How do I handle high traffic in a system design interview?

When interviewers ask “What happens if your system suddenly gets millions of users?” they’re testing whether you can design for scale, not just functionality. The key is to show structured thinking, quantified reasoning, and layered defense against overload.

1️⃣ Start by defining the scale

Always estimate load up front:

“Let’s assume 10 million daily users and 100 K requests per second at peak.”

This anchors your design in data-driven reasoning and shows you understand capacity planning. 🔗 Learn more: Back-of-the-Envelope Sizing in System Design.

2️⃣ Add layers that absorb load

a. Load Balancing

Distribute incoming traffic using an L7 load balancer like Nginx or Envoy.

• Use round-robin or least-connections algorithms.
• Enable auto-scaling and health checks. 🔗 Read: Load Balancer vs Reverse Proxy vs API Gateway.

b. Caching Everywhere

Caching reduces backend hits dramatically:

• Browser/CDN cache → static assets
• Edge cache → regional users
• Service cache → hot database queries 🔗 See: Cache Invalidation Strategies.

c. Database Scaling

• Use read replicas for heavy reads.
• Apply sharding for write distribution. 🔗 Related: Data Replication Strategies.

3️⃣ Use queues to handle bursty traffic

Introduce message queues (Kafka, RabbitMQ, AWS SQS) to smooth out sudden request spikes. Consumers can process jobs steadily without overloading upstream systems. 🔗 Explore: Message Queues and Event-Driven Systems.

4️⃣ Apply rate limiting and graceful degradation

Use token bucket or leaky bucket algorithms to prevent abuse. When systems hit capacity, serve cached responses or show a friendly fallback instead of failing hard. 🔗 Learn: Rate Limiting Explained.

5️⃣ Monitor and autoscale intelligently

Track critical metrics like QPS, latency, and error rates (RED method). Set autoscaling triggers based on CPU load, queue length, or request volume. 🔗 Reference: High Availability System Design Basics.

💡 Interview Insight

Always explain your design evolution:

“I’d start with caching and load balancing. As traffic grows, I’d add asynchronous queues, sharding, and CDNs for global reach.”

That phrasing signals prioritization and scalability awareness — traits senior interviewers look for.

🎓 Learn More

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