Book Image

Building and Delivering Microservices on AWS

By : Amar Deep Singh
4 (1)
Book Image

Building and Delivering Microservices on AWS

4 (1)
By: Amar Deep Singh

Overview of this book

Reliable automation is crucial for any code change going into production. A release pipeline enables you to deliver features for your users efficiently and promptly. AWS CodePipeline, with its powerful integration and automation capabilities of building, testing, and deployment, offers a unique solution to common software delivery issues such as outages during deployment, a lack of standard delivery mechanisms, and challenges faced in creating sustainable pipelines. You’ll begin by developing a Java microservice and using AWS services such as CodeCommit, CodeArtifact, and CodeGuru to manage and review the source code. You’ll then learn to use the AWS CodeBuild service to build code and deploy it to AWS infrastructure and container services using the CodeDeploy service. As you advance, you’ll find out how to provision cloud infrastructure using CloudFormation templates and Terraform. The concluding chapters will show you how to combine all these AWS services to create a reliable and automated CodePipeline for delivering microservices from source code check-in to deployment without any downtime. Finally, you’ll discover how to integrate AWS CodePipeline with third-party services such as Bitbucket, Blazemeter, Snyk, and Jenkins. By the end of this microservices book, you’ll have gained the hands-on skills to build release pipelines for your applications.
Table of Contents (21 chapters)
1
Part 1: Pre-Plan the Pipeline
6
Part 2: Build the Pipeline
11
Part 3: Deploying the Pipeline

Summary

In this chapter, we learned about GitHub and Bitbucket repositories and how we can connect CodePipeline to them. We expanded our CodePipeline beyond AWS infrastructure and connected a pipeline to a Jenkins server, used the CodeDeploy server to deploy our sample application to an offering, and learned details about the Lambda functions, as well as its limitations and benefits. We deployed our Lambda function manually and then created a pipeline to deploy the changes to a function. In the next chapter, we will learn more about CodePipeline and take our knowledge beyond the AWS infrastructure, integrating with other tools and deploying code to on-prem systems using CodePipeline.