amancini/system-design-101

System Design 101 is a learning resource that breaks down complex software engineering concepts using visual diagrams and plain language. It is aimed at two groups: people preparing for system design interviews (a common step in hiring for senior engineering roles), and anyone who simply wants to understand how large-scale software systems actually work beneath the surface. The project covers a remarkably wide range of topics. It walks through communication protocols like REST and GraphQL, explains how databases and caching systems work, breaks down microservice architecture, and demystifies DevOps concepts like Docker and Kubernetes. It also dives into real-world case studies, showing how companies like Netflix, Twitter, Airbnb, and Discord architect their systems. Whether you want to understand how HTTPS works, what happens when you swipe a credit card, or how Discord stores trillions of messages, there is a visual breakdown for it. Each topic follows a consistent format: a diagram or illustration paired with a concise explanation. Rather than dense paragraphs of technical jargon, the content relies on step-by-step visuals that show data flowing through a system, then follows up with short descriptions of what each step does. This makes it easier to grasp abstract concepts like API gateways, load balancing, or HTTP evolution without needing to read a textbook. The primary audience is software engineers preparing for interviews, but it is equally useful for founders, product managers, or anyone working alongside engineering teams who wants to understand the vocabulary and tradeoffs of modern system architecture. A PM could use it to understand why their engineering team chose a particular caching strategy, or a founder could reference the Netflix case study to understand what scaling looks like in practice. What makes this project notable is its insistence on visual explanation over text. Rather than asking readers to mentally simulate how components interact, it shows the interaction directly. The tradeoff is that explanations are intentionally high-level and simplified, favoring clarity over exhaustive technical depth, which is exactly the point for interview prep and conceptual understanding.