AWS CodePipeline Concepts

External

• https://docs.aws.amazon.com/codepipeline/latest/userguide/concepts.html
• CreatePipeline API Request Reference

Internal

• AWS CodePipeline

CodePipeline as AWS Service

CodePipeline is an AWS service, named "codepipeline.amazonaws.com".

Pipeline

Pipeline Structure

A pipeline is a top-level AWS resource that provides CI/CD release pipeline functionality.

From a conceptual perspective, a pipeline is a workflow construct that describes how software changes go through a release process.

As implemented in AWS, the pipeline, consist in a set of sequential stages, each stage containing one or more actions. A specific stage is always in a fixed position relative to other stages, and only one stage runs at a time. However, actions within a stage can be executed sequentially, according their run order or in parallel. Stages and actions process artifacts, which "advance" along the pipeline.

A pipeline starts automatically when a change is made in the source location, as defined in a source action in a pipeline. The pipeline can also be started manually. A rule can be configured in Amazon CloudWatch to automatically start a pipeline when a specific event occurs. After a pipeline starts, the revision runs through every stage and action in the pipeline.

A pipeline can be created the following CloudFormation sequence:

Resources:
  Pipeline:
    Name: !Ref AWS::StackName
    Type: AWS::CodePipeline::Pipeline
    Properties:
      RoleArn: 'arn:aws:iam::777777777777:role/CodePipelineServiceRole-1'
      ArtifactStore
        Type: 'S3'
        Location: 'experimental-s3-bucket-for-codepipeline'
      ...
  Stages:
    ...

An example of a simple, working GitHub-based pipeline is available here:

Simple GitHub - Simulated Shell Build - Simulated Deployment Pipeline

Required Configuration

The pipeline requires a number of configuration properties:

RoleArn

The pipeline needs to be associated with a service role, which allows the codepipeline service to execute various actions required by pipeline operations.

ArtifactStore

The pipeline requires an artifact store, which provides the storage for transient and final artifacts that are processed by the various stages and actions. In most cases, the storage is provided by an Amazon S3 bucket. "Location" specifies the name of the bucket. When the pipeline is initialized, the codepipeline service creates a directory associated with the pipeline. The directory will have the same name as the pipeline. As the pipeline operates, sub-directories corresponding to various input and output artifacts declared by actions will be also created.

When Amazon Console is used to create the first pipeline, an S3 bucket is created in the same region as the pipeline to be sued items for all pipelines in that region, associated with the account.

Optional Configuration

Optionally, a name can also be configured with a name:

Name

Optional parameter, that provides the physical ID for the pipeline. If not specified, a name will be generated based on the stack-name-Pipeline-24RCYXM52UE6A pattern. A recommended name is:

Name: !Ref AWS::StackName

Revision

A revision is a change made to a source that feeds a pipeline. The revision can be triggered by a git push command, or an S3 file update in a versioned S3 bucket. Each revision runs separately through the pipeline. Multiple revisions can be processed in the same pipeline, but each stage can process only one revision at a time. Revisions are run through the pipeline as soon as a change is made in the location specified in the source stage of the pipeline.

Because only one revision can run through a stage at a time, CodePipeline batches any revisions that have completed the previous stage until the next stage is available. If a more recent revision completes running through the stage, the batched revision is replaced by the most current revision.

Stage

A stage is a component of the workflow implemented by the pipeline. Each stage has an unique name within the pipeline. Intrinsically related to a stage is the concept of serialization: stages cannot be execute in parallel, just one stage of the pipeline executes at a time.

A pipeline must have at least 2 stages, one-stage pipeline will be considered invalid. A stage contains one or more actions, which could be executed sequentially or in parallel. All actions configured in a stage must complete successfully before a stage is considered complete.

Resources:
  MyPipeline:
    Type: AWS::CodePipeline::Pipeline
      ...
      Stages:
        - Name: ...
          Actions:
            - ...
        - Name: ...
          Actions:
            - ...

Artifact

A revision propagates through the pipeline by having files associated with actions performed at different stages copied by CodePipeline service in different folders of the S3 bucket associated with the pipeline. These folders - not the high granularity files produced by an action - are referred to as artifacts. Artifacts may be used as input to an action - Input Artifacts - or may be produced by an action - Output Artifacts.

