Create a pipeline, stages, and actions

Step 1: Create and name your pipeline

1. Sign in to the AWS Management Console and open the CodePipeline console at http://console.aws.amazon.com/codesuite/codepipeline/home.

2. On the Welcome page, choose Create pipeline.

   If this is your first time using CodePipeline, choose Get Started.

3. On the Step 1: Choose creation option page, under Creation options, choose the Build custom pipeline option. Choose Next.

4. On the Step 2: Choose pipeline settings page, in Pipeline name, enter the name for your pipeline.

   In a single AWS account, each pipeline you create in an AWS Region must have a unique name. Names can be reused for pipelines in different Regions.

   Note

   After you create a pipeline, you cannot change its name. For information about other limitations, see Quotas in AWS CodePipeline.

5. In Pipeline type, choose one of the following options. Pipeline types differ in characteristics and price. For more information, see Pipeline types.

   • V1 type pipelines have a JSON structure that contains standard pipeline, stage, and action-level parameters.

   • V2 type pipelines have the same structure as a V1 type, along with additional parameter support, such as triggers on Git tags and pipeline-level variables.

6. In Service role, do one of the following:

   • Choose New service role to allow CodePipeline to create a new service role in IAM.

   • Choose Existing service role to use a service role already created in IAM. In Role ARN, choose your service role ARN from the list.

   Note

   Depending on when your service role was created, you might need to update its permissions to support additional AWS services. For information, see Add permissions to the CodePipeline service role.

   For more information about the service role and its policy statement, see Manage the CodePipeline service role.

7. (Optional) Under Variables, choose Add variable to add variables at the pipeline level.

   For more information about variables at the pipeline level, see Variables reference. For a tutorial with a pipeline-level variable that is passed at the time of the pipeline execution, see Tutorial: Use pipeline-level variables.

   Note

   While it is optional to add variables at the pipeline level, for a pipeline specified with variables at the pipeline level where no values are provided, the pipeline execution will fail.

8. (Optional) Expand Advanced settings.

9. In Artifact store, do one of the following:

   1. Choose Default location to use the default artifact store, such as the S3 artifact bucket designated as the default, for your pipeline in the AWS Region you have selected for your pipeline.

   2. Choose Custom location if you already have an artifact store, such as an S3 artifact bucket, in the same Region as your pipeline. In Bucket, choose the bucket name.

   Note

   This is not the source bucket for your source code. This is the artifact store for your pipeline. A separate artifact store, such as an S3 bucket, is required for each pipeline. When you create or edit a pipeline, you must have an artifact bucket in the pipeline Region and one artifact bucket per AWS Region where you are running an action.

   For more information, see Input and output artifacts and CodePipeline pipeline structure reference.

10. In Encryption key, do one of the following:

    1. To use the CodePipeline default AWS KMS key to encrypt the data in the pipeline artifact store (S3 bucket), choose Default AWS Managed Key.

    2. To use your customer managed key to encrypt the data in the pipeline artifact store (S3 bucket), choose Customer Managed Key. Choose the key ID, key ARN, or alias ARN.

11. Choose Next.

Step 2: Create a source stage

1. On the Step 3: Add source stage page, in Source provider, choose the type of repository where your source code is stored, specify its required options. The additional fields display depending on the source provider selected as follows.

   • For Bitbucket Cloud, GitHub (via GitHub App), GitHub Enterprise Server, GitLab.com, or GitLab self-managed:

     1. Under Connection, choose an existing connection or create a new one. To create or manage a connection for your GitHub source action, see GitHub connections.

     2. Choose the repository you want to use as the source location for your pipeline.

        Choose to add a trigger or filter on trigger types to start your pipeline. For more information about working with triggers, see Add trigger with code push or pull request event types. For more information about filtering with glob patterns, see Working with glob patterns in syntax.

     3. In Output artifact format, choose the format for your artifacts.

        • To store output artifacts from the GitHub action using the default method, choose CodePipeline default. The action accesses the files from the GitHub repository and stores the artifacts in a ZIP file in the pipeline artifact store.

        • To store a JSON file that contains a URL reference to the repository so that downstream actions can perform Git commands directly, choose Full clone. This option can only be used by CodeBuild downstream actions.

          If you choose this option, you will need to update the permissions for your CodeBuild project service role as shown in Troubleshooting CodePipeline. For a tutorial that shows you how to use the Full clone option, see Tutorial: Use full clone with a GitHub pipeline source.

