Problem statement

Once a kernel is built, a developer/janitor may want to boot the kernel for various reasons, such as performing simple boot test or running tests and workloads from user space or simply playing around in a shell. However, an easy to use and a descriptive tool to perform those tasks doesn't exist to our knowledge.

We talked to kernel developers and were told to have a look at the following resources:

The approach

We plan to address this issue in the upcoming Hackweek. Our idea is to leverage LinuxKit as a driver to boot a given kernel image in different environments (qemu, Hyper-V, VMware and public clouds). As linuxkit is container-based, it is trivial to boot the kernel with various rootfs-images of all kinds of distributions. Note that it's easy to create custom rootfs images.

The tool we seek to implement should wrap everything up into something useful for developers and CI systems to use from the command line as well as from configuration files. The benefits of using a container-based infrastructure include:

Reproducibility: We bundle kernel images with the desired rootfs together and store them for a given amount of time. Re-running and re-creating those becomes trivial and easy.

Declarative approach: All steps to create the desired image are baked into configuration files. The benefits are again reproducibility and documentation.

Flexibility: In theory, we can bundle any kernel image with any rootfs and add as many files, binaries and directories on top as we please. Supporting different kinds of environments, including public clouds, makes the tool attractive for a broader audience.

Looking for hackers with the skills:

linux kernel testing containers infrastructure

This project is part of:

Hack Week 16

Activity

  • over 7 years ago: metan liked this project.
  • over 7 years ago: sebchlad liked this project.
  • over 7 years ago: vrothberg added keyword "linux" to this project.
  • over 7 years ago: vrothberg added keyword "kernel" to this project.
  • over 7 years ago: vrothberg added keyword "testing" to this project.
  • over 7 years ago: vrothberg added keyword "containers" to this project.
  • over 7 years ago: vrothberg added keyword "infrastructure" to this project.
  • over 7 years ago: FabianBmn joined this project.
  • over 7 years ago: ereslibre joined this project.
  • over 7 years ago: vrothberg started this project.
  • over 7 years ago: vrothberg originated this project.

  • Comments

    • metan
      over 7 years ago by metan | Reply

      FYI there is also the 0day framework from intel that more or less does this. But it works only on Debian, etc. See:

      https://01.org/lkp/documentation https://github.com/intel/lkp-tests

      • vrothberg
        over 7 years ago by vrothberg | Reply

        Thanks for the pointer. We're aware of the 0-Day robot, but the infrastructure behind isn't open. However, we can re-use parts of the tests.

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    • Add an interface to openQA cli

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    • https://github.com/flightaware/dump1090 (dump1090 fork by FlightAware)
    • https://github.com/wiedehopf/tar1090

    Project status (2024-11-22)

    So I'd say that I'm pretty satisfied with how it turned out. I've packaged readsb (as a replacement for dump1090), tar1090, tar1090-db and mlat-client (not used yet).

    Current status:

    • Able to set-up a working receiver using combustion+ignition (web app based on Fuel Ignition)
    • Able to feed to various feeds using the Beast protocol (Airplanes.live, ADSB.fi, ADSB.lol, ADSBExchange.com, Flyitalyadsb.com, Planespotters.net)
    • Able to feed to Flightradar24 (initial-setup available but NOT tested! I've only tested using a key I already had)
    • Local web interface (tar1090) to easily visualize the results
    • Cockpit pre-configured to ease maintenance

    What's missing:

    • MLAT (Multilateration) support. I've packaged mlat-client already, but I have to wire it up
    • FlightAware support

    Give it a go at https://g7.github.io/adsbreceiver/ !

    Project links


    Port the classic browser game HackTheNet to PHP 8 by dgedon

    Description

    The classic browser game HackTheNet from 2004 still runs on PHP 4/5 and MySQL 5 and needs a port to PHP 8 and e.g. MariaDB.

    Goals

    • Port the game to PHP 8 and MariaDB 11
    • Create a container where the game server can simply be started/stopped

    Resources

    • https://github.com/nodeg/hackthenet


    SUSE AI Meets the Game Board by moio

    Use tabletopgames.ai’s open source TAG and PyTAG frameworks to apply Statistical Forward Planning and Deep Reinforcement Learning to two board games of our own design. On an all-green, all-open source, all-AWS stack!
    A chameleon playing chess in a train car, as a metaphor of SUSE AI applied to games


    Results: Infrastructure Achievements

    We successfully built and automated a containerized stack to support our AI experiments. This included:

    A screenshot of k9s and nvtop showing PyTAG running in Kubernetes with GPU acceleration

    ./deploy.sh and voilà - Kubernetes running PyTAG (k9s, above) with GPU acceleration (nvtop, below)

    Results: Game Design Insights

    Our project focused on modeling and analyzing two card games of our own design within the TAG framework:

    • Game Modeling: We implemented models for Dario's "Bamboo" and Silvio's "Totoro" and "R3" games, enabling AI agents to play thousands of games ...in minutes!
    • AI-driven optimization: By analyzing statistical data on moves, strategies, and outcomes, we iteratively tweaked the game mechanics and rules to achieve better balance and player engagement.
    • Advanced analytics: Leveraging AI agents with Monte Carlo Tree Search (MCTS) and random action selection, we compared performance metrics to identify optimal strategies and uncover opportunities for game refinement .

    Cards from the three games

    A family picture of our card games in progress. From the top: Bamboo, Totoro, R3

    Results: Learning, Collaboration, and Innovation

    Beyond technical accomplishments, the project showcased innovative approaches to coding, learning, and teamwork:

    • "Trio programming" with AI assistance: Our "trio programming" approach—two developers and GitHub Copilot—was a standout success, especially in handling slightly-repetitive but not-quite-exactly-copypaste tasks. Java as a language tends to be verbose and we found it to be fitting particularly well.
    • AI tools for reporting and documentation: We extensively used AI chatbots to streamline writing and reporting. (Including writing this report! ...but this note was added manually during edit!)
    • GPU compute expertise: Overcoming challenges with CUDA drivers and cloud infrastructure deepened our understanding of GPU-accelerated workloads in the open-source ecosystem.
    • Game design as a learning platform: By blending AI techniques with creative game design, we learned not only about AI strategies but also about making games fun, engaging, and balanced.

    Last but not least we had a lot of fun! ...and this was definitely not a chatbot generated line!

    The Context: AI + Board Games