Book Image

Building Serverless Microservices in Python

By : Richard Takashi Freeman
Book Image

Building Serverless Microservices in Python

By: Richard Takashi Freeman

Overview of this book

Over the last few years, there has been a massive shift from monolithic architecture to microservices, thanks to their small and independent deployments that allow increased flexibility and agile delivery. Traditionally, virtual machines and containers were the principal mediums for deploying microservices, but they involved a lot of operational effort, configuration, and maintenance. More recently, serverless computing has gained popularity due to its built-in autoscaling abilities, reduced operational costs, and increased productivity. Building Serverless Microservices in Python begins by introducing you to serverless microservice structures. You will then learn how to create your first serverless data API and test your microservice. Moving on, you'll delve into data management and work with serverless patterns. Finally, the book introduces you to the importance of securing microservices. By the end of the book, you will have gained the skills you need to combine microservices with serverless computing, making their deployment much easier thanks to the cloud provider managing the servers and capacity planning.
Table of Contents (13 chapters)
Title Page

Loading and end-to-end testing at scale

Next, we are going to take a look at Locust, which is a Python tool for performance and load testing. Then we are going to talk about strategies to reduce the API's latency and improve the response time of the API, and using Locust will show us the performance improvements.

Load testing your serverless microservice

First, you need to have a serverless microservice stack running with ./, and have loaded data into the DynamoDB table using the python3 Python script.

Then install Locust, if it hasn't already been installed with the other packages in requirements.txt:

$ sudo pip3 install locustio