This book will give you an all encompassing view of the domain name ecosystem combined with a comprehensive set of operations strategies. About This Book ? Manage infrastructure, risk, and management of DNS name servers. Get hands-on with factors like types of name servers, DNS queries and and so on. ? Practical guide for system administrators to manage mission-critical servers ? Based on real-world experience - Written by an industry veteran who has made every possible mistake within this field. Who This Book Is For Ideal for sysadmins, webmasters, IT consultants, and developers-anyone responsible for maintaining your organization's core DNS What You Will Learn ? Anatomy of a domain - how a domain is the sum of both its DNS zone and its registration data, and why that matters. ? The domain name ecosystem - the role of registries, registrars and oversight bodies and their effect on your names. ? How DNS queries work - queries and responses are examined including debugging techniques to zero in on problems. ? Nameserver considerations - alternative nameserver daemons, numbering considerations, and deployment architectures. ? DNS use cases - the right way for basic operations such as domain transfers, large scale migrations, GeoDNS, Anycast DNS. ? Securing your domains - All aspects of security from registrar vendor selection, to DNSSEC and DDOS mitigation strategies. In Detail Managing your organization's naming architecture and mitigating risks within complex naming environments is very important. This book will go beyond looking at “how to run a name server” or “how to DNSSEC sign a domain”, Managing Mission Critical Domains & DNS looks across the entire spectrum of naming; from external factors that exert influence on your domains to all the internal factors to consider when operating your DNS. The readers are taken on a comprehensive guided tour through the world of naming: from understanding the role of registrars and how they interact with registries, to what exactly is it that ICANN does anyway? Once the prerequisite knowledge of the domain name ecosystem is acquired, the readers are taken through all aspects of DNS operations. Whether your organization operates its own nameservers or utilizes an outsourced vendor, or both, we examine the complex web of interlocking factors that must be taken into account but are too frequently overlooked. By the end of this book, our readers will have an end to end to understanding of all the aspects covered in DNS name servers. Style and approach The book is divided into two parts, the first part looks at the wider domain name ecosystem: registries, registrars and oversight policies. The second and larger part goes into operations. Every aspect of naming is considered from the viewpoint of how this affects ones domains, what are the ramifications of different operating methods as portfolios scale.

Find out how to create visually stunning and feature-rich applications by empowering Python's built-in Tkinter GUI toolkit About This Book ? Explore Tkinter's powerful features to easily design and customize your GUI application ? Learn the basics of 2D and 3D animation in GUI applications. ? Learn to integrate stunning Data Visualizations using Tkinter Canvas and Matplotlib. Who This Book Is For This book will appeal to developers and programmers who would like to build GUI-based applications. Knowledge of Python is a prerequisite. What You Will Learn ? Implement the tools provided by Tkinter to design beautiful GUIs ? Discover cross-platform development through minor customizations in your existing application ? Visualize graphs in real time as data comes in using Tkinter's animation capabilities ? Use PostgreSQL authentication to ensure data security for your application ? Write unit tests to avoid regressions when updating code In Detail Tkinter is a lightweight, portable, and easy-to-use graphical toolkit available in the Python Standard Library, widely used to build Python GUIs due to its simplicity and availability. This book teaches you to design and build graphical user interfaces that are functional, appealing, and user-friendly using the powerful combination of Python and Tkinter. After being introduced to Tkinter, you will be guided step-by-step through the application development process. Over the course of the book, your application will evolve from a simple data-entry form to a complex data management and visualization tool while maintaining a clean and robust design. In addition to building the GUI, you'll learn how to connect to external databases and network resources, test your code to avoid errors, and maximize performance using asynchronous programming. You'll make the most of Tkinter's cross-platform availability by learning how to maintain compatibility, mimic platform-native look and feel, and build executables for deployment across popular computing platforms. By the end of this book, you will have the skills and confidence to design and build powerful high-end GUI applications to solve real-world problems. Style and approach This is a comprehensive guide that explores the essential Tkinter features and modules and implements them in building real-world cross-platform GUI applications

