Create CI pipeline

.github/workflows/ci.yml

@@ -0,0 +1,25 @@
+name: 'Continuous Integration'
+
+on: [push, pull_request]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.9'
+
+      - name: Install dependencies
+        run: |
+          pip install -r requirements.txt -r requirements-dev.txt -r requirements-test.txt
+
+      - name: Run model tests
+        run: make model-test
+
+      - name: Run API tests
+        run: make api-test

docs/challenge.md

@@ -122,3 +122,12 @@ The API is deployed as a Cloud Run Service that exposes a public endpoint. In or
 After the deployment is completed, the API is available at https://delay-model-dpmrk4cwxq-uw.a.run.app, and the prediction endpoint is available at https://delay-model-dpmrk4cwxq-uw.a.run.app/predict. We can test the service using Postman or run the provided stress test.
 
 The results of the stress test are an error rate of 0%, an average response time of 343ms, a maximum response time of 743ms and the API is able to respond to 87.69 requests per second.
+
+
+## CI/CD Pipeline
+
+On this final step, the goal is to setup a proper CI/CD pipeline.
+
+The CI workflows focus on running the tests and assesing the quality of the code each time there's a push to the repository, with the goal of detecting bugs earlier, correcting code faster and ensuring good code quality practices.
+
+The CD workflows focus on training the model, deploying the API and running the stress testing against it. These workflows only run when there's a push to the `main`, `develop` or `release` branches on the repository.cua