A journey toward containerized applications in production with a cloud-portable, secure, robust and highly available Docker Enterprise platform. Key Features * Get an insider’s view into the container movement and Docker Enterprise * Manage the transformation associated with enterprise container adoption * Walk through the enterprise container adoption journey Book Description While known mostly as the open source engine behind tens of millions of server nodes, Docker also offers commercially supported enterprise tooling known as the Docker Enterprise. This platform leverages the deep roots from Docker Engine - Community (formerly Docker CE) and Kubernetes, but adds support and tooling to efficiently operate a secure container platform at scale. With hundreds of enterprises on board, best practices and adoption patterns are emerging rapidly. These learning points can be used to inform adopters and help manage the enterprise transformation associated with enterprise container adoption. This book starts by explaining the case for Docker Enterprise, as well as its structure and reference architecture. From there, we progress through the PoC,pilot and production stages as a working model for adoption, evolving the platform’s design and configuration for each stage and using detailed application examples along the way to clarify and demonstrate important concepts.The book concludes with Docker’s impact on other emerging software technologies, such as Blockchain and Serverless computing. By the end of this book, you’ll have a better understanding of what it takes to get your enterprise up and running with Docker Enterprise and beyond. What you will learn * Understand why containers are important to an enterprise * Understand the features and components of Docker Enterprise 2 * Find out about the PoC, pilot, and production adoption phases * Get to know the best practices for installing and operating Docker Enterprise * Understand what is important for a Docker Enterprise in production * Run Kubernetes on Docker Enterprise Who this book is for This book is for Software Architects, DevOps Engineers, Tech Ops, Docker professionals, or any IT professional working with Docker and containers who wants to move containerized workloads to production. This book discusses the enterprise adoption of Docker and Kubernetes,therefore a basic understanding of Docker concepts will be helpful.

Enhance and secure your datacenter with the newest Microsoft server platform Key Features * Develop necessary skills to design and implement Microsoft Server 2019 in enterprise environment * Provide support to your medium to large enterprise and leverage your experience in administering Microsoft Server 2019 * Effectively administering Windows server 2019 with the help of practical examples Book Description Mastering Windows Server 2019 – Second Edition covers all of the essential information needed to implement and utilize this latest-and-greatest platform as the core of your data center computing needs. You will begin by installing and managing Windows Server 2019, and by clearing up common points of confusion surrounding the versions and licensing of this new product. Centralized management, monitoring, and configuration of servers is key to an efficient IT department, and you will discover multiple methods for quickly managing all of your servers from a single pane of glass. To this end, you will spend time inside Server Manager, PowerShell, and even the new Windows Admin Center, formerly known as Project Honolulu. Even though this book is focused on Windows Server 2019 LTSC, we will still discuss containers and Nano Server, which are more commonly related to the SAC channel of the server platform, for a well-rounded exposition of all aspects of using Windows Server in your environment. We also discuss the various remote access technologies available in this operating system, as well as guidelines for virtualizing your data center with Hyper-V. By the end of this book, you will have all the ammunition required to start planning for, implementing, and managing Windows. What you will learn * Work with the updated Windows Server 2019 interface, including Server Core and Windows Admin Center * Secure your network and data with new technologies in Windows Server 2019 * Learn about containers and understand the appropriate situations to use Nano Server * Discover new ways to integrate your data center with Microsoft Azure * Harden your Windows Servers to help keep the bad guys out * Virtualize your data center with Hyper-V Who this book is for If you are a System Administrator or an IT professional interested in designing and deploying Windows Server 2019 then this book is for you. Previous experience of Windows Server operating systems and familiarity with networking concepts is required.

