Learn enough Golang and hack on CoreDNS by jkuzilek

Description

I'm implementing a split-horizon DNS for my home Kubernetes cluster to be able to access my internal (and external) services over the local network through public domains. I managed to make a PoC with the k8s_gateway plugin for CoreDNS. However, I soon found out it responds with IPs for all Gateways assigned to HTTPRoutes, publishing public IPs as well as the internal Loadbalancer ones.

To remedy this issue, a simple filtering mechanism has to be implemented.

Goals

• Learn an acceptable amount of Golang
• Implement GatewayClass (and IngressClass) filtering for k8s_gateway
• Deploy on homelab cluster
• Profit?

Resources

• https://github.com/ori-edge/k8s_gateway/issues/36
• https://github.com/coredns/coredns/issues/2465#issuecomment-593910983

EDIT: Feature mostly complete. An unfinished PR lies here. Successfully tested working on homelab cluster.

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Harvester Packer Plugin by mrohrich

Description

Hashicorp Packer is an automation tool that allows automatic customized VM image builds - assuming the user has a virtualization tool at their disposal. To make use of Harvester as such a virtualization tool a plugin for Packer needs to be written. With this plugin users could make use of their Harvester cluster to build customized VM images, something they likely want to do if they have a Harvester cluster.

Goals

Write a Packer plugin bridging the gap between Harvester and Packer. Users should be able to create customized VM images using Packer and Harvester with no need to utilize another virtualization platform.

Resources

Hashicorp documentation for building custom plugins for Packer https://developer.hashicorp.com/packer/docs/plugins/creation/custom-builders

Source repository of the Harvester Packer plugin https://github.com/m-ildefons/harvester-packer-plugin

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Mammuthus - The NFS-Ganesha inside Kubernetes controller by vcheng

Description

As the user-space NFS provider, the NFS-Ganesha is wieldy use with serval projects. e.g. Longhorn/Rook. We want to create the Kubernetes Controller to make configuring NFS-Ganesha easy. This controller will let users configure NFS-Ganesha through different backends like VFS/CephFS.

Goals

1. Create NFS-Ganesha Package on OBS: nfs-ganesha5, nfs-ganesha6
2. Create NFS-Ganesha Container Image on OBS: Image
3. Create a Kubernetes controller for NFS-Ganesha and support the VFS configuration on demand. Mammuthus

Resources

NFS-Ganesha

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Introducing "Bottles": A Proof of Concept for Multi-Version CRD Management in Kubernetes by aruiz

Description

As we delve deeper into the complexities of managing multiple CRD versions within a single Kubernetes cluster, I want to introduce "Bottles" - a proof of concept that aims to address these challenges.

Bottles propose a novel approach to isolating and deploying different CRD versions in a self-contained environment. This would allow for greater flexibility and efficiency in managing diverse workloads.

Goals

• Evaluate Feasibility: determine if this approach is technically viable, as well as identifying possible obstacles and limitations.
• Reuse existing technology: leverage existing products whenever possible, e.g. build on top of Kubewarden as admission controller.
• Focus on Rancher's use case: the ultimate goal is to be able to use this approach to solve Rancher users' needs.

Resources

Core concepts:

• ConfigMaps: Bottles could be defined and configured using ConfigMaps.
• Admission Controller: An admission controller will detect "bootled" CRDs being installed and replace the resource name used to store them.
• Aggregated API Server: By analyzing the author of a request, the aggregated API server will determine the correct bottle and route the request accordingly, making it transparent for the user.

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Metrics Server viewer for Kubernetes by bkampen

This project is finished please visit the github repo below for the tool.

Description

Build a CLI tools which can visualize Kubernetes metrics from the metrics-server, so you're able to watch these without installing Prometheus and Grafana on a cluster.

Goals

• Learn more about metrics-server
• Learn more about the inner workings of Kubernetes.
• Learn more about Go

Resources

https://github.com/bvankampen/metrics-viewer

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A CLI for Harvester by mohamed.belgaied

[comment]: # Harvester does not officially come with a CLI tool, the user is supposed to interact with Harvester mostly through the UI [comment]: # Though it is theoretically possible to use kubectl to interact with Harvester, the manipulation of Kubevirt YAML objects is absolutely not user friendly. [comment]: # Inspired by tools like multipass from Canonical to easily and rapidly create one of multiple VMs, I began the development of Harvester CLI. Currently, it works but Harvester CLI needs some love to be up-to-date with Harvester v1.0.2 and needs some bug fixes and improvements as well.

