OpenFaaS - Functions as a Service
Get familiar with one of the hottest topics for this year: https://www.openfaas.com/
OpenFaaS (Functions as a Service) is a framework for building serverless functions with Docker which has first class support for metrics. Any process can be packaged as a function enabling you to consume a range of web events without repetitive boiler-plate coding.
Requirements:
- Setup SUSE CaaSP 2.0 (k8s 1.7> is required)
- Install faas-cli
- Install the k8s Package Manager - Helm
- Install faas-netes
Goals:
- Create an openFaaS SUSE Docker image in DockerHub
- Convert some binaries into functions
- Write some functions
- Try to scale those functions
- See how function chaining works
Extra:
- Try to package this project in OBS for Tumbleweed
- Convert if possible some of the internal QA Maintenance tools into Functions running in K8s
- Write blog post about it
- Contribute to upstream
Blog Post: http://panosgeorgiadis.com/blog/2017/11/08/how-to-start-with-openfaas/
This project is part of:
Hack Week 16
Activity
Comments
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about 7 years ago by hennevogel | Reply
Sounds cool are you willing to have a co-hacker? :-)
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about 7 years ago by pgeorgiadis | Reply
That would be AWESOME :D
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about 7 years ago by hennevogel | Reply
Awesome, you're in the Nürnberg office right? :-) Let's meet on Friday!
-
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Description
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Screen shot of home page at the end of Hackweek:
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Project Description
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Github Repo for Harvester CLI: https://github.com/belgaied2/harvester-cli
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What you might learn
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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.
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Resources
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Description
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Goals
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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 byopenQA
people?) - use
LXC
from IBM to start CP commands and analyze the results - use
zPXE
to do some PXE-alike booting (used by theorthos
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 theopenstack
terraform
provider (used byRancher
QA) - use
zvm_ansible
to controlSMAPI
- 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 withcurl
- use
zvmconnector
client python library from Feilong - use
zthin
part of Feilong to directly commandSMAPI
.
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
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
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- 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
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
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Resources
Jenny Static Site Generator by adam.pickering
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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
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- Easy to understand and use
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- Automated releases
Resources
https://github.com/adamkpickering/jenny
WebUI for your data by avicenzi
A single place to view every bit of data you have.
Problem
You have too much data and you are a data hoarder.
- Family photos and videos.
- Lots of eBooks, TV Shows, Movies, and else.
- Boxes full of papers (taxes, invoices, IDs, certificates, exams, and else).
- Bank account statements (multiple currencies, countries, and people).
Maybe you have some data on S3, some on your NAS, and some on your local PC.
- How do you get it all together?
- How do you link a bank transaction to a product invoice?
- How to tag any object type and create a collection out of it (mix videos, photos, PDFs, transactions)?
- How to store this? file/folder structure does not work, everything is linked together
Project Description
The idea is a place where you can throw all your data, photos, videos, documents, binaries, and else.
Create photo albums, document collections, add tags across multiple file-formats, link content, and else.
The UI should be easy to use, where the data is not important for now (could be all S3 or local drive).
Similar proposals
The closest I found so far is https://perkeep.org/, but this is not what I'm looking for.
Goal for this Hackweek
Create a web UI, in Svelte ideally, perhaps React.
It should be able to show photos and videos at least.
Resources
None so far, this is just an idea.
Testing and adding GNU/Linux distributions on Uyuni by juliogonzalezgil
Join the Gitter channel! https://gitter.im/uyuni-project/hackweek
Uyuni is a configuration and infrastructure management tool that saves you time and headaches when you have to manage and update tens, hundreds or even thousands of machines. It also manages configuration, can run audits, build image containers, monitor and much more!
Currently there are a few distributions that are completely untested on Uyuni or SUSE Manager (AFAIK) or just not tested since a long time, and could be interesting knowing how hard would be working with them and, if possible, fix whatever is broken.
For newcomers, the easiest distributions are those based on DEB or RPM packages. Distributions with other package formats are doable, but will require adapting the Python and Java code to be able to sync and analyze such packages (and if salt does not support those packages, it will need changes as well). So if you want a distribution with other packages, make sure you are comfortable handling such changes.
No developer experience? No worries! We had non-developers contributors in the past, and we are ready to help as long as you are willing to learn. If you don't want to code at all, you can also help us preparing the documentation after someone else has the initial code ready, or you could also help with testing :-)
The idea is testing Salt and Salt-ssh clients, but NOT traditional clients, which are deprecated.
To consider that a distribution has basic support, we should cover at least (points 3-6 are to be tested for both salt minions and salt ssh minions):
- Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)
- Onboarding (salt minion from UI, salt minion from bootstrap scritp, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator)
- Package management (install, remove, update...)
- Patching
- Applying any basic salt state (including a formula)
- Salt remote commands
- Bonus point: Java part for product identification, and monitoring enablement
- Bonus point: sumaform enablement (https://github.com/uyuni-project/sumaform)
- Bonus point: Documentation (https://github.com/uyuni-project/uyuni-docs)
- Bonus point: testsuite enablement (https://github.com/uyuni-project/uyuni/tree/master/testsuite)
If something is breaking: we can try to fix it, but the main idea is research how supported it is right now. Beyond that it's up to each project member how much to hack :-)
- If you don't have knowledge about some of the steps: ask the team
- If you still don't know what to do: switch to another distribution and keep testing.
This card is for EVERYONE, not just developers. Seriously! We had people from other teams helping that were not developers, and added support for Debian and new SUSE Linux Enterprise and openSUSE Leap versions :-)
Pending
FUSS
FUSS is a complete GNU/Linux solution (server, client and desktop/standalone) based on Debian for managing an educational network.
https://fuss.bz.it/
Seems to be a Debian 12 derivative, so adding it could be quite easy.
