Code Deployment

Learn how to deploy your code and what happens in Cloud Manager when you do.

Deploying Code with Cloud Manager

Once you have configured your production pipeline including the necessary repository and environments, you are ready to deploy your code.

1. Click Deploy from the Cloud Manager to start the deployment process.

   

2. The Pipeline Execution screen displays. Click Build to start the process.

   

The build process starts the code deployment process including the following steps:

• Stage deployment
• Stage testing
• Production deployment

You can review the steps from various deployment processes by viewing logs, or reviewing results, for the testing criteria.

Deployment Steps

A number of actions occur during each step of the deployment, which are described in this section. See the section Deployment Process Details for technical details of how the code itself is deployed behind-the-scenes.

Stage Deployment Step

The Stage deployment step includes the following actions:

• Validation: This step ensures that the pipeline is configured to use the currently available resources, e.g. that the configured branch exists and that the environments are available.
• Build & Unit Testing: This step runs a containerized build process. See the document The Build Environment for details.
• Code Scanning: This step evaluates the quality of your application code. See the document Understanding Test Results for details on the testing process.
• Deploy to Stage

Stage Testing Step

The Stage testing step includes the following actions:

• Security Testing: This step evaluates the security impact of your code on the AEM environment. See the document Understanding Test Results for details on the testing process.

  • Performance Testing: This step evaluates the performance of your code. See Understanding Test Results for details on the testing process.

  

Production Deployment Step

The Production Deployment step, includes the following actions:

• Application for Approval
  • This option is enabled while configuring the pipeline.
  • Using this option, you can either schedule your production deployment or click Now to execute the production deployment immediately.
• Schedule Production Deployment
  • This option is enabled while configuring the pipeline.
  • The scheduled date and time is specified in terms of the user’s timezone.
    
• CSE Support (if enabled)
• Deploy to Production

Once your deployment is complete, your code is in its targeted environment and you can view the logs.

Timeouts

The following steps will timeout if left waiting for user feedback:

Deployment Process Details

Cloud Manager uploads all target/*.zip files produced by the build process to a storage location. These artifacts are retrieved from this location during the deploy phases of the pipeline.

When Cloud Manager deploys to non-production topologies, the goal is to complete the deployment as quickly as possible and therefore the artifacts are deployed to all nodes simultaneously as follows:

1. Cloud Manager determines whether each artifact is an AEM or dispatcher package.

2. Cloud Manager removes all dispatchers from the load balancer to isolate the environment during the deployment.

   • Unless configured otherwise, you can skip load balancer changes in development and staging Deployments, i.e. for development environment, detach and attach steps in both non-production pipelines, and for staging environment the production pipeline.

   

   NOTE

   This feature is expected to be primarily used by 1-1-1 customers.

3. Each AEM artifact is deployed to each AEM instance via Package Manager APIs, with package dependencies determining the deployment order.

   • To learn more about how you can use packages to install new functionality, transfer content between instances, and back up repository content, please refer to the document Package Manager.
   NOTE

   All AEM artifacts are deployed to both the author and the publishers. Run modes should be leveraged when node-specific configurations are required. To learn more about how the run-modes allow you to tune your AEM instance for a specific purpose, please refer to the Run Modes section of the document Deploying to AEM as a Cloud Service.

4. The dispatcher artifact is deployed to each dispatcher as follows:

   1. Current configurations are backed up and copied to a temporary location.
   2. All configurations are deleted except the immutable files. Refer to the document Dispatcher Configurations for more details. This clears the directories to ensure no orphaned files are left behind.
   3. The artifact is extracted to the httpd directory. Immutable files are not overwritten. Any changes you make to immutable files in your git repository will be ignored at the time of deployment. These files are core to the AMS dispatcher framework and can not be changed.
   4. Apache performs a configuration test. If no errors are found, the service is reloaded. If an error occurs, the configurations are restored from backup, the service is reloaded, and the error is reported back to Cloud Manager.
   5. Each path specified in the pipeline configuration is invalidated or flushed from the dispatcher cache.
   NOTE

   Cloud Manager expects the dispatcher artifact to contain the full file set. All dispatcher configuration files must be present in the git repository. Missing files or folders will result in deployment failure.

5. Following the successful deployment of all AEM and dispatcher packages to all nodes, the dispatchers are added back to the load balancer and the deployment is complete.

   NOTE

   you can skip load balancer changes in development and staging Deployments, i.e. for development environment, detach and attach steps in both non-production pipelines, and for staging environment the production pipeline.

Deployment to Production Phase

The process for deploying to production topologies differs slightly in order to minimize impact to AEM site visitors.

