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Designing Cloud Data Platforms
Designing Cloud Data Platforms

Centralized data warehouses, the long-time defacto standard for housing data for analytics, are rapidly giving way to multi-faceted cloud data platforms. Companies that embrace modern cloud data platforms benefit from an integrated view of their business using all of their data and can take advantage of advanced analytic practices to drive predictions and as yet unimagined data services. Designing Cloud Data Platforms is a hands-on guide to envisioning and designing a modern scalable data platform that takes full advantage of the flexibility of the cloud. As you read, you'll learn the core components of a cloud data platform design, along with the role of key technologies like Spark and Kafka Streams. You'll also explore setting up processes to manage cloud-based data, keep it secure, and using advanced analytic and BI tools to analyze it. Well-designed pipelines, storage systems, and APIs eliminate the complicated scaling and maintenance required with on ...
Cloud Native Go
Cloud Native Go

What do Docker, Kubernetes, and Prometheus have in common? All of these cloud native technologies are written in the Go programming language. This practical book shows you how to use Go's strengths to develop cloud native services that are scalable and resilient, even in an unpredictable environment. You'll explore the composition and construction of these applications, from lower-level features of Go to mid-level design patterns to high-level architectural considerations. Each chapter builds on the lessons of the last, walking intermediate to advanced developers through Go to construct a simple but fully featured distributed key-value store. You'll learn best practices for adopting Go as your development language for solving cloud native management and deployment issues. - Learn how cloud native applications differ from other software architectures; - Understand how Go can solve the challenges of designing scalable distributed services; - Leverage G ...
TensorFlow 2.x in the Colaboratory Cloud
TensorFlow 2.x in the Colaboratory Cloud

Use TensorFlow 2.x with Google's Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab's default install of the most current TensorFlow 2.x along with Colab's easy access to on-demand GPU hardware acceleration in the cloud for fast execution of deep learning models. This book offers you the opportunity to grasp deep learning in an applied manner with the only requirement being an Internet connection. Everything else - Python, TensorFlow 2.x, GPU support, and Jupyter Notebooks - is provided and ready to go from Colab. The book begins with an introduction to TensorFlow 2.x and the Google Colab cloud service. You will learn how to provision a workspace on Google Colab and build a simple neural network application. From there you will progress into TensorFlow datasets and building input pipelines in support of modeling and ...
Spring Boot: Up and Running
Spring Boot: Up and Running

With over 75 million downloads per month, Spring Boot is the most widely used Java framework available. Its ease and power have revolutionized application development from monoliths to microservices. Yet Spring Boot's simplicity can also be confounding. How do developers learn enough to be productive immediately? This practical book shows you how to use this framework to write successful mission-critical applications. Mark Heckler from VMware, the company behind Spring, guides you through Spring Boot's architecture and approach, covering topics such as debugging, testing, and deployment. If you want to develop cloud native Java or Kotlin applications with Spring Boot rapidly and effectively (using reactive programming, building APIs, and creating database access of all kinds) this book is for you. Learn how Spring Boot simplifies cloud native application development and deployment; Build reactive applications and extend communication across the network boundary to c ...
Practical Rust Web Projects
Practical Rust Web Projects

Go beyond the basics of Rust and build web and serverless cloud applications. The applications explained in this practical book include web sites, RESTful APIs, a real-time web chat application, and frontend application with WebAssembly. Each chapter is organized in the following format: what this kind of application looks like; requirements for the example program; an introduction to the Rust libraries used; step-by-step implementation of the example program, including common pitfalls and best practices; and a brief comparison of libraries and frameworks in the same domain. This book will open your eyes to the world of practical web applications of Rust. After reading the book, you will be able to apply your Rust knowledge to build your own web projects. ...
Kubeflow Operations Guide
Kubeflow Operations Guide

