If you want to design and develop enterprise applications using .NET Core as the development framework and learn about industry-wide best practices and guidelines, then this book is for you. The book starts with a brief introduction to enterprise architecture, which will help you to understand what enterprise architecture is and what the key components are. It will then teach you about the types of patterns and the principles of software development, and explain the various aspects of distributed computing to keep your applications effective and scalable. These chapters act as a catalyst to start the practical implementation, and design and develop applications using different architectural approaches, such as layered architecture, service oriented architecture, microservices and cloud-specific solutions. Gradually, you will learn about the different approaches and models of the Security framework and explore various authentication models and authorization techniques, such as social media-based authentication and safe storage using app secrets. By the end of the book, you will get to know the concepts and usage of the emerging fields, such as DevOps, BigData, architectural practices, and Artificial Intelligence.

Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide. About This Book ? Load, store, edit, and visualize data using OpenCV and Python ? Grasp the fundamental concepts of classification, regression, and clustering ? Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide ? Evaluate, compare, and choose the right algorithm for any task Who This Book Is For This book targets Python programmers who are already familiar with OpenCV; this book will give you the tools and understanding required to build your own machine learning systems, tailored to practical real-world tasks. What You Will Learn ? Explore and make effective use of OpenCV's machine learning module ? Learn deep learning for computer vision with Python ? Master linear regression and regularization techniques ? Classify objects such as flower species, handwritten digits, and pedestrians ? Explore the effective use of support vector machines, boosted decision trees, and random forests ? Get acquainted with neural networks and Deep Learning to address real-world problems ? Discover hidden structures in your data using k-means clustering ? Get to grips with data pre-processing and feature engineering In Detail Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine learning, with Deep Learning driving innovative systems such as self-driving cars and Google’s DeepMind. OpenCV lies at the intersection of these topics, providing a comprehensive open-source library for classic as well as state-of-the-art computer vision and machine learning algorithms. In combination with Python Anaconda, you will have access to all the open-source computing libraries you could possibly ask for. Machine learning for OpenCV begins by introducing you to the essential concepts of statistical learning, such as classification and regression. Once all the basics are covered, you will start exploring various algorithms such as decision trees, support vector machines, and Bayesian networks, and learn how to combine them with other OpenCV functionality. As the book progresses, so will your machine learning skills, until you are ready to take on today's hottest topic in the field: Deep Learning. By the end of this book, you will be ready to take on your own machine learning problems, either by building on the existing source code or developing your own algorithm from scratch! Style and approach OpenCV machine learning connects the fundamental theoretical principles behind machine learning to their practical applications in a way that focuses on asking and answering the right questions. This book walks you through the key elements of OpenCV and its powerful machine learning classes, while demonstrating how to get to grips with a range of models.

Master the principles to make applications robust, scalable and responsive About This Book ? Implement concurrent applications using the Java 9 Concurrency API and its new components ? Improve the performance of your applications and process more data at the same time, taking advantage of all of your resources ? Construct real-world examples related to machine learning, data mining, natural language processing, and more Who This Book Is For This book is for competent Java developers who have basic understanding of concurrency, but knowledge of effective implementation of concurrent programs or usage of streams for making processes more efficient is not required What You Will Learn ? Master the principles that every concurrent application must follow ? See how to parallelize a sequential algorithm to obtain better performance without data inconsistencies and deadlocks ? Get the most from the Java Concurrency API components ? Separate the thread management from the rest of the application with the Executor component ? Execute phased-based tasks in an efficient way with the Phaser components ? Solve problems using a parallelized version of the divide and conquer paradigm with the Fork / Join framework ? Find out how to use parallel Streams and Reactive Streams ? Implement the “map and reduce” and “map and collect” programming models ? Control the concurrent data structures and synchronization mechanisms provided by the Java Concurrency API ? Implement efficient solutions for some actual problems such as data mining, machine learning, and more In Detail Concurrency programming allows several large tasks to be divided into smaller sub-tasks, which are further processed as individual tasks that run in parallel. Java 9 includes a comprehensive API with lots of ready-to-use components for easily implementing powerful concurrency applications, but with high flexibility so you can adapt these components to your needs. The book starts with a full de*ion of the design principles of concurrent applications and explains how to parallelize a sequential algorithm. You will then be introduced to Threads and Runnables, which are an integral part of Java 9's concurrency API. You will see how to use all the components of the Java concurrency API, from the basics to the most advanced techniques, and will implement them in powerful real-world concurrency applications. The book ends with a detailed de*ion of the tools and techniques you can use to test a concurrent Java application, along with a brief insight into other concurrency mechanisms in JVM. Style and approach This is a complete guide that implements real-world examples of algorithms related to machine learning, data mining, and natural language processing in client/server environments. All the examples are explained using a step-by-step approach.

