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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.

Become an advanced practitioner with this progressive set of master classes on application-oriented machine learning About This Book ? Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects ? More than 15 open source Java tools in a wide range of techniques, with code and practical usage. ? More than 10 real-world case studies in machine learning highlighting techniques ranging from data ingestion up to analyzing the results of experiments, all preparing the user for the practical, real-world use of tools and data analysis. Who This Book Is For This book will appeal to anyone with a serious interest in topics in Data Science or those already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have experience with the fundamentals of machine learning and now have a desire to explore the area further, are up to grappling with the mathematical complexities of its algorithms, and you wish to learn the complete ins and outs of practical machine learning. What You Will Learn ? Master key Java machine learning libraries, and what kind of problem each can solve, with theory and practical guidance. ? Explore powerful techniques in each major category of machine learning such as classification, clustering, anomaly detection, graph modeling, and text mining. ? Apply machine learning to real-world data with methodologies, processes, applications, and analysis. ? Techniques and experiments developed around the latest specializations in machine learning, such as deep learning, stream data mining, and active and semi-supervised learning. ? Build high-performing, real-time, adaptive predictive models for batch- and stream-based big data learning using the latest tools and methodologies. ? Get a deeper understanding of technologies leading towards a more powerful AI applicable in various domains such as Security, Financial Crime, Internet of Things, social networking, and so on. In Detail Java is one of the main languages used by practicing data scientists; much of the Hadoop ecosystem is Java-based, and it is certainly the language that most production systems in Data Science are written in. If you know Java, Mastering Machine Learning with Java is your next step on the path to becoming an advanced practitioner in Data Science. This book aims to introduce you to an array of advanced techniques in machine learning, including classification, clustering, anomaly detection, stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, deep learning, and big data batch and stream machine learning. Accompanying each chapter are illustrative examples and real-world case studies that show how to apply the newly learned techniques using sound methodologies and the best Java-based tools available today. On completing this book, you will have an understanding of the tools and techniques for building powerful machine learning models to solve data science problems in just about any domain. Style and approach A practical guide to help you explore machine learning—and an array of Java-based tools and frameworks—with the help of practical examples and real-world use cases.

Build scalable, reliable, and cost-effective applications with a serverless architecture About This Book ? Design a real-world serverless application from scratch ? Learn about AWS Lambda function and how to use Lambda functions to glue other AWS Services ? Use the Java programming language and well-known design patterns. Although Java is used for the examples in this book, the concept is applicable across all languages ? Learn to migrate your JAX-RS application to AWS Lambda and API Gateway Who This Book Is For This book is for developers and software architects who are interested in designing on the back end. Since the book uses Java to teach concepts, knowledge of Java is required. What You Will Learn ? Learn to form microservices from bigger Softwares ? Orchestrate and scale microservices ? Design and set up the data flow between cloud services and custom business logic ? Get to grips with cloud provider’s APIs, limitations, and known issues ? Migrate existing Java applications to a serverless architecture ? Acquire deployment strategies ? Build a highly available and scalable data persistence layer ? Unravel cost optimization techniques In Detail Over the past years, all kind of companies from start-ups to giant enterprises started their move to public cloud providers in order to save their costs and reduce the operation effort needed to keep their shops open. Now it is even possible to craft a complex software system consisting of many independent micro-functions that will run only when they are needed without needing to maintain individual servers. The focus of this book is to design serverless architectures, and weigh the advantages and disadvantages of this approach, along with decision factors to consider. You will learn how to design a serverless application, get to know that key points of services that serverless applications are based on, and known issues and solutions. The book addresses key challenges such as how to slice out the core functionality of the software to be distributed in different cloud services and cloud functions. It covers basic and advanced usage of these services, testing and securing the serverless software, automating deployment, and more. By the end of the book, you will be equipped with knowledge of new tools and techniques to keep up with this evolution in the IT industry. Style and approach The book takes a pragmatic approach, showing you all the examples you need to build efficient serverless applications.

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.

