Generative AI Infrastructure Automation | Rafay

Generative AI Infrastructure Automation

Delivering AI use cases to market faster is a constant request for enterprises and cloud service providers who are either looking to accelerate application delivery internally or do so for their customers to have a competitive advantage.

The Rafay Platform's vast library of Generative AI, compute consumption, and infrastructure management built in offers customers "as a Service" experiences at every layer of the stack, including ready-made templates for GenAI use cases to speed up their enterprise AI journey.

Transform Your AI Infrastructure Management Today

Launch GPU-as-a-Service, Serverless Inferencing, and AI Marketplaces in days—not months with the Rafay Platform. Deliver self-service environments (EaaS) for developers, ML teams, and platform users while supporting AI/ML training, model deployment, and GenAI inference across multiple environments.

Self-Service Experience

Developers and data scientists can deploy, view, and manage their GenAI applications and infrastructure in isolation using self-service workflows.

Environment Templates for Any Cloud or On-Prem Infrastructure

Teams can create environment and Kubernetes blueprints that brings standardization and consistency across any EKS, AKS, GKE or private data center or edge location.

Multi-tenancy for AI/ML Apps

It is incredibly common for enterprises to have different teams share clusters – perhaps with specific LLM resources – in an effort to save costs. The Rafay Platform's multi-modal, multi-tenancy capabilities can easily support many AI/ML teams on the same Kubernetes cluster.

Leverage the Power of GenAI

Experience unparalleled efficiency and cost savings with AI infrastructure management features that simplify operations while enhancing performance across all environments.

Trusted by leading enterprises, neoclouds and service providers

AI Infrastructure Management - Latest Insights and Trends

Questions and answers about AI infrastructure management

What counts as a node?
A node is a physical or virtual server/machine.

Do you have any volume discounts?
Yes! As the number of nodes increases the price per cluster or per node decreases.

What about short-lived or ephemeral clusters?
Our customers love to experiment, and we don’t ding them for it. We don’t charge for node count spikes, but look at the running average of nodes in use when calculating usage.

Is there a difference between production and non-production pricing?
The management overhead for helping our customers operate dev vs prod clusters is effectively the same, so we treat all nodes the same.

What if I use more nodes than I’ve licensed?
Rafay has a true-up forward policy, meaning that we don’t carry out chargebacks for scenarios where the consumption in a completed billing cycle exceeded the licensed count.

How much does Enterprise Support (24x7x365) cost?
Enterprise Support is available at an additional fee equaling 20% of the cluster or node subscription.

Do you have EDU or GOV discounts?
Yes, please contact sales for more information about discounts for educational institutions and government agencies.

What is AI infrastructure management?
AI infrastructure management is the practice of turning GPUs, compute, AI platforms, and related resources into governed, self-service services that can be consumed, managed, and scaled efficiently.

How does AI Infrastructure work?
AI infrastructure works by combining GPU compute, high-speed networking, distributed storage, and an orchestration layer that schedules workloads across those resources.

Is AI Infrastructure scalable?
Yes, AI Infrastructure is designed to be scalable. Organizations can easily expand their resources to accommodate growing data and processing needs.

How do I get started with AI Infrastructure?
Getting started with AI infrastructure on the Rafay Platform begins with a guided architecture review rather than a generic sign-up flow.

Building AI Value within Borders

Rafay's central orchestration platform facilitates efficient, self-service infrastructure and AI application management.

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