Anticipating the right questions for an interview is the best way to feel confident about your knowledge and experience as a software engineer. If you have been searching for the most common questions asked during system design interviews by tech companies, you’ve come to the right place. 

 

As you read through this blog, assess your knowledge and how much more practice you will be needing for your interview. All IT giants examine interview candidates according to their knowledge of system design concepts so let’s start cracking! 

 

What is System Design? 

 

System Design entails defining all the elements in a distributed system — its modules, components, architecture, and interfaces — based on the specific needs of an organization. It involves the following stages:

 

• Requirements gathering

• Analysis

• Architecture design

• Component design

• Interface design

• Testing

• Deployment

 

This design process must consider and seek to accommodate various product goals and organizational needs, such as optimizing user experience and minimizing cost. 

 

System Design Interview Questions 

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1. What skills do you need to design distributed systems? 

 

Entry-level system design skills include a combination of technical knowledge and soft skills that help you make effective decisions during the design process. You don't need to memorize every single one of these skills to answer this interview question, but it's good to understand the scope of your responsibilities.  

 

Technical skills 

• Basic programming: Proficiency in at least one programming language commonly used in system design, such as Java, C++, or Python, is essential for creating and modifying system components. 

• Software development methodologies: Familiarity with processes like Agile, Scrum, or Waterfall is important for executing projects. It's also good for managing time, resources, and expectations. 

• Fundamental design principles: Understanding basic principles like modularity, abstraction, and encapsulation can help create well-structured systems that are more efficient and maintainable. 

• Basic UX/UI design knowledge: Awareness of user-centered design principles can help developers implement more user-friendly interfaces and can lead to an improved user experience. 

• Deployment and scaling: System designers need to know how to deploy and scale systems to handle varying levels of demand. This includes understanding cloud infrastructure, containerization, load balancing, and other techniques. 

• Modeling tools: Familiarity with tools like UML or SysML is good for creating visual representations of system components, relationships, and behaviors. 

• Version control systems: Experience using version control tools like Git or Apache Subversion (SVN) streamlines collaboration, code management, and change tracking. 

• API integration: APIs allow different components, services, and applications to interact and exchange data. Gaining proficiency in API integration makes it much easier to create flexible, modular, and feature-rich systems. 

 

Soft skills are particularly important for system designers due to the collaborative and creative nature of their work. Having these soft skills will help you handle real-world problems efficiently with your teams and other stakeholders:  

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• Problem-solving: System designers are called in to solve intricate challenges that require innovative and efficient solutions. Having strong problem-solving skills is essential for breaking down obstacles and developing effective strategies to address them.  

• Communication: System designers often collaborate with various stakeholders, such as developers, project managers, and clients. Clear and effective communication for technical and non-technical audiences is critical in conveying design ideas, understanding requirements, and ensuring everyone is on the same page. 

• Teamwork: System design projects typically involve multidisciplinary teams with diverse expertise, such as software engineers, hardware engineers, UX/UI designers, and project managers.

• Adaptability: Technologies and methodologies are constantly evolving, and system designers need to stay on top of these changes to ensure the systems they create remain relevant and effective. 

• Time management: System designers often work on multiple tasks and projects simultaneously, each with different deadlines and priorities. Effective time management helps them balance these competing demands, ensuring tasks are completed efficiently and deadlines are met.

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Consider signing up for our system design interview preparation handbook for an in-depth look at the skills you'll need to demonstrate. 

 

2. Define load balancing. Why is it important in system design? 

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Load balancing is a technique used in computing and networking for distributing workload evenly across multiple resources, such as servers, processors, or network links. This prevents any single resource from becoming a bottleneck or point of failure. 

 

In other words, load balancing optimizes how resources are utilized to enhance system performance, and ensures both high availability and reliability. 

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​3. Differentiate between horizontal and vertical scaling

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Horizontal and vertical scaling are both methods of increasing the system’s capacity to handle increased workloads. However, they differ in how resources are added or adjusted to increase this capacity.  

• Horizontal scaling, also known as "scaling out," adds more server nodes or instances to a system to distribute the workload evenly. Here, capacity is increased by connecting multiple servers, usually with a load balancer. 

  • Advantages: Easier to scale, better load distribution, and improved fault tolerance because the failure of a single node won't crash the entire system. 

  • Drawbacks: More nodes make systems more complex, have higher costs due to additional hardware, and can make applications sensitive to latency because of the physical distance between server nodes.

• Vertical scaling, also known as "scaling up," involves upgrading or increasing the resources (such as CPU, RAM, or storage) of an existing node or server to handle larger workloads.

  • Advantages: Less complex, fewer nodes simplifies system management, and pretty cost-effective for smaller-scale applications or systems. 

  • Drawbacks: Single point of failure due to reliance on a single node or server, upgrades require downtime, and there's an upper limit to how much you can augment a single node or server. 

