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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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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OpenQA Golang api client by hilchev

Description

I would like to make a simple cli tool to communicate with the OpenQA API

Goals

• OpenQA has a ton of information that is hard to get via the UI. A tool like this would make my life easier :)
• Would potentially make it easier in the future to make UI changes without Perl.
• Improve my Golang skills

Resources

• https://go.dev/doc/
• https://openqa.opensuse.org/api

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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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Dartboard TUI by IValentin

Description

Our scalability and performance testing swiss-army knife tool Dartboard is a major WIP so why not add more scope creep? Dartboard is a cli tool which enables users to:

• Define a "Dart" config file as YAML which defines the various components to be created/setup when Dartboard runs its commands
• Spin up infrastructure utilizing opentofu/terraform providers
• Setup K3s or RKE2 clusters on the newly created infrastructure
• Deploy Rancher (with or without downstream cluster), rancher-monitoring (Grafana + Prometheus)
• Create resources in-bulk within the newly created Rancher cluster (ConfigMaps, Secrets, Users, Roles, etc.)
• Run various performance and scalability tests via k6
• Export/Import various tracked metrics (WIP)

Given all these features (and the features to come), it can be difficult to onboard and transfer knowledge of the tool. With a TUI, Dartboard's usage complexity can be greatly reduced!

Goals

• Create a TUI for Dartboard's "subcommands"
• Gain more familiarity with Dartboard and create a more user-friendly interface to enable others to use it
• Stretch Create a TUI workflow for generating a Dart file

Resources

https://github.com/charmbracelet/bubbletea

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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.

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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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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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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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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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