Production deployments generally follow the same steps as above, but in a rolling manner:

1. Deploy AEM packages to author.
2. Detach dispatcher1 from the load balancer.
3. Deploy AEM packages to publish1 and the dispatcher package to dispatcher1 in parallel, flush dispatcher cache.
4. Put dispatcher1 back into the load balancer.
5. Once dispatcher1 is back in service, detach dispatcher2 from the load balancer.
6. Deploy AEM packages to publish2 and the dispatcher package to dispatcher2 in parallel, flush dispatcher cache.
7. Put dispatcher2 back into the load balancer.

This process continues until the deployment has reached all publishers and dispatchers in the topology.

Emergency Pipeline Execution Mode

In critical situations, Adobe Managed Services customers may need to deploy code changes to their stage and production environments without waiting for a full Cloud Manager test cycle to execute.

To address these situations, the Cloud Manager production pipeline may be executed in an emergency mode. When this mode is used, the security and performance test steps are not executed. All other steps, including any configured approval steps, are executed as in the normal pipeline execution mode.

Using Emergency Pipeline Execution Mode

When starting a production pipeline execution, if the emergency pipeline execution mode feature has been activated for the program, you can start the execution in either normal or emergency mode from a dialog box.

When viewing the pipeline execution details page for an execution run in emergency mode, the breadcrumbs at the top of the screen show an indicator that the pipeline is executing in emergency mode.

Executing a pipeline in emergency mode can also be done through the Cloud Manager API or CLI. To start an execution in emergency mode, submit a PUT request to the pipeline’s execution endpoint with the query parameter ?pipelineExecutionMode=EMERGENCY or, when using the CLI:

$ aio cloudmanager:pipeline:create-execution PIPELINE_ID --emergency

Re-Executing a Production Deployment

In rare cases, production deployment steps may fail for transient reasons. In such cases, re-execution of the production deployment step is supported so long as the production deployment step has completed, regardless of the type of completion (e.g. successful, cancelled or unsuccessful). Re-execution creates a new execution using the same pipeline consisting of three steps.

1. The validate step - This is essentially the same validation that occurs during a normal pipeline execution.
2. The build step - In the context of a re-execution, the build step copies artifacts and does not actually execute a new build process.
3. The production deployment step - This uses the same configuration and options as the production deployment step in a normal pipeline execution.

In such circumstances where a re-execution is possible, the production pipeline status page provides the Re-execute option next to the usual Download build log option.

Limitations

• Re-executing the production deployment step is only available for the last execution.
• Re-execution is not available for rollback executions or push update executions.
• If the last execution failed at any point prior to the production deployment step, re-execution is not possible.

Re-Execute API

In addition to being available in the UI, you can use the Cloud Manager API to trigger re-executions as well as identify executions that were triggered as re-executions.

Triggering a Re-Execution

To trigger a re-execution, a PUT request needs to be made to the HAL Link http://ns.adobe.com/adobecloud/rel/pipeline/reExecute on the production deploy step state.

• If this link is present, the execution can be restarted from that step.
• If it is absent, the execution can not be restarted from that step.

This link is only ever available for the production deploy step.

 {
  "_links": {
    "http://ns.adobe.com/adobecloud/rel/pipeline/logs": {
      "href": "/api/program/4/pipeline/1/execution/953671/phase/1575676/step/2983530/logs",
      "templated": false
    },
    "http://ns.adobe.com/adobecloud/rel/pipeline/reExecute": {
      "href": "/api/program/4/pipeline/1/execution?stepId=2983530",
      "templated": false
    },
    "http://ns.adobe.com/adobecloud/rel/pipeline/metrics": {
      "href": "/api/program/4/pipeline/1/execution/953671/phase/1575676/step/2983530/metrics",
      "templated": false
    },
    "self": {
      "href": "/api/program/4/pipeline/1/execution/953671/phase/1575676/step/2983530",
      "templated": false
    }
  },
  "id": "6187842",
  "stepId": "2983530",
  "phaseId": "1575676",
  "action": "deploy",
  "environment": "weretail-global-b75-prod",
  "environmentType": "prod",
  "environmentId": "59254",
  "startedAt": "2022-01-20T14:47:41.247+0000",
  "finishedAt": "2022-01-20T15:06:19.885+0000",
  "updatedAt": "2022-01-20T15:06:20.803+0000",
  "details": {
  },
  "status": "FINISHED"

The syntax of the HAL link’s href value is only an example and the actual value should always be read from the HAL link and not generated.

Submitting a PUT request to this endpoint will result in a 201 response if successful and the response body will be the representation of the new execution. This is similar to starting a regular execution through the API.

Identifying a Re-Execute Execution

Re-executed executions can be identified by the value RE_EXECUTE in the trigger field.