   • For Amazon S3:

     1. In Amazon S3 location, provide the S3 bucket name and path to the object in a bucket with versioning enabled. The format of the bucket name and path looks like this:

         s3://bucketName/folderName/objectName

        Note

        When Amazon S3 is the source provider for your pipeline, you may zip your source file or files into a single .zip and upload the .zip to your source bucket. You may also upload a single unzipped file; however, downstream actions that expect a .zip file will fail.

     2. After you choose the S3 source bucket, CodePipeline creates the Amazon CloudWatch Events rule and the AWS CloudTrail trail to be created for this pipeline. Accept the defaults under Change detection options. This allows CodePipeline to use Amazon CloudWatch Events and AWS CloudTrail to detect changes for your new pipeline. Choose Next.

   • For AWS CodeCommit:

     • In Repository name, choose the name of the CodeCommit repository you want to use as the source location for your pipeline. In Branch name, from the drop-down list, choose the branch you want to use.

     • In Output artifact format, choose the format for your artifacts.

       • To store output artifacts from the CodeCommit action using the default method, choose CodePipeline default. The action accesses the files from the CodeCommit repository and stores the artifacts in a ZIP file in the pipeline artifact store.

       • To store a JSON file that contains a URL reference to the repository so that downstream actions can perform Git commands directly, choose Full clone. This option can only be used by CodeBuild downstream actions.

         If you choose this option, you will need to add the codecommit:GitPull permission to your CodeBuild service role as shown in Add CodeBuild GitClone permissions for CodeCommit source actions. You will also need to add the codecommit:GetRepository permissions to your CodePipeline service role as shown in Add permissions to the CodePipeline service role. For a tutorial that shows you how to use the Full clone option, see Tutorial: Use full clone with a GitHub pipeline source.

     • After you choose the CodeCommit repository name and branch, a message is displayed in Change detection options showing the Amazon CloudWatch Events rule to be created for this pipeline. Accept the defaults under Change detection options. This allows CodePipeline to use Amazon CloudWatch Events to detect changes for your new pipeline.

   • For Amazon ECR:

     • In Repository name, choose the name of your Amazon ECR repository.

     • In Image tag, specify the image name and version, if different from LATEST.

     • In Output artifacts, choose the output artifact default, such as MyApp, that contains the image name and repository URI information you want the next stage to use.

       For a tutorial about creating a pipeline for Amazon ECS with CodeDeploy blue-green deployments that includes an Amazon ECR source stage, see Tutorial: Create a pipeline with an Amazon ECR source and ECS-to-CodeDeploy deployment.

     When you include an Amazon ECR source stage in your pipeline, the source action generates an imageDetail.json file as an output artifact when you commit a change. For information about the imageDetail.json file, see imageDetail.json file for Amazon ECS blue/green deployment actions.

   Note

   The object and file type must be compatible with the deployment system you plan to use (for example, Elastic Beanstalk or CodeDeploy). Supported file types might include .zip, .tar, and .tgz files. For more information about the supported container types for Elastic Beanstalk, see Customizing and Configuring Elastic Beanstalk Environments and Supported Platforms. For more information about deploying revisions with CodeDeploy, see Uploading Your Application Revision and Prepare a Revision.

2. To configure the stage for automatic retry, choose Enable automatic retry on stage failure. For more information about automatic retry, see Configure a stage for automatic retry on failure.

3. Choose Next.

Step 4: Create a build stage

This step is optional if you plan to create a deployment stage.

1. On the Step 3: Add build stage page, do one of the following, and then choose Next:

   • Choose Skip build stage if you plan to create a deployment stage.

   • To choose the Commands action for your build stage, choose Commands.

     Note

     Running the Commands action will incur separate charges in AWS CodeBuild

     In Commands, enter the shell commands for your action. For more information about the Commands action, see Commands action reference.

   • To choose other build providers such as CodeBuild, choose Other providers. From Build provider, choose a custom action provider of build services, and provide the configuration details for that provider. For an example of how to add Jenkins as a build provider, see Tutorial: Create a four-stage pipeline.

   • From Build provider, choose AWS CodeBuild.

     In Region, choose the AWS Region where the resource exists. The Region field designates where the AWS resources are created for this action type and provider type. This field is displayed only for actions where the action provider is an AWS service. The Region field defaults to the same AWS Region as your pipeline.

