Hua Jiang and Kedar Sadekar talked about feature engineering using time rewinding in the context of Netflix Recommendations at an ML Platform meetup at LinkedIn HQ. Jan 24, 2018
![Netflix Recommendations Feature Engineering with Time Travel](https://cdn-ak-scissors.b.st-hatena.com/image/square/0aa998dc8b818d3188a97354f923f324ea151f5d/height=288;version=1;width=512/https%3A%2F%2Fcdn.slidesharecdn.com%2Fss_thumbnails%2Fnetflixrecsfeatureengtimetravel-180222070616-thumbnail.jpg%3Fwidth%3D640%26height%3D640%26fit%3Dbounds)
技術部のヨシオリです。 Netflix が Chaos Engineering の論文を公開して 2 年ほど経ちました。 クックパッドは最近、 Chaos Engineering を導入する事を決めました。 この記事ではその背景を紹介したいと思います。 そもそも Chaos Engineering とは Netflix では Failure Injection Testing として、営業時間中に意図的に障害を起す事をやっていました。Chaos Monkey というインスタンスとサービスを落すものから Chaos Gorilla、Kong という availability zone や region 単位で障害を発生させるものなどです。 その経験から Chaos Engineering というものが提唱されました。 Principles of Chaos Engineeringによれば C
Japanese subtitles were first made available on the Netflix service as a part of the Japanese launch in September 2015. This blog post provides a technical description of the work we did leading up to this launch. We cover topics including our specification for source subtitle files, the transformation model from source subtitle files to those deliverable on the Netflix service, the model for deli
“Aren’t you done with every interesting challenge already?” I get this question in various forms a lot. During interviews. At conferences, after we present on some of our technologies and practices. At meetups and social events. You have fully migrated to the Cloud, you must be done… You created multi-regional resiliency framework, you must be done… You launched globally, you must be done… You dep
We recently made a major architectural change to Zuul, our cloud gateway. Did anyone even notice!? Probably not… Zuul 2 does the same thing that its predecessor did — acting as the front door to Netflix’s server infrastructure, handling traffic from all Netflix users around the world. It also routes requests, supports developers’ testing and debugging, provides deep insight into our overall servic
Netflix’s engineering culture is predicated on Freedom & Responsibility, the idea that everyone (and every team) at Netflix is entrusted with a core responsibility. Within that framework they are free to operate with freedom to satisfy their mission. Accordingly, teams are generally responsible for all aspects of their systems, ranging from design, architecture, development, deployments, and opera
ここのところHystrixについて調べていたのですが、Netflixは他にもGitHub上で様々なOSSを公開しています。 github.com Javaのものが中心ですがPythonやGo、Cで書かれているものもあります。ライブラリ的なものからミドルウェアや運用ツールまで多岐に渡っており、NetflixがAWSを利用しているということもありAWS上での利用に特化したものもあります。また各プロダクトのドキュメントもしっかりしており、以下のような専用のサイトも立ち上げられており、社内で開発したものを積極的にOSS化するという方針が伺えます。 netflix.github.io HystrixやEurekaなどを筆頭に有名なものも多いのですが、なにぶん数が多くどのようなものがあるのかを把握するのも割と一苦労な感じなのですが、Netflixでは自社のOSSを紹介するMeetupが継続的に開催され
The journey to the cloud at Netflix began in 2008, and after seven years of diligent effort, we have finally completed… For a company, its billing solution is its financial lifeline, while at the same time, it is a visible representation of a company’s attitude towards its customers. A great customer experience is one of Netflix’s core values. Considering the sensitive nature of Billing for its di
How does Netflix build code before it’s deployed to the cloud? While pieces of this story have been told in the past, we decided it was time we shared more details. In this post, we describe the tools and techniques used to go from source code to a deployed service serving movies and TV shows to more than 75 million global Netflix members. The above diagram expands on a previous post announcing Sp
Our new Keystone data pipeline went live in December of 2015. In this article, we talk about the evolution of Netflix’s data pipeline over the years. This is the first of a series of articles about the new Keystone data pipeline. Netflix is a data-driven company. Many business and product decisions are based on insights derived from data analysis. The charter of the data pipeline is to collect, ag
Slides from the 2016/01/28 Advanced Amazon Web Services (AWS) Meetup. Netflix overviewed the usage of containers at Netflix. We covered technologies we are working on in the runtime (Titus) and developer experience (Newt). We talked about how the Titus container management system was different from others and our journey with Docker, Mesos, Netflix Fenzo and eventually Amazon Elastic Container Ser
Who should use Spinnaker?Spinnaker provides application management and deployment to help you release software changes with high velocity and confidence. Spinnaker is an open-source, multi-cloud continuous delivery platform that combines a powerful and flexible pipeline management system with integrations to the major cloud providers. If you are looking to standardize your release processes and im
After over a year of development and production use at Netflix, we’re excited to announce that our Continuous Delivery platform, Spinnaker, is available on GitHub. Spinnaker is an open source multi-cloud Continuous Delivery platform for releasing software changes with high velocity and confidence. Spinnaker is designed with pluggability in mind; the platform aims to make it easy to extend and enha
Testing Strategies In A Microservice Architectureを読んだを読んでいる途中に出てきた、Circuit Breakerと呼ばれる機構を調べてみました。Martin Fowler氏がこの記事で言及しているものでした。 このCircuit Breaker patternは、Release It! 本番用ソフトウェア製品の設計とデプロイのためにで描かれているような、本番環境化において発生する、複数システムが関係するからこそ発生する障害を抑えることも目的としたデザインパターンのようです。「複数システムが関係するからこそ発生する障害」とは、一部システムの負荷が高まりタイムアウトするといったことを含みます。 内容自体は、 障害検出のための共有のオブジェクト(Circuit Breacker)を用意して、監視・検出できるようにする ということらしいです。Ne
This talk discusses Linux profiling using perf_events (also called "perf") based on Netflix's use of it. It covers how to use perf to get CPU profiling working and overcome common issues. The speaker will give a tour of perf_events features and show how Netflix uses it to analyze performance across their massive Amazon EC2 Linux cloud. They rely on tools like perf for customer satisfaction, cost o
by Andrew Park, Darrell Denlinger, & Coburn Watson Netflix prioritizes innovation and reliability above efficiency, and as we continue to scale globally, finding opportunities that balance these three variables becomes increasingly difficult. However, every so often there is a process or application that can shift the curve out on all three factors; for Netflix this process was incorporating hybri
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
処理を実行中です
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く