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A capability model for microservices

In this article by Rajesh RV , the author of Spring Microservices , you will learn aboutthe concepts of microservices. More than sticking to definitions, it is better to understand microservices by examining some common characteristics of microservices that are seen across many successful microservices implementations. Spring Boot is an ideal framework to implement microservices. In this article, we will examine how to implement microservices using Spring Boot with an example use case. Beyond services, we will have to be aware of the challenges around microservices implementation. This article will also talk about some of the common challenges around microservices. A successful microservices implementation has to have some set of common capabilities. In this article, we will establish a microservices capability model that can be used in a technology-neutral framework to implement large-scale microservices.

Backup and Recovery for Oracle SOA Suite 12C

 In this article written by Ahmed Aboulnaga , Arun Pareek , and Harold Dost , authors of the book Oracle SOA Suite 12c Administrator's Guide , you have already recognized the importance of establishing well-defined backup and recovery procedures as an administrator. It is easy to write in length on this topic alone, discussing various backup, restore, failover, migration, and disaster recovery strategies. Fortunately, we will focus on the most important areas in this chapter to simplify the process for you as best as we can. As long as you understand a few core concepts regarding the overall backup and recovery strategy for Oracle SOA Suite 12 c , you can implement it in any number of ways. Establishing a backup and restore strategy is important because it provides you the ability to restore your environment in the event of a critical infrastructure or hardware failure. For instance, if you experience a hard drive failure, the disks may have to be replaced and the software restored from backup. It also provides you the ability to restore your environment to a previously working snapshot in the event of a faulty patch, faulty code deployment, or faulty configuration. In some cases, these faulty updates are not undoable and thus a restore may be needed. In this chapter, we will cover the following key areas: Understanding what needs to be backed up The rrecommended backup strategy Implementing the backup process Recovery strategies (For more resources related to this topic, see here .)

Tinkering Around in Django JavaScript Integration

One of the great joys of programming is not when we are trying to get the bare essentials basically working, but when the system is working as a whole, and we start to ask, "What about this? What about that?" One positive sense of the term "hacking" can refer to this tinkering, and it can be a joy to tinker with an already working system to see what enhancements are possible. Here we will tinker with the system and make some minor tweaks and two slightly more major enhancements. In this article, by Jonathan Hayward , author of Django JavaScript Integration: AJAX and jQuery we will cover: Minor bugfixes and enhancements A more usable input solution for passwords Telling an (approximate) local time for other people we are working with, who may be in different time zones

Active Directory Domain Services 2016

In this article, by  Dishan Francis , the author of the book  Mastering Active Directory , we will see AD DS features, privileged access management, time based group memberships. Microsoft, released Active Directory domain services 2016 at a very interesting time in technology. Today identity infrastructure requirements for enterprise are challenging, most of the companies uses cloud services for their operations (Software as a Service—SaaS) and lots moved infrastructure workloads to public clouds.

Introduction to Titanic Datasets

In this article by  Alexis Perrier , author of the book  Effective Amazon Machine Learning  says artificial intelligence and big data have become a ubiquitous part of our everyday lives; cloud-based machine learning services are part of a rising billion-dollar industry. Among the several such services currently available on the market, Amazon Machine Learning stands out for its simplicity. Amazon Machine Learning was launched in April 2015 with a clear goal of lowering the barrier to predictive analytics by offering a service accessible to companies without the need for highly skilled technical resources.

Building a Strong Foundation

In this article, by Mickey Macdonald , author of the book Mastering C++ Game Development , we will cover how these libraries can work together and build some of the libraries needed to round out the structure.

Creating Fabric Policies

 In this article by  Stuart Fordham , the author of the book Cisco ACI Cookbook , helps us to understand ACI and the APIC and also explains us how to create fabric policies.

Convolutional Neural Networks with Reinforcement Learning

In this article by Antonio Gulli , Sujit Pal , the authors of the book  Deep Learning with Keras , we will learn about reinforcement learning, or more specifically deep reinforcement learning, that is, the application of deep neural networks to reinforcement learning. We will also see how convolutional neural networks leverage spatial information and they are therefore very well suited for classifying images.

Synchronization – An Approach to Delivering Successful Machine Learning Projects

 “In the midst of chaos, there is also opportunity”                                                                                                                - Sun Tzu In this article, by Cory Lesmeister , the author of the book Mastering Machine Learning with R - Second Edition , Cory provides insights on ensuring the success and value of your machine learning endeavors.

Deploying First Container

In this article by  Srikant Machiraju , author of the book  Learning Windows Server Containers , we will get acquainted with containers and containerization.  Containerization  helps you build software in layers,containersinspiredistributed development, packaging, and publishing in the form of containers. Developers or IT administrators just have to choose a BaseOS Image, create customized layers as per their requirements, and distribute using Public or Private Repositories.Microsoft and Docker together haveprovided an amazing toolset that helps you build and deploy containers within no time. It is very easy to setup a dev/test environment as well. Microsoft Windows Server Operating System or Windows 10 Desktop OS comes with plug and play features for running Windows Server containers or Hyper-V Containers.Docker Hub,a public repository for images,serves as a huge catalogue of customized images built by community or docker enthusiasts. The images on DockerHub are freely available for anyone to download, customize,and distribute images. In this article, we will learn how to create and configure container development environments. The following are a few more concepts that you will learn in this article: Preparing Windows Server Containers Environment Pulling images from Docker Hub Installing Base OS Images

Getting Started with Metasploitable2 and Kali Linux

In this article, by  Michael Hixon , the author of the book,  Kali Linux Network Scanning Cookbook - Second Edition , we will be covering: Installing Metasploitable2 Installing Kali Linux Managing Kali services

Supervised Learning: Classification and Regression

In this article by Alexey Grigorev , author of the book Mastering Java for Data Science , we will look at how to do pre-processing of data in Java and how to do Exploratory Data Analysis inside and outside Java. Now, when we covered the foundation, we are ready to start creating Machine Learning models. First, we start with Supervised Learning. In the supervised settings we have some information attached to each observation – called labels – and we want to learn from it, and predict it for observations without labels. There are two types of labels: the first are discrete and finite, such as True/False or Buy/Sell, and second are continuous, such as salary or temperature. These types correspond to two types of Supervised Learning: Classification and Regression. We will talk about them in this article. This article covers: Classification problems Regression Problems Evaluation metrics for each type Overview of available implementations in Java

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