Find out how to write Kotlin code without overhead and how to use different profiling tools and bytecode viewer to inspect expressions of Kotlin language. About This Book ? Apply modern Kotlin features to speed up processing and implement highly efficient and reliable codes. ? Learn memory optimization, concurrency, multi-threading, scaling, and caching techniques to achieve high performance. ? Learn how to prevent unnecessary overhead and use profiling tools to detect performance issues. Who This Book Is For This book is for Kotlin developers who would like to build reliable and high-performance applications. Prior Kotlin programming knowledge is assumed. What You Will Learn ? Understand the importance of high performance ? Learn performance metrics ? Learn popular design patterns currently being used in Kotlin ? Understand how to apply modern Kotlin features to data processing ? Learn how to use profling tools ? Discover how to read bytecode ? Learn to perform memory optimizations ? Uncover approaches to the multithreading environment In Detail The ease with which we write applications has been increasing, but with it comes the need to address their performance. A balancing act between easily implementing complex applications and keeping their performance optimal is a present-day requirement In this book, we explore how to achieve this crucial balance, while developing and deploying applications with Kotlin. The book starts by analyzing various Kotlin specifcations to identify those that have a potentially adverse effect on performance. Then, we move on to monitor techniques that enable us to identify performance bottlenecks and optimize performance metrics. Next, we look at techniques that help to us achieve high performance: memory optimization, concurrency, multi threading, scaling, and caching. We also look at fault tolerance solutions and the importance of logging. We'll also cover best practices of Kotlin programming that will help you to improve the quality of your code base. By the end of the book, you will have gained some insight into various techniques and solutions that will help to create high-performance applications in the Kotlin environment Style and approach This book guides you through how to use profiling tools to detect performance issues and build high-performance applications in the Kotlin environment.

86 recipes on how to build fast, scalable, and powerful web services and applications with Go About This Book ? Become proficient in RESTful web services ? Build scalable, high-performant web applications in Go ? Get acquainted with Go frameworks for web development Who This Book Is For This book is for Go developers interested in learning how to use Go to build powerful web applications. A background in web development is expected. What You Will Learn ? Create a simple HTTP and TCP web server and understand how it works ? Explore record in a MySQL and MongoDB database ? Write and consume RESTful web service in Go ? Invent microservices in Go using Micro – a microservice toolkit ? Create and Deploy the Beego application with Nginx ? Deploy Go web application and Docker containers on an AWS EC2 instance In Detail Go is an open source programming language that is designed to scale and support concurrency at the language level. This gives you the liberty to write large concurrent web applications with ease. From creating web application to deploying them on Amazon Cloud Services, this book will be your one-stop guide to learn web development in Go. The Go Web Development Cookbook teaches you how to create REST services, write microservices, and deploy Go Docker containers. Whether you are new to programming or a professional developer, this book will help get you up to speed with web development in Go. We will focus on writing modular code in Go; in-depth informative examples build the base, one step at a time. You will learn how to create a server, work with static files, SQL, NoSQL databases, and Beego. You will also learn how to create and secure REST services, and create and deploy Go web application and Go Docker containers on Amazon Cloud Services. By the end of the book, you will be able to apply the skills you've gained in Go to create and explore web applications in any domain. Style and approach This book helps you learn core Go concepts faster by taking a recipe-based approach.

Explore the Rust Standard library and compose algorithms with minimal dependency on external libraries About This Book ? Develop high-quality, fast, and portable applications by leveraging the power of Rust's Standard library. ? Practical recipes that will help you work with the Standard library to boost your productivity as a Rust developer. ? Learn about most relevant external crates to be used along with the Standard library. Who This Book Is For This book is for developers who would like to explore the power of Rust and learn to use the STL for various functionalities. A basic Rust programming knowledge is assumed. What You Will Learn ? How to use the basic modules of the library: strings, command line access, and more. ? Implement collections and folding of collections using vectors, Deque, linked lists, and more. ? Handle various file types , compressing and decompressing data. ? Search for files with glob patterns. ? Implement parsing through various formats such as CSV, TOML, and JSON. ? Utilize drop trait , the Rust version of destructor. ? Resource locking with Bilocks. In Detail Mozilla’s Rust is gaining much attention with amazing features and a powerful library. This book will take you through varied recipes to teach you how to leverage the Standard library to implement efficient solutions. The book begins with a brief look at the basic modules of the Standard library and collections. From here, the recipes will cover packages that support file/directory handling and interaction through parsing. You will learn about packages related to advanced data structures, error handling, and networking. You will also learn to work with futures and experimental nightly features. The book also covers the most relevant external crates in Rust. By the end of the book, you will be proficient at using the Rust Standard library. Style and approach This recipe-based practical guide presents each topic with step-by-step instructions on how you can create fast and efficient applications utilizing Rust's Standard library packages.

