Master the capabilities of PostgreSQL 10 to efficiently manage and maintain your database About This Book ? Your one-stop guide to mastering advanced concepts in PostgreSQL 10 with ease ? Master query optimization, replication, and high availability with PostgreSQL ? Extend the functionalities of your PostgreSQL instance to suit your organizational needs with minimal effort Who This Book Is For If you are a PostgreSQL data architect or an administrator and want to understand how to implement advanced functionalities and master complex administrative tasks with PostgreSQL 10, then this book is perfect for you. Prior experience of administrating a PostgreSQL database and a working knowledge of SQL are required to make the best use of this book. What You Will Learn ? Get to grips with the advanced features of PostgreSQL 10 and handle advanced SQL ? Make use of the indexing features in PostgreSQL and fine-tune the performance of your queries ? Work with stored procedures and manage backup and recovery ? Master replication and failover techniques ? Troubleshoot your PostgreSQL instance for solutions to common and not-so-common problems ? Learn how to migrate your database from MySQL and Oracle to PostgreSQL without any hassle In Detail PostgreSQL is an open source database used for handling large datasets (big data) and as a JSON document database. This book highlights the newly introduced features in PostgreSQL 10, and shows you how you can build better PostgreSQL applications, and administer your PostgreSQL database more efficiently. We begin by explaining advanced database design concepts in PostgreSQL 10, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery, high availability, and much more. You will understand common and not-so-common troubleshooting problems and how you can overcome them. By the end of this book, you will have an expert-level command of advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL 10. Style and approach This mastering-level guide delves into the advanced functionalities of PostgreSQL 10

Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV. About This Book ? Learn how to apply complex visual effects to images with OpenCV 3.x and Python ? Extract features from an image and use them to develop advanced applications ? Build algorithms to help you understand image content and perform visual searches ? Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented reality Who This Book Is For This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. What You Will Learn ? Detect shapes and edges from images and videos ? How to apply filters on images and videos ? Use different techniques to manipulate and improve images ? Extract and manipulate particular parts of images and videos ? Track objects or colors from videos ? Recognize specific object or faces from images and videos ? How to create Augmented Reality applications ? Apply artificial neural networks and machine learning to improve object recognition In Detail Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples. This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications. Style and approach The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation.

Transform yourself into a Kubernetes specialist in serverless applications. About This Book ? Get hands-on experience in installing, configuring, and using services such as Kubeless, Funktion, OpenWhisk, and Fission ? Learn how to launch Kubernetes both locally and in public clouds ? Explore the differences between using services such as AWS Lambda and Azure Functions and running your own Who This Book Is For If you are a DevOps engineer, cloud architect, or a stakeholder keen to learn about serverless functions in Kubernetes environments, then this book is for you. What You Will Learn ? Get a detailed analysis of serverless/Functions as a Service ? Get hands-on with installing and running tasks in Kubernetes using Minikube ? Install Kubeless locally and launch your first function. ? Launch Kubernetes in the cloud and move your applications between your local machine and your cloud cluster ? Deploy applications on Kubernetes using Apache OpenWhisk ? Explore topics such as Funktion and Fission installation on the cloud followed by launching applications ? Monitor a serverless function and master security best practices and Kubernetes use cases In Detail Kubernetes has established itself as the standard platform for container management, orchestration, and deployment. It has been adopted by companies such as Google, its original developers, and Microsoft as an integral part of their public cloud platforms, so that you can develop for Kubernetes and not worry about being locked into a single vendor. This book will initially start by introducing serverless functions. Then you will configure tools such as Minikube to run Kubernetes. Once you are up-and-running, you will install and configure Kubeless, your first step towards running Function as a Service (FaaS) on Kubernetes. Then you will gradually move towards running Fission, a framework used for managing serverless functions on Kubernetes environments. Towards the end of the book, you will also work with Kubernetes functions on public and private clouds. By the end of this book, we will have mastered using Function as a Service on Kubernetes environments. Style and approach A clear, concise, and straightforward book that will empower you work with clusters and run serverless functions effectively.