Leverage the power of PowerShell to bring the best out of your AWS infrastructure About This Book ? A collection of real-world-tested Powershell *s that can be used to manage your Windows server efficiently ? Follow step-by-step processes to solve your problems with Windows servers using AWS tools ? Design examples that work in the Amazon free usage tier, which lets you run the Windows platform on cloud Who This Book Is For This book will be useful for (but not limited to) Windows System administrators, cloud engineers, architects, DevOps engineers, and all those who want to accomplish tasks on the AWS Public Cloud using PowerShell. What You Will Learn ? Install the AWS Tools for PowerShell 6 ? Understand key services provided by Amazon Web services (AWS) ? Understand the Virtual Private Cloud ? Use PowerShell 6 for AWS Identity and Access Management (IAM) ? Use PowerShell 6 for AWS Elastic Compute Cloud (EC2) ? Use PowerShell 6 for AWS Simple Storage Service (S3) ? Use PowerShell 6 for AWS Relational Database Service (RDS) ? Build fault-tolerant and highly-available applications using PowerShell 6 In Detail AWS Tools for PowerShell 6 shows you exactly how to automate all the aspects of AWS. You can take advantage of the amazing power of the cloud, yet add powerful *s and mechanisms to perform common tasks faster than ever before. This book expands on the Amazon documentation with real-world, useful examples and production-ready *s to automate all the aspects of your new cloud platform. It will cover topics such as managing Windows with PowerShell, setting up security services, administering database services, and deploying and managing networking. You will also explore advanced topics such as PowerShell authoring techniques, and configuring and managing storage and content delivery. By the end of this book, you will be able to use Amazon Web Services to automate and manage Windows servers. You will also have gained a good understanding of automating the AWS infrastructure using simple coding. Style and approach This step-by-step guide starts with simple examples then expands to full-blown administrative tasks leading to the efficient management of Windows servers. Each topic covers a section related to Amazon Web Services products, and the examples are built on one another to deliver a comprehensive library of *s for administrators.

Discover how to build full stack web applications with the Raspberry Pi 3 About This Book ? Leverage JavaScript, HTML5, and Cloud APIs to create visual representations and interactive web pages. ? Learn to install and use a Node.js-based web framework to develop Raspberry Pi 3-powered web applications. ? A step-by-step guide that will cover from setting up a embedded system to developing embedded, device-powered interactive web applications. Who This Book Is For This book is aimed at hobbyist, enthusiasts, and developers eager to develop embedded device-powered web applications. Prior programming experience with JavaScript, HTML5, and Node.JS will be beneficial. What You Will Learn ? Get up and running with your Raspberry Pi ? Go full stack! Learn about the end-to-end development process for web applications, right from the OS up to the actual HTML web interface ? Discover that JavaScript is one of the fastest growing languages today, and is the only language that can be used both on a browser and server. This book will empower you to develop in a complete JavaScript stack ? See that the IoT is everywhere!Connect your application to the outside world. Make use of sensors in your Raspberry Pi to give your application an edge, and unleash the full power of the Internet of Things ? Build a rich UI with beautiful charts and data visualizations that can run on any browser ? Make your software data-driven. Learn how to utilize SQLite to collect and analyze data from multiple systems In Detail Modern web technology and portable computing together have enabled huge advances in the Internet of Things (IoT) space,as well as in areas such as machine learning and big data. The Raspberry Pi is a very popular portable computer for running full stack web applications. This book will empower you to master this rapidly evolving technology to develop complex web applications and interfaces. This book starts by familiarizing you with the various components that make up the web development stack and that will integrate into your Raspberry Pi-powered web applications. It also introduces the Raspberry Pi computer and teach you how to get up and running with a brand new one. Next, this book introduces you to the different kinds of sensor you’ll use to make your applications; using these skills, you will be able to create full stack web applications and make them available to users via a web interface. Later, this book will also teach you how to build interactive web applications using JavaScript and HTML5 for the visual representation of sensor data. Finally, this book will teach you how to use a SQLite database to store and retrieve sensor data from multiple Raspberry Pi computers. By the end of this book you will be able to create complex full stack web applications on the Raspberry Pi 3 and will have improved your application’s performance and usability. Style and approach Step-by-step instructions on developing a full stack web application and deploying it to the Cloud.