Unleash Google's Cloud Platform to build, train and optimize machine learning models About This Book ? Get well versed in GCP pre-existing services to build your own smart models ? A comprehensive guide covering aspects from data processing, analyzing to building and training ML models ? A practical approach to produce your trained ML models and port them to your mobile for easy access Who This Book Is For This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy What You Will Learn ? Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile ? Create, train and optimize deep learning models for various data science problems on big data ? Learn how to leverage BigQuery to explore big datasets ? Use Google’s pre-trained TensorFlow models for NLP, image, video and much more ? Create models and architectures for Time series, Reinforcement Learning, and generative models ? Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications In Detail Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. Style and approach An easy-to-follow step by step guide which will help you get to the grips with real-world applications of Google Cloud Machine Learning.

Practical recipes to implement cost-effective and scalable cloud solutions for your organization About This Book ? Implement Google Cloud services in your organization ? Leverage Google Cloud components to secure your organization’s data ? A recipe-based guide that promises hands-on experience in deploying a highly scalable and available environment Who This Book Is For This book is for IT professionals, engineers, and developers looking at implementing Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this book useful. Basic understanding of Cloud services and the Google Cloud platform is necessary. What You Will Learn ? Host a Python application on Google Compute Engine ? Host an application using Google Cloud Functions ? Migrate a MySQL DB to Cloud Spanner ? Configure a network for a highly available application on GCP ? Learn simple image processing using Storage and Cloud Functions ? Automate security checks using Policy Scanner ? Understand tools for monitoring a production environment in GCP ? Learn to manage multiple projects using service accounts In Detail Google Cloud Platform is a cloud computing platform that offers products and services to host applications using state-of-the art infrastructure and technology. You can build and host applications and websites, store data, and analyze data on Google's scalable infrastructure. This book follows a recipe-based approach, giving you hands-on experience to make the most of Google Cloud services. This book starts with practical recipes that explain how to utilize Google Cloud's common services. Then, you'll see how to make full use of Google Cloud components such as networking, security, management, and developer tools. Next, we'll deep dive into implementing core Google Cloud services into your organization, with practical recipes on App Engine, Compute Engine microservices with Cloud Functions, virtual networks, and Cloud Storage. Later, we'll provide recipes on implementing authentication and security, Cloud APIs, command-line management, deployment management, and the Cloud SDK. Finally, we'll cover administration troubleshooting tasks with the Compute and Container Engines and we'll show how to monitor your organization's efficiency with best practices. By the end of this book, you'll have a complete understanding of how to implement Google Cloud services in your organization with ease. Style and approach This book will quickly get you started with using Google Cloud Services.

Explore and master the most important algorithms for solving complex machine learning problems. About This Book ? Discover high-performing machine learning algorithms and understand how they work in depth. ? One-stop solution to mastering supervised, unsupervised, and semi-supervised machine learning algorithms and their implementation. ? Master concepts related to algorithm tuning, parameter optimization, and more Who This Book Is For This book is an ideal and relevant source of content for data science professionals who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. A basic knowledge of machine learning is preferred to get the best out of this guide. What You Will Learn ? Explore how a ML model can be trained, optimized, and evaluated ? Understand how to create and learn static and dynamic probabilistic models ? Successfully cluster high-dimensional data and evaluate model accuracy ? Discover how artificial neural networks work and how to train, optimize, and validate them ? Work with Autoencoders and Generative Adversarial Networks ? Apply label spreading and propagation to large datasets ? Explore the most important Reinforcement Learning techniques In Detail Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn. You will also learn how to use Keras and TensorFlow to train effective neural networks. If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need. Style and approach A hands-on guide filled with real-world examples of popular algorithms used for data science and machine learning