 

4. What are sharding and partitioning? 

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Sharding and partitioning are both performance optimization techniques used in database management to distribute and organize data across multiple nodes or servers.

 

Sharding is a method used to horizontally partition a database into smaller, more manageable pieces called shards. Each shard contains a subset of the data, and the shards are distributed across multiple nodes or database servers. Sharding allows the database workload to be spread across several machines, improving performance and enabling the system to handle larger datasets and more user requests.  

 

Partitioning divides a database into smaller segments based on specific criteria, such as a range of values or a certain attribute. There are two main types of partitioning: 

• Horizontal partitioning divides a database into multiple tables, each containing a subset of the rows from the original table. 

• Vertical partitioning divides a table into smaller tables or partitions by columns, so each partition contains a subset of columns from the original table. 

 

Horizontal partitioning offers faster queries unlike vertical partitioning but it causes issues like data skew. Vertical partitioning is useful because it reduces redundancy and increases data security but complicates query optimization. 

 

​5. What are your best practices for testing and debugging? 

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A good testing and debugging approach involves constant refinement and iteration over time. What helps in this process is defining test cases for system evaluation and utilization of third-party tools to assist automation, monitoring, and other debugging practices. 

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​6. What is the CAP Theorem?

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The CAP Theorem is a fundamental concept in distributed systems that describes the trade-offs between three properties: Consistency, Availability, and Partition Tolerance. According to the CAP Theorem, a distributed system can only guarantee two of these three properties simultaneously.  

 

• Consistency: Every read operation receives the most recent write or an error.

• Availability: Every request (both read and write) receives a non-error response, but does not guarantee that it contains the most recent data. 

• Partition Tolerance: The system continues to function even when communication between nodes is partially or completely disrupted due to network failures.

 

Different databases can offer different advantages:

• An RDBMS (like MySQL, Postgres, etc.) can give Consistency and Availability at the same time, but not Partition Tolerance.

• Redis, HBase databases and MongoDB can guarantee Consistency and Partition Tolerance, but not Availability.

• Cassandra and CouchDB allow Availability and Partition Tolerance simultaneously  

 

7. What is the difference between an open and closed system?

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An open system allows communication with external systems and has a more complex structure as it incorporates communication with entities. 

 

On the other hand, closed systems do not transmit information to the external world. 

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8. What is the link between scalability and performance? 

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Scalability and performance are interrelated concepts in the context of system design. Scalability refers to a system's ability to handle an increasing workload by efficiently utilizing additional resources, such as processing power, memory, or network bandwidth. Performance, on the other hand, refers to the responsiveness, throughput, and overall efficiency of the system when executing tasks or responding to user requests.  

 

A system can have varying degrees of scalability and performance, such as:

 

• High performance and high scalability: Capable of processing requests or tasks efficiently, even as user traffic or workloads increase. As resources are added to this system, it maintains or even improves its performance! 

• High performance and low scalability: Capable of processing requests or tasks efficiently for a limited number of users. As traffic or workloads increase, the system struggles to maintain its performance, resulting in slower response times and reduced throughput. 

• Low performance and low scalability: Struggles to process tasks and requests, even with a limited number of users or workload. As the workload increases, this system's performance worsens. 

• Low performance and high scalability: This system can handle increasing workloads efficiently by utilizing additional resources, but its baseline performance is suboptimal, and it has inherently slow response times or low throughput. 

 

9. How do you measure system performance?

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System performance is measured by the following factors: 

 

• Average response time: The time (in milliseconds) it takes for a system to process a request and return a response.

• Latency: Latency is the speed at which data is exchanged between a client and server. 

• Throughput: This is the amount of data packets produced or processed in a given period. For example, bits per second or HTTP operations per day. 

• Request rate: The number of requests received by a system in a given period, often measured in requests per second (RPS) or transactions per second (TPS). 

• Error rate: The percentage of requests that result in errors or failures.  

• Availability:  The percentage of time a system is operational and accessible to users.

• Scalability: The ability of a system to handle increased workloads by adding resources.

• Reliability: The ability of a system to perform consistently and accurately over time, without errors or failures.

• Apdex (Application Performance Index): A standardized method for measuring user satisfaction.  

• Garbage collection by the system: Affects the memory usage and responsiveness of a system. A system with poor garbage collection can lead to excessive memory usage, slower response times, and crashes.  

