System Design Interview Questions
- Adobe System Design Interview Questions
- Top Atlassian System Design Interview Questions
- Top Amazon System Design Interview Questions
- Top Microsoft System Design Interview Questions
- Top Meta (Facebook) System Design Interview Questions
- Top Netflix System Design Interview Questions
- Top Uber System Design Interview Questions
- Top Google System Design Interview Questions
- Top Apple System Design Interview Questions
- Top Airbnb System Design Interview Questions
- Top 10 System Design Interview Questions
- Mobile App System Design Interview Questions
- Top 20 Stripe System Design Interview Questions
- Top Shopify System Design Interview Questions
- Top 20 System Design Interview Questions
- Top Advanced System Design Questions
- Most-Frequented System Design Questions in Big Tech Interviews
- What Interviewers Look for in System Design Questions
- Critical System Design Questions to Crack Any Tech Interview
- Top 20 API Design Questions for System Design Interviews
- Top 10 Steps to Create a System Design Portfolio for Developers
Introduction to High-Level System Design
System Design Fundamentals
- Functional vs. Non-Functional Requirements
- Scalability, Availability, and Reliability
- Latency and Throughput Considerations
- Load Balancing Strategies
Architectural Patterns
- Monolithic vs. Microservices Architecture
- Layered Architecture
- Event-Driven Architecture
- Serverless Architecture
- Model-View-Controller (MVC) Pattern
- CQRS (Command Query Responsibility Segregation)
Scaling Strategies
- Vertical Scaling vs. Horizontal Scaling
- Sharding and Partitioning
- Data Replication and Consistency Models
- Load Balancing Strategies
- CDN and Edge Computing
Database Design in HLD
- SQL vs. NoSQL Databases
- CAP Theorem and its Impact on System Design
- Database Indexing and Query Optimization
- Database Sharding and Partitioning
- Replication Strategies
API Design and Communication
Caching Strategies
- Types of Caching
- Cache Invalidation Strategies
- Redis vs. Memcached
- Cache-Aside, Write-Through, and Write-Behind Strategies
Message Queues and Event-Driven Systems
- Kafka vs. RabbitMQ vs. SQS
- Pub-Sub vs. Point-to-Point Messaging
- Handling Asynchronous Workloads
- Eventual Consistency in Distributed Systems
Security in System Design
Observability and Monitoring
- Logging Strategies (ELK Stack, Prometheus, Grafana)
- API Security Best Practices
- Secure Data Storage and Access Control
- DDoS Protection and Rate Limiting
Real-World System Design Case Studies
- Distributed locking (Locking and its Types)
- Memory leaks and Out of memory issues
- HLD of YouTube
- HLD of WhatsApp
System Design Interview Questions
- Adobe System Design Interview Questions
- Top Atlassian System Design Interview Questions
- Top Amazon System Design Interview Questions
- Top Microsoft System Design Interview Questions
- Top Meta (Facebook) System Design Interview Questions
- Top Netflix System Design Interview Questions
- Top Uber System Design Interview Questions
- Top Google System Design Interview Questions
- Top Apple System Design Interview Questions
- Top Airbnb System Design Interview Questions
- Top 10 System Design Interview Questions
- Mobile App System Design Interview Questions
- Top 20 Stripe System Design Interview Questions
- Top Shopify System Design Interview Questions
- Top 20 System Design Interview Questions
- Top Advanced System Design Questions
- Most-Frequented System Design Questions in Big Tech Interviews
- What Interviewers Look for in System Design Questions
- Critical System Design Questions to Crack Any Tech Interview
- Top 20 API Design Questions for System Design Interviews
- Top 10 Steps to Create a System Design Portfolio for Developers
Introduction to High-Level System Design
System Design Fundamentals
- Functional vs. Non-Functional Requirements
- Scalability, Availability, and Reliability
- Latency and Throughput Considerations
- Load Balancing Strategies
Architectural Patterns
- Monolithic vs. Microservices Architecture
- Layered Architecture
- Event-Driven Architecture
- Serverless Architecture
- Model-View-Controller (MVC) Pattern
- CQRS (Command Query Responsibility Segregation)
Scaling Strategies
- Vertical Scaling vs. Horizontal Scaling
- Sharding and Partitioning
- Data Replication and Consistency Models
- Load Balancing Strategies
- CDN and Edge Computing
Database Design in HLD
- SQL vs. NoSQL Databases
- CAP Theorem and its Impact on System Design
- Database Indexing and Query Optimization
- Database Sharding and Partitioning
- Replication Strategies
API Design and Communication
Caching Strategies
- Types of Caching
- Cache Invalidation Strategies
- Redis vs. Memcached
- Cache-Aside, Write-Through, and Write-Behind Strategies
Message Queues and Event-Driven Systems
- Kafka vs. RabbitMQ vs. SQS
- Pub-Sub vs. Point-to-Point Messaging
- Handling Asynchronous Workloads
- Eventual Consistency in Distributed Systems
Security in System Design
Observability and Monitoring
- Logging Strategies (ELK Stack, Prometheus, Grafana)
- API Security Best Practices
- Secure Data Storage and Access Control
- DDoS Protection and Rate Limiting
Real-World System Design Case Studies
- Distributed locking (Locking and its Types)
- Memory leaks and Out of memory issues
- HLD of YouTube
- HLD of WhatsApp
Best Practices for Writing Clean and Maintainable Code
Why Clean and Maintainable Code Matters
Improves Collaboration
When working in a team, clean code ensures that everyone can understand and contribute to the codebase without confusion. According to a study by Stack Overflow, 75% of developers believe that readability is the most important aspect of code quality.
Reduces Technical Debt
Poorly written code accumulates technical debt, making future changes time-consuming and expensive. Clean code minimizes this risk, ensuring that your project remains agile and adaptable.
Enhances Debugging and Maintenance
Well-structured code is easier to debug and maintain. A survey by GitLab found that developers spend 35% of their time fixing bugs, and clean code can significantly reduce this burden.