Action

ActionDeclaration

An action is a task performed on an artifact, and it is triggered at a specific stage of a pipeline. The action may occur in a specified order, or in parallel, depending on their configuration. All actions share a common structure:

Action Structure

Action Name

An action name must match the regular expression pattern: [A-Za-z0-9.@\-_]+ The action name must not contain spaces.

Action Type Declaration (ActionTypeId)

ActionTypeId

The action type declaration specifies an action provider. Currently, six types of actions are supported:

• Source
• Build
• Test
• Deploy
• Approval
• Invoke

Custom actions can also be developed.

Input Artifacts

InputArtifact

An action declares zero or more input artifacts, which are the logical names or the IDs for object fed to the action and that are supposed to be processed by the action in a meaningful way. Very commonly, an input artifact is the name of an S3 folder, created by the pipeline inside the pipeline's S3 folder, which is created inside the artifact store S3 bucket. Every input artifact for an action must match an output artifact of an action earlier in the pipeline, whether that action is immediately before the action in a stage or runs in a stage several stages earlier.

Output Artifacts

OutputArtifact

An action declares zero or more output artifacts, which are the names or the IDs of the results of the action. Very commonly, an output artifact is the name of an S3 folder, created by the pipeline inside the pipeline's S3 folder, which is created inside the artifact store S3 bucket. Every output artifact in the pipeline must have a unique name.

Configuration

Configuration elements are specific to the action provider and are passed to it.

Failure

A failure is an action that has not completed successfully. If one action fails in a stage, the revision does not transition to the next action in the stage or the next stage in the pipeline. If a failure occurs, no more transitions occur in the pipeline for that revision. CodePipeline pauses the pipeline until one of the following occurs:

• The stage is manually retried.
• The pipeline is restarted for that revision.
• Another revision is made in a source stage action.

Available Actions

Source

Source Action Integrations

Resources:
  MyPipeline:
    Type: AWS::CodePipeline::Pipeline
    Properties:
      ...
      Stages:
        - Name: Source
          Actions:
            - Name: !Sub 'github-pull-${Branch}'
              ActionTypeId:
                Category: Source
                Provider: GitHub
                Owner: ThirdParty
                Version: '1'
              Configuration:
                Owner: !Ref GitHubOrganizationID
                Repo: !Ref GitHubRepositoryName
                Branch: !Ref Branch
                OAuthToken: !Ref GitHubPersonalAccessCode
              InputArtifacts: []
              OutputArtifacts:
                - Name: 'sources'
              RunOrder: 1
        - Name: ...

The action provider, which can be GitHub or other source repository provider, performs a repository clone and packages the content as a ZIP file. The ZIP file is placed in the artifact store, under the directory corresponding to the pipeline and the sub-directory named based on the "OutputArtifacts.Name" configuration element. Assuming that the pipeline is named "thalarion", the output ZIP file is placed in s3://thalarion-buildbucket-enqyf1xp13z2/thalarion/sources.

An example of a simple, working GitHub-based pipeline is available here:

Simple GitHub - Simulated Shell Build - Simulated Deployment Pipeline

GitHub Authentication

GitHub Authentication for AWS CodePipeline

Build

Build Action Integration

Use CodePipeline with AWS CodeBuild to Test Code and Run Builds

Resources:
  MyPipeline:
    Type: AWS::CodePipeline::Pipeline
    Properties:
      ...
      Stages:
        ...
        - Name: Build
          Actions:
            - Name: !Sub '${Buildspec}-driven-CodeBuild'
              ActionTypeId:
                Category: Build
                Provider: CodeBuild
                Owner: AWS
                Version: '1'
              InputArtifacts:
                - Name: 'sources'
              OutputArtifacts:
                - Name: 'build'
              Configuration:
                ProjectName: !Ref CodeBuildProject
              RunOrder: 1
        - Name: ...

