Scaling with Microservices and Vertical Decomposition – dev.otto.de https://dev.otto.de/2014/07/29/scaling-with-microservices-and-vertical-decomposition/…
1 Canvas教程 <canvas>是一个新的用于通过脚本(通常是JavaScript)绘图的HTML元素.例如,他可以用于绘图.制作图片的组合或者简单的动画(当然并不那么简单).It can for instance be used to draw graphs, make photo compositions or do simple (and not so simple) animations. 1.1 基本用法 Basic usage <canvas>元素 Let's s…
https://martinfowler.com/articles/microservices.html https://martinfowler.com/microservices/ 微服务,最早由Martin Fowler在他的官博中提出,原文和翻译如下: Microservicesa definition of this new architectural term The term "Microservice Architecture" has sprung up over t…
Microservices What are Microservices? What are Microservices - microservices.io Microservices - martinFowler.com What is Microservices? - SmartBear What are Microservices? - RedHat The What, Why, and How of a Microservices Architecture What are Micro…
原文地址 LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first week. Fast forward many years, and LinkedIn's product portfolio, member base, and server load has grown tremen…
We Recommend a Singular Value Decomposition Introduction The topic of this article, the singular value decomposition, is one that should be a part of the standard mathematics undergraduate curriculum but all too often slips between the cracks. Beside…
原文:http://www.ams.org/samplings/feature-column/fcarc-svd Introduction The topic of this article, the singular value decomposition, is one that should be a part of the standard mathematics undergraduate curriculum but all too often slips between the c…
From Zero to OAuth2 in Spring cloud Today I am presenting hours of research about a (apparently) simple question: “How can I maintain security in my microservices architecture?”. The task is to enable a simple but mighty possibility to secure spring…
@(131 - Machine Learning | 机器学习) 1 Feature Scaling transforms features to have range [0,1] according to the formula $x' = \frac{x-x_{min}}{x_{max}-x_{min}} $ 1.1 Sklearn - MinMaxScaler from sklearn.preprocessing import MinMaxScaler import numpy weigh…
