High-Frequency Trade Settlement Engine

A high-performance, concurrent backend system simulating a trade settlement engine. This project demonstrates advanced patterns in Distributed Systems, including ACID transactions, worker pools for concurrency, and infrastructure-as-code.

🏗 Architecture

The system mimics a real-world fintech settlement pipeline:

1. Ingestion API (Producer): A Go HTTP server accepts trade orders and persists them to Postgres (PENDING state) with zero latency.
2. Settlement Engine (Consumer): A background worker pool processes trades concurrently, simulating market latency and execution logic.
3. Real-Time Dashboard: Server-Sent Events (SSE) push updates to the UI instantly upon settlement.

Tech Stack

• Language: Go 1.23+ (Chi Router, Pgx Driver)
• Database: PostgreSQL 16 (running in Docker)
• Infrastructure: Docker Compose, Taskfile
• Frontend: Templ + Datastar (planned)

🚀 Quick Start

This project uses Task (go-task) for workflow automation.

Prerequisites

• Go 1.23+
• Docker Desktop
• Task (or use make if preferred)

1. Setup Environment

Copy the example environment file:

cp .env.example .env

2. Start Infrastructure

Spin up the Postgres database in a container. This will automatically apply the schema migrations found in /migrations.

task up

3. Run Application

Start the Go server locally. It connects to the Dockerized database automatically.

task run

You should see:

Connected to database! Starting server on :8080...

4. Developer Commands

We use a Taskfile.yml to standardize commands across the team.

Command	Description
task up	Start the database container (detached)
task down	Stop and remove the database container
task run	Run the Go application (hot-reloads .env)
task db-shell	Open a PSQL CLI session inside the container
task logs	Tail the database logs
task build	Compile the binary to /bin

5. Testing

(Coming soon...)