Description
Installing an maintaining ceph as storage solution needs a lot of expertise. Rook in combination with Kubernetes tries to make this more convenient. But this is only true if you are familiar with Kubernetes and its peculiarities. This project tries to create a simple tool which creates a K8s cluster providing Ceph-storage.
Goal for this Hackweek
- Create and provide Storage
- Add and remove nodes from/to the cluster
Resources
- Kubernetes
- Rook
- Ceph
Looking for hackers with the skills:
This project is part of:
Hack Week 20
Activity
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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.
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)
Self-Scaling LLM Infrastructure Powered by Rancher by ademicev0
Self-Scaling LLM Infrastructure Powered by Rancher

Description
The Problem
Running LLMs can get expensive and complex pretty quickly.
Today there are typically two choices:
- Use cloud APIs like OpenAI or Anthropic. Easy to start with, but costs add up at scale.
- 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
Preparing KubeVirtBMC for project transfer to the KubeVirt organization by zchang
Description
KubeVirtBMC is preparing to transfer the project to the KubeVirt organization. One requirement is to enhance the modeling design's security. The current v1alpha1 API (the VirtualMachineBMC CRD) was designed during the proof-of-concept stage. It's immature and inherently insecure due to its cross-namespace object references, exposing security concerns from an RBAC perspective.
The other long-awaited feature is the ability to mount virtual media so that virtual machines can boot from remote ISO images.
Goals
- Deliver the v1beta1 API and its corresponding controller implementation
- Enable the Redfish virtual media mount function for KubeVirt virtual machines
Resources
- The KubeVirtBMC repo: https://github.com/starbops/kubevirtbmc
- The new v1beta1 API: https://github.com/starbops/kubevirtbmc/issues/83
- Redfish virtual media mount: https://github.com/starbops/kubevirtbmc/issues/44
OpenPlatform Self-Service Portal by tmuntan1
Description
In SUSE IT, we developed an internal developer platform for our engineers using SUSE technologies such as RKE2, SUSE Virtualization, and Rancher. While it works well for our existing users, the onboarding process could be better.
To improve our customer experience, I would like to build a self-service portal to make it easy for people to accomplish common actions. To get started, I would have the portal create Jira SD tickets for our customers to have better information in our tickets, but eventually I want to add automation to reduce our workload.
Goals
- Build a frontend website (Angular) that helps customers create Jira SD tickets.
- Build a backend (Rust with Axum) for the backend, which would do all the hard work for the frontend.
Resources (SUSE VPN only)
- development site: https://ui-dev.openplatform.suse.com/login?returnUrl=%2Fopenplatform%2Fforms
- https://gitlab.suse.de/itpe/core/open-platform/op-portal/backend
- https://gitlab.suse.de/itpe/core/open-platform/op-portal/frontend
Exploring Modern AI Trends and Kubernetes-Based AI Infrastructure by jluo
Description
Build a solid understanding of the current landscape of Artificial Intelligence and how modern cloud-native technologies—especially Kubernetes—support AI workloads.
Goals
Use Gemini Learning Mode to guide the exploration, surface relevant concepts, and structure the learning journey:
- Gain insight into the latest AI trends, tools, and architectural concepts.
- Understand how Kubernetes and related cloud-native technologies are used in the AI ecosystem (model training, deployment, orchestration, MLOps).
Resources
Red Hat AI Topic Articles
- https://www.redhat.com/en/topics/ai
Kubeflow Documentation
- https://www.kubeflow.org/docs/
Q4 2025 CNCF Technology Landscape Radar report:
- https://www.cncf.io/announcements/2025/11/11/cncf-and-slashdata-report-finds-leading-ai-tools-gaining-adoption-in-cloud-native-ecosystems/
- https://www.cncf.io/wp-content/uploads/2025/11/cncfreporttechradar_111025a.pdf
Agent-to-Agent (A2A) Protocol
- https://developers.googleblog.com/en/a2a-a-new-era-of-agent-interoperability/
Improve chore and screen time doc generator script `wochenplaner` by gniebler
Description
I wrote a little Python script to generate PDF docs, which can be used to track daily chore completion and screen time usage for several people, with one page per person/week.
I named this script wochenplaner and have been using it for a few months now.
It needs some improvements and adjustments in how the screen time should be tracked and how chores are displayed.
Goals
- Fix chore field separation lines
- Change screen time tracking logic from "global" (week-long) to daily subtraction and weekly addition of remainders (more intuitive than current "weekly time budget method)
- Add logic to fill in chore fields/lines, ideally with pictures, falling back to text.
Resources
tbd (Gitlab repo)
Update M2Crypto by mcepl
There are couple of projects I work on, which need my attention and putting them to shape:
Goal for this Hackweek
- Put M2Crypto into better shape (most issues closed, all pull requests processed)
- More fun to learn jujutsu
- Play more with Gemini, how much it help (or not).
