How Netflix microservices tackle dataset pub-sub

Introduction In a microservice architecture such as Netflix’s, propagating datasets from a single source to multiple downstream destinations can be challenging. These datasets can represent anything from service configuration to the results of a batch job, are often needed in-memory to optimize access and must be updated as…

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…

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…

Performance comparison of video coding standards: an adaptive streaming perspective

“This is my advice to people: Learn how to cook, try new recipes, learn from your mistakes, be fearless, and above all have fun” — Julia Child (American chef, author, and television personality) At Netflix, we are continually refining the recipes we use to serve your favorite shows and movies…

Netflix SIRT releases Diffy: A Differencing Engine for Digital Forensics in the Cloud

Can you spot the difference? Hint: it’s not the bow tie. The Netflix Security Intelligence and Response Team (SIRT) announces the release of Diffy under an Apache 2.0 license. Diffy is a triage tool to help digital forensics and incident response (DFIR) teams quickly identify compromised hosts on which to…

Empowering the Visual Effects Community with the NetFX Platform

At Netflix, we want to entertain our global membership with series and films from around the world. In line with that, we’re excited to announce NetFX, a cloud-based platform that will make it easier for…

Data Compression for Large-Scale Streaming Experimentation

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…

Production Media Management: Transforming Media Workflows by leveraging the Cloud

In this post, we will share a behind-the-scenes look at how Netflix delivers technology and infrastructure to help production…

Beyond REST

by Dane Avilla The entertainment industry has struggled with COVID-19 restrictions impacting productions around the globe. Since early 2020, Netflix has been iteratively developing systems to provide internal stakeholders and business leaders with up-to-date tools and dashboards with the latest information on the pandemic. These software solutions allow executive leadership…

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…

Data Engineers of Netflix — Interview with Dhevi Rajendran

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. Dhevi Rajendran is a Data Engineer on the Growth Data Science and Engineering team. Dhevi joined Netflix in July 2020 and is one…

Android Rx onError Guidelines

“Creating a good API is hard.” — anyone who has created an API used by others As with any API, wrapping your data stream in a Rx observable requires consideration for reasonable error handling and intuitive behavior. The following guidelines are intended to help developers create consistent…

Keeping Customers Streaming — The Centralized Site Reliability Practice at Netflix

We’re privileged to be in the business of bringing joy to our customers at Netflix. Whether it’s a compelling new series or an innovative product feature, we strive to provide a best-in-class service that people love and can enjoy anytime, anywhere…

Open Sourcing the Netflix Domain Graph Service Framework: GraphQL for Spring Boot

Netflix has developed a Domain Graph Service (DGS) framework and it is now open source. The DGS framework simplifies the implementation of GraphQL, both for standalone and federated GraphQL services. Our framework is battle-hardened by our…

Evolving Regional Evacuation

At Netflix we prioritize innovation and velocity in pursuit of the best experience for our 150+ million global customers. This means that our microservices constantly evolve and change, but what doesn’t change is our responsibility to provide a highly available service that delivers 100+ million hours of daily streaming to…

Keystone Real-time Stream Processing Platform

Hawkins: Diving into the Reasoning Behind our Design System

by Hawkins team member Joshua Godi; with cover art from Martin Bekerman and additional imagery from Wiki Chaves Hawkins may be the name of a fictional town in Indiana, most widely known as the backdrop for one of Netflix’s most popular TV series “Stranger Things,” but the name is so…

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…

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…

Computational Causal Inference at Netflix

Every Netflix data scientist, whether their background is from biology, psychology, physics, economics, math, statistics, or biostatistics, has made meaningful contributions to the way Netflix analyzes causal effects. Scientists from these fields have made many advancements in causal effects research in the past few decades, spanning…

Netflix at AWS re:Invent 2019

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…

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 …

HDMI — Scaling Netflix Certification

At Netflix, we take the task of preserving the creative vision of our content all the way to a subscriber TV screen very seriously. This significantly increases the scope of our application integration and certification processes for streaming devices like set-top-boxes (STBs) and…

Analytics at Netflix: Who we are and what we do

by Molly Jackman & Meghana Reddy Explained: Season 1 (Photo Credit: Netflix) Across nearly every industry, there is recognition that data analytics is key to driving informed business decision-making. But there is far less agreement on what that term “data analytics” actually means — or what to call the people responsible for the work. Even within…

Achieving observability in async workflows

Managing and operating asynchronous workflows can be difficult without the proper tools and architecture that puts observability, debugging, and tracing at the forefront. Imagine getting paged outside normal work hours — users are having trouble with the application you’re responsible for…