Product
Unlock the Next Step: From Cisco AI PODs to Self-service GPU Clouds with Rafay
Read Now
ai-infrastructure
enterprises
gpu-cloud
gpu-paas
2025-10-20
SERVICES YOU CAN LAUNCH WITH THE RAFAY PLATFORM
Rafay-Powered Bare Metal GPUs-as-a-Service (BMaaS)
Rafay-powered Bare Metal GPUs as a Service (BMaaS) helps organizations turn dedicated compute infrastructure into secure, differentiated, and revenue-ready services.
Traditional GPU rentals quickly become commoditized, provisioning takes weeks, utilization remains low, and customer expectations for performance and control go unmet. Rafay eliminates these bottlenecks by enabling elastic, self-service provisioning of bare metal GPU servers with governance, visibility, and metering built in.
Cloud and service providers can modernize their infrastructure portfolios, enterprises can empower internal AI and HPC teams, and sovereign operators can deliver in-region, compliant GPU services at scale.
Self-Service Provisioning: Tenants can deploy dedicated servers instantly without manual processes
Integrated Monitoring: Continuous visibility into usage, GPU health, and system performance
Accurate Metering: Low-granularity usage accounting supports transparent chargeback and revenue optimization
Simplify and Automate GPU Operations
Rafay automates how GPU servers are deployed, managed, and scaled across multiple tenants and environments.
Latest GPU Hardware Support
Expose NVIDIA H100, A100, and L40S models as premium bare metal SKUs with direct hardware access.
Multi-GPU Configurations
Scale up to eight GPUs per server using NVLink and NVSwitch for training or HPC workloads.
Pre-Configured ML Environments
Secure workload separation with per-tenant tracking
Built-in Monetization
InfiniBand and RDMA-enabled Ethernet deliver maximum throughput for distributed training and HPC performance.
Drive Efficiency and Business Value
Reallocate expensive GPU servers between tenants in minutes to minimize idle time and depreciation
Offer performance SLAs, integrated analytics, and billing to move beyond commodity GPU rentals
.svg)
Deliver air-gapped, compliant GPU environments tailored for regulated industries and national AI projects
Automate provisioning, scaling, and teardown while maintaining full performance visibility across hardware and tenants
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.
Download now
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.
Download now
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."
Download now
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.
Download now
.png)
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.
Download now
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.
Download now
.png)
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.
Download now
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.
Download now
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.
Download now
"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
.png)
Product
Dynamic Resource Allocation for GPU Allocation on Rafay's MKS (Kubernetes 1.34)
Read Now
No items found.
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.
Read Now
No items found.
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!
