Top 20 System Design Interview Questions & Real Architectural Blueprints (FAANG Guide)

1. The 4-Step System Design Interview Framework

System design rounds at FAANG companies are open-ended discussions testing your ability to architect scalable, resilient, and maintainable distributed software under real-world constraints. Follow this proven 4-step framework:

1. Scope & Functional Requirements (5 mins): Clarify features, user volume (DAU/MAU), read/write ratios (e.g. 100:1 read-heavy), latency SLAs (p99 < 50ms), and storage growth over 5 years.
2. High-Level Architecture (10 mins): Draw the client, DNS, CDN, API Gateway, Load Balancer, Microservices, and Databases.
3. Deep-Dive Component Design (20 mins): Detail cache invalidation strategies, database indexing, message queues, and consensus protocols.
4. Bottlenecks & Fault Tolerance (10 mins): Discuss SPOF (Single Point of Failure), replication lag, circuit breakers, and rate limiting.

2. High-Frequency System Design Questions & Solutions

Q1: How would you design a distributed, high-throughput Rate Limiter?

Core Concept: Protect downstream microservices from DDoS and API abuse without introducing high latency.

• Algorithm Choice: Use the Token Bucket or Sliding Window Counter algorithm with Redis.
• Concurrency Handling: Execute atomic operations using Redis Lua scripts (e.g. INCR and EXPIRE) to prevent race conditions across distributed gateway nodes.
• Failure Mode: If Redis is temporarily unreachable, fail-open with local in-memory token buckets to prevent blocking legitimate customer traffic.

Q2: How do you design a real-time Notification System (WebSockets vs Push vs Polling)?

Architectural Blueprint:

• Protocol: Maintain stateful WebSocket connections for active browser/app sessions; fall back to Apple APNs and Firebase FCM for background mobile push.
• Message Broker: Use Apache Kafka with partitioned user ID keys to guarantee strictly ordered delivery across notification consumers.
• User Preferences: Cache user notification opt-out settings in Redis with a 1-hour TTL to prevent querying PostgreSQL on every incoming event.

Q3: How do you handle Database Sharding & Cross-Shard Joins?

Strategy: Use consistent hashing with virtual nodes to distribute user partitions evenly across shard nodes. Avoid cross-shard joins by denormalizing data at write time or routing queries through an application-level scatter-gather query aggregator.

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