Key Principles of Clean Code
1. Follow Consistent Naming Conventions
Use Descriptive Names
Choose names that clearly describe the purpose of the variable or function. For example, instead of x, use userAge.
Avoid Abbreviations
Abbreviations can be confusing. For instance, calc is less clear than calculateTotalPrice.
Use CamelCase or Snake_Case
Stick to a naming convention like CamelCase for variables (totalPrice) or snake_case for functions (calculate_total_price).
Example Table: Naming Conventions
Type | Good Example | Bad Example |
Variable | userAge | ua |
Function | calculateTotalPrice | calc |
Class | ShoppingCart | SC |
2. Keep Functions and Methods Short
Single Responsibility Principle
Each function should do one thing and do it well. For example, a function named validateUserInput should only handle input validation, not data processing.
Ideal Function Length
Aim for functions that are no longer than 20 lines. According to Robert C. Martin, author of Clean Code, “Functions should be small, very small.”
3. Write Meaningful Comments
Avoid Redundant Comments
Don’t state the obvious. For example, // Increment counter is unnecessary if the code is counter++.
Use Comments for Why, Not What
Explain why a particular approach was taken, not what the code does. For example:
# Using bubble sort for small datasets due to its simplicity Â
4. Use Version Control Effectively
Commit Messages
Write clear and concise commit messages. For example:
- Bad: “Fixed stuff”
- Good: “Fixed issue with user login validation”
Branching Strategy
Use a branching strategy like Git Flow to manage features, bugs, and releases effectively.

Tools and Techniques for Clean Code
1. Code Linting and Formatting
Tools like ESLint (for JavaScript) and Prettier can automatically format your code and catch errors.
Benefits of Linting:
- Ensures consistent code style.
- Identifies potential bugs early.
2. Automated Testing
Automated tests ensure that your code works as expected and remains bug-free.
Types of Tests:
- Unit Tests: Test individual functions or methods.
- Integration Tests: Test how different components work together.
- End-to-End Tests: Simulate real user scenarios.
Example Testing Tools:
Language | Tool |
JavaScript | Jest, Mocha |
Python | PyTest |
Java | JUnit |
3. Refactoring Regularly
When to Refactor:
- When you notice duplicated code.
- When a function becomes too long or complex.
- When you need to improve performance.
Refactoring Techniques:
- Extract Method: Break down a large function into smaller ones.
- Rename Variables: Use more descriptive names.
- Remove Dead Code: Delete unused code to reduce clutter.

Common Pitfalls to Avoid
1. Over-Engineering
Avoid adding unnecessary complexity to your code. Keep it simple and straightforward.
2. Ignoring Code Reviews
Code reviews are a great way to catch issues early and share knowledge within the team.
3. Skipping Documentation
Documentation helps new developers understand the codebase quickly. Use tools like JSDoc or Sphinx to generate documentation automatically.

How does a real-time notification system work?
A real-time notification system captures user actions as events, processes them, and delivers notifications instantly. It uses technologies like WebSockets and message queues to ensure timely delivery. To learn more about system design, check out our DSA course.
What are the challenges in designing a real-time notification system?
The main challenges include handling high traffic, reducing latency, and ensuring reliability. Scalability and fault tolerance are also critical. For a deeper dive into these concepts, explore our Web Development course.
Which technologies are best for building a real-time notification system?
Popular technologies include Kafka for event streaming, WebSockets for real-time communication, and Redis for caching. To master these technologies, enroll in our Master DSA, Web Dev & System Design course.
How does YouTube manage high traffic without crashing?
YouTube leverages CDNs (Content Delivery Networks), load balancing, and distributed databases to distribute traffic efficiently and prevent downtime. If you want to learn more about handling large-scale traffic and system design, check out this Master DSA, Web Dev & System Design Course.

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