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Experiences Building InfluxDB in Go
Paul Dix shares his experience building InfluxDB, an open source distributed time series database, in Go.
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Beyond the Hype: 4 Years of Go in Production
Travis Reeder thinks performance, memory, concurrency, reliability, and deployment are key to exploring Go and its value in production. Travis describes how it’s worked for Iron.io.
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Rust: Unlocking Systems Programming
Aaron Turon explains Rust's core notion of “ownership” and shows how Rust uses it to guarantee thread safety, how Rust avoids some of the pitfalls of C++ without compromising on performance.
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Have Native Languages Returned? (TL;DR: Yes)
In this panel users of C++, Rust, and Go talk about how they picked their language of choice, what problems remain, what was impossible to do with VM-based languages and much more.
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Bind to the Cloud with Falcor
Jafar Husain provides an inside look at the innovative Falcor, the open source JS data access framework that powers the Netflix UIs and the new UI design patterns it enables.
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Using React for the Mobile Web
Brian Holt talks about React, performance issues, some general web performance tips, lessons learned while helping write m.reddit.com using React.
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New in ECMAScript 2016 and Beyond
Brian Terlson discusses the changes in the ES2016 specification process and some of the likely candidates including async functions, SIMD, class property declarations, Typed Objects and more.
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The Future of the Web Platform: Does It Have One?
Alex Russell discusses the impact of new standards-track technologies like Service Workers, Web Manifests, and Web Push which are landing in browsers.
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Dino DNA! Health Identity from the Wrist @Jawbone
Brian Wilt discusses how applied machine learning techniques and data science helped Jawbone build a successful fitness tracking app.
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Takes a Village to Raise a Machine Learning Model
Lucian Vlad Lita focuses on the next step in personalization: well-designed software architectures for storing, computing, and delivering responsive, accurate in-product predictions and experiments.
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The Lego Model for Machine Learning Pipelines
Leah McGuire describes the machine learning platform Salesforce wrote on top of Spark to modularize data cleaning and feature engineering.
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Scaling Uber
Matt Ranney covers the evolution of Uber's architecture and some of the systems they built to handle the current scaling challenges.
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