Ankit Sharma | 08 Aug, 2023

Top 20 System Design Interview Questions & Answers [2024]


Are you interviewing for a software engineering position? Chances are, you'll be asked at least one question about system design during the interview process. To help you prepare, we've compiled a list of the most common system design interview questions and answers. 

These systems design questions will test your knowledge in critical areas like problem-solving, analytical skills, and technical ability.

Remember, there’s no one-size-fits-all answer to these questions; it's essential to tailor your responses to the job or company you are interviewing with.

Click here to download’s System Design Interview Questions PDF.

What Are System Design Interview Questions?

System design interview questions are technical interview questions used to assess a candidate's knowledge and skills in system architecture and software engineering. 

They typically involve solving complex problems or designing systems under certain constraints and may include using a whiteboard or other visual aid.

Common design systems interview questions include coding challenges, algorithm questions, and questions about the candidate's experience on large-scale projects.

Types of System Design Interview Questions

Typically, we can separate systems design interview questions into categories.

  • Whiteboard questions: focus on your ability to think through a problem and develop a practical solution in real time with a whiteboard or other visual aid. These are one of the most common systems design interview examples
  • Simple system design questions: emphasize practical aspects of software engineering, such as specific coding challenges and algorithms
  • Complex system design questions: involve larger-scale projects and may require you to demonstrate your ability to work as part of a team
  • Specific application design questions: require you to explain the steps needed to design popular applications, like Instagram, Facebook, Netflix, etc

How to Prepare for a System Design Interview

To prepare for a system design interview, it’s crucial to thoroughly research the company, the position, and the particular field of software engineering. This way, you will have a good sense of what your interviewer will be looking for in your responses.

You should also familiarize yourself with key concepts like object-oriented programming, distributed computing systems, and user interface (UX) design.

It can also be helpful to brush up on system design problems and common coding challenges used in interviews, like implementing a queue or designing an efficient search algorithm.

Before your interview, you should also try to gain experience by working on software projects or collaborating in teams. A portfolio of projects in Java or C can also be incredibly beneficial here, as you can use it to showcase your skills and abilities in a real-world setting.

And remember, if you don't know the answer to a system design interview question, try not to panic!

Stay calm and take a moment to think the question through, noting any ideas or approaches that come to mind. You could also ask your interviewer clarifying questions, like what they are looking for in an answer or whether you can refer to any resources for additional information.

Simple System Design Interview Questions

1. What Is a System, and What Are Its Components?

A system is a set of interconnected components that work together to perform a specific function or group of functions. This can include hardware, software, data, and people working together to accomplish a task or goal.

Components within a system can be simple or complex, depending on its nature and the goals it’s trying to achieve. Examples of standard system components include databases, networks, user interfaces, algorithms, servers, and more.

2. What Is Load Balancing?

Load balancing refers to the process of distributing incoming traffic across multiple computing resources, such as servers or network nodes. This can improve system performance and reliability for large-scale web applications or distributed systems by ‘balancing’ the workload across the system.

There are several load balancing strategies, including round-robin, least connections, weighted least connections, least response time, and more. Choosing the right strategy will depend on factors like specific architecture, availability requirements, and budget constraints.

3. What’s the Difference Between Open & Closed Systems?

Open systems communicate with external systems, while closed systems do not exchange or transmit information with the outside world.

Open systems often involve a higher degree of complexity than closed systems, as they must incorporate communication with entities inside and outside of their scope.

4. How Would You Design a System That Meets Specific Requirements?

The first consideration should be the scope and goals of the system, as these will define its purpose and requirements.

Other important considerations include analysis of existing systems, identification of potential risks or constraints, development of user interfaces and user flows, selection and implementation of software tools or frameworks, testing and debugging strategies, and more.

A common approach to system design involves breaking down larger problems into smaller components or modules that can be addressed individually. This allows the system’s parts to interact flexibly while creating a feedback loop where each component can inform future improvements.

