System Design - Interview

Redis Failure Under Extreme Traffic: How to Prevent a Database Crash When 1 Million Requests Hit at Once

Learn how to design a resilient caching architecture when Redis suddenly goes down and millions of requests fall back to the database. Explore cache stampede, thundering herd, circuit breakers, rate limiting, request coalescing, cache warming, graceful degradation, Redis high availability, TTL strategies, and protecting the database from sudden traffic spikes.

System Design - Interview

Designing a High-Scale Railway Ticket Booking System: Handling 2 Million Users for 500 Seats

Learn how to design a highly scalable railway ticket booking system that can handle 2 million users competing for just 500 seats. Explore traffic spikes, virtual queues, rate limiting, seat inventory management, distributed locking, Redis, database consistency, reservation timeouts, payment processing, idempotency, fault tolerance, and strategies to prevent double booking.

Cybersecurity & API Security

Millions of Requests Hit Your API? DoS vs DDoS vs HTTP Flood Explained

What happens when millions of requests suddenly hit your application? Learn the real difference between DoS, DDoS, and HTTP Flood attacks—and how rate limiting, WAF, CDN, and DDoS protection keep your APIs alive.

System Design - Concepts

Rate Limiting 🚦 — Controlling Excessive Traffic

Rate limiting controls how many requests a client can make within a specific period. It protects APIs from excessive traffic and helps maintain system stability.