Netflix SIRT releases Diffy: A Differencing Engine for Digital Forensics in the Cloud
Forest Monsen and Kevin Glisson, Netflix Security Intelligence and Response Team 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 focus their r
Evolution of Application Data Caching : From RAM to SSD
In 2013, we introduced EVCache a distributed in-memory caching solution based on memcached that offers low-latency, high-reliability caching and storage. It is well integrated with AWS and EC2, a Netflix OSS project, and in many occasions it is termed as “the hidden microservice”. Since then, EVCache has become a fundamental tier-0 service storing petabytes of data and hundred of billions of items
Auto Scaling Production Services on Titus
By Andrew Leung, Amit Joshi, and the rest of the Titus team. Over the past three years, Netflix has been investing in container technology. A large part of this investment has been around Titus, Netflix’s container management platform that was open sourced in April of 2018. Titus schedules application containers to be run across a fleet of thousands of Amazon EC2 instances. Early on Titus focused
Simplifying Media Innovation at Netflix with Archer
By Naveen Mareddy, Frank San Miguel, Rick Wong, Mangala Prabhu and Olof Johansson 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 algorithm right with high confidence without worrying about: Parallel processingCloud infrastructures like EC2
Netflix at Spark+AI Summit 2018
By Faisal Siddiqi A glimpse at Spark usage for Netflix RecommendationsApache 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.
Growth Engineering at Netflix — Accelerating Innovation
by Eric Eiswerth 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 before signing up. These prospective members arrive from over 190 countries around the world, and each person
Metacat: Making Big Data Discoverable and Meaningful at Netflix
by Ajoy Majumdar, Zhen Li 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 (via Hive), Druid, Elasticsearch, Redshift, Snowflake and MySql. Our platform supports Spark, Pre
The End of Video Coding?
In the IEEE Signal Processing Magazine issue November 2006 article “Future of Video Coding and Transmission” Prof. Edward Delp started by asking the panelists “Is video coding dead? Some feel that, with the higher coding efficiency of the H.264/MPEG-4 . . . perhaps there is not much more to do. I must admit that I have heard this compression is dead argument at least four times since I started wor
Lessons from Building Observability Tools at Netflix
Our mission at Netflix is to deliver joy to our members by providing high-quality content, presented with a delightful experience. We are constantly innovating on our product at a rapid pace in pursuit of this mission. Our innovations span personalized title recommendations, infrastructure, and application features like downloading and customer profiles. Our growing global member base of 125 milli
Open Sourcing Zuul 2
We are excited to announce the open sourcing of Zuul 2, Netflix’s cloud gateway. We use Zuul 2 at Netflix as the front door for all requests coming into Netflix’s cloud infrastructure. Zuul 2 significantly improves the architecture and features that allow our gateway to handle, route, and protect Netflix’s cloud systems, and helps provide our 125 million members the best experience possible. The C
Full Cycle Developers at Netflix
The year was 2012 and operating a critical service at Netflix was laborious. Deployments felt like walking through wet sand. Canarying was devolving into verifying endurance (“nothing broke after one week of canarying, let’s push it”) rather than correct functionality. Researching issues felt like bouncing a rubber ball between teams, hard to catch the root cause and harder yet to stop from bounci
Multi-Cloud Continuous Delivery with Spinnaker report now available.
by Emily Burns, Asher Feldman, Rob Fletcher, Tomas Lin, Justin Reynolds, Chris Sanden and Rob Zienert 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 ReportAt Netflix, we’ve built and use Spinnaker as a platform for continuous integration and deli
Netflixにおける日本語字幕の導入
(Please note that this article is a localized (to Japanese) version of a corresponding tech blog article in the English language) 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います。 今回のブログでは、日本語字幕提供に至るまでの技術的な取り組みについて説明します。 字幕ソースファイルの仕様、字幕ソースファイルからNetflix配信用字幕への変換モデル、Netflixにおける日本語字幕の納品モデルなどを取り上げます。さらに、W3C字幕規格Timed Text Markup Language 2 (TTML2)導入に向けた対応についても触れます。 2014年の終盤にかけて、Netflixでは2015年9月に予定していた日
Announcing the Netflix Research Website
We’re pleased to announce that we’ve launched a new website at research.netflix.com that provides an overview of the research that we do here at Netflix. We have many amazing researchers working on a variety of hard problems and are happy to share some of our work with the world. Netflix embraces innovation and has been investing in research to power that innovation for many years. This started wi
Titus, the Netflix container management platform, is now open source
by Amit Joshi, Andrew Leung, Corin Dwyer, Fabio Kung, Sargun Dhillon, Tomasz Bak, Andrew Spyker, Tim Bozarth Today, we are open-sourcing Titus, our container management platform. Titus powers critical aspects of the Netflix business, from video streaming, recommendations and machine learning, big data, content encoding, studio technology, internal engineering tools, and other Netflix workloads. Ti
ChAP: Chaos Automation Platform
We are excited to announce ChAP, the newest member of our chaos tooling family! Chaos Monkey and Chaos Kong ensure our resilience to instance and regional failures, but threats to availability can also come from disruptions at the microservice level. FIT was built to inject microservice-level failure in production, and ChAP was built to overcome the limitations of FIT so we can increase the safety
Developer Experience Lessons Operating a Serverless-like Platform at Netflix
By Vasanth Asokan, Ludovic Galibert and Sangeeta Narayanan The Netflix API is based on a dynamic scripting platform that handles thousands of changes per day. This platform allows our client developers to create a customized API experience on over a thousand device types by executing server side adapter code in response to HTTP requests. Developers are only responsible for the adapter code they wr
Content Popularity for Open Connect
There are many reasons why Netflix cares about the popularity of our TV shows and movies. On the Open Connect Content Delivery team, we predict content popularity to maximize our infrastructure efficiency. Some months ago, we blogged about how we use proactive caching to keep the content on our global network of Open Connect Appliances (OCAs) current. We also recently gave an overview of some of t
Spinnaker Orchestration
Author: Rob Fletcher When the Spinnaker project first started more than two years ago we implemented Orca — Spinnaker’s orchestration engine µservice — using Spring Batch. It wasn’t an entirely unreasonable fit at the time. It gave us atomic, compartmentalized units of work (tasks in a Spinnaker pipeline), retry semantics, the ability to define branching and joining workflows, listeners that could
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Engineers Making Movies (AKA Open Source Test Content)