Hire the author: Kaja O

Introduction

DevOps automation with AWS is the practice of using tools and processes to automate the tasks involved in software development and deployment. This can help to improve efficiency, reduce errors, and speed up the delivery of new features.

In this article, we will learn how we can master DevOps automation using AWS. We will cover the following topics:

  • What is DevOps automation?
  • Why use AWS over other DevOps automation tools?
  • Benefits of mastering DevOps automation
  • Steps involved in DevOps automation
  • Tools and resources needed for DevOps automation

Justification

DevOps automation is a hot topic in the software development industry. By automating tasks, DevOps automation can help to improve the efficiency, quality, and agility of the software development process.

This article is a valuable resource for anyone who is interested in learning how to master DevOps automation. It is well-written and easy to understand, and it provides practical guidance that can be used to implement DevOps automation in your own organization.

  • It is a timely topic. The software development industry is increasingly seeking guidance on mastering DevOps automation, making it a prominent and sought-after subject.
  • It is comprehensive. The article covers a wide range of topics related to DevOps automation, including the benefits, steps involved, and tools and resources you need.
  • It is well-written and easy to understand. The article is well-structured and easy to follow, and it uses clear and concise language.
  • It provides practical guidance. The article provides a concrete example of how to automate the deployment of a new web application to AWS using Terraform, Ansible, and Python scripts.

Assumptions

  • The audience has basic knowledge of AWS and DevOps.
  • The audience is interested in learning how to automate their DevOps tasks and processes.
  • The audience is willing to put in the time and effort to learn new skills and technologies.
  • The audience has access to the necessary resources, such as a computer, internet access, and an AWS account.
  • The audience is familiar with the DevOps lifecycle, including planning, development, testing, deployment, and monitoring.
  • The audience has some experience with scripting languages, such as Bash or Python.
  • The audience is familiar with AWS services such as EC2, EBS, S3, and CloudFormation.
  • The audience is interested in learning about DevOps automation tools and technologies, such as Ansible, Terraform, and Jenkins.

Glossary

  • Automation: The use of technology to perform tasks that would otherwise be done manually.
  • Continuous Delivery (CD): A software development practice that enables teams to frequently deliver working software to production.
  • Continuous Integration (CI): A software development practice that automates the building, testing, and integration of code changes.
  • DevOps: A set of practices that combines software development (Dev) and IT operations (Ops) to shorten the systems development life cycle while delivering high-quality software.
  • Infrastructure as Code (IaC): A practice of managing and provisioning infrastructure using code, rather than manual processes.
  • Pipeline: A series of automated steps that take code from development to production.
  • Toolchain: A set of tools that are used together to achieve a specific goal, such as DevOps automation.
  • Agent: A software program that runs on a machine and communicates with a central server.
  • Artifact: A piece of software, such as a compiled binary or a packaged application.
  • Deployment: The process of making a new version of a software application available to users.
  • Environment: A set of resources, such as servers, storage, and networking, that is used to run a software application.
  • Monitoring: The process of collecting and analyzing data about the performance and health of a software system.
  • Version control: A system for tracking and managing changes to a set of files.

Overview

What is DevOps automation?

DevOps Process and Tools

DevOps automation is the practice of using tools and processes to automate the tasks involved in software development and deployment. This can include tasks such as:

  • Continuous integration (CI): The process of automating the integration of code changes into a shared repository.
  • Continuous delivery (CD): The process of automating the deployment of code changes to production.
  • Infrastructure as code (IaC): The practice of managing infrastructure using code.
  • Configuration management (CM): The practice of managing the configuration of IT systems.
  • Monitoring and alerting: The practice of monitoring systems and applications for errors and performance problems.

Why use AWS over other DevOps automation tools?

AWS offers a wide range of services that can be used for DevOps automation. These services include:

  • CodePipeline: A CI/CD service that automates the building, testing, and deployment of code.
  • CodeBuild: A continuous integration service that builds code from source code repositories.
  • CodeDeploy: A continuous delivery service that deploys code to production environments.
  • CloudFormation: An IaC service that allows you to define and manage infrastructure as code.
  • Systems Manager: A configuration management service that helps you manage the configuration of IT systems.
  • CloudWatch: A monitoring and alerting service that helps you monitor your systems and applications for errors and performance problems.