Unleash the power of MERN stack by building diverse web applications using React, Node.js, Express, and MongoDB About This Book ? Create dynamic web applications with the MERN stack ? Leverage the power of React in building interactive and complex user interfaces ? Unlock the potential of Node, Express, and MongoDB to build modern full-stack applications Who This Book Is For Full-Stack React Web Development Projects is for JavaScript developers who have some experience with React, but no previous experience with full-stack development involving Node, Express, and MongoDB, and who want practical guidelines to start building different types of real-world web applications with this stack. What You Will Learn ? Set up your development environment and develop a MERN application ? Implement user authentication and authorization using JSON Web Tokens ? Build a social media application by extending the basic MERN application ? Create an online marketplace application with shopping cart and Stripe payments ? Develop a media streaming application using MongoDB GridFS ? Implement server-side rendering with data to improve SEO ? Set up and use React 360 to develop user interfaces with VR capabilities ? Learn industry best practices to make MERN stack applications reliable and scalable In Detail The benefits of using a full JavaScript stack for web development are undeniable, especially when robust and widely adopted technologies such as React, Node, and Express and are available. Combining the power of React with industry-tested, server-side technologies, such as Node, Express, and MongoDB, creates a diverse array of possibilities when developing real-world web applications. This book guides you through preparing the development environment for MERN stack-based web development, to creating a basic skeleton application and extending it to build four different web applications. These applications include a social media, an online marketplace, a media streaming, and a web-based game application with virtual reality features. While learning to set up the stack and developing a diverse range of applications with this book, you will grasp the inner workings of the MERN stack, extend its capabilities for complex features, and gain actionable knowledge of how to prepare MERN-based applications to meet the growing demands of real-world web applications. Style and approach This book provides practical guidelines on setting up and building MERN stack based applications, while providing further explanations on key concepts and implementations.

Key concepts, sample applications, best practices, and troubleshooting tips to build highly scalable applications in AWS. About This Book ? Design highly available, cost efficient, fault tolerant, and scalable distributed systems ? A practical guide that will help you build, deploy, and manage applications with ease. ? Develop effective solutions with AWS SDK and Lambda Who This Book Is For This book targets developers who would like to build and manage web and mobile applications and services on the AWS platform. If you are an architect you will be able to take a deep dive and use examples that can be readily applied to real world scenarios. Some prior programming experience is assumed along with familiarity of cloud computing. What You Will Learn ? Learn how to get up and running with AWS Developer Tools. ? Integrate the four major phases in the Release Processes. Source, Build, Test and Production. ? Learn how to integrate Continuous Integration, Continuous Delivery, and Continuous Deployment in AWS. ? Make secure, scalable and fault tolerant applications. ? Understand different architectures and deploy complex architectures within minutes In Detail Continuous deployment and Agile methodology have enabled huge advances in modern applications. This book will enable the reader to make use of this rapidly evolving technology to build highly scalable applications within AWS using different architectures. You will begin with installation of AWS SDK and you will get hands-on experience on creating an application using AWS Management Console and AWS Command Line Interface (CLI). Next you will be integrating Applications with AWS services such as DynamoDB, Amazon Kinesis, AWS Lambda, Amazon SQS and Amazon SWF Following this you will get well versed with CI/CD workflow and work with four major phases in Release processes – Source, Build, Test and Production. Next you will learn to apply AWS developer tools in your Continuous Integration (CI) and Continuous Deployment (CD) WorkFlow. Later you will learn about User Authentication using Amazon Cognito and also how you can evaluate the best architecture as per your infrastructure costs. You will learn about Amazon EC2 service and deploy an app using Amazon EC2.You will also get well versed with container service which is Amazon EC2 Container Service (Amazon ECS) and you will learn to deploy an app using Amazon ECS. Along with EC2 and ECS, you will also deploying a practical real-world example of a CI/CD application with the Serverless Application Framework which is known as AWS Lambda. Finally you will learn how to build, develop and deploy the Application using AWS Developer tools like AWS CodeCommit, AWS CodeBuild, AWS CodeDeploy and AWS CodePipeline as per project needs. Also you can develop and deploy applications within minutes using AWS CodeStar from wizard. By the end of this book, the reader will effectively build, deploy, and manage applications on AWS along with scaling and securing applications with best practices and troubleshooting tips. Style and approach This book covers follows an approach where you will learn the key concepts followed by a real world example and some tips and tricks to make building and deploying easier