     In Project name, choose your build project. If you have already created a build project in CodeBuild, choose it. Or you can create a build project in CodeBuild and then return to this task. Follow the instructions in Create a Pipeline That Uses CodeBuild in the CodeBuild User Guide.

     In Environment variables, to add CodeBuild environment variables to your build action, choose Add environment variable. Each variable is made up of three entries:

     • In Name, enter the name or key of the environment variable.

     • In Value, enter the value of the environment variable. If you choose Parameter for the variable type, make sure this value is the name of a parameter you have already stored in AWS Systems Manager Parameter Store.

       Note

       We strongly discourage the use of environment variables to store sensitive values, especially AWS credentials. When you use the CodeBuild console or AWS CLI, environment variables are displayed in plain text. For sensitive values, we recommend that you use the Parameter type instead.

     • (Optional) In Type, enter the type of environment variable. Valid values are Plaintext or Parameter. The default is Plaintext.

     (Optional) In Build type, choose one of the following:

     • To run each build in a single build action execution, choose Single build.

     • To run multiple builds in the same build action execution, choose Batch build.

     (Optional) If you chose to run batch builds, you can choose Combine all artifacts from batch into a single location to place all build artifacts into a single output artifact.

2. To configure the stage for automatic retry, choose Enable automatic retry on stage failure. For more information about automatic retry, see Configure a stage for automatic retry on failure.

3. Choose Next.

Step 5: Create a deployment stage

This step is optional if you have already created a build stage.

1. On the Step 4: Add deploy stage page, do one of the following, and then choose Next:

   • Choose Skip deploy stage if you created a build stage in the previous step.

     Note

     This option does not appear if you have already skipped the build stage.

   • In Deploy provider, choose a custom action that you have created for a deployment provider.

     In Region, for cross-Region actions only, choose the AWS Region where the resource is created. The Region field designates where the AWS resources are created for this action type and provider type. This field only displays for actions where the action provider is an AWS service. The Region field defaults to the same AWS Region as your pipeline.

   • In Deploy provider, fields are available for default providers as follows:

     • CodeDeploy

       In Application name, enter or choose the name of an existing CodeDeploy application. In Deployment group, enter the name of a deployment group for the application. Choose Next. You can also create an application, deployment group, or both in the CodeDeploy console.

     • AWS Elastic Beanstalk

       In Application name, enter or choose the name of an existing Elastic Beanstalk application. In Environment name, enter an environment for the application. Choose Next. You can also create an application, environment, or both in the Elastic Beanstalk console.

     • AWS OpsWorks Stacks

       In Stack, enter or choose the name of the stack you want to use. In Layer, choose the layer that your target instances belong to. In App, choose the application that you want to update and deploy. If you need to create an app, choose Create a new one in AWS OpsWorks.

       For information about adding an application to a stack and layer in AWS OpsWorks, see Adding Apps in the AWS OpsWorks User Guide.

       For an end-to-end example of how to use a simple pipeline in CodePipeline as the source for code that you run on AWS OpsWorks layers, see Using CodePipeline with AWS OpsWorks Stacks.

     • AWS CloudFormation

       Do one of the following:

       • In Action mode, choose Create or update a stack, enter a stack name and template file name, and then choose the name of a role for AWS CloudFormation to assume. Optionally, enter the name of a configuration file and choose an IAM capability option.

       • In Action mode, choose Create or replace a change set, enter a stack name and change set name, and then choose the name of a role for AWS CloudFormation to assume. Optionally, enter the name of a configuration file and choose an IAM capability option.

       For information about integrating AWS CloudFormation capabilities into a pipeline in CodePipeline, see Continuous Delivery with CodePipeline in the AWS CloudFormation User Guide.

     • Amazon ECS

       In Cluster name, enter or choose the name of an existing Amazon ECS cluster. In Service name, enter or choose the name of the service running on the cluster. You can also create a cluster and service. In Image filename, enter the name of the image definitions file that describes your service's container and image.

       Note

       The Amazon ECS deployment action requires an imagedefinitions.json file as an input to the deployment action. The default file name for the file is imagedefinitions.json. If you choose to use a different file name, you must provide it when you create the pipeline deployment stage. For more information, see imagedefinitions.json file for Amazon ECS standard deployment actions.

       Choose Next.

       Note

       Make sure your Amazon ECS cluster is configured with two or more instances. Amazon ECS clusters must contain at least two instances so that one is maintained as the primary instance and another is used to accommodate new deployments.

