# Create a pipeline, stages, and actions You can use the AWS CodePipeline console or the AWS CLI to create a pipeline. Pipelines must have at least two stages. The first stage of a pipeline must be a source stage. The pipeline must have at least one other stage that is a build or deployment stage. **Important** As part of creating a pipeline, an S3 artifact bucket provided by the customer will be used by CodePipeline for artifacts. (This is different from the bucket used for an S3 source action.) If the S3 artifact bucket is in a different account from the account for your pipeline, make sure that the S3 artifact bucket is owned by AWS accounts that are safe and will be dependable. You can add actions to your pipeline that are in an AWS Region different from your pipeline. A cross-Region action is one in which an AWS service is the provider for an action and the action type or provider type are in an AWS Region different from your pipeline. For more information, see [Add a cross-Region action in CodePipeline](actions-create-cross-region.md). You can also create pipelines that build and deploy container-based applications by using Amazon ECS as the deployment provider. Before you create a pipeline that deploys container-based applications with Amazon ECS, you must create an image definitions file as described in [Image definitions file reference](file-reference.md). CodePipeline uses change detection methods to start your pipeline when a source code change is pushed. These detection methods are based on source type: + CodePipeline uses Amazon CloudWatch Events to detect changes in your CodeCommit source repository and branch or your S3 source bucket. **Note** When you use the console to create or edit a pipeline, the change detection resources are created for you. If you use the AWS CLI to create the pipeline, you must create the additional resources yourself. For more information, see [CodeCommit source actions and EventBridge](triggering.md). **Topics** + [Create a custom pipeline (console)](#pipelines-create-console) + [Create a pipeline (CLI)](#pipelines-create-cli) + [Create a pipeline from static templates](#pipelines-create-templates) ## Create a custom pipeline (console) To create a custom pipeline in the console, you must provide the source file location and information about the providers you will use for your actions. When you use the console to create a pipeline, you must include a source stage and one or both of the following: + A build stage. + A deployment stage. When you use the pipeline wizard, CodePipeline creates the names of stages (source, build, staging). These names cannot be changed. You can use more specific names (for example, BuildToGamma or DeployToProd) to stages you add later. **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](http://console.aws.amazon.com/codesuite/codepipeline/home). 1. On the **Welcome** page, choose **Create pipeline**. If this is your first time using CodePipeline, choose **Get Started**. 1. On the **Step 1: Choose creation option** page, under **Creation options**, choose the **Build custom pipeline** option. Choose **Next**. 1. 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](limits.md). 1. In **Pipeline type**, choose one of the following options. Pipeline types differ in characteristics and price. For more information, see [Pipeline types](pipeline-types.md). + **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. 1. 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](how-to-custom-role.md#how-to-update-role-new-services). For more information about the service role and its policy statement, see [Manage the CodePipeline service role](how-to-custom-role.md). 1. (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](reference-variables.md). For a tutorial with a pipeline-level variable that is passed at the time of the pipeline execution, see [Tutorial: Use pipeline-level variables](tutorials-pipeline-variables.md). **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. 1. (Optional) Expand **Advanced settings**. 1. 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. 1. 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](welcome-introducing-artifacts.md) and [CodePipeline pipeline structure reference](reference-pipeline-structure.md). 1. 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**. 1. 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. 1. 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](connections-github.md). 1. 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](pipelines-filter.md). For more information about filtering with glob patterns, see [Working with glob patterns in syntax](syntax-glob.md). 1. 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](troubleshooting.md). For a tutorial that shows you how to use the **Full clone** option, see [Tutorial: Use full clone with a GitHub pipeline source](tutorials-github-gitclone.md). + 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. 1. 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](troubleshooting.md#codebuild-role-codecommitclone). 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](how-to-custom-role.md#how-to-update-role-new-services). For a tutorial that shows you how to use the **Full clone** option, see [Tutorial: Use full clone with a GitHub pipeline source](tutorials-github-gitclone.md). + 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](tutorials-ecs-ecr-codedeploy.md). 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](file-reference.md#file-reference-ecs-bluegreen). **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](https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/customize-containers.html) and [Supported Platforms](https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/concepts.platforms.html). For more information about deploying revisions with CodeDeploy, see [Uploading Your Application Revision](https://docs.aws.amazon.com/codedeploy/latest/userguide/deployment-steps.html#deployment-steps-uploading-your-app) and [Prepare a Revision](https://docs.aws.amazon.com/codedeploy/latest/userguide/how-to-prepare-revision.html). 1. 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](stage-retry.md#stage-retry-auto). 