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…

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…

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…

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…

Spinnaker Sets Sail to the Continuous Delivery Foundation

Since releasing Spinnaker to the open source community in 2015, the platform has flourished with the addition of new cloud providers, triggers, pipeline stages, and much more. Myriad new features, improvements, and innovations have been added by an ever growing, actively engaged community. Each new innovation has…

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 …

Open-Sourcing riskquant, a library for quantifying risk

Evolution of Netflix Conductor:

By Anoop Panicker and Kishore Banala Conductor is a workflow orchestration engine developed and open-sourced by Netflix. If you’re new to Conductor, this earlier blogpost and the documentation should help you get started and acclimatized to Conductor. Netflix Conductor: A microservices orchestrator visibility into distributed workflowsmedium.com In the last two years since inception, Conductor has seen wide adoption and…

ConsoleMe: A Central Control Plane for AWS Permissions and Access

By Curtis Castrapel, Patrick Sanders, and Hee Won Kim At AWS re:Invent 2020, we open sourced two new tools for managing multi-account AWS permissions and access. We’re very excited to bring you ConsoleMe (pronounced: kuhn-soul-mee), and its CLI utility, Weep…

Essential Suite — Artwork Producer Assistant

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…

Open Sourcing Zuul 2

Engineering a Studio Quality Experience With High-Quality Audio at Netflix

Remember the epic opening sequence of Stranger Things 2? The thrill of that car chase through Pittsburgh not only introduced a whole new set of mysteries, but it returned…

Bringing Rich Experiences to Memory-constrained TV Devices

Netflix has over 148M paid members streaming on more than half a billion devices spanning over 1,900 different types. In the TV space alone, there are hundreds of device types that run the Netflix app. We need to support the same rich Netflix…

Optimizing data warehouse storage

Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3, and each day we ingest and create additional Petabytes. At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions)…

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…

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…

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…

Full Cycle Developers at Netflix

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…

Streaming Video Experimentation at Netflix: Visualizing Practical and Statistical Significance

Streaming video experimentation at Netflix seeks to optimize the Quality of Experience (QoE for short) of the videos we stream to our 130 million members around the world. To measure QoE, we look at a wide variety of metrics for each playback session, including play delay; the…

Packaging award-winning shows with award-winning technology

Introduction In previous blog posts, our colleagues at Netflix have explained how 4K video streams are optimized, how even legacy video streams are improved and more recently how new audio codecs can provide better aural experiences to our members. In all these cases, prior to being delivered through…

Design Principles for Mathematical Engineering in Experimentation Platform at Netflix

At Netflix, we have data scientists coming from many backgrounds such as neuroscience, statistics and biostatistics, economics, and physics; each of these backgrounds has a meaningful contribution to how experiments should be analyzed. To unlock these innovations we…

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…

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…

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…