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.

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Table of Contents (13 chapters)
Title Page
Title Page
Copyright and Credits
Copyright and Credits
Building Serverless Microservices in Python
About Packt
About Packt
Why subscribe?
Packt.com
Dedication
Dedication
Contributors
Contributors
About the author
Packt is searching for authors like you
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Serverless Microservices Architectures and Patterns
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
2
Creating Your First Serverless Data API
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
3
Deploying Your Serverless Stack
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
4
Testing Your Serverless Microservice
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
5
Securing Your Microservice
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
Summary and Future Work
Book summary
Future work
Other Books You May Enjoy
Other Books You May Enjoy
Leave a review - let other readers know what you think

The AWS Serverless Application Model CLI

In this section, we will walk through different features of SAM Local with fully-working examples. For local testing, you can use Python and bash like I have shown or you can also use the SAM CLI (https://github.com/awslabs/aws-sam-cli), which at the time of writing is still in beta. It uses Docker and is based on open source docker-lambda (https://github.com/lambci/docker-lambda) Docker images. If you are using Windows 10 Home, I recommend you upgrade to Pro or Enterprise as it's harder to get Docker working on the Home edition. There are also some hardware requirements, such as virtualization, to be aware of. We need to perform the following steps:

  1. Install the AWS CLI (https://docs.aws.amazon.com/cli/latest/userguide/installing.html).
  2. Install Docker CE (https://docs.docker.com/install/).
  3. Install the AWS SAM CLI (https://docs...
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