Unleash the data processing and analytics capability of Apache Spark with the language of choice: Java About This Book ? Perform big data processing with Spark—without having to learn Scala! ? Use the Spark Java API to implement efficient enterprise-grade applications for data processing and analytics ? Go beyond mainstream data processing by adding querying capability, Machine Learning, and graph processing using Spark Who This Book Is For If you are a Java developer interested in learning to use the popular Apache Spark framework, this book is the resource you need to get started. Apache Spark developers who are looking to build enterprise-grade applications in Java will also find this book very useful. What You Will Learn ? Process data using different file formats such as XML, JSON, CSV, and plain and delimited text, using the Spark core Library. ? Perform analytics on data from various data sources such as Kafka, and Flume using Spark Streaming Library ? Learn SQL schema creation and the analysis of structured data using various SQL functions including Windowing functions in the Spark SQL Library ? Explore Spark Mlib APIs while implementing Machine Learning techniques to solve real-world problems ? Get to know Spark GraphX so you understand various graph-based analytics that can be performed with Spark In Detail Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone. The book starts with an introduction to the Apache Spark 2.x ecosystem, followed by explaining how to install and configure Spark, and refreshes the Java concepts that will be useful to you when consuming Apache Spark's APIs. You will explore RDD and its associated common Action and Transformation Java APIs, set up a production-like clustered environment, and work with Spark SQL. Moving on, you will perform near-real-time processing with Spark streaming, Machine Learning analytics with Spark MLlib, and graph processing with GraphX, all using various Java packages. By the end of the book, you will have a solid foundation in implementing components in the Spark framework in Java to build fast, real-time applications. Style and approach This practical guide teaches readers the fundamentals of the Apache Spark framework and how to implement components using the Java language. It is a unique blend of theory and practical examples, and is written in a way that will gradually build your knowledge of Apache Spark.

Over 60 high-quality recipes covering debugging, security, performance, microservices, web frameworks, databases, deployment and more; rewritten for Node 4, 6, and 8. About This Book ? Security between Node.js and browser applications explained and applied in depth ? Cutting edge techniques and tools for measuring and improving performance ? Contemporary techniques to create developer-ergonomic, readily-scalable production systems Who This Book Is For If you have good knowledge of JavaScript and want to build fast, efficient, scalable client-server solutions, then this book is for you. Some experience with Node.js is assumed to get the most out of this book. If working from a beginner level Node Cookbook 2nd Edition is recommended as a primer for Node Cookbook 3rd Edition. What You Will Learn ? Rapidly become proficient at debugging Node.js programs ? Write and publish your own Node.js modules ? Become deeply acquainted with Node.js core API’s ? Use web frameworks such as Express, Hapi and Koa for accelerated web application development ? Apply Node.js streams for low-footprint infinite-capacity data processing ? Fast-track performance knowledge and optimization abilities ? Compare and contrast various persistence strategies, including database integrations with MongoDB, MySQL/MariaDB, Postgres, Redis, and LevelDB ? Grasp and apply critically essential security concepts ? Understand how to use Node with best-of-breed deployment technologies: Docker, Kubernetes and AWS In Detail The principles of asynchronous event-driven programming are perfect for today's web, where efficient real-time applications and scalability are at the forefront. Server-side JavaScript has been here since the 90s but Node got it right. This edition is a complete rewrite of the original, and is targeted against Node 4, 6, and 8. It shows you how to build fast, efficient, and scalable client-server solutions using the latest versions of Node. Beginning with adopting debugging tips and tricks of the trade and learning how to write your own modules, then covering the fundamentals of streams in Node.js, you will go on to discover I/O control, implementation of various web protocols, you’ll work up to integrating with cross-section of databases such as MongoDB, MySQL/MariaDB, Postgres, Redis, and LevelDB and building web application with Express, Hapi and Koa. You will then learn about security essentials in Node.js and the advanced optimization tools and techniques By the end of the book you should have acquired a level of proficiency that allows you to confidently build a full production-ready and scalable Node.js system. Style and approach This recipe-based practical guide presents each topic with step-by-step instructions on how you can create fast and efficient server side applications using the latest features and capabilities in Node 8 whilst also supporting usage with Node 4 and 6.