Begin your iOS 12 app development journey with this practical guide Key Features *Kick-start your iOS programming career and have fun building iOS apps of your choice *Get to grips with Xcode 10 and Swift 4.2, the building blocks of iOS development *Discover the latest features of iOS 12 - SiriKit, notifications, and much more Book Description Want to build iOS 12 applications from scratch with the latest Swift 4.2 language and Xcode 10 by your side? Forget sifting through tutorials and blog posts; this book is a direct route to iOS development, taking you through the basics and showing you how to put principles into practice. Take advantage of this developer-friendly guide and start building applications that may just take the App Store by storm! If you’re already an experienced programmer, you can jump right in and learn the latest iOS 12 features. For beginners, this book starts by introducing you to iOS development as you learn Xcode and Swift. You'll also study advanced iOS design topics, such as gestures and animations, to give your app the edge. You’ll explore the latest Swift 4.2 and iOS 12 developments by incorporating new features, such as the latest in notifications, custom-UI notifications, maps, and the recent additions in Sirikit. The book will guide you in using TestFlight to quickly get to grips with everything you need to get your project on the App Store. By the end of this book, you'll be ready to start building your own cool iOS applications confidently. What you will learn *Explore the distinctive design principles that define the iOS user experience *Navigate panels within an Xcode project *Use the latest Xcode asset catalogue of Xcode 10 *Create a playgrounds project within your projects and understand how Ranges and Control flow work *Study operations with integers and work your way through if statements *Build a responsive UI and add privacy to your custom-rich notifications *Set up Sirikit to add voice for Siri shortcuts *Collect valuable feedback with TestFlight before releasing your apps on the App Store Who this book is for This book is for you if you are completely new to Swift, iOS, or programming and want to make iOS applications. However, you’ll also find this book useful if you’re an experienced programmer looking to explore the latest iOS 12 features.

Don't waste your energy thinking about servers; use AWS to build enterprise-grade serverless applications. Key Features *Learn how to quickly and easily go serverless *Explore AWS and Lambda: the first building blocks of serverless applications on AWS *Study different approaches to deploy and maintain serverless applications Book Description Serverless Architecture with AWS begins with an introduction to the serverless model and helps you get started with AWS and Lambda. You'll also get to grips with other capabilities of the AWS Serverless Platform and see how AWS supports enterprise-grade serverless applications with and without Lambda. This book will guide you in deploying your first serverless project and exploring the capabilities of serverless Amazon Athena, an interactive query service that makes it easy to analyze data in Amazon Simple Storage Service (S3 Amazon) using standard SQL. You’ll also learn about AWS Glue, a fully managed ETL service that makes categorizing data easy and cost-effective. You'll study how Amazon Kinesis makes it possible to unleash the potential of real-time data insights and analytics with capabilities such as video streams, data streams, data firehose, and data analytics. Last but not least, you’ll be equipped to combine Amazon Kinesis capabilities with AWS Lambda to create lightweight serverless architectures. By the end of the book, you will be ready to create and run your first serverless application that takes advantage of the high availability, security, performance, and scalability of AWS. What you will learn *Explore AWS services for supporting a serverless environment *Set up AWS services to make applications scalable and highly available *Deploy a static website with a serverless architecture *Build your first serverless web application *Study the changes in a deployed serverless web application *Apply best practices to ensure overall security, availability, and reliability Who this book is for This book is for you if you want to develop serverless applications and have some prior coding experience. Though no prior experience of AWS is needed, basic knowledge of Java or Node.js will be an added advantage.

Master shell basics and Unix tools and discover easy commands to perform complex tasks with speed Key Features *Learn why the Bash shell is widely used on Linux and iOS *Explore advanced shell concepts, such as pipes and redirection *Understand how to use Unix command-line tools as building blocks for different tasks Book Description The most basic interface to a computer—the command line—remains the most flexible and powerful way of processing data and performing and automating various day-to-day tasks. Command Line Fundamentals begins by exploring the basics, and then focuses on the most common tool, the Bash shell (which is standard on all Linux and iOS systems). As you make your way through the book, you'll explore the traditional Unix command-line programs as implemented by the GNU project. You'll also learn to use redirection and pipelines to assemble these programs to solve complex problems. By the end of this book, you'll have explored the basics of shell scripting, allowing you to easily and quickly automate tasks. What you will learn *Use the Bash shell to run commands *Utilize basic Unix utilities such as cat, tr, sort, and uniq *Explore shell wildcards to manage groups of files *Apply useful keyboard shortcuts in shell *Employ redirection and pipes to process data *Write both basic and advanced shell scripts to automate tasks Who this book is for Command Line Fundamentals is for programmers who use GUIs but want to understand how to use the command line to complete tasks faster.

Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework Key Features *Master the art of real-time big data processing and machine learning *Explore a wide range of use-cases to analyze large data *Discover ways to optimize your work by using many features of Spark 2.x and Scala Book Description Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: *Mastering Apache Spark 2.x by Romeo Kienzler *Scala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla *Apache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook What you will learn *Get to grips with all the features of Apache Spark 2.x *Perform highly optimized real-time big data processing *Use ML and DL techniques with Spark MLlib and third-party tools *Analyze structured and unstructured data using SparkSQL and GraphX *Understand tuning, debugging, and monitoring of big data applications *Build scalable and fault-tolerant streaming applications *Develop scalable recommendation engines Who this book is for If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.x using modern tools Key Features *Work with powerful open-source libraries for data wrangling, analysis, and visualization *Develop full-featured, full-stack web applications *Learn to perform supervised and unsupervised machine learning and time series analysis with Julia Book Description Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing. After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI. Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting. We'll close with package development, documenting, testing and benchmarking. By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia. What you will learn *Leverage Julia's strengths, its top packages, and main IDE options *Analyze and manipulate datasets using Julia and DataFrames *Write complex code while building real-life Julia applications *Develop and run a web app using Julia and the HTTP package *Build a recommender system using supervised machine learning *Perform exploratory data analysis *Apply unsupervised machine learning algorithms *Perform time series data analysis, visualization, and forecasting Who this book is for Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed.

Web penetration testing by becoming an ethical hacker. Protect the web by learning the tools, and the tricks of the web application attacker. Key Features * Builds on books and courses on penetration testing for beginners * Covers both attack and defense perspectives * Examines which tool to deploy to suit different applications and situations Book Description Becoming the Hacker will teach you how to approach web penetration testing with an attacker's mindset. While testing web applications for performance is common, the ever-changing threat landscape makes security testing much more difficult for the defender. There are many web application tools that claim to provide a complete survey and defense against potential threats, but they must be analyzed in line with the security needs of each web application or service. We must understand how an attacker approaches a web application and the implications of breaching its defenses. Through the first part of the book, Adrian Pruteanu walks you through commonly encountered vulnerabilities and how to take advantage of them to achieve your goal. The latter part of the book shifts gears and puts the newly learned techniques into practice, going over scenarios where the target may be a popular content management system or a containerized application and its network. Becoming the Hacker is a clear guide to web application security from an attacker's point of view, from which both sides can benefit. What you will learn * Study the mindset of an attacker * Adopt defensive strategies * Classify and plan for standard web application security threats * Prepare to combat standard system security problems * Defend WordPress and mobile applications * Use security tools and plan for defense against remote execution Who this book is for The reader should have basic security experience, for example, through running a network or encountering security issues during application development. Formal education in security is useful, but not required. This title is suitable for people with at least two years of experience in development, network management, or DevOps, or with an established interest in security.

A practical guide for solving complex data processing challenges by applying the best optimizations techniques in Apache Spark. Key Features * Learn about the core concepts and the latest developments in Apache Spark * Master writing efficient big data applications with Spark’s built-in modules for SQL, Streaming, Machine Learning and Graph analysis * Get introduced to a variety of optimizations based on the actual experience Book Description Apache Spark is a flexible framework that allows processing of batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to get started with Apache Spark 2.0 and write big data applications for a variety of use cases. It will also introduce you to Apache Spark – one of the most popular Big Data processing frameworks. Although this book is intended to help you get started with Apache Spark, but it also focuses on explaining the core concepts. This practical guide provides a quick start to the Spark 2.0 architecture and its components. It teaches you how to set up Spark on your local machine. As we move ahead, you will be introduced to resilient distributed datasets (RDDs) and DataFrame APIs, and their corresponding transformations and actions. Then, we move on to the life cycle of a Spark application and learn about the techniques used to debug slow-running applications. You will also go through Spark’s built-in modules for SQL, streaming, machine learning, and graph analysis. Finally, the book will lay out the best practices and optimization techniques that are key for writing efficient Spark applications. By the end of this book, you will have a sound fundamental understanding of the Apache Spark framework and you will be able to write and optimize Spark applications. What you will learn * Learn core concepts such as RDDs, DataFrames, transformations, and more * Set up a Spark development environment * Choose the right APIs for your applications * Understand Spark’s architecture and the execution flow of a Spark application * Explore built-in modules for SQL, streaming, ML, and graph analysis * Optimize your Spark job for better performance Who this book is for If you are a big data enthusiast and love processing huge amount of data, this book is for you. If you are data engineer and looking for the best optimization techniques for your Spark applications, then you will find this book helpful. This book also helps data scientists who want to implement their machine learning algorithms in Spark. You need to have a basic understanding of any one of the programming languages such as Scala, Python or Java.

