Project Description
As per discussions in the SOAFEE SIG that SUSE is a founding member of, container users will be in need of running workloads with mixed criticality.
Maybe the easiest starting point will be allowing to assign containerized processes real-time priorities.
During last Hack Week, code review had confirmed no process priorities were being set in runc, but work towards experimental code changes got interrupted.
Goal for this Hackweek
Goal is to create a proof of concept where initially a hardcoded process priority gets assigned to a container (which would confirm we found the right place and have the needed capability permissions). This includes figuring out a development set-up for these container components. SUCCESS! Nice values such as -5 (range -20 to 19) could be assigned to a Tumbleweed container executed via podman on Tumbleweed x86_64, using a modified locally built and installed (PREFIX=/usr) runc binary in the initProcess code path.
Next step would be to alternatively assign a real-time process priority (different syscall and number range). SUCCESS! Among others, FIFO scheduler with real-time priority 42 (range 1 to 99) could be assigned to the Tumbleweed container's bash process.
A further step would be figuring out how to pass such meta information from container manifest through orchestrator to the runtime components, so that the priority does not need to be hardcoded and can be applied to one specific container only.
Out of scope will likely be investigating alternative container components, such as crun in place of runc.
It is understood real-time process priorities can be investigated on regular current Tumbleweed or SLE kernels, without requiring a SLERT kernel with PREEMPT_RT patchset specifically (although that would still be the deployment use case).
Resources
SUSE Labs Conference 2022 paper "SOAFEE: The quest for mixed criticality" by A. Färber, sections "Operating system and real-time" and "Kubernetes and real-time".
Looking for hackers with the skills:
This project is part of:
Hack Week 22 Hack Week 21
Activity
Comments
-
almost 2 years ago by afaerber | Reply
Results presented in SOAFEE MCO tiger team: 20230214_SUSE_Hackweek_real-time.pdf
Code is pushed to GitHub now: https://github.com/afaerber/runc/commits/hackweek22
Similar Projects
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
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.
Multi-pod, autoscalable Elixir application in Kubernetes using K8s resources by socon
Description
Elixir / Erlang use their own solutions to create clusters that work together. Kubernetes provide its own orchestration. Due to the nature of the BEAM, it looks a very promising technology for applications that run in Kubernetes and requite to be always on, specifically if they are created as web pages using Phoenix.
Goals
- Investigate and provide solutions that work in Phoenix LiveView using Kubernetes resources, so a multi-pod application can be used
- Provide an end to end example that creates and deploy a container from source code.
Resources
https://github.com/dwyl/phoenix-liveview-counter-tutorial https://github.com/propedeutica/elixir-k8s-counter
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
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
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).
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
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.
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
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
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
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:
Resources
Python:
Go:
Rust:
Misc:
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
Jenny Static Site Generator by adam.pickering
Description
For my personal site I have been using hugo. It works, but I am not satisfied: every time I want to make a change (which is infrequently) I have to read through the documentation again to understand how hugo works. I don't find the documentation easy to use, and the structure of the repository that hugo requires is unintuitive/more complex than what I need. So, I have decided to write my own simple static site generator in Go. It is named Jenny, after my wife.
Goals
- Pages can be written in markdown (which is automatically converted to HTML), but other file types are also allowed
- Easy to understand and use
- Intuitive, simple design
- Clear documentation
- Hot reloading
- Binaries provided for download
- Future maintenance is easy
- Automated releases
Resources
https://github.com/adamkpickering/jenny
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
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