Unlock the complexities of machine learning algorithms in Spark to generate useful data insights through this data analysis tutorial About This Book ? Process and analyze big data in a distributed and scalable way ? Write sophisticated Spark pipelines that incorporate elaborate extraction ? Build and use regression models to predict flight delays Who This Book Is For Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark. What You Will Learn ? Use Spark streams to cluster tweets online ? Run the PageRank algorithm to compute user influence ? Perform complex manipulation of DataFrames using Spark ? Define Spark pipelines to compose individual data transformations ? Utilize generated models for off-line/on-line prediction ? Transfer the learning from an ensemble to a simpler Neural Network ? Understand basic graph properties and important graph operations ? Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language ? Use K-means algorithm to cluster movie reviews dataset In Detail The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment. Style and approach This book takes a practical approach to help you get to grips with using Spark for analytics and to implement machine learning algorithms. We'll teach you about advanced applications of machine learning through illustrative examples. These examples will equip you to harness the potential of machine learning, through Spark, in a variety of enterprise-grade systems.

Build consistent web apps with Redux by easily centralizing the state of your application. About This Book ? Write applications that behave consistently, run in different environments (client, server and native), and are easy to test ? Take your web apps to the next level by combining the power of Redux with other frameworks such as React and Angular ? Uncover the best practices and hidden features of Redux to build applications that are powerful, consistent, and maintainable Who This Book Is For This book targets developers who are already fluent in JavaScript but want to extend their web development skills to develop and maintain bigger applications. What You Will Learn ? Understand why and how Redux works ? Implement the basic elements of Redux ? Use Redux in combination with React/Angular to develop a web application ? Debug a Redux application ? Interface with external APIs with Redux ? Implement user authentication with Redux ? Write tests for all elements of a Redux application ? Implement simple and more advanced routing with Redux ? Learn about server-side rendering with Redux and React ? Create higher-order reducers for Redux ? Extend the Redux store via middleware In Detail The book starts with a short introduction to the principles and the ecosystem of Redux, then moves on to show how to implement the basic elements of Redux and put them together. Afterward, you are going to learn how to integrate Redux with other frameworks, such as React and Angular. Along the way, you are going to develop a blog application. To practice developing growing applications with Redux, we are going to start from nothing and keep adding features to our application throughout the book. You are going to learn how to integrate and use Redux DevTools to debug applications, and access external APIs with Redux. You are also going to get acquainted with writing tests for all elements of a Redux application. Furthermore, we are going to cover important concepts in web development, such as routing, user authentication, and communication with a backend server After explaining how to use Redux and how powerful its ecosystem can be, the book teaches you how to make your own abstractions on top of Redux, such as higher-order reducers and middleware. By the end of the book, you are going to be able to develop and maintain Redux applications with ease. In addition to learning about Redux, you are going be familiar with its ecosystem, and learn a lot about JavaScript itself, including best practices and patterns. Style and approach This practical guide will teach you how to develop a complex, data-intensive application leveraging the capabilities of the Redux framework.