Project Description

Harvester CLI is a command line interface tool written in Go, designed to simplify interfacing with a Harvester cluster as a user. It is especially useful for testing purposes as you can easily and rapidly create VMs in Harvester by providing a simple command such as: harvester vm create my-vm --count 5 to create 5 VMs named my-vm-01 to my-vm-05.

Harvester CLI is functional but needs a number of improvements: up-to-date functionality with Harvester v1.0.2 (some minor issues right now), modifying the default behaviour to create an opensuse VM instead of an ubuntu VM, solve some bugs, etc.

Github Repo for Harvester CLI: https://github.com/belgaied2/harvester-cli

Done in previous Hackweeks

• Create a Github actions pipeline to automatically integrate Harvester CLI to Homebrew repositories: DONE
• Automatically package Harvester CLI for OpenSUSE / Redhat RPMs or DEBs: DONE

Goal for this Hackweek

The goal for this Hackweek is to bring Harvester CLI up-to-speed with latest Harvester versions (v1.3.X and v1.4.X), and improve the code quality as well as implement some simple features and bug fixes.

Some nice additions might be: * Improve handling of namespaced objects * Add features, such as network management or Load Balancer creation ? * Add more unit tests and, why not, e2e tests * Improve CI * Improve the overall code quality * Test the program and create issues for it

Issue list is here: https://github.com/belgaied2/harvester-cli/issues

Resources

The project is written in Go, and using client-go the Kubernetes Go Client libraries to communicate with the Harvester API (which is Kubernetes in fact). Welcome contributions are:

• Testing it and creating issues
• Documentation
• Go code improvement

What you might learn

Harvester CLI might be interesting to you if you want to learn more about:

• GitHub Actions
• Harvester as a SUSE Product
• Go programming language
• Kubernetes API

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Harvester Packer Plugin by mrohrich

Description

Hashicorp Packer is an automation tool that allows automatic customized VM image builds - assuming the user has a virtualization tool at their disposal. To make use of Harvester as such a virtualization tool a plugin for Packer needs to be written. With this plugin users could make use of their Harvester cluster to build customized VM images, something they likely want to do if they have a Harvester cluster.

Goals

Write a Packer plugin bridging the gap between Harvester and Packer. Users should be able to create customized VM images using Packer and Harvester with no need to utilize another virtualization platform.

Resources

Hashicorp documentation for building custom plugins for Packer https://developer.hashicorp.com/packer/docs/plugins/creation/custom-builders

Source repository of the Harvester Packer plugin https://github.com/m-ildefons/harvester-packer-plugin

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A CLI for Harvester by mohamed.belgaied

[comment]: # Harvester does not officially come with a CLI tool, the user is supposed to interact with Harvester mostly through the UI [comment]: # Though it is theoretically possible to use kubectl to interact with Harvester, the manipulation of Kubevirt YAML objects is absolutely not user friendly. [comment]: # Inspired by tools like multipass from Canonical to easily and rapidly create one of multiple VMs, I began the development of Harvester CLI. Currently, it works but Harvester CLI needs some love to be up-to-date with Harvester v1.0.2 and needs some bug fixes and improvements as well.

Project Description

Harvester CLI is a command line interface tool written in Go, designed to simplify interfacing with a Harvester cluster as a user. It is especially useful for testing purposes as you can easily and rapidly create VMs in Harvester by providing a simple command such as: harvester vm create my-vm --count 5 to create 5 VMs named my-vm-01 to my-vm-05.

Harvester CLI is functional but needs a number of improvements: up-to-date functionality with Harvester v1.0.2 (some minor issues right now), modifying the default behaviour to create an opensuse VM instead of an ubuntu VM, solve some bugs, etc.

