Book Image

Cloud Native Python

By : Manish Sethi
Book Image

Cloud Native Python

By: Manish Sethi

Overview of this book

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
Table of Contents (14 chapters)
6
Creating UIs to Scale with Flux

Summary

In this chapter, we focused on writing lots of code to build our microservices. We basically got an understanding of how the RESTful APIs work. We also saw how we can extend these APIs and make sure that we understand the HTTP response by the response given by these APIs. Moreover, you learned how to write test cases, which are most important to ensure that our code works well and is good to go for the production environment.