Automate the deployment of your environment with the power of the Docker toolchain About This Book ? Written and reviewed by expert Docker developers ? The book precisely covers all the essential topics such as building images and managing container swarms required in day to day use for Docker ? The book includes activities on the docker CLI and exercises such as writing Dockerfiles for Python which will allow you to reinforce the concepts covered Who This Book Is For The book is crafted for developers, system architects, junior and mid-level site reliability engineers interested in adapting a docker workflow. They are also required to have a basic knowledge of UNIX concepts such as ssh, ports and logs What You Will Learn ? Understand how to effectively design and build containers for different applications ? Setup an environment for testing, avoiding environment mismatch that is breaking production ? Setup and manage a multi-tier environment ? Run, debug, and experiment with applications in a container In Detail DevOps with Docker outlines the power of containerization and the influence this innovation has on development teams and general operations. We also get to understand what DevOps really is, the principles involved and how the process contributes to product health, by implementing a Docker workflow. We will learn to interpret Dockerfile syntax, build images and setup containers and images. In addition, we will deploy a Docker image to the Docker Hub.Docker is an open source containerization tool, that makes it easier to streamline product delivery. It helps reduce the time taken to get from a whiteboard sketch of the business to a money-back implementation. This fast-paced book is a perfect amalgamation of theory and hands-on exercises. The book will take you through the basics of Docker and DevOps and why and how they integrate. You will then understand what containers are, and how to create and manage them. Next, we will work on the docker-compose file and CLI. Then we will move to set up a network with the docker-compose tool. Gradually you will learn how to scale a delivery pipeline and multiple deployments with Docker. Lastly, you will grasp the concept of orchestration and learn to implement the delivery of containerized applications. Style and approach This is a fast-paced, practical hands-on book aimed at experienced developers and system architects. As you progress you’ll find helpful tips and tricks, as well as useful self-assessment material, exercises and activities to help benchmark your progress and reinforce what you’ve learned. The activities are devised to simulate the real-world conditions in order to equip you with the necessary skills to accelerate software deployment while still retaining security, portability and saving on costs.

Build robust microservice-based applications that are distributed, fault tolerant, and always available About This Book ? Learn to build message-driven services for effective communication ? Design microservices API using Reactive programming design patterns ? Deploy, scale and monitor microservices for consistent high performance Who This Book Is For This book is for JavaScript developers seeking to utilize their Node.js and Typescript skills to build microservices and move away from the monolithic architecture. Prior knowledge of TypeScript and Node.js is assumed. What You Will Learn ? Get acquainted with the fundamentals behind microservices. ? Explore the behavioral changes needed for moving from monolithic to microservices. ? Dive into reactive programming, Typescript and Node.js to learn its fundamentals in microservices ? Understand and design a service gateway and service registry for your microservices. ? Maintain the state of microservice and handle dependencies. ? Perfect your microservice with unit testing and Integration testing ? Develop a microservice, secure it, deploy it, and then scale it In Detail In the last few years or so, microservices have achieved the rock star status and right now are one of the most tangible solutions in enterprises to make quick, effective, and scalable applications. The apparent rise of Typescript and long evolution from ES5 to ES6 has seen lots of big companies move to ES6 stack. If you want to learn how to leverage the power of microservices to build robust architecture using reactive programming and Typescript in Node.js, then this book is for you. Typescript Microservices is an end-to-end guide that shows you the implementation of microservices from scratch; right from starting the project to hardening and securing your services. We will begin with a brief introduction to microservices before learning to break your monolith applications into microservices. From here, you will learn reactive programming patterns and how to build APIs for microservices. The next set of topics will take you through the microservice architecture with TypeScript and communication between services. Further, you will learn to test and deploy your TypeScript microservices using the latest tools and implement continuous integration. Finally, you will learn to secure and harden your microservice. By the end of the book, you will be able to build production-ready, scalable, and maintainable microservices using Node.js and Typescript. Style and approach This book will be a step by step easy to follow guide with focused examples for building microservices with Typescript.

