async-processing

mern redis kubernetes docker argocd gitops ci-cd distributed-systems async-processing

Production-grade backend demonstrating asynchronous job processing with BullMQ, Redis, PostgreSQL, and Express. Features background workers, retry mechanisms, dead-letter queues, rate limiting, structured logging, and resilient REST APIs.

Event-driven OpenMusic REST API built with Node.js, PostgreSQL, Redis, and RabbitMQ, featuring JWT authentication, server-side caching, async playlist export, and album cover upload.

Real-time distributed system template featuring Nginx TLS/rate-limiting, JWT auth, RabbitMQ worker queues and PostgreSQL audit tracing. Zero-config, single-command setup

Async backend system for transforming compliance policies into structured checklists with AI, retry logic, and failure safe design

A distributed asynchronous job processing system designed to handle concurrent workloads reliably using Redis queues, worker orchestration, retry mechanisms, dead-letter queues, and failure recovery workflows.

Async Document Processing System with real-time status tracking | Next.js | MongoDB | Tailwind

A beginner-friendly Node.js project demonstrating fast, slow, and asynchronous background job processing using Express, BullMQ, Redis, and Worker Threads. Handle CPU-intensive tasks efficiently ... ❤️

Demonstrates async processing patterns with Node.js. Calculate Fibonacci numbers without freezing - instant feedback, background processing, and smart caching. Applicable to image processing, reports, and any long-running tasks.

Privacy intelligence engine for analyzing web trackers, fingerprinting, cookies, and third-party data flows using scalable crawler pipelines.

An observable, self-healing async job processing pipeline built with Fastify, MongoDB, BullMQ/Redis, and Kubernetes — designed to showcase DevOps practices (observability, autoscaling, CI/CD) on top of a MERN-style backend.

Analytics Service is a high-performance, production-ready website analytics system built using Node.js, Express, Redis, and MongoDB. It is designed to handle high-volume event ingestion with sub-5ms response times, using Redis as an in-memory queue for fast, non-blocking data pipelines.