Rafay Platform.
.png)
This paper explores the key challenges that organizations experience supporting these initiatives, as well as best practices for successfully leveraging Kubernetes to accelerate AI/ML projects.
"We are able to deliver new, innovative products and services to the global market faster and manage them cost-effectively with Rafay"
"We are able to deliver new, innovative products and services to the global market faster and manage them cost-effectively with Rafay"
"We are able to deliver new, innovative products and services to the global market faster and manage them cost-effectively with Rafay"
This blog details the specific features of the Rafay Platform Version 4.0 Which Further Simplifies Kubernetes Management and Accelerates Cloud-Native Operations for Enterprises and Cloud Providers
Read Now
In Part-2, we show how you can provide users the means to select fractional GPU memory.
Read Now
This is Part-1 in a multi-part series on end user, self service access to Fractional GPU based AI/ML resources.
Read Now
See for yourself how to turn static compute into self-service engines. Deploy AI and cloud-native applications faster, reduce security & operational risk, and control the total cost of Kubernetes operations by trying the Rafay Platform!