Extract patterns and knowledge from your data in easy way using MATLAB About This Book ? Get your first steps into machine learning with the help of this easy-to-follow guide ? Learn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLAB ? Understand how your data works and identify hidden layers in the data with the power of machine learning. Who This Book Is For This book is for data analysts, data scientists, students, or anyone who is looking to get started with machine learning and want to build efficient data processing and predicting applications. A mathematical and statistical background will really help in following this book well. What You Will Learn ? Learn the introductory concepts of machine learning. ? Discover different ways to transform data using SAS XPORT, import and export tools, ? Explore the different types of regression techniques such as simple & multiple linear regression, ordinary least squares estimation, correlations and how to apply them to your data. ? Discover the basics of classification methods and how to implement Naive Bayes algorithm and Decision Trees in the Matlab environment. ? Uncover how to use clustering methods like hierarchical clustering to grouping data using the similarity measures. ? Know how to perform data fitting, pattern recognition, and clustering analysis with the help of MATLAB Neural Network Toolbox. ? Learn feature selection and extraction for dimensionality reduction leading to improved performance. In Detail MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners. You’ll start by getting your system ready with t he MATLAB environment for machine learning and you’ll see how to easily interact with the Matlab workspace. We’ll then move on to data cleansing, mining and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB. Style and approach The book takes a very comprehensive approach to enhance your understanding of machine learning using MATLAB. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work.

Apply Functional Programming techniques to C++ to build highly modular, testable, and reusable code About This Book ? Modularize your applications and make them highly reusable and testable ? Get familiar with complex concepts such as metaprogramming, concurrency, and immutability ? A highly practical guide to building functional code in C++ filled with lots of examples and real-world use cases Who This Book Is For This book is for C++ developers comfortable with OOP who are interested in learning how to apply the functional paradigm to create robust and testable apps. What You Will Learn ? Get to know the difference between imperative and functional approaches ? See the use of first-class functions and pure functions in a functional style ? Discover various techniques to apply immutable state to avoid side effects ? Design a recursive algorithm effectively ? Create faster programs using lazy evaluation ? Structure code using design patterns to make the design process easier ? Use concurrency techniques to develop responsive software ? Learn how to use the C++ Standard Template Library and metaprogramming in a functional way to improve code optimization In Detail Functional programming allows developers to divide programs into smaller, reusable components that ease the creation, testing, and maintenance of software as a whole. Combined with the power of C++, you can develop robust and scalable applications that fulfill modern day software requirements. This book will help you discover all the C++ 17 features that can be applied to build software in a functional way. The book is divided into three modules—the first introduces the fundamentals of functional programming and how it is supported by modern C++. The second module explains how to efficiently implement C++ features such as pure functions and immutable states to build robust applications. The last module describes how to achieve concurrency and apply design patterns to enhance your application’s performance. Here, you will also learn to optimize code using metaprogramming in a functional way. By the end of the book, you will be familiar with the functional approach of programming and will be able to use these techniques on a daily basis. Style and approach This book uses a module-based approach, where each module will cover important aspects of functional programming in C++ and will help you develop efficient and robust applications through gaining a practical understanding.

Discover practical solutions for a wide range of real-world network programming tasks About This Book ? Solve real-world tasks in the area of network programming, system/networking administration, network monitoring, and more. ? Familiarize yourself with the fundamentals and functionalities of SDN ? Improve your skills to become the next-gen network engineer by learning the various facets of Python programming Who This Book Is For This book is for network engineers, system/network administrators, network programmers, and even web application developers who want to solve everyday network-related problems. If you are a novice, you will develop an understanding of the concepts as you progress with this book. What You Will Learn ? Develop TCP/IP networking client/server applications ? Administer local machines' IPv4/IPv6 network interfaces ? Write multi-purpose efficient web clients for HTTP and HTTPS protocols ? Perform remote system administration tasks over Telnet and SSH connections ? Interact with popular websites via web services such as XML-RPC, SOAP, and REST APIs ? Monitor and analyze major common network security vulnerabilities ? Develop Software-Defined Networks with Ryu, OpenDaylight, Floodlight, ONOS, and POX Controllers ? Emulate simple and complex networks with Mininet and its extensions for network and systems emulations ? Learn to configure and build network systems and Virtual Network Functions (VNF) in heterogeneous deployment environments ? Explore various Python modules to program the Internet In Detail Python Network Programming Cookbook - Second Edition highlights the major aspects of network programming in Python, starting from writing simple networking clients to developing and deploying complex Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) systems. It creates the building blocks for many practical web and networking applications that rely on various networking protocols. It presents the power and beauty of Python to solve numerous real-world tasks in the area of network programming, network and system administration, network monitoring, and web-application development. In this edition, you will also be introduced to network modelling to build your own cloud network. You will learn about the concepts and fundamentals of SDN and then extend your network with Mininet. Next, you’ll find recipes on Authentication, Authorization, and Accounting (AAA) and open and proprietary SDN approaches and frameworks. You will also learn to configure the Linux Foundation networking ecosystem and deploy and automate your networks with Python in the cloud and the Internet scale. By the end of this book, you will be able to analyze your network security vulnerabilities using advanced network packet capture and analysis techniques. Style and approach This book follows a practical approach and covers major aspects of network programming in Python. It provides hands-on recipes combined with short and concise explanations on code snippets. This book will serve as a supplementary material to develop hands-on skills in any academic course on network programming. This book further elaborates network softwarization, including Software-Defined Networking (SDN), Network Functions Virtualization (NFV), and orchestration. We learn to configure and deploy enterprise network platforms, develop applications on top of them with Python.