A step-by-step approach to building stunning dashboards with QlikView Key Features * Perform effective storytelling through interactive dashboards built with QlikView * Create different types of visualizations from a variety of data sources * Includes tips, tricks, and best practices to perform effective Business Intelligence using QlikView Book Description QlikView is one of the market leaders when it comes to building effective Business Intelligence solutions. This book will show how you can leverage its power to build your own dashboards to tell your own data story. The book starts with showing you how to connect your data to QlikView and create your own QlikView application. You will learn how to add data from multiple sources, create a data model by joining data, and then review it on the front end. You will work with QlikView components such as charts, list boxes, input boxes, and text objects to create stunning visualizations that help give actionable business insights. You will also learn how to perform analysis on your data in QlikView and master the various types of security measures to be taken in QlikView. By the end of this book, you will have all the essential knowledge required for insightful data storytelling and creating useful BI dashboards using QlikView. What you will learn * Learn to use the latest and newest features of QlikView * Connect QlikView to various data sources, such as databases and websites * Create a fully featured data model without circular references * Display your data in maps, charts, and text across multiple sheets * Apply set analysis to your data in QlikView expressions * Secure your data based on the various audience types Who this book is for This book is best suited for BI professionals, data analysts and budding QlikView developers who wish to build effective dashboards using QlikView. Some basic understanding of the data visualization concepts and Business Intelligence is required.

Use Qt 5 to design and build functional, appealing, and user-friendly graphical user interfaces (GUIs) for your applications. Key Features * Learn to use Qt 5 to design and customize the look and feel of your application * Improve the visual quality of an application by using graphics rendering and animation * Understand the balance of presentation and web content that will make an application appealing yet functional Book Description With the growing need to develop GUIs for multiple targets and multiple screens, improving the visual quality of your application becomes important so that it stands out from your competitors. With its cross-platform ability and the latest UI paradigms, Qt makes it possible to build intuitive, interactive, and user-friendly user interfaces for your applications. Qt5 C++ GUI Programming Cookbook, Second Edition teaches you how to develop functional and appealing user interfaces using the latest version of QT5 and C++.?This book will help you learn a variety of topics such as GUI customization and animation, graphics rendering, implementing Google Maps, and more. You will also be taken through advanced concepts like asynchronous programming, event handling using signals and slots, network programming, various aspects of optimizing your application. By the end of the book, you will be confident to design and customize GUI applications that meet your clients' expectations and have an understanding of best practice solutions for common problems. What you will learn * Animate GUI elements using Qt5's built-in animation system * Draw shapes and 2D images using Qt5's powerful rendering system * Implement an industry-standard OpenGL library in your project * Build a mobile app that supports touch events and exports it onto devices * Parse and extract data from an XML file and present it on your GUI * Interact with web content by calling JavaScript functions from C++ * Access MySQL and SQLite databases to retrieve data and display it on your GUI Who this book is for This intermediate-level book is designed for those who want to develop software using Qt 5. If you want to improve the visual quality and content presentation of your software application, this book is for you. Prior experience of C++ programming is required.

Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key Features * Build state-of-the-art algorithms that can solve your business' problems * Learn how to find hidden patterns in your data * Revise key concepts with hands-on exercises using real-world datasets Book Description Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection. What you will learn * Implement clustering methods such as k-means, agglomerative, and divisive * Write code in R to analyze market segmentation and consumer behavior * Estimate distribution and probabilities of different outcomes * Implement dimension reduction using principal component analysis * Apply anomaly detection methods to identify fraud * Design algorithms with R and learn how to edit or improve code Who this book is for Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including exponents, square roots, means, and medians.

