The incredible Neal Gompa has packaged Open Shift Origin (RH's core Docker + Kubernetes stack) for openSUSE

Links:

  • "https://build.opensuse.org/package/show/home:Pharaoh_Atem:SUSE_Origin/origin"
  • https://src.fedoraproject.org/rpms/origin/tree/master
  • https://github.com/openshift/openshift-ansible
  • https://www.openshift.org/

For HackWeek I want to take what Neal has done to the next level

Steps to be completed

  • Test the package
  • Build & Test Tumbleweed Containers with OpenShift
  • Decide which approach makes more sense for Kubic (Production Deployment favours rpms)
  • Get rpms/containers heading towards Factory properly
  • Create and integrate an OpenShift System Role in Kubic

Looking for hackers with the skills:

kubernetes packaging containers satanicrituals

This project is part of:

Hack Week 17

Activity

  • over 7 years ago: Pharaoh_Atem liked this project.
  • over 7 years ago: RBrownSUSE added keyword "kubernetes" to this project.
  • over 7 years ago: RBrownSUSE added keyword "packaging" to this project.
  • over 7 years ago: RBrownSUSE added keyword "containers" to this project.
  • over 7 years ago: RBrownSUSE added keyword "satanicrituals" to this project.
  • over 7 years ago: RBrownSUSE started this project.
  • over 7 years ago: RBrownSUSE originated this project.

  • Comments

    • Pharaoh_Atem
      over 7 years ago by Pharaoh_Atem | Reply

      Happy to help where I can, Richard! add-emoji

      • RBrownSUSE
        over 7 years ago by RBrownSUSE | Reply

        You have all 4 of the mad skills required? ;)

        • Pharaoh_Atem
          over 7 years ago by Pharaoh_Atem | Reply

          I've got two of the four, does that help?

    Similar Projects

    Kubernetes-Based ML Lifecycle Automation by lmiranda

    Description

    This project aims to build a complete end-to-end Machine Learning pipeline running entirely on Kubernetes, using Go, and containerized ML components.

    The pipeline will automate the lifecycle of a machine learning model, including:

    • Data ingestion/collection
    • Model training as a Kubernetes Job
    • Model artifact storage in an S3-compatible registry (e.g. Minio)
    • A Go-based deployment controller that automatically deploys new model versions to Kubernetes using Rancher
    • A lightweight inference service that loads and serves the latest model
    • Monitoring of model performance and service health through Prometheus/Grafana

    The outcome is a working prototype of an MLOps workflow that demonstrates how AI workloads can be trained, versioned, deployed, and monitored using the Kubernetes ecosystem.

    Goals

    By the end of Hack Week, the project should:

    1. Produce a fully functional ML pipeline running on Kubernetes with:

      • Data collection job
      • Training job container
      • Storage and versioning of trained models
      • Automated deployment of new model versions
      • Model inference API service
      • Basic monitoring dashboards
    2. Showcase a Go-based deployment automation component, which scans the model registry and automatically generates & applies Kubernetes manifests for new model versions.

    3. Enable continuous improvement by making the system modular and extensible (e.g., additional models, metrics, autoscaling, or drift detection can be added later).

    4. Prepare a short demo explaining the end-to-end process and how new models flow through the system.

    Resources

    Project Repository

    Updates

    1. Training pipeline and datasets
    2. Inference Service py


    Self-Scaling LLM Infrastructure Powered by Rancher by ademicev0

    Self-Scaling LLM Infrastructure Powered by Rancher

    logo


    Description

    The Problem

    Running LLMs can get expensive and complex pretty quickly.

    Today there are typically two choices:

    1. Use cloud APIs like OpenAI or Anthropic. Easy to start with, but costs add up at scale.
    2. Self-host everything - set up Kubernetes, figure out GPU scheduling, handle scaling, manage model serving... it's a lot of work.

    What if there was a middle ground?

    What if infrastructure scaled itself instead of making you scale it?

    Can we use existing Rancher capabilities like CAPI, autoscaling, and GitOps to make this simpler instead of building everything from scratch?

    Project Repository: github.com/alexander-demicev/llmserverless


    What This Project Does

    A key feature is hybrid deployment: requests can be routed based on complexity or privacy needs. Simple or low-sensitivity queries can use public APIs (like OpenAI), while complex or private requests are handled in-house on local infrastructure. This flexibility allows balancing cost, privacy, and performance - using cloud for routine tasks and on-premises resources for sensitive or demanding workloads.

    A complete, self-scaling LLM infrastructure that:

    • Scales to zero when idle (no idle costs)
    • Scales up automatically when requests come in
    • Adds more nodes when needed, removes them when demand drops
    • Runs on any infrastructure - laptop, bare metal, or cloud

    Think of it as "serverless for LLMs" - focus on building, the infrastructure handles itself.

