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…

Ready for changes with Hexagonal Architecture

As the production of Netflix Originals grows each year, so does our need to build apps that enable efficiency throughout the entire creative process. Our wider Studio Engineering Organization has built numerous apps that help content progress from pitch (aka screenplay) to playback: ranging…

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…

Growth Engineering at Netflix — Automated Imagery Generation

Background There’s a good chance you’ve probably visited the Netflix homepage. In the Growth Engineering team, we refer to this as the top of the signup funnel. For more background on the signup funnel and Growth Engineering’s role in the signup funnel, please read our initial post on…

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…

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…

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…

How Netflix uses eBPF flow logs at scale for network insight

Netflix has developed a network observability sidecar called Flow Exporter that uses eBPF tracepoints to capture TCP flows at near real time. At much less than 1% of CPU and memory on the instance, this highly performant sidecar provides…

Detecting Performance Anomalies in External Firmware Deployments

Netflix has over 139M members streaming on more than half a billion devices spanning over 1,700 different types of devices from hundreds of brands. This diverse device ecosystem results in a high dimensionality feature space, often with sparse data, and can make identifying device performance issues challenging…

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…

Introducing Dispatch

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 effectively…

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…

Metacat: Making Big Data Discoverable and Meaningful at Netflix

Most large companies have numerous data sources with different data formats and large data volumes. These data stores are accessed and analyzed by many people throughout the enterprise. At Netflix, our data warehouse consists of a large number of data sets stored in Amazon S3…

Enhancing the Netflix UI Experience with HDR

Some of you have probably heard about HDR, or High Dynamic Range, which can produce a higher level of brightness, a wider range of colors, and an increased level of detail and accuracy that empowers visual storytellers to deliver more impactful experiences for…

Improving our video encodes for legacy devices

Netflix has been one of the pioneers of streaming video-on-demand content — we announced our intention to stream video over 13 years ago, in January 2007 — and have only increased both our device and content reach since then…

Unbundling Data Science Workflows with Metaflow and AWS Step Functions

tl;dr Today, we are releasing a new job scheduler integration with AWS Step Functions. This integration allows the users of Metaflow to schedule their production workflows using a highly available, scalable, maintenance-free service, without…

Cache warming: Agility for a stateful service

EVCache has been a fundamental part of the Netflix platform (we call it Tier-1), holding Petabytes of data. Our caching layer serves multiple use cases from signup, personalization, searching, playback, and more. It is comprised of thousands of nodes in…

Making our Android Studio Apps Reactive with UI Components & Redux

Recently Netflix has started building mobile apps to bring technology and innovation to our Studio Physical Productions, the portion of the business responsible for producing our TV shows and movies. Our very first mobile app is called Prodicle and was…

Open Sourcing Zuul 2

How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

Netflix’s engineering culture is predicated on Freedom & Responsibility, the idea that everyone (and every team) at Netflix is entrusted with a core responsibility and they are free to operate with freedom to satisfy their mission. This…

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…

Open Sourcing Mantis: A Platform For Building Cost-Effective, Realtime, Operations-Focused…

Today we’re excited to announce that we’re open sourcing Mantis, a platform that helps Netflix engineers better understand the behavior of their applications to ensure the highest quality experience for our members. We…

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…

Lessons from Building Observability Tools at Netflix

Netflix Studio Engineering Overview

Netflix is revolutionizing the way a modern studio operates. Our mission in Studio Engineering is to build a unified, global, and digital studio that powers the effective production of amazing content. Studio Engineering at Netflix …