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Modern Data Architecture on AWS. A Practical Guide for Building Next-Gen Data Platforms on AWS
Many IT leaders and professionals are adept at extracting data from a particular type of database and deriving value from it. However, designing and implementing an enterprise-wide holistic data platform with purpose-built data services, all seamlessly working in tandem with the least amount of manual intervention, still poses a challenge.This book will help you explore end-to-end solutions to common data, analytics, and AI/ML use cases by leveraging AWS services. The chapters systematically take you through all the building blocks of a modern data platform, including data lakes, data warehouses, data ingestion patterns, data consumption patterns, data governance, and AI/ML patterns. Using real-world use cases, each chapter highlights the features and functionalities of numerous AWS services to enable you to create a scalable, flexible, performant, and cost-effective modern data platform.By the end of this book, you’ll be equipped with all the necessary architectural patterns and be able to apply this knowledge to efficiently build a modern data platform for your organization using AWS services.
Modern Data Architectures with Python will teach you how to seamlessly incorporate your machine learning and data science work streams into your open data platforms. You’ll learn how to take your data and create open lakehouses that work with any technology using tried-and-true techniques, including the medallion architecture and Delta Lake.Starting with the fundamentals, this book will help you build pipelines on Databricks, an open data platform, using SQL and Python. You’ll gain an understanding of notebooks and applications written in Python using standard software engineering tools such as git, pre-commit, Jenkins, and Github. Next, you’ll delve into streaming and batch-based data processing using Apache Spark and Confluent Kafka. As you advance, you’ll learn how to deploy your resources using infrastructure as code and how to automate your workflows and code development. Since any data platform's ability to handle and work with AI and ML is a vital component, you’ll also explore the basics of ML and how to work with modern MLOps tooling. Finally, you’ll get hands-on experience with Apache Spark, one of the key data technologies in today’s market.By the end of this book, you’ll have amassed a wealth of practical and theoretical knowledge to build, manage, orchestrate, and architect your data ecosystems.
Containers have entirely changed how developers and end-users see applications as a whole. With this book, you'll learn all about containers, their architecture and benefits, and how to implement them within your development lifecycle.You'll discover how you can transition from the traditional world of virtual machines and adopt modern ways of using DevOps to ship a package of software continuously. Starting with a quick refresher on the core concepts of containers, you'll move on to study the architectural concepts to implement modern ways of application development. You'll cover topics around Docker, Kubernetes, Ansible, Terraform, Packer, and other similar tools that will help you to build a base. As you advance, the book covers the core elements of cloud integration (AWS ECS, GKE, and other CaaS services), continuous integration, and continuous delivery (GitHub actions, Jenkins, and Spinnaker) to help you understand the essence of container management and delivery. The later sections of the book will take you through container pipeline security and GitOps (Flux CD and Terraform).By the end of this DevOps book, you'll have learned best practices for automating your development lifecycle and making the most of containers, infrastructure automation, and CaaS, and be ready to develop applications using modern tools and techniques.
DevOps and the cloud have changed how we look at software development and operations like never before, leading to the rapid growth of various DevOps tools, techniques, and practices. This updated edition helps you pick up the right tools by providing you with everything you need to get started with your DevOps journey.The book begins by introducing you to modern cloud-native architecture, and then teaches you about the architectural concepts needed to implement the modern way of application development. The next set of chapters helps you get familiarized with Git, Docker, Kubernetes, Ansible, Terraform, Packer, and other similar tools to enable you to build a base. As you advance, you’ll explore the core elements of cloud integration—AWS ECS, GKE, and other CaaS services. The chapters also discuss GitOps, continuous integration, and continuous delivery—GitHub actions, Jenkins, and Argo CD—to help you understand the essence of modern app delivery. Later, you’ll operate your container app in production using a service mesh and apply AI in DevOps. Throughout the book, you’ll discover best practices for automating and managing your development lifecycle, infrastructure, containers, and more.By the end of this DevOps book, you'll be well-equipped to develop and operate applications using modern tools and techniques.
