# AWS CodeDeploy

Cloud service · AWS. Updated 2026-10-29. Page: https://blowstack.com/tools/cloud-services-hub/aws-codedeploy

> AWS CodeDeploy is a fully managed deployment service that automates software deployments to a variety of compute services such as Amazon EC2, AWS Fargate, AWS Lambda, and your on-premises servers.

Practice exams covering AWS CodeDeploy: [SOA-C03 AWS Certified CloudOps Engineer - Associate](https://blowstack.com/practice-exams/aws-certified-cloudops-engineer-associate), [DEA-C01 AWS Certified Data Engineer - Associate](https://blowstack.com/practice-exams/aws-certified-data-engineer-associate), [DVA-C02 AWS Certified Developer - Associate](https://blowstack.com/practice-exams/aws-certified-developer-associate), [DOP-C02 AWS Certified DevOps Engineer - Professional](https://blowstack.com/practice-exams/aws-certified-devops-engineer-professional), [AIP-C01 AWS Certified Generative AI Developer - Professional](https://blowstack.com/practice-exams/aws-certified-generative-ai-developer-professional), [MLA-C02 (beta) AWS Certified Machine Learning Engineer - Associate](https://blowstack.com/practice-exams/aws-certified-machine-learning-engineer-associate), [SAP-C02 AWS Certified Solutions Architect - Professional](https://blowstack.com/practice-exams/aws-certified-solutions-architect-professional).

## 5 key features of AWS CodeDeploy

AWS CodeDeploy is a fully managed deployment service that automates software deployments to various compute services such as Amazon EC2 and on-premises servers, offering features like automated rollbacks, centralized control, scalability, and customizable deployment configurations.

1. **Automated Deployments**: AWS CodeDeploy automates code deployments to any instance, including Amazon EC2 instances and on-premises servers, allowing you to rapidly release new features.
2. **Centralized Control**: Manage and configure your deployments from a central location, giving you the ability to track the progress of your deployments across your application.
3. **Scalability**: Designed to scale with your deployment needs, AWS CodeDeploy can handle deployments to a single instance or thousands of instances across the globe.
4. **Rollbacks**: In case of deployment issues, AWS CodeDeploy supports automatic or manual rollbacks to quickly revert to a previous stable version of your application.
5. **Deployment Configurations**: Customize your deployment strategies with deployment configurations, including canary, linear, and all-at-once deployments, to meet specific business, regulatory, or technical requirements.

## Where AWS CodeDeploy is used

AWS CodeDeploy use cases revolve around automating deployment processes across various environments including EC2, Lambda, and on-premises servers, supporting strategies like high-availability, blue/green deployments, and integration with CI/CD pipelines for both traditional and serverless applications.

1. **Automated Deployment to AWS EC2 Instances**: AWS CodeDeploy automates code deployments to any number of EC2 instances, simplifying the process of releasing new features and ensuring that the application deployment process is repeatable and scalable. This use case involves automatically deploying application updates across a fleet of EC2 instances without downtime, ensuring a consistent and reliable deployment process.
2. **High-Availability Deployments**: Leverage AWS CodeDeploy to update applications deployed across availability zones while minimizing downtime. Deployments operate within a single AWS Region; multi-Region rollouts require defining the application in each target Region, copying the application bundle to an S3 bucket in each Region, and starting deployments serially or in parallel.
3. **Blue/Green Deployments**: AWS CodeDeploy supports blue/green deployment methodologies, allowing developers to release new versions of applications alongside the old version and seamlessly switch traffic. This can drastically reduce downtime and the risk associated with deploying new versions, providing an efficient method for quickly rolling back if issues arise.
4. **Integration with Continuous Integration/Continuous Deployment Pipelines**: CodeDeploy can be integrated into CI/CD pipelines to automate the deployment phase in the software development lifecycle. This deployment can trigger automatically after a successful build/test phase, ensuring that the software is continuously delivered to production environments or staging with minimal human intervention.
5. **Serverless Deployments**: AWS CodeDeploy now also supports deployments to AWS Lambda. This allows developers to automatically shift traffic between already-published Lambda function versions, enabling serverless applications to be updated with new code or configurations without managing servers.

