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Podcasty
Cloud Foundry for Developers. Deploy, manage, and orchestrate cloud-native applications with ease
Rick Farmer, Rahul Kumar Jain, David Wu
Cloud Foundry is the open source platform to deploy, run, and scale applications. Cloud Foundry is growing rapidly and a leading product that provides PaaS (Platform as a Service) capabilities to enterprise, government, and organizations around the globe. Giants like Dell Technologies, GE, IBM, HP and the US government are using Cloud Foundry innovate faster in a rapidly changing world. Cloud Foundry is a developer’s dream. Enabling them to create modern applications that can leverage the latest thinking, techniques and capabilities of the cloud, including:? DevOps? Application Virtualization? Infrastructure agnosticism ? Orchestrated containers? Automation? Zero downtime upgrades? A/B deployment? Quickly scaling applications out or inThis book takes readers on a journey where they will first learn the Cloud Foundry basics, including how to deploy and scale a simple application in seconds. Readers will build their knowledge of how to create highly scalable and resilient cloud-native applications and microservices running on Cloud Foundry. Readers will learn how to integrate their application with services provided by Cloud Foundry and with those external to Cloud Foundry. Readers will learn how to structure their Cloud Foundry environment with orgs and spaces. After that, we’ll discuss aspects of continuous integration/continuous delivery (CI/CD), monitoring and logging. Readers will also learn how to enable health checks, troubleshoot and debug applications.By the end of this book, readers will have hands-on experience in performing various deployment and scaling tasks. Additionally, they will have an understanding of what it takes to migrate and develop applications for Cloud Foundry.
REST is an architectural style that tackles the challenges of building scalable web services. In today's connected world, APIs have taken a central role on the web. APIs provide the fabric through which systems interact, and REST has become synonymous with APIs. The depth, breadth, and ease of use of ASP.NET Core makes it a breeze for developers to work with for building robust web APIs. This book takes you through the design of RESTful web services and leverages the ASP.NET Core framework to implement these services. This book begins by introducing you to the basics of the philosophy behind REST. You'll go through the steps of designing and implementing an enterprise-grade RESTful web service. This book takes a practical approach, that you can apply to your own circumstances. This book brings forth the power of the latest .NET Core release, working with MVC. Later, you will learn about the use of the framework to explore approaches to tackle resilience, security, and scalability concerns. You will explore the steps to improve the performance of your applications. You'll also learn techniques to deal with security in web APIs and discover how to implement unit and integration test strategies. By the end of the book, you will have a complete understanding of Building a client for RESTful web services, along with some scaling techniques.
Amazon Web Services (AWS) is the most popular and widely-used cloud platform. Administering and deploying application on AWS makes the applications resilient and robust. The main focus of the book is to cover the basic concepts of cloud-based development followed by running solutions in AWS Cloud, which will help the solutions run at scale.This book not only guides you through the trade-offs and ideas behind efficient cloud applications, but is a comprehensive guide to getting the most out of AWS. In the first section, you will begin by looking at the key concepts of AWS, setting up your AWS account, and operating it. This guide also covers cloud service models, which will help you build highly scalable and secure applications on the AWS platform. We will then dive deep into concepts of cloud computing with S3 storage, RDS and EC2. Next, this book will walk you through VPC, building real-time serverless environments, and deploying serverless APIs with microservices. Finally, this book will teach you to monitor your applications, automate your infrastructure, and deploy with CloudFormation.By the end of this book, you will be well-versed with the various services that AWS provides and will be able to leverage AWS infrastructure to accelerate the development process.
OAuth 2.0 Cookbook. Protect your web applications using Spring Security
OAuth 2.0 is a standard protocol for authorization and focuses on client development simplicity while providing specific authorization flows for web applications, desktop applications, mobile phones, and so on. This book also provides useful recipes for solving real-life problems using Spring Security and creating Android applications.The book starts by presenting you how to interact with some public OAuth 2.0 protected APIs such as Facebook, LinkedIn and Google. You will also be able to implement your own OAuth 2.0 provider with Spring Security OAuth2. Next, the book will cover practical scenarios regarding some important OAuth 2.0 profiles such as Dynamic Client Registration, Token Introspection and how to revoke issued access tokens. You will then be introduced to the usage of JWT, OpenID Connect, and how to safely implement native mobile OAuth 2.0 Clients.By the end of this book, you will be able to ensure that both the server and client are protected against common vulnerabilities.
