How to Crack System Design Interviews at FAANG Companies

Workflow:
Start with seed URLs → workers fetch pages → extract links and content → store data → enqueue new unique URLs.

Trade-offs:
Depth-first vs. breadth-first crawling (risk of traps vs. broad coverage); domain-specific rate limiting for politeness vs. speed.

9. How would you design a mapping service like Google Maps?

Requirements:
Functional: Provide directions, real-time traffic, POI search.
Non-functional: Handle global queries with real-time updates.

Architecture:
Graph-based routing algorithms integrated with live data feeds.

Components:
CDN for map tiles, routing service (A* or Dijkstra), Kafka for traffic ingestion, PostGIS for geospatial database.

Workflow:
User queries location → fetches tiles and computes route → incorporates real-time traffic → provides turn-by-turn guidance.

Trade-offs:
Precomputed routes for common paths vs. fully dynamic calculations (speed vs. accuracy in variable conditions).

10. How would you design a notification system for apps?

Requirements:
Functional: Deliver push, email, SMS notifications; user preferences.
Non-functional: High throughput, reliable delivery.

Architecture:
Event-driven with message queues for decoupling producers and consumers.

Components:
Notification service, Kafka queues, channel integrations (FCM for push, Twilio for SMS), preferences database.

Workflow:
Event triggers notification → enqueues with user prefs → processes and sends via appropriate channel with retry logic.

Trade-offs:
At-least-once delivery vs. fire-and-forget (reliability vs. reduced complexity and duplicates).

11. How would you design a rate limiting system for APIs?

Requirements:
Functional: Enforce call limits, configurable per user/IP.
Non-functional: Low latency, distributed enforcement.

Architecture:
Algorithms like token bucket or sliding window counters for flexible limiting.

Components:
Middleware layer, Redis for distributed counters, rules database for configurations.

Workflow:
Incoming request → checks token availability in Redis → allows or returns 429 error.

Trade-offs:
Fixed window (simple but allows bursts) vs. sliding window (smoother but higher memory usage).

12. How would you design a distributed key-value store?

Requirements:
Functional: Support get/set operations, expirations.
Non-functional: High throughput, persistence across nodes.

Architecture:
Distributed hash table with replication for fault tolerance.

Components:
Cluster nodes using consistent hashing, replication mechanisms, write-ahead logs for durability.

Workflow:
Client hashes key → routes to node → performs read/write with replicas for consistency.

Trade-offs:
Eventual vs. strong consistency (faster operations vs. stricter guarantees).

13. How would you design a file synchronization service like Dropbox?

Requirements:
Functional: Upload and sync files, sharing capabilities.
Non-functional: Secure storage, scalable to petabytes.

Architecture:
Chunk-based uploads with metadata management for efficient syncing.

Components:
Client applications, metadata database, blob storage like S3, delta sync service.

Workflow:
File modified → chunks uploaded → metadata updated → notifies other devices for download.

Trade-offs:
Client-side encryption for privacy vs. server-side features like searchable content.

14. How would you design a news feed system for social media?

Requirements:
Functional: Generate personalized feeds, rank content.
Non-functional: Real-time updates for active users.

Architecture:
Hybrid push (for frequent users) and pull model for efficiency.

Components:
Feed builder service, ML ranking model, caching layer for quick access.

Workflow:
New post created → pushed to select followers → ranked and merged on feed request.

Trade-offs:
Push overload on writes vs. pull latency on reads.

15. How would you design an autocomplete feature for search?

Requirements:
Functional: Suggest terms based on input, rank by relevance.
Non-functional: Respond in under 100ms.

Architecture:
Trie data structure with frequency-based pruning for suggestions.

Components:
Trie builder from logs, search service, edge caching.

Workflow:
User types prefix → traverses trie → returns top-ranked suggestions by popularity.

Trade-offs:
High memory usage for trie vs. query speed; periodic rebuilds for freshness.

Perfect. Here’s the continuation (Questions 16–30) — still in the exact same clean, Google-Docs-ready format and structure, without a single change to your content.

16. How would you design a peer-to-peer file sharing system like BitTorrent?

Requirements:
Functional: Distribute files via peers, track progress.
Non-functional: Decentralized, resilient to failures.

Architecture:
Tracker-based with DHT for peer discovery.

Components:
Central tracker server, peer clients, distributed hash tables.

Workflow:
Torrent file parsed → connects to peers via tracker/DHT → downloads file pieces in parallel.

Trade-offs:
Centralized tracker for simplicity vs. fully decentralized DHT (avoids single point of failure).

17. How would you design a product recommendation system?

Requirements:
Functional: Suggest items based on user behavior.
Non-functional: Real-time personalization.

Architecture:
ML models combining collaborative and content-based filtering.

Components:
User data store, model training pipeline, online serving layer.

Workflow:
User interacts → updates profile → model infers and serves recommendations.

Trade-offs:
Offline batch processing for accuracy vs. online updates for recency.

18. How would you design a parking lot management system?

Requirements:
Functional: Assign spots, handle payments, track availability.
Non-functional: Real-time status updates.

Architecture:
Object-oriented design with sensor integration for automation.

Components:
Entry/exit gates, spot database, payment processor.

Workflow:
Vehicle enters → assigns available spot → monitors time → processes payment on exit.

Trade-offs:
Fixed spot allocation vs. dynamic optimization (simplicity vs. efficiency).

19. How would you design a vending machine software?

Requirements:
Functional: Product selection, payment, dispensing.
Non-functional: Manage inventory accurately.

