Twitter Engineering

Building the world’s first real-time distributed public platform connecting people to their interests, events and each other

Twitter University
Building a culture of learning for @TwitterEng and the world at large through videos, code samples, and more.
Open Source
Twitter engineers use, contribute to and release a lot of open source software. We share what we learn with the greater community via the @TwitterOSS office.
Research
Twitter encourages publication through scientific bodies and industry standards groups. We also have a strong open source culture to share our research widely.

From the Twitter Engineering Blog

  • Improving communication across distributed teams Friday, September 04, 2015

    As a global company, Twitter has offices in numerous locations around the world. Optimizing collaboration and improving productivity between employees across offices is a challenge faced by many companies and something we’ve spent a great deal of time on. For our part, we’ve learned a few lessons about what it takes to make distributed engineering offices successful. Over the next few months, we’ll share what we’ve learned. We’ll also periodically offer workshops about how to do distributed engineering well.

  • Diffy: Testing services without writing tests Thursday, September 03, 2015

    Today, we’re excited to release Diffy, an open-source tool that automatically catches bugs in Apache Thrift and HTTP-based services. It needs minimal setup and is able to catch bugs without requiring developers to write many tests.

  • Twitter at @MesosCon 2015 Friday, July 31, 2015

    Once again, we’re pleased to sponsor and participate in #MesosCon. As heavy users of both Mesos and Apache Aurora to power our cloud infrastructure, we’re excited to be part of this growing community event.

  • Flying faster with Twitter Heron Tuesday, June 02, 2015

    We process billions of events on Twitter every day. As you might guess, analyzing these events in real time presents a massive challenge. Our main system for such analysis has been Storm, a distributed stream computation system we’ve open-sourced. But as the scale and diversity of Twitter data has increased, our requirements have evolved.