Deploy and manage VMware vSphere 6.5 components with ease. About This Book ? Simplified and to-the-point theory and practical recipes to deploy and manage vSphere 6.5 ? Discover the best ways to deploy stateless and stateful ESXi hosts and upgrade them ? Storage and network resource management ? Certificate management using VMCA ? Monitor the performance of a vSphere environment. Who This Book Is For If you are a system administrator, support professional, or anyone interested in learning how to install, configure, and manage a vSphere environment, then this book is for you. This task-oriented reference guide will also benefit consultants or infrastructure architects who design and deploy vSphere 6.5 environments. What You Will Learn ? Upgrade your existing vSphere environment or perform a fresh deployment. ? Automate the deployment and management of large sets of ESXi hosts in your vSphere Environment ? Configure and manage FC, iSCSI, and NAS storage, and get more control over how storage resources are allocated and managed ? Configure vSphere networking by deploying host-wide and data center-wide switches in your vSphere environment ? Configure high availability on a host cluster and learn how to enable the fair distribution and utilization of compute resources ? Patch and upgrade the vSphere environment ? Handle certificate request generation and renew component certificates ? Monitor performance of a vSphere environment In Detail VMware vSphere is a complete and robust virtualization product suite that helps transform data centers into simplified on-premises cloud infrastructures, providing for the automation and orchestration of workload deployment and life cycle management of the infrastructure. This book focuses on the latest release of VMware vSphere and follows a recipe-based approach, giving you hands-on instructions required to deploy and manage a vSphere environment. The book starts with the procedures involved in upgrading your existing vSphere infrastructure to vSphere 6.5, followed by deploying a new vSphere 6.5 environment. Then the book delves further into the procedures involved in managing storage and network access to the ESXi hosts and the virtual machines running on them. Moving on, the book covers high availability and fair distribution/utilization of clustered compute and storage resources. Finally, the book covers patching and upgrading the vSphere infrastructure using VUM, certificate management using VMCA, and finishes with a chapter covering the tools that can be used to monitor the performance of a vSphere infrastructure. Style and approach This book will quickly get you started with managing VMware components.

Take a deep dive into building data-driven test frameworks using Selenium WebDriver About This Book ? A comprehensive guide to designing data-driven test frameworks using the Selenium 3 WebDriver API, AppiumDriver API, Java-Bindings, and TestNG ? Learn how to use Selenium Page Object Design Patterns and D.R.Y. (Don’t Repeat Yourself) Approaches to software development in automated testing ? Discover the Selenium Grid Architecture and build your own grid for browser and mobile devices ? Use third party tools and services like ExtentReports for results processing, reporting, and SauceLabs for cloud-based test services Who This Book Is For This book is intended for software quality assurance/testing professionals, software project managers, or software developers with prior experience in using Selenium and Java to test web-based applications.This book is geared towards the quality assurance and development professionals responsible for designing and building enterprise-based testing frameworks.The user should have a working knowledge of the Java, TestNG, and Selenium technologies What You Will Learn ? Design the Selenium Driver Class for local, remote, and third party grid support ? Build Page Object Classes using the Selenium Page Object Model ? Develop Data-Driven Test Classes using the TestNG framework ? Encapsulate Data using the JSON Protocol ? Build a Selenium Grid for RemoteWebDriver Testing ? Construct Utility Classes for use in Synchronization, File I/O, Reporting and Test Listener Classes ? Run the sample framework and see the benefits of a live data-driven framework in real-time In Detail The Selenium WebDriver 3.x Technology is an open source API available to test both Browser and Mobile applications. It is completely platform independent in that tests built for one browser or mobile device, will also work on all other browsers and mobile devices. Selenium supports all major development languages which allow it to be tied directly into the technology used to develop the applications. This guide will provide a step-by-step approach to designing and building a data-driven test framework using Selenium WebDriver, Java, and TestNG. The book starts off by introducing users to the Selenium Page Object Design Patterns and D.R.Y Approaches to Software Development. In doing so, it covers designing and building a Selenium WebDriver framework that supports both Browser and Mobile Devices. It will lead the user through a journey of architecting their own framework with a scalable driver class, Java utility classes, JSON Data Provider, Data-Driven Test Classes, and support for third party tools and plugins. Users will learn how to design and build a Selenium Grid from scratch to allow the framework to scale and support different browsers, mobile devices, versions, and platforms, and how they can leverage third party grids in the Cloud like SauceLabs. Other topics covered include designing abstract base and sub-classes, inheritance, dual-driver support, parallel testing, testing multi-branded applications, best practices for using locators, and data encapsulation. Finally, you will be presented with a sample fully-functional framework to get them up and running with the Selenium WebDriver for browser testing. By the end of the book, you will be able to design your own automation testing framework and perform data-driven testing with Selenium WebDriver. Style and approach A comprehensive approach to designing data-driven test frameworks using the Selenium 3 WebDriver API, Java-Bindings, and TestNG Technologies