       For a tutorial about deploying container-based applications with your pipeline, see Tutorial: Continuous Deployment with CodePipeline.

     • Amazon ECS (Blue/Green)

       Enter the CodeDeploy application and deployment group, Amazon ECS task definition, and AppSpec file information, and then choose Next.

       Note

       The Amazon ECS (Blue/Green) action requires an imageDetail.json file as an input artifact to the deploy action. Because the Amazon ECR source action creates this file, pipelines with an Amazon ECR source action do not need to provide an imageDetail.json file. For more information, see imageDetail.json file for Amazon ECS blue/green deployment actions.

       For a tutorial about creating a pipeline for blue-green deployments to an Amazon ECS cluster with CodeDeploy, see Tutorial: Create a pipeline with an Amazon ECR source and ECS-to-CodeDeploy deployment.

     • AWS Service Catalog

       Choose Enter deployment configuration if you want to use fields in the console to specify your configuration, or choose Configuration file if you have a separate configuration file. Enter product and configuration information, and then choose Next.

       For a tutorial about deploying product changes to Service Catalog with your pipeline, see Tutorial: Create a pipeline that deploys to Service Catalog.

     • Alexa Skills Kit

       In Alexa Skill ID, enter the skill ID for your Alexa skill. In Client ID and Client secret, enter the credentials generated using a Login with Amazon (LWA) security profile. In Refresh token, enter the refresh token you generated using the ASK CLI command for retrieving a refresh token. Choose Next.

       For a tutorial about deploying Alexa skills with your pipeline and generating the LWA credentials, see Tutorial: Create a pipeline that deploys an Amazon Alexa skill.

     • Amazon S3

       In Bucket, enter the name of the S3 bucket you want to use. Choose Extract file before deploy if the input artifact to your deploy stage is a ZIP file. If Extract file before deploy is selected, you may optionally enter a value for Deployment path to which your ZIP file will be unzipped. If it is not selected, you are required to to enter a value in S3 object key.

       Note

       Most source and build stage output artifacts are zipped. All pipeline source providers except Amazon S3 zip your source files before providing them as the input artifact to the next action.

       (Optional) In Canned ACL, enter the canned ACL to apply to the object deployed to Amazon S3.

       Note

       Applying a canned ACL overwrites any existing ACL applied to the object.

       (Optional) In Cache control, specify the cache control parameters for requests to download objects from the bucket. For a list of valid values, see the Cache-Control header field for HTTP operations. To enter multiple values in Cache control, use a comma between each value. You can add a space after each comma (optional), as shown in this example.

       

       The preceding example entry is displayed in the CLI as follows:

       "CacheControl": "public, max-age=0, no-transform"

       Choose Next.

       For a tutorial about creating a pipeline with an Amazon S3 deployment action provider, see Tutorial: Create a pipeline that uses Amazon S3 as a deployment provider.

2. To configure the stage for automatic retry, choose Enable automatic retry on stage failure. For more information about automatic retry, see Configure a stage for automatic retry on failure.

3. To configure the stage for automatic rollback, choose Configure automatic rollback on stage failure. For more information about automatic rollback, see Configure a stage for automatic rollback.

4. Choose Next step.

Step 6: Review the pipeline

• On the Step 6: Review page, review your pipeline configuration, and then choose Create pipeline to create the pipeline or Previous to go back and edit your choices. To exit the wizard without creating a pipeline, choose Cancel.

To create the JSON file

1. At a terminal (Linux, macOS, or Unix) or command prompt (Windows), create a new text file in a local directory.

2. (Optional) You can add one or more variables at the pipeline level. You can reference this value in configuration of CodePipeline actions. You can add the variable names and values when you create the pipeline, and you can also choose to assign values when you start the pipeline in the console.

   Note

   While it is optional to add variables at the pipeline level, for a pipeline specified with variables at the pipeline level where no values are provided, the pipeline execution will fail.

   A variable at the pipeline level is resolved at run time of pipeline. All variables are immutable, meaning that they cannot be updated after a value is assigned. Variables at the pipeline level with resolved values will display in the history for each execution.

   You provide variables at the pipeline level using the variables attribute in the pipeline structure. In the following example, the variable Variable1 has a value of Value1.

          "variables": [
               {
                   "name": "Timeout",
                   "defaultValue": "1000",
                   "description": "description"
               }
           ]

   Add this structure to your pipeline JSON, or to the example JSON in the following step. For more information about variables, including namespace information, see Variables reference.