Liudmila Molkova, Sergey Kanzhelev
As distributed systems become more complex and dynamic, their observability needs to grow to aid the development of holistic solutions for performance or usage analysis and debugging. Distributed tracing brings structure, correlation, causation, and consistency to your telemetry, thus allowing you to answer arbitrary questions about your system and creating a foundation for observability vendors to build visualizations and analytics.Modern Distributed Tracing in .NET is your comprehensive guide to observability that focuses on tracing and performance analysis using a combination of telemetry signals and diagnostic tools. You'll begin by learning how to instrument your apps automatically as well as manually in a vendor-neutral way. Next, you’ll explore how to produce useful traces and metrics for typical cloud patterns and get insights into your system and investigate functional, configurational, and performance issues. The book is filled with instrumentation examples that help you grasp how to enrich auto-generated telemetry or produce your own to get the level of detail your system needs, along with controlling your costs with sampling, aggregation, and verbosity.By the end of this book, you'll be ready to adopt and leverage tracing and other observability signals and tools and tailor them to your needs as your system evolves.
Almost a decade after the release of Node.js, the tooling used by frontend developers is fully embracing this cross-platform JavaScript runtime, which is sadly often limited to server-side web development. This is where this Node.js book comes in, showing you what this popular runtime has to offer and how you can unlock its full potential to create frontend-focused web apps.You’ll begin by learning the basics and internals of Node.js, before discovering how to divide your code into modules and packages. Next, you’ll get to grips with the most popular package managers and their uses and find out how to use TypeScript and other JavaScript variants with Node.js. Knowing which tool to use when is crucial, so this book helps you understand all the available state-of-the-art tools in Node.js. You’ll interact with linters such as ESLint and formatters such as Prettier. As you advance, you’ll become well-versed with the Swiss Army Knife for frontend developers – the bundler. You’ll also explore various testing utilities, such as Jest, for code quality verification. Finally, you’ll be able to publish your code in reusable packages with ease.By the end of this web development book, you’ll have gained the knowledge to confidently choose the right code structure for your repositories with all that you’ve learned about monorepos.
Understanding full-stack development is vital as companies aim to bridge the gap between frontend and backend development. Recent trends show deeper integration between the two, opening numerous possibilities for building real-world web applications, through server-side technologies like Node.js, Express, and MongoDB. Written by the author of Learning Redux and Learn React Hooks, and CEO of TouchLay, Modern Full-Stack React Projects will guide you through the entire process of advancing from a frontend developer to a full-stack developer. Starting with how to set up robust projects that can be maintained for a long time, you’ll then progress toward developing a backend system and integrating it with the frontend. Throughout the book, you’ll learn how to build, test, and deploy a blog application and a chat application. You’ll also explore MongoDB, Express, React, Node.js (MERN) stack, best practices for frontend and backend development, different full-stack architectures, unit and end-to-end testing, and deployment of full-stack web applications. Once you get to grips with the essential concepts, you’ll progress to learn how to use Next.js, an enterprise-grade full-stack web framework for React. By the end, you’ll be well-versed in the MERN stack and all set to create performant and scalable full-stack web applications.
In the ASP.NET Core ecosystem, choosing the right JavaScript framework is key to addressing diverse project requirements. Witten by a four-time Microsoft MVP with 16 years of software development experience, this book is your comprehensive guide to mastering full-stack development, combining ASP.NET Core’s robust backend capabilities with the dynamic frontend power of Vue.js, Angular, and React.This book uses ASP.NET Core to teach you best practices for integrating modern JavaScript frameworks, and creating responsive, high-performance applications that deliver seamless client–server interactions and scalable RESTful APIs. In addition to building expertise in ASP.NET Core’s core strengths, such as API security, architecture principles, and performance optimization, the chapters will help you develop the essential frontend skills needed for full-stack development. Sections on Blazor take a C#-based approach to creating interactive UIs, showcasing ASP.NET Core’s flexibility in handling both server and client-side needs.By the end of this book, you will have a complete toolkit for designing, deploying, and maintaining complex full-stack applications, along with practical knowledge of both backend and frontend development.
Few things are more annoying for gamers than encountering a buggy new game. This often leads to negative reviews, and in turn, you’ll find that demand for your games declines. The solution lies in better quality assurance (QA) – and Modern Game Testing will show you how to achieve just that. Whether you’re a new tester, developer or producer, the QA testing techniques shown in this book, using modern methodologies and the latest technology, will have you releasing quality games that are on time and, most importantly, on budget.The book begins by introducing you to QA and the various types of tests that are performed on games. You’ll then explore test cases and bug reporting, building tests for different platforms (even consoles and PCs), and LiveOps and test management. As you advance, you’ll build a QA team from scratch and work with remote QA testers. The chapters help you take a more traditional approach to learning lessons, enabling you to examine the modern agile approach and various testing strategies that you can then adopt. All angles are covered with oodles of examples, so you’ll have everything you need to implement QA strategies in your organization.By the end of this book, you’ll have a clear understanding of the modern methodologies of QA testing for games, and be able to build efficient, reliable, and long-lasting QA teams.