Discover Android programming and web development by understanding the concepts of Kotlin Programming About This Book ? Practical solutions to your common programming problems with Kotlin 1.1 ? Leverage the functional power of Kotlin to ease your Android application development ? Learn to use Java code in conjunction with Kotlin Who This Book Is For This book will appeal to Kotlin developers keen to find solutions for their common programming problems. Java programming knowledge would be an added advantage. What You Will Learn ? Understand the basics and object-oriented concepts of Kotlin Programming ? Explore the full potential of collection frameworks in Kotlin ? Work with SQLite databases in Android, make network calls, and fetch data over a network ? Use Kotlin's Anko library for efficient and quick Android development ? Uncover some of the best features of Kotlin: Lambdas and Delegates ? Set up web service development environments, write servlets, and build RESTful services with Kotlin ? Learn how to write unit tests, integration tests, and instrumentation/acceptance tests. In Detail The Android team has announced first-class support for Kotlin 1.1. This acts as an added boost to the language and more and more developers are now looking at Kotlin for their application development. This recipe-based book will be your guide to learning the Kotlin programming language. The recipes in this book build from simple language concepts to more complex applications of the language. After the fundamentals of the language, you will learn how to apply the object-oriented programming features of Kotlin 1.1. Programming with Lambdas will show you how to use the functional power of Kotlin. This book has recipes that will get you started with Android programming with Kotlin 1.1, providing quick solutions to common problems encountered during Android app development. You will also be taken through recipes that will teach you microservice and concurrent programming with Kotlin. Going forward, you will learn to test and secure your applications with Kotlin. Finally, this book supplies recipes that will help you migrate your Java code to Kotlin and will help ensure that it's interoperable with Java. Style and approach This book explains concepts related to Kotlin Programming using a practical approach and with the help of easy-to-follow recipes.

The common patterns and practices of the microservice architecture and their application using the Clojure programming language. About This Book ? Relevance of the microservice architecture and benefits of Clojure's functional and simple features to implement it. ? Learn best practices and common principles to avoid common pitfalls while developing microservices. ? Learn how to use Pedestal to build your next microservices, secure them using JWT, and monitor them using the ELK stack Who This Book Is For You should have a working knowledge of programming in Clojure. However, no knowledge of RESTful architecture, microservices, or web services is expected. If you are looking to apply techniques to your own projects, taking your first steps into microservice architecture, this book is for you. What You Will Learn ? Explore the pros and cons of monolithic and microservice architectures ? Use Clojure to effectively build a reallife application using Microservices ? Gain practical knowledge of the Clojure Pedestal framework and how to use it to build Microservices ? Explore various persistence patterns and learn how to use Apache Kafka to build event-driven microservice architectures ? Secure your Microservices using JWT ? Monitor Microservices at scale using the ELK stack ? Deploy Microservices at scale using container orchestration platforms such as Kubernetes In Detail The microservice architecture is sweeping the world as the de facto pattern with which to design and build scalable, easy-tomaintain web applications. This book will teach you common patterns and practices, and will show you how to apply these using the Clojure programming language. This book will teach you the fundamental concepts of architectural design and RESTful communication, and show you patterns that provide manageable code that is supportable in development and at scale in production. We will provide you with examples of how to put these concepts and patterns into practice with Clojure. This book will explain and illustrate, with practical examples, how teams of all sizes can start solving problems with microservices. You will learn the importance of writing code that is asynchronous and non-blocking and how Pedestal helps us do this. Later, the book explains how to build Reactive microservices in Clojure that adhere to the principles underlying the Reactive Manifesto. We finish off by showing you various ways to monitor, test, and secure your microservices. By the end, you will be fully capable of setting up, modifying, and deploying a microservice with Clojure and Pedestal. Style and approach This book highlights the merits of the microservice architecture and its implementation with Clojure. Learn to implement microservices by migrating a monolithic application to a microservice-based architecture.

Get command of your organizational Big Data using the power of data science and analytics About This Book ? A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions ? Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses ? Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Who This Book Is For The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience. What You Will Learn ? Get a 360-degree view into the world of Big Data, data science and machine learning ? Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives ? Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R ? Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions ? Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications ? Understand corporate strategies for successful Big Data and data science projects ? Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies In Detail Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. Style and approach This book equips you with a knowledge of various NoSQL tools, R, Python programming, cloud platforms, and techniques so you can use them to store, analyze, and deliver meaningful insights from your data.

