Book Overview & Buying
Table Of Contents
Feedback & Rating

Building Serverless Microservices in Python

By : Takashi Freeman

3 (5)

Buy this Book

Building Serverless Microservices in Python

3 (5)

By: Takashi Freeman

Buy this Book

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.

Preface

Who this book is for

What this book covers

To get the most out of this book

Get in touch

Free Chapter

Serverless Microservices Architectures and Patterns

Understanding different architecture types and patterns

Virtual machines, containers, and serverless computing

Overview of microservice integration patterns

Communication styles and decomposition microservice patterns

Serverless computing in AWS

Setting up your serverless environment

Summary

Creating Your First Serverless Data API

Overview of security in AWS

Securing your serverless microservices

Building a serverless microservice data API

Setting up Lambda security in the AWS Management Console

Creating and writing to a NoSQL database called DynamoDB using AWS

Creating and writing to a NoSQL database called DynamoDB using Python

Creating a Lambda to query DynamoDB

Setting up the API Gateway and integrating it with a Lambda proxy

Connecting API Gateway, Lambda, and DynamoDB

Cleaning-up

Summary

Deploying Your Serverless Stack

An overview of serverless stack build and deploy options

Creating a profile, an S3 bucket, IAM policies, and IAM roles resources

Building and deploying with API Gateway, Lambda, and DynamoDB

Summary

Testing Your Serverless Microservice

Unit testing your Python Lambda code

Running and debugging your AWS Lambda code locally

Integration testing using real test data

The AWS Serverless Application Model CLI

Loading and end-to-end testing at scale

Strategies to reduce the API's latency

Cleaning up

Summary

Securing Your Microservice

Overview of the security in AWS

Overview of AWS Identity and Access Management (IAM)

Securing your serverless microservice

Summary

Summary and Future Work

Book summary

Future work

Other Books You May Enjoy

Leave a review - let other readers know what you think

Customer Reviews

3 (5)

5 star

20%

4 star

20%

3 star

20%

2 star

20%

1 star

20%

Creating and writing to a NoSQL database called DynamoDB using Python

Now that we understand how to create a table, add data, and query DynamoDB using the AWS Console, we will look at how we can do this using only Python code.

We recommend you use a Python Integrated development environment (IDE) such as Eclipse PyDev (http://www.pydev.org/download.html) or PyCharm (https://www.jetbrains.com/pycharm/). You do not need to use an IDE, but I would recommend that you do. If you really want to, you can use VI, for example, on Linux to actually edit your code. But using an IDE allows you, for example, to run debugging or set up unit testing locally and step through it, which makes it easier and more productive for development.

First create the table using Boto3 https://boto3.readthedocs.io/ in Python. Run the code in the following section in PyCharm or your favorite text editor...