From 66662a23e3f6bbff8afc98d10276bec481eb404b Mon Sep 17 00:00:00 2001 From: binhnguyennus Date: Sat, 6 Mar 2021 15:50:17 +0800 Subject: [PATCH] Remove 4 dead links, Rakuten --- README.md | 4 ---- 1 file changed, 4 deletions(-) diff --git a/README.md b/README.md index b1bfa8e..c1b3cc5 100644 --- a/README.md +++ b/README.md @@ -50,7 +50,6 @@ An updated and organized reading list for illustrating the patterns of scalable, * [Stateless vs Stateful Scalability](http://ithare.com/scaling-stateful-objects/) * [Scale Up vs Scale Out](https://www.brianjgraf.com/scalability-scale-up-scale-out-care/) * [Scale Up vs Scale Out: Hidden Costs](https://blog.codinghorror.com/scaling-up-vs-scaling-out-hidden-costs/) -* [Best Practices for Continuous Delivery](https://techblog.rakuten.co.jp/2018/02/06/cd-the-best-practice/) * [ACID and BASE](https://neo4j.com/blog/acid-vs-base-consistency-models-explained/) * [Blocking/Non-Blocking and Sync/Async](https://blogs.msdn.microsoft.com/csliu/2009/08/27/io-concept-blockingnon-blocking-vs-syncasync/) * [Performance and Scalability of Databases](https://use-the-index-luke.com/sql/testing-scalability) @@ -108,7 +107,6 @@ An updated and organized reading list for illustrating the patterns of scalable, * [Microservice at SoundCloud](https://developers.soundcloud.com/blog/inside-a-soundcloud-microservice) * [Operate Kubernetes Reliably at Stripe](https://stripe.com/blog/operating-kubernetes) * [Cross-Cluster Traffic Mirroring with Istio at Trivago](https://tech.trivago.com/2020/06/10/cross-cluster-traffic-mirroring-with-istio/) - * [Kubernetes Traffic Routing (2 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/09/28/k8s-routing2/) * [Agrarian-Scale Kubernetes (3 parts) at New York Times](https://open.nytimes.com/agrarian-scale-kubernetes-part-3-ee459887ed7e) * [Nanoservices at BBC](https://medium.com/bbc-design-engineering/powering-bbc-online-with-nanoservices-727840ba015b) * [PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg](https://www.techatbloomberg.com/blog/powerfulseal-testing-tool-kubernetes-clusters/) @@ -282,7 +280,6 @@ An updated and organized reading list for illustrating the patterns of scalable, * [Kafka at Pinterest](https://medium.com/pinterest-engineering/how-pinterest-runs-kafka-at-scale-ff9c6f735be) * [Kafka at Trello](https://tech.trello.com/why-we-chose-kafka/) * [Kafka at Salesforce](https://engineering.salesforce.com/how-apache-kafka-inspired-our-platform-events-architecture-2f351fe4cf63) - * [Kafka at Rakuten](https://techblog.rakuten.co.jp/2016/01/28/rakuten-paas-kafka/) * [Kafka at The New York Times](https://open.nytimes.com/publishing-with-apache-kafka-at-the-new-york-times-7f0e3b7d2077) * [Kafka at Yelp](https://engineeringblog.yelp.com/2016/07/billions-of-messages-a-day-yelps-real-time-data-pipeline.html) * [Kafka at Criteo](https://medium.com/criteo-labs/upgrading-kafka-on-a-large-infra-3ee99f56e970) @@ -718,7 +715,6 @@ An updated and organized reading list for illustrating the patterns of scalable, * [Personalised Recommender Systems at BBC](https://medium.com/bbc-design-engineering/developing-personalised-recommender-systems-at-the-bbc-e26c5e0c4216) * [Machine Learning (2 parts) at Condé Nast](https://technology.condenast.com/story/handbag-brand-and-color-detection) * [Natural Language Processing and Content Analysis (2 parts) at Condé Nast](https://technology.condenast.com/story/natural-language-processing-and-content-analysis-at-conde-nast-part-2-system-architecture) - * [Machine Learning Applications In The E-commerce Domain (4 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/07/12/machine-learning-applications-in-the-e-commerce-domain-4/) * [Mapping the World of Music Using Machine Learning (2 parts) at iHeartRadio](https://tech.iheart.com/mapping-the-world-of-music-using-machine-learning-part-2-aa50b6a0304c) * [Machine Learning to Improve Streaming Quality at Netflix](https://medium.com/netflix-techblog/using-machine-learning-to-improve-streaming-quality-at-netflix-9651263ef09f) * [Machine Learning to Match Drivers & Riders at GO-JEK](https://blog.gojekengineering.com/how-we-use-machine-learning-to-match-drivers-riders-b06d617b9e5)