Rafay-Powered Jupyter Notebooks as a Service | Rafay Platform

Rafay-Powered Jupyter Notebooks as a Service (JNBaaS)

Rafay-powered Jupyter Notebooks as a Service (JNBaaS) allows providers and enterprises to offer governed, on-demand JupyterLab environments for data science, AI, and ML teams. Developers and researchers often face delays in provisioning GPU-backed environments or managing dependencies.

Rafay eliminates these challenges by offering instant, fully managed Jupyter notebooks equipped with pre-installed AI/ML libraries, GPU access, and built-in collaboration tools.

Service providers, enterprises, and sovereign cloud operators can deliver ready-to-use, GPU-enabled notebook workspaces that accelerate experimentation and improve productivity.

Simplify and Automate AI/ML Experimentation

Rafay automates how teams access, share, and manage GPU-powered notebook environments—removing operational friction from model development.

Pre-Configured Environments

PyTorch, TensorFlow, CUDA, and other frameworks are ready to use out of the box.

Persistent Storage

Maintain consistent access to datasets and results for reproducible workflows.

Collaboration Controls

Enable secure notebook sharing with role-based access and team visibility.

Integrated Governance

Ensure compliance, traceability, and consistent policies across all environments.

Accelerate Experimentation and Improve Resource Utilization

Move from concept to GPU-backed experimentation in seconds, accelerating AI/ML projects.

Monetize notebooks as value-added SKUs to increase utilization per GPU.

Enable secure, multi-user access with reproducibility and version control.

Deliver compliant, notebook services aligned with data residency and governance requirements

Featured Resources

Operationalizing AI Fabrics with Aviz ONES, NVIDIA Spectrum-X, and Rafay

Discover the new AI operations model available to enterprises that enables self-service consumption and cloud-native orchestration for developers. Learn More

The Definitive GPU PaaS Reference Architecture

Understand what it takes to deliver the right GPU infrastructure to your business. Learn More

Unlock Your AI Potential with Cisco and Rafay: Transform AI PODs into a Self-Service GPU Cloud

Cisco provides AI-optimized infrastructure. Rafay makes it usable across teams, tenants, and use cases in days. Learn More

The CIO’s guide to scalable, compliant, and developer-ready AI deployment

Orchestrating the future of AI: The CIO’s guide to scalable, compliant, and developer-ready AI deployment. Learn More

Rafay Named Outperformer in 2025 GigaOm Radar Report for Managed Kubernetes

The latest Radar report from GigaOm, Managed Kubernetes Rafay is ranked as an “Outperformer” for its solution. Learn More

Building AI Value within Borders

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

GPU cloud evaluation report

Evaluating how the Rafay Platform delivers a GPU cloud for enterprises and cloud service providers by PivotNine. Learn More

How Enterprise Platform Teams Can Accelerate AI/ML Initiatives

This paper explores the key challenges that organizations experience supporting these initiatives, as well as best practices for successfully leveraging Kubernetes to accelerate AI/ML projects. Learn More

Joe Vaughan
Chief Technology Officer,
MoneyGram

Most Recent Blogs

NVIDIA ❤️ Rafay Managed Kubernetes

Read Now

Telco Cloud Services: How Communication Service Providers Can Monetize Cloud Infrastructure

Read Now

One-Click Digital Twins: Deploying the NVIDIA Omniverse DSX Blueprint using Rafay

Read Now

Hybrid Cloud Meets Kubernetes

Learn how to Streamline Kubernetes Ops in Hybrid Clouds with AWS & Rafay. DOWNLOAD

Start a conversation with Rafay

Talk with Rafay experts to assess your infrastructure, explore your use cases, and see how teams like yours operationalize AI/ML and cloud-native initiatives with self-service and governance built in. Start a Conversation