Master the intricacies of Apache Storm and develop real-time stream processing applications with ease About This Book ? Exploit the various real-time processing functionalities offered by Apache Storm such as parallelism, data partitioning, and more ? Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka ? An easy-to-understand guide to effortlessly create distributed applications with Storm Who This Book Is For If you are a Java developer who wants to enter into the world of real-time stream processing applications using Apache Storm, then this book is for you. No previous experience in Storm is required as this book starts from the basics. After finishing this book, you will be able to develop not-so-complex Storm applications. What You Will Learn ? Understand the core concepts of Apache Storm and real-time processing ? Follow the steps to deploy multiple nodes of Storm Cluster ? Create Trident topologies to support various message-processing semantics ? Make your cluster sharing effective using Storm scheduling ? Integrate Apache Storm with other Big Data technologies such as Hadoop, HBase, Kafka, and more ? Monitor the health of your Storm cluster In Detail Apache Storm is a real-time Big Data processing framework that processes large amounts of data reliably, guaranteeing that every message will be processed. Storm allows you to scale your data as it grows, making it an excellent platform to solve your big data problems. This extensive guide will help you understand right from the basics to the advanced topics of Storm. The book begins with a detailed introduction to real-time processing and where Storm fits in to solve these problems. You’ll get an understanding of deploying Storm on clusters by writing a basic Storm Hello World example. Next we’ll introduce you to Trident and you’ll get a clear understanding of how you can develop and deploy a trident topology. We cover topics such as monitoring, Storm Parallelism, scheduler and log processing, in a very easy to understand manner. You will also learn how to integrate Storm with other well-known Big Data technologies such as HBase, Redis, Kafka, and Hadoop to realize the full potential of Storm. With real-world examples and clear explanations, this book will ensure you will have a thorough mastery of Apache Storm. You will be able to use this knowledge to develop efficient, distributed real-time applications to cater to your business needs. Style and approach This easy-to-follow guide is full of examples and real-world applications to help you get an in-depth understanding of Apache Storm. This book covers the basics thoroughly and also delves into the intermediate and slightly advanced concepts of application development with Apache Storm.

A practical guide to testing your network’s security with Kali Linux, the preferred choice of penetration testers and hackers. About This Book ? Employ advanced pentesting techniques with Kali Linux to build highly-secured systems ? Get to grips with various stealth techniques to remain undetected and defeat the latest defenses and follow proven approaches ? Select and configure the most effective tools from Kali Linux to test network security and prepare your business against malicious threats and save costs Who This Book Is For Penetration Testers, IT professional or a security consultant who wants to maximize the success of your network testing using some of the advanced features of Kali Linux, then this book is for you.Some prior exposure to basics of penetration testing/ethical hacking would be helpful in making the most out of this title. What You Will Learn ? Select and configure the most effective tools from Kali Linux to test network security ? Employ stealth to avoid detection in the network being tested ? Recognize when stealth attacks are being used against your network ? Exploit networks and data systems using wired and wireless networks as well as web services ? Identify and download valuable data from target systems ? Maintain access to compromised systems ? Use social engineering to compromise the weakest part of the network—the end users In Detail This book will take you, as a tester or security practitioner through the journey of reconnaissance, vulnerability assessment, exploitation, and post-exploitation activities used by penetration testers and hackers. We will start off by using a laboratory environment to validate tools and techniques, and using an application that supports a collaborative approach to penetration testing. Further we will get acquainted with passive reconnaissance with open source intelligence and active reconnaissance of the external and internal networks. We will also focus on how to select, use, customize, and interpret the results from a variety of different vulnerability scanners. Specific routes to the target will also be examined, including bypassing physical security and exfiltration of data using different techniques. You will also get to grips with concepts such as social engineering, attacking wireless networks, exploitation of web applications and remote access connections. Later you will learn the practical aspects of attacking user client systems by backdooring executable files. You will focus on the most vulnerable part of the network—directly and bypassing the controls, attacking the end user and maintaining persistence access through social media. You will also explore approaches to carrying out advanced penetration testing in tightly secured environments, and the book's hands-on approach will help you understand everything you need to know during a Red teaming exercise or penetration testing Style and approach An advanced level tutorial that follows a practical approach and proven methods to maintain top notch security of your networks.