Generative AI models and AI language models are becoming increasingly popular due to their unparalleled capabilities. This book will provide you with insights into the inner workings of the LLMs and guide you through creating your own language models. You’ll start with an introduction to the field of generative AI, helping you understand how these models are trained to generate new data.Next, you’ll explore use cases where ChatGPT can boost productivity and enhance creativity. You’ll learn how to get the best from your ChatGPT interactions by improving your prompt design and leveraging zero, one, and few-shots learning capabilities. The use cases are divided into clusters of marketers, researchers, and developers, which will help you apply what you learn in this book to your own challenges faster.You’ll also discover enterprise-level scenarios that leverage OpenAI models’ APIs available on Azure infrastructure; both generative models like GPT-3 and embedding models like Ada. For each scenario, you’ll find an end-to-end implementation with Python, using Streamlit as the frontend and the LangChain SDK to facilitate models' integration into your applications.By the end of this book, you’ll be well equipped to use the generative AI field and start using ChatGPT and OpenAI models’ APIs in your own projects.
Colleen M. Farrelly, Franck Kalala Mutombo, Michael Giske
We are living in the age of big data, and scalable solutions are a necessity. Network science leverages the power of graph theory and flexible data structures to analyze big data at scale.This book guides you through the basics of network science, showing you how to wrangle different types of data (such as spatial and time series data) into network structures. You’ll be introduced to core tools from network science to analyze real-world case studies in Python. As you progress, you’ll find out how to predict fake news spread, track pricing patterns in local markets, forecast stock market crashes, and stop an epidemic spread. Later, you’ll learn about advanced techniques in network science, such as creating and querying graph databases, classifying datasets with graph neural networks (GNNs), and mining educational pathways for insights into student success. Case studies in the book will provide you with end-to-end examples of implementing what you learn in each chapter.By the end of this book, you’ll be well-equipped to wrangle your own datasets into network science problems and scale solutions with Python.
Modern JavaScript Applications. Keep abreast of the practical uses of modern JavaScript
Over the years, JavaScript has become vital to the development of a wide range of applications with different architectures. But JS moves lightning fast, and it’s easy to fall behind. Modern JavaScript Applications is designed to get you exploring the latest features of JavaScript and how they can be applied to develop high-quality applications with different architectures. Begin by creating a single page application that builds on the innovative MVC approach using AngularJS, then move forward to develop an enterprise-level application with the microservices architecture using Node to build web services. After that, shift your focus to network programming concepts as you build a real-time web application with websockets. Learn to build responsive, declarative UIs with React and Bootstrap, and see how the performance of web applications can be enhanced using Functional Reactive Programming (FRP). Along the way, explore how the power of JavaScript can be increased multi-fold with high performance techniques. By the end of the book, you’ll be a skilled JavaScript developer with a solid knowledge of the latest JavaScript techniques, tools, and architecture to build modern web apps.
JavaScript has evolved into a language that you can use on any platform. Modern JavaScript Web Development Cookbook is a perfect blend of solutions for traditional JavaScript development and modern areas that developers have lately been exploring with JavaScript. This comprehensive guide teaches you how to work with JavaScript on servers, browsers, mobile phones and desktops.You will start by exploring the new features of ES8. You will then move on to learning the use of ES8 on servers (with Node.js), with the objective of producing services and microservices and dealing with authentication and CORS. Once you get accustomed to ES8, you will learn to apply it to browsers using frameworks, such as React and Redux, which interact through Ajax with services. You will then understand the use of a modern framework to develop the UI. In addition to this, development for mobile devices with React Native will walk you through the benefits of creating native apps, both for Android and iOS.Finally, you’ll be able to apply your new-found knowledge of server-side and client-side tools to develop applications with Electron.
