Distributed Task Queue System
A high-performance distributed task queue system that can process millions of jobs per day with fault tolerance and horizontal scaling capabilities.
Completed
2023
Category
Backend Infrastructure
Team Size
4 developers
Project Overview
This Backend Infrastructure project was designed to solve complex challenges in scalability and performance. The system architecture was carefully planned to handle high traffic loads while maintaining responsiveness and data integrity.
One of the key technical challenges was implementing an efficient caching strategy that would reduce database load while ensuring data consistency. We solved this by using a multi-layered caching approach with Redis for hot data and implemented cache invalidation patterns.
The project was deployed using a containerized approach with Docker and Kubernetes, allowing for seamless scaling and deployment across multiple environments. Continuous integration and deployment pipelines were set up to ensure code quality and rapid iteration.
Key Features
Horizontal Scaling
Dynamically scales worker nodes based on queue size and processing demands.
Priority Queues
Supports multiple priority levels to ensure critical tasks are processed first.
Failure Recovery
Implements dead-letter queues and automatic retry mechanisms for failed tasks.
Real-time Monitoring
Provides dashboards and metrics for queue health, processing rates, and error tracking.
Technical Details
Primary Language
Node.js
Database
Redis
Architecture
Microservices
Deployment
Kubernetes
Testing
Jest, Supertest
CI/CD
GitHub Actions