Build maintainable websites with elegant Django design patterns and modern best practices About This Book ? Explore aspects of Django from Models and Views to testing and deployment ? Understand the nuances of web development such as browser attack and data design ? Walk through various asynchronous tools such as Celery and Channels Who This Book Is For This book is for you whether you’re new to Django or just want to learn its best practices. You do not have to be an expert in Django or Python. No prior knowledge of patterns is expected for reading this book but it would be helpful. What You Will Learn ? Make use of common design patterns to help you write better code ? Implement best practices and idioms in this rapidly evolving framework ? Deal with legacy code and debugging ? Use asynchronous tools such as Celery, Channels, and asyncio ? Use patterns while designing API interfaces with the Django REST Framework ? Reduce the maintenance burden with well-tested, cleaner code ? Host, deploy, and secure your Django projects In Detail Building secure and maintainable web applications requires comprehensive knowledge. The second edition of this book not only sheds light on Django, but also encapsulates years of experience in the form of design patterns and best practices. Rather than sticking to GoF design patterns, the book looks at higher-level patterns. Using the latest version of Django and Python, you’ll learn about Channels and asyncio while building a solid conceptual background. The book compares design choices to help you make everyday decisions faster in a rapidly changing environment. You’ll first learn about various architectural patterns, many of which are used to build Django. You’ll start with building a fun superhero project by gathering the requirements, creating mockups, and setting up the project. Through project-guided examples, you’ll explore the Model, View, templates, workflows, and code reusability techniques. In addition to this, you’ll learn practical Python coding techniques in Django that’ll enable you to tackle problems related to complex topics such as legacy coding, data modeling, and code reusability. You’ll discover API design principles and best practices, and understand the need for asynchronous workflows. During this journey, you’ll study popular Python code testing techniques in Django, various web security threats and their countermeasures, and the monitoring and performance of your application. Style and approach This comprehensive project-driven guide will enhance your skill set by taking you through the well-known design patterns and industry-standard best practices in Django web development.

This book contains more than 65 recipes that will equip you with what you need to know to work with Windows 2016 Server. This book will help you learn how to administrate your Windows Server for optimal performance. About This Book ? A focussed guide to help you with the core functionalities of Windows Server 2016 ? Explore tasks that will help you build a datacenter from scratch using Windows Server 2016 ? Step-by-step instructions for common Windows Server administration duties Who This Book Is For This book is for system administrators or IT professionals who want the skills to manage and maintain the core infrastructure of a Windows Server 2016 environment.? Prior experience in Windows Server 2012 R2 environments will be helpful. What You Will Learn ? Become skilled in the navigation of Windows Server 2016, and explore the technologies and options that it provides ? Build the infrastructure required for a successful Windows Server network ? Move away from those open-source web server platforms and start migrating your websites to Server 2016's Internet Information Services today ? Provide a centralized point for users to access applications and data by confguring Remote Desktop Services ? Compose optimal Group Policies In Detail Windows Server 2016 is an operating system designed to run on servers. It supports enterprise-level data storage, communications, management, and applications. This book contains specially selected, detailed help on core, essential administrative tasks of Windows Server 2016. This book starts by helping you to navigate the interface of Windows Server 2016, and quickly shifts gears to implementing roles that are necessarily in any Microsoft-centric datacenter. This book will also help you leverage the web services platform built into Windows Server 2016, available to anyone who runs this latest and greatest Server operating system. Further, you will also learn to compose optimal Group Policies and monitor system performance and IP address management. This book will be a handy quick-reference guide for any Windows Server administrator, providing easy to read, step-by-step instructions for many common administrative tasks that will be part of any Server Administrator’s job description as they administer their Windows Server 2016 powered servers. The material in the book has been selected from the content of Packt's Windows Server 2016 Cookbook by Jordan Krause to provide a specific focus on key Windows Server administration tasks. Style and approach This book contains recipes that have been specially selected to help with the core, essential administrative tasks of Windows Server 2016.

Leverage the power of Matplotlib to visualize and understand your data more effectively About This Book ? Perform effective data visualization with Matplotlib and get actionable insights from your data ? Design attractive graphs, charts, and 2D plots, and deploy them to the web ? Get the most out of Matplotlib in this practical guide with updated code and examples Who This Book Is For This book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If you’re a data scientist or analyst and wish to create attractive visualizations using Python, you’ll find this book useful. Some knowledge of Python programming is all you need to get started. What You Will Learn ? Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots ? Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of Matplotlib ? Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn ? Create interactive plots with real-time updates ? Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Django ? Write data visualization code that is readily expandable on the cloud platform In Detail Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you’ll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you’ll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations. Style and approach Step by step approach to learning the best of Matplotlib 2.1.x

