FizzBuzz OS by mssola

Project Description

FizzBuzz OS (or just fbos) is an idea I've had in order to better grasp the fundamentals of the low level of a RISC-V machine. In practice, I'd like to build a small Operating System kernel that is able to launch three processes: one that simply prints "Fizz", another that prints "Buzz", and the third which prints "FizzBuzz". These processes are unaware of each other and it's up to the kernel to schedule them by using the timer interrupts as given on openSBI (fizz on % 3 seconds, buzz on % 5 seconds, and fizzbuzz on % 15 seconds).

This kernel provides just one system call, write, which allows any program to pass the string to be written into stdout.

This project is free software and you can find it here.

Goal for this Hackweek

• Better understand the RISC-V SBI interface.
• Better understand RISC-V in privileged mode.
• Have fun.

Resources

• SBI v2.0 ratified specification
• Blog post on SBI
• mssola/fbos

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Add a machine-readable output to dmidecode by jdelvare

Description

There have been repeated requests for a machine-friendly dmidecode output over the last decade. During Hack Week 19, 5 years ago, I prepared the code to support alternative output formats, but didn't have the time to go further. Last year, Jiri Hnidek from Red Hat Linux posted a proof-of-concept implementation to add JSON output support. This is a fairly large pull request which needs to be carefully reviewed and tested.

Goals

Review Jiri's work and provide constructive feedback. Merge the code if acceptable. Evaluate the costs and benefits of using a library such as json-c.

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Create a DRM driver for VGA video cards by tdz

Yes, those VGA video cards. The goal of this project is to implement a DRM graphics driver for such devices. While actual hardware is hard to obtain or even run today, qemu emulates VGA output.

VGA has a number of limitations, which make this project interesting.

• There are only 640x480 pixels (or less) on the screen. That resolution is also a soft lower limit imposed by DRM. It's mostly a problem for desktop environments though.
• Desktop environments assume 16 million colors, but there are only 16 colors with VGA. VGA's 256 color palette is not available at 640x480. We can choose those 16 colors freely. The interesting part is how to choose them. We have to build a palette for the displayed frame and map each color to one of the palette's 16 entries. This is called dithering, and VGA's limitations are a good opportunity to learn about dithering algorithms.
• VGA has an interesting memory layout. Most graphics devices use linear framebuffers, which store the pixels byte by byte. VGA uses 4 bitplanes instead. Plane 0 holds all bits 0 of all pixels. Plane 1 holds all bits 1 of all pixels, and so on.

The driver will probably not be useful to many people. But, if finished, it can serve as test environment for low-level hardware. There's some interest in supporting old Amiga and Atari framebuffers in DRM. Those systems have similar limitations as VGA, but are harder to obtain and test with. With qemu, the VGA driver could fill this gap.

Apart from the Wikipedia entry, good resources on VGA are at osdev.net and FreeVGA

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Create DRM drivers for VESA and EFI framebuffers by tdz

Description

We already have simpledrm for firmware framebuffers. But the driver is originally for ARM boards, not PCs. It is already overloaded with code to support both use cases. At the same time it is missing possible features for VESA and EFI, such as palette modes or EDID support. We should have DRM drivers for VESA and EFI interfaces. The infrastructure exists already and initial drivers can be forked from simpledrm.

Goals

• Initially, a bare driver for VESA or EFI should be created. It can take functionality from simpledrm.
• Then we can begin to add additional features. The boot loader can provide EDID data. With VGA hardware, VESA can support paletted modes or color management. Example code exists in vesafb.

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Finish gfxprim application multiplexor (window manager) by metan

Project Description

I've implemented drivers for a few e-ink displays during the last hackweek and made sure that gfxprim widgets run nicely on e-ink as well. The missing piece to have a portable e-ink computer/reader/music player/... is a application that can switch between currently running applications and that can start new applications as well. Half of the solution is ready, there is a proxy gfxprim backend where applications render into a piece of a shared memory and input events (e.g. keyboard, mouse) can be multiplexed. What is missing is an interface (possibly touchscreen friendly as well) to make it user friendly.

Goal for this Hackweek

Make nekowm usable "window manager".

Resources

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New openSUSE-welcome by lkocman

Project Description

Let's revisit our existing openSUSE welcome app.

My goal was to show Leap 16 in a new coat. Welcome app adds to the first time use experience. We've recently added donation button to our existing welcome.

