20 Common System Design Interview Questions (With Sample Answers)

System design interviews are a key part of the hiring process at top tech companies, and they can be pretty tough. But don't worry – with the right prep, you can nail them.

In this article, we'll dive into 20 common system design interview questions and give you some sample answers to help you get ready.

We'll start by breaking down what system design interviews are all about. Then, we'll jump into those 20 questions, covering everything from basic concepts to more complex problems. We'll also throw in some bonus questions and share a handy framework to tackle any system design challenge. Plus, we'll give you some tips on how to prepare for these interviews. By the end, you'll have a solid game plan to ace your next system design interview.

What Are System Design Interviews?

System design interviews are a crucial part of the hiring process for software engineers, especially for more senior positions. These interviews assess your ability to create large-scale systems and solve complex engineering problems. They're known for being challenging and open-ended, often leaving candidates feeling a bit overwhelmed.

Definition

System design interviews evaluate your skills in designing real-world software systems that involve multiple components. Unlike coding interviews, which focus on finding solutions to specific problems, system design interviews are more about creating solutions. They're less like a science and more like an art, where there's no single correct answer, but there can certainly be incorrect ones.

During these interviews, you'll be asked to design systems like social media platforms, video streaming services, or e-commerce websites. The goal is to see how you approach complex problems, make decisions under uncertainty, and communicate your ideas effectively.

Interview Structure

A system design interview usually lasts about 45 minutes to an hour. Here's what you can expect:

1. You'll be given a broad, open-ended problem to solve.
2. You'll need to ask questions to clarify requirements and constraints.
3. You'll sketch out a high-level system design, often using a whiteboard or online tool.
4. You'll discuss trade-offs, potential bottlenecks, and scaling considerations with your interviewer.
5. You might be asked follow-up questions about specific components or how to handle certain scenarios.

The key is to treat this as a collaborative process. Think of your interviewer as a junior engineer you're working with to design this system.

What is Whiteboarding?

Whiteboarding is a crucial part of the system design interview process. It involves visually representing your ideas and system architecture, traditionally on a physical whiteboard. However, with the shift to remote interviews, many companies now use online whiteboarding tools like Zoom Whiteboard, Miro, or Whimsical.

When whiteboarding, you'll typically:

1. Break down the problem into smaller, manageable pieces
2. List design requirements
3. Draw diagrams of system components and their relationships
4. Define data models
5. Note key points and takeaways

Remember, your whiteboard should be clear and easy to understand. It's not just about the final design, but how you communicate and explain your thought process throughout the interview.

20 Common FAANG System Design Interview Questions

When preparing for system design interviews at top tech companies, it's crucial to practice with common questions. Here are some frequently asked system design interview questions from FAANG companies:

Facebook (Meta) system design interview questions

• Design Instagram
• Design Facebook's Newsfeed
• Design Facebook Messenger or WhatsApp
• Design a live commenting system for Facebook posts
• Design a file storage and sharing system like Dropbox.

Amazon system design interview questions

• Design an online bookstore
• Design a warehouse system
• Design an API rate limiter
• Design a recommendation system

Apple system design interview questions

• Design iCloud
• Design Apple Music
• Design the App Store

Netflix system design interview questions

• Design Netflix's video streaming service
• Design a recommendation engine
• Design a content delivery network (CDN)

Google system design interview questions

• Design Google Search
• Design Google Maps
• Design Google Drive
• Design YouTube
• Design Google Photos (video answer front-end)

These system design interview questions cover a wide range of scenarios and challenge your ability to create scalable, efficient, and reliable systems. Practice solving these problems to improve your skills and prepare for your next system design interview at a FAANG company.

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Bonus: Other System Design Interview Questions

Beyond the common system design interview questions asked by FAANG companies, there are numerous other challenging problems that interviewers might present. These questions often test your ability to think creatively and apply your knowledge to unique scenarios.

• Design a heat map for Uber drivers
• Design a global file storage
• Design a global chat service
• Design a file sharing system
• Design a system to match rider and driver
• Design a URL Shortening Service
• Design TripAdvisor (written answer)
• Design YouTube feed with API
• Design a search engine

Sample Answers

Each answer requires a deep dive into multiple aspects of architecture, design decisions, scalable systems, and optimization. Before providing answers, let’s first outline a structured approach for answering each type of system design question, which can serve as a framework that you can apply to all these scenarios:

General Approach to System Design Questions:

1. Clarify Requirements:

• Start by asking questions to understand the problem better.
• Define the scope (e.g., users, features, data flow).
• Identify key features (core vs. optional).