Create powerful data visualizations and unlock intelligent business insights with Tableau Key Features * Explore all the latest Tableau 2019 features and redefine business analytics for your organization * Create impressive data visualizations and interactive dashboards to get insights from your data * Learn effective data storytelling to transform how your business leverages data and makes decisions Book Description Tableau is the gold standard of business intelligence and visual analytics tools in every industry. It enables rapid data visualization and interpretation with charts, graphs, dashboards, and much more. Updated with the latest features of Tableau, this book takes you from the foundations of the Tableau 2019 paradigm through to advanced topics. This third edition of the bestselling guide by Tableau Zen Master, Milligan, will help you come to grips with updated features, such as set actions and transparent views. Beginning with installation, you'll create your first visualizations with Tableau and then explore practical examples and advanced techniques. You'll create bar charts, tree maps, scatterplots, time series, and a variety of other visualizations. Next, you'll discover techniques to overcome challenges presented by data structure and quality and engage in effective data storytelling and decision making with business critical information. Finally, you'll be introduced to Tableau Prep, and learn how to use it to integrate and shape data for analysis. By the end of this book, you will be equipped to leverage the powerful features of Tableau 2019 for decision making. What you will learn * Develop stunning visualizations that explain complexity with clarity * Explore the exciting new features of Tableau Desktop and Tableau Prep * Connect to various data sources to bring all your data together * Uncover techniques to prep and structure your data for easy analysis * Create and use calculations to solve problems and enrich analytics * Master advanced topics such as sets, LOD calcs, and much more * Enable smart decisions with clustering, distribution, and forecasting * Share your data stories to build a culture of trust and action Who this book is for This Tableau book is for anyone who wants to understand data. If you’re new to Tableau, don’t worry. This book builds on the foundations to help you understand how Tableau really works and then builds on that knowledge with practical examples before moving on to advanced techniques. Working experience with databases will be useful but is not necessary to get the most out of this book.

Build cost-effective and robust cloud solutions with Google Cloud Platform (GCP) using these simple and practical recipes Key Features * Explore the various service offerings of the GCP * Host a Python application on Google Compute Engine * Securely maintain application states with Cloud Storage, Datastore, and Bigtable Book Description GCP is a cloud computing platform with a wide range of products and services that enable you to build and deploy cloud-hosted applications. This Learning Path will guide you in using GCP and designing, deploying, and managing applications on Google Cloud. You will get started by learning how to use App Engine to access Google's scalable hosting and build software that runs on this framework. With the help of Google Compute Engine, you’ll be able to host your workload on virtual machine instances. The later chapters will help you to explore ways to implement authentication and security, Cloud APIs, and command-line and deployment management. As you hone your skills, you’ll understand how to integrate your new applications with various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage. Following this, the book will teach you how to streamline your workflow with tools, including Source Repositories, Container Builder, and Stackdriver. You'll also understand how to deploy and debug services with IntelliJ, implement continuous delivery pipelines, and configure robust monitoring and alerts for your production systems. By the end of this Learning Path, you'll be well versed with GCP’s development tools and be able to develop, deploy, and manage highly scalable and reliable applications. This Learning Path includes content from the following Packt products: * Google Cloud Platform for Developers Ted Hunter and Steven Porter * Google Cloud Platform Cookbook by Legorie Rajan PS What you will learn * Host an application using Google Cloud Functions * Migrate a MySQL database 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 * Deploy and run services on App Engine and Container Engine * Minimize downtime and mitigate issues with Stackdriver Monitoring and Debugger * Integrate with big data solutions, including BigQuery, Dataflow, and Pub/Sub Who this book is for This Learning Path is for IT professionals, engineers, and developers who want to implement Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this Learning Path useful. Basic understanding of GCP and its services is a must.