[x]
Reposync (this will require using spacewalk-common-channels and adding channels to the .ini file)[P]
Onboarding (salt minion from UI, salt minion from bootstrap scritp, and salt-ssh minion) (this will probably require adding OS to the bootstrap repository creator) --> Works from UI, need to test the rest.[P]
Package management (install, remove, update...) --> Installing a new package works, needs to test the rest.[ ]
Patching (if patch information is available, could require writing some code to parse it, but IIRC we have support for Ubuntu already)[ ]
Applying any basic salt state (including a formula)[ ]
Salt remote commands[ ]
Bonus point: Java part for product identification, and monitoring enablement
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
Ansible for add-on management by lmanfredi
Description
Machines can contains various combinations of add-ons and are often modified during the time.
The list of repos can change so I would like to create an automation able to reset the status to a given state, based on metadata available for these machines
Goals
Create an Ansible automation able to take care of add-on (repo list) configuration using metadata as reference
Resources
- Machines
- Repositories
- Developing modules
- Basic VM Guest management
- Module
zypper_repository_list
- ansible-collections community.general
Results
Created WIP project Ansible-add-on-openSUSE
Saline (state deployment control and monitoring tool for SUSE Manager/Uyuni) by vizhestkov
Project Description
Saline is an addition for salt used in SUSE Manager/Uyuni aimed to provide better control and visibility for states deploymend in the large scale environments.
In current state the published version can be used only as a Prometheus exporter and missing some of the key features implemented in PoC (not published). Now it can provide metrics related to salt events and state apply process on the minions. But there is no control on this process implemented yet.
Continue with implementation of the missing features and improve the existing implementation:
authentication (need to decide how it should be/or not related to salt auth)
web service providing the control of states deployment
Goal for this Hackweek
Implement missing key features
Implement the tool for state deployment control with CLI
Resources
https://github.com/openSUSE/saline
Run local LLMs with Ollama and explore possible integrations with Uyuni by PSuarezHernandez
Description
Using Ollama you can easily run different LLM models in your local computer. This project is about exploring Ollama, testing different LLMs and try to fine tune them. Also, explore potential ways of integration with Uyuni.
Goals
- Explore Ollama
- Test different models
- Fine tuning
- Explore possible integration in Uyuni
Resources
- https://ollama.com/
- https://huggingface.co/
- https://apeatling.com/articles/part-2-building-your-training-data-for-fine-tuning/
Save pytorch models in OCI registries by jguilhermevanz
Description
A prerequisite for running applications in a cloud environment is the presence of a container registry. Another common scenario is users performing machine learning workloads in such environments. However, these types of workloads require dedicated infrastructure to run properly. We can leverage these two facts to help users save resources by storing their machine learning models in OCI registries, similar to how we handle some WebAssembly modules. This approach will save users the resources typically required for a machine learning model repository for the applications they need to run.
Goals
Allow PyTorch users to save and load machine learning models in OCI registries.
Resources
Mortgage Plan Analyzer by RMestre
https://github.com/rjpmestre/mortgage-plan-analyzer
Project Description
Many people face challenges when trying to renegotiate their mortgages with different banks. They receive offers from multiple lenders and struggle to compare them effectively. Each proposal may have slightly different terms and data presentation, making it hard to make informed decisions. Additionally, understanding the impact of various taxes and variables can be complex. The Mortgage Plan Analyzer project aims to address these issues.
Project Overview:
The Mortgage Plan Analyzer is a web-based tool built using PHP, Laravel, Livewire, and AdminLTE/bootstrap. It provides a user-friendly platform for individuals to input basic specifications about their mortgage, adjust taxes and variables, and obtain short-term projections for each proposal. Users can also compare multiple mortgage offers side by side, enabling them to make informed decisions about their mortgage renegotiation.
Why Start This Project:
I found myself in this position and most tools I found around are either for marketing/selling purposes or not flexible enough. As i was starting getting lost in a jungle of spreadsheets i thought I could just create a tool to help me and others that may be experiencing the same struggles to provide clarity and transparency in the decision-making process.
Hackweek 25 ideas (to refine still :) )
- Euribor Trends in Projections
- - Use historical Euribor data to model optimistic and pessimistic scenarios for variable-rate loans.
- Use the annual summaries (installments, amortizations, etc) and run some analysis to highlight key differences, like short-term savings vs. long-term costs
- Financial plan can be hard/boring to follow. Create a simple viewing mode that summarizes monthly values and their annual sums.
Hackweek 24 update
- Improved summaries graphs by adding:
- - Line graph;
- - Accumulated line graph;
- - Set the range to short/mid/long term;
- - Highlight best simulation and value per year;
- Improve the general behaviour of the forms:
- - Simulations name setting;
- - Cloning simulations;
- - Adjust update timing on input changes;
- Show/Hide big tables;
- Support multi languages (added english);
- Added examples;
- Adjustments to fonts and sizes;
- Fixed loading screen;
- Dependencies adjustments;
Hackweek 23 initial release
- Developed a base site that:
- - Allows adding up to 3 simulations;
- - Create financial plans;
- - Simulations comparison graph for the first 4 years;
- Created Github project @ https://github.com/rjpmestre/mortgage-plan-analyzer ;
- Launched a demo instance using Oracle Cloud Free Tier currently @ http://138.3.251.182/
Resources
- Banco de Portugal: Main simulator all portuguese banks have to follow ( https://clientebancario.bportugal.pt/credito-habitacao )
- Laravel: A PHP web application framework for building robust and scalable applications. ( https://laravel.com/ )
- Livewire: A Laravel library for building dynamic interfaces without writing JavaScript. ( https://livewire.laravel.com/ )
- AdminLTE: A responsive admin dashboard template for creating a visually appealing interface. ( https://adminlte.io/ )