2. Establish Assumptions:

• Estimate the scale (e.g., users, read/write ratio).
• Understand traffic expectations (e.g., requests per second).
• Confirm data size and latency requirements.

3. High-Level Design:

• Draw a block diagram with all major components.
• Describe how each component interacts with others.
• Think about APIs and data models at a high level.

4. Deep Dive on Specific Components:

• Discuss important components in detail (e.g., database, a load balancer, caching).
• Cover data storage (SQL vs. NoSQL) and replication.

5. Address Scale and Reliability:

• Talk about scaling (horizontal/vertical).
• Discuss replication, sharding, and load balancing strategies.
• Consider caching for high-speed access and CDN for content delivery.

6. Think About Edge Cases and Trade-Offs:

• Address failover, consistency, and availability.
• Discuss trade-offs like CAP theorem, consistency, scalability, etc.
• Identify bottlenecks and potential solutions.

Now let’s break down each framework on how to respond to each system design interview question.

Example Framework for Each Design Question:

Facebook (Meta) System Design Interview Questions:

1. Design Instagram:

• Clarify Requirements: Core features (photo upload, timeline, notifications), scalability (millions of users).
• High-Level Components: Web server, photo service (storage, resizing), timeline service.
• Data Storage: Use NoSQL for storing photos, metadata, comments; relational database for user information.
• Scaling: CDN for distributing images and videos; sharding for user data; caching frequently accessed timelines.

2. Design Facebook's Newsfeed:

• Requirements: Personalized feed, multiple content types, real-time updates.
• High-Level Components: Feed generator, data store, caching layer.
• Scaling Strategy: Use fan-out on write to deliver updates; caching for most recent posts.
• Consistency vs. Latency: Discuss trade-offs for real-time updates vs. user experience.

3. Design Facebook Messenger or WhatsApp:

• Requirements: Real-time messaging, encryption, offline storage.
• Core Components: Messaging servers, chat database, push notifications.
• Database Considerations: Use NoSQL for message storage, Pub/Sub for real-time delivery.
• Reliability: Ensure message delivery and support for high availability across regions.

Amazon System Design Interview Questions:

1. Design an Online Bookstore:

• Clarify Requirements: Product listings, search, user reviews, shopping cart.
• High-Level Components: Product service, search engine, user management.
• Storage: Use SQL for orders and transactions, NoSQL for product metadata.
• Scalability: Implement load balancing for front-end servers; cache product listings for faster access.

2. Design a Warehouse System:

• Requirements: Inventory management, order processing.
• Components: Warehouse database, order processor, inventory tracker.
• Database: Relational for accurate inventory tracking, NoSQL for scaling.
• Optimization: Design worker queues for efficient order fulfillment.

3. Design an API Rate Limiter:

• Clarify Requirements: Per-user rate limit, burst allowance.
• Approach: Use token bucket algorithm or sliding window log.
• High-Level Design: Rate limiting middleware, distributed counter to track requests.
• Storage and Scale: Consider Redis for quick access to counters.

Apple System Design Interview Questions:

1. Design iCloud:

• Requirements: Storage, backup, synchronization.
• Components: Storage service, sync engine, authorization.
• Storage Considerations: Object storage for files, database system for metadata.
• Reliability and Scale: Data replication across regions to ensure high availability.

2. Design Apple Music:

• Clarify Features: Streaming, playlists, recommendation.
• Components: Audio streaming service, recommendation engine, music database.
• Data Storage: SQL for playlists and subscriptions, NoSQL for large-scale music metadata.
• Optimization: Use a CDN for delivering audio with low latency.

Netflix System Design Interview Questions:

1. Design Netflix's Video Streaming Service:

• Clarify Requirements: Streaming quality, content delivery, multi-device.
• High-Level Components: Streaming server, encoding pipeline, content storage.
• CDN: Discuss how a content delivery network can reduce latency.
• Scaling: Optimize video encoding and distribute storage using regional data centers.

2. Design a Content Delivery Network (CDN):

• Requirements: Reduce latency, serve static content.
• Components: Origin server, edge servers, caching layer.
• Caching Strategy: Implement edge caching to deliver content faster to users.
• Scalability: DNS-based load balancing to redirect users to the nearest edge server.

