AWS CodeDeploy Best Practices

AWS CodeDeploy is a powerful deployment service that automates application deployments to various compute services including Amazon EC2, AWS Fargate, AWS Lambda, and on-premises servers. As organizations continue to migrate applications to the cloud and optimize their development pipelines, understanding the nuances of effective deployment becomes crucial. In this post, we will delve deep into best practices that ensure smooth, efficient, and error-free deployments with AWS CodeDeploy.

Why are Best Practices Important?

Following best practices is not just about ensuring that the deployment goes through without hitches. It’s about optimizing costs, enhancing security, achieving faster deployment times, and ensuring that in the case of failures, there’s a clear strategy to handle them.


Before diving into the best practices, it’s essential to ensure you have the necessary groundwork in place.

  • Setting up an AWS account: If you don’t have an AWS account, sign up for one here. Ensure that you have the necessary permissions to access and manage AWS CodeDeploy and related services.
  • Familiarity with AWS services: While this guide will cover the basics of CodeDeploy, having a foundational understanding of AWS services, particularly EC2, IAM, and S3, can be beneficial.
  • Basic Deployment Concepts: Familiarize yourself with basic deployment concepts like rolling deployments, blue-green deployments, and deployment configurations.

Understanding AWS CodeDeploy

Before diving into the best practices, it’s crucial to have a clear understanding of what AWS CodeDeploy is and its key components.

  • Basic Concepts and Components:
    • Deployment Groups: This defines a set of EC2 instances or Lambda functions to which a new revision of software will be deployed.
    • AppSpec Files: A YAML or JSON formatted file used to define the deployment actions AWS CodeDeploy should execute.
    • Lifecycle Events: AWS CodeDeploy will trigger specific scripts or actions at different phases of the deployment lifecycle, such as application start or application stop.
  • Key Benefits of Using CodeDeploy:
    • Automated Deployments: CodeDeploy automates the process, reducing the chances of manual errors and speeding up the deployment process.
    • Integrated with AWS Ecosystem: Seamlessly integrates with other AWS services for monitoring, logging, load balancing, and more.
    • Flexibility: Whether you’re deploying to a fleet of EC2 instances, Lambda functions, or an on-premises server, CodeDeploy has you covered.

By understanding these core components and benefits, you will be better prepared to harness the full potential of AWS CodeDeploy and implement the best practices discussed in this guide.

Setting Up Your Environment

Before delving into the deployment strategies and configurations, it’s vital to ensure your AWS environment is correctly set up for CodeDeploy.

  • IAM roles and permissions:
    • Ensure that CodeDeploy has the necessary permissions to access other AWS services. For instance, if deploying to EC2 instances, CodeDeploy needs permissions to make EC2 and Auto Scaling calls.
    • Define service roles that allow AWS CodeDeploy to act on your behalf.
  • EC2 instance configurations and tags:
    • Tag your EC2 instances. AWS CodeDeploy uses these tags to identify and group instances.
    • Ensure that the CodeDeploy Agent is running on your EC2 instances. This agent is responsible for coordinating the deployment tasks.
  • VPC and Security Group considerations:
    • Ensure your security groups allow outbound connections so the instances can reach the CodeDeploy service endpoint.
    • If deploying within a VPC, ensure the necessary connections between subnets, especially if the VPC architecture separates resources across different subnets.

Deployment Strategies

One of the significant advantages of AWS CodeDeploy is its flexibility in supporting various deployment strategies. Choosing the right one is crucial based on your application’s needs and the level of risk you’re willing to assume during deployment.

  • All-at-once deployment:
    • Deploys the application revision to all instances simultaneously. It’s the fastest method but poses the most risk as all instances are updated simultaneously.
  • Rolling deployments:
    • Deploys the new revision in stages. At each stage, a predefined number of instances are taken out of service, updated, and then returned to service. It strikes a balance between speed and risk.
  • Canary deployments:
    • A small percentage of instances are updated first. Once confident in the update’s success, the remaining instances are then upgraded. This is a safer approach, allowing for testing a change with a smaller subset of users.
  • Blue-green deployments:
    • The deployment environment is duplicated (creating a “blue” and “green” environment). The new revision is deployed to the green environment, and once testing is complete, traffic is redirected to the green environment, making it the new production environment.

Deployment Configurations

Once you’ve chosen a deployment strategy, the next step is to define the deployment configuration which determines how the traffic is routed to instances during the deployment.

  • Customizing deployment configurations:
    • While AWS CodeDeploy provides predefined configurations, you can define custom configurations based on your needs.
  • Failures and rollbacks:
    • It’s essential to define failure thresholds. For instance, if you have ten instances and set a threshold of 2, the deployment will stop after two failures.
    • Understand and configure automatic rollbacks to revert to the previous application version if the deployment doesn’t meet the success criteria.

Understanding Application Revisions in AWS CodeDeploy

The AWS CodeDeploy agent uses this max_revisions setting to determine how many application revisions to keep in its deployment-root folder. The agent automatically deletes the oldest revisions once the specified limit is reached. This ensures that the agent doesn’t excessively use disk space over time as more and more deployments are executed.

