Grokking the System Design Interview

10 System Design Interview Questions I Wished I Knew Before the Interview

Prepare for your system design interview confidently! Ace high-stakes questions with our top-notch guides, practice materials, and expert tips.

System design interviews have become an essential aspect of the hiring process in the tech industry, with top companies like Google, Facebook, and Amazon relying heavily on them to evaluate a candidate’s ability to design and optimize large-scale systems.

I have had helped hundreds of candidates navigate this challenge. In my experience, acing a system design interview requires not only a strong understanding of the fundamental concepts but also the ability to communicate your thought process clearly and efficiently. This is where most candidates struggle, as they may have the knowledge but are unable to express it in a manner that resonates with their interviewers.

In this article, I’ll share the top 10 system design interview questions that I have encountered through my interview experiences with major tech companies. I’ve chosen these questions based on their frequency in interviews. Moreover, I’ll provide you with a step-by-step approach to answering each question effectively, along with practical tips and best practices that you can incorporate into your own interview preparation.

Entry-Level Candidates vs. Experienced Professionals

There’s a stark difference in the expectations for entry-level candidates and experienced professionals during system design interviews.

For Entry-Level Candidates: If you’re fresh out of college or have less than two years of experience, interviewers are often lenient. They don’t expect you to design Facebook’s backend. Instead, they look for a solid understanding of basic system design principles and the capability to think logically. For instance, a typical question might be about designing a simple ticket booking system or understanding database schemas.

Example: Did you know? According to Glassdoor, about 12% of entry-level software engineer interviews focus on basic system design, to ensure a foundational grasp.

For Experienced Professionals: As you climb the experience ladder, the intricacy of the questions ramps up. Now, interviewers will focus on scalability, data consistency, and high-level design principles. You might be asked to design a global distributed system or optimize a social media platform for millions of users.

Example: Surprising Stat: On a study conducted by Hired.com, it was found that over 48% of senior engineers faced complex system design questions in their interviews.

Let’s start with a small description of top 10 system design questions.

The Top 10 System Design Interview Questions:

1. Design a URL Shortening Service (e.g., bit.ly)

This question assesses your ability to design a service that can generate short, unique URLs for longer web addresses. Key concepts include hashing, database design, and API development.

2. Design a Scalable Rate Limiter

Rate limiters are crucial in protecting systems from being overwhelmed by a high volume of requests. This question tests your understanding of distributed systems and techniques like token bucket or leaky bucket algorithms.

3. Design Twitter or a Similar Social Media Platform

Designing a social media platform like Twitter requires you to consider various aspects such as user registration, following/follower relationships, tweeting, and timeline generation. This question evaluates your skills in designing scalable and fault-tolerant systems.

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4. Design a Web Crawler

A web crawler is used to extract information from websites and index it for search engines. In this question, you’ll need to showcase your knowledge of web technologies, parallel processing, and data storage.

5. Design an Online Chat System (e.g., WhatsApp or Slack)

This question challenges you to create a system that supports real-time messaging, group chats, and offline message delivery. Key considerations include message storage, data synchronization, and efficient communication protocols.

6. Design a Distributed File System (e.g., HDFS or Amazon S3)

Distributed file systems are essential for storing and managing large amounts of data across multiple machines. This question gauges your understanding of distributed systems, data replication, and consistency models.

7. Design a Load Balancer

Load balancers help distribute incoming network traffic across multiple servers to ensure high availability and fault tolerance. This question requires a strong grasp of networking concepts, algorithms, and session management.

8. Design a Content Delivery Network (CDN)

A CDN is a system that caches and serves content from servers located closer to end-users, improving performance and reducing latency. This question tests your ability to optimize content delivery while managing cache consistency and resource allocation.

9. Design an API Rate Limiter

API rate limiting is crucial for maintaining the stability and security of a web service. This question focuses on your understanding of API design, token-based authentication, and rate-limiting algorithms.

10. Design a Key-Value Store (e.g., Redis or Amazon DynamoDB)

Key-value stores are used for fast, scalable data storage and retrieval. This question evaluates your skills in database design, caching mechanisms, and data replication and partitioning strategies.

By preparing for these top 10 system design interview questions, you’ll have a solid foundation for handling a wide variety of design problems that you may encounter during your interviews. Keep in mind that interviewers are not only interested in your final solution but also the thought process and trade-offs you consider while designing the system. As you practice answering these questions, focus on developing a structured step-by-step approach that takes into account the scalability, reliability, and efficiency of the system you’re designing. And most importantly, don’t forget to communicate your ideas clearly and effectively, as this is a crucial skill that interviewers will be assessing throughout the process.