Architecture:
Finite state machine for handling user interactions.

Components:
Inventory mapping, payment validator, product dispenser.

Workflow:
Insert payment → select item → verify stock and funds → dispense and update inventory.

Trade-offs:
Support cash vs. digital payments (convenience vs. security risks).

20. How would you design a ticket booking system like Ticketmaster?

Requirements:
Functional: Search events, select seats, book tickets.
Non-functional: Handle high-concurrency sales.

Architecture:
Optimistic/pessimistic locking for seat reservations.

Components:
Event inventory database, booking service, queuing for peak loads.

Workflow:
User searches event → locks seats temporarily → completes payment → confirms booking.

Trade-offs:
Optimistic locking for higher concurrency vs. pessimistic to avoid conflicts.

21. How would you design a distributed caching system?

Requirements:
Functional: Store/retrieve data with eviction policies.
Non-functional: Consistent across clusters.

Architecture:
Hash-based partitioning like Memcached.

Components:
Cache nodes, client-side hashing library.

Workflow:
Key hashed to node → store or retrieve data → handle evictions (e.g., LRU).

Trade-offs:
Invalidation broadcasts vs. direct updates (consistency vs. network overhead).

22. How would you design a job scheduling system?

Requirements:
Functional: Schedule tasks, support retries/cron.
Non-functional: Distributed execution.

Architecture:
Leader election for coordination in a cluster.

Components:
Job queue, worker pools, persistent database for state.

Workflow:
Submit job with schedule → enqueued → workers execute at due time with retries.

Trade-offs:
At-most-once vs. at-least-once execution semantics (idempotency requirements).

23. How would you design a metrics logging and monitoring system?

Requirements:
Functional: Collect and aggregate metrics.
Non-functional: High ingestion rates.

Architecture:
Time-series optimized storage with aggregation layers.

Components:
Agent collectors, Prometheus for scraping, InfluxDB for storage.

Workflow:
Metrics emitted → aggregated in buffers → stored and queried for dashboards.

Trade-offs:
Push model from agents vs. pull scraping (control vs. scalability).

24. How would you design a stream processing system like Kafka?

Requirements:
Functional: Pub-sub messaging, durable storage.
Non-functional: Fault-tolerant partitioning.

Architecture:
Topic-based partitions with broker replication.

Components:
Broker nodes, ZooKeeper for metadata, consumer/producer clients.

Workflow:
Producer publishes to topic → broker stores and replicates → consumer pulls from partitions.

Trade-offs:
Higher replication factors for durability vs. increased storage usage.

25. How would you design a hotel booking platform?

Requirements:
Functional: Search rooms, make bookings.
Non-functional: Handle concurrent reservations.

Architecture:
Transactional database with locking for inventory.

Components:
Room inventory service, payment integration.

Workflow:
User searches dates → checks availability → locks room → processes booking and payment.

Trade-offs:
Strict overbooking prevention vs. performance under load.

26. How would you design an A/B testing framework?

Requirements:
Functional: Assign users to variants, track metrics.
Non-functional: Compute statistical significance.

Architecture:
User bucketing with random assignment.

Components:
Experiment config service, analytics pipeline.

Workflow:
User request → assigns to variant → logs interactions → analyzes results.

Trade-offs:
Larger sample sizes for accuracy vs. longer test durations.

27. How would you design a stock price alert system?

Requirements:
Functional: Set price thresholds, send alerts.
Non-functional: Real-time monitoring.

Architecture:
Event-driven with market data feeds.

Components:
Price streaming feed, alert database, notification sender.

Workflow:
User sets alert → system monitors feed → triggers notification on match.

Trade-offs:
Polling feeds vs. streaming subscriptions (latency vs. resource use).

28. How would you design a weather forecasting app?

Requirements:
Functional: Provide forecasts, location-based alerts.
Non-functional: Accurate and timely data.

Architecture:
Integration with external weather APIs and caching.

Components:
Geolocation service, API wrappers, local cache.

Workflow:
Get user location → query API → cache and display forecast with alerts.

Trade-offs:
Cached data for speed vs. frequent refreshes for accuracy.

29. How would you design a collaborative editing tool like Google Docs?

Requirements:
Functional: Real-time editing, version history.
Non-functional: Resolve conflicts seamlessly.

Architecture:
Operational transformation (OT) or CRDT for merging edits.

Components:
Document server, WebSocket for live updates, storage backend.

Workflow:
User edits → sends deltas → server merges and broadcasts to collaborators.

Trade-offs:
OT for simplicity vs. CRDT for better offline support.

30. How would you design a live commenting feature for events?

Requirements:
Functional: Post and view comments in real-time.
Non-functional: Scale for large audiences.

Architecture:
Pub-sub model for broadcasting comments.

Components:
Comment ingestion service, message queue, WebSocket frontend.

Workflow:
User posts comment → publishes to queue → subscribers receive updates.

Trade-offs:
Immediate posting vs. moderation delays for content quality.

Tips for the Interview Day

Stay calm and collaborative—treat it as a discussion. Think aloud, draw boxes/arrows for clarity. If stuck, say, “Let me think about that.” Handle changes gracefully, like “If we add video, I’d integrate a media service with CDNs.” End with a summary and questions.

Conclusion: Your Path to FAANG Success

Cracking system design at FAANG requires practice, but with the right approach, it’s achievable. Focus on fundamentals, mock often, and remember: interviewers want to see how you think. Ready to dive deeper? Enroll in our courses today and take the next step toward your dream job.

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