1. Choose **Next**. **Step 4: Create a build stage** This step is optional if you plan to create a deployment stage. 1. On the **Step 4: Add build stage** page, do one of the following, and then choose **Next**: + Choose **Skip build stage** if you plan to create a test or 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. If you plan to insert build commands as part of a CodeBuild action, go ahead and choose Other build providers, and then select CodeBuild. In **Commands**, enter the shell commands for your action. For more information about the Commands action, see [Commands action reference](action-reference-Commands.md). + 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](tutorials-four-stage-pipeline.md). + 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](https://docs.aws.amazon.com/codebuild/latest/userguide/how-to-create-pipeline.html#pipelines-create-console) in the *CodeBuild User Guide*. Under **Build specifications**, the CodeBuild buildspec file is optional, and you can enter commands instead. In **Insert build commands**, enter the shell commands for your action. For more information about considerations for using build commands, see [Commands action reference](action-reference-Commands.md). Choose **Use a buildspec file** if you want to run commands in other phases or if you have a long list of commands. 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. 1. 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](stage-retry.md#stage-retry-auto). 1. Choose **Next**. **Step 5: Create a test stage** This step is optional if you plan to create a build or deployment stage. 1. On the **Step 5: Add test stage** page, do one of the following, and then choose **Next**: + Choose **Skip test stage** if you plan to create a build or deployment stage. + In **Test provider**, choose the test action provider and complete the appropriate fields. 1. Choose **Next**. **Step 6: Create a deployment stage** This step is optional if you have already created a build stage. 1. On the **Step 6: Add deploy stage** page, do one of the following, and then choose **Next**: + Choose **Skip deploy stage** if you created a build or test stage in the previous steps. **Note** This option does not appear if you have already skipped the build or test 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](https://docs.aws.amazon.com/opsworks/latest/userguide/workingapps-creating.html) 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](https://docs.aws.amazon.com/opsworks/latest/userguide/other-services-cp.html). + **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](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/continuous-delivery-codepipeline.html) 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](file-reference.md#pipelines-create-image-definitions). 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](https://docs.aws.amazon.com/AmazonECS/latest/developerguide/ecs-cd-pipeline.html). + **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](file-reference.md#file-reference-ecs-bluegreen). 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](tutorials-ecs-ecr-codedeploy.md). + **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](tutorials-S3-servicecatalog.md). + **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](tutorials-alexa-skills-kit.md). + **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](https://docs.aws.amazon.com/AmazonS3/latest/userguide/acl-overview.html#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 [http://www.w3.org/Protocols/rfc2616/rfc2616-sec14.html#sec14.9](http://www.w3.org/Protocols/rfc2616/rfc2616-sec14.html#sec14.9) 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. ![\[Image showing the Cache control field in the console with the following entry: public, max-age=0, no-transform\]](http://docs.aws.amazon.com/codepipeline/latest/userguide/images/cache_control_values.png) 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](tutorials-s3deploy.md). 1. 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](stage-retry.md#stage-retry-auto). 1. 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](stage-rollback-auto.md). 1. Choose **Next step**. **Step 7: Review the pipeline** + On the **Step 7: 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**. Now that you've created your pipeline, you can view it in the console. The pipeline starts to run after you create it. For more information, see [View pipelines and details in CodePipeline](pipelines-view.md). For more information about making changes to your pipeline, see [Edit a pipeline in CodePipeline](pipelines-edit.md). ## Create a pipeline (CLI) To use the AWS CLI to create a pipeline, you create a JSON file to define the pipeline structure, and then run the **create-pipeline** command with the `--cli-input-json` parameter. **Important** You cannot use the AWS CLI to create a pipeline that includes partner actions. You must use the CodePipeline console instead. For more information about pipeline structure, see [CodePipeline pipeline structure reference](reference-pipeline-structure.md) and [create-pipeline](http://docs.aws.amazon.com/cli/latest/reference/codepipeline/create-pipeline.html) in the CodePipeline [API Reference](http://docs.aws.amazon.com/cli/latest/reference/codepipeline). To create a JSON file, use the sample pipeline JSON file, edit it, and then call that file when you run the **create-pipeline** command. **Prerequisites:** You need the ARN of the service role you created for CodePipeline in [Getting started with CodePipeline](getting-started-codepipeline.md). You use the CodePipeline service role ARN in the pipeline JSON file when you run the **create-pipeline** command. For more information about creating a service role, see [Create the CodePipeline service role](pipelines-create-service-role.md). Unlike the console, running the **create-pipeline** command in the AWS CLI does not have the option to create the CodePipeline service role for you. The service role must already exist. You need the name of an S3 bucket where artifacts for the pipeline are stored. This bucket must be in the same Region as the pipeline. You use the bucket name in the pipeline JSON file when you run the **create-pipeline** command. Unlike the console, running the **create-pipeline** command in the AWS CLI does not create an S3 bucket for storing artifacts. The bucket must already exist. **Note** You can also use the **get-pipeline** command to get a copy of the JSON structure of that pipeline, and then modify that structure in a plain-text editor. **Topics** **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. 