Essential Suite — Artwork Producer Assistant

By: Hamid Shahid & Syed Haq

Introduction

Netflix continues to invest in content for a global audience with a diverse range of unique tastes and interests. Correspondingly, the member experience must also evolve to connect this global audience to the content that most appeals to each of them. Images that represent titles on Netflix (what we at Netflix call “ artwork” ) have proven to be one of the most effective ways to help our members discover the content they love to watch. We thus need to

By Aditya Mavlankar, Jan De Cock¹, Cyril Concolato, Kyle Swanson, Anush Moorthy and Anne Aaron

TL; DR

We need an alternative to JPEG that a) is widely supported, b) has better compression efficiency and c) has a wider feature set. We believe AV1 Image File Format (AVIF) has the potential. Using the framework we have open sourced, AVIF compression efficiency can be seen at work and compared against a whole range of image codecs that came before it.

Image compression at Netflix

Netflix

By Liwei Guo , Vivian Li , Julie Beckley , Venkatesh Selvaraj , and Jeff Watts

Today we are excited to announce that Netflix has started streaming AV1 to our Android mobile app. AV1 is a high performance, royalty-free video codec that provides 20% improved compression efficiency over our VP9† encodes. AV1 is made possible by the wide-ranging industry commitment of expertise and intellectual property within the Alliance for Open Media (AOMedia), of which Netflix is a founding member.

Our support for

Andreas Andreakis , Ioannis Papapanagiotou

Overview

Change-Data-Capture (CDC) allows capturing committed changes from a database in real-time and propagating those changes to downstream consumers [1][2]. CDC is becoming increasingly popular for use cases that require keeping multiple heterogeneous datastores in sync (like MySQL and ElasticSearch) and addresses challenges that exist with traditional techniques like dual-writes and distributed transactions [3][4].

In databases like MySQL and PostgreSQL, transaction logs are the source of CDC events. As

Netflix Hack Day — Fall 2019

By Tom Richards , Carenina Garcia Motion , and Leslie Posada

Hack Day at Netflix is an opportunity to build and show off a feature, tool, or quirky app. The goal is simple: experiment with new ideas/technologies, engage with colleagues across different disciplines, and have fun!

We know even the silliest idea can spur something more.

The most important value of our Hack Days is that they support a culture of innovation. We believe in this work, even if

by David Berg , Ravi Kiran Chirravuri , Romain Cledat , Savin Goyal , Ferras Hamad , Ville Tuulos

tl;dr Metaflow is now open-source! Get started at metaflow.org .

Netflix applies data science to hundreds of use cases across the company, including optimizing content delivery and video encoding. Data scientists at Netflix relish our culture that empowers them to work autonomously and use their judgment to solve problems independently. We want our data scientists to be curious and take smart risks that have the potential for high business impact.

Julie (Novak) Beckley, Andy Rhines, Jeffrey Wong, Matthew Wardrop, Toby Mao, Martin Tingley

Ever wonder why Netflix works so well when you’re streaming at home, on the train, or in a foreign hotel? Behind the scenes, Netflix engineers are constantly striving to improve the quality of your streaming service. The goal is to bring you joy by delivering the content you love quickly and reliably every time you watch. To do this, we have teams of experts that develop more efficient video and audio

by Shefali Vyas Dalal

AWS re:Invent is a couple weeks away and our engineers & leaders are thrilled to be in attendance yet again this year! Please stop by our “Living Room” for an opportunity to connect or reconnect with Netflixers. We’ve compiled our speaking events below so you know what we’ve been working on. We look forward to seeing you there!

Monday — December 2

1pm-2pm CMP 326-R Capacity Management Made Easy with Amazon EC2 Auto Scaling

Vadim

Page Simulation for Better Offline Metrics at Netflix

by David Gevorkyan , Mehmet Yilmaz , Ajinkya More , Gaurav Agrawal ,
Richard Wellington , Vivek Kaushal , Prasanna Padmanabhan , Justin Basilico

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 which movies and TV shows we present on each member’s homepage. Over the years, we have built a recommendation system that uses many different machine learning algorithms

by Artem Shtatnov and Ravi Srinivas Ranganathan

Almost a year ago we described our learnings from adopting GraphQL on the Netflix Marketing Tech team. We have a lot more to share since then! There are plenty of existing resources describing how to express a search query in GraphQL and paginate the results. This post looks at the other side of search: how to index data and make it searchable. Specifically, how our team uses the relationships and schemas defined within GraphQL to automatically build and maintain a search database.

Marketing Tech at Netflix