Modern love 6 gorących opowiadań na walentynki
Modern Love to zbiór 6 romantycznych i seksownych opowiadań, które udowadniają, że miłość, pożądanie i cielesność mają różne oblicza. Zachwiane fundamenty. Dwa oblicza Sary Larson" Catriny Curant: Czy wózek inwalidzki jest ograniczeniem, czy ograniczenia mamy w głowie? Kim stanie się Łukasz, gdy postanowi realizować się w życiu bez względu na wszystko i gdy na jego drodze stanie nowa szefowa, zimna Sara Larson? Dojrzała rozkosz" Anny Kaveto: Dwoje dojrzałych ludzi po przejściach. Czy taka miłość może być namiętna i pełna rozkoszy? Odnaleźć swoje miejsce" Annah Viki M.: Drogi Ewy i Jana ciągle się rozchodzą. Jednak nie potrafią o sobie zapomnieć i rok w rok, w walentynki, kontaktują się ze sobą mimo innych relacji... Blizny" rehab-e: Czy starszy mężczyzna, zrażony poprzednimi relacjami, pozwoli sobie na nową znajomość z młodszym przystojniakiem? Jakie sekrety oboje skrywają? Walentynkowe tajemnice" Catriny Curant: Inez ma dar, chociaż czasami wydaje jej się, że jest to przekleństwo... widzi przyszłość ludzi, los ich miłości. A Wy? Odważylibyście się skorzystać z daru, aby zobaczyć swoją przyszłość z ukochaną osobą? W drodze do ciebie" Annah Viki M.: Ewa porywa Łucję w podróż, by przekonać ją do siebie. Tymczasem Łucja nie chce związać z kobietą, ponieważ boi się konsekwencji społecznych i rodzinnych. Czy ta podróż zbliży dziewczyny do siebie? Czy Ewa wyzna Łucji, co ją najbardziej podnieca?
David Flores, Christian Adell, Josh VanDeraa, Eric Chou, ...
As modern IT services and software architectures such as microservices rely increasingly on network performance, the relevance of networks has never been greater. Network observability has emerged as a critical evolution of traditional monitoring, providing the deep visibility needed to manage today’s complex, dynamic environments. In Modern Network Observability, authors David Flores, Christian Adell, and Josh VanDeraa share their extensive experience to guide you through building and deploying a flexible observability stack using open-source tools.This book begins by addressing the limitations of monolithic monitoring solutions, showing you how to transform them into a composable, flexible observability stack. Through practical implementations, you’ll learn how to collect, normalize, and analyze network data from diverse sources, build intuitive dashboards, and set up actionable alerts that help you stay ahead of potential issues. Later, you’ll cover advanced topics, such as integrating observability data into your network automation strategy, ensuring your network operations align with business objectives.By the end of this book, you'll be able to proactively manage your network, minimize downtime, and ensure resilient, efficient, and future-proof operations.
Your experience and knowledge always influence the approach you take and the tools you use to write your programs. With a sound understanding of how to approach your goal and what software paradigms to use, you can create high-performing applications quickly and efficiently.In this two-part book, you’ll discover the untapped features of object-oriented programming and use it with other software tools to code fast and efficient applications. The first part of the book begins with a discussion on how OOP is used today and moves on to analyze the ideas and problems that OOP doesn’t address. It continues by deconstructing the complexity of OOP, showing you its fundamentally simple core. You’ll see that, by using the distinctive elements of OOP, you can learn to build your applications more easily.The next part of this book talks about acquiring the skills to become a better programmer. You’ll get an overview of how various tools, such as version control and build management, help make your life easier. This book also discusses the pros and cons of other programming paradigms, such as aspect-oriented programming and functional programming, and helps to select the correct approach for your projects. It ends by talking about the philosophy behind designing software and what it means to be a good developer.By the end of this two-part book, you will have learned that OOP is not always complex, and you will know how you can evolve into a better programmer by learning about ethics, teamwork, and documentation.
Python is the go-to language for developers, engineers, data scientists, and hobbyists worldwide. Known for its versatility, Python can efficiently power applications, offering remarkable speed, safety, and scalability. This book distills Python into a collection of straightforward recipes, providing insights into specific language features within various contexts, making it an indispensable resource for mastering Python and using it to handle real-world use cases.The third edition of Modern Python Cookbook provides an in-depth look into Python 3.12, offering more than 140 new and updated recipes that cater to both beginners and experienced developers. This edition introduces new chapters on documentation and style, data visualization with Matplotlib and Pyplot, and advanced dependency management techniques using tools like Poetry and Anaconda. With practical examples and detailed explanations, this cookbook helps developers solve real-world problems, optimize their code, and get up to date with the latest Python features.
Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand.This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications.The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it.By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation.