Learn to build a full-fledged application in Spring and Kotlin taking a reactive, microservice-based approach for scalability and robustness in the cloud About This Book ? Build a full-fledged application in Spring and Kotlin ? Architect your application to take a microservice-based approach in the cloud ? Integrate your application with a variety of Spring components Who This Book Is For Developers comfortable using Spring who have basic knowledge of Kotlin and want to take their development skills to the next level and build enterprise-grade applications will benefit from this book. What You Will Learn ? Explore Spring 5 concepts with Kotlin ? Learn both dependency injections and complex configurations ? Utilize Spring Data, Spring Cloud, and Spring Security in your applications ? Create efficient reactive systems with Project Reactor ? Write unit tests for your Spring/Kotlin applications ? Deploy applications on cloud platforms like AWS In Detail Kotlin is being used widely by developers because of its light weight, built-in null safety, and functional and reactive programming aspects. Kotlin shares the same pragmatic, innovative and opinionated mindset as Spring, so they work well together. Spring when combined with Kotlin helps you to reach a new level of productivity. This combination has helped developers to create Functional Applications using both the tools together. This book will teach you how to take advantage of these developments and build robust, scalable and reactive applications with ease. In this book, you will begin with an introduction to Spring and its setup with Kotlin. You will then dive into assessing the design considerations of your application. Then you will learn to use Spring (with Spring Boot) along with Kotlin to build a robust backend in a microservice architecture with a REST based collaboration, and leverage Project Reactor in your application. You’ll then learn how to integrate Spring Data and Spring Cloud to manage configurations for database interaction and cloud deployment. You’ll also learn to use Spring Security to beef up security of your application before testing it with the JUnit framework and then deploying it on a cloud platform like AWS. Style and approach Everything you learn will be demonstrated on real-world Spring project. In each chapter we will cover some of Spring features and apply it on our project. We will guide you from the project initialization till the project deployment.

Discover how to use the next-generation language Red for full-stack development, from systems coding over user-interfaces to blockchain programming About This Book ? Explore the latest features of Red to build scalable, fast, and secure applications ? Learn graphical programming and build highly sophisticated reactive applications ? Get familiar with the specific concepts and techniques of Red development, like working with series, viewing code as data, and using dialects. Who This Book Is For This book is for software developers and architects who want to learn Red because of its conciseness, flexibility, and expressiveness, and more specifically for its possibilities in GUI apps and blockchain / smart contracts programming. Some knowledge of the basic concepts and experience of any programming language is assumed. What You Will Learn ? Set up your Red environment to achieve the highest productivity ? Get grounded in Red, gaining experience and insight through many examples and exercises ? Build simple, compact, and portable applications ? Analyze streams of data through Parse ? Compose GUI applications with View and Draw ? Get prepared for smart contract blockchain programming in Red In Detail A key problem of software development today is software bloat, where huge toolchains and development environments are needed in software coding and deployment. Red significantly reduces this bloat by offering a minimalist but complete toolchain. This is the first introductory book about it, and it will get you up and running with Red as quickly as possible. This book shows you how to write effective functions, reduce code redundancies, and improve code reuse. It will be helpful for new programmers who are starting out with Red to explore its wide and ever-growing package ecosystem and also for experienced developers who want to add Red to their skill set. The book presents the fundamentals of programming in Red and in-depth informative examples using a step-by-step approach. You will be taken through concepts and examples such as doing simple metaprogramming, functions, collections, GUI applications, and more. By the end of the book, you will be fully equipped to start your own projects in Red. Style and approach This book will gently guide you step by step into the fascinating programming universe of the Red language, offering real-world examples and practical exercises to sharpen your insight.

Mivel az informatika egyre inkább átsz?vi életünket, a szoftverek min?ségével kapcsolatos elvárások egyre magasabbak. Egy szoftver el?állítása azonban nem csak programozásból áll, és a programozóktól sem lehet elvárni emberfeletti képességeket, a megrendel? el nem mondott elképzelésének t?kéletesen megfelel?, teljesen hibamentes munkát, mivel csak az nem hibázik, aki nem is dolgozik. Az informatika világában a szoftvertesztel?k azok, akik a szoftverek min?ségéért dolgoznak. A szoftvertesztel?k?n óriási felel?sség nyugszik és folyamatosan elvárások kereszttüzében kell helytállniuk. Mégis, szoftvertesztelés nélkül a legt?bb szoftver el sem jutna a felhasználókig, vagy ha igen, akkor megjelenésük botrányokkal, valamint óriási anyagi és erk?lcsi veszteségekkel járna együtt, a rengeteg fel nem tárt programhiba miatt. Szoftvertesztelésre és tesztel?kre ezért mindenképp szükség van. K?nyvünk a professzionális szoftvertesztelés alapjaival ismerteti meg az olvasót, számos gyakorlati példával f?szerezve, mell?zve a száraz, pusztán technikai megk?zelítés? leírásokat, kezdve a szoftvertesztelés általános bemutatásától, a fogalmak ismertetését?l, majd részleteiben tárgyalva a szoftvertesztelést és annak helyét a fejlesztési folyamatokban. Segítségével jó adag gyakorlati ismerettel vértezhetjük fel magunkat, melynek során valódi, a tesztelést támogató alkalmazásokat ismerhetünk meg, biztos alapot nyújtva a szoftvertesztelésben elhelyezked? leend? és gyakorló szakembereknek a mindennapi munkájukhoz. A szoftverteszteléssel most ismerked? szakembereknek és laikusoknak kimondottan hasznos lehet ez a k?nyv, de fejleszt?k és cégvezet?k számára is tartogat hasznos információkat, melyek segítségével bevezethetik, illetve hatékonyabbá tehetik a szoftvertesztelést munkájuk során.

