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
NVIDIA Blueprints-as-a-Service, Powered by Rafay
NVIDIA Blueprints-as-a-Service powered by Rafay enables organizations to transform NVIDIA NIM Blueprints into fully operational, self-service AI services that can be deployed in minutes instead of weeks.
Rafay automates the end-to-end process of provisioning, configuring, and operationalizing NVIDIA Blueprints, combining cloud-like agility with enterprise-grade control.
Service providers, enterprises, and sovereign cloud operators can now deliver governed, compliant, and production-ready AI deployments with a single click.
One-Click Deployment: Deploy NVIDIA Blueprints instantly, including all associated NIM models and dependencies
Automated Infrastructure Orchestration: Provision GPU, storage, and network resources automatically for each blueprint
Governed Operations: Enforce role-based access, audit logging, and compliance controls across all deployments
Automate Deployment and Lifecycle Management
Rafay simplifies the complexity of deploying and managing NVIDIA AI Blueprints across hybrid, cloud, and sovereign environments
NIM Model Integration
Support for individual NIM models as modular components or combined multi-model blueprints
Self-Service Portal
Expose blueprints as governed catalog items within Rafay’s multi-tenant interface
Air-Gapped & On-Prem Ready
Deploy securely within disconnected or sovereign environments while maintaining compliance
Version & Lifecycle Management
Manage updates to NIM components and dependencies without downtime
Accelerate AI Deployment and Ensure Consistency
Reduce deployment time from weeks to minutes through complete automation
Ensure identical blueprint deployments across cloud, on-prem, or sovereign setups with zero drift
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Enable enterprises and national clouds to deploy complex AI workloads securely and locally
Track resource usage, deployment health, and performance metrics in real time
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!