Build your own hybrid cloud strategy with this comprehensive learning guide. About This Book ? Build a hybrid cloud strategy for your organization with AWS and OpenStack ? Leverage Hybrid Cloud to design a complex deployment pipeline ? Learn to implement security and monitoring best practices with real-world examples Who This Book Is For This book is targeted at cloud architects, cloud solution providers, DevOps engineers, or any working stakeholder who wants to learn about the hybrid cloud architecture. A basic understanding of public and private cloud is desirable. What You Will Learn ? Learn the demographics and definitions of Hybrid Cloud ? Understand the different architecture and design of Hybrid Cloud ? Explore multi-cloud strategy and use it with your hybrid cloud ? Implement a Hybrid Cloud using CMP / Common API’s ? Implement a Hybrid Cloud using Containers ? Overcome various challenges and issues while working with your Hybrid Cloud ? Understand how to monitor your Hybrid Cloud ? Discover the security implications in the Hybrid Cloud In Detail Hybrid cloud is currently the buzz word in the cloud world. Organizations are planning to adopt hybrid cloud strategy due to its advantages such as untested workloads, cloud-bursting, cloud service brokering and so on. This book will help you understand the dynamics, design principles, and deployment strategies of a Hybrid Cloud. You will start by understanding the concepts of hybrid cloud and the problems it solves as compared to a stand-alone public and private cloud. You will be delving into the different architecture and design of hybrid cloud. The book will then cover advanced concepts such as building a deployment pipeline, containerization strategy, and data storage mechanism. Next up, you will be able to deploy an external CMP to run a Hybrid cloud and integrate it with your OpenStack and AWS environments. You will also understand the strategy for designing a Hybrid Cloud using containerization and work with pre-built solutions like vCloud Air, VMware for AWS, and Azure Stack. Finally, the book will cover security and monitoring related best practices that will help you secure your cloud infrastructure. By the end of the book, you will be in a position to build a hybrid cloud strategy for your organization. Style and approach This book follows a step-by-step, practical approach to deploying and implementing hybrid cloud architectures using AWS and OpenStack.

Build neural network models in text, vision and advanced analytics using PyTorch About This Book ? Learn PyTorch for implementing cutting-edge deep learning algorithms. ? Train your neural networks for higher speed and flexibility and learn how to implement them in various scenarios; ? Cover various advanced neural network architecture such as ResNet, Inception, DenseNet and more with practical examples; Who This Book Is For This book is for machine learning engineers, data analysts, data scientists interested in deep learning and are looking to explore implementing advanced algorithms in PyTorch. Some knowledge of machine learning is helpful but not a mandatory need. Working knowledge of Python programming is expected. What You Will Learn ? Use PyTorch for GPU-accelerated tensor computations ? Build custom datasets and data loaders for images and test the models using torchvision and torchtext ? Build an image classifier by implementing CNN architectures using PyTorch ? Build systems that do text classification and language modeling using RNN, LSTM, and GRU ? Learn advanced CNN architectures such as ResNet, Inception, Densenet, and learn how to use them for transfer learning ? Learn how to mix multiple models for a powerful ensemble model ? Generate new images using GAN’s and generate artistic images using style transfer In Detail Deep learning powers the most intelligent systems in the world, such as Google Voice, Siri, and Alexa. Advancements in powerful hardware, such as GPUs, software frameworks such as PyTorch, Keras, Tensorflow, and CNTK along with the availability of big data have made it easier to implement solutions to problems in the areas of text, vision, and advanced analytics. This book will get you up and running with one of the most cutting-edge deep learning libraries—PyTorch. PyTorch is grabbing the attention of deep learning researchers and data science professionals due to its accessibility, efficiency and being more native to Python way of development. You'll start off by installing PyTorch, then quickly move on to learn various fundamental blocks that power modern deep learning. You will also learn how to use CNN, RNN, LSTM and other networks to solve real-world problems. This book explains the concepts of various state-of-the-art deep learning architectures, such as ResNet, DenseNet, Inception, and Seq2Seq, without diving deep into the math behind them. You will also learn about GPU computing during the course of the book. You will see how to train a model with PyTorch and dive into complex neural networks such as generative networks for producing text and images. By the end of the book, you'll be able to implement deep learning applications in PyTorch with ease. Style and approach An end-to-end guide that teaches you all about PyTorch and how to implement it in various scenarios.

Highly available microservice-based web apps for Cloud with Java About This Book ? Take advantage of the simplicity of Spring to build a full-fledged application ? Let your applications run faster while generating smaller cloud service bills ? Integrate your application with various tools such as Docker and ElasticSearch and use specific tools in Azure and AWS Who This Book Is For Java developers who want to build secure, resilient, robust and scalable applications that are targeted for cloud based deployment, will find this book helpful. Some knowledge of Java, Spring, web programming and public cloud providers (AWS, Azure) should be sufficient to get you through the book. What You Will Learn ? See the benefits of the cloud environment when it comes to variability, provisioning, and tooling support ? Understand the architecture patterns and considerations when developing on the cloud ? Find out how to perform cloud-native techniques/patterns for request routing, RESTful service creation, Event Sourcing, and more ? Create Docker containers for microservices and set up continuous integration using Jenkins ? Monitor and troubleshoot an application deployed in the cloud environment ? Explore tools such as Docker and Kubernetes for containerization and the ELK stack for log aggregation and visualization ? Use AWS and Azure specific tools to design, develop, deploy, and manage applications ? Migrate from monolithic architectures to a cloud native deployment In Detail Businesses today are evolving so rapidly that they are resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This means developers now are faced with the challenge of building build applications that are native to the cloud. For this, they need to be aware of the environment, tools, and resources they’re coding against. If you’re a Java developer who wants to build secure, resilient, robust, and scalable applications that are targeted for cloud-based deployment, this is the book for you. It will be your one stop guide to building cloud-native applications in Java Spring that are hosted in On-prem or cloud providers - AWS and Azure The book begins by explaining the driving factors for cloud adoption and shows you how cloud deployment is different from regular application deployment on a standard data centre. You will learn about design patterns specific to applications running in the cloud and find out how you can build a microservice in Java Spring using REST APIs You will then take a deep dive into the lifecycle of building, testing, and deploying applications with maximum automation to reduce the deployment cycle time. Gradually, you will move on to configuring the AWS and Azure platforms and working with their APIs to deploy your application. Finally, you’ll take a look at API design concerns and their best practices. You’ll also learn how to migrate an existing monolithic application into distributed cloud native applications. By the end, you will understand how to build and monitor a scalable, resilient, and robust cloud native application that is always available and fault tolerant. Style and approach Filled with examples, this book will build you an entire cloud-native application through its course and will stop at each point and explain in depth the functioning and design considerations that will make a robust, highly available application

