- Table View
- List View
Python Concurrency with asyncio
by Matthew FowlerLearn how to speed up slow Python code with concurrent programming and the cutting-edge asyncio library. Use coroutines and tasks alongside async/await syntax to run code concurrently Build web APIs and make concurrency web requests with aiohttp Run thousands of SQL queries concurrently Create a map-reduce job that can process gigabytes of data concurrently Use threading with asyncio to mix blocking code with asyncio code Python is flexible, versatile, and easy to learn. It can also be very slow compared to lower-level languages. Python Concurrency with asyncio teaches you how to boost Python's performance by applying a variety of concurrency techniques. You'll learn how the complex-but-powerful asyncio library can achieve concurrency with just a single thread and use asyncio's APIs to run multiple web requests and database queries simultaneously. The book covers using asyncio with the entire Python concurrency landscape, including multiprocessing and multithreading. About the technology It&’s easy to overload standard Python and watch your programs slow to a crawl. Th e asyncio library was built to solve these problems by making it easy to divide and schedule tasks. It seamlessly handles multiple operations concurrently, leading to apps that are lightning fast and scalable. About the book Python Concurrency with asyncio introduces asynchronous, parallel, and concurrent programming through hands-on Python examples. Hard-to-grok concurrency topics are broken down into simple flowcharts that make it easy to see how your tasks are running. You&’ll learn how to overcome the limitations of Python using asyncio to speed up slow web servers and microservices. You&’ll even combine asyncio with traditional multiprocessing techniques for huge improvements to performance. What's inside Build web APIs and make concurrency web requests with aiohttp Run thousands of SQL queries concurrently Create a map-reduce job that can process gigabytes of data concurrently Use threading with asyncio to mix blocking code with asyncio code About the reader For intermediate Python programmers. No previous experience of concurrency required. About the author Matthew Fowler has over 15 years of software engineering experience in roles from architect to engineering director. Table of Contents 1 Getting to know asyncio 2 asyncio basics 3 A first asyncio application 4 Concurrent web requests 5 Non-blocking database drivers 6 Handling CPU-bound work 7 Handling blocking work with threads 8 Streams 9 Web applications 10 Microservices 11 Synchronization 12 Asynchronous queues 13 Managing subprocesses 14 Advanced asyncio
Math for Programmers: 3D graphics, machine learning, and simulations with Python
by Paul OrlandIn Math for Programmers you&’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today&’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you&’ll master the key Python libraries used to turn them into real-world software applications.Summary To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today&’s hottest programming fields. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Skip the mathematical jargon: This one-of-a-kind book uses Python to teach the math you need to build games, simulations, 3D graphics, and machine learning algorithms. Discover how algebra and calculus come alive when you see them in code! About the book In Math for Programmers you&’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today&’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you&’ll master the key Python libraries used to turn them into real-world software applications. What's inside Vector geometry for computer graphics Matrices and linear transformations Core concepts from calculus Simulation and optimization Image and audio processing Machine learning algorithms for regression and classification About the reader For programmers with basic skills in algebra. About the author Paul Orland is a programmer, software entrepreneur, and math enthusiast. He is co-founder of Tachyus, a start-up building predictive analytics software for the energy industry. You can find him online at www.paulor.land. Table of Contents 1 Learning math with code PART I - VECTORS AND GRAPHICS 2 Drawing with 2D vectors 3 Ascending to the 3D world 4 Transforming vectors and graphics 5 Computing transformations with matrices 6 Generalizing to higher dimensions 7 Solving systems of linear equations PART 2 - CALCULUS AND PHYSICAL SIMULATION 8 Understanding rates of change 9 Simulating moving objects 10 Working with symbolic expressions 11 Simulating force fields 12 Optimizing a physical system 13 Analyzing sound waves with a Fourier series PART 3 - MACHINE LEARNING APPLICATIONS 14 Fitting functions to data 15 Classifying data with logistic regression 16 Training neural networks
The Well-Grounded Python Developer: How the pros use Python and Flask
by Doug FarrellIf you&’re new to Python, it can be tough to understand when, where, and how to use all its language features. This friendly guide shows you how the Python ecosystem fits together, and grounds you in the skills you need to continue your journey to being a software developer.Summary Inside The Well-Grounded Python Developer you will discover: Building modules of functionality Creating a well-constructed web server application Integrating database access into your Python applications Refactor and decoupling systems to help scale them How to think about the big picture of your application The Well-Grounded Python Developer builds on Python skills you&’ve learned in isolation and shows you how to unify them into a meaningful whole. It helps you understand the dizzying array of libraries and teaches important concepts, like modular construction, APIs, and the design of a basic web server. As you work through this practical guide, you&’ll discover how all the bits of Python link up as you build and modify a typical web server application—the kind of web app that&’s in high demand by modern businesses. About the technology As a new programmer, you&’re happy just to see your code run. A professional developer, on the other hand, needs to create software that runs reliably. It must be fast, maintainable, scalable, secure, well designed and documented, easy for others to update, and quick to ship. This book teaches you the skills you need to go from Python programmer to Python developer. About the book The Well-Grounded Python Developer shows you why Python, the world&’s most popular programming language, is a fantastic tool for professional development. It guides you through the most important skills, like how to name variables, functions, and classes, how to identify and write a good API, and how to use objects. You&’ll also learn how to deal with inevitable failures, how to make software that connects to the internet, core security practices, and many other professional-grade techniques. What's inside Create a web application Connect to a database Design programs to handle big tasks About the reader For experienced beginners who want to learn professional-level skills. About the author Doug Farrell has been a professional developer since 1983, and has worked with Python for over 20 years. Table of Contents 1 Becoming a Pythonista PART 1 - GROUNDWORK 2 That&’s a good name 3 The API: Let&’s talk 4 The object of conversation 5 Exceptional events PART 2 - FIELDWORK 6 Sharing with the internet 7 Doing it with style 8 Do I know you? Authentication 9 What can you do? Authorization 10 Persistence is good: Databases 11 I&’ve got something to say 12 Are we there yet?
