Because we are running our application within containers, we need a way to quickly iterate and make changes to them. Some of our tactics in 06-building-container-images help here (e.g. protecting the layer cache) so that images build quickly, but we can do better.

We want our development environment to have the following attributes:

1. Easy/simple to set up: Using docker compose, we can define the entire environment with a single yaml file. To get started, team members can issue a single command make compose-up-build or make compose-up-build-debug depending if they want to run the debugger or not.

2. Ability to iterate without rebuilding the container image: In order to avoid having to rebuild the container image with every single change, we can use a bind mount to mount the code from our host into the container filesystem. For example:

      - type: bind
        source: ../05-example-web-application/api-node/
        target: /usr/src/app/

3. Automatic reloading of the application:

   • React Client: We are using Vite for the react client which handles this handles this automatically
   • Node API: We added nodemon as a development dependency and specify the Docker CMD to use it
   • Golang API: We added a utility called air (https://github.com/cosmtrek/air) within Dockerfile.dev which watches for changes and rebuild the app automatically.

4. Use a debugger:

   • React Client: For a react app, you can use the browser developer tools + extensions to debug. I did include react-query-devtools to help debug react query specific things. It is also viewed from within the browser.

   • Node API: To enable debugging for a NodeJS application we can run the app with the --inspect flag. The debug session can then be accessed via a websocket on port 9229. The additional considerations in this case are to specify that the debugger listen for requests from 0.0.0.0 (any) and to publish port 9229 from the container to localhost.

   • Golang API: To enable remote debugging for a golang application I installed a tool called delve (https://github.com/go-delve/delve) within ./api-golang/Dockerfile.dev. We then override the command used to run the container to use this tool (see: docker-compose-debug.yml)

     ---

     These modifications to the configuration (overridden commands + port publishing) are specified in docker-compose-debug.yml. By passing both docker-compose-dev.yml AND docker-compose-debug.yml to the docker compose up command (See: make compose-up-debug-build) Docker combines the two files, taking the config from the latter and overlaying it onto the former.

     Both ./api-golang/README.md and ./api-node/README.md show a launch.json configuration you can use to connnect to these remote debuggers using VSCode. The key setting is substitutePath such that you can set breakpoints on your local system that get recognized within the container.

5. Executing tests: We also need the ability to execute our test suites within containers. Again, we can create a custom docker-compose-test.yml overlay which modifies the container commands to execute our tests. To build the api images and execute their tests, you can execute make run-tests which will use the test compose file along with the dev compose file to do so.

See .github/workflows/image-ci.yml for a basic GitHub Action workflow that builds, scans, tags, and pushes a container image.

It leverages a few publicly available actions from the marketplace:

1. https://github.com/marketplace/actions/docker-metadata-action (generates tags for the container images)
2. https://github.com/marketplace/actions/docker-login (logs into DockerHub)
3. https://github.com/marketplace/actions/build-and-push-docker-images (builds and pushes the images)
4. https://github.com/marketplace/actions/aqua-security-trivy (scans the images for vulnerabilities)

If you want to build out more advanced CI workflows I recommend looking at Bret Fisher's Automation with Docker for CI/CD Workflows repo (https://github.com/BretFisher/docker-cicd-automation). It has many great examples of the types of things you might want to do with Docker in a CI/CD pipeline!