Скачать или смотреть FastTrack: Building a Production-Ready Data Ingestion System (Golang, RabbitMQ, MySQL, Docker)

In this video, I walk through a fully production-ready data ingestion pipeline designed using Golang, RabbitMQ, MySQL, and Docker. The system simulates a real-world event-driven architecture that handles streaming payments data with full reliability, duplicate handling, fault tolerance, and operational safety.

Tech Stack:

Golang (project structure follows golang-standards/project-layout)

RabbitMQ for message streaming and queue management

MySQL for durable storage with transactional integrity

Docker & Docker Compose for full local orchestration

Duplicate handling via MySQL error code 1062 detection

Retry logic, graceful shutdown, health checks, and environment-driven config

Key Features:

Publisher/Consumer separation following clean architecture

Duplicate record management with skipped_messages routing

Fully containerized deployment using Docker Compose

Automated setup using Makefile for build/run/test flows

Unit tests for publisher and consumer

End-to-end validation covered by a Minimal Local Test Plan

This solution demonstrates engineering patterns commonly used in modern streaming pipelines, distributed systems, and backend data processing infrastructure.

If you're building data platforms or exploring end-to-end data ingestion architectures, this walkthrough may serve as a hands-on example of how production systems handle real-time ingestion reliably.

GitHub Repo:
https://github.com/prakharsdev/fasttrack