A comprehensive guide to mastering the art of preventing your Linux system from getting compromised. About This Book ? Leverage this guide to confidently deliver a system that reduces the risk of being hacked ? Perform a number of advanced Linux security techniques such as network service detection, user authentication, controlling special permissions, encrypting file systems, and much more ? Master the art of securing a Linux environment with this end-to-end practical guide Who This Book Is For If you are a systems administrator or a network engineer interested in making your Linux environment more secure, then this book is for you. Security consultants wanting to enhance their Linux security skills will also benefit from this book. Prior knowledge of Linux is mandatory. What You Will Learn ? Use various techniques to prevent intruders from accessing sensitive data ? Prevent intruders from planting malware, and detect whether malware has been planted ? Prevent insiders from accessing data that they aren’t authorized to access ? Do quick checks to see whether a computer is running network services that it doesn’t need to run ? Learn security techniques that are common to all Linux distros, and some that are distro-specific In Detail This book has extensive coverage of techniques that will help prevent attackers from breaching your system, by building a much more secure Linux environment. You will learn various security techniques such as SSH hardening, network service detection, setting up firewalls, encrypting file systems, protecting user accounts, authentication processes, and so on. Moving forward, you will also develop hands-on skills with advanced Linux permissions, access control, special modes, and more. Lastly, this book will also cover best practices and troubleshooting techniques to get your work done efficiently. By the end of this book, you will be confident in delivering a system that will be much harder to compromise. Style and approach An advanced-level guide filled with real-world examples that will help you secure your Linux system

Learn to design, implement and secure your IoT infrastructure About This Book ? Build a complete IoT system that is the best fit for your organization ? Learn about different concepts, technologies, and tradeoffs in the IoT architectural stack ? Understand the theory, concepts, and implementation of each element that comprises IoT design—from sensors to the cloud ? Implement best practices to ensure the reliability, scalability, robust communication systems, security, and data analysis in your IoT infrastructure Who This Book Is For This book is for architects, system designers, technologists, and technology managers who want to understand the IoT ecosphere, various technologies, and tradeoffs and develop a 50,000-foot view of IoT architecture. What You Will Learn ? Understand the role and scope of architecting a successful IoT deployment, from sensors to the cloud ? Scan the landscape of IoT technologies that span everything from sensors to the cloud and everything in between ? See the trade-offs in choices of protocols and communications in IoT deployments ? Build a repertoire of skills and the vernacular necessary to work in the IoT space ? Broaden your skills in multiple engineering domains necessary for the IoT architect In Detail The Internet of Things (IoT) is the fastest growing technology market. Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is necessary if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of devices. This book encompasses the entire spectrum of IoT solutions, from sensors to the cloud. We start by examining modern sensor systems and focus on their power and functionality. After that, we dive deep into communication theory, paying close attention to near-range PAN, including the new Bluetooth? 5.0 specification and mesh networks. Then, we explore IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, SigFox, and LoRaWAN. Next, we cover edge routing and gateways and their role in fog computing, as well as the messaging protocols of MQTT and CoAP. With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. We wrap up the analytics portion of the book with the application of statistical analysis, complex event processing, and deep learning models. Finally, we conclude by providing a holistic view of the IoT security stack and the anatomical details of IoT exploits while countering them with software defined perimeters and blockchains. Style and approach This hands-on guide combines theory and application to the Internet of Things. This book covers the entire architectural stack of components and engineering domains from sensors to power analysis, communication systems, information theory, networking and routing, data security, protocols, software stacks, cloud mechanics, and data analytics with deep learning.