 

10. What are the different types of documentation created during system design?

 

Software documentation includes: 

• Product Documentation 

1. System documentation

2. Requirements document 

3. Software architecture documentation

4. Source code documentation

5. Quality assurance documentation

6. Maintenance and help guide

7. User documentation

8. End-user documentation

9. System administrators documentation 

• Process documentation 

1. Plans, estimates, and schedules 

2. Reports and metrics 

3. Working papers 

4. Standards 

 

11. What are some of the factors to consider when designing a system's data architecture?

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Here are some key considerations for designing the system’s data architecture: 

 

• Types of data the system will be computing 

• The databases that the data will be interacting with 

• Whether the system will require offline functionality and/or real-time streaming abilities 

• Alignment with the organization’s goals 

• Data volume and growth 

• Privacy of data 

• How the data will be accessed 

 

12. What is a controller in system design? 

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A controller is an essential part of the system as it receives input from a user or external system and manages the flow of data or operations within a system. The controller acts as an intermediary between the user/external system and the underlying system components, such as a database. In short, a controller directs other components and makes decisions for the entire system. 

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13. What are the different types of consistency patterns in system design? 

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There are three different types of consistency patterns — each one works well in different kinds of applications: 

 

• Weak consistency: In this type of consistency, the read request does not get the newly written data. This can be adequate in real-time uses (e.g., VoIP, video chat, online multiplayer games, etc.) because losing information from some seconds ago does not matter in these situations 

• Eventual consistency: This kind of consistency pattern is well-suited for highly available systems, like DNS and email systems, where data is replicated asynchronously so the written data is read within milliseconds

• Strong consistency: When the data is written in this type of consistency, subsequent reads see the latest data instantly in a synchronous manner. RDBMS and file systems follow this for data transaction 

 

14. What is a Content Delivery Network? 

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A Content Delivery Network (CDN) is a proxy server network distributed globally to deliver content to users more efficiently and quickly. End-users in different locations receive HTML, CSS, JS files, images, and videos from the CDN closest to them. This reduces the user’s waiting time and prevents any single server from becoming overloaded.

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15. What is a web crawler?

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Web crawlers are automated programs used by search engines like Google to search documents on the web and retrieve information from websites. The purpose of a web crawler is to index the contents of websites and gather data that can be used for various purposes, such as search engine indexing, content analysis, and data mining.

 

16. Which structure tools are used in system design? 

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Some of the important tools used to structure during system design are: 

 

• Data flow diagrams (DFD): Data flow diagrams show the flow of data from external entities to its logical storage. 

• Decision trees: It is a tree-like model of decisions and their consequences.  

• Pseudocode: A program outline written in a formal natural language instead of a programming language.  

• Data dictionary: It lists the information (default label, description, units, etc.) of all the data items that are in the DFD. 

• Structured English: Structured English uses straightforward English to break down the program code into an easily understandable logical sequence of steps. 

 

17. What is your strategy for designing a recommendation system?

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When designing a recommendation system for maximum user satisfaction, it is important to include the following: 

 

• Features should be based on user requirements from the system — movies, music, apparel shopping recommendations, etc. 

• Mechanism to recommend relevant content in real-time 

• Collaborative filtering approach 

• Evaluation component to understanding the system’s working 

 

18. Design a URL-shortening service 

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Here’s a possible design approach for designing a URL-shortening system: 

 

• Define the required features: 

1. Generating a shorter URL than the original one

2. Mapping the original URL to the shortened one

3. Allowing redirection to the short URL

4. Enabling the system to handle multiple requests

5. Support custom names for the short URLs 

• Identify the common problems like handling user load and regulating database storage space 

• Select the best type of database to store original URLS 

 

19. Design a ride-sharing service 

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You can approach this design problem by following these steps: 

• Define the architecture for the system (suggested architecture: monolithic or microservices)

• Choose the database to use 

• Design an optimized dispatch system to match users with drivers

• Design the mechanism for maps and routing 

• Define an approach to storing geographical locations 

 

Our detailed blog on designing the Uber backend system is extremely helpful to tackle this common system design problem. 
 

20. Design a video streaming service like Youtube

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A video-sharing platform would allow users to upload, watch, share, and comment on video-based content. It is a huge system that will be transmitting petabytes of data — it will have to be scalable so that a large number of users can view and share the video content simultaneously. You can use the following approach: 

 

• Define the components for this system, which would be

1. Client: Devices to use the service like mobile phones, smart TV, etc. 

2. CDN (Content Delivery Network): All videos are stored in the CDN which allows viewers to stream videos 

3. API (Application Programming Interface) servers: Other functionalities like playlist creation, feed recommendation, user signup, etc. are performed by the API servers

• Design the approach to record video stats 

• Decide how users would be able to add comments in real-time 

 

The System Design Interview Cheatsheet RESHADED method is a great resource if you are wondering how to approach system design questions like these.  

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Ready for your system design interview?

 

As you can see from these questions, your knowledge of how distributed systems work and the various methods used to increase a system’s efficiency are going to be extremely important to perform well in your system design interview. Hope these questions make you feel less intimidated!

 

Our Grokking the Modern System Design Interview course is exactly what you need to build the required skills and get into tech companies like Google, Microsoft, and Amazon to reach your career goals.

Are you interested in reviewing more topics besides system design? Try solving Blind 75 problems to help you tackle questions with confidence. 

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