Building models is a small part of the story when it comes to deploying machine learning applications. The entire process involves developing, orchestrating, deploying, and running scalable and portable machine learning workloads-a process Kubeflow makes much easier. This practical book shows data scientists, data engineers, and platform architects how to plan and execute a Kubeflow project to make their Kubernetes workflows portable and scalable. Authors Josh Patterson, Michael Katzenellenbogen, and Austin Harris demonstrate how this open source platform orchestrates workflows by managing machine learning pipelines. You'll learn how to plan and execute a Kubeflow platform that can support workflows from on-premises to cloud providers including Google, Amazon, and Microsoft. Dive into Kubeflow architecture and learn best practices for using the platform; Understand the process of planning your Kubeflow deployment; Install Kubeflow on an existing on-premise Kubernetes clust ...
Practical AI on the Google Cloud Platform
Practical AI on the Google Cloud Platform

Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. With this book, you'll learn how to use Google's AI-powered cloud services to do everything from creating a chatbot to analyzing text, images, and video. Author Micheal Lanham demonstrates methods for building and training models step-by-step and shows you how to expand your models to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, you'll quickly get up to speed with Google Cloud Platform, whether you want to build an AI assistant or a simple business AI application. Learn key concepts for data science, machine learning, and deep learning; Explore tools like Video AI and AutoML Tables; Build a simple language processor using deep learning systems; Perform image recognition using CNNs, transfer ...
Learn Microservices with Spring Boot, 2nd Edition
Learn Microservices with Spring Boot, 2nd Edition

Build Java-based microservices architecture using the Spring Boot framework by evolving an application from a small monolith to an event-driven architecture composed of several services. This revised book follows an incremental approach in teaching the structure of microservices, test-driven development, and common patterns in distributed systems such as service discovery, load balancing, routing, centralized logs, per-environment configuration, and containerization. This updated book now covers what's been added to the latest Spring Boot release, including support for the latest Java SE; more deep-dive knowledge on how Spring Boot works; testing with JUnit 5; changes in the Spring Cloud tools used for service discovery and load balancing; building Docker images using cloud-native buildpacks; a basic centralized logging solution; E2E traceability with Sleuth; centralized configuration with Consul; many dependency upgrades; support for Spring Data Neumann; and more. Author Mo ...
Learning Dapr
Learning Dapr

Get the authoritative guide to Dapr, the distributed application runtime that works with new and existing programming languages alike. Written by the model's creators, this introduction shows you how Dapr not only unifies stateless, stateful, and actor programming models but also runs everywhere - in the cloud or on the edge. Authors Haishi Bai and Yaron Schneider, both with Microsoft's Azure CTO team, explain that, with Dapr, you don't need to include any SDKs or libraries in your user code. Instead, you automatically get flexible binding, state management, the actor pattern, pub-sub, reliable messaging, and many more features. This book shows developers, architects, CIOs, students, and computing enthusiasts how to get started with Dapr. ...
Angular for Enterprise-Ready Web Applications, 2nd Edition
Angular for Enterprise-Ready Web Applications, 2nd Edition

This 2nd edition of Angular for Enterprise-Ready Web Applications is updated with in-depth coverage of the evergreen Angular platform. You'll start by mastering Angular programming fundamentals. Using the Kanban method and GitHub tools, you'll build great-looking apps with Angular Material and also leverage reactive programming patterns with RxJS, discover the flux pattern with NgRx, become familiar with automated testing, utilize continuous integration using CircleCI, and deploy your app to the cloud using Vercel Now and GCloud. You will then learn how to design and develop line-of-business apps using router-first architecture with observable data anchors, demonstrated through oft-used recipes like master/detail views, and data tables with pagination and forms. Next, you'll discover robust authentication and authorization design demonstrated via integration with Firebase, API documentation using Swagger, and API implementation using the MEAN stack. Finally, you will le ...
IoT and Edge Computing for Architects, 2nd Edition
IoT and Edge Computing for Architects, 2nd Edition

Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is needed if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of IoT devices. IoT and Edge Computing for Architects, Second Edition encompasses the entire spectrum of IoT solutions, from IoT sensors to the cloud. It examines modern sensor systems, focusing on their power and functionality. It also looks at communication theory, paying close attention to near-range PAN, including the new Bluetooth® 5.0 specification and mesh networks. Then, the book explores IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, Sigfox, and LoRaWAN. It also explains edge computing, routing and gateways, and their role in fog computing, as well as the messaging protocols of MQTT 5.0 and CoAP. With the data now in internet form, you'll get an understanding of ...
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