Documentation AEM as a Cloud Service User Guide

Deploy your code deploy-your-code

Last update: Thu Oct 10 2024 00:00:00 GMT+0000 (Coordinated Universal Time)

CREATED FOR:

Admin
Developer

Learn how to deploy your code to Production using Cloud Manager pipelines in AEM as a Cloud Service.

Production pipeline diagram

Deploying code seamlessly to Stage and then through to Production is done through a Production pipeline. The Production pipeline execution is broken into the two following logical phases:

Deployment to Stage environment - The code is built and deployed to the Stage environment for automated functional testing, UI testing, experience audit, and User Acceptance Testing (UAT).
Deployment to Production environment - Once the build is validated on Stage, and approved for promotion to Production, the same build artifact is deployed to the Production environment.

Only the Full Stack Code pipeline type supports code scanning, function testing, UI testing, and experience audit.

Deployment process deployment-process

All Cloud Service deployments follow a rolling process to ensure zero downtime. See How Rolling Deployments Work to learn more.

NOTE

The Dispatcher cache is wiped out on each deployment. It is subsequently “warmed up” before the new publish nodes accept traffic.

Deploy your code with Cloud Manager in AEM as a Cloud Service deploying-code-with-cloud-manager

Once you have configured your production Pipeline including repository, environment, and testing environment, you are ready to deploy your code.

Log into Cloud Manager at my.cloudmanager.adobe.com and select the appropriate organization.
On the My Programs console, click the program for which you want to deploy code.
On the Overview page, in the call-to-action area, click Deploy.
On the Deploy to production page, click Build.

The build process deploys your code through the following three ordered phases:

Stage deployment phase
Stage testing phase
Production deployment phase

TIP

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

Stage deployment phase stage-deployment

The Stage Deployment phase involves the following steps:

Stage deployment step

Description

Validation

Ensures that the pipeline is configured to use the currently available resources. for example, testing that the configured branch exists and that the environments are available.

Build & Unit Testing

Runs a containerized build process.
See Build Environment Details for details on the build environment.

Code Scanning

Evaluates the quality of your application code.
See Code Quality Testing for details on the testing process.

Build Images

This process converts content and Dispatcher packages from the Build step into Docker images. It also generates Kubernetes configurations based on those packages.

Deploy to Stage

The image is deployed to the staging environment in preparation for the Stage testing stage.

Stage Deployment

Stage testing phase stage-testing

The Stage testing phase involves the following steps:

Stage testing step

Description

Product Functional Testing

Cloud Manager pipeline executes tests that run against the stage environment.
See also Product Functional Testing.

Custom Functional Testing

This step in the pipeline is always executed and cannot be skipped. If the build does not produce a test JAR, the test automatically passes.
See also Custom Functional Testing.

Custom UI Testing

An optional feature that automatically runs UI tests created for custom applications.
UI tests are Selenium-based and packaged in a Docker image to offer flexibility in language and frameworks. This approach lets you use Java and Maven, Node and WebDriver.io, or any Selenium-based framework or technology.
See also Custom UI Testing.

Experience Audit

This step in the pipeline is always executed and cannot be skipped. As a production pipeline is executed, an experience audit step is included after custom functional testing that runs the checks.

The pages that are configured are submitted to the service and evaluated.
The results are informational and show the scores and the change between the current and previous scores.
This insight is valuable to determine if there is a regression that is introduced with the current deployment.

See Understanding Experience Audit results.

Stage Testing

Production deployment phase production-deployment

The process for deploying to production topologies differs slightly to minimize the impact on visitors to an AEM site.

Production deployments generally follow the same steps as previously described, but in a rolling manner. These steps include the following:

Deploy AEM packages to author.
Detach dispatcher1 from the load balancer.
Deploy AEM packages to publish1 and the Dispatcher package to dispatcher1, flush Dispatcher cache.
Put dispatcher1 back into the load balancer.
When dispatcher1 is back in service, detach dispatcher2 from the load balancer.
Deploy AEM packages to publish2 and the Dispatcher package to dispatcher2, flush Dispatcher cache.
Put dispatcher2 back into the load balancer.

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

Production Deployment phase

Timeouts during a deployment timeouts

The following steps time out if they are left waiting for user feedback during a deployment:

Step

Timeout

Code Quality Testing

14 days

Security Testing

14 days

Performance Testing

14 days

Application for Approval

14 days

Schedule Production Deployment

14 days

CSE Support

14 days

Re-execute a production deployment reexecute-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 been completed, regardless of the type of completion (for example, canceled or unsuccessful). Re-execution creates a new execution using the same pipeline consisting of the following three steps:

Validation - The same validation that occurs during a normal pipeline execution.
Build - In the context of a re-execution, the build step copies artifacts and does not actually execute a new build process.
Production deployment - 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.

The Re-execute option in the pipeline overview window

NOTE

In a re-execution, the build step is labeled in the UI to reflect that it is copying artifacts, not re-building.

Limitations limitations

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

Re-execute API reexecute-API

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

Trigger a re-execution reexecute-deployment-api

To trigger a re-execution, make a PUT request to the HAL Link https://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 cannot be restarted from that step.

This link is only available for the production deploy step.

 {
  "_links": {
    "https://ns.adobe.com/adobecloud/rel/pipeline/logs": {
      "href": "/api/program/4/pipeline/1/execution/953671/phase/1575676/step/2983530/logs",
      "templated": false
    },
    "https://ns.adobe.com/adobecloud/rel/pipeline/reExecute": {
      "href": "/api/program/4/pipeline/1/execution?stepId=2983530",
      "templated": false
    },
    "https://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. The actual value should always be read from the HAL link and not generated.

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

Identify a re-execute execution identify-reexecution

The system identifies re-executions by setting the trigger field to the value RE_EXECUTE.

recommendation-more-help

fbcff2a9-b6fe-4574-b04a-21e75df764ab