Red Hat Enterprise Linux 10 AI/ML Environment with JupyterLab
Madarson It, LLC · Operations & Productivity
Certification per Microsoft Marketplace.
Evidence tier Source Confirmed · 7 captures on record
What the publisher says
As described on Microsoft Marketplace.
Overview
This Azure Marketplace image provides a secure, enterprise-ready AI and machine learning environment built on Red Hat Enterprise Linux (RHEL). It includes JupyterLab pre-installed and configured with token-based authentication, offering a reliable foundation for data science and machine learning workloads on Microsoft Azure.
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Key Features
- Red Hat Enterprise Linux base image optimized for Azure
- JupyterLab pre-installed in a Python virtual environment
- Token-based authentication enabled by default
- Persistent storage layout aligned with Azure VM best practices
- SELinux enforcing and firewall enabled
Network Access
JupyterLab listens on TCP port 8888. Customers must explicitly allow inbound access to this port using an Azure Network Security Group (NSG) or equivalent firewall configuration. No ports are exposed automatically by this image.
Enterprise-Ready Design
The image follows Azure and RHEL best practices for security, filesystem layout, and lifecycle management. Application binaries and user notebooks are stored on persistent disks to ensure durability across reboots, resizing, and VM redeployments. Azure ephemeral storage is intentionally not used for application data.
Security Model
- No hardcoded credentials or embedded secrets
- Runtime-generated JupyterLab access tokens
- SELinux running in enforcing mode
- Minimal exposed network surface
Typical Use Cases
- Data science and machine learning experimentation
- Model prototyping and notebook-based research
- Enterprise AI/ML proof-of-concept environments
- Training and educational labs
Getting Started
- Deploy the VM from Azure Marketplace
- Connect via SSH using Azure-configured credentials
- Allow TCP port 8888 in your Network Security Group
- Start the JupyterLab service
- Access JupyterLab using the generated access token
Customization
Customers may install additional Python libraries, frameworks, or tooling to tailor the environment to their AI/ML workflows. This image serves as a clean, extensible baseline rather than a locked-down appliance.
Private Offers and Custom Engagements
To speak with us about private offers, custom security requirements, or compliance needs, contact us at
info@madarsonit.com.
Disclaimer: Red Hat, Red Hat Enterprise Linux, RHEL, Cockpit, and Lightspeed are trademarks of Red Hat, Inc.
Madarson IT does not provide commercial licenses for Red Hat products or third-party software.
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5 images
Agent build and provenance
See the full provenance
The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.
Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Vendor
External enrichment · as of 2026-08-29
Sources
Publisher resources
5 linksLinked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
Evidence risk is the share of the build you cannot see before you deploy, not a security rating. Sign in to see the layer-by-layer basis for this band.