Study foundational system design concepts such as load balancing, caching, and sharding before a technical interview
Read architecture case studies for products like Instagram, Netflix, and Uber to understand how real systems scale
Follow a structured path from basics to advanced system design without assembling your own reading list
Supplement study with linked YouTube videos and Substack breakdowns of real company engineering decisions
This repository is a curated study guide for learning system design, aimed at software developers preparing for technical interviews at large technology companies. System design is the practice of planning how large-scale software systems are structured: how to handle millions of users, store and retrieve data quickly, keep services running reliably, and scale capacity up or down as demand changes. These topics come up regularly in senior-level software engineering interviews, where candidates are asked to sketch out how they would build something like a social media platform or a video streaming service. The repository does not contain runnable code. It is primarily a collection of links organized into two sections. The first covers foundational concepts: topics like load balancing, message queues, caching, database sharding, the CAP theorem, content delivery networks, concurrency, and microservices architecture, each pointing to an external article in a numbered series. The second section is a table of system design case studies for specific products, including Instagram, Twitter, YouTube, Netflix, Uber, Dropbox, TikTok, and around twenty others, again linking to external write-ups. Additional links point to a companion YouTube channel, a Substack newsletter with real-world engineering breakdowns covering how companies like Lyft, Facebook, and PayPal handle their infrastructure at scale, and a data structures and algorithms study series. The repository is maintained by a creator who publishes technical education content across Medium, Substack, and YouTube. The README is dense with links but light on explanatory text, so most of the actual learning happens on the linked platforms rather than directly in the repository. No software license is stated.
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