Leverage the power of the Reinforcement Learning techniques to develop self-learning systems using Tensorflow About This Book ? Learn reinforcement learning concepts and their implementation using TensorFlow ? Discover different problem-solving methods for Reinforcement Learning ? Apply reinforcement learning for autonomous driving cars, robobrokers, and more Who This Book Is For If you want to get started with reinforcement learning using TensorFlow in the most practical way, this book will be a useful resource. The book assumes prior knowledge of machine learning and neural network programming concepts, as well as some understanding of the TensorFlow framework. No previous experience with Reinforcement Learning is required. What You Will Learn ? Implement state-of-the-art Reinforcement Learning algorithms from the basics ? Discover various techniques of Reinforcement Learning such as MDP, Q Learning and more ? Learn the applications of Reinforcement Learning in advertisement, image processing, and NLP ? Teach a Reinforcement Learning model to play a game using TensorFlow and the OpenAI gym ? Understand how Reinforcement Learning Applications are used in robotics In Detail Reinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effective method to train your learning agents and solve a variety of problems in Artificial Intelligence—from games, self-driving cars and robots to enterprise applications that range from datacenter energy saving (cooling data centers) to smart warehousing solutions. The book covers the major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. The book also introduces readers to the concept of Reinforcement Learning, its advantages and why it’s gaining so much popularity. The book also discusses on MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP. By the end of this book, you will have a firm understanding of what reinforcement learning is and how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym. Style and approach An Easy-to-follow, step-by-step guide to help you get to grips with real-world applications of Reinforcement Learning with TensorFlow.

Learn how to build efficient, secure and robust code in C++ by using data structures and algorithms - the building blocks of C++ About This Book ? Use data structures such as arrays, stacks, trees, lists, and graphs with real-world examples ? Learn the functional and reactive implementations of the traditional data structures ? Explore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner Who This Book Is For This book is for developers who would like to learn the Data Structures and Algorithms in C++. Basic C++ programming knowledge is expected. What You Will Learn ? Know how to use arrays and lists to get better results in complex scenarios ? Build enhanced applications by using hashtables, dictionaries, and sets ? Implement searching algorithms such as linear search, binary search, jump search, exponential search, and more ? Have a positive impact on the efficiency of applications with tree traversal ? Explore the design used in sorting algorithms like Heap sort, Quick sort, Merge sort and Radix sort ? Implement various common algorithms in string data types ? Find out how to design an algorithm for a specific task using the common algorithm paradigms In Detail C++ is a general-purpose programming language which has evolved over the years and is used to develop software for many different sectors. This book will be your companion as it takes you through implementing classic data structures and algorithms to help you get up and running as a confident C++ programmer. We begin with an introduction to C++ data structures and algorithms while also covering essential language constructs. Next, we will see how to store data using linked lists, arrays, stacks, and queues. Then, we will learn how to implement different sorting algorithms, such as quick sort and heap sort. Along with these, we will dive into searching algorithms such as linear search, binary search and more. Our next mission will be to attain high performance by implementing algorithms to string datatypes and implementing hash structures in algorithm design. We'll also analyze Brute Force algorithms, Greedy algorithms, and more. By the end of the book, you'll know how to build components that are easy to understand, debug, and use in different applications. Style and approach Readers will be taken through an indispensable list of data structures and algorithms so they can confidently begin coding in C++.

Automate data and model pipelines for faster machine learning applications About This Book ? Build automated modules for different machine learning components ? Understand each component of a machine learning pipeline in depth ? Learn to use different open source AutoML and feature engineering platforms Who This Book Is For If you’re a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book is ideal for you. You’ll also find this book useful if you’re an ML engineer or data professional interested in developing quick machine learning pipelines for your projects. Prior exposure to Python programming will help you get the best out of this book. What You Will Learn ? Understand the fundamentals of Automated Machine Learning systems ? Explore auto-sklearn and MLBox for AutoML tasks ? Automate your preprocessing methods along with feature transformation ? Enhance feature selection and generation using the Python stack ? Assemble individual components of ML into a complete AutoML framework ? Demystify hyperparameter tuning to optimize your ML models ? Dive into Machine Learning concepts such as neural networks and autoencoders ? Understand the information costs and trade-offs associated with AutoML In Detail AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible. In this book, you’ll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning. By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you’ll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions. Style and approach Step by step approach to understand how to automate your machine learning tasks