    How It Works

    A combination of open source tools working together:

    Flow:

    • Users interact with OpenWebUI (chat interface)
    • Requests go to LiteLLM Gateway
    • LiteLLM routes requests to:
      • Ollama (Knative) for local model inference (auto-scales pods)
      • Or cloud APIs for fallback


    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

    DONE in HackWeek 24:

    DONE in 2025 (out of Hackweek)

    • Support of ClusterClass
    • Add to clusterctl community providers, you can add it directly with clusterctl
    • Testing on newer versions of Harvester v1.4.X and v1.5.X
    • Support for clusterctl generate cluster ...
    • Improve Status Conditions to reflect current state of Infrastructure
    • Improve CI (some bugs for release creation)

    Goals for HackWeek 2025

    • FIRST and FOREMOST, any topic is important to you
    • Add e2e testing
    • Certify the provider for Rancher Turtles
    • Add Machine pool labeling
    • Add PCI-e passthrough capabilities.
    • Other improvement suggestions are welcome!

    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:


    A CLI for Harvester by mohamed.belgaied

    Harvester does not officially come with a CLI tool, the user is supposed to interact with Harvester mostly through the UI. Though it is theoretically possible to use kubectl to interact with Harvester, the manipulation of Kubevirt YAML objects is absolutely not user friendly. 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.

    asciicast

    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
    • Kubevirt API objects (Manipulating VMs and VM Configuration in Kubernetes using Kubevirt)


    The Agentic Rancher Experiment: Do Androids Dream of Electric Cattle? by moio

    Rancher is a beast of a codebase. Let's investigate if the new 2025 generation of GitHub Autonomous Coding Agents and Copilot Workspaces can actually tame it. A GitHub robot mascot trying to lasso a blue bull with a Kubernetes logo tatooed on it


    The Plan

    Create a sandbox GitHub Organization, clone in key Rancher repositories, and let the AI loose to see if it can handle real-world enterprise OSS maintenance - or if it just hallucinates new breeds of Kubernetes resources!

    Specifically, throw "Agentic Coders" some typical tasks in a complex, long-lived open-source project, such as:


    The Grunt Work: generate missing GoDocs, unit tests, and refactorings. Rebase PRs.

    The Complex Stuff: fix actual (historical) bugs and feature requests to see if they can traverse the complexity without (too much) human hand-holding.

    Hunting Down Gaps: find areas lacking in docs, areas of improvement in code, dependency bumps, and so on.


    If time allows, also experiment with Model Context Protocol (MCP) to give agents context on our specific build pipelines and CI/CD logs.

    Why?

    We know AI can write "Hello World." and also moderately complex programs from a green field. But can it rebase a 3-month-old PR with conflicts in rancher/rancher? I want to find the breaking point of current AI agents to determine if and how they can help us to reduce our technical debt, work faster and better. At the same time, find out about pitfalls and shortcomings.

    The CONCLUSION!!!

    A add-emoji State of the Union add-emoji document was compiled to summarize lessons learned this week. For more gory details, just read on the diary below! add-emoji


    openSUSE on ZoL from OpenZFS project by jkohoutek

    Idea is to have SUSE system with OpenZFS as root FS.

    Why ZFS

    Ways in which ZFS is better than BTRFS

    Main goal

    Have OpenZFS as install option in the installer and utilize zedenv Boot Environment Manager for SUSE updates install

    Goals

    • synergy of ZFS with dracut, so snapshots are correctly added to the grub
    • synergy of zedenv with zypper
      • before every update snapshot is created
      • when new kernel or other package which requires reboot is about to be installed, the update will be processed to the new boot environment snapshot and grub configuration changed to boot to this new one
    • integrate Root on ZFS as install option to the YaST
    • configure Kiwi for the ZFS install images

    Completed goals

    • prepare ZFS pool compatible with openSUSE installation ✓
    • install openSUSE with root on ZFS ✓
    • boot to the prepared and installed system ✓

    Current progress

    Resources:


    GHC-9.14 and split Hadrian from GHC build by osukup

    Description

    Prepare openSUSE Tumbleweed project for new GHC Haskell compiler and separate builder (Hadrian) from GHC build

    Goals

    • have GHC-9.14 project with working compiler and if possible filled with packageset
    • have Hadrian in own package built with bootstrap compiler to separate Hadrian bootstrap from ghc bootstrap

    Resources

    devel:languages:haskell

    d:l:h:ghc-9.12.x

    opensuse Haskell rpm macros

    opensuse haskell package gen project


    Port the classic browser game HackTheNet to PHP 8 by dgedon

    Description

    The classic browser game HackTheNet from 2004 still runs on PHP 4/5 and MySQL 5 and needs a port to PHP 8 and e.g. MariaDB.

