uuid: - value: 461af26d-2006-48e4-9aec-6eb2db31d4ef langcode: - value: en type: - target_id: daily_email target_type: node_type target_uuid: 8bde1f2f-eef9-4f2d-ae9c-96921f8193d7 revision_timestamp: - value: '2025-05-11T09:00:34+00:00' revision_uid: - target_type: user target_uuid: b8966985-d4b2-42a7-a319-2e94ccfbb849 revision_log: { } status: - value: true uid: - target_type: user target_uuid: b8966985-d4b2-42a7-a319-2e94ccfbb849 title: - value: | Deployments with your CI pipeline created: - value: '2023-08-22T00:00:00+00:00' changed: - value: '2025-05-11T09:00:34+00:00' promote: - value: false sticky: - value: false default_langcode: - value: true revision_translation_affected: - value: true path: - alias: /daily/2023/08/22/deployments-with-your-ci-pipeline langcode: en body: - value: |

You have a CI pipeline in your project.

Every time you push a commit, the CI pipeline runs and performs its checks.

It runs the automated tests and verifies they pass, statically analyses the code to identify any issues and validates the code follows the correct coding style and standards.

Everything passes.

What next?

If the pipeline passes, your change is deployable.

So, why not extend the pipeline to deploy the change once the checks pass?

If the checks don't pass, don't deploy.

It could be as simple as pushing the code to an S3 bucket, a separate Git branch or repository for managing deployments, or creating an artifact like a Docker image.

Instead of waiting for someone to do this manually, remove a step and automate it within the pipeline.

The sooner it's deployed, the sooner it provides value for your application's users.

format: full_html processed: |

You have a CI pipeline in your project.

Every time you push a commit, the CI pipeline runs and performs its checks.

It runs the automated tests and verifies they pass, statically analyses the code to identify any issues and validates the code follows the correct coding style and standards.

Everything passes.

What next?

If the pipeline passes, your change is deployable.

So, why not extend the pipeline to deploy the change once the checks pass?

If the checks don't pass, don't deploy.

It could be as simple as pushing the code to an S3 bucket, a separate Git branch or repository for managing deployments, or creating an artifact like a Docker image.

Instead of waiting for someone to do this manually, remove a step and automate it within the pipeline.

The sooner it's deployed, the sooner it provides value for your application's users.

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