Viktor Farcic's latest book, The DevOps 2.1 Toolkit: Docker Swarm, shows you how to successfully integrate Docker Swarm into your DevOps toolset. About This Book ? Expand your DevOps Toolkit with the DevOps thought leader, Viktor Farcic ? Build, test, deploy, and monitor services inside Docker Swarm clusters ? Translate your understanding to different hosting providers like AWS, Azure, and DigitalOcean ? Go beyond simple deployment to explore how to create a continuous deployment process ? Extend the deep understanding you gained from Viktor's DevOps 2.0 Toolkit book Who This Book Is For This book is for professionals interested in the full microservices life cycle combined with continuous deployment and containers. Target audience could be architects who want to know how to design their systems around microservices. It could be DevOps wanting to know how to apply modern configuration management practices and continuously deploy applications packed in containers. It is for developers who would like to take the process back into their hands as well as for managers who would like to gain a better understanding of the process used to deliver software from the beginning to the end. This book is for everyone wanting to know more about the software development life cycle starting from requirements and design, through the development and testing all the way until deployment and post-deployment phases. We'll create the processes taking into account the best practices developed by and for some of the biggest companies. What You Will Learn ? Learn all aspects of Docker Swarm from building, testing, deploying, and monitoring services inside Docker Swarm clusters, available since Docker 1.12. ? Master the deeper logic of DevOps with Viktor, so that you can successfully apply that logic across any specific set of tools you’re working with. ? Translate a deep understanding to different hosting providers like AWS, Azure, DigitalOcean, among others. ? You’ll go beyond simple deployment: you will explore with Viktor how to create a continuous deployment process. Accomplish zero-downtime deployments, and what to do in case of a failover. ? Know how to run services at scale, how to monitor the systems, and how to make it heal itself. In Detail Viktor Farcic's latest book, The DevOps 2.1 Toolkit: Docker Swarm, takes you deeper into one of the major subjects of his international best seller, The DevOps 2.0 Toolkit, and shows you how to successfully integrate Docker Swarm into your DevOps toolset. Viktor shares with you his expert knowledge in all aspects of building, testing, deploying, and monitoring services inside Docker Swarm clusters. You'll go through all the tools required for running a cluster. You'll travel through the whole process with clusters running locally on a laptop. Once you're confident with that outcome, Viktor shows you how to translate your experience to different hosting providers like AWS, Azure, and DigitalOcean. Viktor has updated his DevOps 2.0 framework in this book to use the latest and greatest features and techniques introduced in Docker. We'll go through many practices and even more tools. While there will be a lot of theory, this is a hands-on book. You won't be able to complete it by reading it on the metro on your way to work. You'll have to read this book while in front of the computer and get your hands dirty. Style and approach We'll go through many practices and even more tools. While there will be a lot of theory, this is a hands-on book. You'll have to read this book while in front of the computer and get your hands dirty. The goal is not to master one particular set of tools, but to learn the logic behind them so that you can apply it to your job in various contexts.

This book is written in Cookbook style, beginning with recipes based on basic structure which gradually progresses towards using Nagios Core as a monitoring framework. This book is for System Administrators who are looking for recipes to help them deal with advanced network monitoring issues with Nagios Core.

