System design interviews are common in technical interviews, especially at top tech companies such as Google, Amazon, Facebook, and Microsoft. These interviews assess your ability to design scalable, maintainable, and reliable systems. Here’s a guide to common system design interview questions, along with possible answers and approaches for each.
1. Design a URL Shortener (e.g., bit.ly)
Question:
Design a URL shortening service like bit.ly. The system should allow users to submit a URL, generate a short version of it, and redirect users to the original URL when the short URL is accessed.
Approach:
- Requirements:
- Accept long URLs and return a short URL.
- Redirect users to the original URL when accessing the short URL.
- Handle millions of requests per day.
- Components:
- URL Storage: Use a database (e.g., NoSQL like Redis or MongoDB) to store the mapping of short URLs to long URLs.
- Short URL Generation: Generate a unique short URL using a base62 encoding technique (A-Z, a-z, 0-9).
- Redirection: Use HTTP 301 or 302 to redirect the user to the original URL.
- Scalability:
- Use sharding to scale the database as the number of URLs grows.
- Implement caching (using Redis or Memcached) to store recently accessed URLs and reduce database load.
- Use load balancers to distribute incoming requests across multiple servers.
- Fault Tolerance:
- Replicate the database across multiple data centers.
- Implement backups for data recovery in case of failure.
Answer:
We can build a URL shortening service using a hashing algorithm (e.g., SHA-256) to generate short URLs. We will store the long URLs and their corresponding short URLs in a database. For scalability, we will use horizontal scaling and load balancing. We will also add a cache layer to reduce the load on the database by caching the most frequently accessed URLs.
2. Design an Online Bookstore
Question:
Design an online bookstore like Amazon. The system should allow users to browse books, add them to their shopping cart, and purchase them.
Approach:
- Requirements:
- Users can search, view, and purchase books.
- Shopping cart and user authentication.
- Order tracking and payment gateway integration.
- Components:
- Catalog Service: Manages the book inventory (e.g., book name, author, price, availability).
- Search Service: Allows users to search for books based on criteria like title, author, genre, etc.
- Cart Service: Manages users’ shopping carts, which contain the books to be purchased.
- Order Service: Handles order processing, including payment integration (e.g., Stripe or PayPal).
- User Authentication: Use OAuth or JWT tokens for secure login.
- Scalability:
- Use microservices architecture to decouple the catalog, cart, and order services.
- Use replication for the database to ensure high availability.
- Database:
- Use SQL databases like MySQL for relational data (book info, orders) and NoSQL databases like MongoDB for unstructured data (reviews, comments).
- Fault Tolerance:
- Replicate services and data to multiple regions.
- Use circuit breakers and retry logic to handle service failures.
Answer:
The bookstore system can be broken into microservices. We can use RESTful APIs for communication between services. The catalog service will store book details in a relational database, while the cart and order services will use separate databases for scalability. For payment, we will integrate with third-party APIs (Stripe, PayPal).
3. Design a Social Media Feed (e.g., Facebook or Twitter)
Question:
Design a social media feed where users can post messages, like posts, and view the posts of people they follow.
Approach:
- Requirements:
- Users can follow other users and post messages (status updates).
- Users can like posts, view feeds, and search for posts.
- The feed should show the latest posts from followed users in real-time.
- Components:
- User Service: Manages user profiles, including information like username, followers, and posts.
- Post Service: Stores and retrieves posts for users.
- Feed Service: Retrieves posts for a user’s feed by pulling posts from followed users.
- Like Service: Allows users to like and unlike posts.
- Notification Service: Sends notifications when someone likes a post or follows the user.
- Scalability:
- Use sharding for user data and posts to distribute data across multiple servers.
- Use caching (e.g., Redis) to store popular posts or feeds for quick access.
- Real-Time Feed:
- Use web sockets or push notifications for real-time feed updates.
- Database:
- Use NoSQL databases like MongoDB to handle large amounts of unstructured data (posts, likes).
- Graph databases like Neo4j can be used for managing user relationships (followers, followees).
- Fault Tolerance:
- Replicate the database and services for high availability.
- Use event-driven architecture for asynchronous operations.
Answer:
For the social media feed, we will use a distributed system where user posts and likes are stored in a NoSQL database. Each user will have a feed that is generated from the posts of the people they follow. For real-time updates, we’ll use web sockets to push new posts to users as soon as they are published. The system should be designed to handle large amounts of data by partitioning the data and replicating it across different servers.
4. Design a Chat Application (e.g., WhatsApp)
Question:
Design a real-time messaging service where users can send and receive messages instantly.
Approach:
- Requirements:
- Real-time messaging between users.
- Users can send text, images, and videos.
- Message history is saved.
- Components:
- Message Service: Handles sending and receiving messages.
- User Service: Manages user authentication and user details.
- Notification Service: Sends push notifications when a new message arrives.
- Media Service: Manages sending and receiving multimedia messages (images, videos).
- Database: Stores message history.
- Scalability:
- Use horizontal scaling to manage increasing traffic and users.
- Implement sharding for chat history storage.
- Real-Time Communication:
- Use WebSockets or MQTT protocol for low-latency communication.
- Database:
- Use NoSQL databases like MongoDB to store message history (since it can be unstructured and growing rapidly).
- Redis can be used to cache frequently accessed chat messages for faster retrieval.
- Fault Tolerance:
- Replicate services to ensure high availability.
- Use message queues (e.g., Kafka) to ensure that messages are delivered even if one of the services is down.
Answer:
For a real-time messaging service, we use WebSockets to establish a persistent connection between users for instant messaging. The message data is stored in MongoDB while Redis is used to cache recent messages. Push notifications are sent via the Notification Service when a new message is received. To ensure reliability, message queues are used for message delivery in case of temporary service disruptions.
5. Design a Video Streaming Service (e.g., YouTube)
Question:
Design a video streaming platform where users can upload, watch, and comment on videos.
Approach:
- Requirements:
- Users can upload videos.
- Users can watch videos in high definition.
- Video streaming should support adaptive bitrate.
- Components:
- Video Upload Service: Manages video upload and storage.
- Video Streaming Service: Streams video content to users.
- Comments Service: Allows users to comment on videos.
- User Service: Manages user authentication and profile.
- Content Delivery Network (CDN): Delivers videos globally with low latency.
- Scalability:
- Use cloud storage (e.g., AWS S3) to store uploaded videos.
- Use a CDN to distribute videos for fast access worldwide.
- Transcoding Service: Converts uploaded videos into different resolutions for adaptive bitrate streaming.
- Database:
- Use NoSQL databases like MongoDB for storing video metadata (e.g., title, description, comments).
- Use SQL databases for transactional data (e.g., user profiles, subscriptions).
- Fault Tolerance:
- Replicate video storage across multiple regions.
- Use caching for frequently accessed videos.
Answer:
For video streaming, we would use AWS S3 to store videos and a CDN like CloudFront to deliver videos efficiently. The transcoding service would convert videos to multiple resolutions for adaptive streaming. MongoDB would be used for metadata like comments, and SQL databases will be used for user and subscription data. A load balancer would be used to distribute traffic across multiple servers.
These are just some of the most commonly asked System Design Interview Questions. The key to solving system design problems is to break down the problem into manageable parts, understand the requirements, and apply best practices related to scalability, reliability, and performance.