White Papers

Operationalizing AI Fabrics with Aviz ONES, NVIDIA Spectrum-X, & Rafay

Aviz ONES, NVIDIA Spectrum-X Ethernet, and the Rafay Platform deliver a unified solution turning GPU fabrics into governed, cloud-native environments, instantly consumable.

GPU PaaS Reference Architecture with NVIDIA

Enterprises and Cloud Providers leverage the Rafay Platform to deliver self-service consumption of AI and cloud-native infrastructure to developers and data scientists.

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.

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.

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."

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.

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.

Supporting documents for Rafay+NVIDIA Reference Architecture

Learn how how NVIDIA customers can deploy and operationalize the Rafay Platform on their infrastructure to deliver a GPU PaaS offering.

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.

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.

Automate the AWS Infrastructure That Drives Your Innovation

Platform Engineering Best Practices: Strategies for Developer Autonomy