Other key considerations include leveraging existing code or platforms, employing iterative and incremental development approaches, utilizing test-driven development methodologies, and more.

5. Describe Some System Design Challenges & How You Would Overcome Them?

One key challenge is managing information flow while ensuring secure and private data transmission. This might involve creating different permission levels for different user types or entities, implementing encryption or other security protocols, and more.

Another challenge is balancing efficiency with resource constraints. This may involve carefully considering the allocation of resources across modules, components, or subsystems to achieve the desired performance while minimizing waste or excessive consumption.

A further challenge is accommodating changing requirements as the system evolves and grows in complexity over time. To address this, it may be necessary to develop flexible design strategies that adapt quickly to new demands and circumstances.

Overall, the key to overcoming system design challenges is to identify potential issues early and develop effective strategies for addressing them at various stages of the design process.

6. What Are Some Best Practices for Testing and Debugging Systems?

When testing and debugging systems, developing an iterative and incremental approach that allows for continuous refinement and improvement over time is essential. 

A key part of this process is creating well-defined test cases that evaluate system performance and functionality. In addition, utilizing third-party tools or software frameworks to assist with automation, monitoring, logging, and other testing and debugging aspects may also be necessary.

Whiteboard Systems Design Interview Questions

7. How Would You Design a URL-Shortening Service Like Bit.Ly?

To design a URL-shortening service, it can be helpful to break the design process into steps.

  1. Gather Requirements: The ability to shorten URLs, the types of URL shortening algorithms, and any user customization options
  2. Design Interface: Input long URLs and receive shortened versions in return. It could include online forms, browser extensions, or mobile applications, and it should be intuitive
  3. Implement Algorithm: Common approach is to use Base 62 encoding, which converts a URL into a numerical equivalent before compressing with an algorithm like SHA-1 or MD5
  4. Setup Database: Store both long and shortened URL versions along with additional metadata (e.g., tracking data)
  5. Redirection Service: Service or endpoint where users can use shortened URLs generated by the system (typically via web pages or API calls) to access the full-length URL via redirection
  6. Testing & Refinement: Test various requests to verify everything is working as expected, can also add analytics tracking to measure usage, identify areas for improvement, or gain insights into customer behavior

8. How Would You Address Data Scalability, Performance Optimization, and High Availability in Your System Design?

With data scalability, you may need to visualize the different layers of a system to identify which components are responsible for handling large volumes of data. 

In terms of performance optimization, you may need to identify slow or resource-intensive components and then brainstorm ways to improve performance. You must then design a plan to scale these components to accommodate increasing traffic or load.

It would also be important to consider how your system design interacts with others and if there are opportunities to optimize this communication.

When addressing high availability, you should focus on anticipating potential issues and planning for contingencies. This may include designing protocols to quickly recover from system failures or adding redundancies to your design to prevent downtime altogether.

9. How Do You Determine & Prioritize System Requirements to Build an Effective Architecture?

As one of the more important system architecture interview questions, determining system requirements can be challenging since it typically involves collaborating with stakeholders to understand their needs and priorities.

To prioritize requirements effectively, consider conducting user interviews or surveys, analyzing similar systems in the market, or performing usability testing on early prototypes of your product.

Additionally, you may need to collaborate with other technical teams, such as architects and developers, to establish a shared understanding of the system's goals and requirements. 

10. How Would You Design a System's Data Architecture & What Are the Key Considerations?

Several factors to consider include the different types of data your system will be working with, how it will be structured, and what systems or databases it will need to interface with.

You may also want to consider whether your system requires real-time streaming capabilities, as well as any offline functionality.

Finally, ensuring that your data architecture aligns with the overall system design and any strategic initiatives or goals of your business is essential.