Google System Design Interview Questions:

1. Design Google Search:

• Clarify Requirements: Fast indexing, ranking algorithms, user query processing.
• High-Level Components: Crawler, indexer, query engine.
• Storage: Distributed NoSQL database for efficient indexing.
• Optimization: Use inverted indexing and ranking algorithms to deliver the best results.

2. Design YouTube:

• Clarify Features: Video upload, viewing, comments.
• Core Components: Video storage, transcoder, streaming servers, recommendation engine.
• Storage and Delivery: Use object storage for video files, CDN for efficient video streaming.
• Scalability: Distributed database for user data and comments, load balancing for high availability.

Key Aspects to Discuss for Each Design:

• Scalability: How would you handle growth in traffic and user base? Talk about techniques like sharding, load balancing, and horizontal scaling.
• Availability: What measures would you put in place to ensure high availability? Consider replication, redundancy, and failure detection.
• Data Storage: Discuss which type of database (SQL or NoSQL) suits the use case and why.
• Caching: Describe how caching can be used towards performance optimization, including specific cache strategies.
• Security: Talk about user authentication, encryption, and data protection where appropriate.
• Latency and Optimization: How can you minimize latency? Discuss CDN, caching, geo-distributed data centers, etc.
• APIs and Protocols: Explain any relevant APIs or communication protocols that would be essential for the system.

This framework can guide you to systematically break down and discuss each problem during a system design interview. Each question is an opportunity to demonstrate your understanding of scaling, architectural principles, and your ability to think strategically about technology and user needs.

System Design Interview Framework

To tackle system design interview questions effectively, you need a structured approach. Here's a framework that can help you navigate these challenging interviews:

1. Understand the Problem: Start by clarifying the requirements. Ask questions to understand both functional and non-functional aspects. For example, "What are the key features needed?" or "How many users should the system support?" This step is crucial as it sets the foundation for your entire design.
2. Scope the System: Define the scale of the system you're designing. Estimate the number of users, requests per second, and storage needs. These calculations will influence your design choices later on.
3. Design the API: Outline the main APIs your system will need. This step helps you define how clients will interact with your system. Consider using REST, SOAP, or GraphQL, depending on the requirements.
4. Define the Data Model: Sketch out the core database schema. This will help you understand how data flows through your system and guide your decisions on data partitioning and management.
5. High-Level Design: Create a block diagram showing the main components of your system. This should include elements like load balancers, web servers, application servers, and databases.
6. Detailed Design: Dive deeper into 2-3 core components based on the interviewer's feedback. Discuss different options, their pros and cons, and justify your choices.
7. Identify and Resolve Bottlenecks: Analyze potential bottlenecks in your design. Discuss how you'd handle issues like single points of failure, data replication, or high traffic scenarios.

Throughout the interview, collaborate with your interviewer. Treat them as a team member you're working with to solve the problem. This approach not only helps clarify doubts but also showcases your ability to work in a team.

Also, manage your time wisely. It's easy to get caught up in details, but you need to cover all aspects of the design within the interview timeframe. Practice this framework with various system design practice questions to improve your skills and confidence. Find the best system design coach to work with on your mock interviews for one-on-one, personalized support here.

Fundamental Concepts for Designing Scalable Systems

In this final part of our guide, we'll break down the fundamental concepts that you need to know when designing scalable systems.

Web Protocols

Web protocols are like the glue that holds network communication together – crucial for making distributed systems function smoothly. They establish standards and rules for data exchange across networks, connecting physical infrastructures like servers and client devices. Two main models – TCP/IP and OSI – serve as the backbone for structuring these communications effectively.

TCP/IP and OSI Models

• TCP/IP Model: Comprises four key layers (Network Access, Internet, Transport, and Application) using protocols such as IP and TCP to manage data transmission across the network.
• OSI Model: This model breaks network communication down into seven layers, giving a more granular look at how data flows and how each part of the process functions.

TCP vs. UDP

• TCP (Transmission Control Protocol): Prioritizes reliability by managing errors like lost or out-of-sequence packets, making it ideal for scenarios where data accuracy is critical.
• UDP (User Datagram Protocol): Emphasizes speed, bypassing error-checking processes, which is why it’s used in applications like live streaming where low latency is crucial.

HTTP and HTTPS

• HTTP: This is a protocol for sending web content and hyperlinks using common request methods like GET and POST.
• HTTPS: Extends HTTP by adding encryption, safeguarding data transmission to prevent unauthorized access.

