Product
Unlock the Next Step: From Cisco AI PODs to Self-service GPU Clouds with Rafay
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ai-infrastructure
enterprises
gpu-cloud
gpu-paas
2025-10-20
SERVICES YOU CAN LAUNCH WITH THE RAFAY PLATFORM
Rafay-Powered SLURM-as-a-Service (SLURMaaS)
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.
HPC Meets Cloud-Native Agility
Traditional SLURM scheduling with Kubernetes orchestration, dynamic GPU allocation, and multi-tenant security
Self-Service SLURM
Launch clusters instantly with Kubernetes integration
Serverless Access
Optimize utilization across SLURM jobs automatically
Multi-Tenant Isolation
Secure workload separation with per-tenant tracking
Full Automation
Provisioning, scaling, and teardown handled automatically
Break Free from HPC Silos
Convert siloed infrastructure into elastic, revenue-ready services
Dynamically allocate GPUs across jobs to reduce idle capacity
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Deliver compliant, governed SLURM for research and regulated industries
Support both traditional HPC and modern AI/ML workflows on shared infrastructure
Featured Resources
Unlock Your AI Potential with Cisco and Rafay: Transform AI PODs into a Self-Service GPU Cloud
Cisco provides AI-optimized infrastructure. The Rafay Platform makes it usable across teams, tenants, and use cases in days.
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The CIO’s guide to scalable, compliant, and developer-ready AI deployment
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.
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Rafay Named Outperformer in 2025 GigaOm Radar Report for Managed Kubernetes
The latest Radar Report from GigaOm, the Rafay Platform's "Managed Kubernetes" capability is ranked as an “Outperformer."
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Gartner® Report – Market Trend: CSPs’ Opportunity to Capitalize on AI Infrastructure Through GPU as a Service
CSPs can harness these strategic opportunities to capitalize on the AI-optimized IaaS market, projected at $80 billion in 2028.
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Building AI Value within Borders
“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.
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GPU Cloud Evaluation Report
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.
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How Enterprise Platform Teams Can Accelerate AI/ML Initiatives
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.
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How Enterprise Platform Teams Can Accelerate AI/ML Initiatives
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.
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10 Multi-Tenancy Best Practices for Namespaces as a Service (NaaS)
The white paper promises to delve into Kubernetes multi-tenancy best practices, aiming to guide organizations in leveraging Kubernetes effectively for improved resource utilization and cost efficiency.
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"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"
Most Recent Blogs
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Product
Dynamic Resource Allocation for GPU Allocation on Rafay's MKS (Kubernetes 1.34)
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2025-10-06
GPU/Neocloud Billing using Rafay’s Usage Metering APIs
Cloud providers offering GPU or Neo Cloud services need accurate and automated mechanisms to track resource consumption.
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2025-09-13
Try the Rafay Platform for Free
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!
