😨 How do you design an API that survives 1 million request per second #interview

Description

1 Million RPS isn’t about code, it’s about architecture. Here are the 8 key layers to scale your API 🚀 ⸻ 1️⃣ Load Balancer 👉 Distributes traffic across multiple servers so no single machine melts. Example: 1M req/s ÷ 200 servers = 5k req/s each ⸻ 2️⃣ Horizontal Scaling 👉 Add more servers when traffic spikes instead of upgrading one big server. Example: Black Friday? Spin up 50+ API nodes in seconds. ⸻ 3️⃣ Stateless APIs 👉 No user data stored in memory → any request can hit any server. Result: Infinite scalability + easy failover. ⸻ 4️⃣ Caching Layer (Redis / CDN) 👉 Serve frequent requests from cache instead of the database. Example: 80% cache hits = 80% fewer DB calls. ⸻ 5️⃣ Database Scaling 👉 Use read replicas, sharding, and proper indexes. Example: Reads → replicas, Writes → primary. ⸻ 6️⃣ Rate Limiting & Throttling 👉 Protect your API from abuse and traffic floods. Example: Max 100 req/min per user. ⸻ 7️⃣ Async Processing 👉 Offload heavy tasks to queues (Kafka / SQS / RabbitMQ). Example: Payment, email, logs → processed in background. ⸻ 8️⃣ Observability & Auto-Healing 👉 Monitor latency, errors, CPU, memory — scale or restart automatically. Example: Crash detected → new pod spins up instantly. ⸻ Architecture scales. Code optimizes. Monitoring saves you. 🔥