R Web Scraping Quick Start Guide. Techniques and tools to crawl and scrape data from websites
Web scraping is a technique to extract data from websites. It simulates the behavior of a website user to turn the website itself into a web service to retrieve or introduce new data. This book gives you all you need to get started with scraping web pages using R programming.You will learn about the rules of RegEx and Xpath, key components for scraping website data. We will show you web scraping techniques, methodologies, and frameworks. With this book's guidance, you will become comfortable with the tools to write and test RegEx and XPath rules. We will focus on examples of dynamic websites for scraping data and how to implement the techniques learned. You will learn how to collect URLs and then create XPath rules for your first web scraping script using rvest library. From the data you collect, you will be able to calculate the statistics and create R plots to visualize them. Finally, you will discover how to use Selenium drivers with R for more sophisticated scraping. You will create AWS instances and use R to connect a PostgreSQL database hosted on AWS. By the end of the book, you will be sufficiently confident to create end-to-end web scraping systems using R.
This is the go-to book for anyone interested in the steps needed to develop predictive analytics solutions with examples from the world of marketing, healthcare, and retail. We'll get startedwith a brief history of predictive analytics and learn about different roles and functions people play within a predictive analytics project. Then, we will learn about various ways of installing R along with their pros and cons, combined with a step-by-step installation of RStudio,and a description of the best practices for organizing your projects.On completing the installation, we will begin to acquire the skills necessary to input, clean, and prepare your data for modeling. We will learn the six specific steps needed to implement andsuccessfully deploy a predictive model starting from asking the right questions through model development and ending with deploying your predictive model into production. We will learn whycollaboration is important and how agile iterative modeling cycles can increase your chances of developing and deploying the best successful model.We will continue your journey in the cloud by extending your skill set by learning about Databricks and SparkR, which allow you to develop predictive models on vast gigabytes of data.
Go Design Patterns. Best practices in software development and CSP
Go is a multi-paradigm programming language that has built-in facilities to create concurrent applications. Design patterns allow developers to efficiently address common problems faced during developing applications. Go Design Patterns will provide readers with a reference point to software design patterns and CSP concurrency design patterns to help them build applications in a more idiomatic, robust, and convenient way in Go. The book starts with a brief introduction to Go programming essentials and quickly moves on to explain the idea behind the creation of design patterns and how they appeared in the 90’s as a common language between developers to solve common tasks in object-oriented programming languages. You will then learn how to apply the 23 Gang of Four (GoF) design patterns in Go and also learn about CSP concurrency patterns, the killer feature in Go that has helped Google develop software to maintain thousands of servers. With all of this the book will enable you to understand and apply design patterns in an idiomatic way that will produce concise, readable, and maintainable software.
Linux Device Drivers Development. Develop customized drivers for embedded Linux
Linux kernel is a complex, portable, modular and widely used piece of software, running on around 80% of servers and embedded systems in more than half of devices throughout the World. Device drivers play a critical role in how well a Linux system performs. As Linux has turned out to be one of the most popular operating systems used, the interest in developing proprietary device drivers is also increasing steadily. This book will initially help you understand the basics of drivers as well as prepare for the long journey through the Linux Kernel. This book then covers drivers development based on various Linux subsystems such as memory management, PWM, RTC, IIO, IRQ management, and so on. The book also offers a practical approach on direct memory access and network device drivers. By the end of this book, you will be comfortable with the concept of device driver development and will be in a position to write any device driver from scratch using the latest kernel version (v4.13 at the time of writing this book).
AWK is one of the most primitive and powerful utilities which exists in all Unix and Unix-like distributions. It is used as a command-line utility when performing a basic text-processing operation, and as programming language when dealing with complex text-processing and mining tasks. With this book, you will have the required expertise to practice advanced AWK programming in real-life examples. The book starts off with an introduction to AWK essentials. You will then be introduced to regular expressions, AWK variables and constants, arrays and AWK functions and more. The book then delves deeper into more complex tasks, such as printing formatted output in AWK, control flow statements, GNU's implementation of AWK covering the advanced features of GNU AWK, such as network communication, debugging, and inter-process communication in the GAWK programming language which is not easily possible with AWK. By the end of this book, the reader will have worked on the practical implementation of text processing and pattern matching using AWK to perform routine tasks.
Building software requires careful planning and architectural considerations; Golang was developed with a fresh perspective on building next-generation applications on the cloud with distributed and concurrent computing concerns.Hands-On Software Architecture with Golang starts with a brief introduction to architectural elements, Go, and a case study to demonstrate architectural principles. You'll then move on to look at code-level aspects such as modularity, class design, and constructs specific to Golang and implementation of design patterns. As you make your way through the chapters, you'll explore the core objectives of architecture such as effectively managing complexity, scalability, and reliability of software systems. You'll also work through creating distributed systems and their communication before moving on to modeling and scaling of data. In the concluding chapters, you'll learn to deploy architectures and plan the migration of applications from other languages.By the end of this book, you will have gained insight into various design and architectural patterns, which will enable you to create robust, scalable architecture using Golang.
