Aolani and Rafay Collaborate on One of the Industry’s First NVIDIA DSX OS Deployments on NVIDIA GB200 NVL72 Infrastructure

2026-07-27 · Source: The AI Journal · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure · Depth: Intermediate, short

Summary

Aolani and Rafay Systems announced a strategic collaboration on July 26, 2026. They are delivering one of the industry's first deployments of NVIDIA DSX OS on NVIDIA GB200 NVL72 infrastructure. This partnership transforms next-generation AI infrastructure into production-ready AI platforms for enterprises and cloud providers. The initiative addresses the challenge of quickly operationalizing GPU investments. It moves beyond hardware acquisition to enable rapid customer onboarding, multi-tenant governance, and immediate delivery of AI services. The solution combines Aolani's AI cloud infrastructure with the Rafay Platform's orchestration, automation, and lifecycle management. This allows organizations to provision Kubernetes clusters, virtual machines, AI workspaces, and inference environments. It offers a secure self-service experience while maintaining centralized governance and operational visibility. This collaboration highlights an industry shift towards the software layer for secure, scalable, and commercially viable AI platforms.

Key takeaway

For AI Architects or MLOps Engineers tasked with deploying next-generation GPU infrastructure, you should prioritize integrated software platforms like Rafay's. This approach transforms raw hardware into production-ready, self-service AI environments faster. It enables rapid operationalization, multi-tenant governance, and streamlined delivery of AI services. This improves GPU utilization and accelerates time-to-value for your organization. Consider solutions that automate lifecycle management and provide centralized control over AI workspaces and inference environments.

Key insights

Operationalizing AI infrastructure requires robust software platforms for rapid service delivery and governance.

Principles

• AI success shifts to operational speed.
• Software layer enables viable AI platforms.
• Centralized governance is crucial.

Method

The Rafay Platform integrates with Aolani's NVIDIA GB200 NVL72 infrastructure to automate lifecycle management, enforce governance, and provide self-service provisioning of AI environments.

In practice

• Provision Kubernetes clusters securely.
• Deliver AI workspaces via self-service.
• Manage multi-tenant GPU environments.

Topics

• NVIDIA DSX OS
• NVIDIA GB200 NVL72
• AI Infrastructure
• MLOps Platforms
• Multi-tenancy
• GPU Orchestration
• Self-service AI

Best for: CTO, VP of Engineering/Data, AI Architect, MLOps Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by The AI Journal.