Testing Java Microservices: Using Arquillian, Hoverfly, AssertJ, JUnit, Selenium, and Mockito
by Jason Porter Alex Soto Andrew GumbrechtSummaryTesting Java Microservices teaches you to implement unit and integration tests for microservice systems running on the JVM. You'll work with a microservice environment built using Java EE, WildFly Swarm, and Docker. You'll learn how to increase your test coverage and productivity, and gain confidence that your system will work as you expect.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyMicroservice applications present special testing challenges. Even simple services need to handle unpredictable loads, and distributed message-based designs pose unique security and performance concerns. These challenges increase when you throw in asynchronous communication and containers.About the BookTesting Java Microservices teaches you to implement unit and integration tests for microservice systems running on the JVM. You'll work with a microservice environment built using Java EE, WildFly Swarm, and Docker. You'll advance from writing simple unit tests for individual services to more-advanced practices like chaos or integration tests. As you move towards a continuous-delivery pipeline, you'll also master live system testing using technologies like the Arquillian, Wiremock, and Mockito frameworks, along with techniques like contract testing and over-the-wire service virtualization. Master these microservice-specific practices and tools and you'll greatly increase your test coverage and productivity, and gain confidence that your system will work as you expect.What's InsideTest automationIntegration testing microservice systemsTesting container-centric systemsService virtualizationAbout the ReaderWritten for Java developers familiar with Java EE, EE4J, Spring, or Spring Boot.About the AuthorsAlex Soto Bueno and Jason Porter are Arquillian team members. Andy Gumbrecht is an Apache TomEE developer and PMC. They all have extensive enterprise-testing experience.Table of ContentsAn introduction to microservicesApplication under testUnit-testing microservicesComponent-testing microservicesIntegration-testing microservicesContract testsEnd-to-end testingDocker and testingService virtualizationContinuous delivery in microservices
.NET Core in Action
by Dustin MetzgarSummary .NET Core in Action shows .NET developers how to build professional software applications with .NET Core. Learn how to convert existing .NET code to work on multiple platforms or how to start new projects with knowledge of the tools and capabilities of .NET Core. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology .NET Core is an open source framework that lets you write and run .NET applications on Linux and Mac, without giving up on Windows. Built for everything from lightweight web apps to industrial-strength distributed systems, it's perfect for deploying .NET servers to any cloud platform, including AWS and GCP. About the Book .NET Core in Action introduces you to cross-platform development with .NET Core. This hands-on guide concentrates on new Core features as you walk through familiar tasks like testing, logging, data access, and networking. As you go, you'll explore modern architectures like microservices and cloud data storage, along with practical matters like performance profi ling, localization, and signing assemblies. What's Inside Choosing the right tools Testing, profiling, and debugging Interacting with web services Converting existing projects to .NET Core Creating and using NuGet packages About the Reader All examples are in C#. About the Author Dustin Metzgar is a seasoned developer and architect involved in numerous .NET Core projects. Dustin works for Microsoft. Table of Contents Why .NET Core? Building your first .NET Core applications How to build with .NET Core Unit testing with xUnit Working with relational databases Simplify data access with object-relational mappers Creating a microservice Debugging Performance and profiling Building world-ready applications Multiple frameworks and runtimes Preparing for release appendix A - Frameworks and runtimes appendix B - xUnit command-line options appendix C - What's in the .NET Standard Library? appendix D - NuGet cache locations
Rx.NET in Action: With Examples In C#
by Tamir DresherSummaryRx.NET in Action teaches developers how to build event-driven applications using the Reactive Extensions (Rx) library.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyModern applications must react to streams of data such as user and system events, internal messages, and sensor input. Reactive Extensions (Rx) is a .NET library containing more than 600 operators that you can compose together to build reactive client- and server-side applications to handle events asynchronously in a way that maximizes responsiveness, resiliency, and elasticity.About the BookRx.NET in Action teaches developers how to build event-driven applications using the Rx library. Starting with an overview of the design and architecture of Rx-based reactive applications, you'll get hands-on with in-depth code examples to discover firsthand how to exploit the rich query capabilities that Rx provides and the Rx concurrency model that allows you to control both the asynchronicity of your code and the processing of event handlers. You'll also learn about consuming event streams, using schedulers to manage time, and working with Rx operators to filter, transform, and group events.What's InsideIntroduction to Rx in C#Creating and consuming streams of data and eventsBuilding complex queries on event streamsError handling and testing Rx codeAbout the ReaderReaders should understand OOP concepts and be comfortable coding in C#.About the AuthorTamir Dresher is a senior software architect at CodeValue and a prominent member of Israel's Microsoft programming community.Table of ContentsPART 1 - GETTING STARTED WITH REACTIVE EXTENSIONSReactive programmingHello, RxFunctional thinking in C#PART 2 - CORE IDEASCreating observable sequencesCreating observables from .NET asynchronous typesControlling the observer-observable relationshipControlling the observable temperatureWorking with basic query operatorsPartitioning and combining observablesWorking with Rx concurrency and synchronizationError handling and recoveryAPPENDIXESWriting asynchronous code in .NETThe Rx Disposables libraryTesting Rx queries and operators
ActiveMQ in Action
by Dejan Bosanac Bruce Snyder Rob DaviesApplications in enterprises need to communicate, most commonly done by messaging. Apache ActiveMQ is an open-source implementation of the Java Message Service (JMS), which provides messaging in Java applications.ActiveMQ in Action is a thorough, practical guide to implementing message-oriented systems using ActiveMQ and Java. Co-authored by one of the leading ActiveMQ developers, Bruce Snyder, the book starts with the anatomy of a core Java message, then moves quickly through fundamentals including data persistence, authentication and authorization. Later chapters cover advanced features such as configuration and performance tuning, illustrating each concept with a running real-world stock portfolio application.Readers will learn to integrate ActiveMQ with Apache Geronimo and JBoss, and tie into both Java and non-Java technologies including AJAX, .NET, C++, Ruby, and the Spring framework. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
