moq-rs: The Rust Implementation Leading MOQ Development

What is moq-rs?

moq-rs is an open-source Rust implementation of the MOQ Transport protocol, created and maintained by Luke Curley, a software engineer at Twitch. It has become one of the most actively developed MOQ implementations and serves as a de facto reference for the protocol.

Key Features

Full Protocol Support

moq-rs implements the core moq-transport protocol including:

• Publishing and subscribing to tracks
• Relay functionality with fan-out
• WebTransport support for browser-based clients
• Catalog handling for track discovery

Relay Server

The project includes a fully functional relay server (moq-relay) that can:

• Accept connections from publishers and subscribers
• Fan out media to multiple subscribers
• Handle subscription filtering (latest group, specific ranges)
• Cascade to other relays

CLI Tools

moq-rs ships with command-line tools for testing:

• moq-pub: Publish media from a file or pipe
• moq-sub: Subscribe and output media to a file or pipe
• Integration with FFmpeg for encoding/decoding

Architecture

The codebase is well-structured into several Rust crates:

moq-rs/
├── moq-transport/  # Core protocol implementation
├── moq-relay/      # Relay server
├── moq-pub/        # Publishing CLI
├── moq-sub/        # Subscribing CLI
├── moq-web/        # Browser demo (WebTransport)
└── moq-api/        # Control plane API

Getting Started

# Clone the repository
git clone https://github.com/kixelated/moq-rs
cd moq-rs

# Run the relay
cargo run --bin moq-relay

# In another terminal, publish a video
ffmpeg -i input.mp4 -f mp4 - | cargo run --bin moq-pub

Impact on the Standard

moq-rs has played a crucial role in validating protocol design decisions. Issues discovered during implementation have directly influenced revisions to the moq-transport draft. This tight feedback loop between specification and implementation is one of the strengths of the MOQ standardization process.

What's Next

The project continues to evolve alongside the draft. Current focus areas include improving relay-to-relay cascading, optimizing memory usage for high-throughput scenarios, and enhancing the web demo for browser-based testing.