Build smart, efficient, and fast enterprise-grade web implementation of the microservices architecture that can be easily scaled. About This Book ? Write easy-to-maintain lean and clean code with Kotlin for developing better microservices ? Scale your Microserivces in your own cloud with Docker and Docker Swarm ? Explore Spring 5 functional reactive web programming with Spring WebFlux Who This Book Is For If you are a Kotlin developer with a basic knowledge of microservice architectures and now want to effectively implement these services on enterprise-level web applications, then this book is for you What You Will Learn ? Understand microservice architectures and principles ? Build microservices in Kotlin using Spring Boot 2.0 and Spring Framework 5.0 ? Create reactive microservices that perform non-blocking operations with Spring WebFlux ? Use Spring Data to get data reactively from MongoDB ? Test effectively with JUnit and Kotlin ? Create cloud-native microservices with Spring Cloud ? Build and publish Docker images of your microservices ? Scaling microservices with Docker Swarm ? Monitor microservices with JMX ? Deploy microservices in OpenShift Online In Detail With Google's inclusion of first-class support for Kotlin in their Android ecosystem, Kotlin's future as a mainstream language is assured. Microservices help design scalable, easy-to-maintain web applications; Kotlin allows us to take advantage of modern idioms to simplify our development and create high-quality services. With 100% interoperability with the JVM, Kotlin makes working with existing Java code easier. Well-known Java systems such as Spring, Jackson, and Reactor have included Kotlin modules to exploit its language features. This book guides the reader in designing and implementing services, and producing production-ready, testable, lean code that's shorter and simpler than a traditional Java implementation. Reap the benefits of using the reactive paradigm and take advantage of non-blocking techniques to take your services to the next level in terms of industry standards. You will consume NoSQL databases reactively to allow you to create high-throughput microservices. Create cloud-native microservices that can run on a wide range of cloud providers, and monitor them. You will create Docker containers for your microservices and scale them. Finally, you will deploy your microservices in OpenShift Online. Style and approach This book guides the reader in designing and implementing services, achieving production- ready, testable, easy-to-maintain, lean code that's shorter and simpler than a traditional Java implementation.

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. About This Book ? Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j ? Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way ? Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework. Who This Book Is For If you want to leverage the power of both Scala and Spark to make sense of Big Data, then this book is for you. If you are well versed with machine learning concepts and wants to expand your knowledge by delving into the practical implementation using the power of Scala, then this book is what you need! Strong understanding of Scala Programming language is recommended. Basic familiarity with machine Learning techniques will be more helpful. What You Will Learn ? Apply advanced regression techniques to boost the performance of predictive models ? Use different classification algorithms for business analytics ? Generate trading strategies for Bitcoin and stock trading using ensemble techniques ? Train Deep Neural Networks (DNN) using H2O and Spark ML ? Utilize NLP to build scalable machine learning models ? Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application ? Learn how to use autoencoders to develop a fraud detection application ? Implement LSTM and CNN models using DeepLearning4j and MXNet In Detail Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment. Style and approach Leverage the power of machine learning and deep learning in different domains, giving best practices and tips from a real world case studies and help you to avoid pitfalls and fallacies towards decision making based on predictive analytics with ML models.

Write code that scales across CPU registers, multi-core, and machine clusters About This Book ? Explore concurrent programming in C++ ? Identify memory management problems ? Use SIMD and STL containers for performance improvement Who This Book Is For If you're a C++ developer looking to improve the speed of your code or simply wanting to take your skills up to the next level, then this book is perfect for you. What You Will Learn ? Find out how to use exciting new tools that will help you improve your code ? Identify bottlenecks to optimize your code ? Develop applications that utilize GPU computation ? Reap the benefits of concurrent programming ? Write code that can protect against application errors using error handling ? Use STL containers and algorithms effciently ? Extend your toolbox with Boost containers ? Achieve effcient memory management by using custom memory allocators In Detail C++ is a highly portable language and can be used to write complex applications and performance-critical code. It has evolved over the last few years to become a modern and expressive language. This book will guide you through optimizing the performance of your C++ apps by allowing them to run faster and consume fewer resources on the device they're running on. The book begins by helping you to identify the bottlenecks in C++. It then moves on to measuring performance, and you'll see how this affects the way you write code. Next, you'll see the importance of data structure optimization and how it can be used efficiently. After that, you'll see which algorithm should be used to achieve faster execution, followed by how to use STL containers. Moving on, you'll learn how to improve memory management in C++. You'll get hands on experience making use of multiple cores to enable more efficient and faster execution. The book ends with a brief overview of utilizing the capabilities of your GPU by using Boost Compute and OpenCL. Style and approach This easy-to-follow guide is full of examples and self-sufficient code snippets that help you with high performance programming with C++. You’ll get your hands dirty with this all-inclusive guide that uncovers hidden performance improvement areas for any C++ code.

