Analysis updated 2026-05-18
Prepare for system-design interviews by studying real-world architectural patterns and trade-offs.
Learn how companies like Netflix, Twitter, and Figma solved specific scaling challenges.
Build vocabulary around distributed systems concepts like load balancing, caching, and messaging.
Understand the infrastructure and design decisions behind everyday software you use.
| bytebytegohq/system-design-101 | animate-css/animate.css | dopplerhq/awesome-interview-questions | |
|---|---|---|---|
| Stars | 82,482 | 82,510 | 82,384 |
| Language | — | CSS | — |
| Setup difficulty | easy | easy | easy |
| Complexity | 1/5 | 1/5 | 1/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
System Design 101 is a reference repository that tries to explain complex software systems using visuals and short text. The README says it is aimed at two readers: people getting ready for a system design interview, and people who want a clearer picture of how production systems work under the surface. It is published by the ByteByteGo team and links out to their YouTube channel and email newsletter from the top of the page. The repository is built around a long table of contents. Each entry is a link to an explainer page on bytebytego.com, and the entries are grouped into broad categories. The first category is API and Web Development, with roughly forty short articles on topics like short polling and long polling, server-sent events, WebSockets, load balancers, gRPC, NAT, HTTP headers, browser rendering, HTTP versions, CSS, common ports, WAN versus LAN versus PAN versus MAN, REST API design, GraphQL adoption, API gateways, URL anatomy, unicast versus broadcast versus multicast versus anycast, SOAP versus REST versus GraphQL versus RPC, HTTP request methods, proxies and reverse proxies, polling versus webhooks, pagination, and API security tips. A later category is Real World Case Studies, which collects writeups of how named companies built or scaled specific systems. Examples in the table of contents include Postgres scaling at Figma, the one-line change that reduced clone times at Pinterest, security analysis of Telegram, automated bug fixing at Meta scale, how Levels.fyi scaled with Google Sheets, McDonald's event-driven architecture, Uber's CI/CD, designing a Stack Overflow clone, the Twitter 1.0 tech stack, the Twitter For You ranking pipeline, YouTube's video upload pipeline, push notification systems, Netflix's caching layers and database stack, and Airbnb's architectural evolution. The README itself is mostly this table of contents plus the project's banner image and a brief tagline, the explanations and diagrams live in the linked pages on bytebytego.com rather than inside this repository. Someone would use it as a reading list, either to grind through one or two topics a day in preparation for a system design interview, or to look up how a named company has solved a specific problem.
Visual guide to how large-scale software systems work, with diagrams and real-world case studies from companies like Netflix, Twitter, and Figma.
License could not be detected automatically. Check the repository's LICENSE file before use.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.