Harness the power of the Cloud, leveraging the speed and scale of Azure Serverless computing About This Book ? Take advantage of the agility, scale, and cost-effectiveness of the cloud using Azure Serverless compute ? Build scalable, reliable, and cost-effecient applications with Serverless architecture and .NET ? Learn to use Azure functions to their fullest potential in .NET Who This Book Is For This book is for .NET developers who would like to learn about serverless architecture. Basic C# programming knowledge is assumed. What You Will Learn ? Understand the best practices of Serverless architecture ? Learn how how to deploy a Text Sentiment Evaluation application in an Azure Serverless environment ? Implement security, identity, and access control ? Take advantage of the speed of deployment in the cloud ? Configure application health monitoring, logging, and alerts ? Design your application to ensure cost effectiveness, high availability, and scale In Detail Serverless architecture allows you to build and run applications and services without having to manage the infrastructure. Many companies have started adopting serverless architecture for their applications to save cost and improve scalability. This book will be your companion in designing Serverless architecture for your applications using the .NET runtime, with Microsoft Azure as the cloud service provider. You will begin by understanding the concepts of Serverless architecture, its advantages and disadvantages. You will then set up the Azure environment and build a basic application using a sample text sentiment evaluation function. From here, you will be shown how to run services in a Serverless environment. We will cover the integration with other Azure and 3rd party services such as Azure Service Bus, as well as configuring dependencies on NuGet libraries, among other topics. After this, you will learn about debugging and testing your Azure functions, and then automating deployment from source control. Securing your application and monitoring its health will follow from there, and then in the final part of the book, you will learn how to Design for High Availability, Disaster Recovery and Scale, as well as how to take advantage of the cloud pay-as-you-go model to design cost-effective services. We will finish off with explaining how azure functions scale up against AWS Lambda, Azure Web Jobs, and Azure Batch compare to other types of compute-on-demand services. Whether you’ve been working with Azure for a while, or you’re just getting started, by the end of the book you will have all the information you need to set up and deploy applications to the Azure Serverless Computing environment. Style and approach This step-by-step guide shows you the concepts and features of Serverless architecture in Azure with .NET.

Unleash the combination of Docker and Jenkins in order to enhance the DevOps workflow About This Book ? Build reliable and secure applications using Docker containers. ? Create a complete Continuous Delivery pipeline using Docker, Jenkins, and Ansible. ? Deliver your applications directly on the Docker Swarm cluster. ? Create more complex solutions using multi-containers and database migrations. Who This Book Is For This book is indented to provide a full overview of deep learning. From the beginner in deep learning and artificial intelligence to the data scientist who wants to become familiar with Theano and its supporting libraries, or have an extended understanding of deep neural nets. Some basic skills in Python programming and computer science will help, as well as skills in elementary algebra and calculus. What You Will Learn ? Get to grips with docker fundamentals and how to dockerize an application for the Continuous Delivery process ? Configure Jenkins and scale it using Docker-based agents ? Understand the principles and the technical aspects of a successful Continuous Delivery pipeline ? Create a complete Continuous Delivery process using modern tools: Docker, Jenkins, and Ansible ? Write acceptance tests using Cucumber and run them in the Docker ecosystem using Jenkins ? Create multi-container applications using Docker Compose ? Managing database changes inside the Continuous Delivery process and understand effective frameworks such as Cucumber and Flyweight ? Build clustering applications with Jenkins using Docker Swarm ? Publish a built Docker image to a Docker Registry and deploy cycles of Jenkins pipelines using community best practices In Detail The combination of Docker and Jenkins improves your Continuous Delivery pipeline using fewer resources. It also helps you scale up your builds, automate tasks and speed up Jenkins performance with the benefits of Docker containerization. This book will explain the advantages of combining Jenkins and Docker to improve the continuous integration and delivery process of app development. It will start with setting up a Docker server and configuring Jenkins on it. It will then provide steps to build applications on Docker files and integrate them with Jenkins using continuous delivery processes such as continuous integration, automated acceptance testing, and configuration management. Moving on you will learn how to ensure quick application deployment with Docker containers along with scaling Jenkins using Docker Swarm. Next, you will get to know how to deploy applications using Docker images and testing them with Jenkins. By the end of the book, you will be enhancing the DevOps workflow by integrating the functionalities of Docker and Jenkins. Style and approach The book is aimed at DevOps Engineers, developers and IT Operations who want to enhance the DevOps culture using Docker and Jenkins.