Discover techniques and tools for building serverless applications with AWS About This Book ? Get well-versed with building and deploying serverless APIs with microservices ? Learn to build distributed applications and microservices with AWS Step Functions ? A step-by-step guide that will get you up and running with building and managing applications on the AWS platform Who This Book Is For If you are an I.T. professional or a system architect who wants to improve infrastructure using AWS, then this book is for you. It is also for programmers who are new to AWS and want to build highly efficient, scalable applications. What You Will Learn ? Set up your AWS account and get started with the basic concepts of AWS ? Learn about AWS terminology and identity access management ? Acquaint yourself with important elements of the cloud with features such as computing, ELB, and VPC ? Back up your database and ensure high availability by having an understanding of database-related services in the AWS cloud ? Integrate AWS services with your application to meet and exceed non-functional requirements ? Create and automate infrastructure to design cost-effective, highly available applications In Detail Amazon Web Services (AWS) is the most popular and widely-used cloud platform. Administering and deploying application on AWS makes the applications resilient and robust. The main focus of the book is to cover the basic concepts of cloud-based development followed by running solutions in AWS Cloud, which will help the solutions run at scale. This book not only guides you through the trade-offs and ideas behind efficient cloud applications, but is a comprehensive guide to getting the most out of AWS. In the first section, you will begin by looking at the key concepts of AWS, setting up your AWS account, and operating it. This guide also covers cloud service models, which will help you build highly scalable and secure applications on the AWS platform. We will then dive deep into concepts of cloud computing with S3 storage, RDS and EC2. Next, this book will walk you through VPC, building realtime serverless environments, and deploying serverless APIs with microservices. Finally, this book will teach you to monitor your applications, and automate your infrastructure and deploy with CloudFormation. By the end of this book, you will be well-versed with the various services that AWS provides and will be able to leverage AWS infrastructure to accelerate the development process. Style and approach ? Learn to write, run, and deploy applications in the AWS cloud ? Make the most of AWS to build scalable and cost-efficient systems ? A practical guide to developing serverless services and make the applications run faster

Learn how to solve blocking user experience and build event based reactive applications with Swift. About This Book ? Build fast and scalable apps with RxSwift ? Apply reactive programming to solve complex problems and build efficient programs with reactive user interfaces ? Take expressiveness, scalability, and maintainability of your Swift code to the next level with this practical guide Who This Book Is For This book is for the developers who are familiar with Swift and iOS application development and are looking out to reduce the complexity of their apps. Prior experience of reactive programming is not necessary. What You Will Learn ? Understand the practical benefits of Rx on a mobile platform ? Explore the building blocks of Rx, and Rx data flows with marble diagrams ? Learn how to convert an existing code base into RxSwift code base ? Learn how to debug and test your Rx Code ? Work with Playgrounds to transform sequences by filtering them using map, flatmap and other operators ? Learn how to combine different operators to work with Events in a more controlled manner. ? Discover RxCocoa and convert your simple UI elements to Reactive components ? Build a complete RxSwift app using MVVM as design pattern In Detail RxSwift belongs to a large family of Rx implementations in different programming languages that share almost identical syntax and semantics. Reactive approach will help you to write clean, cohesive, resilient, scalable, and maintainable code with highly configurable behavior. This book will introduce you to the world of reactive programming, primarily focusing on mobile platforms. It will tell how you can benefit from using RxSwift in your projects, existing or new. Further on, the book will demonstrate the unbelievable ease of configuring asynchronous behavior and other aspects of the app that are traditionally considered to be hard to implement and maintain. It will explain what Rx is made of, and how to switch to reactive way of thinking to get the most out of it. Also, test production code using RxTest and the red/ green approach. Finally, the book will dive into real-world recipes and show you how to build a real-world app by applying the reactive paradigm. By the end of the book, you’ll be able to build a reactive swift application by leveraging all the concepts this book takes you through. Style and approach This book is a definite tutorial in FRP with Swift filled with well-described examples.

