🔹 Overview
I helped scale a backend system from a monolithic architecture to microservices for a high-traffic platform serving 100M+ users and 12,000+ QPS, improving performance, reliability, and deployment speed.
🔹 Problem
The system faced major scalability and performance challenges:
- High latency during traffic spikes
- Limited scalability due to monolithic design
- Slow and risky deployments
- Tight coupling between components
🔹 Solution
I redesigned the system with a scalable and performance-focused approach:
- Broke monolith into well-defined microservices
- Introduced API Gateway for better request routing and control
- Implemented event-driven architecture using Kafka
- Added Redis caching to reduce database load and improve response time
- Optimized database queries and indexing
- Containerized services using Docker and deployed on AWS/GCP
🔹 Tech Stack
Node.js, Kafka, Redis, PostgreSQL, Docker, AWS, GCP
🔹 Results
- Scaled system to support 100M+ users
- Handled 12,000+ QPS with 99.9%+ uptime
- Reduced latency by ~40%
- Improved deployment speed significantly
- Reduced production issues (MTTR ↓ ~50%)
- Optimized infrastructure cost