Relevance Lab CIS Level 2 Windows Data Science AMI for AWS RES

Building a GPU-accelerated data science environment that also meets CIS Level 2 security benchmarks typically requires weeks of manual configuration - hardening the OS, installing and validating drivers, configuring tools to comply with restrictive policies, and documenting controls for audit. Most data science AMIs sacrifice security for convenience, or deliver hardened images that break GPU workflows and development tools.

This AMI eliminates that trade-off. It delivers a fully functional, GPU-ready data science workspace on Windows Server 2022 that has been hardened to CIS Level 2 standards and validated via Amazon Inspector - so your team can start working on day one without compromising your security posture.

CIS Level 2 Compliance, Validated Hardened to meet CIS Level 2 Benchmarks for Windows Server 2022 with validation performed through Amazon Inspector. The configuration applies a defense-in-depth approach with restrictive settings that reduce the attack surface while preserving full tool functionality.

GPU-Optimized for ML and Analytics Pre-installed with CUDA Toolkit, NVIDIA drivers, and cuDNN - configured to operate within the hardened environment. Supports deep learning training and inference workloads on GPU-enabled EC2 instance families.

Complete Data Science Stack Includes JupyterLab, Jupyter Notebook (Python and R kernels), RStudio, VS Code, Visual Studio 2022 CE, and PyCharm CE. ML frameworks include PyTorch, TensorFlow, scikit-learn, PySpark, Dask, and Vowpal Wabbit - all integrated into the secured platform.

Secure Remote Access via NICE DCV High-performance remote desktop access through Amazon NICE DCV, with access policies configured to align with Level 2 security requirements including strict authentication and access control.

AWS RES Integration Fully compatible with AWS Research and Engineering Studio (RES) for streamlined deployment, user management, and workspace orchestration within your cloud environment.

Container and Environment Management Docker, Docker Compose, and Anaconda are configured following container hardening principles for enhanced security.

Productivity and Utilities Includes LibreOffice (Writer, Calc, Impress), Chrome, Git, 7-Zip, and AWS CLI - all with configurations modified to reduce potential vulnerabilities.

1. Subscribe to the AMI through AWS Marketplace.
2. Launch a GPU-enabled EC2 instance (g4dn, g5, or p-family recommended) using this AMI, either standalone or through AWS Research and Engineering Studio (RES).
3. Connect to your workspace via Amazon NICE DCV remote desktop.
4. Open JupyterLab, RStudio, or your preferred IDE and begin working immediately - all tools and GPU drivers are pre-configured.
5. Verify CIS compliance by running an Amazon Inspector scan to generate an auditable compliance report for your security team.

• Operating System: Windows Server 2022 (CIS Level 2 Hardened)
• Remote Access: Amazon NICE DCV
• Languages: Python 3.x, R
• IDEs: VS Code, Visual Studio 2022 CE, PyCharm CE, RStudio
• Notebook UIs: Jupyter Notebook, JupyterLab
• ML Frameworks: PyTorch, TensorFlow, scikit-learn, PySpark, Dask, Vowpal Wabbit
• Environment Tools: Docker, Docker Compose, Anaconda
• Office Tools: LibreOffice (Writer, Calc, Impress)
• GPU Stack: CUDA Toolkit, cuDNN, NVIDIA drivers
• Supported Instances: GPU-enabled EC2 families (g4dn, g5, p4d, p5)

This AMI requires a GPU-enabled EC2 instance to leverage the full CUDA and deep learning stack. Standard EC2 infrastructure costs apply separately from the AMI software charge.

Organizations and professionals in regulated sectors - finance, healthcare, government, and research - who need a secure, auditable, GPU-enabled environment for working with sensitive data. Deploy a compliant data science workspace without weeks of manual hardening and configuration.

To schedule a compliance walkthrough with your security team or request a guided pilot deployment, contact Relevance Lab through the support channel listed on this page.