Build fault-tolerant, robust, and distributed applications in Scala About This Book ? Understand and use the concepts of reactive programming to build distributed systems running on multiple nodes. ? Learn how reactive architecture reduces complexity throughout the development process. ? Get to grips with functional reactive programming and Reactive Microservices. Who This Book Is For This book is for Scala developers who would like to build fault-tolerant, scalable distributed systems. No knowledge of Reactive programming is required. What You Will Learn ? Understand the fundamental principles of Reactive and Functional programming ? Develop applications utilizing features of the Akka framework ? Explore techniques to integrate Scala, Akka, and Play together ? Learn about Reactive Streams with real-time use cases ? Develop Reactive Web Applications with Play, Scala, Akka, and Akka Streams ? Develop and deploy Reactive microservices using the Lagom framework and ConductR In Detail Reactive programming is a scalable, fast way to build applications, and one that helps us write code that is concise, clear, and readable. It can be used for many purposes such as GUIs, robotics, music, and others, and is central to many concurrent systems. This book will be your guide to getting started with Reactive programming in Scala. You will begin with the fundamental concepts of Reactive programming and gradually move on to working with asynchronous data streams. You will then start building an application using Akka Actors and extend it using the Play framework. You will also learn about reactive stream specifications, event sourcing techniques, and different methods to integrate Akka Streams into the Play Framework. This book will also take you one step forward by showing you the advantages of the Lagom framework while working with reactive microservices. You will also learn to scale applications using multi-node clusters and test, secure, and deploy your microservices to the cloud. By the end of the book, you will have gained the knowledge to build robust and distributed systems with Scala and Akka. Style and approach The book takes a pragmatic approach, showing you how to build a scalable distributed system using Scala and Akka.

Explore various Generative Adversarial Network architectures using the Python ecosystem Key Features * Use different datasets to build advanced projects in the Generative Adversarial Network domain * Implement projects ranging from generating 3D shapes to a face aging application * Explore the power of GANs to contribute in open source research and projects Book Description Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you’ll gain an understanding of the architecture and functioning of generative models through their practical implementation. By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects. What you will learn * Train a network on the 3D ShapeNet dataset to generate realistic shapes * Generate anime characters using the Keras implementation of DCGAN * Implement an SRGAN network to generate high-resolution images * Train Age-cGAN on Wiki-Cropped images to improve face verification * Use Conditional GANs for image-to-image translation * Understand the generator and discriminator implementations of StackGAN in Keras Who this book is for If you’re a data scientist, machine learning developer, deep learning practitioner, or AI enthusiast looking for a project guide to test your knowledge and expertise in building real-world GANs models, this book is for you.

Discover the unified, distributed storage system and improve the performance of applications Key Features * Explore the latest features of Ceph's Mimic release * Get to grips with advanced disaster and recovery practices for your storage * Harness the power of Reliable Autonomic Distributed Object Store (RADOS) to help you optimize storage systems Book Description Ceph is an open source distributed storage system that is scalable to Exabyte deployments. This second edition of Mastering Ceph takes you a step closer to becoming an expert on Ceph. You’ll get started by understanding the design goals and planning steps that should be undertaken to ensure successful deployments. In the next sections, you’ll be guided through setting up and deploying the Ceph cluster with the help of orchestration tools. This will allow you to witness Ceph’s scalability, erasure coding (data protective) mechanism, and automated data backup features on multiple servers. You’ll then discover more about the key areas of Ceph including BlueStore, erasure coding and cache tiering with the help of examples. Next, you’ll also learn some of the ways to export Ceph into non-native environments and understand some of the pitfalls that you may encounter. The book features a section on tuning that will take you through the process of optimizing both Ceph and its supporting infrastructure. You’ll also learn to develop applications, which use Librados and distributed computations with shared object classes. Toward the concluding chapters, you’ll learn to troubleshoot issues and handle various scenarios where Ceph is not likely to recover on its own. By the end of this book, you’ll be able to master storage management with Ceph and generate solutions for managing your infrastructure. What you will learn * Plan, design and deploy a Ceph cluster * Get well-versed with different features and storage methods * Carry out regular maintenance and daily operations with ease * Tune Ceph for improved ROI and performance * Recover Ceph from a range of issues * Upgrade clusters to BlueStore Who this book is for If you are a storage professional, system administrator, or cloud engineer looking for guidance on building powerful storage solutions for your cloud and on-premise infrastructure, this book is for you.