A developer's field-guide to designing scalable services using Kubernetes About This Book ? Develop and run your software using containers within a Kubernetes environment ? Get hands-on experience of using Kubernetes with DevOps concepts such as continuous integration, benchmark testing, monitoring, and so on ? Pragmatic example-based approach showing how to use Kubernetes in the development process Who This Book Is For If you are a full-stack or back-end software developers interested, curious, or being asked to test as well as run the code you're creating, you can leverage Kubernetes to make that process simpler and consistent regardless of where you deploy. If you're looking for developer focused examples in NodeJS and Python for how to build, test, deploy, and run your code with Kubernetes, this is perfect for you. What You Will Learn ? Build your software into containers ? Deploy and debug software running in containers within Kubernetes ? Declare and add configuration through Kubernetes ? Define how your application fits together, using internal and external services ? Add feedback to your code to help Kubernetes manage your services ? Monitor and measure your services through integration testing and in production deployments In Detail Kubernetes is documented and typically approached from the perspective of someone running software that has already been built. Kubernetes may also be used to enhance the development process, enabling more consistent testing and analysis of code to help developers verify not only its correctness, but also its efficiency. This book introduces key Kubernetes concepts, coupled with examples of how to deploy and use them with a bit of Node.js and Python example code, so that you can quickly replicate and use that knowledge. You will begin by setting up Kubernetes to help you develop and package your code. We walk you through the setup and installation process before working with Kubernetes in the development environment. We then delve into concepts such as automating your build process, autonomic computing, debugging, and integration testing. This book covers all the concepts required for a developer to work with Kubernetes. By the end of this book, you will be in a position to use Kubernetes in development ecosystems. Style and approach This book will cover examples using NodeJS and Python that walk you through building containers, defining your deployments, deploying, debugging, testing, and generally interacting with your code running on Kubernetes. The examples are focused on common development needs, and include pragmatic advice and the explanations behind that advice.

Master the art of identifying vulnerabilities within the Windows OS and develop the desired solutions for it using Kali Linux. Key Features *Identify the vulnerabilities in your system using Kali Linux 2018.02 *Discover the art of exploiting Windows kernel drivers *Get to know several bypassing techniques to gain control of your Windows environment Book Description Windows has always been the go-to platform for users around the globe to perform administration and ad hoc tasks, in settings that range from small offices to global enterprises, and this massive footprint makes securing Windows a unique challenge. This book will enable you to distinguish yourself to your clients. In this book, you'll learn advanced techniques to attack Windows environments from the indispensable toolkit that is Kali Linux. We'll work through core network hacking concepts and advanced Windows exploitation techniques, such as stack and heap overflows, precision heap spraying, and kernel exploitation, using coding principles that allow you to leverage powerful Python scripts and shellcode. We'll wrap up with post-exploitation strategies that enable you to go deeper and keep your access. Finally, we'll introduce kernel hacking fundamentals and fuzzing testing, so you can discover vulnerabilities and write custom exploits. By the end of this book, you'll be well-versed in identifying vulnerabilities within the Windows OS and developing the desired solutions for them. What you will learn *Get to know advanced pen testing techniques with Kali Linux *Gain an understanding of Kali Linux tools and methods from behind the scenes *See how to use Kali Linux at an advanced level *Understand the exploitation of Windows kernel drivers *Understand advanced Windows concepts and protections, and how to bypass them using Kali Linux *Discover Windows exploitation techniques, such as stack and heap overflows and kernel exploitation, through coding principles Who this book is for This book is for penetration testers, ethical hackers, and individuals breaking into the pentesting role after demonstrating an advanced skill in boot camps. Prior experience with Windows exploitation, Kali Linux, and some Windows debugging tools is necessary