TLS and WebSocket

• TLS (Transport Layer Security): Adds a layer of security by encrypting data, ensuring that communications are private and secure through a handshake involving digital certificates.
• WebSocket: Provides real-time data transfer between clients and servers, which is perfect for applications needing a continuous data stream without repeated requests.

APIs: Building Blocks of System Integration

APIs (Application Programming Interfaces) make it possible for different systems to communicate, allowing them to share resources efficiently. Think of APIs as the bridges between applications, defining exactly how data is requested and delivered, often using HTTP for data transfer.

REST APIs

• REST (Representational State Transfer) is a common style that utilizes familiar web URL structures and HTTP methods, making interactions simple and stateless.

Other API Types:

• RPC (Remote Procedure Call): Ideal for lightweight data exchanges, allowing different systems to interact seamlessly.
• GraphQL: Gives clients control over precisely what data is retrieved, offering more flexibility and efficiency.
• SOAP (Simple Object Access Protocol): Uses XML to handle transactions where high security is essential.

API Security and Management:

• API gateways are essential in managing security, acting as control points for managing rate limits, authentication, and keeping systems secure.

Reliability: Keeping Systems Stable

Reliability in system design is about making sure everything works as expected, even in the face of challenges. It covers aspects such as handling errors, preventing unauthorized access, and securing recovery from potential failures. Reliable systems often plan for various types of failures—from temporary network outages to major hardware issues.

Retries:

• Simple retries help manage occasional glitches, but it's important to limit retries to avoid system overload.
• Delayed retries with exponential backoff are great for common issues, preventing all systems from retrying at the same time and overwhelming the network.

Circuit Breakers:

• A circuit breaker stops repeated failed operations to avoid exhausting resources. It's particularly useful to prevent cascading failures that could crash a system.

Saga Patterns:

• Sagas manage distributed transactions, ensuring that if one component fails, compensatory actions take place, maintaining overall data consistency across microservices.

Availability: Being There When Users Need You

High availability means a system is always accessible when users need it, despite challenges like scaling and potential hardware failures. While achieving 100% uptime is unrealistic, good design strives for high availability through redundancy and thoughtful architecture.

Rate Limiting:

• Rate limiting helps manage the load by limiting the number of operations within a set timeframe, keeping the system from being overwhelmed.

Techniques for Rate Limiting:

• Token bucket allocates a specific number of tokens per request.
• Leaky bucket controls the rate by discarding excess requests.
• Fixed and sliding windows help prevent request overload during spikes.

Queue-Based Load Leveling:

• Introducing a queue can help regulate the demand on a service, especially when there are sudden spikes. It’s ideal for scenarios where a bit of latency is okay to keep everything functioning smoothly.

Gateway Aggregation:

• By consolidating multiple requests into one, gateway aggregation helps reduce the load on backend services, which is especially helpful in reducing latency for mobile and microservice-heavy applications.

Load Balancing: Distributing the Load

Load balancers are crucial for spreading incoming traffic across multiple servers, optimizing performance, and ensuring no single server becomes overwhelmed. They are key to achieving horizontal scaling, which means adding more servers to accommodate increased load.

Load Balancer Strategies:

• Round robin assigns servers cyclically, providing an even distribution of requests.
• Least connections send requests to the server handling the fewest current connections.
• Consistent hashing keeps user requests consistently routed, maintaining user session integrity.

Considerations:

• Load balancers can become bottlenecks themselves, necessitating multiple load balancers at high scales.
• Managing user sessions across servers can be complex unless session persistence is maintained.

SQL vs. NoSQL Databases: Choosing the Right Tool

SQL Databases:

• Relational databases are great for managing structured data and complex relationships through predefined schemas, providing strong data consistency.
• Ideal for applications requiring complex transactions, SQL databases ensure ACID compliance for reliable operations.

NoSQL Databases:

• Designed for flexibility, NoSQL databases handle unstructured data and allow for easy scaling across distributed environments.
• These databases are perfect for high-speed, large-scale use cases but may sacrifice data consistency in favor of eventual consistency.

Database Sharding: Dividing to Conquer

Database sharding is a technique used to split a large database into smaller, more manageable pieces or "shards." Each shard is hosted on separate servers, enhancing scalability and performance.