Discover end-to-end penetration testing solutions to enhance your ethical hacking skills Key Features * Practical recipes to conduct effective penetration testing using the latest version of Kali Linux * Leverage tools like Metasploit, Wireshark, Nmap, and more to detect vulnerabilities with ease * Confidently perform networking and application attacks using task-oriented recipes Book Description Many organizations have been affected by recent cyber events. At the current rate of hacking, it has become more important than ever to pentest your environment in order to ensure advanced-level security. This book is packed with practical recipes that will quickly get you started with Kali Linux (version 2018.4 / 2019), in addition to covering the core functionalities. The book will get you off to a strong start by introducing you to the installation and configuration of Kali Linux, which will help you to perform your tests. You will also learn how to plan attack strategies and perform web application exploitation using tools such as Burp and JexBoss. As you progress, you will get to grips with performing network exploitation using Metasploit, Sparta, and Wireshark. The book will also help you delve into the technique of carrying out wireless and password attacks using tools such as Patator, John the Ripper, and airoscript-ng. Later chapters will draw focus to the wide range of tools that help in forensics investigations and incident response mechanisms. As you wrap up the concluding chapters, you will learn to create an optimum quality pentest report. By the end of this book, you will be equipped with the knowledge you need to conduct advanced penetration testing, thanks to the book’s crisp and task-oriented recipes. What you will learn * Learn how to install, set up and customize Kali for pentesting on multiple platforms * Pentest routers and embedded devices * Get insights into fiddling around with software-defined radio * Pwn and escalate through a corporate network * Write good quality security reports * Explore digital forensics and memory analysis with Kali Linux Who this book is for If you are an IT security professional, pentester, or security analyst who wants to conduct advanced penetration testing techniques, then this book is for you. Basic knowledge of Kali Linux is assumed.

Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key Features *Understand the common architecture of different types of GANs *Train, optimize, and deploy GAN applications using TensorFlow and Keras *Build generative models with real-world data sets, including 2D and 3D data Book Description Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand. This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use. By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away. What you will learn *Structure a GAN architecture in pseudocode *Understand the common architecture for each of the GAN models you will build *Implement different GAN architectures in TensorFlow and Keras *Use different datasets to enable neural network functionality in GAN models *Combine different GAN models and learn how to fine-tune them *Produce a model that can take 2D images and produce 3D models *Develop a GAN to do style transfer with Pix2Pix Who this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.

A comprehensive guide in developing and deploying high performance microservices with Rust Key Features * Start your microservices journey and get a broader perspective on microservices development using RUST 2018, * Build, deploy, and test microservices using AWS * Explore advanced techniques for developing microservices such as actor model, Requests Routing, and threads Book Description Microservice architecture is sweeping the world as the de facto pattern for building web-based applications. Rust is a language particularly well-suited for building microservices. It is a new system programming language that offers a practical and safe alternative to C. This book describes web development using the Rust programming language and will get you up and running with modern web frameworks and crates with examples of RESTful microservices creation. You will deep dive into Reactive programming, and asynchronous programming, and split your web application into a set of concurrent actors. The book provides several HTTP-handling examples with manageable memory allocations. You will walk through stateless high-performance microservices, which are ideally suitable for computation or caching tasks, and look at stateful microservices, which are filled with persistent data and database interactions. As we move along, you will learn how to use Rust macros to describe business or protocol entities of our application and compile them into native structs, which will be performed at full speed with the help of the server's CPU. Finally, you will be taken through examples of how to test and debug microservices and pack them into a tiny monolithic binary or put them into a container and deploy them to modern cloud platforms such as AWS. What you will learn * Get acquainted with leveraging Rust web programming * Get to grips with various Rust crates, such as hyper, Tokio, and Actix * Explore RESTful microservices with Rust * Understand how to pack Rust code to a container using Docker * Familiarize yourself with Reactive microservices * Deploy your microservices to modern cloud platforms such as AWS Who this book is for This book is for developers who have basic knowledge of RUST, and want to learn how to build, test, scale, and manage RUST microservices. No prior experience of writing microservices in RUST is assumed.