## How AWS CodeDeploy is priced

AWS CodeDeploy pricing is based on the Pay-As-You-Go model for the AWS resources used, and there is a Free Tier available for new accounts.

- **Pay-As-You-Go**: There is no additional CodeDeploy charge for deployments to Amazon EC2, AWS Lambda, or Amazon ECS. Users still pay for other AWS resources used to store and run their applications.
- **Free Tier**: AWS offers a Free Tier for new accounts, which includes 750 hours per month of EC2 micro instances and 1 GB of outbound data transfer for one year, which can be applied to the resources used by CodeDeploy.
- **On-Premises Instance Updates**: CodeDeploy charges $0.02 per on-premises instance update.

## Services AWS CodeDeploy works with

- **[Amazon S3](https://blowstack.com/tools/cloud-services-hub/amazon-s3)**: CodeDeploy can fetch applications, deployment scripts, and resources stored in S3 buckets.
- **[AWS Lambda](https://blowstack.com/tools/cloud-services-hub/aws-lambda)**: CodeDeploy supports updating Lambda function versions and has the ability to shift traffic to new versions gradually.
- **[Amazon EC2](https://blowstack.com/tools/cloud-services-hub/amazon-ec2)**: CodeDeploy deploys applications to EC2 instances with support for both in-place and blue/green deployment methods.
- **[AWS Elastic Beanstalk](https://blowstack.com/tools/cloud-services-hub/aws-elastic-beanstalk)**: CodeDeploy can be used as an alternative deployment mechanism for applications running on Elastic Beanstalk.

## What is AWS CodeDeploy

AWS CodeDeploy is a fully managed deployment service provided by Amazon Web Services (AWS) that automates the deployment of software applications to various computing services such as Amazon EC2, AWS Fargate, AWS Lambda, and your on-premises servers. This service simplifies the process of rapidly releasing new features, helps avoid downtime during application deployment, and handles the complexity of updating your applications, allowing you to rapidly release new features.

The essence of AWS CodeDeploy lies in its capability to automate the entire deployment process. Before the advent of continuous integration and continuous deployment (CI/CD) pipelines, deploying applications could be a cumbersome and error-prone process, often requiring manual steps that could lead to inconsistent configurations or deployment failures.

CodeDeploy eliminates this friction by automating deployments, making them repeatable, predictable, and scalable. CodeDeploy works by leveraging application specifications defined in either AWS CloudFormation templates or AppSpec files, a YAML or JSON configuration file used to manage the deployment. This file specifies the deployment actions you want AWS CodeDeploy to execute. For example, it can specify the scripts to be run at various stages of the deployment process, such as installation, application stop, application start, and validation checks. This flexibility allows developers to customize their deployment processes to their specific needs, whether they are deploying to Lambda, which involves updating function code, or to EC2/Fargate where applications are typically deployed to a fleet of instances.

One of the key benefits of using AWS CodeDeploy is the ability to maintain application availability during the deployment process. CodeDeploy offers several deployment strategies, including in-place and blue/green deployments. In-place deployments, also called rolling updates, replace the current version of the application on each host with the latest version, with deployment concurrency controlled by the deployment configuration rather than always updating one host at a time, which can be useful for applications that can tolerate brief downtime. Blue/green deployments, on the other hand, redirect traffic from the current version of the application to a completely separate set of instances running the new version, which can drastically reduce downtime and risk by allowing a quick rollback if needed.

Furthermore, AWS CodeDeploy integrates seamlessly with other AWS services and third-party tools, enhancing its utility in CI/CD pipelines. For instance, developers can integrate CodeDeploy with AWS CodePipeline to automate the entire software release process, from code commit through build, test, and deployment.

Additionally, AWS CloudWatch can be used for monitoring deployments and alerting on failures, while AWS Identity and Access Management (IAM) ensures that deployments are secure and only authorized personnel can execute deployments.

In conclusion, AWS CodeDeploy represents an essential service for developers and businesses looking to streamline their deployment processes. By automating deployments, ensuring high availability, and providing flexible deployment strategies, CodeDeploy facilitates a more reliable, scalable, and efficient software deployment process, enabling teams to focus more on development and less on the logistics of releasing new updates.

