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A Kasm Workspaces desktop with data science toolsets based on the NVIDIA CUDA Kasm base image.

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Kasm Workspaces Data Science Desktop Environment

This project provides a desktop environment geared for data science. It is meant as an example to using DevOps to provide a secure working environment for data science using the Kasm Workspaces platform.

Kasm Workspaces is a container streaming platform that provides browser-based access to desktops, applications, and web services. Kasm uses a modern DevSecOps approach for programmatic delivery of services via Containerized Desktop Infrastructure (CDI) technology to create on-demand Docker containers that are accessible via web browser. The rendering of the graphical-based containers is powered by the open-source project KasmVNC

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Kasm Workspaces was developed by a team of cybersecurity experts to meet the most demanding secure collaboration requirements. Our solution makes use of the latest technology in DevOps to establish an architecture that is highly scalable, customizable, and easy to maintain. Most importantly, Kasm provides a solution, rather than a service, so it is infinitely customizable to your unique requirements and includes a developer API so that it can be integrated with, rather than replace, your existing applications and workflows.

Install Kasm Workspaces

Get the link to the latest install package from Kasm Downloads

wget https://<latest-kasm-version-url>
tar -xzvf kasm*.tar.gz
sudo kasm_release/install.sh

When the installation is complete it will output randomly generated credentials.

Build Image

On the server that Kasm Workspaces is deployed on, build the image. You can also build this image in a pipeline and push to a central respository. Workspaces can point to a central repository and can automatically pull images when they are updated.

sudo docker build -t kasmweb/datascience:1.9.0 .

Update Kasm Workspaces

Add a new Workspace image to the deployment and launch.

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Manual Deployment

While this image is primarily built to run inside the Kasm platform, it can also be executed manually. Please note that certain functionality, such as audio, is only available within the Kasm platform.

sudo docker run --rm  -it --shm-size=512m -p 6901:6901 -e VNC_PW=password kasmweb/datascience:1.9.0

The container is now accessible via a browser : https://<IP>:6901

  • User : kasm_user
  • Password: password

Help Us Make It Better

Please make a merge request or submit an issue to help us make this a better product for the community. We would greatly appreciate your feedback.

Tags

  • [version-number]

    Images are built and tagged along with the release of Kasm Workspaces (e.g 1.9.0). Utilize the version that corresponds to your version of Kasm Server.

  • [version-number]-rolling

    Rolling tags are images that are updated and built nightly (e.g 1.9.0-rolling). Kasm Workspaces administrators may consider using these rolling images to ensure their systems are always up to date.

  • develop

    The develop tag is meant for testers and provides no expectation of compatibility with current release of Kasm Workspaces

More Info

  • Platform Documentation

    Documentation: Instructions for installing and configuring Kasm Workspaces

  • Reporting Issues

    BitBucket: Report an issue with Kasm Workspaces

  • Creating Custom Workspaces Images

    Documentation: Info on configuring custom images and installing software.

    BitBucket: Coding examples for creating custom images.

  • KasmVNC

    GitHub: Kasm’s Open Source VNC server: browser-based, secure, high-performance.

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A Kasm Workspaces desktop with data science toolsets based on the NVIDIA CUDA Kasm base image.

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