Sharding Techniques:

• Geo-based sharding distributes data by geographic location to reduce latency but may lead to uneven data distribution.
• Range-based sharding segments data into specific ranges but might cause unbalanced load if data distribution isn’t uniform.
• Hash-based sharding evenly distributes data across shards, minimizing hotspots, though related data might end up spread across multiple shards.

Database Replication: Copying for Consistency and Performance

Database replication ensures that copies of data are available on multiple servers, which enhances availability, improves data access speed, and provides resilience during failures. It’s especially important in distributed systems where data consistency across nodes is crucial.

Replication Strategies:

• Leader-Follower Replication: One main server handles all writes and updates follower databases.
• Synchronous vs. Asynchronous Replication: Synchronous keeps all replicas updated immediately, while asynchronous improves speed but may lead to temporary inconsistencies.
• Multi-Leader Replication: Allows multiple databases to accept writes, boosting availability.

Consistent Hashing: Balancing Efficiency and Scalability

Consistent hashing is a technique used to distribute data among servers efficiently, particularly useful for distributed systems. Unlike traditional hashing, it minimizes the need for reassigning data when servers are added or removed, maintaining balance with minimal disruption.

How Consistent Hashing Works:

• Servers and keys are placed on a circular hash space, with each key assigned to the nearest server clockwise.
• Adding or removing servers only requires reassigning keys between the affected nodes, reducing the overhead.

CAP Theorem: Trade-Offs in Distributed Systems

The CAP theorem states that in distributed systems, you can only guarantee two of three properties (Consistency, Availability, and Partition Tolerance) at the same time.

Consistency ensures all nodes have the latest data, Availability guarantees that requests are always answered, and Partition Tolerance means the system continues to operate despite network failures. When designing a system, you must decide which two attributes to prioritize depending on the specific use case.

Asynchronous Processing: Improving Responsiveness

Asynchronous processing allows systems to handle tasks independently rather than sequentially, which improves responsiveness and scalability. Unlike synchronous tasks that require waiting for each operation to complete before moving on, asynchronous methods let multiple tasks proceed in parallel.

Methods of Asynchronous Processing:

• Batch Processing: For handling large sets of data periodically.
• Stream Processing: For real-time data as soon as it arrives.
• Message Queues: Manage tasks in an orderly fashion, keeping things flowing smoothly without overloading the system.

Caching: Making Things Faster

Caching stores frequently accessed data closer to where it's used, significantly speeding up response times and reducing server load. Caches can be managed in-memory, across distributed nodes, or even on file systems for static content.

Caching Policies:

• FIFO (First In, First Out) removes the oldest data.
• LRU (Least Recently Used) evicts data that hasn't been accessed in a while.
• LFU (Least Frequently Used) eliminates data with the fewest accesses.

Encryption: Securing Data

Encryption is vital for protecting data both while it's stored and during transmission. Symmetric encryption uses one key for both encrypting and decrypting data, whereas asymmetric encryption employs a pair of keys—public for encryption and private for decryption, providing enhanced security.

• Data in transit: Typically secured with TLS to ensure safe online communication.
• Data at rest: Encrypted using algorithms like AES to prevent unauthorized access.

Authentication and Authorization

Authentication verifies who a user is, while authorization determines what they’re allowed to do within the system. These two steps are critical for managing access securely.

OAuth 2 is a popular framework that allows users to authorize applications without sharing their credentials, making it perfect for integrating different platforms safely.

Cloud Architecture: Why Go to the Cloud?

Cloud computing allows businesses to outsource the hosting and maintenance of their applications. Providers like AWS, Google Cloud, and Microsoft Azure offer scalability, affordability, and advanced security measures with minimal upfront cost.

Cloud Migration Strategies:

• Re-host: Moving applications as-is to the cloud.
• Re-platform: Minor changes for better cloud optimization.
• Refactor: Complete re-architecture to fully exploit cloud capabilities.

CDNs: Delivering Content Faster

CDNs (Content Delivery Networks) are used to distribute static content, such as images and videos, across globally distributed servers, ensuring that users receive content quickly from a server near them.

CDN Types:

• Push CDN: Requires manual updates to keep content current.
• Pull CDN: Fetches content automatically, caching it for future requests, which is easier to maintain but may serve slightly outdated content.

How Should You Prepare for System Design Interviews?

Preparing for system design interviews requires a strategic approach. Here are some key steps to help you get ready:

Study fundamental concepts

Start by building a strong foundation in system design principles. Read books like "Designing Data-Intensive Applications" by Martin Kleppmann, which covers essential concepts in depth. While reading cover-to-cover might be time-consuming, focus on chapters most relevant to system design interviews. This will help you understand the core ideas behind designing scalable and efficient systems.