Build fast, scalable, and high performing applications with Delphi About This Book ? Build efficient and concurrent applications in Delphi with focused examples ? Identify performance bottlenecks and apply the correct algorithm to increase the performance of applications. ? Delve into parallel programming and memory management to optimize your code Who This Book Is For This book is for Delphi developers who would like to build high performance applications with Delphi. Prior knowledge of Delphi is assumed. What You Will Learn ? Find performance bottlenecks and easily mitigate them ? Discover different approaches to fix algorithms ? Understand parallel programming and work with various tools included with Delphi ? Master the RTL for code optimization ? Explore memory managers and their implementation ? Leverage external libraries to write better performing programs In Detail Delphi is a cross-platform Integrated Development Environment (IDE) that supports rapid application development for Microsoft Windows, Apple Mac OS X, Google Android, iOS, and now Linux with RAD Studio 10.2. This book will be your guide to build efficient high performance applications with Delphi. The book begins by explaining how to find performance bottlenecks and apply the correct algorithm to fix them. It will teach you how to improve your algorithms before taking you through parallel programming. You’ll then explore various tools to build highly concurrent applications. After that, you’ll delve into improving the performance of your code and master cross-platform RTL improvements. Finally, we’ll go through memory management with Delphi and you’ll see how to leverage several external libraries to write better performing programs. By the end of the book, you’ll have the knowledge to create high performance applications with Delphi. Style and approach This book will take a step-by-step approach with focused examples to teach you how to increase the performance of applications.

Take your application development skills to the next level by implementing Spring Boot features effectively About This Book ? This collection of effective recipes serves as guidelines for Spring Boot application development ? Get up to date with features of the latest version of Spring Boot 2.0 ? Tips and tricks to improve your efficiency through the stages of software development Who This Book Is For This book is for Java Developers who have good knowledge and understanding of Spring and Java application development. What You Will Learn ? Get to know Spring Boot Starters and create custom auto-configurations ? Work with custom annotations that enable bean activation ? Use DevTools to easily develop and debug applications ? Learn the effective testing techniques by integrating Cucumber and Spock ? Observe an eternal application configuration using Consul ? Move your existing Spring Boot applications to the cloud ? Use Hashicorp Consul and Netflix Eureka for dynamic Service Discovery ? Understand the various mechanisms that Spring Boot provides to examine an application’s health In Detail The Spring framework provides great flexibility for Java development, which also results in tedious configuration work. Spring Boot addresses the configuration difficulties of Spring and makes it easy to create standalone, production-grade Spring-based applications. This practical guide makes the existing development process more efficient. Spring Boot Cookbook 2.0 Second Edition smartly combines all the skills and expertise to efficiently develop, test, deploy, and monitor applications using Spring Boot on premise and in the cloud. We start with an overview of the important Spring Boot features you will learn to create a web application for a RESTful service. Learn to fine-tune the behavior of a web application by learning about custom routes and asset paths and how to modify routing patterns. Address the requirements of a complex enterprise application and cover the creation of custom Spring Boot starters. This book also includes examples of the new and improved facilities available to create various kinds of tests introduced in Spring Boot 1.4 and 2.0, and gain insights into Spring Boot DevTools. Explore the basics of Spring Boot Cloud modules and various Cloud starters to make applications in “Cloud Native” and take advantage of Service Discovery and Circuit Breakers. Style and approach This practical guide follows a recipe-based approach and provides extremely helpful guidelines to build, configure, and customize your Spring Boot applications.

