Top System Design Interview Questions for Freshers

System Design Interview Questions

System Design Interview Questions are the gateway to showcasing your skills in building robust, scalable systems from scratch. Tackling these questions effectively highlights your expertise in design patterns, architecture, and high-impact problem-solving. By mastering System Design Interview Questions, you can set yourself apart in any tech interview and impress top recruiters.

In the Interview Tutorial, we will help you to prepare for the System Design Interview Questions, including 'What is System design?','System Design Interview Questions for Freshers,' 'System Design Interview Questions for Experienced,' and a lot more.

What is System Design?

System design is like creating a blueprint for how a software system should work. Imagine you’re planning to build a house; before you start construction, you need a clear plan detailing each room, connection points, and materials. In the same way, system design focuses on planning and organizing the "rooms" and "materials" of a software system to make sure it works well, is efficient, and meets all the requirements.

In practice, system design involves:

• Analyzing Needs and Breaking Down the System: First, we figure out exactly what the system needs to do. Then, we divide it into smaller, manageable parts that each handle specific tasks.
• Choosing Architectural Patterns: Next, we decide on a structure or framework for how these parts should work together. Think of this as choosing the best layout for organizing the system.
• Setting Up APIs: APIs act like doors that let different parts of the system talk to each other. This ensures that all the pieces share information smoothly.
• Choosing Design Patterns: Finally, we select proven solutions, called design patterns, to solve common problems that may come up in the system. These patterns help us build the system more effectively.

System Design Interview Questions for Freshers

Q1. How do you approach a system design problem?

To solve a System Design Problem, we should:

• Understand the requirements: First, make sure you understand what the system needs to do. Ask questions to get the details about who will use it, what features are required, and what are the limitations.
• Break down the system: Think about the system in smaller parts. For example, you might have a database, a user interface, and an API. Breaking it down helps you focus on one piece at a time.
• Choose the right technologies: Based on the system’s needs, choose the tools that will work best—like which database, programming language, or framework to use.
• Plan for growth: Think about how the system can handle more users or data as it grows. You want to make sure it can scale without breaking.
• Define communication between parts: Think about how each part of the system will talk to each other. This could be through APIs or other methods. Make sure the flow of data is clear and efficient.

Q2. What are the main differences between horizontal and vertical scaling?

The main differences between horizontal and vertical scaling are:

Q3. Explain the CAP theorem and its significance in distributed systems.

The CAP theorem states that in a distributed system, you can only guarantee two out of the following three properties: Consistency, Availability, and Partition Tolerance.

• Consistency means that all nodes in the system have the same data at any given time, ensuring that every read returns the most recent write.
• Availability means that the system remains operational and can respond to queries, even if some nodes are down.
• Partition Tolerance means that the system can continue to function even if network partitions occur, causing some nodes to become unreachable.

Significance of CAP Theorem

• The CAP theorem helps in understanding trade-offs when designing distributed systems. For example, a system might prioritize availability and partition tolerance over consistency in scenarios where constant uptime is crucial.
• It guides architects to make decisions on how the system should behave during network failures or when data consistency is hard to maintain.
• Understanding CAP helps in choosing the right tools and technologies, such as NoSQL databases that often trade consistency for availability and partition tolerance.

Q4. What is caching, and why is it important?

Caching is the process of storing copies of frequently accessed data in a temporary storage area (cache) so that it can be quickly retrieved without needing to fetch it from the original source every time.

• Caching speeds up data retrieval by reducing the time it takes to access data from slower sources like databases or APIs.
• It improves system performance by lowering the load on databases and backend servers, especially during peak traffic times.
• Caching reduces the cost of repeated data requests, as it minimizes the need to process the same request multiple times.
• It enhances user experience by providing faster response times and reducing latency.
• Caching helps in handling large-scale applications by distributing data efficiently across systems, ensuring smoother performance under high demand.