Cookbook; packed with recipes to help you create amazing 3D games with Torque. The recipes provide clear step-by-step instruction and practical examples to advance your understanding of Torque 3D and all of its subsystems. The book is written for professional and indie game developers that have basic knowledge of TorqueScript, are acquainted with Torque 3D’s built-in tools, and wish to take their skills to the next level. Having gone through the comprehensive Torque 3D 1.2 FPS game tutorial on the GarageGames website (or its equivalent) is assumed.

This book is aimed at Java developers, system administrators, application testers using WildFly, and anyone who performs a DevOps role. Whether you are completely new to WildFly or just require an understanding of WildFly's new features, this book is for you.

Over 60 recipes to work with topology, overlays, indoor routing, and web application analysis with Python About This Book Explore the practical process of using geospatial analysis to solve simple to complex problems with reusable recipes Concise step-by-step instructions to teach you about projections, vector, raster, overlay, indoor routing and topology analysis Create a basic indoor routing application with geodjango Who This Book Is For If you are a student, teacher, programmer, geospatial or IT administrator, GIS analyst, researcher, or scientist looking to do spatial analysis, then this book is for you. Anyone trying to answer simple to complex spatial analysis questions will get a working demonstration of the power of Python with real-world data. Some of you may be beginners with GIS, but most of you will probably have a basic understanding of geospatial analysis and programming. What You Will Learn Discover the projection and coordinate system information of your data and learn how to transform that data into different projections Import or export your data into different data formats to prepare it for your application or spatial analysis Use the power of PostGIS with Python to take advantage of the powerful analysis functions Execute spatial analysis functions on vector data including clipping, spatial joins, measuring distances, areas, and combining data to new results Create your own set of topology rules to perform and ensure quality assurance rules in Python Find the shortest indoor path with network analysis functions in easy, extensible recipes revolving around all kinds of network analysis problems Visualize your data on a map using the visualization tools and methods available to create visually stunning results Build an indoor routing web application with GeoDjango to include your spatial analysis tools built from the previous recipes In Detail Geospatial development links your data to places on the Earth’s surface. Its analysis is used in almost every industry to answer location type questions. Combined with the power of the Python programming language, which is becoming the de facto spatial *ing choice for developers and analysts worldwide, this technology will help you to solve real-world spatial problems. This book begins by tackling the installation of the necessary software dependencies and libraries needed to perform spatial analysis with Python. From there, the next logical step is to prepare our data for analysis; we will do this by building up our tool box to deal with data preparation, transformations, and projections. Now that our data is ready for analysis, we will tackle the most common analysis methods for vector and raster data. To check or validate our results, we will explore how to use topology checks to ensure top-quality results. This is followed with network routing analysis focused on constructing indoor routes within buildings, over different levels. Finally, we put several recipes together in a GeoDjango web application that demonstrates a working indoor routing spatial analysis application. The round trip will provide you all the pieces you need to accomplish your own spatial analysis application to suit your requirements. Style and approach Easy-to-follow, step-by-step recipes, explaining from start to finish how to accomplish real-world tasks.

"Oracle ADF 11gR2 Development Beginner's Guide" will cover the basics of Oracle ADF 11g development and will then work through more complex topics as the reader gains more skills. This book will follow a tutorial approach with the content and tasks getting more advanced throughout. This book is intended for beginners who know a little about Java programming and would like to learn how to develop rich web applications using the Oracle Application Development Framework.

Follow real-life, step-by-step examples that provide the building blocks to build engaging dashboards. This practical guide is all about doing. Get your data, open up Excel, and go! You don't need to be an expert to get the most out of your Dynamics GP implementation and build great-looking, easily maintained dashboards using Microsoft Excel. If you have a working knowledge of Dynamics and Excel you'll be producing amazing dashboards in hours not days.

This book is written in a Cookbook style, beginning with recipes which focus on helping developers make their software/application available in Android. Android developers who want to learn Android NDK programming, or develop multimedia and games in Android NDK will benefit from this book.

The ideal reader for this book would be someone who already knows LiveCode, is interested in creating mobile apps, and wants to save the many hours it took for me to track down all of the information on how to get started! Chapter 1, LiveCode Fundamentals, will help those of you who know programming but are not familiar with LiveCode. The knowledge you've acquired should be enough for you to benefit from the remainder of the book.