A practical guide to help you undertand the ability of Apache jMeter to load and performance test various server types in a more efficient way. About This Book ? Use jMeter to create and run tests to improve the performance of your webpages and applications ? Learn to build a test plan for your websites and analyze the results ? Unleash the power of various features and changes introduced in Apache jMeter 3.0 Who This Book Is For This book is for software professionals who want to understand and improve the performance of their applications with Apache jMeter. What You Will Learn ? See why performance testing is necessary and learn how to set up JMeter ? Record and test with JMeter ? Handle various form inputs in JMeter and parse results during testing ? Manage user sessions in web applications in the context of a JMeter test ? Monitor JMeter results in real time ? Perform distributed testing with JMeter ? Get acquainted with helpful tips and best practices for working with JMeter In Detail JMeter is a Java application designed to load and test performance for web application. JMeter extends to improve the functioning of various other static and dynamic resources. This book is a great starting point to learn about JMeter. It covers the new features introduced with JMeter 3 and enables you to dive deep into the new techniques needed for measuring your website performance. The book starts with the basics of performance testing and guides you through recording your first test scenario, before diving deeper into JMeter. You will also learn how to configure JMeter and browsers to help record test plans. Moving on, you will learn how to capture form submission in JMeter, dive into managing sessions with JMeter and see how to leverage some of the components provided by JMeter to handle web application HTTP sessions. You will also learn how JMeter can help monitor tests in real-time. Further, you will go in depth into distributed testing and see how to leverage the capabilities of JMeter to accomplish this. You will get acquainted with some tips and best practices with regard to performance testing. By the end of the book, you will have learned how to take full advantage of the real power behind Apache JMeter. Style and approach The book is a practical guide starting with introducing the readers to the importance of automated testing. It will then be a beginner’s journey from getting introduced to Apache jMeter to an in-detail discussion of more advanced features and possibilities with it.

Build Machine Learning models with a sound statistical understanding. About This Book ? Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. ? Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering. ? Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python. Who This Book Is For This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful. What You Will Learn ? Understand the Statistical and Machine Learning fundamentals necessary to build models ? Understand the major differences and parallels between the statistical way and the Machine Learning way to solve problems ? Learn how to prepare data and feed models by using the appropriate Machine Learning algorithms from the more-than-adequate R and Python packages ? Analyze the results and tune the model appropriately to your own predictive goals ? Understand the concepts of required statistics for Machine Learning ? Introduce yourself to necessary fundamentals required for building supervised & unsupervised deep learning models ? Learn reinforcement learning and its application in the field of artificial intelligence domain In Detail Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. You will also design programs for performing tasks such as model, parameter fitting, regression, classification, density collection, and more. By the end of the book, you will have mastered the required statistics for Machine Learning and will be able to apply your new skills to any sort of industry problem. Style and approach This practical, step-by-step guide will give you an understanding of the Statistical and Machine Learning fundamentals you'll need to build models.

Use scikit-learn to apply machine learning to real-world problems About This Book ? Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks ? Learn how to build and evaluate performance of efficient models using scikit-learn ? Practical guide to master your basics and learn from real life applications of machine learning Who This Book Is For This book is intended for software engineers who want to understand how common machine learning algorithms work and develop an intuition for how to use them, and for data scientists who want to learn about the scikit-learn API. Familiarity with machine learning fundamentals and Python are helpful, but not required. What You Will Learn ? Review fundamental concepts such as bias and variance ? Extract features from categorical variables, text, and images ? Predict the values of continuous variables using linear regression and K Nearest Neighbors ? Classify documents and images using logistic regression and support vector machines ? Create ensembles of estimators using bagging and boosting techniques ? Discover hidden structures in data using K-Means clustering ? Evaluate the performance of machine learning systems in common tasks In Detail Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model. This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance. By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach. Style and approach This book is motivated by the belief that you do not understand something until you can describe it simply. Work through toy problems to develop your understanding of the learning algorithms and models, then apply your learnings to real-life problems.