The action provider, which in this case is the CodeBuild service, executes the build. Existing build projects can be used, or new ones can be created in the CodePipeline console. The build artifacts are placed in the artifact store, under the directory corresponding to the pipeline and the sub-directory named based on the "OutputArtifacts.Name" configuration element. Assuming that the pipeline is named "thalarion", the build artifacts are placed in s3://thalarion-buildbucket-enqyf1xp13z2/thalarion/build-files. The following article explains in detail how CodePipeline and CodeBuild interact:

CodePipeline-Driven CodeBuild Builds

An example of a simple, working GitHub-based pipeline is available here:

Simple GitHub - Simulated Shell Build - Simulated Deployment Pipeline

Deploy

AWS CloudFormation Configuration Properties Reference

Resources:
  MyPipeline:
    Type: AWS::CodePipeline::Pipeline
    Properties:
      ...
      Stages:
        ...
        - Name: Deploy
          Actions:
            - Name: !Sub '${DeploymentStackTemplate}-driven-deployment'
              ActionTypeId:
                Category: Deploy
                Provider: CloudFormation
                Owner: AWS
                Version: '1'
              InputArtifacts:
                - Name: 'sources'
                - Name: 'build'
              OutputArtifacts: []
              Configuration:
                StackName: !Ref ProjectID
                TemplatePath: !Sub sources::${DeploymentStackTemplate}
                # The union of parameters specified in 'TemplateConfiguration' and in 'ParameterOverrides' must
                # match exactly the set of deployment template parameters that do not have defaults
                TemplateConfiguration: build::cloudformation-deployment-configuration.json
                # parameter values specified in "ParameterOverrides" take precedence over the values specified in
                # 'TemplateConfiguration'
                ParameterOverrides: !Sub '{ "MyConfigurationParameterA": "yellow", "MyConfigurationParameterB": "black" }'
                ActionMode: CREATE_UPDATE
                Capabilities: CAPABILITY_IAM
                RoleArn:
                  Fn::ImportValue: !Sub '${ProjectID}-cloudformation-service-role-ARN'
              RunOrder: 1

This step relies on the presence of a CloudFormation stack template somewhere in an artifact produced by a previous pipeline stage. The name of the template file is configured as "TemplatePath". In the example above, the template path is relative the "source" InputArtifact, so it is expected to be found in the source tree.

A CloudFront template can be configured externally with parameters, and thus the deployment template can be configured by providing configuration values in a configuration file, specified as "TemplateConfiguration". "TemplateConfiguration" has the ArtifactName::TemplateConfigurationFileName format, which means that the template configuration file must be produced by one of the previous pipeline steps and must be placed in one of the artifacts. If the template configuration file is not found, maybe because the none of the previous stages created it, the deployment stage will fail with an S3 error. The configuration file allows JSON and YAML. A JSON configuration file is similar to:

{
  "Parameters": {
     "MyConfigurationParameter": "my value"
  }
}

The buildspec produces it as follows:

  ...
  - echo "{\"Parameters\":{\"MyConfigurationParameter\":\"spurious\"}}" > ./cloudformation-deployment-configuration.json
  ...

Note that all parameters that do not have defaults in the deployment template must be provided, otherwise the deployment will fail with: "Action execution failed: Parameters: [...] must have values (Service: AmazonCloudFormation; Status Code: 400; Error Code: ValidationError."

It is possible to override values in the template configuration file in the pipeline definition, using the "ParameterOverrides" key. If the same parameter is specified both in "ParameterOverrides" and in the template configuration file, the value specified in "ParameterOverrides" takes precedence.

The union of parameters specified as "ParameterOverrides" and those coming from the configuration files should match exactly the no-default template parameter set.

An example of a simple, working GitHub-based pipeline is available here:

Simple GitHub - Simulated Shell Build - Simulated Deployment Pipeline

Invoke

Invokes an AWS Lambda.

Custom Action

https://docs.aws.amazon.com/codepipeline/latest/userguide/actions-create-custom-action.html

Custom actions can be developed.

Transition

A transition is the act of a revision in a pipeline continuing from one stage to the next in a workflow. After a stage is completed, the pipeline transitions the revision and its artifacts created by the actions in that stage to the next stage in the pipeline. A transition can be manually enabled or disabled. If a transition is disabled, the pipeline will run all actions in the stages before that transition, but will not run any stages or actions after that stage. This is a simple way to prevent changes from running through the entire pipeline.

If a transition is enabled, the most recent revision that ran successfully through the previous stages will be run through the stages after that transition. If all transitions are enabled, the pipeline runs continuously, implementing the concept of continuous deployment.

Approval Action

An approval action prevents a pipeline from transitioning to the next stage until permission is granted - for example, manual approval by user that performed a code review.