CI/CD Automation Scripts

The project at screenly/balena-prometheus-exporter does not currently have a built CI/CD pipeline established. This limits automated deployment and integration processes for code changes.

Next Steps:

To implement CI/CD automation, consider the following steps and recommendations:

1. Set Up a CI/CD Tool: Choose a CI/CD platform such as GitHub Actions, GitLab CI, Travis CI, or CircleCI.

2. Create Configuration Files: Depending on the selected CI/CD tool, create a configuration file in the root directory of the repository.

   For example, using GitHub Actions, create a file named .github/workflows/ci.yml:

   name: CI Pipeline
   
   on:
     push:
       branches:
         - main
   
   jobs:
     build:
       runs-on: ubuntu-latest
   
       steps:
         - name: Checkout code
           uses: actions/checkout@v2
   
         - name: Set up Python
           uses: actions/setup-python@v2
           with:
             python-version: '3.10'
   
         - name: Install dependencies
           run: |
             python -m pip install --upgrade pip
             pip install -r requirements.txt
   
         - name: Run tests
           run: |
             python -m unittest discover -s tests
   

3. Add Docker Support: Given that the project relies on Docker, include steps in the CI/CD process to build and push Docker images to a container registry.

   Extend the example above to include Docker build and push commands:

         - name: Build Docker image
           run: |
             docker build -t yourusername/balena-exporter .
   
         - name: Log in to Docker Hub
           run: echo "${{ secrets.DOCKER_PASSWORD }}" | docker login --username yourusername --password-stdin
   
         - name: Push Docker image
           run: |
             docker push yourusername/balena-exporter
   

4. Environment Handling: Handle environment variables securely. In GitHub Actions, you can add them as secrets under repository settings. This can include BALENA_TOKEN and CRAWL_INTERVAL.

5. Testing: Utilize the existing unit tests defined in tests/test_exporter.py to validate the functionality. Ensure the tests are invoked in the CI process:

   import unittest
   from main import BalenaCollector
   
   class TestBalenaCollector(unittest.TestCase):
       def setUp(self):
           self.collector = BalenaCollector()
   
       def test_collect(self, mock_metrics):
           with mock.patch.object(self.collector, "get_balena_fleets") as mock_fleets:
               mock_fleets.return_value = ["fleet1", "fleet2"]
               mock_metrics.side_effect = [("test_fleet", 3), ("test_fleet", 3)]
   
               result = list(self.collector.collect()[0].samples)
               expected = [('balena_devices_online', {'fleet_name': 'test_fleet'}, 3),
                           ('balena_devices_online', {'fleet_name': 'test_fleet'}, 3)]
   
               result = [(s.name, s.labels, s.value) for s in result]
   
               self.assertEqual(result, expected)
   
   if __name__ == "__main__":
       unittest.main()
   

By following these steps, a fully automated CI/CD pipeline can be established for the screenly/balena-prometheus-exporter project, ensuring efficient integration and deployment processes.

Source:

• Dockerfile
• README.md
• main.py
• requirements.txt
• tests/test_exporter.py