# **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.

- **Instant Access:** Launch JupyterLab notebooks immediately with no setup required **‍**
- **Seamless GPU Integration:** Run notebooks directly on GPUs for model training, testing, and inference **‍**
- **AI/ML-Ready Environments:** Pre-configured libraries and persistent storage simplify data preparation and prototyping

## 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](https://info@rafay.co/white-papers/operationalizing-ai-fabrics-with-aviz-ones-nvidia-spectrum-x-rafay)

**The Definitive GPU PaaS Reference Architecture**  
Understand what it takes to deliver the right GPU infrastructure to your business.  
[Learn More](https://info@rafay.co/nvidia-reference-architecture)

**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](https://info@rafay.co/resources/white-papers/cisco-rafay-ai-pods-gpu-cloud)

**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](https://info@rafay.co/research/silicon-media-analyst-report)

**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](/content/resources/white-papers/rafay-named-outperformer-in-2025-gigaom-radar-report-for-managed-kubernetes/index.html)

**Building AI Value within Borders**  
Rafay's central orchestration platform facilitates efficient, self-service infrastructure and AI application management.  
[Learn More](/content/resources/accenture-whitepaper/index.html)

**GPU cloud evaluation report**  
Evaluating how the Rafay Platform delivers a GPU cloud for enterprises and cloud service providers by PivotNine.  
[Learn More](https://info@rafay.co/resources/white-papers/gpu-cloud-evaluation-report)

**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](/content/resources/white-papers/how-enterprise-platform-teams-accelerate-ai-ml-initiatives/index.html)

"We are able to deliver new, innovative products and services to the global market faster and manage them cost-effectively with Rafay."

## Most Recent Blogs

**NVIDIA ❤️ Rafay Managed Kubernetes**  
[Read Now](https://info@rafay.co/ai-and-cloud-native-blog/rafay-completes-nvidia-gpu-operator-partner-validation)

**Telco Cloud Services: How Communication Service Providers Can Monetize Cloud Infrastructure**  
[Read Now](https://info@rafay.co/ai-and-cloud-native-blog/ai-and-cloud-native-blog-telco-cloud-services-explained)

**One-Click Digital Twins: Deploying the NVIDIA Omniverse DSX Blueprint using Rafay**  
[Read Now](https://info@rafay.co/ai-and-cloud-native-blog/one-click-digital-twins-deploying-the-nvidia-omniverse-dsx-blueprint-using-rafay)

## Hybrid Cloud Meets Kubernetes

Learn how to Streamline Kubernetes Ops in Hybrid Clouds with AWS & Rafay  
[DOWNLOAD](https://info@rafay.co/resources/white-papers/hybrid-cloud-meets-kubernetes-how-to-reduce-complexity-with-amazon-eks-eks-d-and-rafay-systems)

## 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](https://info@rafay.co/start)