binhnguyennus/awesome-scalability

Awesome Scalability is a curated reading list for software engineers and architects who need to understand how to build systems that can handle large amounts of users and traffic without breaking down or slowing down. The README describes it as an organized collection of articles from prominent engineers and case studies from real systems that serve millions or billions of users. It addresses the question of how technology companies like Google, Netflix, Amazon, and Uber design, build, and scale their backend infrastructure. The list is organized by topic rather than by company or technology. Categories include scalability principles, availability (keeping systems running even when parts fail), stability, performance optimization, data and machine learning at scale, real-world architecture diagrams, system design interview preparation notes, technical talks, and books. Rather than providing code or tools, it links to articles, engineering blog posts, academic papers, and conference presentations. Topics covered range from fundamental concepts like the CAP theorem (which describes trade-offs in distributed systems), consistent hashing, caching strategies, and database sharding (splitting large databases across multiple machines), to organizational topics like how tech companies hire and structure their engineering teams. You would use this repository when preparing for a system design interview, when starting to architect a system that needs to scale, when investigating how a specific company solved a particular infrastructure problem, or when building general knowledge about distributed systems. It is not runnable software; it is a reference document in Markdown format. It is part of the "awesome" list convention and is updated periodically with new links.