Modern Python Cookbook. The latest in modern Python recipes for the busy modern programmer
Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide great speed, safety, and scalability. By exposing Python as a series of simple recipes, you can gain insight into specific language features in a particular context. Having a tangible context helps make the language or standard library feature easier to understand.This book comes with over 100 recipes on the latest version of Python. The recipes will benefit everyone ranging from beginner to an expert. The book is broken down into 13 chapters that build from simple language concepts to more complex applications of the language. The recipes will touch upon all the necessary Python concepts related to data structures, OOP, functional programming, as well as statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively use the advantages that it offers. You will end the book equipped with the knowledge of testing, web services, and configuration and application integration tips and tricks. The recipes take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe. You will be armed with the knowledge of creating applications with flexible logging, powerful configuration, and command-line options, automated unit tests, and good documentation.
The Python 3 Standard Library is a vast array of modules that you can use for developing various kinds of applications. It contains an exhaustive list of libraries, and this book will help you choose the best one to address specific programming problems in Python.The Modern Python Standard Library Cookbook begins with recipes on containers and data structures and guides you in performing effective text management in Python. You will find Python recipes for command-line operations, networking, filesystems and directories, and concurrent execution. You will learn about Python security essentials in Python and get to grips with various development tools for debugging, benchmarking, inspection, error reporting, and tracing. The book includes recipes to help you create graphical user interfaces for your application. You will learn to work with multimedia components and perform mathematical operations on date and time. The recipes will also show you how to deploy different searching and sorting algorithms on your data.By the end of the book, you will have acquired the skills needed to write clean code in Python and develop applications that meet your needs.
Modern R Programming Cookbook. Recipes to simplify your statistical applications
R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications.
Scala is both a functional programming and object-oriented programming language designed to express common programming patterns in a concise, readable, and type-safe way. Complete with step-by-step instructions, Modern Scala Projects will guide you in exploring Scala capabilities and learning best practices. Along the way, you'll build applications for professional contexts while understanding the core tasks and components.You’ll begin with a project for predicting the class of a flower by implementing a simple machine learning model. Next, you'll create a cancer diagnosis classification pipeline, followed by tackling projects delving into stock price prediction, spam filtering, fraud detection, and a recommendation engine. The focus will be on application of ML techniques that classify data and make predictions, with an emphasis on automating data workflows with the Spark ML pipeline API. The book also showcases the best of Scala’s functional libraries and other constructs to help you roll out your own scalable data processing frameworks.By the end of this Scala book, you’ll have a firm foundation in Scala programming and have built some interesting real-world projects to add to your portfolio.
We live in a serendipitous era where the explosion in the quantum of data collected and a renewed interest in data-driven techniques such as machine learning (ML), has changed the landscape of analytics, and with it, time series forecasting. This book, filled with industry-tested tips and tricks, takes you beyond commonly used classical statistical methods such as ARIMA and introduces to you the latest techniques from the world of ML.This is a comprehensive guide to analyzing, visualizing, and creating state-of-the-art forecasting systems, complete with common topics such as ML and deep learning (DL) as well as rarely touched-upon topics such as global forecasting models, cross-validation strategies, and forecast metrics. You’ll begin by exploring the basics of data handling, data visualization, and classical statistical methods before moving on to ML and DL models for time series forecasting. This book takes you on a hands-on journey in which you’ll develop state-of-the-art ML (linear regression to gradient-boosted trees) and DL (feed-forward neural networks, LSTMs, and transformers) models on a real-world dataset along with exploring practical topics such as interpretability.By the end of this book, you’ll be able to build world-class time series forecasting systems and tackle problems in the real world.
Manu Joseph, Jeffrey Tackes, Christoph Bergmeir
Predicting the future, whether it's market trends, energy demand, or website traffic, has never been more crucial. This practical, hands-on guide empowers you to build and deploy powerful time series forecasting models. Whether you’re working with traditional statistical methods or cutting-edge deep learning architectures, this book provides structured learning and best practices for both.Starting with the basics, this data science book introduces fundamental time series concepts, such as ARIMA and exponential smoothing, before gradually progressing to advanced topics, such as machine learning for time series, deep neural networks, and transformers. As part of your fundamentals training, you’ll learn preprocessing, feature engineering, and model evaluation. As you progress, you’ll also explore global forecasting models, ensemble methods, and probabilistic forecasting techniques.This new edition goes deeper into transformer architectures and probabilistic forecasting, including new content on the latest time series models, conformal prediction, and hierarchical forecasting. Whether you seek advanced deep learning insights or specialized architecture implementations, this edition provides practical strategies and new content to elevate your forecasting skills.