R in Action, Third Edition: Data analysis and graphics with R and Tidyverse
by Robert I. KabacoffR is the most powerful tool you can use for statistical analysis. This definitive guide smooths R&’s steep learning curve with practical solutions and real-world applications for commercial environments.In R in Action, Third Edition you will learn how to: Set up and install R and RStudio Clean, manage, and analyze data with R Use the ggplot2 package for graphs and visualizations Solve data management problems using R functions Fit and interpret regression models Test hypotheses and estimate confidence Simplify complex multivariate data with principal components and exploratory factor analysis Make predictions using time series forecasting Create dynamic reports and stunning visualizations Techniques for debugging programs and creating packages R in Action, Third Edition makes learning R quick and easy. That&’s why thousands of data scientists have chosen this guide to help them master the powerful language. Far from being a dry academic tome, every example you&’ll encounter in this book is relevant to scientific and business developers, and helps you solve common data challenges. R expert Rob Kabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualizations. This revised and expanded third edition contains fresh coverage of the new tidyverse approach to data analysis and R&’s state-of-the-art graphing capabilities with the ggplot2 package. About the technology Used daily by data scientists, researchers, and quants of all types, R is the gold standard for statistical data analysis. This free and open source language includes packages for everything from advanced data visualization to deep learning. Instantly comfortable for mathematically minded users, R easily handles practical problems without forcing you to think like a software engineer. About the book R in Action, Third Edition teaches you how to do statistical analysis and data visualization using R and its popular tidyverse packages. In it, you&’ll investigate real-world data challenges, including forecasting, data mining, and dynamic report writing. This revised third edition adds new coverage for graphing with ggplot2, along with examples for machine learning topics like clustering, classification, and time series analysis. What's inside Clean, manage, and analyze data Use the ggplot2 package for graphs and visualizations Techniques for debugging programs and creating packages A complete learning resource for R and tidyverse About the reader Requires basic math and statistics. No prior experience with R needed. About the author Dr. Robert I Kabacoff is a professor of quantitative analytics at Wesleyan University and a seasoned data scientist with more than 20 years of experience. Table of Contents PART 1 GETTING STARTED 1 Introduction to R 2 Creating a dataset 3 Basic data management 4 Getting started with graphs 5 Advanced data management PART 2 BASIC METHODS 6 Basic graphs 7 Basic statistics PART 3 INTERMEDIATE METHODS 8 Regression 9 Analysis of variance 10 Power analysis 11 Intermediate graphs 12 Resampling statistics and bootstrapping PART 4 ADVANCED METHODS 13 Generalized linear models 14 Principal components and factor analysis 15 Time series 16 Cluster analysis 17 Classification 18 Advanced methods for missing data PART 5 EXPANDING YOUR SKILLS 19 Advanced graphs 20 Advanced programming 21 Creating dynamic reports 22 Creating a package
Real-World Machine Learning
by Henrik Brink Joseph Richards Mark FetherolfSummary Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learning, preparing you to successfully build and deploy powerful ML systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning systems help you find valuable insights and patterns in data, which you'd never recognize with traditional methods. In the real world, ML techniques give you a way to identify trends, forecast behavior, and make fact-based recommendations. It's a hot and growing field, and up-to-speed ML developers are in demand. About the Book Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems. What's Inside Predicting future behavior Performance evaluation and optimization Analyzing sentiment and making recommendations About the Reader No prior machine learning experience assumed. Readers should know Python. About the Authors Henrik Brink, Joseph Richards and Mark Fetherolf are experienced data scientists engaged in the daily practice of machine learning. Table of Contents PART 1: THE MACHINE-LEARNING WORKFLOW What is machine learning? Real-world data Modeling and prediction Model evaluation and optimization Basic feature engineering PART 2: PRACTICAL APPLICATION Example: NYC taxi data Advanced feature engineering Advanced NLP example: movie review sentiment Scaling machine-learning workflows Example: digital display advertising
Xamarin in Action: Creating native cross-platform mobile apps
by Jim BennettSummaryXamarin in Action teaches you to build cross-platform mobile apps using Xamarin and C#. You'll explore all the layers of a Xamarin app, from design to deployment. By the end, you'll be able to build a quality, production-ready Xamarin app on iOS and Android from scratch with a high level of code reuse.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyRewriting the same app for iOS and Android is tedious, error-prone, and expensive. Microsoft's Xamarin drastically reduces dev time by reusing most application code—typically 70% or more. The core of your iOS and Android app is shared; you write platform-specific code only for the UI layer. And because Xamarin uses C#, your apps benefit from everything this modern language and the .NET ecosystem have to offer.About the BookXamarin in Action teaches you to build cross-platform mobile apps using Xamarin and C#. You'll explore all the layers of a Xamarin app, from design to deployment. Xamarin expert Jim Bennett teaches you design practices that maximize code reuse and isolate device-specific code, making it a snap to incorporate the unique features of each OS.What's InsideUnderstanding MVVM to maximize code reuse and testabilityCreating cross-platform model and UI logic layersBuilding device-specific UIsUnit and automated UI testingPreparing apps for publication with user tracking and crash analyticsAbout the ReaderReaders should have some experience with C#. Mobile development experience is helpful, but not assumed.About the AuthorJim Bennett is a Xamarin MYP, Microsoft MVP, and Senior Cloud Developer Advocate at Microsoft, specializing in Xamarin mobile apps. He's a frequent speaker at events all around the world, including Xamarin user groups and Xamarin and Microsoft conferences. He regularly blogs about Xamarin development at https://jimbobbennett.io.Table of ContentsPART 1 - GETTING STARTED WITH XAMARIN Introducing native cross-platform applications with Xamarin Hello MVVM—creating a simple cross-platform app using MVVM MVVM—the model-view–view model design pattern Hello again, MVVM—understanding and enhancing our simple MVVM appWhat are we (a)waiting for? An introduction to multithreading for Xamarin apps PART 2 - BUILDING APPSDesigning MVVM cross-platform apps Building cross-platform models Building cross-platform view models Building simple Android views Building more advanced Android views Building simple iOS views Building more advanced iOS views PART 3 - FROM WORKING CODE TO THE STORERunning mobile apps on physical devices Testing mobile apps using Xamarin UITest Using App Center to build, test, and monitor apps Deploying apps to beta testers and the stores
C# in Depth: Fourth Edition
by Jonathan SkeetEffective techniques and experienced insights to maximize your C# 6 and 7 programming skills Key Features Written by C# legend and top StackOverflow contributor Jon Skeet Unlock the new features of C# 6 and 7 Insights on the future of the C# language Master asynchronous functions, interpolated strings, tuples, and more Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. &”An excellent overview of C# with helpful and realistic examples that make learning the newest features of C# easy.&” —Meredith Godar About The Book C# is the foundation of .NET development. New features added in C# 6 and 7 make it easier to take on big data applications, cloud-centric web development, and cross-platform software using .NET Core. Packed with deep insight from C# guru Jon Skeet, this book takes you deep into concepts and features other C# books ignore. C# in Depth, Fourth Edition is an authoritative and engaging guide that reveals the full potential of the language, including the new features of C# 6 and 7. It combines deep dives into the C# language with practical techniques for enterprise development, web applications, and systems programming. As you absorb the wisdom and techniques in this book, you&’ll write better code, and become an exceptional troubleshooter and problem solver. What You Will Learn Comprehensive guidance on the new features of C# 6 and 7 Important legacies and greatest hits of C# 2–5 Expression-bodied members Extended pass-by-reference functionality Writing asynchronous C# code String interpolation Composition with tuples Decomposition and pattern matching This Book Is Written For For intermediate C# developers. About The Author Jon Skeet is a senior software engineer at Google. He studied mathematics and computer science at Cambridge, is a recognized authority in Java and C#, and maintains the position of top contributor to Stack Overflow. Table of Contents 1. Survival of the sharpest 2. C# 2 3. C# 3: LINQ and everything that comes with it 4. C# 4: Improving interoperability 5. Writing asynchronous code 6. Async implementation 7. C# 5 bonus features 8. Super-sleek properties and expression-bodied members 9. Stringy features 10. A smörgåsbord of features for concise code 11. Composition using tuples 12. Deconstruction and pattern matching 13. Improving efficiency with more pass by reference 14. Concise code in C# 7 15. C# 8 and beyond PART 1 C# IN CONTEXT PART 2 C# 2–5 PART 3 C# 6 PART 4 C# 7 AND BEYOND
Modern Java in Action: Lambdas, streams, functional and reactive programming
by Raoul-Gabriel Urma Alan Mycroft Mario FuscoSummaryManning's bestselling Java 8 book has been revised for Java 9! In Modern Java in Action, you'll build on your existing Java language skills with the newest features and techniques.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyModern applications take advantage of innovative designs, including microservices, reactive architectures, and streaming data. Modern Java features like lambdas, streams, and the long-awaited Java Module System make implementing these designs significantly easier. It's time to upgrade your skills and meet these challenges head on!About the BookModern Java in Action connects new features of the Java language with their practical applications. Using crystal-clear examples and careful attention to detail, this book respects your time. It will help you expand your existing knowledge of core Java as you master modern additions like the Streams API and the Java Module System, explore new approaches to concurrency, and learn how functional concepts can help you write code that's easier to read and maintain. What's insideThoroughly revised edition of Manning's bestselling Java 8 in ActionNew features in Java 8, Java 9, and beyondStreaming data and reactive programmingThe Java Module SystemAbout the ReaderWritten for developers familiar with core Java features.About the AuthorRaoul-Gabriel Urma is CEO of Cambridge Spark. Mario Fusco is a senior software engineer at Red Hat. Alan Mycroft is a University of Cambridge computer science professor; he cofounded the Raspberry Pi Foundation.Table of ContentsPART 1 - FUNDAMENTALS Java 8, 9, 10, and 11: what's happening? Passing code with behavior parameterization Lambda expressions PART 2 - FUNCTIONAL-STYLE DATA PROCESSING WITH STREAMS Introducing streams Working with streams Collecting data with streams Parallel data processing and performance PART 3 - EFFECTIVE PROGRAMMING WITH STREAMS AND LAMBDASCollection API enhancements Refactoring, testing, and debugging Domain-specific languages using lambdasPART 4 - EVERYDAY JAVA Using Optional as a better alternative to null New Date and Time API Default methods The Java Module System PART 5 - ENHANCED JAVA CONCURRENCY Concepts behind CompletableFuture and reactive programming CompletableFuture: composable asynchronous programming Reactive programming PART 6 - FUNCTIONAL PROGRAMMING AND FUTURE JAVA EVOLUTIONThinking functionally Functional programming techniques Blending OOP and FP: Comparing Java and Scala Conclusions and where next for Java
Spring Microservices in Action, Second Edition
by John Carnell Illary Huaylupo SánchezSpring Microservices in Action, Second Edition teaches you to build microservice-based applications using Java and Spring.Summary By dividing large applications into separate self-contained units, Microservices are a great step toward reducing complexity and increasing flexibility. Spring Microservices in Action, Second Edition teaches you how to build microservice-based applications using Java and the Spring platform. This second edition is fully updated for the latest version of Spring, with expanded coverage of API routing with Spring Cloud Gateway, logging with the ELK stack, metrics with Prometheus and Grafana, security with the Hashicorp Vault, and modern deployment practices with Kubernetes and Istio. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Building and deploying microservices can be easy in Spring! Libraries like Spring Boot, Spring Cloud, and Spring Cloud Gateway reduce the boilerplate code in REST-based services. They provide an effective toolbox to get your microservices up and running on both public and private clouds. About the book Spring Microservices in Action, Second Edition teaches you to build microservice-based applications using Java and Spring. You&’ll start by creating basic services, then move to efficient logging and monitoring. Learn to refactor Java applications with Spring&’s intuitive tooling, and master API management with Spring Cloud Gateway. You&’ll even deploy Spring Cloud applications with AWS and Kubernetes. What's inside Microservice design principles and best practices Configuration with Spring Cloud Config and Hashicorp Vault Client-side resiliency with Resilience4j, and Spring Cloud Load Balancer Metrics monitoring with Prometheus and Grafana Distributed tracing with Spring Cloud Sleuth, Zipkin, and ELK Stack About the reader For experienced Java and Spring developers. About the author John Carnell is a senior cloud engineer with 20 years of Java experience. Illary Huaylupo Sánchez is a software engineer with over 13 years of experience. Table of Contents 1 Welcome to the cloud, Spring 2 Exploring the microservices world with Spring Cloud 3 Building microservices with Spring Boot 4 Welcome to Docker 5 Controlling your configuration with the Spring Cloud Configuration Server 6 On service discovery 7 When bad things happen: Resiliency patterns with Spring Cloud and Resilience4j 8 Service routing with Spring Cloud Gateway 9 Securing your microservices 10 Event-driven architecture with Spring Cloud Stream 11 Distributed tracing with Spring Cloud Sleuth and Zipkin 12 Deploying your microservices
Spring Start Here: Learn what you need and learn it well
by Laurentiu SpilcaQuickly master the massive Spring ecosystem with this focused, hands-on guide that teaches you exactly what you need to know.In Spring Start Here, you will learn how to: Build web applications with Spring Manage application objects with Spring context Implement data persistence using data sources and transactions Implement data exchange between applications using REST services Utilize Spring Boot's convention-over-configuration approach Write unit and integration tests for apps implemented with Spring Minimize work when building any kind of app Persisting data in a Spring application using the latest approach Spring Start Here introduces you to Java development with Spring by concentrating on the core concepts you'll use in every application you build. You'll learn how to refactor an existing application to Spring, how to use Spring tools to make SQL database requests and REST calls, and how to secure your projects with Spring Security. There's always more to learn, and this book will make your next steps much easier. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology For Java developers, Spring is the must-learn framework. This incredible development tool powers everything from small business ecommerce applications to enterprise-scale microservices. Mastering Spring is a long journey. Taking your first step is easy! Start here. About the book Spring Start Here teaches Java developers how to build applications using Spring framework. Informative graphics, relevant examples, and author Laurentiu Spilca's clear and lively writing make it easy to pick up the skills you need. You'll discover how to plan, write, and test applications. And by concentrating on the most important features, this no-nonsense book gives you a firm foundation for exploring Spring's rich ecosystem. What's inside Build web applications with Spring Minimize repetition and manual work Persisting data in a Spring application HTTP and REST-based web services Testing your Spring implementations About the reader For readers with beginning to intermediate Java skills. About the author Lauren?iu Spilca is a skilled Java and Spring developer and an experienced technology instructor. Table of Contents PART 1 FUNDAMENTALS 1 Spring in the real world 2 The Spring context: Defining beans 3 The Spring context: Wiring beans 4 The Spring context: Using abstractions 5 The Spring context: Bean scopes and life cycle 6 Using aspects with Spring AOP PART 2 IMPLEMENTATION 7 Understanding Spring Boot and Spring MVC 8 Implementing web apps with Spring Boot and Spring MVC 9 Using the Spring web scopes 10 Implementing REST services 11 Consuming REST endpoints 12 Using data sources in Spring apps 13 Using transactions in Spring apps 14 Implementing data persistence with Spring Data 15 Testing your Spring app
Chaos Engineering: Site reliability through controlled disruption
by Mikolaj PawlikowskiChaos Engineering teaches you to design and execute controlled experiments that uncover hidden problems.Summary Auto engineers test the safety of a car by intentionally crashing it and carefully observing the results. Chaos engineering applies the same principles to software systems. In Chaos Engineering: Site reliability through controlled disruption, you&’ll learn to run your applications and infrastructure through a series of tests that simulate real-life failures. You'll maximize the benefits of chaos engineering by learning to think like a chaos engineer, and how to design the proper experiments to ensure the reliability of your software. With examples that cover a whole spectrum of software, you'll be ready to run an intensive testing regime on anything from a simple WordPress site to a massive distributed system running on Kubernetes. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Can your network survive a devastating failure? Could an accident bring your day-to-day operations to a halt? Chaos engineering simulates infrastructure outages, component crashes, and other calamities to show how systems and staff respond. Testing systems in distress is the best way to ensure their future resilience, which is especially important for complex, large-scale applications with little room for downtime. About the book Chaos Engineering teaches you to design and execute controlled experiments that uncover hidden problems. Learn to inject system-shaking failures that disrupt system calls, networking, APIs, and Kubernetes-based microservices infrastructures. To help you practice, the book includes a downloadable Linux VM image with a suite of preconfigured tools so you can experiment quickly—without risk. What's inside Inject failure into processes, applications, and virtual machines Test software running on Kubernetes Work with both open source and legacy software Simulate database connection latency Test and improve your team&’s failure response About the reader Assumes Linux servers. Basic scripting skills required. About the author Mikolaj Pawlikowski is a recognized authority on chaos engineering. He is the creator of the Kubernetes chaos engineering tool PowerfulSeal, and the networking visibility tool Goldpinger. Table of Contents 1 Into the world of chaos engineering PART 1 - CHAOS ENGINEERING FUNDAMENTALS 2 First cup of chaos and blast radius 3 Observability 4 Database trouble and testing in production PART 2 - CHAOS ENGINEERING IN ACTION 5 Poking Docker 6 Who you gonna call? Syscall-busters! 7 Injecting failure into the JVM 8 Application-level fault injection 9 There's a monkey in my browser! PART 3 - CHAOS ENGINEERING IN KUBERNETES 10 Chaos in Kubernetes 11 Automating Kubernetes experiments 12 Under the hood of Kubernetes 13 Chaos engineering (for) people
The Jamstack Book: Beyond static sites with JavaScript, APIs, and markup
by Raymond Camden Brian RinaldiJamstack = JavaScript, APIs, and Markup. Use established standard technologies to build super-fast static websites without sacrificing rich, dynamic features.In The Jamstack Book, you will learn how to: Use different static site generators to build websites Deploy Jamstack sites with 11ty, Next.js, Hugo, and Jekyll Add dynamic capabilities like form processing and eCommerce Enhance your Jamstack site with serverless capabilities Integrate a CMS with a Jamstack site Jamstack sites use JavaScript, APIs, and Markup to create fast, dynamic pages without the overhead of heavyweight frameworks. The Jamstack Book is your essential guide to this exciting new web architecture. Written by renowned Jamstack experts Raymond Camden and Brian Rinaldi, it&’s filled with real-world projects to develop and hone your skills. You&’ll learn how to lay out and generate a site, set up your own CMS, and add dynamic features like user logins and search functionality. Confusing jargon is demystified. Plus, you&’ll get the chance to try out different static site generators and find the one that works best for you. Pick up this book today, and you&’ll discover how the Jamstack answers your need for speed and simplicity. About the technology JavaScript, APIs, and pre-rendered Markup put the JAM in Jamstack. This modern web architecture delivers the quick load times of static sites along with the dynamic functionality you need for user-friendly interactive features. Built with lightweight standards and tools, Jamstack sites are fast, secure, easy to maintain, and naturally optimized for mobile and SEO. About the book The Jamstack Book teaches effectively by creating a portfolio of sites, ranging from a simple blog to an eCommerce store. Each new project introduces important skills, including cloud deployment, user logins, and search. You&’ll get hands-on experience with tools like 11ty, Next.js, and Netlify. As your skills grow, the examples become more sophisticated, including serverless technology, dynamic forms, and an integrated CMS. What's inside Use different static site generators to build websites Add dynamic capabilities like form processing and eCommerce Enhance your Jamstack site with serverless capabilities Integrate a CMS with a Jamstack site About the reader For web developers and CMS site developers. About the author Raymond Camden is the author of multiple books on web development and has been blogging and presenting for almost twenty years. Brian Rinaldi has been involved in static site and Jamstack development since the early days. Table of Contents 1 Why Jamstack? 2 Building a basic Jamstack site 3 Building a blog 4 Building a documentation site 5 Building an e-commerce site 6 Deployment 7 Adding dynamic elements 8 Working with serverless computing 9 Adding a content management system 10 Migrating to the Jamstack
Haskell in Depth
by Vitaly BragilevskyHaskell in Depth unlocks a new level of skill with this challenging language. Going beyond the basics of syntax and structure, this book opens up critical topics like advanced types, concurrency, and data processing.Summary Turn the corner from &“Haskell student&” to &“Haskell developer.&” Haskell in Depth explores the important language features and programming skills you&’ll need to build production-quality software using Haskell. And along the way, you&’ll pick up some interesting insights into why Haskell looks and works the way it does. Get ready to go deep! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Software for high-precision tasks like financial transactions, defense systems, and scientific research must be absolutely, provably correct. As a purely functional programming language, Haskell enforces a mathematically rigorous approach that can lead to concise, efficient, and bug-free code. To write such code you&’ll need deep understanding. You can get it from this book! About the book Haskell in Depth unlocks a new level of skill with this challenging language. Going beyond the basics of syntax and structure, this book opens up critical topics like advanced types, concurrency, and data processing. You&’ll discover key parts of the Haskell ecosystem and master core design patterns that will transform how you write software. What's inside Building applications, web services, and networking apps Using sophisticated libraries like lens, singletons, and servant Organizing projects with Cabal and Stack Error-handling and testing Pure parallelism for multicore processors About the reader For developers familiar with Haskell basics. About the author Vitaly Bragilevsky has been teaching Haskell and functional programming since 2008. He is a member of the GHC Steering Committee. Table of Contents PART 1 CORE HASKELL 1 Functions and types 2 Type classes 3 Developing an application: Stock quotes PART 2 INTRODUCTION TO APPLICATION DESIGN 4 Haskell development with modules, packages, and projects 5 Monads as practical functionality providers 6 Structuring programs with monad transformers PART 3 QUALITY ASSURANCE 7 Error handling and logging 8 Writing tests 9 Haskell data and code at run time 10 Benchmarking and profiling PART 4 ADVANCED HASKELL 11 Type system advances 12 Metaprogramming in Haskell 13 More about types PART 5 HASKELL TOOLKIT 14 Data-processing pipelines 15 Working with relational databases 16 Concurrency
Data Engineering on Azure
by Vlad RiscutiaBuild a data platform to the industry-leading standards set by Microsoft&’s own infrastructure.Summary In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft&’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the book In Data Engineering on Azure you&’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you&’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the reader For data engineers familiar with cloud computing and DevOps. About the author Vlad Riscutia is a software architect at Microsoft. Table of Contents 1 Introduction PART 1 INFRASTRUCTURE 2 Storage 3 DevOps 4 Orchestration PART 2 WORKLOADS 5 Processing 6 Analytics 7 Machine learning PART 3 GOVERNANCE 8 Metadata 9 Data quality 10 Compliance 11 Distributing data
Experimentation for Engineers: From A/B testing to Bayesian optimization
by David SweetOptimize the performance of your systems with practical experiments used by engineers in the world&’s most competitive industries.In Experimentation for Engineers: From A/B testing to Bayesian optimization you will learn how to: Design, run, and analyze an A/B test Break the "feedback loops" caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization Clearly define business metrics used for decision-making Identify and avoid the common pitfalls of experimentation Experimentation for Engineers: From A/B testing to Bayesian optimization is a toolbox of techniques for evaluating new features and fine-tuning parameters. You&’ll start with a deep dive into methods like A/B testing, and then graduate to advanced techniques used to measure performance in industries such as finance and social media. Learn how to evaluate the changes you make to your system and ensure that your testing doesn&’t undermine revenue or other business metrics. By the time you&’re done, you&’ll be able to seamlessly deploy experiments in production while avoiding common pitfalls. About the technology Does my software really work? Did my changes make things better or worse? Should I trade features for performance? Experimentation is the only way to answer questions like these. This unique book reveals sophisticated experimentation practices developed and proven in the world&’s most competitive industries that will help you enhance machine learning systems, software applications, and quantitative trading solutions. About the book Experimentation for Engineers: From A/B testing to Bayesian optimization delivers a toolbox of processes for optimizing software systems. You&’ll start by learning the limits of A/B testing, and then graduate to advanced experimentation strategies that take advantage of machine learning and probabilistic methods. The skills you&’ll master in this practical guide will help you minimize the costs of experimentation and quickly reveal which approaches and features deliver the best business results. What's inside Design, run, and analyze an A/B test Break the &“feedback loops&” caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization About the reader For ML and software engineers looking to extract the most value from their systems. Examples in Python and NumPy. About the author David Sweet has worked as a quantitative trader at GETCO and a machine learning engineer at Instagram. He teaches in the AI and Data Science master's programs at Yeshiva University. Table of Contents 1 Optimizing systems by experiment 2 A/B testing: Evaluating a modification to your system 3 Multi-armed bandits: Maximizing business metrics while experimenting 4 Response surface methodology: Optimizing continuous parameters 5 Contextual bandits: Making targeted decisions 6 Bayesian optimization: Automating experimental optimization 7 Managing business metrics 8 Practical considerations
Natural Language Processing in Action: Understanding, analyzing, and generating text with Python
by Hannes Hapke Cole Howard Hobson LaneSummaryNatural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyRecent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries—all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before.About the BookNatural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions.What's insideSome sentences in this book were written by NLP! Can you guess which ones?Working with Keras, TensorFlow, gensim, and scikit-learnRule-based and data-based NLPScalable pipelinesAbout the ReaderThis book requires a basic understanding of deep learning and intermediate Python skills.About the AuthorHobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production.Table of ContentsPART 1 - WORDY MACHINESPackets of thought (NLP overview)Build your vocabulary (word tokenization)Math with words (TF-IDF vectors)Finding meaning in word counts (semantic analysis)PART 2 - DEEPER LEARNING (NEURAL NETWORKS)Baby steps with neural networks (perceptrons and backpropagation)Reasoning with word vectors (Word2vec)Getting words in order with convolutional neural networks (CNNs)Loopy (recurrent) neural networks (RNNs)Improving retention with long short-term memory networksSequence-to-sequence models and attentionPART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES)Information extraction (named entity extraction and question answering)Getting chatty (dialog engines)Scaling up (optimization, parallelization, and batch processing)
Zero to AI: A non-technical, hype-free guide to prospering in the AI era
by Gianluco Mauro Nicolo ValigiSummary How can artificial intelligence transform your business? In Zero to AI, you&’ll explore a variety of practical AI applications you can use to improve customer experiences, optimize marketing, help you cut costs, and more. In this engaging guide written for business leaders and technology pros alike, authors and AI experts Nicolò Valigi and Gianluca Mauro use fascinating projects, hands-on activities, and real-world explanations to make it clear how your business can benefit from AI. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology There&’s no doubt that artificial intelligence has made some impressive headlines recently, from besting chess and Go grand masters to producing uncanny deep fakes that blur the lines of reality. But what can AI do for you? If you want to understand how AI will impact your business before you invest your time and money, this book is for you. About the book Zero to AI uses clear examples and jargon-free explanations to show the practical benefits of AI. Each chapter explores a real-world case study demonstrating how companies like Google and Netflix use AI to shape their industries. You begin at the beginning, with a primer on core AI concepts and realistic business outcomes. To help you prepare for the transition, the book breaks down a successful AI implementation, including advice on hiring the right team and making decisions about resources, risks, and costs. What's inside Identifying where AI can help your organization Designing an AI strategy Evaluating project scope and business impact Using AI to boost conversion rates, curate content, and analyze feedback Understanding how modern AI works and what it can/can&’t do About the reader For anyone who wants to gain an understanding of practical artificial intelligence and learn how to design and develop projects with high business impact. About the author Gianluca Mauro and Nicolò Valigi are the cofounders of AI Academy, a company specializing in AI trainings and consulting. Table of Contents: 1. An introduction to artificial intelligence PART 1 - UNDERSTANDING AI 2. Artificial intelligence for core business data 3. AI for sales and marketing 4. AI for media 5. AI for natural language 6. AI for content curation and community building PART 2 - BUILDING AI 7. Ready—finding AI opportunities 8. Set—preparing data, technology, and people 9. Go—AI implementation strategy 10. What lies ahead
Seriously Good Software: Code that works, survives, and wins
by Marco FaellaSummary Serious developers know that code can always be improved. With each iteration, you make optimizations—small and large—that can have a huge impact on your application&’s speed, size, resilience, and maintainability. In Seriously Good Software: Code that Works, Survives, and Wins, author, teacher, and Java expert Marco Faella teaches you techniques for writing better code. You&’ll start with a simple application and follow it through seven careful refactorings, each designed to explore another dimension of quality. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Great code blends the skill of a programmer with the time-tested techniques and best practices embraced by the entire development community. Although each application has its own context and character, some dimensions of quality are always important. This book concentrates on seven pillars of seriously good software: speed, memory usage, reliability, readability, thread safety, generality, and elegance. The Java-based examples demonstrate techniques that apply to any OO language. About the book Seriously Good Software is a handbook for any professional developer serious about improving application quality. It explores fundamental dimensions of code quality by enhancing a simple implementation into a robust, professional-quality application. Questions, exercises, and Java-based examples ensure you&’ll get a firm grasp of the concepts as you go. When you finish the last version of the book&’s central project, you&’ll be able to confidently choose the right optimizations for your code. What's inside Evaluating software qualities Assessing trade-offs and interactions Fulfilling different objectives in a single task Java-based exercises you can apply in any OO language About the reader For developers with basic object-oriented programming skills and intermediate Java skills. About the author Marco Faella teaches advanced programming at a major Italian university. His published work includes peer-reviewed research articles, a Java certification manual, and a video course. Table of Contents *Part 1: Preliminaries * 1 Software qualities and a problem to solve 2 Reference implementation *Part 2: Software Qualities* 3 Need for speed: Time efficiency 4 Precious memory: Space efficiency 5 Self-conscious code: Reliability through monitoring 6 Lie to me: Reliability through testing 7 Coding aloud: Readability 8 Many cooks in the kitchen: Thread safety 9 Please recycle: Reusability
Fast Python: High performance techniques for large datasets
by Tiago AntaoMaster Python techniques and libraries to reduce run times, efficiently handle huge datasets, and optimize execution for complex machine learning applications. Fast Python is a toolbox of techniques for high performance Python including: Writing efficient pure-Python code Optimizing the NumPy and pandas libraries Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing Fast Python is your guide to optimizing every part of your Python-based data analysis process, from the pure Python code you write to managing the resources of modern hardware and GPUs. You'll learn to rewrite inefficient data structures, improve underperforming code with multithreading, and simplify your datasets without sacrificing accuracy. Written for experienced practitioners, this book dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. About the Technology Face it. Slow code will kill a big data project. Fast pure-Python code, optimized libraries, and fully utilized multiprocessor hardware are the price of entry for machine learning and large-scale data analysis. What you need are reliable solutions that respond faster to computing requirements while using less resources, and saving money. About the Book Fast Python is a toolbox of techniques for speeding up Python, with an emphasis on big data applications. Following the clear examples and precisely articulated details, you&’ll learn how to use common libraries like NumPy and pandas in more performant ways and transform data for efficient storage and I/O. More importantly, Fast Python takes a holistic approach to performance, so you&’ll see how to optimize the whole system, from code to architecture. What&’s Inside Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing About the Reader For intermediate Python programmers familiar with the basics of concurrency. About the Author Tiago Antão is one of the co-authors of Biopython, a major bioinformatics package written in Python. Table of Contents: PART 1 - FOUNDATIONAL APPROACHES 1 An urgent need for efficiency in data processing 2 Extracting maximum performance from built-in features 3 Concurrency, parallelism, and asynchronous processing 4 High-performance NumPy PART 2 - HARDWARE 5 Re-implementing critical code with Cython 6 Memory hierarchy, storage, and networking PART 3 - APPLICATIONS AND LIBRARIES FOR MODERN DATA PROCESSING 7 High-performance pandas and Apache Arrow 8 Storing big data PART 4 - ADVANCED TOPICS 9 Data analysis using GPU computing 10 Analyzing big data with Dask
Cloud Native Patterns: Designing change-tolerant software
by Cornelia DavisSummaryCloud Native Patternsis your guide to developing strong applications that thrive in the dynamic, distributed, virtual world of the cloud. This book presents a mental model for cloud-native applications, along with the patterns, practices, and tooling that set them apart.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyCloud platforms promise the holy grail: near-zero downtime, infinite scalability, short feedback cycles, fault-tolerance, and cost control. But how do you get there? By applying cloudnative designs, developers can build resilient, easily adaptable, web-scale distributed applications that handle massive user traffic and data loads. Learn these fundamental patterns and practices, and you'll be ready to thrive in the dynamic, distributed, virtual world of the cloud.About the BookWith 25 years of experience under her belt, Cornelia Davis teaches you the practices and patterns that set cloud-native applications apart. With realistic examples and expert advice for working with apps, data, services, routing, and more, she shows you how to design and build software that functions beautifully on modern cloud platforms. As you read, you will start to appreciate that cloud-native computing is more about the how and why rather than the where. What's insideThe lifecycle of cloud-native appsCloud-scale configuration managementZero downtime upgrades, versioned services, and parallel deploysService discovery and dynamic routingManaging interactions between services, including retries and circuit breakersAbout the ReaderRequires basic software design skills and an ability to read Java or a similar language.About the AuthorCornelia Davis is Vice President of Technology at Pivotal Software. A teacher at heart, she's spent the last 25 years making good software and great software developers.Table of ContentsPART 1 - THE CLOUD-NATIVE CONTEXTYou keep using that word: Defining "cloud-native"Running cloud-native applications in productionThe platform for cloud-native softwarePART 2 - CLOUD-NATIVE PATTERNSEvent-driven microservices: It's not just request/responseApp redundancy: Scale-out and statelessnessApplication configuration: Not just environment variablesThe application lifecycle: Accounting for constant changeAccessing apps: Services, routing, and service discoveryInteraction redundancy: Retries and other control loopsFronting services: Circuit breakers and API gatewaysTroubleshooting: Finding the needle in the haystackCloud-native data: Breaking the data monolith
Data Pipelines with Apache Airflow
by Julian de Ruiter Bas HarenslakData Pipelines with Apache Airflow teaches you how to build and maintain effective data pipelines.Summary A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, keeping every process along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, Data Pipelines with Apache Airflow teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Data pipelines manage the flow of data from initial collection through consolidation, cleaning, analysis, visualization, and more. Apache Airflow provides a single platform you can use to design, implement, monitor, and maintain your pipelines. Its easy-to-use UI, plug-and-play options, and flexible Python scripting make Airflow perfect for any data management task. About the book Data Pipelines with Apache Airflow teaches you how to build and maintain effective data pipelines. You&’ll explore the most common usage patterns, including aggregating multiple data sources, connecting to and from data lakes, and cloud deployment. Part reference and part tutorial, this practical guide covers every aspect of the directed acyclic graphs (DAGs) that power Airflow, and how to customize them for your pipeline&’s needs. What's inside Build, test, and deploy Airflow pipelines as DAGs Automate moving and transforming data Analyze historical datasets using backfilling Develop custom components Set up Airflow in production environments About the reader For DevOps, data engineers, machine learning engineers, and sysadmins with intermediate Python skills. About the author Bas Harenslak and Julian de Ruiter are data engineers with extensive experience using Airflow to develop pipelines for major companies. Bas is also an Airflow committer. Table of Contents PART 1 - GETTING STARTED 1 Meet Apache Airflow 2 Anatomy of an Airflow DAG 3 Scheduling in Airflow 4 Templating tasks using the Airflow context 5 Defining dependencies between tasks PART 2 - BEYOND THE BASICS 6 Triggering workflows 7 Communicating with external systems 8 Building custom components 9 Testing 10 Running tasks in containers PART 3 - AIRFLOW IN PRACTICE 11 Best practices 12 Operating Airflow in production 13 Securing Airflow 14 Project: Finding the fastest way to get around NYC PART 4 - IN THE CLOUDS 15 Airflow in the clouds 16 Airflow on AWS 17 Airflow on Azure 18 Airflow in GCP