Netflix Android and iOS Studio Apps — now powered by Kotlin Multiplatform
By David Henry & Mel Yahya Over the last few years Netflix has been developing a mobile app called Prodicle to innovate in the physical production of TV shows and movies. The world of physical production is fast-paced, and needs vary significantly between the country, region, and even from one production to the next. The nature of the work means we’re developing write-heavy software, in a distribu
Open-Sourcing riskquant, a library for quantifying risk
Netflix has a program in our Information Security department for quantifying the risk of deliberate (attacker-driven) and accidental losses. This program started on the Detection Engineering team with a home-grown Python library called riskquant, which we’ve released as open source for you to use (and contribute to). Since that library was written, we have hired two amazing full-time Risk Engineer
Introducing Dispatch
By Kevin Glisson, Marc Vilanova, Forest Monsen Netflix is pleased to announce the open-source release of our crisis management orchestration framework: Dispatch!Okay, but what is Dispatch? Put simply, Dispatch is: All of the ad-hoc things you’re doing to manage incidents today, done for you, and a bunch of other things you should’ve been doing, but have not had the time! Dispatch helps us effectiv
Python at Netflix
By Pythonistas at Netflix, coordinated by Amjith Ramanujam and edited by Ellen Livengood As many of us prepare to go to PyCon, we wanted to share a sampling of how Python is used at Netflix. We use Python through the full content lifecycle, from deciding which content to fund all the way to operating the CDN that serves the final video to 148 million members. We use and contribute to many open-sou
Beyond Interactive: Notebook Innovation at Netflix
By Michelle Ufford, M Pacer, Matthew Seal, and Kyle Kelley Notebooks have rapidly grown in popularity among data scientists to become the de facto standard for quick prototyping and exploratory analysis. At Netflix, we’re pushing the boundaries even further, reimagining what a notebook can be, who can use it, and what they can do with it. And we’re making big investments to help make this vision a
Full Cycle Developers at Netflix
The year was 2012 and operating a critical service at Netflix was laborious. Deployments felt like walking through wet sand. Canarying was devolving into verifying endurance (“nothing broke after one week of canarying, let’s push it”) rather than correct functionality. Researching issues felt like bouncing a rubber ball between teams, hard to catch the root cause and harder yet to stop from bounci
Netflixにおける日本語字幕の導入
(Please note that this article is a localized (to Japanese) version of a corresponding tech blog article in the English language) Netflixでは、2015年9月の日本における配信サービス開始時から日本語字幕を提供しています。 今回のブログでは、日本語字幕提供に至るまでの技術的な取り組みについて説明します。 字幕ソースファイルの仕様、字幕ソースファイルからNetflix配信用字幕への変換モデル、Netflixにおける日本語字幕の納品モデルなどを取り上げます。さらに、W3C字幕規格Timed Text Markup Language 2 (TTML2)導入に向けた対応についても触れます。 2014年の終盤にかけて、Netflixでは2015年9月に予定していた日
Titus, the Netflix container management platform, is now open source
by Amit Joshi, Andrew Leung, Corin Dwyer, Fabio Kung, Sargun Dhillon, Tomasz Bak, Andrew Spyker, Tim Bozarth Today, we are open-sourcing Titus, our container management platform. Titus powers critical aspects of the Netflix business, from video streaming, recommendations and machine learning, big data, content encoding, studio technology, internal engineering tools, and other Netflix workloads. Ti
Implementing Japanese Subtitles on Netflix
Japanese subtitles were first made available on the Netflix service as a part of the Japanese launch in September 2015. This blog post provides a technical description of the work we did leading up to this launch. We cover topics including our specification for source subtitle files, the transformation model from source subtitle files to those deliverable on the Netflix service, the model for deli
Artwork Personalization at Netflix
By Ashok Chandrashekar, Fernando Amat, Justin Basilico and Tony Jebara For many years, the main goal of the Netflix personalized recommendation system has been to get the right titles in front each of our members at the right time. With a catalog spanning thousands of titles and a diverse member base spanning over a hundred million accounts, recommending the titles that are just right for each mem
Crafting a high-performance TV user interface using React
by Ian McKay The Netflix TV interface is constantly evolving as we strive to figure out the best experience for our members. For example, after A/B testing, eye-tracking research, and customer feedback we recently rolled out video previews to help members make better decisions about what to watch. We’ve written before about how our TV application consists of an SDK installed natively on the device
Netflix Chaos Monkey Upgraded
chaosmonkey — Chaos Monkey is a resiliency tool that helps applications tolerate random instance failures. The Freedom and Responsibility culture at Netflix doesn’t have a mechanism to force engineers to architect their code in any specific way. Instead, we found that we could build strong alignment around resiliency by taking the pain of disappearing servers and bringing that pain forward. We cre
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