Explore C# and the .NET Core framework to create applications and optimize them with ASP.NET Core 2 Key Features *Get to grips with multi-threaded, concurrent, and asynchronous programming in C# and .NET Core *Develop modern, cross-platform applications with .NET Core 2.0 and C# 7.0 *Create efficient web applications with ASP.NET Core 2. Book Description C# is a widely used programming language, thanks to its easy learning curve, versatility, and support for modern paradigms. The language is used to create desktop apps, background services, web apps, and mobile apps. .NET Core is open source and compatible with Mac OS and Linux. There is no limit to what you can achieve with C# and .NET Core. This Learning Path begins with the basics of C# and object-oriented programming (OOP) and explores features of C#, such as tuples, pattern matching, and out variables. You will understand.NET Standard 2.0 class libraries and ASP.NET Core 2.0, and create professional websites, services, and applications. You will become familiar with mobile app development using Xamarin.Forms and learn to develop high-performing applications by writing optimized code with various profiling techniques. By the end of C# 7 and .NET: Designing Modern Cross-platform Applications, you will have all the knowledge required to build modern, cross-platform apps using C# and .NET. This Learning Path includes content from the following Packt products: *C# 7.1 and .NET Core 2.0 - Modern Cross-Platform Development - Third Edition by Mark J. Price *C# 7 and .NET Core 2.0 High Performance by Ovais Mehboob Ahmed Khan What you will learn *Explore ASP.NET Core to create professional web applications *Master OOP with C# to increase code reusability and efficiency *Protect your data using encryption and hashing *Measure application performance using BenchmarkDotNet *Use design techniques to increase your application’s performance *Learn memory management techniques in .NET Core *Understand tools and techniques to monitor application performance Who this book is for This Learning Path is designed for developers who want to gain a solid foundation in C# and .NET Core, and want to build cross-platform applications. To gain maximum benefit from this Learning Path, you must have basic knowledge of C#.

An effective guide to becoming an AWS Certified SysOps Administrator Key Features * Not only pass the certification with confidence but also enhance your skills to solving real-world scenarios. * A practical guide to getting you hands-on experience with application management, deployment, operation. * Enhance your AWS skills with practice questions and mock tests. Book Description AWS certifications are becoming one of the must have certifications for any IT professional working on an AWS Cloud platform. This book will act as your one stop preparation guide to validate your technical expertise in deployment, management, and operations on the AWS platform. Along with exam specific content this book will also deep dive into real world scenarios and hands-on instructions. This book will revolve around concepts like teaching you to deploy, manage, and operate scalable, highly available, and fault tolerant systems on AWS. You will also learn to migrate an existing on-premises application to AWS. You get hands-on experience in selecting the appropriate AWS service based on compute, data, or security requirements. This book will also get you well versed with estimating AWS usage costs and identifying operational cost control mechanisms. By the end of this book, you will be all prepared to implement and manage resources efficiently on the AWS cloud along with confidently passing the AWS Certified SysOps Administrator – Associate exam. What you will learn * Create and manage users, groups, and permissions using AWS IAM services * Create a secure VPC with public and private subnets, Network Access Control, and security groups * Get started with launching your first EC2 instance, and working with it * Handle application traffic with ELB and monitor AWS resources with CloudWatch * Work with S3, Glacier, and CloudFront * Work across distributed application components using SWF * Understand event-based processing with Lambda and messaging SQS and SNS in AWS * Get familiar with AWS deployment concepts and tools including Elastic Beanstalk, CloudFormation and AWS OpsWorks Who this book is for If you are a system administrator or a system engineer interested in leveraging the AWS platform to deploy applications then, this book is for you. IT professionals interested in passing the AWS Certified Sysops Administrator will also benefit from this book. Some basic understanding of working AWS components would do wonders.

Get to grips with the unified, highly scalable distributed storage system and learn how to design and implement it. Key Features * Explore Ceph's architecture in detail * Implement a Ceph cluster successfully and gain deep insights into its best practices * Leverage the advanced features of Ceph, including erasure coding, tiering, and BlueStore Book Description This Learning Path takes you through the basics of Ceph all the way to gaining in-depth understanding of its advanced features. You’ll gather skills to plan, deploy, and manage your Ceph cluster. After an introduction to the Ceph architecture and its core projects, you’ll be able to set up a Ceph cluster and learn how to monitor its health, improve its performance, and troubleshoot any issues. By following the step-by-step approach of this Learning Path, you’ll learn how Ceph integrates with OpenStack, Glance, Manila, Swift, and Cinder. With knowledge of federated architecture and CephFS, you’ll use Calamari and VSM to monitor the Ceph environment. In the upcoming chapters, you’ll study the key areas of Ceph, including BlueStore, erasure coding, and cache tiering. More specifically, you’ll discover what they can do for your storage system. In the concluding chapters, you will develop applications that use Librados and distributed computations with shared object classes, and see how Ceph and its supporting infrastructure can be optimized. By the end of this Learning Path, you'll have the practical knowledge of operating Ceph in a production environment. This Learning Path includes content from the following Packt products: * Ceph Cookbook by Michael Hackett, Vikhyat Umrao and Karan Singh * Mastering Ceph by Nick Fisk * Learning Ceph, Second Edition by Anthony D'Atri, Vaibhav Bhembre and Karan Singh What you will learn * Understand the benefits of using Ceph as a storage solution * Combine Ceph with OpenStack, Cinder, Glance, and Nova components * Set up a test cluster with Ansible and virtual machine with VirtualBox * Develop solutions with Librados and shared object classes * Configure BlueStore and see its interaction with other configurations * Tune, monitor, and recover storage systems effectively * Build an erasure-coded pool by selecting intelligent parameters Who this book is for If you are a developer, system administrator, storage professional, or cloud engineer who wants to understand how to deploy a Ceph cluster, this Learning Path is ideal for you. It will help you discover ways in which Ceph features can solve your data storage problems. Basic knowledge of storage systems and GNU/Linux will be beneficial.

