Project Description
Create a set of container images for serving a mock git server and mock git clients in a Kubernetes cluster that can be used as building blocks for an interactive git playground.
Goal for this Hackweek
- Have a simple container file for running a mock git server in a Kubernetes cluster.
- Have a simple container file for running a mock git client in a Kubernetes cluster.
- Have a simple UI where a user of these images can visually check operations on the git server.
Resources
- https://docs.docker.com/engine/reference/builder/
- https://git-scm.com/
Looking for hackers with the skills:
This project is part of:
Hack Week 22
Activity
Comments
Be the first to comment!
Similar Projects
Migrate from Docker to Podman by tjyrinki_suse
Description
I'd like to continue my former work on containerization of several domains on a single server by changing from Docker containers to Podman containers. That will need an OS upgrade as well as Podman is not available in that old server version.
Goals
- Update OS.
- Migrate from Docker to Podman.
- Keep everything functional, including the existing "meanwhile done" additional Docker container that is actually being used already.
- Keep everything at least as secure as currently. One of the reasons of having the containers is to isolate risks related to services open to public Internet.
- Try to enable the Podman use in production.
- At minimum, learn about all of these topics.
- Optionally, improve Ansible side of things as well...
Resources
A search engine is one's friend. Migrating from Docker to Podman, and from docker-compose to podman-compose.
Port git-fixup to POSIX shell script and submit to git/git by mcepl
Description
https://github.com/keis/git-fixup is an exceedingly useful program, which I use daily, and I would love to every git user could bask in its awesomeness. Alas, it is a bash script, so it is not appropriate for the inclusion in git proper.
Goals
Port the script to plain POSIX shell and submit for consideration to git@vger.kernel.org
Resources
Explore the integration between OBS and GitHub by pdostal
Project Description
The goals:
1) When GitHub pull request is created or modified the OBS project will be forked and the build results reported back to GitHub. 2) When new version of the GitHub project will be published the OBS will redownload the source and rebuild the project.
Goal for this Hackweek
Do as much as possible, blog about it and maybe use it another existing project.
Resources
- The Blog post
- Issue: poo#123858 - build.opensuse.org: /usr/lib/obs/service//go_modules.service No such file or directory
Integrate Backstage with Rancher Manager by nwmacd
Description
Backstage (backstage.io) is an open-source, CNCF project that allows you to create your own developer portal. There are many plugins for Backstage.
This could be a great compliment to Rancher Manager.
Goals
Learn and experiment with Backstage and look at how this could be integrated with Rancher Manager. Goal is to have some kind of integration completed in this Hack week.
Install Uyuni on Kubernetes in cloud-native way by cbosdonnat
Description
For now installing Uyuni on Kubernetes requires running mgradm
on a cluster node... which is not what users would do in the Kubernetes world. The idea is to implement an installation based only on helm charts and probably an operator.
Goals
Install Uyuni from Rancher UI.
Resources
mgradm
code: https://github.com/uyuni-project/uyuni-tools- Uyuni operator: https://github.com/cbosdo/uyuni-operator
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!
AI + Board Games
Board games have long been fertile ground for AI innovation, pushing the boundaries of capabilities such as strategy, adaptability, and real-time decision-making - from Deep Blue's chess mastery to AlphaZero’s domination of Go. Games aren’t just fun: they’re complex, dynamic problems that often mirror real-world challenges, making them interesting from an engineering perspective.
As avid board gamers, aspiring board game designers, and engineers with careers in open source infrastructure, we’re excited to dive into the latest AI techniques first-hand.
Our goal is to develop an all-open-source, all-green AWS-based stack powered by some serious hardware to drive our board game experiments forward!
Project Goals
Set Up the Stack:
- Install and configure the TAG and PyTAG frameworks on SUSE Linux Enterprise Base Container Images.
- Integrate with the SUSE AI stack for GPU-accelerated training on AWS.
- Validate a sample GPU-accelerated PyTAG workload on SUSE AI.
- Ensure the setup is entirely repeatable with Terraform and configuration scripts, documenting results along the way.
Design and Implement AI Agents:
- Develop AI agents for the two board games, incorporating Statistical Forward Planning and Deep Reinforcement Learning techniques.
- Fine-tune model parameters to optimize game-playing performance.
- Document the advantages and limitations of each technique.
Test, Analyze, and Refine:
- Conduct AI vs. AI and AI vs. human matches to evaluate agent strategies and performance.
- Record insights, document learning outcomes, and refine models based on real-world gameplay.
