How they scaled it
Pick a company. See what’s actually running underneath it.
Real tech stacks and architecture decisions from well-known platforms, based on what their own engineering teams have published - not speculation about what they “probably” do.
8 technologies covered
Netflix
Designing for failure instead of hoping it won't happen
Netflix runs a globally distributed system of hundreds of microservices, streaming to hundreds of millions of devices. At that scale, on public cloud infrastructure, something is failing somewhere at almost every moment - a single "keep everything up" strategy isn't realistic.
7 technologies covered
Uber
A dispatch problem that's really a real-time geospatial problem
Matching riders to drivers isn't a normal CRUD problem - it needs to answer 'which drivers are near this rider, right now' continuously, across a constantly moving dataset, at low latency, across many cities simultaneously.
6 technologies covered
Discord
Millions of concurrent WebSocket connections, and the language choices that followed
Discord's core product is real-time - messages, voice, presence - which means holding open a persistent WebSocket connection per active user, at a scale of many millions of simultaneous connections, without the server-side cost spiraling out of control.
5 technologies covered
Stripe
Money can't be 'probably correct' - reliability as the actual product
Payments infrastructure has a different tolerance for error than most software - a duplicate charge or a lost transaction isn't a minor bug, it's actual money either taken from or owed to a real person. The engineering challenge isn't primarily speed; it's absolute correctness under network conditions that are never fully reliable.
8 technologies covered
Airbnb
Breaking apart a Ruby on Rails monolith without breaking the business
Airbnb's original Ruby on Rails monolith let a small team move fast in the early days, but as the company and engineering org grew, that same monolith became the thing slowing everyone down - every team's code lived in one repository, one deploy pipeline, and one runtime, so a change anywhere could break something everywhere.
8 technologies covered
Spotify
Hundreds of autonomous services, and the cloud migration that took years
Spotify runs a real-time streaming product for a huge global user base, backed by hundreds of independently owned backend services - the architectural challenge isn't one hard technical problem, it's keeping that many services, owned by that many small autonomous teams, reliable and consistent at once.