High-frequency trading (HFT) is a domain where performance, precision, and reliability are paramount. In this first phase of our journey, we lay the groundwork not only for the codebase but for our mental model of trading systems themselves. This article covers the goals, knowledge areas, tools, and design patterns we’ll be using throughout the project.

Goals of Phase 1

Phase 1 sets the direction for everything we’ll build later. The goals are:

• Understand the architecture of an HFT system
• Select the right tools and libraries in the Rust ecosystem
• Establish a project structure and define interfaces
• Design a minimal but scalable first component: a market data feed parser
• Set up the blog and GitHub repository infrastructure to document the journey

This phase emphasizes clarity, robustness, and code quality, even if the first prototype does very little.

Core concepts we must understand

Before writing a single line of code, we must ensure we understand the following domains well enough to model them correctly:

• Market microstructure: What happens at the order book level? What are ticks, spreads, depth, and latency?
• Matching engines: How do exchanges process and match orders?
• Market data feeds: Differences between Level 1 and Level 2 feeds, formats like ITCH, FIX, and proprietary binary protocols like Binance WebSocket.
• Latency-critical system design: Zero-allocation patterns, CPU affinity, memory layout, interrupt handling.
• Rust system programming features: Ownership, concurrency, memory safety, and async performance.

We’ll dedicate the next articles to these topics before implementing anything.

The Rust tooling stack for HFT

Our choice of tools and dependencies will define both performance and maintainability. Here’s the foundation:

Runtime & Performance

• tokio: for async networking and task coordination
• mio: for low-level event-driven IO
• affinity: for CPU pinning
• perf, flamegraph, dhatu: for performance profiling

Serialization

• bincode, nom: for high-performance binary parsing
• serde: only for internal config serialization (never used on hot paths)

Testing & CI

• criterion: microbenchmarks
• insta: snapshot-based testing
• GitHub Actions with Rust toolchain caching and clippy/lints

Project management

• Rust workspaces with clear crate boundaries: core, marketdata, gateway, etc.

Code design principles

Here are the architectural and code design principles we’ll enforce:

• No unnecessary abstraction: Zero-cost abstractions only
• Composition over inheritance: Favor traits and concrete types
• Data-oriented design: Structure data for CPU cache friendliness
• Controlled unsafe blocks: Only where performance demands it
• Explicit time model: Always use monotonic time, model timestamps precisely
• Observability baked in: Logging, metrics, and tracing enabled early on

We’ll document these patterns with real code in each crate, and they’ll guide how we grow the framework.

Development milestones in Phase 1

Week	Focus	Deliverables
1	Market Microstructure & Architecture	Articles + diagrams
2	Protocol Analysis	Feed spec breakdown (e.g. ITCH, Binance)
3	Project bootstrap	Workspace + logging + config crates
4	Market feed parser prototype	Connect to Binance WebSocket, decode trades
5	Benchmarks & Observability	First metrics, latency logs, flamegraph
6	Public release	Blog post, GitHub repo, Mastodon announcement

By the end of Phase 1, we’ll have a working crate that connects to a real-time feed (e.g. Binance Spot), parses trades or order book events, and logs them with latency and jitter measurements.

Blog infrastructure and GitHub setup

We will document every step of the journey in our blog, hosted at https://rustquant.dev. To keep the project open and collaborative, we will:

• Publish every milestone as a separate article at https://github.com/sh4ka/rustquant
• Use GitHub Issues with milestone labels and template.md for features
• Maintain clear CHANGELOG.md, CONTRIBUTING.md, and CODESTYLE.md
• Create GitHub Action workflows for lints, tests, and CI validation

These practices will set the tone for a high-quality, professional Rust codebase.

What’s next?

In the next milestone article, we’ll begin exploring market microstructure in detail. We’ll analyze how modern exchanges operate, what kinds of orders are supported, and how latency influences execution strategies. Then we’ll link that knowledge to how we might model a feed handler and order book in Rust.