Demystifying System Design Interviews: A Guide

How to Answer Each Question

Here is detailed guideline on answering each of these system design interview question:

1. Design a URL Shortening Service (e.g., bit.ly)

URL Shortening Service: bit.ly and goo.gl are popular URL shortening services that generate unique short URLs, provide analytics, and efficiently redirect users to the original URL.

High-level Design of URL Shortening Service

Here are the key design points:

• Understand the requirements: Identify the key features, such as URL shortening, redirection, and analytics.
• Make assumptions: Define the expected number of users, requests, and storage capacity.
• Choose a hashing algorithm: Select an algorithm like MD5 or Base62 to generate unique short URLs.
• Design the database: Use a key-value store or relational database to store mappings between the original and shortened URLs.
• Develop APIs: Create RESTful APIs for shortening URLs and redirecting users to the original URL.
• Consider edge cases: Handle duplicate URLs, collisions, and expired URLs.
• Optimize for performance: Use caching mechanisms, such as Redis or Memcached, to speed up redirection.

2. Design a Scalable Rate Limiter

Cloudflare and Amazon API Gateway are examples of services that offer scalable rate limiting features to protect web applications and APIs from excessive requests and abuse.

Here are the key design points:

• Understand the requirements: Determine the rate-limiting policy, such as requests per minute or per second.
• Choose a rate-limiting algorithm: Use token bucket or leaky bucket algorithms based on the desired behavior.
• Design the data storage: Store user tokens in-memory or use a distributed data store like Redis.
• Implement middleware: Create middleware to handle rate-limiting logic before requests reach the main application.
• Handle distributed systems: Use a consistent hashing algorithm to distribute tokens across multiple servers.
• Monitor and adjust: Continuously monitor the system’s performance and adjust rate limits as needed.

3. Design Twitter or a Similar Social Media Platform

Twitter and Facebook are examples of large-scale social media platforms that handle user registration, relationships, posting, and timeline generation while managing massive amounts of data and traffic.

Here are the key design points:

• Understand the requirements: Identify the main features, such as user registration, following/follower relationships, tweeting, and timeline generation.
• Design the data models: Define the schema for users, tweets, and relationships.
• Choose the right database: Use a combination of databases, such as relational databases for user data and NoSQL databases for tweets and relationships.
• Implement APIs: Develop RESTful APIs for user registration, tweeting, and timeline generation.
• Optimize timelines: Use fan-out-on-write or fan-out-on-read approaches to generate user timelines efficiently.
• Handle scalability: Use sharding, caching, and load balancing to ensure the system remains performant under high loads.
• Ensure fault tolerance: Implement data replication and backup strategies to prevent data loss.

4. Design a Web Crawler

Googlebot and Bingbot are web crawlers used by Google and Bing search engines, respectively, to crawl, index, and rank websites based on various factors, such as relevance and popularity.

Web crawler high-level design

Here are the key design points:

• Understand the requirements: Define the scope of the crawl, such as the number of websites, depth of crawling, and types of content to be indexed.
• Choose the right crawling strategy: Implement breadth-first search (BFS) or depth-first search (DFS) algorithms based on the desired crawling behavior.
• Handle URLs: Use a URL frontier to store and manage the URLs to be crawled.
• Design the parser: Create a parser to extract relevant information from web pages, such as links, metadata, and text.
• Store the data: Use a combination of databases, such as a relational database for structured data and a NoSQL database for unstructured data.
• Handle parallel processing: Implement parallelism using multi-threading or distributed computing frameworks like Apache Spark or Hadoop.
• Manage politeness: Respect website crawl-delay directives and avoid overloading servers.

5. Design an Online Chat System

WhatsApp and Slack are examples of online chat systems that support real-time messaging, group chats, and offline message delivery while ensuring security and privacy through end-to-end encryption.

Messeing app high-level design

Here are the key design points:

• Understand the requirements: Identify key features, such as one-to-one messaging, group chats, and offline message delivery.
• Design the data models: Define the schema for users, messages, and chat rooms.
• Choose the right database: Use a combination of databases, such as a relational database for user data and a NoSQL database for messages and chat rooms.
• Implement communication protocols: Use WebSocket or long polling for real-time messaging and HTTP for offline message delivery.
• Design the message storage: Store messages in a distributed database or message queue for scalability and fault tolerance.
• Handle data synchronization: Implement mechanisms to ensure messages are delivered and synchronized across devices.
• Optimize performance: Use caching and indexing strategies to speed up message retrieval and search.
• Ensure security and privacy: Implement end-to-end encryption and authentication to protect user data and communications.

