AI Infrastructure Management and
Cloud Native Infrastructure Management

PaaS for GPU & CPU Workloads

Supercharge AI adoption by delivering AI applications and tools on NVIDIA-powered hardware | Rafay Vietnam

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Operationalize GPUs

Secure and Compliant Provisioning

63%

Lower cloud costs

More frequent deployments

76%

Lower MTTR

The Rafay Platform

Rafay offers a Platform-as-a-Service (PaaS) solution designed to make compute resources both CPU-based and GPU-based instantly consumable for developers, data scientists, and operations engineers. Rafay simplifies the deployment, management, and scaling of these workloads across data centers, public clouds, and at the edge, enabling businesses to accelerate innovation and improve operational efficiency.

By providing a unified view for Kubernetes operations, Rafay empowers teams to manage workloads at scale while ensuring governance, security, and control over the entire infrastructure. This platform is enterprise-ready, enabling organizations to manage workloads across hybrid and multi-cloud environments with ease.

Challenges Rafay Solves

Rafay knows the challenges associated with infrastructure management and the variabilities that come from multi-cloud requirements.

Struggling to allocate GPUs dynamically for fast AI delivery?
Infrastructure bottlenecks slowing EKS, AKS, or GKE lifecycle management?
Too much manual effort managing Kubernetes in private data centers?
Hard to enforce consistent configs and workflows across environments?
Developers wasting time waiting for GPU access instead of building?

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One Unified PaaS for Modern Infrastructure and Accelerated Computing

Rafay makes CPU-based and GPU-based compute resources instantly consumable by developers and data scientists,enabling customers to empower every developer and data scientist to accelerate the speed of innovation

Designed for Your Biggest Enterprise Cloud Challenges

Go Cloud Native In The Cloud Or On-Prem

Standardize and centralize Kubernetes management.

Rafay enables platform teams to standardize every aspect of a cloud environment’s configuration – cluster & environment configs, resource allocation, approved addons, access controls, security policies, and much more – in one place.

Put EKS/AKS/GKE lifecycle management on autopilot

Rafay allows a small, central team to easily manage the lifecycle of all Kubernetes clusters and cloud resources being used by multiple BUs and hundreds of app teams, hosted across public clouds (AWS, Microsoft Azure, Google Cloud, Oracle Cloud and more). This enables end-to-end lifecycle management automations that eliminate the need for specialized teams.

Operate an EKS-like service in your data center

Rafay provides turnkey management of Kubernetes resources hosted in private, remote, or edge clouds (including bare metal, VMware vSphere, local VMs, and support for their networking and storage needs). Now, your team can focus on higher-value work rather than the menial tasks of keeping Kubernetes operational.

Put EKS/AKS/GKE lifecycle management on autopilot

Launch a customizable GPU PaaS in days

Accelerate your time to-market with high value NVIDIA hardware by rapidly launching a PaaS for GPU consumption, complete with a customizable storefront experience for your internal and external customers.

Deliver a SageMaker-like experience anywhere

Transform the way you build, deploy, and scale machine learning with Rafay’s comprehensive MLOps platform that runs in your data center and any public cloud.

Provide self-service AI Workbenches to data scientists

Data scientists can quickly access a fully functional data scienceenvironment without the need for local setup or maintenance. They can be more productive, sooner, by focusing on coding and analysis rather than managing AI infrastructure.

Consume a scalable, cost-effective GenAI playground to enable experimentation

Help developers experiment with GenAI by enabling them to rapidly train, tune, and test large models, along with approved tools such as vector databases, inference servers, etc.