Github Repo for Harvester CLI: https://github.com/belgaied2/harvester-cli

Done in previous Hackweeks

• Create a Github actions pipeline to automatically integrate Harvester CLI to Homebrew repositories: DONE
• Automatically package Harvester CLI for OpenSUSE / Redhat RPMs or DEBs: DONE

Goal for this Hackweek

The goal for this Hackweek is to bring Harvester CLI up-to-speed with latest Harvester versions (v1.3.X and v1.4.X), and improve the code quality as well as implement some simple features and bug fixes.

Some nice additions might be: * Improve handling of namespaced objects * Add features, such as network management or Load Balancer creation ? * Add more unit tests and, why not, e2e tests * Improve CI * Improve the overall code quality * Test the program and create issues for it

Issue list is here: https://github.com/belgaied2/harvester-cli/issues

Resources

The project is written in Go, and using client-go the Kubernetes Go Client libraries to communicate with the Harvester API (which is Kubernetes in fact). Welcome contributions are:

• Testing it and creating issues
• Documentation
• Go code improvement

What you might learn

Harvester CLI might be interesting to you if you want to learn more about:

• GitHub Actions
• Harvester as a SUSE Product
• Go programming language
• Kubernetes API

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SUSE KVM Best Practices by roseswe

Description

SUSE Best Practices around KVM, especially for SAP workloads. Early Google presentation already made from various customer projects and SUSE sources.

Goals

Complete presentation we can reuse in SUSE Consulting projects

Resources

KVM (virt-manager) images

SUSE/SAP/KVM Best Practices

• https://documentation.suse.com/en-us/sles/15-SP6/single-html/SLES-virtualization/
• SAP Note 1522993 - "Linux: SAP on SUSE KVM - Kernel-based Virtual Machine" && 2284516 - SAP HANA virtualized on SUSE Linux Enterprise hypervisors https://me.sap.com/notes/2284516
• SUSECon24: [TUTORIAL-1253] Virtualizing SAP workloads with SUSE KVM || https://youtu.be/PTkpRVpX2PM
• SUSE Best Practices for SAP HANA on KVM - https://documentation.suse.com/sbp/sap-15/html/SBP-SLES4SAP-HANAonKVM-SLES15SP4/index.html

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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

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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

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Uyuni developer-centric documentation by deneb_alpha

Description

While we currently have extensive documentation on user-oriented tasks such as adding minions, patching, fine-tuning, etc, there is a notable gap when it comes to centralizing and documenting core functionalities for developers.

The number of functionalities and side tools we have in Uyuni can be overwhelming. It would be nice to have a centralized place with descriptive list of main/core functionalities.

Goals

Create, aggregate and review on the Uyuni wiki a set of resources, focused on developers, that include also some known common problems/troubleshooting.

The documentation will be helpful not only for everyone who is trying to learn the functionalities with all their inner processes like newcomer developers or community enthusiasts, but also for anyone who need a refresh.

Resources

The resources are currently aggregated here: https://github.com/uyuni-project/uyuni/wiki

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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

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

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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

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

• a Fully-Automated, One-Command, GPU-accelerated Kubernetes setup: we created an OpenTofu based script, tofu-tag, to deploy SUSE's RKE2 Kubernetes running on CUDA-enabled nodes in AWS, powered by openSUSE with GPU drivers and gpu-operator
• Containerization of the TAG and PyTAG frameworks: TAG (Tabletop AI Games) and PyTAG were patched for seamless deployment in containerized environments. We automated the container image creation process with GitHub Actions. Our forks (PRs upstream upcoming):
  • https://github.com/moio/TabletopGames/tree/hackweek24
  • https://github.com/moio/PyTAG/tree/hackweek24

./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 .
  • 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

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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

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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).

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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.

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toptop - a top clone written in Go by dshah

Description

toptop is a clone of Linux's top CLI tool, but written in Go.

Goals

Learn more about Go (mainly bubbletea) and Linux

Resources

GitHub

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Cluster API Add-on Provider for Kubewarden by csalas

Description

Can we integrate Kubewarden with Cluster API provisioning?

Cluster API is a Kubernetes project focused on providing declarative APIs and tooling to simplify provisioning, upgrading, and operating multiple Kubernetes clusters. TLDR; CAPI let's you define Kubernetes clusters in plain YAML, and CAPI providers (infrastructure, control plane/bootstrap, etc.) manage provisioning and configuration for you.

