Project Description
Iguana is an attempt to have 100% stable initramfs which functionality is enhanced by containers.
Iguana consists of different parts, iguana-workflow being one part of it.
Iguana-workflow is a rust project tasked by parsing special iguana workflow file and start containers based on it.
Goal for this Hackweek
With initramfs one of the goals is to have it as small as possible. Introducing container runtime to the Iguana made initrd big (about 110MB currently). Iguana completely bundles podman and podman takes about 40MB in the initrd.
Goal of this project is to refactor iguana-workflow to support different container frontends with goal to lower its overall size.
For example replacing podman with runc + skopeo should save 10MB in size.
Resources
Looking for hackers with the skills:
This project is part of:
Hack Week 22
Activity
Comments
Similar Projects
Agama installer on-line demo by lslezak
Description
The Agama installer provides a quite complex user interface. We have some screenshots on the web page but as it is basically a web application it would be nice to have some on-line demo where users could click and check it live.
The problem is that the Agama server directly accesses the hardware (storage probing) and loads installation repositories. We cannot easily mock this in the on-line demo so the easiest way is to have just a read-only demo. You could explore the configuration options but you could not change anything, all changes would be ignored.
The read-only demo would be a bit limited but I still think it would be useful for potential users get the feeling of the new Agama installer and get familiar with it before using in a real installation.
As a proof of concept I already created this on-line demo.
The implementation basically builds Agama in two modes - recording mode where it saves all REST API responses and replay mode where it for the REST API requests returns the previously recorded responses. Recording in the browser is inconvenient and error prone, there should be some scripting instead (see below).
Goals
- Create an Agama on-line demo which can be easily tested by users
- The Agama installer is still in alpha phase and in active development, the online demo needs to be easily rebuilt with the latest Agama version
- Ideally there should be some automation so the demo page is rebuilt automatically without any developer interactions (once a day or week?)
TODO
- Use OpenAPI to get all Agama REST API endpoints, write a script which queries all the endpoints automatically and saves the collected data to a file (see this related PR).
- Write a script for starting an Agama VM (use libvirt/qemu?), the script should ensure we always use the same virtual HW so if we need to dump the latest REST API state we get the same (or very similar data). This should ensure the demo page does not change much regarding the storage proposal etc...
- Fix changing the product, currently it gets stuck after clicking the "Select" button.
- Move the mocking data (the recorded REST API responses) outside the Agama sources, it's too big and will be probably often updated. To avoid messing the history keep it in a separate GitHub repository
- Allow changing the UI language
- Display some note (watermark) in the page so it is clear it is a read-only demo (probably with some version or build date to know how old it is)
- Automation for building new demo page from the latest sources. There should be some check which ensures the recorded data still matches the OpenAPI specification.
Changing the UI language
This will be quite tricky because selecting the proper translation file is done on the server side. We would probably need to completely re-implement the logic in the browser side and adapt the server for that.
Also some REST API responses contain translated texts (storage proposal, pattern names in software). We would need to query the respective endpoints in all supported languages and return the correct response in runtime according to the currently selected language.
Resources
- Agama sources
- Experimental proof of concept demo
- The respective source code change
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Resources
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Description
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Resources
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Description
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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!
Results: Infrastructure Achievements
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./deploy.sh
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Results: Game Design Insights
Our project focused on modeling and analyzing two card games of our own design within the TAG framework:
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- 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 .
- more about Bamboo on Dario's site
- more about R3 on Silvio's site (italian, translation coming)
- more about Totoro on Silvio's site
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
ADS-B receiver with MicroOS by epaolantonio
I would like to put one of my spare Raspberry Pis to good use, and what better way to see what flies above my head at any time?
There are various ready-to-use distros already set-up to provide feeder data to platforms like Flightradar24, ADS-B Exchange, FlightAware etc... The goal here would be to do it using MicroOS as a base and containerized decoding of ADS-B data (via tools like dump1090
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Goals
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- Optimize for maximum laziness (i.e. it should take care of itself with minimum intervention)
Resources
- 1x Small Board Computer capable of running MicroOS
- 1x RTL2832U DVB-T dongle
- 1x MicroSD card
- https://github.com/antirez/dump1090
- 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
- https://g7.github.io/adsbreceiver/
- https://github.com/g7/adsbreceiver
- https://build.opensuse.org/project/show/home:epaolantonio:adsbreceiver
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