🏗️ System Design Guides for FAANG Interviews

In-depth walkthroughs of the most common system design problems asked at Google, Meta, Amazon, Apple, and Microsoft. Each guide covers requirements gathering, capacity estimation, data modeling, scalability trade-offs, and architecture decisions — with answers calibrated from L4 to L8.

• URL Shortener System Design: FAANG Interview Guide (L4–L8)

  URL shortener system design walkthrough: requirements, encoding, caching, data model, scalability. Level-calibrated answers from L4 to L8 at FAANG companies.

• URL Shortener Mock Interview: A 50-Minute L6 System Design Transcript

  A full 50-minute URL shortener system design interview, turn by turn: whiteboard sketches, interviewer annotations, two real mistakes, and an L6/L7 scorecard debrief.

• Rate Limiter System Design: FAANG Interview Guide (L4–L8)

  Design a rate limiter for a system design interview: token bucket vs leaky bucket, sliding window, distributed counters, and Redis Lua scripts — L4–L8.

• Twitter/X Feed System Design: FAANG Interview Guide (L4–L8)

  Design a Twitter/X news feed for your system design interview: fan-out strategies, timeline generation, ranking, caching, and real-time delivery — L4–L8.

• Distributed Cache System Design

  Design a distributed cache (Redis, Memcached): consistent hashing, eviction and TTL, hot keys, cache-aside vs write-through, and what changes when there is no backing store — FAANG L4–L8.

• Distributed Key-Value Store System Design

  Design a durable distributed key-value store (DynamoDB, Cassandra): quorum replication, LSM-trees and compaction, vector clocks and read repair, hinted handoff and anti-entropy — FAANG L4–L8.

• Search Autocomplete System Design: FAANG Interview Guide (L4–L8)

  Design a search autocomplete system: trie vs inverted index, prefix ranking, caching, and typeahead at scale — full FAANG interview guide, L4 to L8 depth.

• Web Crawler System Design: FAANG Interview Guide (L4–L8)

  Design a Web Crawler for your system design interview. Covers BFS frontier, politeness, URL deduplication, and distributed crawl at Google/Bing scale.

• Notification Service System Design: FAANG Interview Guide (L4–L8)

  Design a notification service: push, email, and SMS fan-out at scale. Priority queues, delivery guarantees, rate limiting, multi-channel routing — L4–L8.

• Distributed Message Queue System Design: FAANG Interview Guide (L4–L8)

  Design a distributed message queue like Kafka for FAANG interviews: partitioning, ISR, acks, consumer groups, exactly-once delivery, and tiered storage.

• YouTube System Design: FAANG Interview Guide (L4–L8)

  Design YouTube for FAANG interviews: adaptive bitrate streaming (HLS/DASH), async transcoding pipeline, CDN caching, and scalability — L4 to L8 depth.

• Chat System (WhatsApp) System Design: FAANG Interview Guide (L4–L8)

  Design a chat system like WhatsApp for FAANG interviews: WebSocket architecture, message delivery guarantees, fan-out, and multi-device sync — L4 to L8.

• File Storage System Design (Dropbox / Google Drive): FAANG Interview Guide (L4–L8)

  Design a file storage and sync system (Dropbox, Google Drive) for FAANG interviews: chunking, delta sync, global deduplication, and conflict resolution.

• Collaborative Document Editing (Google Docs) System Design: FAANG Interview Guide (L4–L8)

  Design Google Docs: Operational Transformation vs CRDTs, document ownership leases, operation logs, snapshots, offline merge, and version history — FAANG L4–L8.

• Ticketmaster System Design: FAANG Interview Guide (L4–L8)

  Design a ticket booking and flash-sale system like Ticketmaster: seat-hold contention, optimistic vs pessimistic locking, and waiting rooms — L4–L8.

• Photo-Sharing Feed System Design (Instagram)

  Design a photo-sharing feed like Instagram: image upload pipeline, CDN delivery, social graph at scale, and feed fan-out — FAANG interview guide, L4–L8.

• Proximity Search System Design

  Deceptively simple to describe, surprisingly hard to scale: finding the nearest relevant business in under 200 ms across 200 million listings worldwide.

• Ride-Sharing System Design (Uber / Lyft)

  Design a ride-sharing system like Uber or Lyft: geohashing, quadtrees, WebSocket location tracking, ETA prediction, and surge pricing — FAANG L4 to L8.

• Google Maps System Design

  Design Google Maps: road-graph routing from Dijkstra to contraction hierarchies and CRP, vector tiles, live-traffic ETAs, and GPS map matching — FAANG L4–L8.

• Top-K Leaderboard System Design

  Design a Top-K leaderboard at scale: Redis sorted sets, stream aggregation, and approximate counting with Count-Min Sketch — FAANG L4–L8 interview guide.

• Design a Booking & Reservation System like Airbnb

  Design an Airbnb-style booking and reservation system: double-booking prevention, availability staleness, geo-partitioning, and capacity estimation — L4–L8.

• Design a Payment Processing System

  Design a payment processing system for a system design interview: idempotency, exactly-once semantics, ledger models, and multi-region scaling — L4–L8.

• Online Judge System Design

  Design an online judge like LeetCode or HackerRank: secure sandboxing, execution queues, test-case storage, worker scaling, and fairness — FAANG L4–L8.

• Object Storage (Amazon S3) System Design: FAANG Interview Guide (L4–L8)

  How to design object storage like Amazon S3: erasure coding vs replication, 11-nines durability math, metadata partitioning, and strong consistency.

• Social Post Search System Design: FAANG Interview Guide (L4–L8)

  Design search over a trillion social posts where every result must pass a per-viewer privacy check. Inverted index, visibility filtering, sharding, freshness.