Q5. What is load balancing, and how does it work?

Load balancing is the process of distributing incoming network traffic across multiple servers to ensure no single server is overwhelmed. It helps improve the performance, availability, and reliability of applications.

How it works

• A load balancer sits between the client and the server, acting as a reverse proxy.
• It distributes incoming requests to multiple servers based on factors like server health, load, and response time.
• It ensures high availability by rerouting traffic if a server goes down or is underperforming.
• It improves scalability by allowing additional servers to be added without affecting performance.

Q6. How would you design a URL shortener (like bit.ly)?

• Generate a Short URL: When a user submits a long URL, generate a unique, short identifier (e.g., a random string or base62 encoding of a number).
• Store the Mapping: Save the mapping of the short URL to the original long URL in a database (e.g., MySQL, Redis). Each short URL will point to the corresponding long URL.
• Redirecting: When someone accesses the short URL, look up the short URL in the database and redirect them to the original long URL.
• Handle Collisions: Ensure that the short identifier is unique by checking the database. If there's a collision, generate a new identifier.
• Expiration (Optional): Set an expiration time for the short URL if needed, after which the link will no longer work.
• Analytics (Optional): Track and store metrics such as the number of clicks, the source of the clicks, and the time of access for the short URL.
• Scaling: Use caching (e.g., Redis) for frequently accessed URLs to improve performance and horizontally scale the database as needed to handle large amounts of traffic.

Q7. What are SQL and NoSQL databases, and when should each be used?

SQL Database

• Structured Data: Ideal for data that is organized in tables with fixed columns and rows.
• ACID Transactions: Suitable for applications that need reliable, consistent transactions (e.g., banking systems).
• Relational Data: It is best when data is interconnected, like users, orders, and products, and relationships between tables are required.
• Examples: MySQL, PostgreSQL, Oracle, SQL Server.

NoSQL Database

• Flexible Schema: Works well when data is semi-structured or unstructured (e.g., JSON, key-value pairs).
• Scalability: Good for applications that need to scale horizontally and handle large amounts of data.
• Unstructured or Dynamic Data: Ideal for rapidly changing data models, such as social media posts, logs, or product catalogs.
• Examples: MongoDB, Cassandra, CouchDB, Redis.

When to Use Each

• Use SQL: When you have structured, relational data and need strong consistency and complex querying.
• Use NoSQL: When your data is unstructured, needs to scale quickly, or when you require flexibility in the schema.

Q8. Explain what an API is and the difference between REST and GraphQL.

An API (Application Programming Interface) is a set of rules and protocols that allows different software applications to communicate with each other. It defines how requests and responses should be made between systems, allowing them to interact seamlessly.

Also Consider: Difference between SOAP And REST APIs

Q9. What is a message queue, and why might it be useful in a system design?

Message queues handle tasks asynchronously by queuing messages, enabling efficient background processing and improving system performance under high load.

Q10. What are microservices, and how are they different from monolithic architecture?

Microservices are an architectural style where an application is divided into small, independent services that communicate over a network. Each service focuses on a specific business functionality and can be developed, deployed, and scaled independently.

Q11. How would you design a basic login and registration system?

To design a basic login and registration system, I would:

• User Registration: Allow users to create an account by providing essential details like username, email, and password. Store the password securely using hashing (e.g., bcrypt).
• Email Verification: Send a verification email to the user with a unique link to confirm their email address before completing the registration process.
• Login System: Allow users to log in using their email/username and password. Compare the entered password with the stored hashed password to authenticate.
• Session Management: Use tokens (e.g., JWT) or session cookies to maintain the user's login state across multiple requests, ensuring they stay logged in.
• Password Reset: Provide a "Forgot Password" option, where users can reset their password via a secure email link. Make sure to validate the link to prevent unauthorized access.

Q12. What is a CDN (Content Delivery Network), and how does it work?