Practice with mock interviews

Mock interviews are crucial for honing your skills and gaining confidence. Platforms like DesignGuru offer personalized mock interviews conducted by experienced FAANG engineers. These sessions provide valuable feedback on your strengths and areas for improvement. Additionally, consider using platforms like Meetapro, which connects you with seasoned interviewers from top-tier companies at a lower cost.

Review real-world system architectures

Study case studies of popular systems like Google's search engine, Amazon's e-commerce platform, or Netflix's streaming service. These examples offer insights into how large-scale systems are designed and managed in practice. Pay attention to aspects like scalability, reliability, and efficient data handling.

Stay updated with latest technologies

The tech landscape is constantly evolving. Keep yourself informed about the latest trends in cloud computing, microservices, and other relevant technologies. This knowledge will help you propose up-to-date solutions during your interviews.

Ask clarifying questions

During the interview, don't hesitate to take a few seconds and ask questions to understand the problem better. Clarify requirements, constraints, and expected scale of the system you're designing. This demonstrates your analytical thinking and helps you tailor your solution effectively.

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Conclusion

System design interviews are a crucial part of the hiring process for software engineers, testing their ability to create large-scale systems and solve complex problems. This article has walked through 20 common system design interview questions, covering a range of scenarios from designing social media platforms to creating recommendation engines. We've also shared a helpful framework to tackle these challenges, emphasizing the importance of understanding the problem, scoping the system, and identifying potential bottlenecks.

To get ready for your next system design interview, it's key to build a strong foundation in system design principles and practice with mock interviews. Studying real-world system architectures and staying up-to-date with the latest technologies can give you an edge. Remember, the goal isn't to have perfect solutions ready, but to show your problem-solving process and ability to communicate your ideas clearly. With the right prep and mindset, you'll be well-equipped to ace your next system design interview and take your career to new heights.

FAQs

What is asked in a system design interview?

• In a system design interview, candidates are usually asked to create a high-level architecture for a complex software system. Questions often focus on designing systems (i.e. a distributed key value store), considering factors such as data storage, load balancing, and fault tolerance mechanisms. These questions aim to test your understanding of key system design concepts and your ability to solve real-world engineering problems.

How do I prepare for a design system interview?

• System design interview preparation includes studying common architecture patterns, understanding the fundamentals of distributed systems, and practicing design problems. You should become familiar with topics like load balancing, data consistency, and scalability to develop robust solutions. Practicing mock interviews and reviewing case studies can significantly enhance your system design skills.

Are system design interviews hard?

• System design interviews can be challenging because they require a deep understanding of system design concepts and the ability to make informed decisions with ambiguous requirements. Designing distributed systems that can handle large-scale user demands while maintaining reliability requires a broad skill set. However, with focused system design interview preparation, you can build confidence and master the skills needed to succeed.

How to solve system design problems?

• To solve system design problems, start by clarifying the requirements and identifying constraints to define the scope clearly. Break down the system into core components, focusing on system design concepts like scalability, reliability, and data consistency. Incorporate principles of distributed systems to design a solution that can handle large traffic and ensure fault tolerance.

What is a system design interview question?

• A system design interview question typically asks you to create an architecture for a large-scale application, such as a messaging platform or a content delivery network. It aims to evaluate your system design skills, including how well you can address scalability, reliability, and data consistency. These questions often involve designing a distributed system to manage vast amounts of data or traffic.

What is the approach to system design interviews?

• The best approach to system design interviews is to break the problem into smaller parts and address each part systematically. Start by gathering requirements, identifying key components, and designing an architecture, keeping scalability, fault tolerance, and data consistency in mind. Mastering system design interviews involves extensive practice to develop a structured problem-solving approach.

What are the 5 criteria for system design?

• The five criteria for system design include scalability, reliability, availability, performance, and data consistency. Scalability ensures that the system can handle increased loads, while reliability and availability ensure minimal downtime.

What are the three main parts of system design?

• The three main parts of system design are architecture, data management, and communication. Architecture involves defining components and services, ensuring scalability and reliability; data management focuses on storage solutions, data consistency, and access patterns. Communication is about how components interact in distributed systems, using APIs or messaging protocols to ensure seamless data exchange.

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