Rafay Debuts New Platform Capabilities to Speed Up GPU Infrastructure Consumption and Monetization

November 20, 2024

New Capabilities Enable Self-service Consumption of Accelerated Computing Infrastructure in Addition to AI and ML Tooling for Cloud Providers and Enterprises

SUNNYVALE, Calif. – Nov. 19, 2024 – Rafay Systems, the leading provider of Platform-as-a-Service (PaaS) capabilities for cloud-native and GPU and AI consumption, today announced new platform advancements that help enterprises and GPU cloud providers deliver developer-friendly consumption workflows for GPU infrastructure. The new Rafay Platform capabilities include enterprise-grade controls, SKU definition, customer-specific policy enforcement and granular chargeback data.

Enterprises investing in GPU-based infrastructure in data centers can leverage the Rafay Platform to roll out feature-rich enterprise-wide GPU clouds that developers and data scientists can consume on demand — complete with workbenches for model training, fine-tuning and inferencing. GPU cloud providers deploying GPUs for consumption by downstream customers can leverage the Rafay Platform to operate a full-featured, multi-tenant GPU PaaS that delivers both accelerated computing resources along with AI and ML tooling for training, tuning and serving large language models (LLMs).

GPU Investments Outpace Platform Team Bandwidth, Delaying AI Projects and Increasing Costs

Demand for accelerated computing infrastructure is at an all-time high. A majority of enterprises and service providers are investing in GPU hardware to meet generative AI application development demand. Whether they are buying hardware and deploying it in a data center, or committing to long-term leases with GPU cloud providers, there is urgency to provide developers and data scientists with this expensive hardware. Unfortunately, building a platform to enable self-service consumption of accelerated computing hardware and AI and ML workbenches can be a one to two year project. As a result of these platform development delays, expensive hardware is underutilized — nearly a third of enterprises are utilizing less than 15% of GPU capacity.

“Our work with customers across high-stakes industries over the last two quarters has revealed that enterprises and GPU cloud providers are running into similar challenges. Both are looking for ways to speed up the delivery of accelerated computing hardware to developers and data scientists,” said Haseeb Budhani, CEO and co-founder of Rafay Systems. “The new Rafay Platform capabilities address this need, helping enterprises and GPU cloud providers speed the delivery of a PaaS experience in order to monetize their significant investments in accelerated computing infrastructure.”

Rafay Accelerates GPU Monetization With Standardized Platform Building Blocks

With Rafay, GPU cloud providers and enterprises can quickly launch production-ready AI services. Platform teams can now deliver much-needed services to developers and data scientists through a PaaS offering that enables self-service consumption of compute as well as AI and ML workbenches for fast experimentation and productization of AI-based applications. Newly added Rafay Platform capabilities include:

• Multi-tenancy enforcement: Rafay implements robust multi-tenancy controls that allow GPU cloud providers and enterprises to safely and securely deploy workloads from multiple customers on the same infrastructure without the risk of lateral escalation attacks. The Rafay Platform offers new controls to protect against lateral escalation.

• Programmatic SKUs: For both GPU cloud and enterprise platform teams, Rafay allows programmatic definition of compute and service profiles that can be offered to developers and data scientists as a turnkey package.

• Purpose-built AI workbenches: With Rafay’s service profile capabilities, platform teams can provide Rafay’s native fine-tuning and inferencing tools or third-party services, such as NVIDIA NIMs and Run:AI, to create AI workbenches for developers and data scientists.

• Chargeback and billing: Rafay provides detailed resource tracking and cost attribution features to help GPU cloud providers and enterprises monitor consumption across their user base.

The new platform capabilities are now generally available to customers in the Rafay Platform.

Additional Resources

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About Rafay Systems

Rafay builds infrastructure orchestration and workflow automation software that powers self-service compute consumption for Sovereign AI Clouds, Cloud Service Providers & large Enterprises. Customers leverage the Rafay Platform to orchestrate multi-tenant consumption of AI infrastructure. For more information, please visit www.rafay.co.