3. Open the file in a plain-text editor and edit the values to reflect the structure you want to create. At a minimum, you must change the name of the pipeline. You should also consider whether you want to change:

   • The S3 bucket where artifacts for this pipeline are stored.

   • The source location for your code.

   • The deployment provider.

   • How you want your code deployed.

   • The tags for your pipeline.

   The following two-stage sample pipeline structure highlights the values you should consider changing for your pipeline. Your pipeline likely contains more than two stages:

   {
       "pipeline": {
           "roleArn": "arn:aws:iam::80398EXAMPLE::role/AWS-CodePipeline-Service",  
           "stages": [
               {
                   "name": "Source",
                   "actions": [
                       {
                           "inputArtifacts": [],
                           "name": "Source",
                           "actionTypeId": {
                               "category": "Source",
                               "owner": "AWS",
                               "version": "1",
                               "provider": "S3"
                           },
                           "outputArtifacts": [
                               {
                                   "name": "MyApp"
                               }
                           ],
                           "configuration": {
                               "S3Bucket": "amzn-s3-demo-source-bucket",
                               "S3ObjectKey": "ExampleCodePipelineSampleBundle.zip",
                               "PollForSourceChanges": "false"
                           },
                           "runOrder": 1                       
                       }
                   ]
               },
               {
                   "name": "Staging",
                   "actions": [
                       {
                           "inputArtifacts": [
                               {
                                   "name": "MyApp"
                               }
                           ],
                           "name": "Deploy-CodeDeploy-Application",
                           "actionTypeId": {
                               "category": "Deploy",
                               "owner": "AWS",
                               "version": "1",
                               "provider": "CodeDeploy"
                           },
                           "outputArtifacts": [],
                           "configuration": {
                               "ApplicationName": "CodePipelineDemoApplication",
                               "DeploymentGroupName": "CodePipelineDemoFleet"
                           },
                           "runOrder": 1
                       }
                   ]
               }
           ],
           "artifactStore": {
               "type": "S3",
               "location": "codepipeline-us-east-2-250656481468"
           },
           "name": "MyFirstPipeline",
           "version": 1,
           "variables": [
               {
                   "name": "Timeout",
                   "defaultValue": "1000",
                   "description": "description"
               }
             ]
           },
           "triggers": [
               {
                   "providerType": "CodeStarSourceConnection",
                   "gitConfiguration": {
                       "sourceActionName": "Source",
                       "push": [
                           {
                               "tags": {
                                   "includes": [
                                       "v1"
                                   ],
                                   "excludes": [
                                       "v2"
                                   ]
                               }
                           }
                       ]
                   }
               }
           ]
       "metadata": {
           "pipelineArn": "arn:aws:codepipeline:us-east-2:80398EXAMPLE:MyFirstPipeline",
           "updated": 1501626591.112,
           "created": 1501626591.112
       },
       "tags": [{
         "key": "Project",
         "value": "ProjectA"
       }]
   } 

   This example adds tagging to the pipeline by including the Project tag key and ProjectA value on the pipeline. For more information about tagging resources in CodePipeline, see Tagging resources.

   Make sure the PollForSourceChanges parameter in your JSON file is set as follows:

                   "PollForSourceChanges": "false",

   CodePipeline uses Amazon CloudWatch Events to detect changes in your CodeCommit source repository and branch or your S3 source bucket. The next step includes instructions to manually create these resources for your pipeline. Setting the flag to false disables periodic checks, which are not necessary when you are using the recommended change detection methods.

4. To create a build, test, or deploy action in a Region different from your pipeline, you must add the following to your pipeline structure. For instructions, see Add a cross-Region action in CodePipeline.

   • Add the Region parameter to your action's pipeline structure.

   • Use the artifactStores parameter to specify an artifact bucket for each AWS Region where you have an action.

5. When you are satisfied with its structure, save your file with a name like pipeline.json.

To create a pipeline

1. Run the create-pipeline command and use the --cli-input-json parameter to specify the JSON file you created previously.

   To create a pipeline named MySecondPipeline with a JSON file named pipeline.json that includes the name "MySecondPipeline" as the value for name in the JSON, your command would look like the following:

   aws codepipeline create-pipeline --cli-input-json file://pipeline.json

   Important

   Be sure to include file:// before the file name. It is required in this command.

   This command returns the structure of the entire pipeline you created.

2. To view the pipeline, either open the CodePipeline console and choose it from the list of pipelines, or use the get-pipeline-state command. For more information, see View pipelines and details in CodePipeline.