Want to boost your database knowledge before your next interview? Take a look at:

RDBMS Interview Questions & Answers

11. What’s the Difference Between Horizontal & Vertical Scaling?

Horizontal scaling involves altering the number of resources within a system by adding/removing nodes or servers. This is usually referred to as ‘scaling out’ when increasing resources or ‘scaling in’ when reducing resources. Horizontal scaling has its pros and cons:

  • Pros: Easier to scale hardware without downtime, increased resilience & performance
  • Cons: Maintenance/operation complexity is increased, can be expensive vs. vertical scaling

Vertical scaling refers to adding or removing computational power from system components (CPU, RAM, Storage, etc). When we add power, the process is termed ‘scaling up’, while ‘scaling down’ refers to reducing computational power. Vertical scaling also has pros and cons:

  • Pros: Cheaper than horizontal scaling, easy maintenance, less need to update software
  • Cons: Single point of failure & risk of downtime, limited scope for increasing power

Depending on budget and system priorities, it is possible to implement both horizontal and vertical scaling to meet differing needs for different system components. For instance, you may want to implement horizontal scaling for a web server, but vertical scaling may be more appropriate for a sub-system that handles computationally intensive tasks.

Complex System Design Interview Questions

12. How Would You Design the Backend for a Social Network Like Facebook?

One approach could begin by identifying the data that needs to be stored and managed, such as user profile information, photos and videos, and other relevant content.

You can then think about how to structure and organize this data. This may include putting different data types in separate tables or databases or determining components within your system that will handle specific tasks (e.g., photo uploads or managing user profiles).

For a system like Facebook, the backend needs to handle large amounts of data, high levels of concurrent traffic, and potential traffic spikes. As a result, you may need to consider load balancing, caching strategies, and other architectural optimizations to optimize performance and scalability.

It is also essential to consider how the system will interact with others in the broader infrastructure ecosystem (e.g., user authentication or tracking mechanisms) and any specific security requirements.

Overall, designing a complex system like a social network requires careful planning and collaboration with key stakeholders to ensure all requirements are met from a functional and technical standpoint.

13. How Would You Design an API for Third-Party Developers?

There are several key considerations to keep in mind, including the level of required documentation, whether it offers various types of access (e.g., public versus private), and which features or functionalities will be available.

Thinking about traffic spikes or performance bottlenecks and how you can best manage user authentication while maintaining security standards is also essential.

One approach to optimizing performance might involve caching strategies to minimize query load on backend systems. You may also consider load balancers, message queues, or other asynchronous messaging mechanisms to optimize resource usage and balance traffic.

It’s also essential to think about support requests or troubleshooting issues. This might involve implementing a bug-tracking system, providing detailed documentation and tutorials, or offering additional resources like forums or community support channels.


What is API Testing? Understanding API and How it Works

14. What Do You Need to Consider When Designing the Infrastructure for a Large Online Application?

Important considerations include overall performance and scalability, data storage and management, system monitoring and logging, and security or compliance standards.

One possible method for optimizing performance and scalability involves caching strategies at different system layers to minimize query load on the backend, reduce latency, and improve overall efficiency.

Additionally, it may be helpful to break down complex tasks into smaller microservices that can be deployed separately or managed by separate teams or systems.

It’s also essential to think about user authentication and access control. To do this, you may need to use tools like OAuth (or other authorization protocols) so that users can log in with existing account details, or you’ll need to implement complex authentication processes with multiple approval levels.

Security requirements and compliance standards are also critical when handling sensitive data, such as Personally Identifiable Information (PII) or financial information.

15. Demonstrate How Load Balancing Optimizes System Performance

One approach to load-balancing is a hardware solution like an application delivery controller (ADC). These analyze incoming traffic and distribute it across multiple servers to balance the workload and improve overall system performance and response times.

Another load-balancing strategy is via DNS routing and a round-robin method. This redirects incoming requests to different IP addresses or hostnames in a rotating fashion, distributing traffic across resources evenly. This is typically easier and more cost-effective than hardware solutions.