Some things that I recently wanted to address were EOL and possibly upgrade notification.

I've already done some experiments with mint welcome app, but not sure if it's better than the existing one.

There is also a PR to rework existing app https://github.com/openSUSE/openSUSE-welcome/pull/36 (this should be considered as an option too)

Goal for this Hackweek

New welcome app, possibly with EOL notification for Leap.

1) Welcome application(s) with (rebrand changes) maintained under github.com/openSUSE

2) Application is submitted to openSUSE:Factory && openSUSE:Leap:16.0

3) Updated needles in openQA (probably post hackweek)

Resources

Reddit discussion about the best welcome app out there.

Github repo for the current welcome app.

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Saline (state deployment control and monitoring tool for SUSE Manager/Uyuni) by vizhestkov

Project Description

Saline is an addition for salt used in SUSE Manager/Uyuni aimed to provide better control and visibility for states deploymend in the large scale environments.

In current state the published version can be used only as a Prometheus exporter and missing some of the key features implemented in PoC (not published). Now it can provide metrics related to salt events and state apply process on the minions. But there is no control on this process implemented yet.

Continue with implementation of the missing features and improve the existing implementation:

• authentication (need to decide how it should be/or not related to salt auth)

• web service providing the control of states deployment

Goal for this Hackweek

• Implement missing key features

• Implement the tool for state deployment control with CLI

Resources

https://github.com/openSUSE/saline

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Symbol Relations by hli

Description

There are tools to build function call graphs based on parsing source code, for example, cscope.

This project aims to achieve a similar goal by directly parsing the disasembly (i.e. objdump) of a compiled binary. The assembly code is what the CPU sees, therefore more "direct". This may be useful in certain scenarios, such as gdb/crash debugging.

Detailed description and Demos can be found in the README file:

Supports x86 for now (because my customers only use x86 machines), but support for other architectures can be added easily.

Tested with python3.6

Goals

Any comments are welcome.

Resources

https://github.com/lhb-cafe/SymbolRelations

symrellib.py: mplements the symbol relation graph and the disassembly parser

symrel_tracer*.py: implements tracing (-t option)

symrel.py: "cli parser"

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Make more sense of openQA test results using AI by livdywan

Description

AI has the potential to help with something many of us spend a lot of time doing which is making sense of openQA logs when a job fails.

User Story

Allison Average has a puzzled look on their face while staring at log files that seem to make little sense. Is this a known issue, something completely new or maybe related to infrastructure changes?

Goals

• Leverage a chat interface to help Allison
• Create a model from scratch based on data from openQA
• Proof of concept for automated analysis of openQA test results

Bonus

• Use AI to suggest solutions to merge conflicts
  • This would need a merge conflict editor that can suggest solving the conflict
• Use image recognition for needles

Resources

• TensorFlow
• open-webui
• openQA instance of openSUSE
• openQA documentation

Timeline

Day 1

• Conversing with open-webui to teach me how to create a model based on openQA test results
  • Asking for example code using TensorFlow in Python
  • Discussing log files to explore what to analyze
  • Drafting a new project called Testimony (based on Implementing a containerized Python action) - the project name was also suggested by the assistant

Day 2

• Using NotebookLLM (Gemini) to produce conversational versions of blog posts
  • Writing openQA tests in Python
  • Developing in distrobox containers
• Researching the possibility of creating a project logo with AI
  • Asking open-webui, persons with prior experience and conducting a web search for advice

Highlights

• I briefly tested compared models to see if they would make me more productive. Between llama, gemma and mistral there was no amazing difference in the results for my case.
• Convincing the chat interface to produce code specific to my use case required very explicit instructions.
• Asking for advice on how to use open-webui itself better was frustratingly unfruitful both in trivial and more advanced regards.
• Documentation on source materials used by LLM's and tools for this purpose seems virtually non-existent - specifically if a logo can be generated based on particular licenses

Outcomes

• Chat interface-supported development is providing good starting points and open-webui being open source is more flexible than Gemini. Although currently some fancy features such as grounding and generated podcasts are missing.
• Allison still has to be very experienced with openQA to use a chat interface for test review. Publicly available system prompts would make that easier, though.

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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

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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!

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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!

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Project Goals

1. 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.

2. 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.

3. 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.

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Technical Stack

• Frameworks: TAG and PyTAG for AI agent development
• Platform: SUSE AI
• Tools: AWS for high-performance GPU acceleration

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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.

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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!

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