Harness the power of Scala to program Spark and analyze tonnes of data in the blink of an eye! About This Book ? Learn Scala’s sophisticated type system that combines Functional Programming and object-oriented concepts ? Work on a wide array of applications, from simple batch jobs to stream processing and machine learning ? Explore the most common as well as some complex use-cases to perform large-scale data analysis with Spark Who This Book Is For Anyone who wishes to learn how to perform data analysis by harnessing the power of Spark will find this book extremely useful. No knowledge of Spark or Scala is assumed, although prior programming experience (especially with other JVM languages) will be useful to pick up concepts quicker. What You Will Learn ? Understand object-oriented & functional programming concepts of Scala ? In-depth understanding of Scala collection APIs ? Work with RDD and DataFrame to learn Spark’s core abstractions ? Analysing structured and unstructured data using SparkSQL and GraphX ? Scalable and fault-tolerant streaming application development using Spark structured streaming ? Learn machine-learning best practices for classification, regression, dimensionality reduction, and recommendation system to build predictive models with widely used algorithms in Spark MLlib & ML ? Build clustering models to cluster a vast amount of data ? Understand tuning, debugging, and monitoring Spark applications ? Deploy Spark applications on real clusters in Standalone, Mesos, and YARN In Detail Scala has been observing wide adoption over the past few years, especially in the field of data science and analytics. Spark, built on Scala, has gained a lot of recognition and is being used widely in productions. Thus, if you want to leverage the power of Scala and Spark to make sense of big data, this book is for you. The first part introduces you to Scala, helping you understand the object-oriented and functional programming concepts needed for Spark application development. It then moves on to Spark to cover the basic abstractions using RDD and DataFrame. This will help you develop scalable and fault-tolerant streaming applications by analyzing structured and unstructured data using SparkSQL, GraphX, and Spark structured streaming. Finally, the book moves on to some advanced topics, such as monitoring, configuration, debugging, testing, and deployment. You will also learn how to develop Spark applications using SparkR and PySpark APIs, interactive data analytics using Zeppelin, and in-memory data processing with Alluxio. By the end of this book, you will have a thorough understanding of Spark, and you will be able to perform full-stack data analytics with a feel that no amount of data is too big. Style and approach Filled with practical examples and use cases, this book will hot only help you get up and running with Spark, but will also take you farther down the road to becoming a data scientist.

Advanced analytics on your Big Data with latest Apache Spark 2.x About This Book ? An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities. ? Extend your data processing capabilities to process huge chunk of data in minimum time using advanced concepts in Spark. ? Master the art of real-time processing with the help of Apache Spark 2.x Who This Book Is For If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected. What You Will Learn ? Examine Advanced Machine Learning and DeepLearning with MLlib, SparkML, SystemML, H2O and DeepLearning4J ? Study highly optimised unified batch and real-time data processing using SparkSQL and Structured Streaming ? Evaluate large-scale Graph Processing and Analysis using GraphX and GraphFrames ? Apply Apache Spark in Elastic deployments using Jupyter and Zeppelin Notebooks, Docker, Kubernetes and the IBM Cloud ? Understand internal details of cost based optimizers used in Catalyst, SystemML and GraphFrames ? Learn how specific parameter settings affect overall performance of an Apache Spark cluster ? Leverage Scala, R and python for your data science projects In Detail Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and SQL. This book aims to take your knowledge of Spark to the next level by teaching you how to expand Spark’s functionality and implement your data flows and machine/deep learning programs on top of the platform. The book commences with an overview of the Spark ecosystem. It will introduce you to Project Tungsten and Catalyst, two of the major advancements of Apache Spark 2.x. You will understand how memory management and binary processing, cache-aware computation, and code generation are used to speed things up dramatically. The book extends to show how to incorporate H20, SystemML, and Deeplearning4j for machine learning, and Jupyter Notebooks and Kubernetes/Docker for cloud-based Spark. During the course of the book, you will learn about the latest enhancements to Apache Spark 2.x, such as interactive querying of live data and unifying DataFrames and Datasets. You will also learn about the updates on the APIs and how DataFrames and Datasets affect SQL, machine learning, graph processing, and streaming. You will learn to use Spark as a big data operating system, understand how to implement advanced analytics on the new APIs, and explore how easy it is to use Spark in day-to-day tasks. Style and approach This book is an extensive guide to Apache Spark modules and tools and shows how Spark's functionality can be extended for real-time processing and storage with worked examples.

This unique book provides you with a wealth of tips, tricks, best practices, and answers to the day-to-day questions that programmers face in their careers. It is split into three parts: Coder Skills, Freelancer Skills, and Career Skills, providing the knowledge you need to get ahead in programming. About This Book ? Over 50 essays with practical advice on improving your programming career ? Practical focus gives solutions to common problems, and methods to become a better coder ? Includes advice for existing programmers and those wanting to begin a career in programming Who This Book Is For This book is useful for programmers of any ability or discipline. It has advice for those thinking about beginning a career in programming, those already working as a fully employed programmer, and for those working as freelance developers. What You Will Learn ? Improve your soft skills to become a better and happier coder ? Learn to be a better developer ? Grow your freelance development business ? Improve your development career ? Learn the best approaches to breaking down complex topics ? Have the confidence to charge what you're worth as a freelancer ? Succeed in developer job interviews In Detail This is an all-purpose toolkit for your programming career. It has been built by Jordan Hudgens over a lifetime of coding and teaching coding. It helps you identify the key questions and stumbling blocks that programmers encounter, and gives you the answers to them! It is a comprehensive guide containing more than 50 insights that you can use to improve your work, and to give advice in your career. The book is split up into three topic areas: Coder Skills, Freelancer Skills, and Career Skills, each containing a wealth of practical advice. Coder Skills contains advice for people starting out, or those who are already working in a programming role but want to improve their skills. It includes such subjects as: how to study and understand complex topics, and getting past skill plateaus when learning new languages. Freelancer Skills contains advice for developers working as freelancers or with freelancers. It includes such subjects as: knowing when to fire a client, and tips for taking over legacy applications. Career Skills contains advice for building a successful career as a developer. It includes such subjects as: how to improve your programming techniques, and interview guides and developer salary negotiation strategies. Style and approach This unique book provides over 50 insightful essays full of practical advice for improving your programming career. The book is split into three broad sections covering different aspects of a developer's career. Each essay is self-contained and can be read individually, or in chunks.