To modify the max_revisions setting:

  1. Access the CodeDeploy agent’s configuration file: The location of this file depends on your operating system:
    • On Amazon Linux, RHEL, and Ubuntu Server: /etc/codedeploy-agent/conf/codedeployagent.yml
    • On Windows Server: C:\ProgramData\Amazon\CodeDeploy\conf\codedeployagent.yml
  2. Edit the max_revisions setting: Open the configuration file in a text editor. Look for the :max_revisions: setting (or add it if it’s not there) and set your desired value. For example:
:max_revisions: 5

This would mean the agent will retain the five most recent application revisions in the deployment-root folder and delete older ones.

Restart the CodeDeploy agent
Once you’ve made your changes, save the file and restart the CodeDeploy agent for the changes to take effect.

On Linux-based systems:

sudo service codedeploy-agent restart

On Windows Server, you’d restart the CodeDeploy Agent service via the Service Management Console or with PowerShell.
This configuration change will ensure that old application revisions are purged regularly, helping to manage the disk space used by the CodeDeploy agent on your instances.

AppSpec File Best Practices

The AppSpec (Application Specification) file is a crucial part of AWS CodeDeploy. It provides instructions for deploying and managing each revision of the application.

  • Script Lifecycle Event Hooks:
    • AWS CodeDeploy uses scripts associated with lifecycle event hooks to manage the deployment. For instance, scripts can be tied to BeforeInstall, AfterInstall, etc.
    • Ensure that scripts are idempotent: If a script runs multiple times, it should have the same result.
  • Specifying Files and Directories:
    • Clearly define which files and directories should be copied from the revision to the target location.
    • Use wildcards with caution, ensuring you don’t inadvertently deploy unwanted files.
  • Managing Permissions:
    • Define the permissions for each file to ensure application security. Avoid overly permissive settings.

Load Balancing

For applications with high availability requirements, integrating CodeDeploy with a load balancer is often necessary. This ensures minimal downtime and a seamless user experience during deployments.

  • Integrating with AWS Elastic Load Balancing (ELB):
    • AWS CodeDeploy can automatically deregister instances from ELB, deploy the application revision, and then re-register them.
    • Ensure health checks are correctly configured so that only healthy instances are serving traffic.
  • Handling Traffic During Deployments:
    • When using strategies like Blue-Green deployment, understand how traffic is routed between environments.
    • Ensure that session stickiness, if used, doesn’t disrupt user experiences during deployment.

Monitoring and Logging

A successful deployment doesn’t end with pushing a revision. It’s crucial to monitor the application and be alert to any issues that arise.

  • Integrating with AWS CloudWatch:
    • Set up CloudWatch alarms and metrics to monitor the health and performance of your deployments.
    • Monitor the CodeDeploy agent’s health on EC2 instances.
  • Analyzing Deployment Logs:
    • AWS CodeDeploy logs deployment details, which can be invaluable when troubleshooting issues. These logs can be sent to Amazon CloudWatch Logs or S3 for analysis.
  • Setting up Alerts and Notifications:
    • Integrate with Amazon SNS to receive notifications about deployment progress or failures.
    • React promptly to any alerts to ensure application uptime and health.

FAQ (Frequently Asked Questions)

  1. What is the difference between AWS CodeDeploy and AWS CodePipeline?
    • AWS CodeDeploy focuses on the deployment of applications, while AWS CodePipeline is a continuous integration and continuous delivery (CI/CD) service that automates the build, test, and deployment phases.
  2. Can I use AWS CodeDeploy with non-AWS environments?
    • Yes, AWS CodeDeploy supports on-premises instances, allowing you to deploy applications outside of the AWS cloud.
  3. How am I billed for using AWS CodeDeploy?
    • With CodeDeploy, you pay only for what you use. There are no upfront fees or long-term commitments. Typically, you’re billed based on the number of deployment operations.
  4. Is AWS CodeDeploy suitable for small applications or projects?
    • Absolutely! CodeDeploy scales according to your needs, making it suitable for both small projects and large enterprise applications.
  5. Do I need to change my existing code to use AWS CodeDeploy?
    • No, CodeDeploy deploys your application code as-is. However, you’ll need to provide an AppSpec file to instruct CodeDeploy on how to handle your deployment.
  6. How does AWS CodeDeploy ensure zero downtime during deployments?
    • By integrating with load balancers and using deployment strategies like Blue-Green deployments, CodeDeploy can ensure that there’s always a version of your application available to users.


AWS CodeDeploy is an incredibly powerful and flexible service that automates the application deployment process, ensuring that your applications are delivered efficiently, consistently, and reliably. By understanding its intricacies and following best practices, you can harness its full potential and ensure smooth deployments regardless of the scale and complexity of your projects.

Whether you’re just starting out with AWS CodeDeploy or looking to optimize an existing setup, we hope this guide has provided valuable insights and actionable tips. Remember, the cloud landscape is ever-evolving, so it’s always a good idea to keep abreast of AWS updates and continuously refine your deployment practices.

Thank you for joining us on this deep dive into AWS CodeDeploy best practices. We wish you successful and seamless deployments in all your future endeavors!

Atiqur Rahman

I am MD. Atiqur Rahman graduated from BUET and is an AWS-certified solutions architect. I have successfully achieved 6 certifications from AWS including Cloud Practitioner, Solutions Architect, SysOps Administrator, and Developer Associate. I have more than 8 years of working experience as a DevOps engineer designing complex SAAS applications.

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