Swift Functional Programming. Ease the creation, testing, and maintenance of Swift codes - Second Edition

Dr. Fatih Nayebi

Swift is a multi-paradigm programming language enabling you to tackle different problems in various ways. Understanding each paradigm and knowing when and how to utilize and combine them can lead to a better code base. Functional programming (FP) is an important paradigm that empowers us with declarative development and makes applications more suitable for testing, as well as performant and elegant. This book aims to simplify the FP paradigms, making them easily understandable and usable, by showing you how to solve many of your day-to-day development problems using Swift FP.It starts with the basics of FP, and you will go through all the core concepts of Swift and the building blocks of FP. You will also go through important aspects, such as function composition and currying, custom operator definition, monads, functors, applicative functors,memoization, lenses, algebraic data types, type erasure, functional data structures, functional reactive programming (FRP), and protocol-oriented programming(POP). You will then learn to combine those techniques to develop a fully functional iOS application from scratch

Learning Elasticsearch. Structured and unstructured data using distributed real-time search and analytics

Abhishek Andhavarapu

Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. You can use Elasticsearch for small or large applications with billions of documents. It is built to scale horizontally and can handle both structured and unstructured data. Packed with easy-to- follow examples, this book will ensure you will have a firm understanding of the basics of Elasticsearch and know how to utilize its capabilities efficiently.You will install and set up Elasticsearch and Kibana, and handle documents using the Distributed Document Store. You will see how to query, search, and index your data, and perform aggregation-based analytics with ease. You will see how to use Kibana to explore and visualize your data. Further on, you will learn to handle document relationships, work with geospatial data, and much more, with this easy-to-follow guide. Finally, you will see how you can set up and scale your Elasticsearch clusters in production environments.

Information Security Handbook. Develop a threat model and incident response strategy to build a strong information security framework

Darren Death

Having an information security mechanism is one of the most crucial factors for any organization. Important assets of organization demand a proper risk management and threat model for security, and so information security concepts are gaining a lot of traction. This book starts with the concept of information security and shows you why it’s important.It then moves on to modules such as threat modeling, risk management, and mitigation. It also covers the concepts of incident response systems, information rights management, and more. Moving on, it guides you to build your own information security framework as the best fit for your organization. Toward the end, you’ll discover some best practices that can be implemented to make your security framework strong. By the end of this book, you will be well-versed with all the factors involved in information security, which will help you build a security framework that is a perfect fit your organization’s requirements.

Apache Spark Deep Learning Cookbook. Over 80 best practice recipes for the distributed training and deployment of neural networks using Keras and TensorFlow

Ahmed Sherif, Amrith Ravindra

Organizations these days need to integrate popular big data tools such as Apache Spark with highly efficient deep learning libraries if they’re looking to gain faster and more powerful insights from their data. With this book, you’ll discover over 80 recipes to help you train fast, enterprise-grade, deep learning models on Apache Spark.Each recipe addresses a specific problem, and offers a proven, best-practice solution to difficulties encountered while implementing various deep learning algorithms in a distributed environment. The book follows a systematic approach, featuring a balance of theory and tips with best practice solutions to assist you with training different types of neural networks such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs). You’ll also have access to code written in TensorFlow and Keras that you can run on Spark to solve a variety of deep learning problems in computer vision and natural language processing (NLP), or tweak to tackle other problems encountered in deep learning.By the end of this book, you'll have the skills you need to train and deploy state-of-the-art deep learning models on Apache Spark.

Learning Apache Cassandra. Managing fault-tolerant, scalable data with high performance - Second Edition

Sandeep Yarabarla

Cassandra is a distributed database that stands out thanks to its robust feature set and intuitive interface, while providing high availability and scalability of a distributed data store. This book will introduce you to the rich feature set offered by Cassandra, and empower you to create and manage a highly scalable, performant and fault-tolerant database layer.The book starts by explaining the new features implemented in Cassandra 3.x and get you set up with Cassandra. Then you’ll walk through data modeling in Cassandra and the rich feature set available to design a flexible schema. Next you’ll learn to create tables with composite partition keys, collections and user-defined types and get to know different methods to avoid denormalization of data. You will then proceed to create user-defined functions and aggregates in Cassandra. Then, you will set up a multi node cluster and see how the dynamics of Cassandra change with it. Finally, you will implement some application-level optimizations using a Java client.By the end of this book, you'll be fully equipped to build powerful, scalable Cassandra database layers for your applications.

Hands-On Reactive Programming with Reactor. Build reactive and scalable microservices using the Reactor framework

Rahul Sharma

Reactor is an implementation of the Java 9 Reactive Streams specification, an API for asynchronous data processing. This specification is based on a reactive programming paradigm, enabling developers to build enterprise-grade, robust applications with reduced complexity and in less time. Hands-On Reactive Programming with Reactor shows you how Reactor works, as well as how to use it to develop reactive applications in Java.The book begins with the fundamentals of Reactor and the role it plays in building effective applications. You will learn how to build fully non-blocking applications and will later be guided by the Publisher and Subscriber APIs. You will gain an understanding how to use two reactive composable APIs, Flux and Mono, which are used extensively to implement Reactive Extensions. All of these components are combined using various operations to build a complete solution. In addition to this, you will get to grips with the Flow API and understand backpressure in order to control overruns. You will also study the use of Spring WebFlux, an extension of the Reactor framework for building microservices.By the end of the book, you will have gained enough confidence to build reactive and scalable microservices.

Android Development with Kotlin. Enhance your skills for Android development using Kotlin

Igor Wojda, Marcin Moskala

Nowadays, improved application development does not just mean building better performing applications. It has become crucial to find improved ways of writing code. Kotlin is a language that helps developers build amazing Android applications easily and effectively. This book discusses Kotlin features in context of Android development. It demonstrates how common examples that are typical for Android development, can be simplified using Kotlin. It also shows all the benefits, improvements and new possibilities provided by this language.The book is divided in three modules that show the power of Kotlin and teach you how to use it properly. Each module present features in different levels of advancement. The first module covers Kotlin basics. This module will lay a firm foundation for the rest of the chapters so you are able to read and understand most of the Kotlin code. The next module dives deeper into the building blocks of Kotlin, such as functions, classes, and function types. You will learn how Kotlin brings many improvements to the table by improving common Java concepts and decreasing code verbosity. The last module presents features that are not present in Java. You will learn how certain tasks can be achieved in simpler ways thanks to Kotlin.Through the book, you will learn how to use Kotlin for Android development. You will get to know and understand most important Kotlin features, and how they can be used. You will be ready to start your own adventure with Android development with Kotlin.

Microservices Deployment Cookbook. Deploy and manage scalable microservices

Vikram Murugesan

This book will help any team or organization understand, deploy, and manage microservices at scale. It is driven by a sample application, helping you gradually build a complete microservice-based ecosystem. Rather than just focusing on writing a microservice, this book addresses various other microservice-related solutions: deployments, clustering, load balancing, logging, streaming, and monitoring.The initial chapters offer insights into how web and enterprise apps can be migrated to scalable microservices. Moving on, you’ll see how to Dockerize your application so that it is ready to be shipped and deployed. We will look at how to deploy microservices on Mesos and Marathon and will also deploy microservices on Kubernetes. Next, you will implement service discovery and load balancing for your microservices. We’ll also show you how to build asynchronous streaming systems using Kafka Streams and Apache Spark. Finally, we wind up by aggregating your logs in Kafka, creating your own metrics, and monitoring the metrics for the microservice.