Leverage the power of Kubernetes to build an efficient software delivery pipeline. Key Features * Learn about DevOps, containers, and Kubernetes all within one handy book * A practical guide to container management and orchestration * Learn how to monitor, log, and troubleshoot your Kubernetes applications Book Description Kubernetes has been widely adopted across public clouds and on-premise data centers. As we're living in an era of microservices, knowing how to use and manage Kubernetes is an essential skill for everyone in the IT industry. This book is a guide to everything you need to know about Kubernetes—from simply deploying a container to administrating Kubernetes clusters wisely. You'll learn about DevOps fundamentals, as well as deploying a monolithic application as microservices and using Kubernetes to orchestrate them. You will then gain an insight into the Kubernetes network, extensions, authentication and authorization. With the DevOps spirit in mind, you'll learn how to allocate resources to your application and prepare to scale them efficiently. Knowing the status and activity of the application and clusters is crucial, so we’ll learn about monitoring and logging in Kubernetes. Having an improved ability to observe your services means that you will be able to build a continuous delivery pipeline with confidence. At the end of the book, you'll learn how to run managed Kubernetes services on three top cloud providers: Google Cloud Platform, Amazon Web Services, and Microsoft Azure. What you will learn * Learn fundamental and advanced DevOps skills and tools * Get a comprehensive understanding of containers * Dockerize an application * Administrate and manage Kubernetes cluster * Extend the cluster functionality with custom resources * Understand Kubernetes network and service mesh * Implement Kubernetes logging and monitoring * Manage Kubernetes services in Amazon Web Services, Google Cloud Platform,and Microsoft Azure Who this book is for This book is for anyone who wants to learn containerization and clustering in a practical way using Kubernetes. No prerequisite skills are required, however, essential DevOps skill and public/private Cloud knowledge will accelerate the reading speed. If you're advanced, you can get a deeper understanding of all the tools and technique described in the book.

From learning about the most sought-after design patterns to a comprehensive coverage of architectural patterns and code testing, this book is all you need to write clean, reusable code Key Features *Write clean, reusable and maintainable code, and make the most of the latest Swift version. *Analyze case studies of some of the popular open source projects and give your workflow a huge boost *Choose patterns such as MVP, MVC, and MVVM depending on the application being built Book Description Swift keeps gaining traction not only amongst Apple developers but also as a server-side language. This book demonstrates how to apply design patterns and best practices in real-life situations, whether that's for new or already existing projects. You’ll begin with a quick refresher on Swift, the compiler, the standard library, and the foundation, followed by the Cocoa design patterns – the ones at the core of many cocoa libraries – to follow up with the creational, structural, and behavioral patterns as defined by the GoF. You'll get acquainted with application architecture, as well as the most popular architectural design patterns, such as MVC and MVVM, and learn to use them in the context of Swift. In addition, you’ll walk through dependency injection and functional reactive programming. Special emphasis will be given to techniques to handle concurrency, including callbacks, futures and promises, and reactive programming. These techniques will help you adopt a test-driven approach to your workflow in order to use Swift Package Manager and integrate the framework into the original code base, along with Unit and UI testing. By the end of the book, you'll be able to build applications that are scalable, faster, and easier to maintain. What you will learn *Work efficiently with Foundation and Swift Standard library *Understand the most critical GoF patterns and use them efficiently *Use Swift 4.2 and its unique capabilities (and limitations) to implement and improve GoF patterns *Improve your application architecture and optimize for maintainability and performance *Write efficient and clean concurrent programs using futures and promises, or reactive programming techniques *Use Swift Package Manager to refactor your program into reusable components *Leverage testing and other techniques for writing robust code Who this book is for This book is for intermediate developers who want to apply design patterns with Swift to structure and scale their applications. You are expected to have basic knowledge of iOS and Swift.

