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)…

How Netflix brings safer and faster streaming experience to the living room on crowded networks…

At Netflix, we are obsessed with the best streaming experiences. We want playback to start instantly and to never stop unexpectedly in any network environment. We are also committed to protecting users’ privacy and service security without sacrificing any part of the playback experience. To achieve that…

Beyond Interactive: Notebook Innovation at Netflix

Notebooks have rapidly grown in popularity among data scientists to become the de facto standard for quick prototyping and exploratory analysis. At Netflix, we’re pushing the boundaries even further, reimagining what a notebook can be, who can use it, and…

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…

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…

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…

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…

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…

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 …

Netflix at the Spinnaker Summit 2018

Since releasing Spinnaker as an open source project in late 2015, the Spinnaker user and contributor community has grown by leaps and bounds. Our strong partnership with Google and other companies has led to a plethora of innovations and features that enable rapid, safe, and reliable delivery…

Open Sourcing Zuul 2

How Netflix uses Druid for Real-time Insights to Ensure a High-Quality Experience

Ensuring a consistently great Netflix experience while continuously pushing innovative technology updates is no easy feat. How can we be confident that updates are not harming our users? And that we’re actually making measurable improvements when we intend to? Using real-time logs from playback devices as a…

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…

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…

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…

Byte Down: Making Netflix’s Data Infrastructure Cost-Effective

Background on data efficiency At Netflix, we invest heavily in our data infrastructure which is composed of dozens of data platforms, hundreds of data producers and consumers, and petabytes of data. At many other organizations, an effective way to manage data infrastructure costs is to…

Part 2: Scheduling Notebooks at Netflix

At Netflix we’ve put substantial effort into adopting notebooks as an integrated development platform. The idea started as a discussion of what development and collaboration interfaces might look like in the future. It evolved into a strategic bet on notebooks, both as…

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…

Machine Learning for a Better Developer Experience

Imagine having to go through 2.5GB (not often, but does happen time to time) log entries from a failed software build — 3 million lines — to search for a bug or a regression that happened on line 1M. It’s probably not even doable manually! However…

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…

Protecting a Story’s Future with History and Science

Kylee’s parents after their wedding in 1978. I — Kylee — have two photos from my parents’ wedding. Just two. This year they celebrated 40 years of marriage, so both photos were shot on film. Both capture a joy and awkwardness that come with young weddings. They’re…

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…

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…

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…

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…