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Cloud Native Python

You're reading from Cloud Native Python Build and deploy resilent applications on the cloud using microservices, AWS, Azure and more

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781787129313

Length 374 pages

Edition 1st Edition

Languages

Python

Tools

AWS

Concepts

Cloud Native

Author (1):

Manish Sethi

View More author details

Table of Contents (14) Chapters

Preface

1. Introducing Cloud Native Architecture and Microservices

2. Building Microservices in Python FREE CHAPTER

3. Building a Web Application in Python

4. Interacting Data Services

5. Building WebViews with React

6. Creating UIs to Scale with Flux

7. Learning Event Sourcing and CQRS

8. Securing the Web Application

9. Continuous Delivery

10. Dockerizing Your Services

11. Deploying on the AWS Platform

12. Implementing on the Azure Platform

13. Monitoring the Cloud Application

Getting started with Amazon Web Services (AWS)

Amazon Web Services (AWS) is a secure cloud platform. It has various offerings in IaaS as well as PaaS, including computing power, database storage, and content delivery, which help in scaling applications, and also grows our business across the globe. AWS is a public cloud, and as per the cloud computing concepts, it provides all its resources in an on-demand delivery with a pay-as-you-go plan.

You can read more about AWS and its services at https://aws.amazon.com/.

As specified previously in Chapter 1, Introducing Cloud Native Architecture and Microservices, you need to create an AWS account to start using the services. You can use the following link to create an account:

https://medium.com/appliedcode/setup-aws-account-1727ce89353e

Once you are logged in, you will see the following screen, which showcases the AWS and its categories...

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Authors (1)

Sethi

Sethi

Manish Sethi works as an engineer in Bangalore, India. Over the course of his career, he has worked for start-ups and Fortune 10 companies, helping organizations adopt a cloud-native approach to architecting massively scalable products. He regularly spends time learning and implementing new technology paradigms and actively finds himself solving practical problems using serverless architecture, machine and deep learning, and so on. He contributes to Bangalore DevOps and the Docker community by writing blog posts, giving talks in meetups, and more.

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