Technical Stack
- Frameworks: TAG and PyTAG for AI agent development
- Platform: SUSE AI
- Tools: AWS for high-performance GPU acceleration
Why This Project Matters
This project not only deepens our understanding of AI techniques by doing but also showcases the power and flexibility of SUSE’s open-source infrastructure for supporting high-level AI projects. By building on an all-open-source stack, we aim to create a pathway for other developers and AI enthusiasts to explore, experiment, and deploy their own innovative projects within the open-source space.
Our Motivation
We believe hands-on experimentation is the best teacher.
Combining our engineering backgrounds with our passion for board games, we’ll explore AI in a way that’s both challenging and creatively rewarding. Our ultimate goal? To hack an AI agent that’s as strategic and adaptable as a real human opponent (if not better!) — and to leverage it to design even better games... for humans to play!
Extending KubeVirtBMC's capability by adding Redfish support by zchang
Description
In Hack Week 23, we delivered a project called KubeBMC (renamed to KubeVirtBMC now), which brings the good old-fashioned IPMI ways to manage virtual machines running on KubeVirt-powered clusters. This opens the possibility of integrating existing bare-metal provisioning solutions like Tinkerbell with virtualized environments. We even received an inquiry about transferring the project to the KubeVirt organization. So, a proposal was filed, which was accepted by the KubeVirt community, and the project was renamed after that. We have many tasks on our to-do list. Some of them are administrative tasks; some are feature-related. One of the most requested features is Redfish support.
Goals
Extend the capability of KubeVirtBMC by adding Redfish support. Currently, the virtbmc component only exposes IPMI endpoints. We need to implement another simulator to expose Redfish endpoints, as we did with the IPMI module. We aim at a basic set of functionalities:
- Power management
- Boot device selection
- Virtual media mount (this one is not so basic )
Resources
ClusterOps - Easily install and manage your personal kubernetes cluster by andreabenini
Description
ClusterOps is a Kubernetes installer and operator designed to streamline the initial configuration
and ongoing maintenance of kubernetes clusters. The focus of this project is primarily on personal
or local installations. However, the goal is to expand its use to encompass all installations of
Kubernetes for local development purposes.
It simplifies cluster management by automating tasks and providing just one user-friendly YAML-based
configuration config.yml
.
Overview
- Simplified Configuration: Define your desired cluster state in a simple YAML file, and ClusterOps will handle the rest.
- Automated Setup: Automates initial cluster configuration, including network settings, storage provisioning, special requirements (for example GPUs) and essential components installation.
- Ongoing Maintenance: Performs routine maintenance tasks such as upgrades, security updates, and resource monitoring.
- Extensibility: Easily extend functionality with custom plugins and configurations.
- Self-Healing: Detects and recovers from common cluster issues, ensuring stability, idempotence and reliability. Same operation can be performed multiple times without changing the result.
- Discreet: It works only on what it knows, if you are manually configuring parts of your kubernetes and this configuration does not interfere with it you can happily continue to work on several parts and use this tool only for what is needed.
Features
- distribution and engine independence. Install your favorite kubernetes engine with your package
manager, execute one script and you'll have a complete working environment at your disposal.
- Basic config approach. One single
config.yml
file with configuration requirements (add/remove features): human readable, plain and simple. All fancy configs managed automatically (ingress, balancers, services, proxy, ...). - Local Builtin ContainerHub. The default installation provides a fully configured ContainerHub available locally along with the kubernetes installation. This configuration allows the user to build, upload and deploy custom container images as they were provided from external sources. Internet public sources are still available but local development can be kept in this localhost server. Builtin ClusterOps operator will be fetched from this ContainerHub registry too.
- Kubernetes official dashboard installed as a plugin, others planned too (k9s for example).
- Kubevirt plugin installed and properly configured. Unleash the power of classic virtualization (KVM+QEMU) on top of Kubernetes and manage your entire system from there, libvirtd and virsh libs are required.
- One operator to rule them all. The installation script configures your machine automatically during installation and adds one kubernetes operator to manage your local cluster. From there the operator takes care of the cluster on your behalf.
- Clean installation and removal. Just test it, when you are done just use the same program to uninstall everything without leaving configs (or pods) behind.
Planned features (Wishlist / TODOs)
- Containerized Data Importer (CDI). Persistent storage management add-on for Kubernetes to provide a declarative way of building and importing Virtual Machine Disks on PVCs for
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
) and web frontend (tar1090
).
Goals
- Create a working receiver using MicroOS as a base, and containers based on Tumbleweed
- Make it easy to install
- 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
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!