    Goals

    • Port the game to PHP 8 and MariaDB 11
    • Create a container where the game server can simply be started/stopped

    Resources

    • https://github.com/nodeg/hackthenet


    Rewrite Distrobox in go (POC) by fabriziosestito

    Description

    Rewriting Distrobox in Go.

    Main benefits:

    • Easier to maintain and to test
    • Adapter pattern for different container backends (LXC, systemd-nspawn, etc.)

    Goals

    • Build a minimal starting point with core commands
    • Keep the CLI interface compatible: existing users shouldn't notice any difference
    • Use a clean Go architecture with adapters for different container backends
    • Keep dependencies minimal and binary size small
    • Benchmark against the original shell script

    Resources

    • Upstream project: https://github.com/89luca89/distrobox/
    • Distrobox site: https://distrobox.it/
    • ArchWiki: https://wiki.archlinux.org/title/Distrobox


    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.


    Help Create A Chat Control Resistant Turnkey Chatmail/Deltachat Relay Stack - Rootless Podman Compose, OpenSUSE BCI, Hardened, & SELinux by 3nd5h1771fy

    Description

    The Mission: Decentralized & Sovereign Messaging

    FYI: If you have never heard of "Chatmail", you can visit their site here, but simply put it can be thought of as the underlying protocol/platform decentralized messengers like DeltaChat use for their communications. Do not confuse it with the honeypot looking non-opensource paid for prodect with better seo that directs you to chatmailsecure(dot)com

    In an era of increasing centralized surveillance by unaccountable bad actors (aka BigTech), "Chat Control," and the erosion of digital privacy, the need for sovereign communication infrastructure is critical. Chatmail is a pioneering initiative that bridges the gap between classic email and modern instant messaging, offering metadata-minimized, end-to-end encrypted (E2EE) communication that is interoperable and open.

    However, unless you are a seasoned sysadmin, the current recommended deployment method of a Chatmail relay is rigid, fragile, difficult to properly secure, and effectively takes over the entire host the "relay" is deployed on.

    Why This Matters

    A simple, host agnostic, reproducible deployment lowers the entry cost for anyone wanting to run a privacy‑preserving, decentralized messaging relay. In an era of perpetually resurrected chat‑control legislation threats, EU digital‑sovereignty drives, and many dangers of using big‑tech messaging platforms (Apple iMessage, WhatsApp, FB Messenger, Instagram, SMS, Google Messages, etc...) for any type of communication, providing an easy‑to‑use alternative empowers:

    • Censorship resistance - No single entity controls the relay; operators can spin up new nodes quickly.
    • Surveillance mitigation - End‑to‑end OpenPGP encryption ensures relay operators never see plaintext.
    • Digital sovereignty - Communities can host their own infrastructure under local jurisdiction, aligning with national data‑policy goals.

    By turning the Chatmail relay into a plug‑and‑play container stack, we enable broader adoption, foster a resilient messaging fabric, and give developers, activists, and hobbyists a concrete tool to defend privacy online.

    Goals

    As I indicated earlier, this project aims to drastically simplify the deployment of Chatmail relay. By converting this architecture into a portable, containerized stack using Podman and OpenSUSE base container images, we can allow anyone to deploy their own censorship-resistant, privacy-preserving communications node in minutes.

    Our goal for Hack Week: package every component into containers built on openSUSE/MicroOS base images, initially orchestrated with a single container-compose.yml (podman-compose compatible). The stack will:

    • Run on any host that supports Podman (including optimizations and enhancements for SELinux‑enabled systems).
    • Allow network decoupling by refactoring configurations to move from file-system constrained Unix sockets to internal TCP networking, allowing containers achieve stricter isolation.
    • Utilize Enhanced Security with SELinux by using purpose built utilities such as udica we can quickly generate custom SELinux policies for the container stack, ensuring strict confinement superior to standard/typical Docker deployments.
    • Allow the use of bind or remote mounted volumes for shared data (/var/vmail, DKIM keys, TLS certs, etc.).
    • Replace the local DNS server requirement with a remote DNS‑provider API for DKIM/TXT record publishing.

    By delivering a turnkey, host agnostic, reproducible deployment, we lower the barrier for individuals and small communities to launch their own chatmail relays, fostering a decentralized, censorship‑resistant messaging ecosystem that can serve DeltaChat users and/or future services adopting this protocol

    Resources