217 lines
10 KiB
Markdown
217 lines
10 KiB
Markdown
---
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stage: Release
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group: Release
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info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/engineering/ux/technical-writing/#assignments
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type: howto
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---
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# Deploy to AWS from GitLab CI/CD **(FREE)**
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GitLab provides Docker images with the libraries and tools you need to deploy
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to AWS. You can reference these images in your CI/CD pipeline.
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If you're using GitLab.com and deploying to the [Amazon Elastic Container Service](https://aws.amazon.com/ecs/) (ECS),
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read about [deploying to ECS](ecs/quick_start_guide.md).
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## Authenticate GitLab with AWS
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To use GitLab CI/CD to connect to AWS, you must authenticate.
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After you set up authentication, you can configure CI/CD to deploy.
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1. Sign on to your AWS account.
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1. Create [an IAM user](https://console.aws.amazon.com/iam/home#/home).
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1. Select your user to access its details. Go to **Security credentials > Create a new access key**.
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1. Note the **Access key ID** and **Secret access key**.
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1. In your GitLab project, go to **Settings > CI/CD**. Set the following
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[CI/CD variables](../variables/index.md):
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| Environment variable name | Value |
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|:-------------------------------|:------------------------|
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| `AWS_ACCESS_KEY_ID` | Your Access key ID. |
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| `AWS_SECRET_ACCESS_KEY` | Your secret access key. |
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| `AWS_DEFAULT_REGION` | Your region code. You might want to confirm that the AWS service you intend to use is [available in the chosen region](https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/). |
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1. Variables are [protected by default](../variables/index.md#protected-cicd-variables).
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To use GitLab CI/CD with branches or tags that are not protected,
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clear the **Protect variable** checkbox.
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## Use an image to run AWS commands
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If an image contains the [AWS Command Line Interface](https://aws.amazon.com/cli/),
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you can reference the image in your project's `.gitlab-ci.yml` file. Then you can run
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`aws` commands in your CI/CD jobs.
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For example:
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```yaml
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deploy:
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stage: deploy
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image: registry.gitlab.com/gitlab-org/cloud-deploy/aws-base:latest
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script:
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- aws s3 ...
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- aws create-deployment ...
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```
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GitLab provides a Docker image that includes the AWS CLI:
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- Images are hosted in the GitLab Container Registry. The latest image is
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`registry.gitlab.com/gitlab-org/cloud-deploy/aws-base:latest`.
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- [Images are stored in a GitLab repository](https://gitlab.com/gitlab-org/cloud-deploy/-/tree/master/aws).
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Alternately, you can use an [Amazon Elastic Container Registry (ECR)](https://aws.amazon.com/ecr/) image.
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[Learn how to push an image to your ECR repository](https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-push-ecr-image.html).
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You can also use an image from any third-party registry.
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## Deploy your application to ECS
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> - [Introduced](https://gitlab.com/gitlab-org/gitlab/-/issues/207962) in GitLab 12.9.
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> - The `Deploy-ECS.gitlab-ci.yml` template was [moved](https://gitlab.com/gitlab-org/gitlab/-/issues/220821) to `AWS/Deploy-ECS.gitlab-ci.yml` in GitLab 13.2.
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You can automate deployments of your application to your [Amazon ECS](https://aws.amazon.com/ecs/)
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cluster.
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Prerequisites:
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- [Authenticate AWS with GitLab](#authenticate-gitlab-with-aws).
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- Create a cluster on Amazon ECS.
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- Create related components, like an ECS service, a database on Amazon RDS, and so on.
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- Create an ECS task definition, where the value for the `containerDefinitions[].name` attribute is
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the same as the `Container name` defined in your targeted ECS service. The task definition can be:
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- An existing task definition in ECS.
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- [In GitLab 13.3 and later](https://gitlab.com/gitlab-org/gitlab/-/issues/222618),
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a JSON file in your GitLab project. Use the
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[template in the AWS documentation](https://docs.aws.amazon.com/AmazonECS/latest/developerguide/create-task-definition.html#task-definition-template)
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and save the file in your project. For example `<project-root>/ci/aws/task-definition.json`.
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To deploy to your ECS cluster:
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1. In your GitLab project, go to **Settings > CI/CD**. Set the following
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[CI/CD variables](../variables/index.md). You can find these names by
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selecting the targeted cluster on your [Amazon ECS dashboard](https://console.aws.amazon.com/ecs/home).
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| Environment variable name | Value |
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|:-------------------------------|:------------------------|
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| `CI_AWS_ECS_CLUSTER` | The name of the AWS ECS cluster that you're targeting for your deployments. |
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| `CI_AWS_ECS_SERVICE` | The name of the targeted service tied to your AWS ECS cluster. |
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| `CI_AWS_ECS_TASK_DEFINITION` | If the task definition is in ECS, the name of the task definition tied to the service. |
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| `CI_AWS_ECS_TASK_DEFINITION_FILE` | If the task definition is a JSON file in GitLab, the filename, including the path. For example, `ci/aws/my_task_definition.json`. If the name of the task definition in your JSON file is the same name as an existing task definition in ECS, then a new revision is created when CI/CD runs. Otherwise, a brand new task definition is created, starting at revision 1. |
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WARNING:
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If you define both `CI_AWS_ECS_TASK_DEFINITION_FILE` and `CI_AWS_ECS_TASK_DEFINITION`,
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`CI_AWS_ECS_TASK_DEFINITION_FILE` takes precedence.
