Create a Kubernetes API client in Rust
an idea by robdaemon
Updated almost 4 years ago. No love. Has no hacker: grab it!

Rust is a systems programming language from Mozilla. It has stronger safety guarantees than Go, and is well suited to working on cloud native infrastructure.

Most Kubernetes development is focused in Go, and it would be great to have something like https://github.com/kubernetes/client-go in Rust.

No Hackers yet

Join this project

Looking for hackers with the skills:

rust kubernetes

This project is part of:

Hack Week 15

Activity

  • almost 9 years ago: robdaemon added keyword "rust" to this project.
  • almost 9 years ago: robdaemon added keyword "kubernetes" to this project.
  • almost 9 years ago: robdaemon originated this project.


    • Comments

    Be the first to comment!

    Similar Projects

    Arcticwolf - A rust based user space NFS server by vcheng

    Description

    Rust has similar performance to C. Also, have a better async IO module and high integration with io_uring. This project aims to develop a user-space NFS server based on Rust.

    Goals

    • Get an understanding of how cargo works
    • Get an understanding of how XDR was generated with xdrgen
    • Create the RUST-based NFS server that supports basic operations like mount/readdir/read/write

    Result (2025 Hackweek)

    • In progress PR: https://github.com/Vicente-Cheng/arcticwolf/pull/1

    Resources

    https://github.com/Vicente-Cheng/arcticwolf

    Mail client with mailing list workflow support in Rust by acervesato

    Description

    To create a mail user interface using Rust programming language, supporting mailing list patches workflow. I know, aerc is already there, but I would like to create something simpler, without integrated protocols. Just a plain user interface that is using some crates to read and create emails which are fetched and sent via external tools.

    I already know Rust, but not the async support, which is needed in this case in order to handle events inside the mail folder and to send notifications.

    Goals

    • simple user interface in the style of aerc, with some vim keybindings for motions and search
    • automatic run of external tools (like mbsync) for checking emails
    • automatic run commands for notifications
    • apply patch set from ML
    • tree-sitter support with styles

    Resources

    • ratatui: user interface (https://ratatui.rs/)
    • notify: folder watcher (https://docs.rs/notify/latest/notify/)
    • mail-parser: parser for emails (https://crates.io/crates/mail-parser)
    • mail-builder: create emails in proper format (https://docs.rs/mail-builder/latest/mail_builder/)
    • gitpatch: ML support (https://crates.io/crates/gitpatch)
    • tree-sitter-rust: support for mail format (https://crates.io/crates/tree-sitter)

    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.

    Learn a bit of embedded programming with Rust in a micro:bit v2 by aplanas

    Description

    micro:bit is a small single board computer with a ARM Cortex-M4 with the FPU extension, with a very constrain amount of memory and a bunch of sensors and leds.

    The board is very well documented, with schematics and code for all the features available, so is an excellent platform for learning embedded programming.

    Rust is a system programming language that can generate ARM code, and has crates (libraries) to access the micro:bit hardware. There is plenty documentation about how to make small programs that will run in the micro:bit.

    Goals

    Start learning about embedded programming in Rust, and maybe make some code to the small KS4036F Robot car from keyestudio.

    Resources

    Diary

    Day 1

    • Start reading https://mb2.implrust.com/abstraction-layers.html
    • Prepare the dev environment (cross compiler, probe-rs)
    • Flash first code in the board (blinky led)
    • Checking differences between BSP and HAL
    • Compile and install a more complex example, with stack protection
    • Reading about the simplicity of xtask, as alias for workspace execution
    • Reading the CPP code of the official micro:bit libraries. They have a font!

    Day 2

    • There are multiple BSP for the microbit. One is using async code for non-blocking operations
    • Download and study a bit the API for microbit-v2, the nRF official crate
    • Take a look of the KS4036F programming, seems that the communication is multiplexed via I2C
    • The motor speed can be selected via PWM (pulse with modulation): power it longer (high frequency), and it will increase the speed
    • Scrolling some text
    • Debug by printing! defmt is a crate that can be used with probe-rs to emit logs
    • Start reading input from the board: buttons
    • The logo can be touched and detected as a floating point value

    Day 3

    • A bit confused how to read the float value from a pin

    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

    Rust book: https://doc.rust-lang.org/book/

    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/

    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

    Self-Scaling LLM Infrastructure Powered by Rancher by ademicev0

    Self-Scaling LLM Infrastructure Powered by Rancher

    logo

    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?

    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

    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

    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:

    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: