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In Amazon Web Services in Action, Third Edition: An in-depth guide to AWS, the Wittig brothers give you a comprehensive, practical introduction to deploying and managing applications on the AWS cloud platform. With a sharp focus on the most important AWS tasks and services, they will save you hours of unproductive time. You will learn hands-on as you complete real-world projects like hosting a WordPress site, setting up a private cloud, and deploying an app on containers. About the reader Written for mid-level developers, DevOps or platform engineers, architects, and system administrators. This revised third edition features new chapters on containerization, along with a variety of AWS innovations. You will also learn how automating your infrastructure with IAC is a game changer for your cloud deployment, delivering a massive boost to efficiency and quality. You will learn how to: Leverage globally distributed data centers to launch virtual machines Enhance performance with caching data in-memory Secure workloads running in the cloud with VPC and IAM Build fault-tolerant web applications with ALB and SQS

In Evolutionary Deep Learning you'll master a toolbox of EC techniques that can be applied to any stage of the deep learning pipeline--from data collection, to hyperparameter tuning, and even optimizing network architecture. Hands-on examples demonstrate genetic algorithms and other EC approaches in action, and apply evolutionary deep learning to network topology, criterion loss and rewards, generative modeling, and reinforcement learning. Google Colab notebooks make it easy to experiment and play around with each exciting example. By the time you've finished reading, you'll be ready to build deep learning models as self-sufficient systems you can efficiently adapt to changing requirements.

Razor Pages lets you build, configure, and deploy amazing dynamic ASP.NET websites with ease. In ASP.NET Core Razor Pages in Action you will learn: Building, configuring, and publishing a data-driven website Creating a complete web application step-by-step Forms for collecting and processing user data Connecting to databases from a Razor Page Protecting areas of a Razor Page from unauthorized access with ASP.NET Identity Using Object Relational Mapping tools to work with data in Razor Pages applications Generating CRUD pages using scaffolding gestures Generating and sending email from your web application ASP.NET Core Razor Pages in Action teaches you to develop dynamic websites using the powerful Razor Pages framework, .NET 6, and ASP.NET. Razor Pages generates HTML on the server, and is the perfect choice for eCommerce sites, intranet services, content management systems, and other apps that require reliability. In this book, you'll use Razor Pages to build a complete application for booking city breaks, learning to iterate amazing new features chapter-by-chapter. about the technology Razor Pages sits on top of .NET 6 as a key part of ASP.NET Core, and has become the recommended tool for any developer building websites with Microsoft technologies. The page-focused framework is great for building dynamic websites that change frequently, and simplifies the process of building complex applications.

About the book Geometry for Programmers reveals important geometry concepts you need to write more efficient code. It is full of practical guidance relevant to your daily work as a developer. There are no unnecessary theories or formal proofs. Instead, you will learn how geometry can help you optimise your code to boost performance, and real reductions in your cloud services bill. You don't need to be a maths expert -- all complex equations are offloaded to the user-friendly SymPy computer algebra system! Hands-on examples show you how to apply geometry in the real world, including changing a 3D scan into a CAD model and turning a parametric function into a set of contours for 3D printing. About the reader For developers writing code, using CAD libraries, game engines, or rendering tools. Everything in this book is easy to understand with just high school math. Examples demonstrated in Python.

Have you ever asked yourself, "How do I do that in Python?" If so, you'll love this practical collection of the most important Python techniques. About the book Python How-To is full of techniques and best practices for writing readable and maintainable Python code, with careful cross-referencing that reveals how the same concept can be used in different contexts. Each chapter stands alone, so you can dip in whenever you need a practical solution to a common Python problem. About the reader For beginning to intermediate Python programmers.

Get ready to code like a pro in Rust! This hands-on guide dives deep into memory management, asynchronous programming, and Rust design patterns and explores essential productivity techniques like testing, tooling, and project management. In Code Like A Pro in Rust you will learn: Essential Rust tooling Core Rust data structures Memory management Design patterns for Rust Testing in Rust Asynchronous programming for Rust Optimized Rust Rust project management Code Like A Pro in Rust is a fast-track guide to building and delivering professional quality software in Rust. You'll upgrade your basic knowledge of Rust with conventions, best practices, and veteran's secrets that are normally only learned through years of experience. Skip the fluff and get right to the heart of this powerful modern language, including Rust's support for asynchronous programming and integrating Rust with codebases written in other languages. about the technology Programmers prize Rust for its safety, performance, and security. However, its strict syntax and tricky memory management can make it challenging to master. This practical guide shows you how to balance Rust's trade offs, lessen its cognitive load, and rapidly bring your productivity to a professional level. about the book Code Like a Pro in Rust shows you how to quickly create and ship Rust programs without wasting time on language quirks, compiler problems, and unexpected complexities. It builds on your existing Rust knowledge with design patterns and shortcuts direct from veteran Rust contributor Brenden Matthews. You'll learn to use important Rust tooling like rust-analyzer, Clippy, and Cargo, as well as best practices for unit testing and code optimization. By the time you're done, you'll be writing high quality code with less maintenance overhead.

Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations. about the book Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks.

Google Anthos in Action comes directly from the Anthos team at Google. This comprehensive book takes a true DevOps mindset, considering Google-tested patterns for how an application is designed, built, deployed, managed, monitored, and scaled. In a cloud-centric world, all deployment is becoming hybrid deployment. Anthos is a modern, Kubernetes-based cloud platform that enables you to run your software in multi cloud, hybrid, or on-premises deployments using the same operations tools and approach. With powerful automation features, it boosts your efficiency along the whole development lifecycle. Google Anthos in Action demystifies Anthos with practical examples of Anthos at work and invaluable insights from the Google team that built it. Developers will love how having a consistent platform across clouds brings a massive performance boost by standardizing the application across deployment targets, as well as how Anthos makes it easy to modernize legacy applications to cloud native infrastructure. Operations pros will appreciate how simple it is to integrate Anthos with CI/CD pipelines, automate security and policy management, and work with enterprise-level Kubernetes. Each concept is fully illustrated with exercises and hands-on examples, so you can see the power of Anthos in action.

Learn the big skills of C programming by creating bite-size projects! Work your way through these 21 fun and interesting tiny challenges to master essential C techniques you'll use in full-size applications. Tiny C Projects builds and hones your C programming skills with interesting and exciting challenges. You'll expand your C programming portfolio by creating useful utility programs, fun games, password generators, directory utilities, and more. Each program you create starts out simple and then deepens as you explore approaches and alternatives you can use to achieve your goals. Once you're done, you'll find it easy to scale up the skills you've learned from tiny projects into real applications.

Learn how to evaluate the changes you make to your system and ensure that your testing does not undermine revenue or other business metrics. Experimentation for Engineers: From A/B testing to Bayesian optimization delivers a toolbox of processes for optimising software systems. From learning the limits of A/B testing to advanced experimentation strategies involving machine learning and probabilistic methods, this practical guide will help you master the skills. It will also help you minimise the costs of experimentation and will quickly reveal which approaches and features deliver the best business results. What's inside Design, run, and analyse 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 optimisation About the reader For ML and software engineers looking to extract the most value from their systems. Examples are found in Python and NumPy.

The art of unit testing is more than just learning the right collection of tools and practices. It's about understanding what makes great tests tick, finding the right strategy for each unique situation, and knowing what to do when the testing process gets messy. This book delivers insights and advice that will transform the way you test your software. The art of unit testing, third edition shows you how to create readable and maintainable tests. It goes well beyond basic test creation into organization-wide test strategies, troubleshooting, working with legacy code, and "merciless" refactoring. You'll love the practical examples and familiar scenarios that make testing come alive as you read. This third edition has been updated with techniques specific to object-oriented, functional, and modular coding styles. The examples use JavaScript.

Kubernetes is an essential tool for anyone deploying and managing cloud-native applications. It lays out a complete introduction to container technologies and containerized applications along with practical tips for efficient deployment and operation. This revised edition of the bestselling Kubernetes in Action contains new coverage of the Kubernetes architecture, including the Kubernetes API, and a deep dive into managing a Kubernetes cluster in production.In Kubernetes in Action, Second Edition, you'll start with an overview of how Docker containers work with Kubernetes and move quickly to building your first cluster. You'll gradually expand your initial application, adding features and deepening your knowledge of Kubernetes architecture and operation. As you navigate this comprehensive guide, you'll also appreciate thorough coverage of high-value topics like monitoring, tuning, and scaling.

Design patterns and architectures for building production quality applications using functional programming, with examples in Haskell and other FP languages. In Functional Design and Architecture you will learn: Designing production applications in statically typed functional languages such as Haskell Controlling code complexity with functional interfaces Architectures, subsystems, and services for functional languages Developing concurrent frameworks and multithreaded applications Domain-driven design using free monads and other functional tools Property-based, integrational, functional, unit, and automatic whitebox testing Functional Design and Architecture is a pioneering guide to software engineering using Haskell and other functional languages. In it, you'll discover Functional Declarative Design and other design principles perfect for working in Haskell, PureScript, F#, and Scala. about the technology Functional programming offers a powerful alternative to object-oriented programming that helps tackle the complexities of large-scale software. Entrenched design patterns and architectural principles made for OOP are poorly suited for creating large-scale functional applications. This book lays out new methodologies, principles, and architectures optimized for high-level software design using functional languages. about the book Functional Design and Architecture is a comprehensive guide to software engineering using functional programming. Inside, you'll find cutting-edge functional design principles and practices for every stage of application development, from architecting your application through to running simple and maintainable tests. There's no abstract theory--you'll learn by building exciting sample applications, including an application for controlling a spaceship and a full-fledged backend framework. You'll explore functional design by looking at object-oriented principles you might already know, and learn how they can be reapplied to a functional environment. By the time you're done, you'll be ready to apply the brilliant innovations of the functional world to serious software projects.

Take the fast track in your journey to continuous delivery, with open source tools for Kubernetes and cloud applications. This book explores the tools and techniques you'll need to overcome common cloud native challenges. In Continuous Delivery for Kubernetes you will learn how to: Select the right open source project to solve challenges with your Kubernetes application Package, version, distribute and instant cloud native services using Helm Create and run pipelines using Tekton Plan and implement a multicloud strategy with Crossplane Implement risk-free and progressive upgrades with Knative Utilize Knative for serving, routing, and event-driven applications Automate testing, even when you don't have all your services up and running Troubleshoot and measure application performance Continuous Delivery for Kubernetes lays out a toolbox of free, open source projects you can use to implement continuous delivery for Kubernetes-based applications in the cloud. Each chapter covers a different project, clearly demonstrating how it simplifies essential CD tasks like packaging, building pipelines, and multi-cloud deployment. This book shows developers and architects confidently identify common patterns in successful open source tools so they can pick the right options for their own platforms. about the technology Continuous delivery practices help your team quickly introduce, iterate on, and deploy new features so you can get software into production quickly. The tools in this book help facilitate continuous delivery practices by solving the technical and architectural challenges commonly found when adopting Kubernetes, automating essential dev and deployment tasks, and improving your team's collaboration.

Build and use systems that safely automate software delivery from testing through release with this jargon-busting guide to Continuous Delivery pipelines.In Grokking Continuous Delivery you will learn how to:Design effective CD pipelines for new and legacy projectsKeep your software projects release-readyMaintain effective testsScale CD across multiple applicationsEnsure pipelines give the right signals at the right timeUse version control as the source of truthSafely automate deployments with metricsDescribe CD in a way that makes sense to your colleaguesGrokking Continuous Delivery teaches you the design and purpose of continuous delivery systems that you can use with any language or stack. You'll learn directly from your mentor Christie Wilson, Google engineer and co-creator of the Tekton CI/CD framework. Using crystal-clear, well-illustrated examples, Christie lays out the practical nuts and bolts of continuous delivery for developers and pipeline designers.

Practice makes perfect pandas. Work out your pandas skills against dozens of real-world challenges, each carefully designed to build an intuitive knowledge of essential pandas tasks. In Pandas Workout you'll learn how to: Clean your data for accurate analysis Work with rows and columns for retrieving and assigning data Handle indexes, including hierarchical indexes Read and write data with a number of common formats, such as CSV and JSON Process and manipulate textual data from within pandas Work with dates and times in pandas Perform aggregate calculations on selected subsets of data Produce attractive and useful visualizations that make your data come alive Discover 50 exercises that will strengthen your pandas skills to a level of automatic fluency. You'll test yourself against common pandas challenges such as data cleaning, and explore real-world datasets such as New York Taxis, Kickstarter projects, and global tourist spending. Detailed explanations help guide your success and make your new skills stick. You'll even get a big boost to productivity, with tasks that used to mean a trip to StackOverflow now a natural part of your skillset. about the technology Mastering pandas means working out your new skills until they become like reflexes. This book gives you lots of pandas practice by working through the kind of scenarios you'll face in the real world. Whether you're a data scientist or a programmer handling large quantities of data, you'll soon overcome pandas's learning curve and start solving complex problems in less time. about the book Pandas Workout hones your pandas skills to a professional-level through 50 hands-on exercises, along with 150 bonus challenges to really test your skills. Expert Python trainer Reuven Lerner coaches you through essentials like data frames and reveals pandas's rich functionality for string and date/time handling, complex indexing, and visualization. Clear explanations and detailed Jupyter Notebooks accompany every exercise, along with comparisons of different possible solutions. Work through this book, and you'll be ready to flex your muscles against even the trickiest pandas problems!

Julia as a Second Language makes it easy to add Julia to your programming toolbox. You will learn about Julia's type system and data structures by modeling the launch of a space rocket, use dictionaries to parse Roman numerals, and discover tuples and arrays through tracking pizza sales. You will even use Julia's unique multiple dispatch feature to send knights and archers into a simulated battle. By the time you are finished, you will be confident in the foundations of Julia and ready to dive into a specialised field like machine learning or data science. Don't be put off by Julia's reputation as a scientific programming language. There's no data science or numerical computing knowledge required. You can get started with what you learned in high school math classes. Research scientists, data analysts and machine learning professionals will appreciate how easy Julia makes it to handle and explore data sets. Experienced programmers will love to learn about Julia's interesting metaprogramming capabilities and the exciting possibilities of the language.

How To Read Java: Understanding, debugging, and optimizing JVM applications teaches you how to better understand Java application code. It's filled with code investigation techniques for tricky issues like uncovering glitches in code logic or locating intermittent runtime problems. Armed with these tools and practices you'll save time whenever you need to identify performance issues, understand dependencies, discover the root cause of crashes, or interpret unexpected results. Whether you're a senior software engineer or you're just getting started, this invaluable guide will help you in the fundamental task of understanding how your applications work. For intermediate Java developers.

Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting.In Time Series Forecasting in Python you will learn how to:Recognize a time series forecasting problem and build a performant predictive modelCreate univariate forecasting models that account for seasonal effects and external variablesBuild multivariate forecasting models to predict many time series at onceLeverage large datasets by using deep learning for forecasting time seriesAutomate the forecasting processTime Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You'll explore interesting real-world datasets like Google's daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.

Master Java persistence using the industry-leading tools Spring Data and Hibernate.In Java Persistence with Spring Data and Hibernate you will learn: Mapping persistent classes, value types, and inheritance Mapping collections and entity associations Processing transactions with Spring Data and Hibernate Creating fetch plans, strategies, and profiles Filtering data Building Spring Data REST projects Using Java persistence with non-relational databases Querying JPA with QueryDSL Testing Java persistence applications Java Persistence with Spring Data and Hibernate teaches you the ins-and-outs of Java persistence with hands-on examples using Spring Data, JPA, and Hibernate. The book carefully analyzes the capabilities of the major Java persistence tools, and guides you through the most common use cases. By comparing and contrasting the alternatives, you’ll find it easy to choose the right tool choice for your applications. You’ll learn how to make and utilize mapping strategies, about the different approach to transactions for both Hibernate and Spring Data, and even how to efficiently test Java persistence applications. The practical techniques are demonstrated with both relational and non-relational databases. Forewords by Dmitry Aleksandrov and Mohamed Taman. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Effectively managing application data is essential for any serious application. Spring Data and Hibernate bridge the gap between object-oriented code and relational data stores, radically simplifying Java persistence. By implementing the Java Persistence API (JPA) standard, these powerful tools help you avoid common bugs related to state and application data storage. About the book Java Persistence with Spring Data and Hibernate explores Java persistence using industry-standard tools. Hands-on examples introduce object-relational mapping and guide you through different mapping strategies to suit your needs. Covering transactions, persistent application testing, and non-relational databases, this book is your go-to resource for managing data in Java applications. What's inside Mapping persistent classes, value types, and inheritance Creating fetch plans, strategies, and profiles Building Spring Data REST projects Querying JPA with QueryDSL About the reader For intermediate Java programmers. About the author Catalin Tudose has more than 20 years of experience in the Java community. Christian Bauer, Gavin King, and Gary Gregory are the authors of Java Persistence with Hibernate, Second Edition, on which this book is based. Table of Contents PART 1 - GETTING STARTED WITH ORM 1 Understanding object/relational persistence 2 Starting a project 3 Domain models and metadata 4 Working with Spring Data JPA PART 2 - MAPPING STRATEGIES 5 Mapping persistent classes 6 Mapping value types 7 Mapping inheritance 8 Mapping collections and entity associations 9 Advanced entity association mappings PART 3 - TRANSACTIONAL DATA PROCESSING 10 Managing data 11 Transactions and concurrency 12 Fetch plans, strategies, and profiles 13 Filtering data PART 4 - BUILDING JAVA PERSISTENCE APPLICATIONS WITH SPRING 14 Integrating JPA and Hibernate with Spring 15 Working with Spring Data JDBC 16 Working with Spring Data REST PART 5 - BUILDING JAVA PERSISTENCE APPLICATIONS WITH SPRING 17 Working with Spring Data MongoDB 18 Working with Hibernate OGM PART 6 - WRITING QUERIES AND TESTING JAVA PERSISTENCE APPLICATIONS 19 Querying JPA with Querydsl 20 Testing Java persistence applications

Create bulletproof, high-performance web apps and servers with Rust.In Rust Web Development you will learn:Handling the borrow checker in an asynchronous environmentCreating web APIs and using JSON in RustGraceful error handlingTesting, tracing, logging, and debuggingDeploying Rust applicationsEfficient database accessRust Web Development is a hands-on guide to building server-based web applications with Rust. If youve built web servers using Java, C#, or PHP, youll instantly fall in love with the performance and development experience Rust delivers. This book shows you how to work efficiently using pure Rust, along with important Rust libraries such as tokio for async runtimes, warp for web servers and APIs, and reqwest to run external HTTP requests.

You know how to build Go programsGÇönow learn how to ship them to your customers efficiently! This practical guide to continuous delivery shows you how to rapidly establish an automated pipeline that will improve your testing, code quality, and final product.Bootstrapping Go is a hands-on guide to shipping Go-based software. Following examples in the powerful Go programming language, youGÇÖll learn how to establish pipelines that seamlessly ferry your projects through production and deployment. Put the theory of continuous delivery and continuous integration into action, and discover instantly useful guidance on automating your teamGÇÖs build and reacting with agility to customer demands. Development pipelines built to the principles of continuous delivery are the best way for code to flow through your organization. A properly functioning pipeline makes it seamless to modify functionality, enhance code quality, and evolve your deployments to meet your customerGÇÖs needs.

Securing Kubernetes Secrets is a compact hands-on guide to storing and protecting sensitive data in a Kubernetes environment. YouGÇÖll learn a security-first mindset that is vital for storing and using secrets correctly, and tools and concepts that will help you manage sensitive assets such as certificates, keys, and key rotation. Throughout, youGÇÖll tinker with relevant real-world examples. Protect secrets stored in a source code repository and consume them in a Kubernetes cluster, deploy HashiCorp Vault to secure KubernetesGÇÖs underlying infrastructure components and applications running on the platform, along with adding layers of security to maintain protection even in the event of a partial breach. By the time youGÇÖre finished, youGÇÖll have a toolbox of techniques that you can apply both as a developer or operations professional.