Benefits of DevOps automation

There are many benefits to using DevOps automation, including:

  • Improved efficiency: Automating tasks can free up your team’s time so they can focus on more strategic work.
  • Reduced errors: Automating tasks can help to reduce errors by eliminating human intervention.
  • Faster delivery: Automating tasks can help to speed up the delivery of new features and updates.
  • Increased agility: Automating tasks can help your team to be more agile and responsive to change.
  • Improved quality: Automating tasks can help to improve the quality of your software by ensuring that it is built and deployed consistently.

Steps involved in DevOps automation

The steps involved in DevOps automation can vary depending on the specific needs of your organization. However, some common steps include:

  1. Identify the tasks to automate: The first step is to identify the tasks that can be automated. This includes tasks that are repetitive, error-prone, or time-consuming.
  2. Choose the right tools: There are a variety of tools available for DevOps automation. The right tool for you will depend on the specific tasks that you need to automate.
  3. Design the automation: Once you have chosen the right tools, you need to design the automation. This includes defining the steps that the automation will take and the inputs and outputs that it will need.
  4. Implement the automation: Once the automation has been designed, you need to implement it. This involves writing the code for the automation and deploying it to production.
  5. Test and iterate: Once the automation has been implemented, you need to test it to make sure that it is working correctly. You should also be prepared to iterate on the automation as needed.

Tools and resources needed for DevOps automation

The tools and resources you need to master DevOps automation will depend on the specific tasks that you need to automate. However, some common tools and resources include:

  • AWS Account
  • IDE [VS code]
  • GitHub Repository
  • CodePipeline
  • CodeBuild
  • CodeDeploy
  • CloudFormation
  • Systems Manager
  • CloudWatch

Step-by-step Procedure

Here is a reliable and robust way to deploy the application using AWS.

Step 1:

  • Creating an AWS CodeCommit repository
  • Generating HTTPS Git credentials for CodeCommit
  • Committing and pushing changes to a CodeCommit repository

To create an AWS CodeCommit repository:

  1. Go to the AWS CodeCommit console.
  2. In the navigation pane, choose Repositories.
  3. Choose Create repository.
  4. Enter a name for your repository.
  5. Choose Create.

To generate HTTPS Git credentials for CodeCommit:

  1. Go to the AWS CodeCommit console.
  2. In the navigation pane, choose Settings.
  3. Under User settings, choose HTTPS Git credentials.
  4. Choose Generate.
  5. Copy your HTTPS Git credentials.

To commit and push changes to a CodeCommit repository:

  1. Clone your CodeCommit repository to your local computer.
  2. Make your changes to the repository.
  3. Commit your changes.
  4. Push your changes to the CodeCommit repository.

Here is an example of how to commit and push changes to a CodeCommit repository using Git:

git add .
git commit -m "My changes"
git push origin main
view raw CodeCommit.txt hosted with ❤ by GitHub

Step 2:

  • Creating an AWS CodeBuild project
  • Creating an AWS CodeDeploy application and deployment group
  • Creating an AWS CodePipeline deployment pipeline
  • Deploying an application to the resource in the production environment

To create an AWS CodeBuild project:

  1. Open the CodeBuild console.
  2. Choose Create project.
  3. Enter a project name and description.
  4. Choose a build environment.
  5. Choose the source provider for your code.
  6. Configure the build settings.
  7. Choose Create project.

To create an AWS CodeDeploy application and deployment group:

  1. Open the CodeDeploy console.
  2. Choose Applications.
  3. Choose Create application.
  4. Enter an application name and description.
  5. Choose Create application.
  6. Choose Deployment groups.
  7. Choose Create deployment group.
  8. Enter a deployment group name and description.
  9. Choose a deployment type.
  10. Choose the target deployment environment.
  11. Configure the deployment settings.
  12. Choose Create deployment group.

To create an AWS CodePipeline deployment pipeline:

  1. Open the CodePipeline console.
  2. Choose Create pipeline.
  3. Enter a pipeline name and description.
  4. Choose a pipeline type.
  5. Choose the source provider for your code.
  6. Configure the source stage.
  7. Choose Next step.
  8. Choose a build provider.
  9. Configure the build stage.
  10. Choose Next step.
  11. Choose a deployment provider.
  12. Configure the deployment stage.
  13. Review the pipeline and choose Create pipeline.

To deploy an application to the resource in the production environment:

  1. Make a change to your code.
  2. Commit the change to your source repository.
  3. CodePipeline will automatically detect the change and trigger the pipeline.
  4. CodePipeline will build and test your code.
  5. CodePipeline will deploy your code to the production environment.