Mastering Drupal can lead to a mighty website - discover what Drupal 8 can really do with hidden techniques, best practices, and more! About This Book ? The most up-to-date advanced practical guide on Drupal 8 with an in-depth look at all the advanced new features such as authoring, HTML markup, built-in web services, and more ? If you are looking to dive deep into Drupal 8 and create industry-standard web apps, then this is the ideal book for you ? All the code and examples are explained in great detail to help you in the development process Who This Book Is For This book is ideally suited to web developers, designers, and web administrators who want to dive deep into Drupal. Previous experience with Drupal is a must to unleash the full potential of this book. What You Will Learn ? Discover how to better manage content using custom blocks and views ? Display content in multiple ways, taking advantage of display modes ? Create custom modules with YAML and Symfony 2 ? Easily translate content using the new multilingual capabilities ? Use RESTful services and JavaScript frameworks to build headless websites ? Manage Drupal configuration from one server to another easily In Detail Drupal is an open source content management system trusted by governments and organizations around the globe to run their websites. It brings with it extensive content authoring tools, reliable performance, and a proven track record of security. The community of more than 1,000,000 developers, designers, editors, and others have developed and maintained a wealth of modules, themes, and other add-ons to help you build a dynamic web experience. Drupal 8 is the latest release of the Drupal built on the Symfony2 framework. This is the largest change to the Drupal project in its history. The entire API of Drupal has been rebuilt using Symfony and everything from the administrative UI to themes to custom module development has been affected. This book will cover everything you need to plan and build a complete website using Drupal 8. It will provide a clear and concise walkthrough of the more than 200 new features and improvements introduced in Drupal core. In this book, you will learn advanced site building techniques, create and modify themes using Twig, create custom modules using the new Drupal API, explore the new REST and Multilingual functionality, import, and export Configuration, and learn how to migrate from earlier versions of Drupal. Style and approach This book takes a practical approach with equal emphasis on examples and illustrative screenshots.

A guide to mastering Visual Studio 2017 About This Book ? Focus on coding with the new, improved, and powerful tools of VS 2017 ? Master improved debugging and unit testing support capabilities ? Accelerate cloud development with the built-in Azure tools Who This Book Is For .NET Developers who would like to master the new features of VS 2017, and would like to delve into newer areas such as cloud computing, would benefit from this book. Basic knowledge of previous versions of Visual Studio is assumed. What You Will Learn ? Learn what's new in the Visual Studio 2017 IDE, C# 7.0, and how it will help developers to improve their productivity ? Learn the workloads and components of the new installation wizard and how to use the online and offline installer ? Build stunning Windows apps using Windows Presentation Foundation (WPF) and Universal Windows Platform (UWP) tools ? Get familiar with .NET Core and learn how to build apps targeting this new framework ? Explore everything about NuGet packages ? Debug and test your applications using Visual Studio 2017 ? Accelerate cloud development with Microsoft Azure ? Integrate Visual Studio with most popular source control repositories, such as TFS and GitHub In Detail Visual Studio 2017 is the all-new IDE released by Microsoft for developers, targeting Microsoft and other platforms to build stunning Windows and web apps. Learning how to effectively use this technology can enhance your productivity while simplifying your most common tasks, allowing you more time to focus on your project. With this book, you will learn not only what VS2017 offers, but also what it takes to put it to work for your projects. Visual Studio 2017 is packed with improvements that increase productivity, and this book will get you started with the new features introduced in Visual Studio 2017 IDE and C# 7.0. Next, you will learn to use XAML tools to build classic WPF apps, and UWP tools to build apps targeting Windows 10. Later, you will learn about .NET Core and then explore NuGet, the package manager for the Microsoft development platform. Then, you will familiarize yourself with the debugging and live unit testing techniques that comes with the IDE. Finally, you'll adapt Microsoft's implementation of cloud computing with Azure, and the Visual Studio integration with Source Control repositories. Style and approach This comprehensive guide covers the advanced features of Visual Studio 2017, and communicates them through a practical approach to explore the underlying concepts of how, when, and why to use it.