Understand, explore, and effectively present data using the powerful data visualization techniques of Python Key Features *Use the power of Pandas and Matplotlib to easily solve data mining issues *Understand the basics of statistics to build powerful predictive data models *Grasp data mining concepts with helpful use-cases and examples Book Description Data mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining. You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models. By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional. This Learning Path includes content from the following Packt products: *Statistics for Machine Learning by Pratap Dangeti *Matplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin Yim *Pandas Cookbook by Theodore Petrou What you will learn *Understand the statistical fundamentals to build data models *Split data into independent groups *Apply aggregations and transformations to each group *Create impressive data visualizations *Prepare your data and design models *Clean up data to ease data analysis and visualization *Create insightful visualizations with Matplotlib and Seaborn *Customize the model to suit your own predictive goals Who this book is for If you want to learn how to use the many libraries of Python to extract impactful information from your data and present it as engaging visuals, then this is the ideal Learning Path for you. Some basic knowledge of Python is enough to get started with this Learning Path.

Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key Features * Build independent machine learning (ML) systems leveraging the best features of R 3.5 * Understand and apply different machine learning techniques using real-world examples * Use methods such as multi-class classification, regression, and clustering Book Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you’ll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you’ll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learn * Prepare data for machine learning methods with ease * Understand how to write production-ready code and package it for use * Produce simple and effective data visualizations for improved insights * Master advanced methods, such as Boosted Trees and deep neural networks * Use natural language processing to extract insights in relation to text * Implement tree-based classifiers, including Random Forest and Boosted Tree Who this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement advanced machine learning algorithms. The book will help you take your skills to the next level and advance further in this field. Working knowledge of machine learning with R is mandatory.

Build, secure, and deploy real-world serverless applications in AWS and peek into the serverless cloud offerings from Azure, Google Cloud, and IBM Cloud Key Features * Build serverless applications with AWS Lambda, AWS CloudFormation and AWS CloudWatch * Perform data analytics and natural language processing(NLP)on the AWS serverless platform * Explore various design patterns and best practices involved in serverless computing Book Description Managing physical servers will be a thing of the past once you’re able to harness the power of serverless computing. If you’re already prepped with the basics of serverless computing, Serverless Programming Cookbook will help you take the next step ahead. This recipe-based guide provides solutions to problems you might face while building serverless applications. You'll begin by setting up Amazon Web Services (AWS), the primary cloud provider used for most recipes. The next set of recipes will cover various components to build a Serverless application including REST APIs, database, user management, authentication, web hosting, domain registration, DNS management, CDN, messaging, notifications and monitoring. The book also introduces you to the latest technology trends such as Data Streams, Machine Learning and NLP. You will also see patterns and practices for using various services in a real world application. Finally, to broaden your understanding of Serverless computing, you'll also cover getting started guides for other cloud providers such as Azure, Google Cloud Platform and IBM cloud. By the end of this book, you’ll have acquired the skills you need to build serverless applications efficiently using various cloud offerings. What you will learn * Serverless computing in AWS and explore services with other clouds * Develop full-stack apps with API Gateway, Cognito, Lambda and DynamoDB * Web hosting with S3, CloudFront, Route 53 and AWS Certificate Manager * SQS and SNS for effective communication between microservices * Monitoring and troubleshooting with CloudWatch logs and metrics * Explore Kinesis Streams, Amazon ML models and Alexa Skills Kit Who this book is for For developers looking for practical solutions to common problems while building a serverless application, this book provides helpful recipes. To get started with this intermediate-level book, knowledge of basic programming is a must.

