Prepare for your next system design interview with this comprehensive guide. These 30 questions progress from basic concepts to advanced scenarios, helping freshers, 1-3 year experienced professionals, and 3-6 year veterans master scalable system architecture.
Basic System Design Questions (1-10)
1. What is System Design and why is it important?
System Design is the process of defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements. It ensures scalability, reliability, and maintainability for real-world applications[1][3].
2. Explain the difference between High-Level Design (HLD) and Low-Level Design (LLD).
HLD provides an overview of system architecture, components, and data flow. LLD details class diagrams, methods, data structures, and interactions between components[3].
3. What are Functional and Non-Functional Requirements in system design?
Functional requirements define what the system should do (features like user registration). Non-functional requirements specify how the system performs (scalability, latency, availability)[4][5].
4. What is the CAP Theorem?
CAP Theorem states that a distributed system can provide at most two of three guarantees: Consistency (all nodes see same data), Availability (every request gets response), Partition tolerance (system continues during network failures)[1][3].
5. Differentiate between Horizontal and Vertical Scaling.
Vertical scaling adds more resources to existing servers (more CPU/RAM). Horizontal scaling adds more servers and distributes load across them, better for high traffic[3].
6. What is a Load Balancer and its role in system design?
A Load Balancer distributes incoming traffic across multiple servers to ensure no single server is overwhelmed, improving availability and scalability[1].
7. Explain Monolithic vs Microservices architecture.
Monolithic: Single deployable unit with all components tightly coupled. Microservices: Independent, loosely coupled services that communicate via APIs, enabling independent scaling[3].
8. What is Caching and when should you use it?
Caching stores frequently accessed data in fast storage (like Redis/Memcached) to reduce database load and improve response times for read-heavy operations[1][3].
9. What is Database Sharding?
Sharding divides a large database into smaller, distributed partitions (shards) across multiple servers based on a shard key, enabling horizontal scaling[1][3].
10. Difference between SQL and NoSQL databases?
SQL databases (MySQL, PostgreSQL) use structured schemas with ACID transactions. NoSQL (Cassandra, DynamoDB) handle unstructured data with eventual consistency for high scalability[1].
Intermediate System Design Questions (11-20)
11. How do you approach a system design interview question?
1. Clarify requirements (functional/non-functional)
2. Define scope and assumptions
3. High-level design with components
4. Deep dive into critical components
5. Discuss trade-offs and scaling[2][4][5].
12. What is an API Gateway?
API Gateway acts as a single entry point for clients, handling authentication, rate limiting, request routing, and aggregating responses from multiple microservices[3].
13. Explain Read Path vs Write Path in system design.
Read Path: Client → Load Balancer → Cache → App Servers → Database. Write Path: Client → Load Balancer → App Servers → Database → Cache invalidation[1].
14. What is Database Replication and its types?
Replication creates database copies for redundancy and read scaling. Master-Slave: Master handles writes, slaves handle reads. Master-Master: Both handle reads/writes[1].
15. Design a URL Shortening Service like Bitly (High-level).
Components: Load Balancer → App Servers → Redis (for counter) → MySQL (URL mappings). Use base62 encoding for short codes. Handle collisions with unique ID generation[6].
16. How does Consistent Hashing work for load distribution?
Consistent Hashing maps data and nodes to a hash ring. When nodes are added/removed, only a subset of keys need remapping, minimizing data movement[3].
17. What is Rate Limiting and common algorithms?
Rate Limiting controls request frequency per user/IP. Algorithms: Token Bucket (fixed tokens/sec), Leaky Bucket (constant rate), Fixed Window Counter[3].
18. Explain the role of Message Queues in system design.
Message Queues (RabbitMQ, Kafka) decouple services, handle async processing, provide reliability through retries, and enable load smoothing[1].
19. How would you design file storage like Dropbox (Paytm scenario)?
For Paytm’s file sharing: Clients → Load Balancer → App Servers → CDN (static files) → Object Storage (S3-like) → Metadata DB (MySQL). Use chunked uploads for large files[1][5].
20. What are Circuit Breakers in distributed systems?
Circuit Breakers prevent cascading failures by stopping requests to failing services. States: Closed (normal), Open (fail fast), Half-Open (test recovery)[3].
Advanced System Design Questions (21-30)
21. Design a Messaging System like WhatsApp (Zoho scenario).
Components: Load Balancer → WebSocket servers → NoSQL DB (Cassandra) → Message Queue → Push Notification Service. Use pub/sub for real-time delivery[1].
22. How do you handle Database Schema Evolution in production?
Strategies: Backward/forward compatible changes, feature flags, dual writes (old+new schema), gradual migration, blue-green deployment[3].
23. Design a News Feed System (Flipkart recommendations).
For Flipkart: Fan-out on write for active users, fan-out on read for others. Use Redis for ranking, Cassandra for storage, ML service for personalization[1].
24. Explain Leader Election in distributed systems (Atlassian use case).
Leader Election selects one coordinator node among many. Algorithms: Bully Algorithm, Raft, ZooKeeper. Used for locking, coordination in Atlassian tools[3].
25. How to design a system with Strong vs Eventual Consistency?
Strong consistency: All reads see latest writes (2PC, Paxos). Eventual consistency: Replicas converge over time (Dynamo, Cassandra). Choose based on use case[1].
26. Design a Ride-Sharing Service like Uber (Swiggy delivery adaptation).
Swiggy delivery: Driver App → Matching Service → Geospatial Index (GeoHash) → Order Service → Payment → ETA Calculator. Real-time updates via WebSockets[7].
27. What is the Two-Phase Commit (2PC) protocol?
2PC ensures atomicity across distributed transactions: Phase 1 (Prepare – can commit?), Phase 2 (Commit/Rollback). Coordinator manages voting[3].
28. How do you estimate capacity for a system (Salesforce scenario)?
For Salesforce: Estimate DAU, QPS, storage needs. Example: 1M DAU, 10% active/hour = 28K RPS. Each request 1KB → 28MB/s bandwidth[3][8].
29. Design a Content Delivery Network (CDN) architecture (Adobe use case).
Adobe CDN: Origin Server → Regional Edge Servers → Client. Use DNS for geo-routing, cache invalidation via purge API, HTTPS termination at edge[3].
30. How would you design a distributed counter for Oracle analytics?
Oracle scenario: Use Redis with Lua scripts for atomic increments, sharding counters across multiple Redis instances, leader election for coordination, periodic merging[1][3].