3. If you use the CLI to create a pipeline, you must manually create the recommended change detection resources for your pipeline:

   • For a pipeline with a CodeCommit repository, you must manually create the CloudWatch Events rule, as described in Create an EventBridge rule for a CodeCommit source (CLI).

   • For a pipeline with an Amazon S3 source, you must manually create the CloudWatch Events rule and AWS CloudTrail trail, as described in Connecting to Amazon S3 source actions that use EventBridge and AWS CloudTrail.

Step 1: Choose your creation option

1. Sign in to the AWS Management Console and open the CodePipeline console at http://console.aws.amazon.com/codesuite/codepipeline/home.

2. On the Welcome page, choose Create pipeline.

   If this is your first time using CodePipeline, choose Get Started.

3. On the Step 1: Choose creation option page, under Creation options, choose the Create pipeline from template option. Choose Next.

Step 2: Choose template

Choose a template to create a pipeline with a deployment stage, automation, or a CI pipeline.

1. On the Step 2: Choose template page, do one of the following, and then choose Next:

   • Choose Deployment if you plan to create a deployment stage. View the options for templates that deploy to ECR or CloudFormation. For this example, choose Deployment, and then choose to deploy to CloudFormation.

   • Choose Continuous Integration if you plan to create a CI pipeline. View the options for CI pipelines, such as building to Gradle.

   • Choose Automation if you plan to create an automated pipeline. View the options for automation, such as scheduling a python build.

2. 
   
   

Step 3: Choose source

• On the Step 3: Choose source page, in Source provider, choose the provider for the repository where your source code is stored, specify its required options, and then choose Next step.

  • For Bitbucket Cloud, GitHub (via GitHub App), GitHub Enterprise Server, GitLab.com, or GitLab self-managed:

    1. Under Connection, choose an existing connection or create a new one. To create or manage a connection for your GitHub source action, see GitHub connections.

    2. Choose the repository you want to use as the source location for your pipeline.

       Choose to add a trigger or filter on trigger types to start your pipeline. For more information about working with triggers, see Add trigger with code push or pull request event types. For more information about filtering with glob patterns, see Working with glob patterns in syntax.

    3. In Output artifact format, choose the format for your artifacts.

       • To store output artifacts from the GitHub action using the default method, choose CodePipeline default. The action accesses the files from the GitHub repository and stores the artifacts in a ZIP file in the pipeline artifact store.

       • To store a JSON file that contains a URL reference to the repository so that downstream actions can perform Git commands directly, choose Full clone. This option can only be used by CodeBuild downstream actions.

         If you choose this option, you will need to update the permissions for your CodeBuild project service role as shown in Troubleshooting CodePipeline. For a tutorial that shows you how to use the Full clone option, see Tutorial: Use full clone with a GitHub pipeline source.

  • For Amazon ECR:

    • In Repository name, choose the name of your Amazon ECR repository.

    • In Image tag, specify the image name and version, if different from LATEST.

    • In Output artifacts, choose the output artifact default, such as MyApp, that contains the image name and repository URI information you want the next stage to use.

    When you include an Amazon ECR source stage in your pipeline, the source action generates an imageDetail.json file as an output artifact when you commit a change. For information about the imageDetail.json file, see imageDetail.json file for Amazon ECS blue/green deployment actions.

  Note

  The object and file type must be compatible with the deployment system you plan to use (for example, Elastic Beanstalk or CodeDeploy). Supported file types might include .zip, .tar, and .tgz files. For more information about the supported container types for Elastic Beanstalk, see Customizing and Configuring Elastic Beanstalk Environments and Supported Platforms. For more information about deploying revisions with CodeDeploy, see Uploading Your Application Revision and Prepare a Revision.

Step 4: Configure template

For this example, the deployment to CloudFormation was selected. In this step, add configuration for your template.

1. In Step 4: Configure template, in Stack name, enter a name for your pipeline.

2. Edit the placeholder IAM policy for the permissions that apply for your template.

3. Choose Create pipeline from template

4. A message displays stating that your pipeline resources are being created.

Step 5: View the pipeline

• Now that you've created your pipeline, you can view it in the CodePipeline console and view the stack in AWS CloudFormation. The pipeline starts to run after you create it. For more information, see View pipelines and details in CodePipeline. For more information about making changes to your pipeline, see Edit a pipeline in CodePipeline.