Diving into the tech giants' inner circle is no easy feat, with system design interviews acting as formidable gatekeepers. The challenge? Crafting a distributed system on the spot, a skill rarely honed in the day-to-day grind of most jobs. This calls for more than just casual preparation; it demands a targeted, in-depth study of system design's core principles.

Fortunately, the task ahead, while daunting, is far from impossible. Armed with a methodical approach, you can demystify the complex web of components that form the backbone of today's tech architectures. This article is your roadmap, pinpointing the critical elements you need to master in order to navigate through the most typical system design queries with ease.

As a companion on your journey, I've prepared a unique toolkit: an Excalidraw component library, specifically designed to hone your system design skills. Available at no cost, this resource is poised to sharpen your understanding and elevate your ability to craft cogent, efficient designs.

The cornerstone of mastering system design lies in grasping the four fundamental tasks every system must execute: transporting, storing, processing, and presenting data. Each component within a system architecture is tailored to one of these essential functions:

  1. Transport Data
  2. Store Data
  3. Process Data
  4. Present Data

By understanding and applying these categories to your system design interviews, you position yourself to not just answer questions, but to showcase a deep understanding of how scalable, efficient systems are built. Are you ready to dive deep into the realm of data transportation and beyond?

Let's embark on this detailed exploration together.

Transport Data

Any system needs to "transport" data from one component to another, especially in a microservice architecture. There are three component types, which are essential to design the data transport functionality of your system.

Message Queue


A message queue enables asynchronous communications between services so that the sending service does not need to wait for the receiving service’s reply. Thereby the fault tolerance and resiliency of a system improves. Message queues are managed by a message broker which implements the pub/sub pattern to simplify the connection of services.

This allows handling a growing number of services by adding them as publishers or subscribers and thereby scale the system dynamically.