What if we could create an add-on provider that automatically installs Kubewarden and deploys Policy Servers to CAPI clusters?

Goals

• As a user I'd like to set a cluster (or list of clusters) and have the provider install Kubewarden for me.
• As a user I'd like to set what policies must be enforced for a cluster (or list of clusters).

Resources

• Cluster API: https://cluster-api.sigs.k8s.io/
• Kubewarden: https://docs.kubewarden.io/

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Metrics Server viewer for Kubernetes by bkampen

This project is finished please visit the github repo below for the tool.

Description

Build a CLI tools which can visualize Kubernetes metrics from the metrics-server, so you're able to watch these without installing Prometheus and Grafana on a cluster.

Goals

• Learn more about metrics-server
• Learn more about the inner workings of Kubernetes.
• Learn more about Go

Resources

https://github.com/bvankampen/metrics-viewer

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Automate PR process by idplscalabrini

Description

This project is to streamline and enhance the pr review process by adding automation for identifying some issues like missing comments, identifying sensitive information in the PRs like credentials. etc. By leveraging GitHub Actions and golang hooks we can focus more on high-level reviews

Goals

• Automate lints and code validations on Github actions
• Automate code validation on hook
• Implement a bot to pre-review the PRs

Resources

Golang hooks and Github actions

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Cluster API Provider for Harvester by rcase

Project Description

The Cluster API "infrastructure provider" for Harvester, also named CAPHV, makes it possible to use Harvester with Cluster API. This enables people and organisations to create Kubernetes clusters running on VMs created by Harvester using a declarative spec.

The project has been bootstrapped in HackWeek 23, and its code is available here.

Work done in HackWeek 2023

• Have a early working version of the provider available on Rancher Sandbox : *DONE *
• Demonstrated the created cluster can be imported using Rancher Turtles: DONE
• Stretch goal - demonstrate using the new provider with CAPRKE2: DONE and the templates are available on the repo

Goals for HackWeek 2024

• Add support for ClusterClass
• Add e2e testing
• Add more Unit Tests
• Improve Status Conditions to reflect current state of Infrastructure
• Improve CI (some bugs for release creation)
• Testing with newer Harvester version (v1.3.X and v1.4.X)
• Due to the length and complexity of the templates, maybe package some of them as Helm Charts.
• Other improvement suggestions are welcome!

DONE in HackWeek 24:

• Add more Unit Tests
• Improve Status Conditions for some phases
• Add cloud provider config generation
• Testing with Harvester v1.3.2
• Template improvements
• Issues creation

Thanks to @isim and Dominic Giebert for their contributions!

Resources

Looking for help from anyone interested in Cluster API (CAPI) or who wants to learn more about Harvester.

This will be an infrastructure provider for Cluster API. Some background reading for the CAPI aspect:

• Cluster infrastructure provider contract
• Machine infrastructure provider contract
• Provider implementers guide

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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

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terraform-provider-feilong by e_bischoff

Project Description

People need to test operating systems and applications on s390 platform.

Installation from scratch solutions include:

• just deploy and provision manually (with the help of ftpboot script, if you are at SUSE)
• use s3270 terminal emulation (used by openQA people?)
• use LXC from IBM to start CP commands and analyze the results
• use zPXE to do some PXE-alike booting (used by the orthos team?)
• use tessia to install from scratch using autoyast
• use libvirt for s390 to do some nested virtualization on some already deployed z/VM system
• directly install a Linux kernel on a LPAR and use kvm + libvirt from there

Deployment from image solutions include:

• use ICIC web interface (openstack in disguise, contributed by IBM)
• use ICIC from the openstack terraform provider (used by Rancher QA)
• use zvm_ansible to control SMAPI
• connect directly to SMAPI low-level socket interface

IBM Cloud Infrastructure Center (ICIC) harnesses the Feilong API, but you can use Feilong without installing ICIC, provided you set up a "z/VM cloud connector" into one of your VMs following this schema.

What about writing a terraform Feilong provider, just like we have the terraform libvirt provider? That would allow to transparently call Feilong from your main.tf files to deploy and destroy resources on your system/z.