Specific Application Design Questions

General Considerations When Designing Specific Applications

  • Scaling: Plan to handle growing traffic via horizontal or vertical scaling
  • Security & Reliability: Consider potential points of failure & take steps to mitigate these via encryption, data replication, and automated monitoring tools
  • User interface (UX): Ensure it is intuitive, easy to navigate, and consistent. Also, incorporate user feedback into the design process

16. Design Scenario: Build Instagram From Scratch

  1. Define Purpose: Create an image-sharing platform that allows users to share photos and videos with friends and family
  2. Brainstorm Potential Modules: Decide on functionalities, such as creating a profile, following other users, creating posts, liking posts, commenting on posts, searching for friends, and discovering content
  3. Plan Data Storage: Outline data types that need to be stored, like user information (name, email address, etc.), posts (information about each post such as location tags), followers/followings/likes/comments/views/etc
  4. Design Database Schema: Tables for users, posts, likes, and comments; columns for specific attributes like user name or post caption; and relationships between tables
  5. Develop Back-End Services: Choose an appropriate language (PHP, Python, etc.) to create services like registration/authentication, functions to store user data securely, and access control measures to ensure authorized users can access their data
  6. Create APIs: Enable communication between different system components; for example, between the front-end and back-end or between various front-end modules like authentication and friend search
  7. Design UI: Select a platform for designing the UI, such as React Native or Flutter, that provides features like a navigation drawer, post feed page, and profile page, along with styling options
  8. Test & Debugging: Thoroughly test every module before integrating into the system to identify and fix any bugs quickly and easily
  9. Deployment & Maintenance: Set up the infrastructure to host your app (e.g., cloud hosting) and maintain regular updates to ensure optimal functionality

17. Design Scenario: Hosting Platform for Web Applications

  1. Goals & Requirements: Identify key features of similar services like BlueHost, and gather specific system requirements via stakeholder interviews
  2. System Architecture: Outline interaction between software and hardware, design server infrastructure, databases, APIs, and other necessary components
  3. Design Data Models: Design a fast and efficient relational database schema to store user data and application-specific information
  4. Design UIs: Should be Easy to perform actions without extra training or customer support. Can use tools like Sketch or Figma and include best practices like color theory & accessibility guidelines for equal access regardless of physical capabilities or language preference
  5. Develop APIs: Let developers create logical connections between different services or products without writing extra code from scratch. Can use JavaScript for the front-end and Ruby on Rails or Python for the back-end
  6. Testing & Debugging: Detect and fix errors or bugs before going into production with real customers

18. Design Scenario: Web Crawler

  1. Research: Analyze existing web crawlers to understand how they work, their everyday challenges, and which components are needed for a successful system
  2. Goals: Define the types of data the system needs to collect and how it will be used
  3. Design: Outline a system architecture, including hardware components, crawling algorithms, scalability options, and speed for crawling large amounts of data
  4. Crawling Frequency: Consider how often new content appears online; news websites may publish more frequently than blogs, etc. Also, consider available resources and data volume to choose an appropriate crawling frequency
  5. Data Access Methodology: Need to access data from various sources without violating copyright laws or web service terms & conditions. May need API calls or dedicated scraping libraries like BeautifulSoup or Scrapy (for Python) for HTML/XML documents from websites
  6. Process Data: Store crawled data for further analysis. May need to perform data cleaning, transformations, annotations, and indexing before storing in SQL or NoSQL databases or using ElasticSearch to assess search engine optimization (SEO) performance
  7. Quality Assurance: Tests to check if required components are present in crawled pages, validate links extracted from pages are correct, etc. You may also need to perform stress tests if you plan to crawl vast amounts of data without crashing servers or causing slowdowns