A Content Delivery Network (CDN) is a system of distributed servers that work together to deliver content (like images, videos, or web pages) to users based on their geographical location.

How it works

The CDN caches copies of content on multiple servers located in different regions. When a user requests content, the request is directed to the nearest server, reducing load times and improving the user experience.

• Faster content delivery: By serving content from a nearby server, CDNs reduce latency and speed up access for users.
• Reduced server load: CDNs offload traffic from the origin server, improving scalability and performance.
• Improved reliability: If one server fails, others can take over, ensuring continuous availability of content.
• Global reach: CDNs allow content to be served efficiently to users all around the world, enhancing accessibility.

Q13. Explain sharding and partitioning in databases.

Sharding distributes data across multiple databases for better scalability, while partitioning organizes data within a single database, improving performance.

Q14. How would you design a simple e-commerce system?

To design a simple e-commerce system, we should follow:

• Product Catalog: Create a system to store and display products, including details like name, price, description, and images. This can be done with a database for easy querying.
• User Accounts and Authentication: Allow users to create accounts, log in, and manage their information. This includes user registration, login, and secure password storage.
• Shopping Cart: Design a cart system where users can add, remove, and update products before checkout. Store the cart temporarily while users browse.
• Checkout and Payment: Integrate a secure payment gateway to handle transactions. Include order summary, shipping details, and payment processing.

Q15. What is data replication, and why is it useful in distributed systems?

Data replication is the process of copying data from one database or server to another to ensure availability and reliability. It helps distribute copies of data across multiple locations. It is useful in distributed systems:

• Enhances data availability by ensuring multiple copies of data are accessible even if one server fails.
• Improves fault tolerance by preventing data loss during hardware failures or network issues.
• Increases read performance, as users can access data from the nearest replica server.
• Ensures high availability of data in geographically distributed systems, reducing latency.
• Supports disaster recovery by maintaining copies of data in different locations for backup.

Q16. How would you handle security in a web application?

To handle security in a web application, I will perform the following actions:

• User Authentication and Authorization: Implement strong authentication methods (e.g., multi-factor authentication) and ensure users can only access data they’re authorized to view.
• Encrypt Sensitive Data: Use HTTPS to encrypt data in transit and store passwords securely using hashing algorithms like bcrypt or Argon2.
• Prevent SQL Injection: Use parameterized queries or ORM frameworks to interact with databases and avoid SQL injection vulnerabilities safely.
• Cross-Site Scripting (XSS) Protection: Sanitize user inputs and use proper encoding to prevent malicious scripts from being executed in the browser.
• Regular Security Audits: Perform regular security assessments, updates, and patch management to ensure the web application remains secure against new vulnerabilities.

Q17. How would you design a system to handle real-time notifications?

To design a system to handle real-time notifications:

• First, I would use WebSockets or push notifications to establish a constant connection between the server and the client. This way, we can send notifications instantly whenever something happens.
• Next, I’d make sure the server can handle many concurrent connections. Technologies like Node.js or Redis can help with managing connections efficiently, allowing real-time data to be sent to many users simultaneously.
• I would also create a notification queue to manage the flow of notifications. This ensures that notifications are processed and sent in the right order, and we can prioritize important ones.
• To allow users to view past notifications, I would store notifications in a database. This also helps track which notifications have been delivered or read.
• Finally, for scalability, I’d ensure that the system can handle more users by distributing notifications across multiple servers. Load balancers would help in spreading traffic evenly to avoid overloading a single server.

Q18. What are design patterns, and why are they important in system design?

Design patterns are reusable solutions to common software design problems. They are proven and generalizable strategies that can be applied to specific problems in software development. These patterns are not code but templates or blueprints that help in designing systems in a more efficient, maintainable, and understandable way.

Importance of Design Patterns:

• They provide standardized solutions to recurring problems, reducing the need to reinvent the wheel.
• They improve code maintainability and readability, as other developers can easily recognize and understand the design.
• They help in managing system complexity by offering structured ways to organize and connect components.
• They enhance scalability and flexibility, enabling systems to adapt to changes more easily over time.