Other Feilong-based solutions include:

• make libvirt Feilong-aware
• simply call Feilong from shell scripts with curl
• use zvmconnector client python library from Feilong
• use zthin part of Feilong to directly command SMAPI.

Goal for Hackweek 23

My final goal is to be able to easily deploy and provision VMs automatically on a z/VM system, in a way that people might enjoy even outside of SUSE.

My technical preference is to write a terraform provider plugin, as it is the approach that involves the least software components for our deployments, while remaining clean, and compatible with our existing development infrastructure.

Goals for Hackweek 24

Feilong provider works and is used internally by SUSE Manager team. Let's push it forward!

Let's add support for fiberchannel disks and multipath.

Goals for Hackweek 25

• Finish support for fiberchannel disks and multipath
• Fix problems with registration on hashicorp providers registry

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iSCSI integration in Warewulf by ncuralli

Description

This Hackweek project aims to enhance Warewulf’s capabilities by adding iSCSI support, enabling both remote boot and flexible mounting of iSCSI devices within the filesystem. The project, which already handles NFS, DHCP, and iPXE, will be extended to offer iSCSI services as well, centralizing all necessary services for provisioning and booting cluster nodes.

Goals

• iSCSI Boot Option: Enable nodes to boot directly from iSCSI volumes
• Mounting iSCSI Volumes within the Filesystem: Implement support for mounting iSCSI devices at various points within the filesystem

Resources

https://warewulf.org/

Steps

• add generic framework to handle remote ressource/filesystems to wwctl [ ]
• add iSCSI handling to wwctl configure [ ]
• add iSCSI to dracut files [ ]
• test it [ ]

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Mammuthus - The NFS-Ganesha inside Kubernetes controller by vcheng

Description

As the user-space NFS provider, the NFS-Ganesha is wieldy use with serval projects. e.g. Longhorn/Rook. We want to create the Kubernetes Controller to make configuring NFS-Ganesha easy. This controller will let users configure NFS-Ganesha through different backends like VFS/CephFS.

Goals

1. Create NFS-Ganesha Package on OBS: nfs-ganesha5, nfs-ganesha6
2. Create NFS-Ganesha Container Image on OBS: Image
3. Create a Kubernetes controller for NFS-Ganesha and support the VFS configuration on demand. Mammuthus

Resources

NFS-Ganesha

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Hack on rich terminal user interfaces by amanzini

Description

TUIs (Textual User Interface) are a big classic of our daily workflow. Many linux users 'live' in the terminal and modern implementations have a lot to offer : unicode fonts, 24 bit colors etc.

Goals

• Explore the current available solution on modern languages and implement a PoC , for example a small maze generator, porting of a classic game or just display the HackWeek cute logo.
• Practice some Go / Rust coding and programming patterns
• Fiddle around, hack, learn, have fun
• keep a development diary, practice on project documentation

Follow this link for source code repository

• includes development diary

Some ideas for inspiration:

• https://github.com/coding-horror/basic-computer-games
• https://git.imzadi.de/acn/vt100-games
• https://github.com/skx/lighthouse-of-doom
• https://github.com/rothgar/awesome-tuis
• https://www.zq1.de/~bernhard/images/share/geeko/logo.txt

Related projects:

• https://hackweek.opensuse.org/24/projects/suse-rancher-supportconfig from @eminguez

Resources

• Python:

  • https://github.com/Textualize/rich

• Go:

  • https://charm.sh/
  • https://github.com/JoelOtter/termloop
  • https://github.com/gdamore/tcell
  • https://earthly.dev/blog/tui-app-with-go/
  • https://www.inngest.com/blog/interactive-clis-with-bubbletea
  • https://m.youtube.com/watch?v=uJ2egAkSkjg

• Rust:

  • https://ratatui.rs/
  • https://github.com/lemunozm/ruscii
  • https://gitlab.com/thustle/thardians-rs
  • https://www.youtube.com/live/qaaHhfPGde0

• Misc:

  • Book about programming mazes

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Testing and adding GNU/Linux distributions on Uyuni by juliogonzalezgil

Join the Gitter channel! https://gitter.im/uyuni-project/hackweek

Uyuni is a configuration and infrastructure management tool that saves you time and headaches when you have to manage and update tens, hundreds or even thousands of machines. It also manages configuration, can run audits, build image containers, monitor and much more!