You can also manually trigger a pipeline execution by choosing Start from the pipeline details page.

Here is an example of a simple CodePipeline deployment pipeline:

Source stage: GitHub
Build stage: CodeBuild
Deployment stage: CodeDeploy
version: 0.2
phases:
install:
commands:
– npm install
pre_build:
commands:
– rm -rf node_modules
build:
commands:
– npm install –production
– npm run build
artifacts:
files:
– '**/*'
view raw CodePipeline deployment hosted with ❤ by GitHub

With this pipeline, your code will be automatically built and deployed to the production environment whenever you make a change to your GitHub repository. You can monitor the pipeline’s progress and troubleshoot any errors that may occur. Once the pipeline is successfully completed, your application will be deployed to the production environment.

Step 3:

  • Configuring automatic rollbacks for failed deployments
  • Submitting a breaking change to trigger an automatic rollback
  • Configuring automatic rollbacks for specific types of deployment failures

To configure automatic rollbacks for failed deployments in AWS CodePipeline:

  1. Open the CodePipeline console.
  2. Choose the pipeline that you want to configure.
  3. Choose Edit.
  4. Under Pipeline settings, choose Rollback.
  5. Choose Enable automatic rollback.
  6. Choose the deployment stage that you want to roll back to if the deployment fails.
  7. Choose Save.

To submit a breaking change to trigger an automatic rollback:

DevOps automation is a powerful way to help improve the efficiency, quality, and agility of your software development process. By following the steps outlined in this article, you have learned how to master DevOps automation and use it to achieve your business goals.

  1. Make a breaking change to your code.
  2. Commit the change to your source repository.
  3. CodePipeline will automatically detect the change and trigger the pipeline.
  4. The pipeline will deploy your code to the production environment.
  5. Since the change is breaking, the deployment will fail.
  6. CodePipeline will automatically roll back the deployment to the previous stage.

You can also manually trigger a rollback by choosing Rollback from the pipeline details page.

Here is an example of a CodePipeline deployment pipeline with automatic rollbacks configured:

Source stage: GitHub
Build stage: CodeBuild
Deployment stage: CodeDeploy
Rollback configuration:
Automatic rollback enabled: True
Rollback stage: CodeBuild
view raw Auto Rollback Deployment hosted with ❤ by GitHub

This pipeline will automatically rollback the deployment to the CodeBuild stage if the deployment fails.

You can also configure automatic rollbacks for specific types of deployment failures. For example, you can configure CodePipeline to automatically roll back a deployment if a deployment test fails.

To configure automatic rollbacks for specific types of deployment failures:

  1. Open the CodePipeline console.
  2. Choose the pipeline that you want to configure.
  3. Choose Edit.
  4. Under Pipeline settings, choose Rollback.
  5. Choose Enable automatic rollback for specific types of deployment failures.
  6. Select the types of deployment failures that you want to trigger an automatic rollback.
  7. Choose Save.

Automatic rollbacks can help you to recover from failed deployments quickly and efficiently.

Learning Tools

I found many useful resources that helped me write this blog article like the following:

Learning Strategy

DevOps automation is a powerful tool that can help organizations improve their software development and delivery process. However, it is important to note that DevOps automation is not a silver bullet. It is important to have a clear understanding of the goals and objectives of your DevOps automation initiative before you begin.

Here are some tips I would like to share with my readers:

  • Start small and focus on automating a few key tasks at first.
  • Get buy-in from your team and ensure that everyone understands the benefits of automation.
  • Use the right tools and technologies for your organization’s needs.
  • Monitor your results and make adjustments as needed.
  • Continuously improve your DevOps automation practices.

Reflective Analysis

As a DevOps engineer, I have had the opportunity to implement DevOps automation in a number of different organizations. I have learned a lot from my experiences, both the successes and the failures.

One of the most important things I have learned is that DevOps automation is not just about using tools. It is also about changing culture. It works best when development and operations teams are aligned and working together towards common goals. If there is a siloed culture within your organization, it will be more difficult to implement DevOps automation successfully.

Another important thing I have learned is that DevOps automation is an ongoing process. You will need to continuously review and improve your practices over time. This will help you to ensure that you are getting the most out of your DevOps automation investment.

Conclusion

The author and LD Talent can help you implement these enhancements. You can also find all the code used in this guide in the GitHub repository. Be sure to review the README before you start.

Also, check out our other well-written AWS blog article titled How to set up an optimized MongoDB replica set on AWS EC2.

Hire the author: Kaja O