How to Crack Any System Design Interview as a Fresher

Introduction

• Preparation for system design interviews, especially for freshers.
• Importance of knowing how to design scalable systems.
• Content is theoretical and crucial for freshers and intermediate-level students switching jobs.

Interview Structure in Startups

• Two rounds are typical:
  1. Knowledge Round: Tests proficiency in languages and tech stack (e.g., JavaScript, MERN stack).
  2. System Design Round: Major rejection occurs here. Candidates must design a scalable system.

Understanding System Design

• Common misconception: Approach using vertical scaling (incorrect term used, should be horizontal scaling).
• Examples often involve client-server models with discussion on scaling techniques.

Vertical vs. Horizontal Scaling

• Vertical Scaling: Increasing resources (e.g., RAM) on a single server (not ideal).
• Horizontal Scaling: Adding more server instances (ideal for handling increased load).
• Issues with vertical scaling: Time-consuming, costly, and doesn’t instantly handle real-time traffic spikes.

Using Queues in System Design

• Essential for handling non-critical tasks asynchronously to reduce server load.
• Example from "TeachUs": Payment completion is critical; sending confirmation email is non-critical.
• Queue systems like Redis can help manage non-critical tasks while prioritizing critical ones.
• Queue Consumer: Handles tasks queued for processing asynchronously, ensuring server efficiency.

Practical Example: Design a Scalable LMS

• Identify and separate critical from non-critical tasks (e.g., payment collection vs. sending emails).
• Use a queue to manage email dispatching asynchronously.
• This methodology reduces server load and increases responsiveness.

Chat System Design Example (e.g., WhatsApp)

• Simple approach: Single server handling multiple clients (limited scalability).
• Horizontal scaling with Redis Pub/Sub architecture for message handling between servers.
• Use of queues for message delivery, ensuring messages are not lost even if servers are busy.
• Implementing asynchronous processing reduces the likelihood of bottlenecks.

Key Takeaways

• Always design with scalability in mind using horizontal scaling and asynchronous processing.
• Critical tasks should be handled immediately; non-critical tasks can be queued for later processing.
• Queue systems (e.g., Redis) are vital in managing load and ensuring system resilience.

Final Notes

• Mastering queue systems is essential for building scalable systems.
• Practice designing systems by categorizing tasks and implementing queues for optimal performance.
• Watch additional videos on queue systems and scalable architectures to deepen understanding.

Recommended Videos

• How to Scale Websockets (video link on scaling websockets by the same presenter).
• Understanding Queue Systems (video link on using BullMQ for queue management).

Feel free to comment for more in-depth architectural examples or coding demonstrations.