Description
Firecracker is an open-source virtualization technology that is purpose-built for creating and managing secure, multi-tenant container and function-based services.
Integrating Firecracker with a CF container runtime will bring security to the underlying Kubernetes cluster and to other apps when using the Cloud Application Platform.
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This project is part of:
Hack Week 19
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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
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
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
Remote control for Adam Audio active monitor speakers by dmach
Description
I own a pair of Adam Audio A7V active studio monitor speakers. They have ethernet connectors that allow changing their settings remotely using the A Control software. From Windows :-( I couldn't find any open source alternative for Linux besides AES70.js library.
Goals
- Create a command-line tool for controlling the speakers.
- Python is the language of choice.
- Implement only a simple tool with the desired functionality rather than a full coverage of AES70 standard.
TODO
- ✅ discover the device
- ❌ get device manufacturer and model
- ✅ get serial number
- ✅ get description
- ✅ set description
- ✅ set mute
- ✅ set sleep
- ✅ set input (XRL (balanced), RCA (unbalanced))
- ✅ set room adaptation
- bass (1, 0, -1, -2)
- desk (0, -1, -2)
- presence (1, 0, -1)
- treble (1, 0, -1)
- ✅ set voicing (Pure, UNR, Ext)
- ❌ the Ext voicing enables the following extended functionality:
- gain
- equalizer bands
- on/off
- type
- freq
- q
- gain
- ❌ udev rules to sleep/wakeup the speakers together with the sound card
Resources
- https://www.adam-audio.com/en/a-series/a7v/
- https://www.adam-audio.com/en/technology/a-control-remote-software/
- https://github.com/DeutscheSoft/AES70.js
- https://www.aes.org/publications/standards/search.cfm?docID=101 - paid
- https://www.aes.org/standards/webinars/AESStandardsWebinarSC0212L20220531.pdf
- https://ocaalliance.github.io/downloads/AES143%20Network%20track%20NA10%20-%20AES70%20Controller.pdf
Result
- The code is available on GitHub: https://github.com/dmach/pacontrol
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
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
Extending KubeVirtBMC's capability by adding Redfish support by zchang
Description
In Hack Week 23, we delivered a project called KubeBMC (renamed to KubeVirtBMC now), which brings the good old-fashioned IPMI ways to manage virtual machines running on KubeVirt-powered clusters. This opens the possibility of integrating existing bare-metal provisioning solutions like Tinkerbell with virtualized environments. We even received an inquiry about transferring the project to the KubeVirt organization. So, a proposal was filed, which was accepted by the KubeVirt community, and the project was renamed after that. We have many tasks on our to-do list. Some of them are administrative tasks; some are feature-related. One of the most requested features is Redfish support.
Goals
Extend the capability of KubeVirtBMC by adding Redfish support. Currently, the virtbmc component only exposes IPMI endpoints. We need to implement another simulator to expose Redfish endpoints, as we did with the IPMI module. We aim at a basic set of functionalities:
- Power management
- Boot device selection
- Virtual media mount (this one is not so basic )
Resources
Contribute to terraform-provider-libvirt by pinvernizzi
Description
The SUSE Manager (SUMA) teams' main tool for infrastructure automation, Sumaform, largely relies on terraform-provider-libvirt. That provider is also widely used by other teams, both inside and outside SUSE.
It would be good to help the maintainers of this project and give back to the community around it, after all the amazing work that has been already done.
If you're interested in any of infrastructure automation, Terraform, virtualization, tooling development, Go (...) it is also a good chance to learn a bit about them all by putting your hands on an interesting, real-use-case and complex project.
Goals
- Get more familiar with Terraform provider development and libvirt bindings in Go
- Solve some issues and/or implement some features
- Get in touch with the community around the project
Resources
- CONTRIBUTING readme
- Go libvirt library in use by the project
- Terraform plugin development
- "Good first issue" list
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
- Create NFS-Ganesha Package on OBS: nfs-ganesha5, nfs-ganesha6
- Create NFS-Ganesha Container Image on OBS: Image
- Create a Kubernetes controller for NFS-Ganesha and support the VFS configuration on demand. Mammuthus
Resources
Extending KubeVirtBMC's capability by adding Redfish support by zchang
Description
In Hack Week 23, we delivered a project called KubeBMC (renamed to KubeVirtBMC now), which brings the good old-fashioned IPMI ways to manage virtual machines running on KubeVirt-powered clusters. This opens the possibility of integrating existing bare-metal provisioning solutions like Tinkerbell with virtualized environments. We even received an inquiry about transferring the project to the KubeVirt organization. So, a proposal was filed, which was accepted by the KubeVirt community, and the project was renamed after that. We have many tasks on our to-do list. Some of them are administrative tasks; some are feature-related. One of the most requested features is Redfish support.
Goals
Extend the capability of KubeVirtBMC by adding Redfish support. Currently, the virtbmc component only exposes IPMI endpoints. We need to implement another simulator to expose Redfish endpoints, as we did with the IPMI module. We aim at a basic set of functionalities:
- Power management
- Boot device selection
- Virtual media mount (this one is not so basic )
Resources
Setup Kanidm as OIDC provider on Kubernetes by jkuzilek
Description
I am planning to upgrade my homelab Kubernetes cluster to the next level and need an OIDC provider for my services, including K8s itself.
Goals
- Successfully configure and deploy Kanidm on homelab cluster
- Integrate with K8s auth
- Integrate with other services (Envoy Gateway, Container Registry, future deployment of Forgejo?)
Resources
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):
./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
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.