Cloud Native Python
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Cloud Native Python
Build cloud native applications in Python About This Book This is the only reliable resource that showcases the tools and techniques you need build robust and resilient cloud native applications in Python Learn how to architect your application on both, the AWS and Azure clouds for high availability Assess, monitor, and troubleshoot your applications in the cloud Who This Book Is For This book is ideal for developers with a basic knowledge of Python who want to learn to build, test, and scale their Python-based applications. No prior experience of writing microservices in Python is required. What You Will Learn Get to know “the way of the cloud”, including why developing good cloud software is fundamentally about mindset and discipline Know what microservices are and how to design them Create reactive applications in the cloud with third-party messaging providers Build massive-scale, user-friendly GUIs with React and Flux Secure cloud-based web applications: the do's, don'ts, and options Plan cloud apps that support continuous delivery and deployment In Detail Businesses today are evolving so rapidly that having their own infrastructure to support their expansion is not feasible. As a result, they have been resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications. This book will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you'll learn how to build microservices in Python using REST APIs in an event driven approach and you will build the web layer. Next, you'll learn about Interacting data services and building Web views with React, after which we will take a detailed look at application security and performance. Then, you'll also learn how to Dockerize your services. And finally, you'll learn how to deploy the application on the AWS and Azure platforms. We will end the book by discussing some concepts and techniques around troubleshooting problems that might occur with your applications after you've deployed them. This book will teach you how to craft applications that are built as small standard units, using all the proven best practices and avoiding the usual traps. It's a practical book: we're going to build everything using Python 3 and its amazing tooling ecosystem. The book will take you on a journey, the destination of which, is the creation of a complete Python application based on microservices over the cloud platform Style and approach Filled with examples, this book takes a step-by-step approach to teach you each and every configuration you need to make your application highly available and fault tolerant.
Getting Started with Cloud-native Python
"Businesses today are evolving so rapidly that having their own infrastructure to support their expansion is not feasible. As a result, they have been resorting to the elasticity of the cloud to provide a platform to build and deploy their highly scalable applications.This video will be the one stop for you to learn all about building cloud-native architectures in Python. It will begin by introducing you to cloud-native architecture and will help break it down for you. Then you'll learn how to build microservices in Python using REST APIs in an event-driven approach and you will build the web layer."--Resource description page.
Python for AI, Automation, and Cloud-Native Systems
Attention: Are you ready to build the intelligent systems shaping the future of cloud computing and automation? In today's fast-moving digital landscape, the ability to orchestrate AI workflows, automate cloud-native operations, and deploy scalable systems efficiently is what separates expert developers from the rest. Interest: Python for AI, Automation, and Cloud-Native Systems is your complete hands-on roadmap to mastering the intersection of Python, artificial intelligence, and modern cloud technologies. This book bridges theory with practice, guiding you step-by-step through real-world scenarios that demonstrate how to design, automate, and scale intelligent systems for today's adaptive infrastructure. You'll discover how to: Build end-to-end AI-driven automation pipelines using Python and popular frameworks. Orchestrate multi-step workflows that connect data ingestion, prediction, and cloud deployment seamlessly. Use tools like Docker(R), Kubernetes(R), and Airflow(R) to manage scalable, fault-tolerant systems. Automate machine learning tasks in AWS(R), Azure(R), and Google Cloud(R) environments. Integrate Python-based automation into DevOps and MLOps practices. Debug, test, and continuously improve distributed intelligent systems. Desire: Whether you're a developer, data engineer, AI practitioner, or cloud architect, this book empowers you to think like an automation architect-combining creativity, precision, and system thinking to build intelligent, adaptive solutions. Each chapter is built around real-world projects and industry best practices, blending AI-powered automation, orchestration design, and cloud-native workflows into one cohesive learning path. By the end of this guide, you'll be able to: ✅ Design reliable, self-healing automation pipelines. ✅ Leverage Python's AI ecosystem for predictive, adaptive systems. ✅ Streamline deployments across multi-cloud platforms. ✅ Future-proof your skills for the next generation of intelligent computing. Action: Don't just code-orchestrate intelligence. Equip yourself with the skills that drive the future of automation and cloud development.