Ha kíváncsi az olyan témákra, mint például hogy miként lehet felt?rni egy jelszót, vagy egy webhelyet, esetleg hogyan lehet lehallgatni bárki kommunikációját egy nyílt wifi hálózaton, akkor ez a k?nyv ?nnek szól. Sokan azt hiszik, hogy ezek ?rd?ng?s dolgok, pedig egyáltalán nem azok. ?ppen ezért fontos, hogy védekezni is kell ellenük, ami szintén nem bonyolult, csak egy kis odafigyelésre van szükség. K?nyvünk mindkét oldalt megmutatja, elrettentésképpen a lehet?ségeket, okulásként a védekezési módokat. Ha ?n azt hiszi, hogy biztonságban van, hiszen nem csinál semmi illegálisat és még vírusirtó is van a gépén, akkor nagyon téved! Teljesk?r? védelem ugyanis nem létezik! Ha elolvassa ezt a k?nyvet, meg fog d?bbenni, hogy milyen sok támadási lehet?ség van adataink ellen. A k?nyv, azon túl, hogy ismerteti, mit jelentenek az információbiztonsági szakkifejezések olyan témákkal foglalkozik, mint hogy milyen eszk?z?k támadhatók és hogyan, hogyan dolgozik egy hacker, mekkora kockázatot jelent az emberi tényez? (social engineering), stb. Kitér a jelszavak biztonságára, a kül?nféle hackeléshez használható programok és azok kezelésére, a billenty?zetnaplózási lehet?ségekre, a hálózatok és weboldalak támadására és felt?résére, az online bankolási kockázatokra, a titkosítási módszerekre, illetve hogy mit érdemes tenni a biztonságos adattárolás érdekében.Természetesen senkit sem akarunk illegális tevékenységre buzdítani, célunk sokkal inkább azt megmutatni, hogy mekkora veszélynek vagyunk kitéve, ezáltal a támadási és védekezési lehet?ségek bemutatásával ?szt?n?zzük az embereket a biztonságosabb számítógéphasználatra.

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

A practical guide filled with case studies and easy solutions to solve the most common user experience issues About This Book ? Understand and fix the pain points of a bad UX design to ensure greater customer satisfaction. ? Correct UX issues at various stages of a UX Design with the help of different methodologies for fixing bad UXs ? See best practices and established principles in UX with case studies illustrating these practices and principles Who This Book Is For This book is for anyone confronted with a poorly designed UX. It is ideal for UX professionals who want to solve problems with existing UX designs, and UX designers who want to enhance their designs or analyze and rectify where they went wrong. What You Will Learn ? Learn about ROI and metrics in UX ? Understand the importance of getting stakeholders involved ? Learn through real cases how to fix bad UX ? Identify and fix UX issues using different methodologies ? Learn how to turn insights and finding into practical UX solutions ? Learn to validate, test and measure the UX solutions implemented ? Learn about UX refactoring In Detail Have your web applications been experiencing more hits and less conversions? Are bad designs consuming your time and money? This book is the answer to these problems. With intuitive case studies, you’ll learn to simplify, fix, and enhance some common, real-world application designs. You’ll look at the common issues of simplicity, navigation, appearance, maintenance, and many more. The challenge that most UX designers face is to ensure that the UX is user-friendly. In this book, we address this with individual case studies starting with some common UX applications and then move on to complex applications. Each case study will help you understand the issues faced by a bad UX and teach you to break it down and fix these problems. As we progress, you’ll learn about the information architecture, usability testing, iteration, UX refactoring, and many other related features with the help of various case studies. You’ll also learn some interesting UX design tools with the projects covered in the book. By the end of the book, you’ll be armed with the knowledge to fix bad UX designs and to ensure great customer satisfaction for your applications. Style and approach This book takes a practical approach, with case studies, best practices, and practical solutions to bad design