## Concepts related to AWS CodeDeploy

- [Acceptance Testing](https://blowstack.com/tools/cloud-concepts-hub/acceptance-testing): Acceptance testing verifies that a system satisfies agreed acceptance criteria and is suitable for its intended business use.
- [Agile Development](https://blowstack.com/tools/cloud-concepts-hub/agile-development): Agile development is an iterative, incremental approach to software delivery that adapts plans through frequent feedback, collaboration, and working software.
- [All-at-Once Deployment](https://blowstack.com/tools/cloud-concepts-hub/all-at-once-deployment): All-at-once deployment releases a new application version to the entire targeted environment in a single deployment batch rather than through staged updates.
- [Blue-Green Deployment](https://blowstack.com/tools/cloud-concepts-hub/blue-green-deployment): Blue-green deployment releases a new application version into a separate environment and then redirects production traffic from the current environment to the new one.
- [Blue-Green Deployments](https://blowstack.com/tools/cloud-concepts-hub/blue-green-deployments): Blue-green deployments release application changes by preparing a separate production-ready environment and switching traffic from the current environment to the new one.
- [Canary Deployment](https://blowstack.com/tools/cloud-concepts-hub/canary-deployment): Canary deployment releases a new application or model version to a small portion of production traffic before expanding exposure after validation.
- [Canary Testing](https://blowstack.com/tools/cloud-concepts-hub/canary-testing): Canary testing validates a candidate configuration by exposing it to a small share of production traffic before deciding whether to expand or reverse the rollout.
- [CI/CD](https://blowstack.com/tools/cloud-concepts-hub/cicd): CI/CD is a software engineering approach that continuously integrates code changes and automates their validation and delivery or deployment.
- [Deployment Rollback](https://blowstack.com/tools/cloud-concepts-hub/deployment-rollback): Deployment rollback restores a previously validated application, infrastructure, or model release when a new deployment fails or causes unacceptable behavior.
- [Error Budgets](https://blowstack.com/tools/cloud-concepts-hub/error-budgets): Error budgets quantify the amount of unreliability a service can tolerate within a defined period while still meeting its service-level objective.
- [Exit Codes](https://blowstack.com/tools/cloud-concepts-hub/exit-codes): Exit codes are numeric status values that processes return when they terminate so calling systems can determine whether an operation succeeded or failed.
- [Fail-Fast](https://blowstack.com/tools/cloud-concepts-hub/fail-fast): Fail-Fast is the practice of detecting invalid conditions early, reporting failure explicitly, and stopping work that cannot safely succeed.
- [Gitflow](https://blowstack.com/tools/cloud-concepts-hub/gitflow): Gitflow is a Git branching workflow that separates ongoing development, release preparation, and production fixes using branches with defined roles.
- [Health Checks](https://blowstack.com/tools/cloud-concepts-hub/health-checks): Health checks are automated tests that determine whether a component is functioning and suitable for receiving work.
- [Quality Gates](https://blowstack.com/tools/cloud-concepts-hub/quality-gates): Quality gates are explicit pass-or-fail checkpoints that use evidence to determine whether a change can advance through a delivery workflow.
- [Rollback](https://blowstack.com/tools/cloud-concepts-hub/rollback): Rollback is the reversal of a change to return a system to a previously known-good operational state.
- [Rolling Deployment](https://blowstack.com/tools/cloud-concepts-hub/rolling-deployment): Rolling deployment updates an application in successive batches while keeping part of the existing deployment available to serve traffic.
- [Test Pyramid](https://blowstack.com/tools/cloud-concepts-hub/test-pyramid): The Test Pyramid is a testing strategy that favors many fast, focused tests, fewer integration tests, and a small set of broad end-to-end tests.
- [Trunk-Based Development](https://blowstack.com/tools/cloud-concepts-hub/trunk-based-development): Trunk-Based Development is a version-control strategy in which developers integrate small changes frequently into a single shared main branch, using direct commits or short-lived branches.
- [Waterfall Model](https://blowstack.com/tools/cloud-concepts-hub/waterfall-model): The Waterfall Model is a software development lifecycle approach that organizes work into sequential phases, typically completing and approving each phase before the next begins.