AI + Board Games
Board games have long been fertile ground for AI innovation, pushing the boundaries of capabilities such as strategy, adaptability, and real-time decision-making - from Deep Blue's chess mastery to AlphaZero’s domination of Go. Games aren’t just fun: they’re complex, dynamic problems that often mirror real-world challenges, making them interesting from an engineering perspective.
As avid board gamers, aspiring board game designers, and engineers with careers in open source infrastructure, we’re excited to dive into the latest AI techniques first-hand.
Our goal is to develop an all-open-source, all-green AWS-based stack powered by some serious hardware to drive our board game experiments forward!
Project Goals
Set Up the Stack:
- Install and configure the TAG and PyTAG frameworks on SUSE Linux Enterprise Base Container Images.
- Integrate with the SUSE AI stack for GPU-accelerated training on AWS.
- Validate a sample GPU-accelerated PyTAG workload on SUSE AI.
- Ensure the setup is entirely repeatable with Terraform and configuration scripts, documenting results along the way.
Design and Implement AI Agents:
- Develop AI agents for the two board games, incorporating Statistical Forward Planning and Deep Reinforcement Learning techniques.
- Fine-tune model parameters to optimize game-playing performance.
- Document the advantages and limitations of each technique.
Test, Analyze, and Refine:
- Conduct AI vs. AI and AI vs. human matches to evaluate agent strategies and performance.
- Record insights, document learning outcomes, and refine models based on real-world gameplay.
Technical Stack
- Frameworks: TAG and PyTAG for AI agent development
- Platform: SUSE AI
- Tools: AWS for high-performance GPU acceleration
Why This Project Matters
This project not only deepens our understanding of AI techniques by doing but also showcases the power and flexibility of SUSE’s open-source infrastructure for supporting high-level AI projects. By building on an all-open-source stack, we aim to create a pathway for other developers and AI enthusiasts to explore, experiment, and deploy their own innovative projects within the open-source space.
Our Motivation
We believe hands-on experimentation is the best teacher.
Combining our engineering backgrounds with our passion for board games, we’ll explore AI in a way that’s both challenging and creatively rewarding. Our ultimate goal? To hack an AI agent that’s as strategic and adaptable as a real human opponent (if not better!) — and to leverage it to design even better games... for humans to play!
Enable the containerized Uyuni server to run on different host OS by j_renner
Description
The Uyuni server is provided as a container, but we still require it to run on Leap Micro? This is not how people expect to use containerized applications, so it would be great if we tested other host OSs and enabled them by providing builds of necessary tools for (e.g. mgradm). Interesting candidates should be:
- openSUSE Leap
- Cent OS 7
- Ubuntu
- ???
Goals
Make it really easy for anyone to run the Uyuni containerized server on whatever OS they want (with support for containers of course).
Improve Development Environment on Uyuni by mbussolotto
Description
Currently create a dev environment on Uyuni might be complicated. The steps are:
- add the correct repo
- download packages
- configure your IDE (checkstyle, format rules, sonarlint....)
- setup debug environment
- ...
The current doc can be improved: some information are hard to be find out, some others are completely missing.
Dev Container might solve this situation.
Goals
Uyuni development in no time:
- using VSCode:
- setting.json should contains all settings (for all languages in Uyuni, with all checkstyle rules etc...)
- dev container should contains all dependencies
- setup debug environment
- implement a GitHub Workspace solution
- re-write documentation
Lots of pieces are already implemented: we need to connect them in a consistent solution.
Resources
- https://github.com/uyuni-project/uyuni/wiki
Technical talks at universities by agamez
Description
This project aims to empower the next generation of tech professionals by offering hands-on workshops on containerization and Kubernetes, with a strong focus on open-source technologies. By providing practical experience with these cutting-edge tools and fostering a deep understanding of open-source principles, we aim to bridge the gap between academia and industry.
For now, the scope is limited to Spanish universities, since we already have the contacts and have started some conversations.
Goals
- Technical Skill Development: equip students with the fundamental knowledge and skills to build, deploy, and manage containerized applications using open-source tools like Kubernetes.
- Open-Source Mindset: foster a passion for open-source software, encouraging students to contribute to open-source projects and collaborate with the global developer community.
- Career Readiness: prepare students for industry-relevant roles by exposing them to real-world use cases, best practices, and open-source in companies.
Resources
- Instructors: experienced open-source professionals with deep knowledge of containerization and Kubernetes.
- SUSE Expertise: leverage SUSE's expertise in open-source technologies to provide insights into industry trends and best practices.