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:

• 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

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:

• Cluster infrastructure provider contract
• Machine infrastructure provider contract

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Self-Scaling LLM Infrastructure Powered by Rancher by ademicev0

Self-Scaling LLM Infrastructure Powered by Rancher

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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?

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

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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 Autoscaler scales nodes up/down as needed
• Fleet keeps everything in sync via GitOps

Goals

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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.

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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 Outputs

❥ A "State of the Agentic Union" for SUSE engineers, detailing what works, what explodes, and how much coffee we can drink while the robots do the rebasing.

❥ Honest, Daily Updates With All the Gory Details

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Rancher/k8s Trouble-Maker by tonyhansen

Project Description

When studying for my RHCSA, I found trouble-maker, which is a program that breaks a Linux OS and requires you to fix it. I want to create something similar for Rancher/k8s that can allow for troubleshooting an unknown environment.

Goals for Hackweek 25

• Update to modern Rancher and verify that existing tests still work
• Change testing logic to populate secrets instead of requiring a secondary script
• Add new tests

Goals for Hackweek 24 (Complete)

• Create a basic framework for creating Rancher/k8s cluster lab environments as needed for the Break/Fix
• Create at least 5 modules that can be applied to the cluster and require troubleshooting

Resources

• https://github.com/celidon/rancher-troublemaker
• https://github.com/rancher/terraform-provider-rancher2
• https://github.com/rancher/tf-rancher-up
• https://github.com/rancher/quickstart

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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)

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Exploring Rust's potential: from basics to security by sferracci

Description

This project aims to conduct a focused investigation and practical application of the Rust programming language, with a specific emphasis on its security model. A key component will be identifying and understanding the most common vulnerabilities that can be found in Rust code.

Goals

Achieve a beginner/intermediate level of proficiency in writing Rust code. This will be measured by trying to solve LeetCode problems focusing on common data structures and algorithms. Study Rust vulnerabilities and learning best practices to avoid them.

Resources

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vex8s-controller: a kubernetes controller to automatically generate VEX documents of your running workloads by agreggi

Description

vex8s-controller is an add-on for SBOMscanner project. Its purpose is to automatically generate VEX documents based on the workloads running in a kubernetes cluster. It integrates directly with SBOMscanner by monitoring VulnerabilityReports created for container images and producing corresponding VEX documents that reflect each workload’s SecurityContext.

Here's the workflow explained:

1. sbomscanner scans for images in registry
2. generates a VulnerabilityReport with the image CVEs
3. vex8s-controller triggers when a workload is scheduled on the cluster and generates a VEX document based on the workload SecurityContext configuration
4. the VEX document is provided by vex8s-controller using a VEX Hub repository
5. sbomscanner configure the VEXHub CRD to point to the internal vex8s-controller VEX Hub repository

Goals

The objective is to build a kubernetes controller that uses the vex8s mitigation rules engine to generate VEX documents and serve them through an internal VEX Hub repository within the cluster. SBOMscanner can then be configured to consume VEX data directly from this in-cluster repository managed by vex8s-controller.

Resources

• vex8s
• SBOMscanner

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Looking at Rust if it could be an interesting programming language by jsmeix

Get some basic understanding of Rust security related features from a general point of view.

This Hack Week project is not to learn Rust to become a Rust programmer. This might happen later but it is not the goal of this Hack Week project.

The goal of this Hack Week project is to evaluate if Rust could be an interesting programming language.

An interesting programming language must make it easier to write code that is correct and stays correct when over time others maintain and enhance it than the opposite.

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