Rafay Platform Use Cases for AI & Cloud Infrastructure | Rafay
Transform Raw Infrastructure into Real Business Outcomes
The Rafay Platform delivers on three core use cases:
- Self-service Compute Consumption,
- Accelerated Computing & AI Infrastructure Management,
- and GPU Cloud Orchestration (go from GPU-as-a-Service to AI-as-a-Service).
Compared to DIY tools, general-purpose orchestration platforms that weren’t designed to automate multi-tenant cloud environments, or first-generation Kubernetes solutions that were designed for small-footprint use cases, the Rafay Platform offers production-ready orchestration and workflow automation that reduces AI and cloud-native infrastructure complexity, and helps customers drive business outcomes in weeks.
The Rafay Platform: Common Use Cases
Scale Self-service Compute Consumption with Confidence
With Rafay, enterprises and service providers deliver self-service experience across public clouds and data center environments. Developers get self-service access to compute and tooling needed to move fast and experiment, while platform teams maintain full control, governance, and cost-efficiency.
Accelerated Computing Infrastructure Management
With a vast library of Generative AI, compute consumption and infrastructure management built in, enterprises and service providers can deliver “as a Service” experiences at each layer of the stack without investing in massive teams and multiple quarters.
From GPU-as-a-Service to AI-as-a-Service
Cloud providers, neoclouds and Sovereign AI clouds who have partnered with Rafay are leading the charge to deliver CSP-grade use cases to their user communities. From agentic applications, ML workbenches, models as a service, to highly tuned virtual machines, K8s clusters and baremetal servers, Rafay is fast becoming the global partner of choice for the most innovative GPU providers in the world.
Use Cases Tailored For Your Environment
The Rafay Platform enables businesses to simplify Kubernetes lifecycle operations across public cloud, private data centers, and sovereign deployments and at the edge. Teams can pool compute (GPUs and CPUs) into a secure, multi-tenant shared resource for use across multiple business units and end-users.
For Enterprises Leveraging the Public Cloud
Your developers don’t want to wait on IT tickets. Give them push-button environments across AWS, Azure, and GCP—while you enforce governance, automate scaling, and control costs.
- Rafay customers report saving 20–25% of developer time on infrastructure setup
- Rafay customers gain the ability to maintain thousands of clusters and pipelines with platform teams as small as 3-4 engineers
For Sovereign AI Clouds & GPU Cloud Providers
Transform GPU infrastructure into a revenue engine. Launch branded GPU Clouds with self-service SKUs, marketplaces, and monetizable services in under 6 weeks.
- Indosat onboarded 28 enterprise customers within weeks
- Partners charge 50–100% more by selling apps, not just GPUs
For Enterprises Operating Private Clouds
Run secure, compliant AI initiatives on-premises without slowing down innovation. Customers leverage the Rafay Platform to orchestrate multi-tenant consumption of AI infrastructure along with AI platforms and applications such as AI-Models-as-a-Service, Accenture's AI Refinery, and other 3rd-party applications.
- Air-gapped deployments for regulated industries
- Quota enforcement ensures 80–90% of infrastructure gets consumed before expansion
For Enterprises Using Public Clouds
Are platform teams stuck managing infrastructure instead of enabling AI at scale? Achieve AI/ML infrastructure automation, on-demand access to GPU resources, and get cost and governance controls for AI workloads–all governed by enterprise policy.
For GPU & Sovereign Cloud Providers
GPU Clouds: Frustrated with monetary 'wastage' from idle or underutilized GPUs? Get elevated infrastructure orchestration, compute-as-a-service, and access to AI/ML and GenAI services–all within the Rafay Platform.
For Enterprises Using Private Clouds/AI
Does speed of AI/ML workloads come at the cost of governance? Not any more. With the Rafay Platform, enterprise teams can run secure, compliant AI/ML initiatives complete with automated infrastructure operations, cluster lifecycle workflows, and more.
The Definitive GPU PaaS Reference Architecture
Understand what it takes to deliver the right GPU infrastructure to your business.