Book Image

Python Microservices Development

Book Image

Python Microservices Development

Overview of this book

We often deploy our web applications into the cloud, and our code needs to interact with many third-party services. An efficient way to build applications to do this is through microservices architecture. But, in practice, it's hard to get this right due to the complexity of all the pieces interacting with each other. This book will teach you how to overcome these issues and 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: you’ll build everything using Python 3 and its amazing tooling ecosystem. You will understand the principles of TDD and apply them. You will use Flask, Tox, and other tools to build your services using best practices. You will learn how to secure connections between services, and how to script Nginx using Lua to build web application firewall features such as rate limiting. You will also familiarize yourself with Docker’s role in microservices, and use Docker containers, CoreOS, and Amazon Web Services to deploy your services. This book will take you on a journey, ending with the creation of a complete Python application based on microservices. By the end of the book, you will be well versed with the fundamentals of building, designing, testing, and deploying your Python microservices.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Introduction

Data Service


The following diagram describes our new application organization. Both the Reports and Strava service get some work from Redis and interact with the Data Service, as shown in the following diagram:

The Data Service is an HTTP API that wraps the database containing all the users and runs data. The dashboard is the frontend that implements the HTML user interface.

Note

When you have any doubt about whether it's a good idea to split out a new microservice out of your main app, don't do it.

Some of the information required by the Celery workers can be passed through the Redis broker, such as the Strava tokens for the Strava service.

For the Reports service, however, it's not practical to send all the info through Redis because the amount of data can be significant. If a runner is doing 30 runs per month, it's simpler to let the Reports service pull them directly from the Data Service.

The Data service view needs to implement the following APIs:

  • For the Strava service--a POST endpoint to...