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner About This Book ? Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide ? Train different types of neural networks using Tensorflow for real-world problems in language processing, computer vision, transfer learning, and more ? Designed for those who believe in the concept of 'learn by doing', this book is a perfect blend of theory and code examples Who This Book Is For This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial. What You Will Learn ? Understand the fundamentals of deep learning and how it is different from machine learning ? Get familiarized with Tensorflow, one of the most popular libraries for advanced machine learning ? Increase the predictive power of your model using feature engineering ? Understand the basics of deep learning by solving a digit classification problem of MNIST ? Demonstrate face generation based on the CelebA database, a promising application of generative models ? Apply deep learning to other domains like language modeling, sentiment analysis, and machine translation In Detail Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence. Style and approach A step-by-step guide filled with multiple examples to help you get started with data science and deep learning.

Learn continuous deployment and automation with code-signing, continuous testing, building, deploying, and releasing of your app. About This Book ? A practical guide on automating your mobile development pipeline with Fastlane, Jenkins, and Slack. ? Build, test, run and deploy your mobile application release with this end to end guide. ? Implement Continuous Integration, delivery, and deployment practices to optimize your application development workflow for faster and efficient release builds. Who This Book Is For This book is intended for mobile developers who are keen on incorporating Continuous integration and deployment practices in their workflow. What You Will Learn ? Harness the fastlane tools for the Continuous Deployment strategy ? Integrate Continuous Deployment with existing Continuous Integration. ? Automate upload of screenshots across all device screen-sizes ? Manage push notifications, provisioning profiles, and code-signing certificates ? Orchestrate automated build and deployments of new versions of your app ? Regulate your TestFlight users and on-board new testers In Detail Competitive mobile apps depend strongly on the development team’s ability to deliver successful releases, consistently and often. Although continuous integration took a more mainstream priority among the development industry, companies are starting to realize the importance of continuity beyond integration and testing. This book starts off with a brief introduction to fastlane—a robust command-line tool that enables iOS and Android developers to automate their releasing workflow. The book then explores and guides you through all of its features and utilities; it provides the reader a comprehensive understanding of the tool and how to implement them. Themes include setting up and managing your certificates and provisioning and push notification profiles; automating the creation of apps and managing the app metadata on iTunes Connect and the Apple Developer Portal; and building, distributing and publishing your apps to the App Store. You will also learn how to automate the generation of localized screenshots and mesh your continuous delivery workflow into a continuous integration workflow for a more robust setup. By the end of the book, you will gain substantial knowledge on delivering bug free, developer-independent, and stable application release cycle. Style and approach A step by step guide taking the readers through all the tools of fastlane.

A tutorial leading the aspiring Go developer to full mastery of Golang's distributed features. About This Book ? This book provides enough concurrency theory to give you a contextual understanding of Go concurrency ? It gives weight to synchronous and asynchronous data streams in Golang web applications ? It makes Goroutines and Channels completely familiar and natural to Go developers Who This Book Is For This book is for developers who are familiar with the Golang syntax and have a good idea of how basic Go development works. It would be advantageous if you have been through a web application product cycle, although it’s not necessary. What You Will Learn ? Gain proficiency with concurrency and parallelism in Go ? Learn how to test your application using Go's standard library ? Learn industry best practices with technologies such as REST, OpenAPI, Docker, and so on ? Design and build a distributed search engine ? Learn strategies on how to design a system for web scale In Detail Distributed Computing with Go gives developers with a good idea how basic Go development works the tools to fulfill the true potential of Golang development in a world of concurrent web and cloud applications. Nikhil starts out by setting up a professional Go development environment. Then you’ll learn the basic concepts and practices of Golang concurrent and parallel development. You’ll find out in the new few chapters how to balance resources and data with REST and standard web approaches while keeping concurrency in mind. Most Go applications these days will run in a data center or on the cloud, which is a condition upon which the next chapter depends. There, you’ll expand your skills considerably by writing a distributed document indexing system during the next two chapters. This system has to balance a large corpus of documents with considerable analytical demands. Another use case is the way in which a web application written in Go can be consciously redesigned to take distributed features into account. The chapter is rather interesting for Go developers who have to migrate existing Go applications to computationally and memory-intensive environments. The final chapter relates to the rather onerous task of testing parallel and distributed applications, something that is not usually taught in standard computer science curricula. Style and approach Distributed Computing with Go takes you through a series of carefully graded tutorials, building ever more sophisticated applications.