6. Design a Distributed File System

Hadoop Distributed File System (HDFS) and Amazon S3 are widely used distributed file systems designed to store and manage large amounts of data across multiple machines while providing high availability and fault tolerance.

Here are the key design points:

• Understand the requirements: Determine the expected number of files, file sizes, and access patterns.
• Design the file system architecture: Use a master-slave or peer-to-peer architecture based on the desired scalability and fault tolerance.
• Handle file partitioning: Implement data partitioning techniques, such as consistent hashing or range partitioning, to distribute files across multiple nodes.
• Implement data replication: Use replication strategies like quorum-based or eventual consistency to ensure data durability and availability.
• Optimize data access: Implement caching and prefetching strategies to improve read performance.
• Manage metadata: Use a centralized or distributed metadata store to maintain file metadata and directory structures.
• Handle fault tolerance and recovery: Implement mechanisms to detect and recover from node failures, such as heartbeat checks and automatic failover.

7. Design a Load Balancer

Amazon Elastic Load Balancing (ELB) and Google Cloud Load Balancing are examples of cloud-based load balancers that automatically distribute incoming traffic across multiple servers to ensure high availability and fault tolerance.

Load balancing

Here are the key design points:

• Understand the requirements: Define the expected number of clients, servers, and traffic patterns.
• Choose a load balancing algorithm: Implement algorithms like round-robin, least connections, or least response time based on the desired distribution behavior.
• Design the load balancer architecture: Use a hardware or software-based load balancer depending on the required performance and flexibility.
• Handle session persistence: Implement mechanisms like sticky sessions or session affinity to ensure clients maintain a consistent connection to a specific server.
• Manage health checks: Monitor server health and automatically remove unhealthy servers from the load balancer.
• Ensure fault tolerance: Implement redundant load balancers and automatic failover mechanisms to prevent single points of failure.

8. Design a Content Delivery Network (CDN)

Akamai and Cloudflare are leading content delivery networks that cache and serve content from edge servers located closer to end-users, improving performance and reducing latency.

Here are the key design points:

• Understand the requirements: Determine the types of content to be served, the expected number of users, and their geographic distribution.
• Design the CDN architecture: Use a hierarchical or flat architecture based on the desired scalability and performance.
• Implement caching strategies: Use cache eviction policies like least recently used (LRU) or time-to-live (TTL) to manage content in edge servers.
• Optimize content delivery: Implement techniques like request routing, prefetching, and compression to improve content delivery performance.
• Manage cache consistency: Implement cache invalidation mechanisms to ensure up-to-date content is served to users.
• Monitor and analyze performance: Collect and analyze performance metrics to continuously optimize the CDN’s performance and resource allocation.

9. Design an API Rate Limiter

GitHub and Google Maps API are examples of services that implement API rate limiting to maintain stability and security while allowing developers to access their resources within specified limits.

Here are the key design points:

• Understand the requirements: Define the rate-limiting policy, such as requests per minute or per second, and the scope of the rate limits (per user, IP address, or API endpoint).
• Design the rate-limiting mechanism: Implement a fixed window, sliding window, or token bucket algorithm based on the desired rate-limiting behavior.
• Store rate-limiting data: Use in-memory data structures or distributed data stores like Redis to store and manage rate-limiting information.
• Implement middleware: Create middleware to handle rate-limiting logic and enforce rate limits before requests reach the main application.
• Handle distributed systems: Use a consistent hashing algorithm or distributed locks to synchronize rate limits across multiple servers.
• Monitor and adjust: Continuously monitor the system’s performance and adjust rate limits as needed to balance user experience and system stability.

10. Design a Key-Value Store

Redis and Amazon DynamoDB are popular key-value stores used for fast, scalable data storage and retrieval, often utilized for caching, session management, and real-time analytics.

Distributed key-value store

Here are the key design points:

• Understand the requirements: Determine the expected number of keys, value sizes, and access patterns.
• Design the data partitioning: Implement data partitioning techniques, such as consistent hashing or range partitioning, to distribute keys across multiple nodes.
• Implement data replication: Use replication strategies like master-slave or quorum-based to ensure data durability and availability.
• Optimize data access: Implement caching and indexing strategies to improve read and write performance.
• Handle data eviction: Use eviction policies like least recently used (LRU) or time-to-live (TTL) to manage memory usage.
• Ensure fault tolerance: Implement mechanisms to detect and recover from node failures, such as heartbeat checks and automatic failover.

As you prepare for your system design interviews, keep in mind that these questions are meant to assess your ability to design scalable, efficient, and reliable systems. It’s essential to understand the key concepts and trade-offs involved in each problem and be able to communicate your thought process clearly.

