The Most Common System Design Questions Answered

System design interviews can feel like a jump into the deep end. I remember prepping for my first one, feeling overwhelmed by the sheer scope of possibilities. Where do you even begin?

I want to share some of the most common system design questions I've encountered, along with some straightforward approaches to tackle them. If you're prepping for interviews or just curious about system design, this is for you. Let's dive in!

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1. Designing a URL Shortener Like TinyURL

This question tests your understanding of hashing, databases, and load balancing.

Here's how I'd approach it:

• Functional Requirements: Shorten URLs, redirect to original URLs, handle high traffic.
• Capacity Estimation: Estimate the number of URLs shortened per day and the read/write ratio.
• Database Design: Use a simple database schema with columns for the short URL, original URL, and creation timestamp.
• Hashing Algorithm: Choose a hash function to generate short URLs (e.g., MD5, SHA-256). Consider collision resolution strategies.
• System Architecture: Include a load balancer, web servers, application servers, and a database.
• Scalability: Discuss horizontal scaling, caching strategies, and database sharding.

Internal Linking Opportunity:

For a deeper dive into scalability, check out the system design section on Coudo AI.

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2. Designing a Rate Limiter

Rate limiters are crucial for preventing abuse and ensuring system stability.

Here's what I'd cover:

• Functional Requirements: Limit the number of requests a user can make within a given time window.
• Algorithms: Discuss common algorithms like token bucket, leaky bucket, and fixed window counters.
• System Architecture: Consider where to place the rate limiter (e.g., client-side, server-side, or using a dedicated service).
• Data Storage: Use a fast data store like Redis to track request counts.
• Scalability: Discuss distributed rate limiting using a central counter or consistent hashing.

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3. Designing a Message Queue Like RabbitMQ

Message queues are essential for asynchronous communication between services.

Key aspects to address:

• Functional Requirements: Enqueue and dequeue messages, guarantee message delivery, handle message persistence.
• Architecture: Discuss the roles of producers, consumers, and the message queue itself.
• Message Persistence: Implement message persistence to prevent data loss in case of failures.
• Delivery Guarantees: Ensure at-least-once or exactly-once message delivery.
• Scalability: Discuss horizontal scaling of the message queue and handling message ordering.

Internal Linking Opportunity:

Explore more about message queues in real-world applications by checking out Coudo AI's problems on Amazon MQ RabbitMQ.

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4. Designing a Social Media Feed

This question tests your ability to handle large-scale data and complex relationships.

My approach:

• Functional Requirements: Display posts from friends and followed accounts in chronological or reverse chronological order.
• Data Model: Design database tables for users, posts, and follows.
• Feed Generation: Discuss different feed generation strategies (e.g., push-based, pull-based, or hybrid).
• Caching: Implement caching to reduce database load and improve performance.
• Scalability: Discuss sharding, content delivery networks (CDNs), and optimizing database queries.

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5. Designing a Search Autocomplete System

Autocomplete systems provide real-time suggestions as users type.

Key considerations:

• Functional Requirements: Suggest relevant search queries based on user input.
• Data Structure: Use a trie data structure to store search queries efficiently.
• Ranking Algorithm: Rank suggestions based on popularity, relevance, and recency.
• Caching: Cache popular suggestions to improve response time.
• Scalability: Discuss distributed trie implementations and handling large datasets.

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6. Designing a Distributed Cache

Distributed caches are essential for improving application performance and reducing latency.

Here's what I'd address:

• Functional Requirements: Store and retrieve data quickly, handle cache invalidation, ensure data consistency.
• Cache Eviction Policies: Discuss policies like LRU (Least Recently Used), LFU (Least Frequently Used), and FIFO (First In, First Out).
• Consistency Models: Explain different consistency models (e.g., eventual consistency, strong consistency).
• System Architecture: Use a distributed caching system like Redis or Memcached.
• Scalability: Discuss consistent hashing, cache replication, and handling cache misses.

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7. Designing an E-commerce Platform Like Amazon

This is a broad question that requires you to cover multiple aspects of system design.

My approach:

• Functional Requirements: Product catalog, shopping cart, checkout, payment processing, order management.
• Database Design: Design tables for products, users, orders, and payments.
• Microservices Architecture: Break down the system into microservices (e.g., product service, order service, payment service).
• Scalability: Discuss horizontal scaling, load balancing, caching, and database sharding.
• Fault Tolerance: Implement redundancy and failover mechanisms.

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8. Designing a Video Streaming Service Like YouTube

Video streaming services require efficient storage, encoding, and delivery of video content.

Key aspects to cover:

• Functional Requirements: Upload, store, encode, and stream videos.
• Video Encoding: Discuss different video codecs (e.g., H.264, VP9) and adaptive bitrate streaming.
• Content Delivery Network (CDN): Use a CDN to distribute video content globally.
• Database Design: Design tables for videos, users, and comments.
• Scalability: Discuss horizontal scaling, load balancing, and caching.

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9. Designing a Notification System

Notification systems are used to send real-time updates to users.

Here's my take:

• Functional Requirements: Send notifications via different channels (e.g., email, SMS, push notifications).
• System Architecture: Use a message queue to decouple notification producers and consumers.
• Delivery Guarantees: Ensure reliable notification delivery.
• Scalability: Discuss horizontal scaling and handling high notification volumes.

Internal Linking Opportunity:

For more insights on notification system design, check out Coudo AI's blog on Factory Design Pattern Notification System Implementation.

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10. Designing a Recommendation System

Recommendation systems suggest relevant items to users based on their preferences.

Key considerations:

• Functional Requirements: Recommend products, movies, or articles based on user history and preferences.
• Algorithms: Discuss different recommendation algorithms (e.g., collaborative filtering, content-based filtering, hybrid approaches).
• Data Storage: Store user data, item data, and interaction data.
• Scalability: Discuss handling large datasets and real-time recommendations.

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FAQs

Q: How important is it to clarify requirements in a system design interview?

It's crucial. Always start by asking clarifying questions to understand the scope and constraints of the problem.

Q: What's the best way to practice system design problems?

Practice with real-world scenarios and case studies. Working through problems like these can be very helpful.

Q: How important is communication during system design interviews?

Very important. Interviews are as much about your thought process as your final answer. Explain your ideas clearly and seek feedback when needed.

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Wrapping Up

I hope this breakdown of common system design questions helps you prepare for your next interview. System design interviews can be challenging, but with the right approach and practice, you can ace them. If you want to deepen your understanding, check out more practice problems and guides on Coudo AI. Remember, continuous improvement is the key to mastering system design. Good luck, and keep pushing forward! These system design questions are the stepping stones to becoming a 10x developer!