Netflixにおける日本語字幕の導入

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 …

Key Challenges with Quasi Experiments at Netflix

At Netflix, when we can’t run A/B experiments we run quasi experiments! We run quasi experiments with various objectives such as non-member experiments focusing on acquisition, member experiments focusing on member engagement, or video streaming experiments focusing on content delivery. Consolidating on one methodology…

Page Simulator

At Netflix, we spend a lot of effort to make it easy for our members to find content they will love. To make this happen, we personalize many aspects of our service, including…

Simplifying Media Innovation at Netflix with Archer

Imagine you are developing a quick prototype to sift through all the frames of the movie Bright to find the best shots of Will Smith with an action-packed background. Your goal is to get the computer vision…

The Netflix Cosmos Platform

by Frank San Miguel on behalf of the Cosmos team Introduction Cosmos is a computing platform that combines the best aspects of microservices with asynchronous workflows and serverless functions. Its sweet spot is applications that involve resource-intensive algorithms coordinated via complex, hierarchical workflows that last anywhere from minutes to years. It…

Netflix Public Bug Bounty, 1 year later

As Netflix continues to create entertainment people love, the security team continues to keep our members, partners, and employees secure. The security research community has partnered with us to improve the security of the Netflix service for the past few years through our responsible…

SVT-AV1: an open-source AV1 encoder and decoder

SVT-AV1 is an open-source AV1 codec implementation hosted on GitHub https://github.com/OpenVisualCloud/SVT-AV1/ under a BSD + patent license. As mentioned in our earlier blog post, Intel and Netflix have been collaborating on the SVT-AV1 encoder and decoder framework since August 2018. The teams have been working closely on SVT-AV1 development, discussing…

Quasi Experimentation at Netflix

Experimentation informs much of our decision making at Netflix. We design, analyze, and execute experiments with rigor so that we have confidence that the changes we’re making are the right ones for our members and our business. We have many years of experience running…

Engineers Making Movies (AKA Open Source Test Content)

If you’re a die-hard Netflix fan, you may have already stumbled onto the dark and brooding story of a timeless struggle between man and nature, water and fountain, ball and tether known much more plainly as Example Short. In the good old days of…

Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

Imagine yourself in the role of a data-inspired decision maker staring at a metric on a dashboard about to make a critical business decision but pausing to ask a question — “Can I run a check myself to understand what data is behind…

Netflix Drive

Written by Vikram Krishnamurthy, Kishore Kasi, Abhishek Kapatkar, Tejas Chopra, Prudhviraj Karumanchi, Kelsey Francis, Shailesh Birari In this post, we are introducing Netflix Drive, a Cloud drive for media assets and providing a high level overview of some of its features and interfaces. We intend this to be a first…

Re-Architecting the Video Gatekeeper

This is the story about how the Content Setup Engineering team used Hollow, a Netflix OSS technology, to re-architect and simplify an essential component in our content pipeline — delivering a large amount of business value in the process. The Context Each movie and show on the Netflix service is carefully curated…

Growth Engineering at Netflix — Accelerating Innovation

Millions of people visit Netflix every day. Many of them are already Netflix members, looking to enjoy their favorite movies and TV shows, and we work hard to ensure they have a great experience. Others are not yet members, and are looking to better understand our service…

ML Platform Meetup: Infra for Contextual Bandits and Reinforcement Learning

Infrastructure for Contextual Bandits and Reinforcement Learning — theme of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019. Contextual and Multi-armed Bandits enable faster and adaptive alternatives to traditional A/B Testing. They enable rapid learning and better decision-making for product rollouts. Broadly speaking, these approaches…

Introducing Netflix Timed Text Authoring Lineage

By: Bhanu Srikanth, Andy Swan, Casey Wilms, Patrick Pearson The Art of Dubbing and Subtitling Dubbing and subtitling are inherently creative processes. At Netflix, we strive to make shows as joyful to watch in every language as in the original language, whether a member watches with original or dubbed audio, closed captions…

Engineering to Improve Marketing Effectiveness (Part 2) — Scaling Ad Creation and Management

In the first part of this series of blogs, we described our philosophy, motivations, and approach to blending ad technology into our marketing. In addition, we laid out some of the engineering undertakings to solve creative development and localization at scale. In this Part-2…

Announcing the Netflix Post Technology Alliance

You’re working on the next great show or film that will deliver to Netflix. You know Netflix has a high quality bar for its content and you want the delivery to go smoothly. Do you know if the tools you have invested in can…

A Day in the Life of an Experimentation and Causal Inference Scientist @ Netflix

Source credit: Netflix Within the rapid expansion of data-related roles in the last decade, the title Data Scientist has emerged as an umbrella term for myriad skills and areas of business focus. What does this title mean within a given company, or even within a given industry…

Python at Netflix

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…

Introducing SVT-AV1: a scalable open-source AV1 framework

Netflix Headquarters, Winchester Circle. Netflix headquarters circa 2014. It’s a nice building with good architecture! This was the primary home of Netflix for a number of years during the company’s growth, but at some point Netflix had outgrown its home and needed more space. One approach to solve this problem would have been to…

Data Engineers of Netflix — Interview with Samuel Setegne

This post is part of our “Data Engineers of Netflix” interview series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Samuel Setegne is a Senior Software Engineer on the Core Data Science and Engineering team. Samuel and his team build tools and frameworks…

Edgar: Solving Mysteries Faster with Observability

by Elizabeth Carretto Our Team — Kevin Lew, Maulik Pandey, Narayanan Arunachalam, Dustin Haffner, Andrei Ushakov, Seth Katz, Greg Burrell, Ram Vaithilingam, Mike Smith and Elizabeth Carretto Everyone loves Unsolved Mysteries. There’s always someone who seems like the surefire culprit. There’s a clear motive, the perfect opportunity, and an…

Netflix at MIT CODE 2020

In November, Netflix was a proud sponsor of the 2020 Conference on Digital Experimentation (CODE), hosted by the MIT Initiative on the Digital Economy. As well as providing sponsorship, Netflix data scientists were active participants, with three contributions. Eskil Forsell and colleagues presented a poster describing Success stories…

Netflix Cloud Security: Detecting Credential Compromise in AWS

Credential compromise is an important concern for anyone operating in the cloud. The problem becomes more obvious over time, as organizations continue to adopt cloud resources as part of their infrastructure without maintaining an accompanying capability to observe and react to these compromises…

Remote Workstations for the Discerning Artists

Netflix is poised to become the world’s most prolific producer of visual effects and original animated content. To meet that demand, we need to attract the world’s best artistic talent. Artists like to work at places where they can create groundbreaking entertainment instead of worrying about getting…