Rancher microfrontend extensions by ftorchia

Description

Rancher UI Extensions allow users, developers, partners, and customers to extend and enhance the Rancher UI. Extensions are Helm charts that can only be installed once into a cluster. The charts contain a UI built package that is downloaded and linked to the Host UI at runtime; this means that the extension pkg needs to be implemented using the same technology and have the same APIs as Rancher UI.

Goals

We want to create a new type of Rancher extension, based on microfrontend pattern. The extension is served in a docker container in the k8s clusters and embedded in the host UI; this would guarantee us to be able to create extensions unrelated to the rancher UI architecture, in any technology.

Non Goals

We want to apply the microfrontend pattern to the product-level extensions; we don't want to apply it to cluster-level extensions.

Resources

rancher-extension-microfrontend, Rancher extensions

---

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

---

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.

---

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.

---

Rancher/k8s Trouble-Maker by tonyhansen

Project Description

When studying for my RHCSA, I found trouble-maker, which is a program that breaks a Linux OS and requires you to fix it. I want to create something similar for Rancher/k8s that can allow for troubleshooting an unknown environment.

Goal for this Hackweek

Create a basic framework for creating Rancher/k8s cluster lab environments as needed for the Break/Fix Create at least 5 modules that can be applied to the cluster and require troubleshooting

Resources

https://github.com/rancher/terraform-provider-rancher2 https://github.com/rancher/tf-rancher-up

---

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

---

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

---

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

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.

---

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).

---

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.

---