Currently there are a few distributions that are completely untested on Uyuni or SUSE Manager (AFAIK) or just not tested since a long time, and could be interesting knowing how hard would be working with them and, if possible, fix whatever is broken.

For newcomers, the easiest distributions are those based on DEB or RPM packages. Distributions with other package formats are doable, but will require adapting the Python and Java code to be able to sync and analyze such packages (and if salt does not support those packages, it will need changes as well). So if you want a distribution with other packages, make sure you are comfortable handling such changes.

No developer experience? No worries! We had non-developers contributors in the past, and we are ready to help as long as you are willing to learn. If you don't want to code at all, you can also help us preparing the documentation after someone else has the initial code ready, or you could also help with testing :-)

The idea is testing Salt and Salt-ssh clients, but NOT traditional clients, which are deprecated.

To consider that a distribution has basic support, we should cover at least (points 3-6 are to be tested for both salt minions and salt ssh minions):

1. Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
2. Onboarding (salt minion from UI, salt minion from bootstrap scritp, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator)
3. Package management (install, remove, update...)
4. Patching
5. Applying any basic salt state (including a formula)
6. Salt remote commands
7. Bonus point: Java part for product identification, and monitoring enablement
8. Bonus point: sumaform enablement (https://github.com/uyuni-project/sumaform)
9. Bonus point: Documentation (https://github.com/uyuni-project/uyuni-docs)
10. Bonus point: testsuite enablement (https://github.com/uyuni-project/uyuni/tree/master/testsuite)

If something is breaking: we can try to fix it, but the main idea is research how supported it is right now. Beyond that it's up to each project member how much to hack :-)

• If you don't have knowledge about some of the steps: ask the team
• If you still don't know what to do: switch to another distribution and keep testing.

This card is for EVERYONE, not just developers. Seriously! We had people from other teams helping that were not developers, and added support for Debian and new SUSE Linux Enterprise and openSUSE Leap versions :-)

Pending

FUSS

FUSS is a complete GNU/Linux solution (server, client and desktop/standalone) based on Debian for managing an educational network.

https://fuss.bz.it/

Seems to be a Debian 12 derivative, so adding it could be quite easy.

• [W] Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
• [W] Onboarding (salt minion from UI, salt minion from bootstrap script, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator) --> Working for all 3 options (salt minion UI, salt minion bootstrap script and salt-ssh minion from the UI).
• [W] Package management (install, remove, update...) --> Installing a new package works, needs to test the rest.
• [I] Patching (if patch information is available, could require writing some code to parse it, but IIRC we have support for Ubuntu already). No patches detected. Do we support patches for Debian at all?
• [W] Applying any basic salt state (including a formula)
• [W] Salt remote commands
• [ ] Bonus point: Java part for product identification, and monitoring enablement

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Ansible for add-on management by lmanfredi

Description

Machines can contains various combinations of add-ons and are often modified during the time.

The list of repos can change so I would like to create an automation able to reset the status to a given state, based on metadata available for these machines

Goals

Create an Ansible automation able to take care of add-on (repo list) configuration using metadata as reference

Resources

• Machines
• Repositories
• Developing modules
• Basic VM Guest management
• Module zypper_repository_list
• ansible-collections community.general
  • plugins/modules/zypper.py
  • plugins/modules/zypper_repository.py
  • plugins/modules/zypperrepositoryinfo.py

Results

Created WIP project Ansible-add-on-openSUSE

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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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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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Results: Infrastructure Achievements

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

• a Fully-Automated, One-Command, GPU-accelerated Kubernetes setup: we created an OpenTofu based script, tofu-tag, to deploy SUSE's RKE2 Kubernetes running on CUDA-enabled nodes in AWS, powered by openSUSE with GPU drivers and gpu-operator
• Containerization of the TAG and PyTAG frameworks: TAG (Tabletop AI Games) and PyTAG were patched for seamless deployment in containerized environments. We automated the container image creation process with GitHub Actions. Our forks (PRs upstream upcoming):
  • https://github.com/moio/TabletopGames/tree/hackweek24
  • https://github.com/moio/PyTAG/tree/hackweek24

./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 .
  • 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

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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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