Q19. How would you design a search function for a large application?

I would design a search function for a large application by:

• Use indexing: Create indexes for the data (like product names, descriptions, etc.) to make searches faster, rather than searching through every record every time.
• Leverage a search engine: Use a powerful search engine like Elasticsearch or Apache Solr to handle complex search queries and full-text search efficiently.
• Implement autocomplete: Add autocomplete functionality to suggest results as users type, improving user experience and making the search process faster.
• Optimize with caching: Cache frequent or popular search queries and their results to reduce the load on the database and speed up response times.
• Support filtering and sorting: Allow users to filter search results (e.g., by price, date, category) and sort them by relevance or other criteria to make the search more useful and tailored

Q20. Explain fault tolerance and its importance in system design.

Fault tolerance is the ability of a system to continue functioning properly even when some of its components fail. It ensures that the system remains available and reliable, even during unexpected issues.

• Fault tolerance minimizes downtime by ensuring the system remains operational, even if part of it fails, reducing system outages.
• It improves reliability by maintaining consistent performance and service availability, which is crucial for user trust.
• It handles hardware or software failures by using redundancy, allowing the system to recover quickly without affecting overall service.
• It enhances the user experience by avoiding interruptions and ensuring a smooth, reliable service.
• Fault tolerance supports scalability by allowing systems to grow while maintaining performance, ensuring long-term stability.

System Design Interview Questions for Experienced

Q 21. Design a scalable notification system

To design a scalable notification system, start by using a publish-subscribe pattern with a message queue. This allows the system to decouple the sending process from the user’s requests and scale independently. Use technologies like Kafka or RabbitMQ to handle high-throughput message delivery, ensuring real-time notifications are sent to millions of users.

Q 22. Design a rate limiter

A rate limiter is used to control the number of requests a user can make within a specific time period. Implement token bucket or leaky bucket algorithms to handle traffic spikes and ensure fairness efficiently. You can use Redis to store the count of requests and timestamps to enforce limits across distributed systems.

Q 23. Design a file storage system like Google Drive or Dropbox

For a file storage system, use a distributed file system (e.g., HDFS or AWS S3) that can store and manage large volumes of files. Implement file chunking for efficient storage and retrieval, and use a metadata database (e.g., SQL or NoSQL) to store file information like permissions, users, and access logs.

Q 24. Design a social media feed

Designing a social media feed involves indexing posts and using a push model for real-time updates. You would need to implement a content delivery system that supports efficient querying and pagination, caching for frequently accessed posts, and the use of distributed databases to handle massive data load across users globally.

Q 25. Design a search engine

For a search engine, use a combination of web crawlers to gather data, indexing to store and organize content, and an efficient ranking algorithm (e.g., PageRank) to return the most relevant results. Distributed search engines like Elasticsearch can be used to provide fast and scalable search functionalities.

Q 26. Design an online payment system

An online payment system needs secure transaction handling, fraud detection, and integration with banks or payment processors. Use encryption protocols (e.g., SSL/TLS) for secure transactions and implement strong API security measures (e.g., OAuth). The system should scale horizontally to process millions of transactions efficiently.

Q 27. Design a content delivery network (CDN)

A CDN caches static content like images, videos, and web pages across geographically distributed servers. When a user requests content, it is served from the closest server to minimize latency. Use technologies like HTTP/2, caching strategies, and edge servers to optimize delivery and reduce the load on origin servers.

Q 28. Design a real-time chat system

For a real-time chat system, use WebSockets or HTTP/2 for bi-directional communication between users and the server. Implement message queues (e.g., Kafka) for message storage and delivery, and ensure data consistency by storing chat history in a distributed database. Scale the system using horizontal scaling and load balancers.