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1. Include this template in `.gitlab-ci.yml`:
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```yaml
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include:
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- template: AWS/Deploy-ECS.gitlab-ci.yml
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```
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The `AWS/Deploy-ECS` template ships with GitLab and is available
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[on GitLab.com](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/ci/templates/AWS/Deploy-ECS.gitlab-ci.yml).
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1. Commit and push your updated `.gitlab-ci.yml` to your project's repository.
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Your application Docker image is rebuilt and pushed to the GitLab Container Registry.
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If your image is located in a private registry, make sure your task definition is
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[configured with a `repositoryCredentials` attribute](https://docs.aws.amazon.com/AmazonECS/latest/developerguide/private-auth.html).
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The targeted task definition is updated with the location of the new
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Docker image, and a new revision is created in ECS as result.
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Finally, your AWS ECS service is updated with the new revision of the
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task definition, making the cluster pull the newest version of your
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application.
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NOTE:
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ECS deploy jobs wait for the rollout to complete before exiting. To disable this behavior,
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set `CI_AWS_ECS_WAIT_FOR_ROLLOUT_COMPLETE_DISABLED` to a non-empty value.
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WARNING:
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The [`AWS/Deploy-ECS.gitlab-ci.yml`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/ci/templates/AWS/Deploy-ECS.gitlab-ci.yml)
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template includes two templates: [`Jobs/Build.gitlab-ci.yml`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/ci/templates/Jobs/Build.gitlab-ci.yml)
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and [`Jobs/Deploy/ECS.gitlab-ci.yml`](https://gitlab.com/gitlab-org/gitlab/-/blob/master/lib/gitlab/ci/templates/Jobs/Deploy/ECS.gitlab-ci.yml). Do not include these templates on their own. Only include the
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`AWS/Deploy-ECS.gitlab-ci.yml` template. These other templates are designed to be
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used only with the main template. They may move or change unexpectedly. Also, the job names within
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these templates may change. Do not override these job names in your own pipeline,
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because the override stops working when the name changes.
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## Deploy your application to EC2
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> [Introduced](https://gitlab.com/gitlab-org/gitlab/-/issues/201742) in GitLab 13.5.
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GitLab provides a template, called `AWS/CF-Provision-and-Deploy-EC2`,
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to assist you in deploying to Amazon EC2.
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When you configure related JSON objects and use the template, the pipeline:
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1. **Creates the stack**: Your infrastructure is provisioned by using
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the [AWS CloudFormation](https://aws.amazon.com/cloudformation/) API.
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1. **Pushes to an S3 bucket**: When your build runs, it creates an artifact.
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The artifact is pushed to an [AWS S3](https://aws.amazon.com/s3/) bucket.
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1. **Deploys to EC2**: The content is deployed on an [AWS EC2](https://aws.amazon.com/ec2/) instance.
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### Configure the template and JSON
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To deploy to EC2, complete the following steps.
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1. Create JSON for your stack. Use the [AWS template](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/template-anatomy.html).
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1. Create JSON to push to S3. Include the following details.
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```json
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{
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"applicationName": "string",
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"source": "string",
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"s3Location": "s3://your/bucket/project_built_file...]"
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}
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```
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The `source` is the location where a `build` job built your application.
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The build is saved to [`artifacts:paths`](../yaml/index.md#artifactspaths).
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1. Create JSON to deploy to EC2. Use the [AWS template](https://docs.aws.amazon.com/codedeploy/latest/APIReference/API_CreateDeployment.html).
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1. Make the JSON objects accessible to your pipeline:
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- If you want these JSON objects saved in your repository, save the objects as three
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separate files.
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In your `.gitlab-ci.yml` file, add [CI/CD variables](../variables/index.md)
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that point to the file paths relative to the project root. For example,
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if your JSON files are in a `<project_root>/aws` folder:
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```yaml
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variables:
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CI_AWS_CF_CREATE_STACK_FILE: 'aws/cf_create_stack.json'
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CI_AWS_S3_PUSH_FILE: 'aws/s3_push.json'
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CI_AWS_EC2_DEPLOYMENT_FILE: 'aws/create_deployment.json'
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```
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- If you do not want these JSON objects saved in your repository, add each object
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as a separate [file type CI/CD variable](../variables/index.md#cicd-variable-types)
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in the project settings. Use the same variable names as above.
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1. In your `.gitlab-ci.yml` file, create a CI/CD variable for the name of the stack. For example:
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```yaml
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variables:
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CI_AWS_CF_STACK_NAME: 'YourStackName'
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```
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1. In your `.gitlab-ci.yml` file, add the CI template:
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```yaml
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include:
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- template: AWS/CF-Provision-and-Deploy-EC2.gitlab-ci.yml
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```
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1. Run the pipeline.
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- Your AWS CloudFormation stack is created based on the content of your
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`CI_AWS_CF_CREATE_STACK_FILE` variable.
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If your stack already exists, this step is skipped, but the `provision`
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job it belongs to still runs.
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- Your built application is pushed to your S3 bucket then and deployed to your EC2 instance, based
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on the related JSON object's content. The deployment job finishes when the deployment to EC2
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is done or has failed.
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