k10s: GPU-Aware Kubernetes Toolkit

k10s is two things:

• kitty - a Daemonset that lives on your kubernetes cluster that collects node-level GPU + Network diagnostics
• k10s - (kittens) a TUI that shows the ML training jobs in your cluster and surfaces ranks that are misbehaving.

The outcomes will be:

1. Your idle / misbehaving GPUs are LOUD so you know if you are burning $$
2. You know exactly WHY your training job is messed up (stragger ranks, oom issues, network chokes etc)
3. You don't have to leave your terminal

These are problems that I have and thats the main reason to build this. If you also have these problems join our discord and consider becoming a contributor and shape this tool:

Other separate motivations for building k10s on the dev log: why build k10s?

Project Structure

src/crates/
├── kitty/    # daemonset agent
├── tui/      # tui duh
└── e2e/      # End-to-end tests

Quick Start

cargo build                          # Build all crates
cargo run -p kitty                   # Run the agent
cargo run -p tui                     # Run the TUI
cargo run -p e2e                     # Run e2e tests
cargo build --release                # Optimized release build

License

Apache 2.0. See LICENSE for details.

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What happened to the Go version?

There was a vibe-coded go-version of the TUI. Still available for use here: https://github.com/shvbsle/k10s/tree/archive/go-v0.4.0

It became unmaintainable so I've archived that branch and decided to hand-write this TUI again from scratch in Rust. I speak more about it here: Blog: I'm going back to writing code by hand