19. Design Scenario: Storage System Like Google Drive

  1. Problem Scope: Key considerations include access control, user authentication, data storage, security, scalability, system performance, storage capacity, and backup strategy
  2. User Requirements: Identify the operational activities that need to be supported; for example, users may require a secure data-sharing platform or a collaborative workspace with file editing capabilities
  3. Set Objectives: Goals to ensure key performance metrics are met for reliability and usability. This could include maximizing uptime, optimizing response time for read/writes, or minimizing downtime due to maintenance
  4. Design Architecture: Select appropriate technologies such as databases, web servers, and programming languages, all while considering budgetary needs. You can also define user roles, access control policies, and API integration with other systems
  5. Build Components: Use the finalized architecture to build drive storage components with suitable coding languages and frameworks such as React JS for the front-end or Node JS for the back-end
  6. Test Components: Implement rigorous testing procedures to identify any potential bugs or problems before going live
  7. Deployment & Monitoring: Configure necessary services (like firewall rules, etc.) before going into production. Perform ongoing monitoring by tracking key metrics like response time and customer feedback/feature requests

20. Design Scenario: Recommendation Engine for Movies

  1. Define Objectives: Create an algorithm that can accurately predict a user's favorite movies based on their previous viewing habits, preferences, and characteristics
  2. Develop Entity Relationship Diagram (ERD): Define the relationship between key entities (i.e., users, movies, etc.), allowing you to visualize how data will be stored, manipulated, and retrieved from various sources within the system
  3. Design Algorithms: Determine which variables/features will be used for analysis to form logical suggestions about movie recommendations. You will need to use machine learning (ML) techniques like regression analysis or clustering to find patterns in user behavior
  4. Testing & Debugging: Thoroughly test the system before releasing it into production to fix bugs or errors early. Also, ensure performance metrics are met accordingly, such as accuracy scores or latency times
  5. Deployment & Monitoring: Keep track of key metrics such as accuracy scores over time, allowing you to make changes or improvements if desired. Likewise, monitor for any errors encountered during usage to address them quickly

Bonus Tips

You can try a few strategies if you are unsure about the answer to system design questions during an interview.

One approach is to ask for more information or clarification from the interviewer, which can help you better understand what they are looking for and give you more time to respond. 

You should also take a moment to think your answer through before responding, or ask if you can get back to them later.

Finally, if all else fails and you don't know the answer, be honest and let the interviewer know that this is outside your area of expertise. 

Whatever happens, it’s essential to remain composed and professional throughout the process and to avoid making negative or defensive statements that could reflect poorly on your candidacy.

In the end, being transparent and honest about what you know is often better than trying to bluff or providing a response you’re not confident about.


If you’re planning to interview for a software engineering position, there’s a strong chance that you'll be faced with at least one system design interview question. These are technical questions that assess your knowledge and skills in system architecture and software engineering. 

To help you ace your next interview, we've covered the top system design interview questions and answers. These will help you to demonstrate your knowledge in problem-solving, analytical skills, and technical ability.

But remember to tailor your responses to the job or company you’re applying for!

Click here to download’s System Design Interview Questions PDF.

Want to become a systems design expert?

Check out this Udemy course:

How to Become a Pro in Systems Design

Frequently Asked Questions

1. How Do I Prepare for a Design System Interview?

It is crucial to focus on building your technical expertise and gaining hands-on experience with different systems and software. This may involve taking online courses, attending workshops, practicing coding challenges, building personal projects, and reading up on the latest system design and development trends.

2. Is Systems Design Important for Interviews?

Yes, it is an essential aspect of many technical interviews to demonstrate your knowledge and skills in the area. A solid understanding of system design can also deepen your knowledge of different systems and software types, which can give you an advantage when formulating practical solutions to complex problems.

3. How Long Is a System Design Interview?

There is no set length for a system design interview; it will depend on the particular role and company. Generally, you can expect to spend at least an hour or two discussing your experience and answering questions about your technical background, expertise, and interests. Some interviews may include hands-on exercises or coding challenges that will need extra time.


By Ankit Sharma

Ankit Sharma is a technical writer for He specializes in data science, machine learning, and AI, among others. Coming from a computer science engineering major, his experience lies more in analytics and solving problems with tech solutions to empower people's work lives. He has worked extensively in SQL, DevOps, and Front-End development, and loves to write about NoCode solutions as well.

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