Issue 8: Testing and Deployment with Dockerized Image

[victorgrubio]

Description:

Conduct thorough testing of the backend API to ensure functionality, performance, and security. Deploy the backend application to production using the CI/CD pipeline. Monitor the application's performance and address any issues that arise.

Tasks:

Phase 1: Testing

1. Unit Testing:

   • Implement unit tests for the Flask application to verify individual components and functions.
   • Utilize unit testing frameworks like pytest or unittest to automate test execution.
   • Run unit tests regularly to ensure code quality and consistency.

2. Integration Testing:

   • Combine unit tests into integration tests to verify interactions between components.
   • Mock external dependencies to simulate real-world scenarios.
   • Run integration tests periodically to ensure system-level functionality remains intact.

3. End-to-End Testing:

   • Develop end-to-end tests that simulate user interactions with the API.
   • Use tools like Postman or automation frameworks to execute end-to-end tests.
   • Run end-to-end tests before each deployment to ensure the entire system operates smoothly.

Phase 2: Deployment

1. CI/CD Pipeline Integration:

   • Integrate the CI/CD pipeline with GCP Cloud Run to trigger deployments automatically.
   • Configure the pipeline to build, test, and deploy updated Docker images to Cloud Run.
   • Verify that the deployment process is automated and efficient.

2. Production Deployment:

   • Trigger the CI/CD pipeline for a production deployment.
   • Monitor the application's performance and resource usage in production.
   • Rollback to the previous deployment if any issues arise.

3. Monitoring and Logging:

   • Set up application monitoring tools to track key metrics like request latency, error rates, and resource consumption.
   • Implement logging mechanisms to capture relevant events and errors.
   • Analyze monitoring data and logs to identify potential issues and optimize performance.