Dreamforce 16 brought forth the latest addition to the Salesforce platform: an AI tool named Einstein. Einstein promises to provide users of all Salesforce applications with a powerful platform to help them gain deep insights into the data they work on. This book will introduce you to Einstein and help you integrate it into your respective business applications based on the Salesforce platform. We start off with an introduction to AI, then move on to look at how AI can make your CRM and apps smarter. Next, we discuss various out-of-the-box components added to sales, service, marketing, and community clouds from Salesforce to add Artificial Intelligence capabilities. Further on, we teach you how to use Heroku, PredictionIO, and the Force platform, along with Einstein, to build smarter apps. The core chapters focus on developer content and introduce PredictionIO and Salesforce Einstein Vision Services. We explore Einstein Predictive Vision Services, along with analytics cloud, the Einstein Data Discovery product, and IOT core concepts. Throughout the book, we also focus on how Einstein can be integrated into CRM and various clouds such as sales, services, marketing, and communities. By the end of the book, you will be able to embrace and leverage the power of Einstein, incorporating its functions to gain more knowledge. Salesforce developers will be introduced to the world of AI, while data scientists will gain insights into Salesforce’s various cloud offerings and how they can use Einstein’s capabilities and enhance applications.
ServiceNow IT Operations Management. Demystifying IT Operations Management
ServiceNow ITOM enables infrastructure and processes to be managed in a highly automated manner. It contains various segments that ensure its applications and enterprise infrastructures are optimized for high performance and helps in creating a lean and agile organization through service?level visibility and automation.This book will be a comprehensive guide that will be based on Geneva release and will help you discover how IT activities can be connected to your business needs, rather than just focusing on internal IT process. It will take a service-centric approach to operations management and consolidate all your resource data into a single system IT record. You will learn about discovery, orchestration, MID server and cloud management, helping you take full advantage of ServiceNow IT Operations Management to improve the quality of service & increasing the service availability.By the end of the book, you will be able to achieve improved service availability, immediate visibility of vital business services and much more, all from the convenience of your single screen.
Troubleshooting OpenVPN. Click here to enter text
OpenVPN, the most widely used open source VPN package, allows you to create a secure network across systems, keeping your private data secure. Connectivity and other issues are a pain to deal with, especially if they are impacting your business. This book will help you resolve the issues faced by OpenVPN users and teach the techniques on how to troubleshoot it like a true expert. This book is a one stop solution for troubleshooting any issue related to OpenVPN. We will start by introducing you to troubleshooting techniques such as Packet Sniffing, Log Parsing, and OpenSSL. You will see how to overcome operating system specific errors. Later on, you will get to know about network and routing errors by exploring the concepts of IPv4 and IPv6 networking issues. You will discover how to overcome these issues to improve the performance of your OpenVPN deployment. By the end of the book, you will know the best practices, tips, and tricks to ensure the smooth running of your OpenVPN.
Keras 2.x Projects explains how to leverage the power of Keras to build and train state-of-the-art deep learning models through a series of practical projects that look at a range of real-world application areas. To begin with, you will quickly set up a deep learning environment by installing the Keras library. Through each of the projects, you will explore and learn the advanced concepts of deep learning and will learn how to compute and run your deep learning models using the advanced offerings of Keras. You will train fully-connected multilayer networks, convolutional neural networks, recurrent neural networks, autoencoders and generative adversarial networks using real-world training datasets. The projects you will undertake are all based on real-world scenarios of all complexity levels, covering topics such as language recognition, stock volatility, energy consumption prediction, faster object classification for self-driving vehicles, and more. By the end of this book, you will be well versed with deep learning and its implementation with Keras. You will have all the knowledge you need to train your own deep learning models to solve different kinds of problems.
Vitor Bianchi Lanzetta, Nataraj Dasgupta, Ricardo Anjoleto Farias
R is the most widely used programming language, and when used in association with data science, this powerful combination will solve the complexities involved with unstructured datasets in the real world. This book covers the entire data science ecosystem for aspiring data scientists, right from zero to a level where you are confident enough to get hands-on with real-world data science problems.The book starts with an introduction to data science and introduces readers to popular R libraries for executing data science routine tasks. This book covers all the important processes in data science such as data gathering, cleaning data, and then uncovering patterns from it. You will explore algorithms such as machine learning algorithms, predictive analytical models, and finally deep learning algorithms. You will learn to run the most powerful visualization packages available in R so as to ensure that you can easily derive insights from your data.Towards the end, you will also learn how to integrate R with Spark and Hadoop and perform large-scale data analytics without much complexity.