1. (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](reference-variables.md). 1. 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](tag-resources.md). 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. 1. 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](actions-create-cross-region.md). + 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. 1. 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. 1. 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](pipelines-view.md). 1. 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)](pipelines-trigger-source-repo-changes-cli.md). + 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](create-cloudtrail-S3-source.md). ## Create a pipeline from static templates You can create a pipeline in the console that uses a template to configure a pipeline with source code and properties that you specify. You must provide the source file location and information about the source providers you will use for your actions. You can specify a source action for Amazon ECR or any third-party repository supoorted by CodeConnections, such as GitHub. The template will create a stack in CloudFormation for your pipeline that includes the following resources: + A pipeline is created with the V2 pipeline type. In **Pipeline type**, choose one of the following options. Pipeline types differ in characteristics and price. For more information, see [Pipeline types](pipeline-types.md). + A service role is created for your pipeline and referenced in the template. + An artifact store is created using 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. To view the collection of open source starter templates that are used for the static template creation wizard, see the repository at [https://github.com/aws/codepipeline-starter-templates](https://github.com/aws/codepipeline-starter-templates). When you use static templates to create a pipeline, the pipeline structure is configured in each template according to the needs of the use case. For example, the template for a deployment to CloudFormation is used as an example in this procedure. The template generates a pipeline named **DeployToCloudFormationService** with the following structure: + A build stage that contains a source action with configuration that you specify in the wizard. + A deployment stage with a deploy action and associated resource stack in CloudFormation. When you use a static template to create a pipeline, CodePipeline creates the names of stages (source, build, staging). These names cannot be changed. You can use more specific names (for example, BuildToGamma or DeployToProd) to stages you add later. **Step 1: Access the console** 1. Sign in to the AWS Management Console and open the CodePipeline console at [http://console.aws.amazon.com/codesuite/codepipeline/home](http://console.aws.amazon.com/codesuite/codepipeline/home). 1. On the **Welcome** page, choose **Create pipeline**. If this is your first time using CodePipeline, choose **Get Started**. **Step 2: Choose template** Choose a template to create a pipeline with a deployment stage, automation, or a CI pipeline. 1. On the **Step 1: Choose creation option** 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. 1. ![\[Image showing the choose template option with CloudFormation deployment selecrtedin the wizard\]](http://docs.aws.amazon.com/codepipeline/latest/userguide/images/create-static-choose-template-depl.png) ![\[Image showing the choose source page in the wizard\]](http://docs.aws.amazon.com/codepipeline/latest/userguide/images/create-static-choose-template-CI.png) ![\[Image showing the choose template option with automation selected in the wizard\]](http://docs.aws.amazon.com/codepipeline/latest/userguide/images/create-static-choose-template-auto.png) **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](connections-github.md). 1. 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](pipelines-filter.md). For more information about filtering with glob patterns, see [Working with glob patterns in syntax](syntax-glob.md). 1. 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](troubleshooting.md). For a tutorial that shows you how to use the **Full clone** option, see [Tutorial: Use full clone with a GitHub pipeline source](tutorials-github-gitclone.md). + 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](file-reference.md#file-reference-ecs-bluegreen). **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](https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/customize-containers.html) and [Supported Platforms](https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/concepts.platforms.html). For more information about deploying revisions with CodeDeploy, see [Uploading Your Application Revision](https://docs.aws.amazon.com/codedeploy/latest/userguide/deployment-steps.html#deployment-steps-uploading-your-app) and [Prepare a Revision](https://docs.aws.amazon.com/codedeploy/latest/userguide/how-to-prepare-revision.html). **Step 4: Configure template** For this example, the deployment to CloudFormation was selected. In this step, add configuration for your template. ![\[Image showing the configure template page in the wizard\]](http://docs.aws.amazon.com/codepipeline/latest/userguide/images/create-static-conf-template.png) 1. In **Step 4: Configure template**, in **Stack name**, enter a name for your pipeline. 1. Edit the placeholder IAM policy for the permissions that apply for your template. 1. Choose **Create pipeline from template** 1. 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 CloudFormation. The pipeline starts to run after you create it. For more information, see [View pipelines and details in CodePipeline](pipelines-view.md). For more information about making changes to your pipeline, see [Edit a pipeline in CodePipeline](pipelines-edit.md).