Choose the smarter way to learn about containerizing your applications and running them in production. Key Features * Deploy and manage highly scalable, containerized applications with Kubernetes * Build high-availability Kubernetes clusters * Secure your applications via encapsulation, networks, and secrets Book Description Kubernetes is an open source orchestration platform for managing containers in a cluster environment. This Learning Path introduces you to the world of containerization, in addition to providing you with an overview of Docker fundamentals. As you progress, you will be able to understand how Kubernetes works with containers. Starting with creating Kubernetes clusters and running applications with proper authentication and authorization, you'll learn how to create high-availability Kubernetes clusters on Amazon Web Services (AWS), and also learn how to use kubeconfig to manage different clusters. Whether it is learning about Docker containers and Docker Compose, or building a continuous delivery pipeline for your application, this Learning Path will equip you with all the right tools and techniques to get started with containerization. By the end of this Learning Path, you will have gained hands-on experience of working with Docker containers and orchestrators, including SwarmKit and Kubernetes. This Learning Path includes content from the following Packt products: * Kubernetes Cookbook - Second Edition by Hideto Saito, Hui-Chuan Chloe Lee, and Ke-Jou Carol Hsu * Learn Docker - Fundamentals of Docker 18.x by Gabriel N. Schenker What you will learn * Build your own container cluster * Run a highly distributed application with Docker Swarm or Kubernetes * Update or rollback a distributed application with zero downtime * Containerize your traditional or microservice-based application * Build a continuous delivery pipeline for your application * Track metrics and logs for every container in your cluster * Implement container orchestration to streamline deploying and managing applications Who this book is for This beginner-level Learning Path is designed for system administrators, operations engineers, DevOps engineers, and developers who want to get started with Docker and Kubernetes. Although no prior experience with Docker is required, basic knowledge of Kubernetes and containers will be helpful.

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 practical guide to testing your infrastructure security with Kali Linux, the preferred choice of pentesters and hackers Key Features * Employ advanced pentesting techniques with Kali Linux to build highly secured systems * Discover various stealth techniques to remain undetected and defeat modern infrastructures * Explore red teaming techniques to exploit secured environment Book Description This book takes you, as a tester or security practitioner, through the reconnaissance, vulnerability assessment, exploitation, privilege escalation, and post-exploitation activities used by pentesters. To start with, you'll use a laboratory environment to validate tools and techniques, along with an application that supports a collaborative approach for pentesting. You'll then progress to passive reconnaissance with open source intelligence and active reconnaissance of the external and internal infrastructure. You'll also focus on how to select, use, customize, and interpret the results from different vulnerability scanners, followed by examining specific routes to the target, which include bypassing physical security and the exfiltration of data using a variety of techniques. You'll discover concepts such as social engineering, attacking wireless networks, web services, and embedded devices. Once you are confident with these topics, you'll learn the practical aspects of attacking user client systems by backdooring with fileless techniques, followed by focusing on the most vulnerable part of the network – directly attacking the end user. By the end of this book, you'll have explored approaches for carrying out advanced pentesting in tightly secured environments, understood pentesting and hacking techniques employed on embedded peripheral devices. What you will learn * Configure the most effective Kali Linux tools to test infrastructure security * Employ stealth to avoid detection in the infrastructure being tested * Recognize when stealth attacks are being used against your infrastructure * Exploit networks and data systems using wired and wireless networks as well as web services * Identify and download valuable data from target systems * Maintain access to compromised systems * Use social engineering to compromise the weakest part of the network - the end users Who this book is for This third edition of Mastering Kali Linux for Advanced Penetration Testing is for you if you are a security analyst, pentester, ethical hacker, IT professional, or security consultant wanting to maximize the success of your infrastructure testing using some of the advanced features of Kali Linux. Prior exposure of penetration testing and ethical hacking basics will be helpful in making the most out of this book.

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.

Build effective RESTful APIs for enterprise with design patterns and REST framework’s out-of-the-box capabilities Key Features * Understand advanced topics such as API gateways, API securities, and cloud * Implement patterns programmatically with easy-to-follow examples * Modernize legacy codebase using API connectors, layers, and microservices Book Description This book deals with the Representational State Transfer (REST) paradigm, which is an architectural style that allows networked devices to communicate with each other over the internet. With the help of this book, you’ll explore the concepts of service-oriented architecture (SOA), event-driven architecture (EDA), and resource-oriented architecture (ROA). This book covers why there is an insistence for high-quality APIs toward enterprise integration. It also covers how to optimize and explore endpoints for microservices with API gateways and touches upon integrated platforms and Hubs for RESTful APIs. You’ll also understand how application delivery and deployments can be simplified and streamlined in the REST world. The book will help you dig deeper into the distinct contributions of RESTful services for IoT analytics and applications. Besides detailing the API design and development aspects, this book will assist you in designing and developing production-ready, testable, sustainable, and enterprise-grade APIs. By the end of the book, you’ll be empowered with all that you need to create highly flexible APIs for next-generation RESTful services and applications. What you will learn * Explore RESTful concepts, including URI, HATEOAS, and Code on Demand * Study core patterns like Statelessness, Pagination, and Discoverability * Optimize endpoints for linked microservices with API gateways * Delve into API authentication, authorization, and API security implementations * Work with Service Orchestration to craft composite and process-aware services * Expose RESTful protocol-based APIs for cloud computing Who this book is for This book is primarily for web, mobile, and cloud services developers, architects, and consultants who want to build well-designed APIs for creating and sustaining enterprise-class applications. You’ll also benefit from this book if you want to understand the finer details of RESTful APIs and their design techniques along with some tricks and tips.

Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-time Key Features *Make a hands-on start in the fields of Big Data, Distributed Technologies and Machine Learning *Learn how to design, develop and interpret the results of common Machine Learning algorithms *Uncover hidden patterns in your data in order to derive real actionable insights and business value Book Description Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits to fighting disease and serious organized crime. Ultimately, we manage data in order to derive value from it, and many organizations around the world have traditionally invested in technology to help process their data faster and more efficiently. But we now live in an interconnected world driven by mass data creation and consumption where data is no longer rows and columns restricted to a spreadsheet, but an organic and evolving asset in its own right. With this realization comes major challenges for organizations: how do we manage the sheer size of data being created every second (think not only spreadsheets and databases, but also social media posts, images, videos, music, blogs and so on)? And once we can manage all of this data, how do we derive real value from it? The focus of Machine Learning with Apache Spark is to help us answer these questions in a hands-on manner. We introduce the latest scalable technologies to help us manage and process big data. We then introduce advanced analytical algorithms applied to real-world use cases in order to uncover patterns, derive actionable insights, and learn from this big data. What you will learn *Understand how Spark fits in the context of the big data ecosystem *Understand how to deploy and configure a local development environment using Apache Spark *Understand how to design supervised and unsupervised learning models *Build models to perform NLP, deep learning, and cognitive services using Spark ML libraries *Design real-time machine learning pipelines in Apache Spark *Become familiar with advanced techniques for processing a large volume of data by applying machine learning algorithms Who this book is for This book is aimed at Business Analysts, Data Analysts and Data Scientists who wish to make a hands-on start in order to take advantage of modern Big Data technologies combined with Advanced Analytics.

Process large volumes of data in real-time while building high performance and robust data stream processing pipeline using the latest Apache Kafka 2.0 Key Features *Solve practical large data and processing challenges with Kafka *Tackle data processing challenges like late events, windowing, and watermarking *Understand real-time streaming applications processing using Schema registry, Kafka connect, Kafka streams, and KSQL Book Description Apache Kafka is a great open source platform for handling your real-time data pipeline to ensure high-speed filtering and pattern matching on the ?y. In this book, you will learn how to use Apache Kafka for efficient processing of distributed applications and will get familiar with solving everyday problems in fast data and processing pipelines. This book focuses on programming rather than the configuration management of Kafka clusters or DevOps. It starts off with the installation and setting up the development environment, before quickly moving on to performing fundamental messaging operations such as validation and enrichment. Here you will learn about message composition with pure Kafka API and Kafka Streams. You will look into the transformation of messages in different formats, such asext, binary, XML, JSON, and AVRO. Next, you will learn how to expose the schemas contained in Kafka with the Schema Registry. You will then learn how to work with all relevant connectors with Kafka Connect. While working with Kafka Streams, you will perform various interesting operations on streams, such as windowing, joins, and aggregations. Finally, through KSQL, you will learn how to retrieve, insert, modify, and delete data streams, and how to manipulate watermarks and windows. What you will learn *How to validate data with Kafka *Add information to existing data ?ows *Generate new information through message composition *Perform data validation and versioning with the Schema Registry *How to perform message Serialization and Deserialization *How to perform message Serialization and Deserialization *Process data streams with Kafka Streams *Understand the duality between tables and streams with KSQL Who this book is for This book is for developers who want to quickly master the practical concepts behind Apache Kafka. The audience need not have come across Apache Kafka previously; however, a familiarity of Java or any JVM language will be helpful in understanding the code in this book.