When building RESTful services, it is really important to choose the right framework. Node.js, with its asynchronous, event-driven architecture, is exactly the right choice for building RESTful APIs.This third edition of RESTful Web API Design with Node.js 10 will teach you to create scalable and rich RESTful applications based on the Node.js platform. You will be introduced to the latest NPM package handler and understand how to use it to customize your RESTful development process. You will begin by understanding the key principle that makes an HTTP application a RESTful-enabled application. After writing a simple HTTP request handler, you will create and test Node.js modules using automated tests and mock objects; explore using the NoSQL database, MongoDB, to store data; and get to grips with using self-descriptive URLs. You’ll learn to set accurate HTTP status codes along with understanding how to keep your applications backward-compatible. Also, while implementing a full-fledged RESTful service, you will use Swagger to document the API and implement automation tests for a REST-enabled endpoint with Mocha. Lastly, you will explore some authentication techniques to secure your application.
David Millán Escrivá, Prateek Joshi, Vinícius G. Mendonça, Roy Shilkrot
OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation.This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books:•Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millán Escrivá•Learn OpenCV 4 By Building Projects - Second Edition by David Millán Escrivá, Vinícius G. Mendonça, and Prateek Joshi
Jason De Oliveira, Engin Polat, Stephane Belkheraz
The ASP.NET Core 2.0 Framework has been designed to meet all the needs of today’s web developers. It provides better control, support for test-driven development, and cleaner code. Moreover, it’s lightweight and allows you to run apps on Windows, OSX and Linux, making it the most popular web framework with modern day developers.This book takes a unique approach to web development, using real-world examples to guide you through problems with ASP.NET Core 2.0 web applications. It covers Visual Studio 2017- and ASP.NET Core 2.0-specifc changes and provides general MVC development recipes. It explores setting up .NET Core, Visual Studio 2017, Node.js modules, and NuGet. Next, it shows you how to work with Inversion of Control data pattern and caching. We explore everyday ASP.NET Core MVC 2.0 patterns and go beyond it into troubleshooting. Finally, we lead you through migrating, hosting, and deploying your code.By the end of the book, you’ll not only have explored every aspect of ASP.NET Core MVC 2.0, you’ll also have a reference you can keep coming back to whenever you need to get the job done.
Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark.The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark.As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models.By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases.
Modern R Programming Cookbook. Recipes to simplify your statistical applications
R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications.
Enterprise Cloud Security and Governance. Efficiently set data protection and privacy principles
Modern day businesses and enterprises are moving to the Cloud, to improve efficiency and speed, achieve flexibility and cost effectiveness, and for on-demand Cloud services. However, enterprise Cloud security remains a major concern because migrating to the public Cloud requires transferring some control over organizational assets to the Cloud provider. There are chances these assets can be mismanaged and therefore, as a Cloud security professional, you need to be armed with techniques to help businesses minimize the risks and misuse of business data.The book starts with the basics of Cloud security and offers an understanding of various policies, governance, and compliance challenges in Cloud. This helps you build a strong foundation before you dive deep into understanding what it takes to design a secured network infrastructure and a well-architected application using various security services in the Cloud environment.Automating security tasks, such as Server Hardening with Ansible, and other automation services, such as Monit, will monitor other security daemons and take the necessary action in case these security daemons are stopped maliciously. In short, this book has everything you need to secure your Cloud environment with. It is your ticket to obtain industry-adopted best practices for developing a secure, highly available, and fault-tolerant architecture for organizations.
Chef Cookbook. Achieve powerful IT infrastructure management and automation - Third Edition
Chef is a configuration management tool that lets you automate your more cumbersome IT infrastructure processes and control a large network of computers (and virtual machines) from one master server. This book will help you solve everyday problems with your IT infrastructure with Chef. It will start with recipes that show you how to effectively manage your infrastructure and solve problems with users, applications, and automation. You will then come across a new testing framework, InSpec, to test any node in your infrastructure.Further on, you will learn to customize plugins and write cross-platform cookbooks depending on the platform. You will also install packages from a third-party repository and learn how to manage users and applications. Toward the end, you will build high-availability services and explore what Habitat is and how you can implement it.
Rich Collier, Bahaaldine Azarmi
Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data.As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure.By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly.
Around 80% of time in data analysis is spent on cleaning and preparing data for analysis. This is, however, an important task, and is a prerequisite to the rest of the data analysis workflow, including visualization, analysis and reporting. Python and R are considered a popular choice of tool for data analysis, and have packages that can be best used to manipulate different kinds of data, as per your requirements. This book will show you the different data wrangling techniques, and how you can leverage the power of Python and R packages to implement them.You’ll start by understanding the data wrangling process and get a solid foundation to work with different types of data. You’ll work with different data structures and acquire and parse data from various locations. You’ll also see how to reshape the layout of data and manipulate, summarize, and join data sets. Finally, we conclude with a quick primer on accessing and processing data from databases, conducting data exploration, and storing and retrieving data quickly using databases.The book includes practical examples on each of these points using simple and real-world data sets to give you an easier understanding. By the end of the book, you’ll have a thorough understanding of all the data wrangling concepts and how to implement them in the best possible way.