- Perhaps, also (just slightly related), help to fix vis to work with LuaJIT, particularly to make vis-lspc working.
Improvements to osc (especially with regards to the Git workflow) by mcepl
Description
There is plenty of hacking on osc, where we could spent some fun time. I would like to see a solution for https://github.com/openSUSE/osc/issues/2006 (which is sufficiently non-serious, that it could be part of HackWeek project).
Improve/rework household chore tracker `chorazon` by gniebler
Description
I wrote a household chore tracker named chorazon, which is meant to be deployed as a web application in the household's local network.
It features the ability to set up different (so far only weekly) schedules per task and per person, where tasks may span several days.
There are "tokens", which can be collected by users. Tasks can (and usually will) have rewards configured where they yield a certain amount of tokens. The idea is that they can later be redeemed for (surprise) gifts, but this is not implemented yet. (So right now one needs to edit the DB manually to subtract tokens when they're redeemed.)
Days are not rolled over automatically, to allow for task completion control.
We used it in my household for several months, with mixed success. There are many limitations in the system that would warrant a revisit.
It's written using the Pyramid Python framework with URL traversal, ZODB as the data store and Web Components for the frontend.
Goals
- Add admin screens for users, tasks and schedules
- Add models, pages etc. to allow redeeming tokens for gifts/surprises
- …?
Resources
tbd (Gitlab repo)
Song Search with CLAP by gcolangiuli
Description
Contrastive Language-Audio Pretraining (CLAP) is an open-source library that enables the training of a neural network on both Audio and Text descriptions, making it possible to search for Audio using a Text input. Several pre-trained models for song search are already available on huggingface
Goals
Evaluate how CLAP can be used for song searching and determine which types of queries yield the best results by developing a Minimum Viable Product (MVP) in Python. Based on the results of this MVP, future steps could include:
- Music Tagging;
- Free text search;
- Integration with an LLM (for example, with MCP or the OpenAI API) for music suggestions based on your own library.
The code for this project will be entirely written using AI to better explore and demonstrate AI capabilities.
Result
In this MVP we implemented:
- Async Song Analysis with Clap model
- Free Text Search of the songs
- Similar song search based on vector representation
- Containerised version with web interface
We also documented what went well and what can be improved in the use of AI.
You can have a look at the result here:
Future implementation can be related to performance improvement and stability of the analysis.
References
- CLAP: The main model being researched;
- huggingface: Pre-trained models for CLAP;
- Free Music Archive: Creative Commons songs that can be used for testing;
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
terraform-provider-feilong by e_bischoff
Project Description
People need to test operating systems and applications on s390 platform. While this is straightforward with KVM, this is very difficult with z/VM.
IBM Cloud Infrastructure Center (ICIC) harnesses the Feilong API, but you can use Feilong without installing ICIC(see 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 z/VM system.
Goal for Hackweek 23
I would like 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
Modernization, maturity, and maintenance: support for SLES 16 and openTofu, new API calls, fixes...
Resources
Outcome
Updatecli Autodiscovery supporting WASM plugins by olblak
Description
Updatecli is a Golang Update policy engine that allow to write Update policies in YAML manifest. Updatecli already has a plugin ecosystem for common update strategies such as automating Dockerfile or Kubernetes manifest from Git repositories.
This is what we call autodiscovery where Updatecli generate manifest and apply them dynamically based on some context.
Obviously, the Updatecli project doesn't accept plugins specific to an organization.
I saw project using different languages such as python, C#, or JS to generate those manifest.
It would be great to be able to share and reuse those specific plugins
During the HackWeek, I'll hang on the Updatecli matrix channel
https://matrix.to/#/#Updatecli_community:gitter.im
Goals
Implement autodiscovery plugins using WASM. I am planning to experiment with https://github.com/extism/extism
To build a simple WASM autodiscovery plugin and run it from Updatecli
Resources
- https://github.com/extism/extism
- https://github.com/updatecli/updatecli
- https://www.updatecli.io/docs/core/autodiscovery/
- https://matrix.to/#/#Updatecli_community:gitter.im
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.
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)
Play with the userfaultfd(2) system call and download on demand using HTTP Range Requests with Golang by rbranco
Description
The userfaultfd(2) is a cool system call to handle page faults in user-space. This should allow me to list the contents of an ISO or similar archive without downloading the whole thing. The userfaultfd(2) part can also be done in theory with the PROT_NONE mprotect + SIGSEGV trick, for complete Unix portability, though reportedly being slower.
Goals
- Create my own library for userfaultfd(2) in Golang.
- Create my own library for HTTP Range Requests.
- Complete portability with Unix.
- Benchmarks.
- Contribute some tests to LTP.
Resources
- https://docs.kernel.org/admin-guide/mm/userfaultfd.html
- https://www.cons.org/cracauer/cracauer-userfaultfd.html