Q 29. Design an e-commerce checkout system

An e-commerce checkout system can be broken down into components such as user authentication, cart management, payment processing, and inventory management. Ensure that each component is scalable and independent by using microservices. For payment, integrate with payment gateways securely and implement order validation and fraud detection.

Q 30. Design a URL-shortening service

A URL shortening service works by generating a unique short key (e.g., a random string) and mapping it to the long URL in a database. Use a hash function or a base62 encoding scheme to ensure a compact representation of URLs. Implement cache mechanisms for fast lookups, and consider scaling horizontally with sharded databases.

Q 31. Design a recommendation system

Design a recommendation system by using collaborative filtering (based on user behavior) or content-based filtering (based on item features). You can store user preferences in a NoSQL database like MongoDB and use machine learning algorithms to analyze and predict recommendations. Caching and real-time processing can improve performance.

Q 32. Design a large-scale logging system

A large-scale logging system should be capable of collecting logs from various services, storing them in a centralized repository, and allowing real-time search and analysis. Use distributed logging tools like ELK stack (Elasticsearch, Logstash, Kibana) or Splunk, and implement log aggregation to handle large volumes of log data.

Q 33. Design a distributed cache

To design a distributed cache, use systems like Redis or Memcached that store frequently accessed data in-memory for fast retrieval. Implement cache invalidation strategies and replication to ensure high availability. Use sharding to distribute data across multiple nodes and prevent cache bottlenecks.

Q 34. Design a scalable analytics platform

A scalable analytics platform should be able to handle large volumes of data and support real-time processing. Stream processing tools like Apache Kafka or Apache Flink can be used for real-time analytics, and historical data can be stored in distributed databases like Hadoop or BigQuery. Ensure the system can scale horizontally to process data in parallel.

Q 35. Design an event-driven architecture

An event-driven architecture relies on events that trigger actions within the system. Use message brokers (e.g., Kafka, RabbitMQ) to publish and subscribe to events, ensuring decoupled components. Each event can trigger workflows or microservices, which allows for scalability and fault tolerance in a distributed environment.

Q 36. Design a video streaming platform

A video streaming platform should handle video uploads, transcoding for different resolutions, and serving to users globally. Use CDNs for efficient content delivery, and implement adaptive bitrate streaming (e.g., HLS) to adjust video quality based on user bandwidth. Store metadata and user interactions in a distributed database.

Q 37. Design a ride-sharing system like Uber

For a ride-sharing system, design components like ride matching, real-time tracking, payment processing, and driver ratings. Use geospatial data and APIs to calculate distances and provide live tracking. Implement a distributed backend with load balancing and microservices for scalable, low-latency processing of ride requests and matches.

Q 38. Design a distributed database

A distributed database should handle large-scale data storage across multiple nodes, ensuring high availability and fault tolerance. Use sharding to divide data across nodes and replication to ensure consistency. Implement consensus algorithms like Paxos or Raft to maintain consistency and handle network partitions.

Q 39. Design a multiplayer gaming system

In a multiplayer gaming system designed for low-latency communication using WebSockets or UDP. Implement real-time state synchronization and event handling between clients and servers. To handle scalability, use game state sharding, load balancing, and distributed matchmaking systems to support millions of concurrent users.

Q 40. Design a messaging queue system

A messaging queue system is designed to decouple components of a distributed system by passing messages asynchronously. Use a distributed message broker like Kafka or RabbitMQ, which supports high throughput and durability. Ensure the system can scale horizontally, provide message persistence, and guarantee message delivery even under heavy load.

Conclusion

In conclusion, preparing for System Design Interview Questions is essential for any software engineer looking to excel in interviews, especially for roles that require building scalable and efficient systems. By understanding key concepts such as scaling, caching, and distributed systems, candidates can tackle complex design problems confidently. Mastering System Design Interview Questions will help candidates not only perform well in interviews but also build better systems in their professional careers.