Unearth the power of GraphQL, React, Apollo, Node, and Express to build a scalable, production ready application Key Features * Build full stack applications with modern APIs using GraphQL and Apollo * Integrate Apollo into React and build frontend components using GraphQL * Implement a self-updating notification pop-up with a unique GraphQL feature called Subscriptions Book Description React, one of the most widely used JavaScript frameworks, allows developers to build fast and scalable front end applications for any use case. GraphQL is the modern way of querying an API. It represents an alternative to REST and is the next evolution in web development. Combining these two revolutionary technologies will give you a future-proof and scalable stack you can start building your business around. This book will guide you in implementing applications by using React, Apollo, Node.js and SQL. We'll focus on solving complex problems with GraphQL, such as abstracting multi-table database architectures and handling image uploads. Our client, and server will be powered by Apollo. Finally we will go ahead and build a complete Graphbook. While building the app, we'll cover the tricky parts of connecting React to the back end, and maintaining and synchronizing state. We'll learn all about querying data and authenticating users. We'll write test cases to verify the front end and back end functionality for our application and cover deployment. By the end of the book, you will be proficient in using GraphQL and React for your full-stack development requirements. What you will learn * Resolve data from multi-table database and system architectures * Build a GraphQL API by implementing models and schemas with Apollo and Sequelize * Set up an Apollo Client and build front end components using React * Use Mocha to test your full-stack application * Write complex React components and share data across them * Deploy your application using Docker Who this book is for The book is for web developers who want to enhance their skills and build complete full stack applications using industry standards. Familiarity with JavaScript, React, and GraphQL is expected to get the most from this book.

Create responsive eLearning content, including quizzes, demonstrations, simulations and Virtual Reality projects that fit on any device with Adobe Captivate 2019 Key Features * Build responsive, interactive and highly engaging eLearning content with Adobe Captivate 2019 * Build Virtual Reality eLearning experiences with Adobe Captivate 2019 * Assess your student knowledge with interactive and random quizzes * Seamlessly integrate your eLearning content with any SCORM or xAPI compliant LMS Book Description Adobe Captivate is used to create highly engaging, interactive, and responsive eLearning content. This book takes you through the production of a few pieces of eLearning content, covering all the project types and workflows of Adobe Captivate. First, you will learn how to create a typical interactive Captivate project. This will give you the opportunity to review all Captivate objects and uncover the application's main tools. Then, you will use the built-in capture engine of Captivate to create an interactive software simulation and a Video Demo that can be published as an MP4 video. Then, you will approach the advanced responsive features of Captivate to create a project that can be viewed on any device. And finally, you will immerse your learners in a 360o environment by creating Virtual Reality projects of Adobe Captivate. At the end of the book, you will empower your workflow and projects with the newer and most advanced features of the application, including variables, advanced actions, JavaScript, and using Captivate 2019 with other applications. If you want to produce high quality eLearning content using a wide variety of techniques, implement eLearning in your company, enable eLearning on any device, assess the effectiveness of the learning by using extensive Quizzing features, or are simply interested in eLearning, this book has you covered! What you will learn * Learn how to use the objects in Captivate to build professional eLearning content * Enhance your projects by adding interactivity, animations, and more * Add multimedia elements, such as audio and video, to create engaging learning experiences * Use themes to craft a unique visual experience * Use question slides to create SCORM-compliant quizzes that integrate seamlessly with your LMS * Make your content fit any device with responsive features of Captivate * Create immersive 360° experiences with Virtual Reality projects of Captivate 2019 * Integrate Captivate with other applications (such as PowerPoint and Photoshop) to establish a professional eLearning production workflow * Publish your project in a wide variety of formats including HTML5 and Flash Who this book is for If you are a teacher, instructional designer, eLearning developer, or human resources manager who wants to implement eLearning, then this book is for you. A basic knowledge of your OS is all it takes to create the next generation of responsive eLearning content.

Master a range of machine learning domains with real-world projects using TensorFlow for R, H2O, MXNet, and more Key Features *Master machine learning, deep learning, and predictive modeling concepts in R 3.5 *Build intelligent end-to-end projects for finance, retail, social media, and a variety of domains *Implement smart cognitive models with helpful tips and best practices Book Description R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. This book will help you test your knowledge and skills, guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next, you’ll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You’ll also explore different clustering techniques to segment customers using wholesale data. In addition to this, the book will get you acquainted with credit card fraud detection using autoencoders, and reinforcement learning to make predictions and win on a casino slot machine. By the end of the book, you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations. What you will learn *Explore deep neural networks and various frameworks that can be used in R *Develop a joke recommendation engine to recommend jokes that match users’ tastes *Create powerful ML models with ensembles to predict employee attrition *Build autoencoders for credit card fraud detection *Work with image recognition and convolutional neural networks *Make predictions for casino slot machine using reinforcement learning *Implement NLP techniques for sentiment analysis and customer segmentation Who this book is for If you’re a data analyst, data scientist, or machine learning developer who wants to master machine learning concepts using R by building real-world projects, this is the book for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this book.