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Continuous Integration

Vortex offers continuous integration configurations for GitHub Actions and CircleCI providers that allows to automate the process of building, testing, and deploying your site.

The workflow configuration is identical for both continuous integration providers. You would need to choose one of them and follow the setup instructions.

The continuous integration pipeline consists of multiple jobs executed in a containerized environment to ensure consistency across runs.

Trigger Conditions​

The continuous integration pipeline is triggered by:

  • Push events to the following branches:
    • production,
    • main,
    • master,
    • develop
    • release/**,
    • hotfix/**,
    • project/**
  • Pull requests to these branches
  • Scheduled runs for automatic database caching

Workflow Structure​

1. Database​

  • Runs in a drevops/ci-runner runner container
  • Downloads the latest DB version based on a caching strategy
  • Caches database dumps to speed up the follow-up runs

2. Build​

  • Runs after the database job
  • Uses Docker Compose to set up the environment
  • Provisions a website
  • Lints code (only on the first instance)
  • Runs unit tests
  • Runs BDD tests
  • Generates code coverage reports
  • Collects and stores test results and artifacts

3. Deployment​

  • Runs after successful completion of a previous build job
  • Uses the built codebase without development dependencies from the build step
  • Adds required secrets and environment variables
  • Triggers a deployment using a router script

Caching Strategy​

Database is downloaded overnight and cached so that the next continuous integration run on the same day uses the cached database dump.

By default, the database is cached per-branch for 24 hours. If cache is not available, the fallback default branch is used.

note

Database caching is a very powerful feature that allows to speed up the continuous integration runs on large projects with a lot of data.

In case of a project with a large database >1GB, the database import itself may take a long time, so it may be worth looking into either packaging the database dump into a container image (overnight) or using a sanitized database dump with only the required data for the tests.

Vortex supports both creating and using a database container image with embedded data. You may use MariaDB data container for Drupal with database captured as Docker layers to create an initial database image.

There are other tools also available for this purpose, such as Drush GDPR Dumper that allows to remove data from the database dump during Drush database export command without the need for an intermediate database import step.