Practice answering these questions using a structured approach, starting with understanding the requirements and making assumptions, then moving on to designing the data models, choosing the right databases and algorithms, and finally optimizing the system for performance and fault tolerance. Be prepared to discuss alternative solutions and justify your design choices.

Remember that interviewers are not only interested in your final solution but also the thought process and trade-offs you consider while designing the system. As you practice answering these questions, focus on developing a structured approach that takes into account the scalability, reliability, and efficiency of the system you’re designing. And most importantly, don’t forget to communicate your ideas clearly and effectively, as this is a crucial skill that interviewers will be assessing throughout the process.

Common Mistakes and How to Avoid Them

When tackling system design interview questions, it’s essential to be aware of common mistakes and understand how to avoid them. Here are some key points to keep in mind:

• Not understanding the problem: It’s crucial to fully understand the problem and its requirements before diving into the design. Take the time to clarify any ambiguities and ensure you have a clear understanding of the system’s scope and goals.

How to avoid: Ask the interviewer questions to clarify requirements, and don’t hesitate to restate the problem in your own words to confirm your understanding.

• Jumping to a solution too quickly: Starting with a solution before analyzing the problem and considering alternatives can lead to suboptimal designs.

How to avoid: Take a step-by-step approach to analyze the problem, identify key components, and explore different design choices before settling on a solution.

• Ignoring scalability, reliability, and performance: Failing to consider these factors can result in designs that don’t meet the requirements of large-scale systems.

How to avoid: Keep scalability, reliability, and performance in mind throughout the design process, and be prepared to discuss trade-offs and optimizations related to these factors.

• Not discussing trade-offs: System design often involves making trade-offs between various factors, such as consistency vs. availability, or storage vs. computation. Failing to discuss these trade-offs can leave interviewers questioning your understanding of the problem.

How to avoid: Be proactive in discussing trade-offs and the rationale behind your design choices. This shows interviewers that you understand the complexities of system design and can make informed decisions.

• Poor communication: Failing to clearly communicate your thought process and design choices can make it difficult for interviewers to assess your problem-solving abilities and design skills.

How to avoid: Practice speaking clearly and concisely about your design choices, and use diagrams or visual aids when appropriate to help illustrate your points.

For more details, check my blog on what distinguish you from others in a system design interview.

Useful Resources for System Design Interview Preparation

Navigating the vast sea of interview preparation can be daunting. However, fear not! With the right resources, you can elevate your understanding and position yourself as the top candidate. Let’s spotlight some of the best tools and resources to help you stand out in your system design interview.

a. Books and Online Courses

Ah, the age-old method of learning — but now with a digital twist!

• “Designing Data-Intensive Applications” by Martin Kleppmann: Dubbed by many as the ‘Bible’ for system design, this book delves deep into the challenges of creating robust, scalable, and maintainable apps.
• “Grokking System Design Fundamentals” by Design Gurus: Learn system design essentials required for designing scalable and high-performance systems.
• “Grokking the System Design Interview” by Design Gurus: Learn how to prepare for system design interviews and practice common system design interview questions.

b. Mock Interview Services

There’s a saying: “Practice makes perfect.” But practicing in an environment that mirrors the real thing? Even better.

• DesignGurus.io: This platform offers mock interviews by FAANG engineers, covering a range of topics from algorithms to system design.
• Interviewing.io: Get paired with engineers from top tech companies like Google, Facebook, or Amazon, and receive invaluable feedback on your performance.

Fun Fact: According to a survey by Indeed, over 70% of candidates who used mock interview platforms felt more confident and performed better in their real interviews.

Conclusion

Mastering system design interviews is a critical skill for tech professionals seeking to advance their careers. In this blog, we’ve covered the top 10 system design interview questions.

➡ Learn more about these questions in “Grokking the System Design Interview” and “Grokking the Advanced System Design Interview.”

As you prepare for your interviews, keep in mind that interviewers are interested not only in your final solution but also in your thought process and ability to make trade-offs. Focus on understanding the requirements, analyzing the problem, and designing scalable, efficient, and reliable systems while clearly communicating your thought process and design choices.

Remember that practice is the key to success in system design interviews. Work through various design problems, discuss alternative solutions, and refine your skills in evaluating trade-offs and making informed decisions. By doing so, you’ll be well on your way to acing your system design interviews and securing your dream tech job. Good luck, and happy system designing!

➡ Check Grokking System Design Fundamentals for a list of common system design concepts.

➡ If you like this article, join my newsletter.

Keep learn more on system design interviews:

Mastering the System Design Interview: A Complete Guide

16 System Design Concepts I Wish I Knew Before the Interview.

System Design Interview Survival Guide (2023): Preparation Strategies and Practical Tips

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