Netflix at Spark+AI Summit 2018

A glimpse at Spark usage for Netflix Recommendations Apache Spark has been an immensely popular big data platform for distributed computing. Netflix has been using Spark extensively for various batch and stream-processed workloads. A substantial list of use cases for Spark computation come from the various applications in the domain of content recommendations and personalization…

Trace Event, Chrome and More Profile Formats on FlameScope

Less than a year ago, FlameScope was released as a proof of concept for a new profile visualization. Since then, it helped us, and many other users, to easily find and fix performance issues, and allowed us to see patterns that we had never noticed before in our profiles. As…

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…

Edgar: Solving Mysteries Faster with Observability

by Elizabeth Carretto Our Team — Kevin Lew, Maulik Pandey, Narayanan Arunachalam, Dustin Haffner, Andrei Ushakov, Seth Katz, Greg Burrell, Ram Vaithilingam, Mike Smith and Elizabeth Carretto Everyone loves Unsolved Mysteries. There’s always someone who seems like the surefire culprit. There’s a clear motive, the perfect opportunity, and an…

Delta: A Data Synchronization and Enrichment Platform

Andreas Andreakis, Falguni Jhaveri, Ioannis Papapanagiotou, Mark Cho, Poorna Reddy, Tongliang Liu Overview It is a commonly observed pattern for applications to utilize multiple datastores where each is used to serve a specific need such as storing the canonical form of data (MySQL etc.), providing advanced search capabilities (ElasticSearch etc.), caching…

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…

Evolution of Application Data Caching : From RAM to SSD

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…

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…

Multi-Cloud Continuous Delivery with Spinnaker report now available.

We’re pleased to announce the release of our O’Reilly report, Continuous Delivery with Spinnaker. The report is available to download for free on the Spinnaker website. ( Pdf | Epub | Mobi ) About The Report At…

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 …

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…

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…

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…

A Day in the Life of an Experimentation and Causal Inference Scientist @ Netflix

Source credit: Netflix Within the rapid expansion of data-related roles in the last decade, the title Data Scientist has emerged as an umbrella term for myriad skills and areas of business focus. What does this title mean within a given company, or even within a given industry…

Seamlessly Swapping the API backend of the Netflix Android app

by Rohan Dhruva, Ed Ballot As Android developers, we usually have the luxury of treating our backends as magic boxes running in the cloud, faithfully returning us JSON. At Netflix, we have adopted the Backend for Frontend (BFF) pattern: instead of having one general purpose “backend API”, we have one…

Optimized shot-based encodes for 4K: Now streaming!

Netflix has an ever-expanding collection of titles which customers can enjoy in 4K resolution with a suitable device and subscription plan. Netflix creates premium bitstreams for those titles in addition to the catalog-wide 8-bit stream profiles¹. Premium features comprise a…

Telltale: Netflix Application Monitoring Simplified

Our Telltale Vision An alert fires and you get paged in the middle of the night. A metric crossed a threshold. You’re half awake and wondering, “Is there really a problem or is this just an alert…

Data Engineers of Netflix — Interview with Samuel Setegne

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. Samuel Setegne is a Senior Software Engineer on the Core Data Science and Engineering team. Samuel and his team build tools and frameworks…

Open Sourcing Zuul 2

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…

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…

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…

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…

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…