Distributed Job Queue System

This project implements a production-grade distributed job queue system designed for asynchronous report generation. Leveraging a decoupled microservices architecture, it ensures high availability, scalability, and reliability by using Redis as a message broker and AWS S3 for persistent storage.

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Summary

Built a reliable worker-based system for async report generation where throughput and retry safety were more important than synchronous response time.

Challenge

When reports scale in volume, direct synchronous processing creates latency spikes, overload, and brittle retry behavior. The workflow needed durable execution with clear failure isolation.

Solution

I implemented a queue-based architecture with worker processes, Redis-backed messaging, and durable storage for generated artifacts. This allowed the API to remain responsive while reports were processed asynchronously.

Impact

The system became far more resilient under load and easier to scale independently without sacrificing user experience or operational confidence.

What mattered most