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.

Learn how to write scalable and concurrent programs in Scala, a language that grows with you. About This Book ? Get a grip on the functional features of the Scala programming language ? Understand and develop optimal applications using object-oriented and functional Scala constructs ? Learn reactive principles with Scala and work with the Akka framework Who This Book Is For This book is for programmers who choose to get a grip over Scala to write concurrent, scalable, and reactive programs. No prior experience with any programming language is required to learn the concepts explained in this book. Knowledge of any programming language would help the reader understanding concepts faster though. What You Will Learn ? Get to know the reasons for choosing Scala: its use and the advantages it provides over other languages ? Bring together functional and object-oriented programming constructs to make a manageable application ? Master basic to advanced Scala constructs ? Test your applications using advanced testing methodologies such as TDD ? Select preferred language constructs from the wide variety of constructs provided by Scala ? Make the transition from the object-oriented paradigm to the functional programming paradigm ? Write clean, concise, and powerful code with a functional mindset ? Create concurrent, scalable, and reactive applications utilizing the advantages of Scala In Detail Scala is a general-purpose programming language that supports both functional and object-oriented programming paradigms. Due to its concise design and versatility, Scala's applications have been extended to a wide variety of fields such as data science and cluster computing. You will learn to write highly scalable, concurrent, and testable programs to meet everyday software requirements. We will begin by understanding the language basics, syntax, core data types, literals, variables, and more. From here you will be introduced to data structures with Scala and you will learn to work with higher-order functions. Scala's powerful collections framework will help you get the best out of immutable data structures and utilize them effectively. You will then be introduced to concepts such as pattern matching, case classes, and functional programming features. From here, you will learn to work with Scala's object-oriented features. Going forward, you will learn about asynchronous and reactive programming with Scala, where you will be introduced to the Akka framework. Finally, you will learn the interoperability of Scala and Java. After reading this book, you'll be well versed with this language and its features, and you will be able to write scalable, concurrent, and reactive programs in Scala. Style and approach This book is for programmers who want to master Scala to write concurrent, scalable, and reactive programs. Though no experience with any programming language is needed, some basic knowledge would help understand concepts faster.

Get to grips with the essentials of deep learning by leveraging the power of Python About This Book ? Your one-stop solution to get started with the essentials of deep learning and neural network modeling ? Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more ? Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner Who This Book Is For Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python. What You Will Learn ? Get to grips with the core concepts of deep learning and neural networks ? Set up deep learning library such as TensorFlow ? Fine-tune your deep learning models for NLP and Computer Vision applications ? Unify different information sources, such as images, text, and speech through deep learning ? Optimize and fine-tune your deep learning models for better performance ? Train a deep reinforcement learning model that plays a game better than humans ? Learn how to make your models get the best out of your GPU or CPU In Detail Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more. This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications. Style and approach This step-by-step guide is filled with real-world practical examples and use cases to solve various deep learning problems.

A pragmatic companion guide to your Agile journey About This Book ? Make your team Agile by implementing industry-standard Agile techniques ? Assess scope, scale up efficiently ? Create the correct roles and identify the right candidates for your team ? Finish your projects faster and stay ahead of the curve Who This Book Is For If you’re a software developer or a project manager with little to no experience of Agile, but you want to efficiently implement it, this is the book for you. What You Will Learn ? Create a solid foundation that gives your team an Agile jumpstart ? Understand how to select and evolve practices to increase your team’s agility ? Use experiments to accelerate your team’s understanding ? Fine-tune your approach by incorporating aspects of Lean and Lean Startup ? Know how to foster an environment of continuous improvement and learning that will become self-sustaining In Detail This book will help you overcome the common challenges you’ll face when transforming your working practices from waterfall to Agile. Each chapter builds on the last, starting with easy-to-grasp ways to get going with Agile. Next you’ll see how to choose the right Agile framework for your organization. Moving on, you’ll implement systematic product delivery and measure and report progress with visualization. Then you’ll learn how to create high performing teams, develop people in Agile, manage in Agile, and perform distributed Agile and collaborative governance. At the end of the book, you’ll discover how Agile will help your company progressively deliver software to customers, increase customer satisfaction, and improve the level of efficiency in software development teams. Style and approach Think of this book like a manual, rather than a theoretical textbook. It’s packed full of visual ways to understand Agile, helpful tips to get you set up quickly, tried and tested solutions when challenges arise, and heaps of support to get the day-to-day tasks in Agile done. You’ll want to keep a copy on your desk, right next to your coffee cup.

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.

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.