Hexagon codebase containing real world examples (CRUD, auth, advanced patterns, etc) that adheres to the RealWorld spec and API.

Demo

RealWorld

This codebase was created to demonstrate a fully fledged fullstack application built with Hexagon including CRUD operations, authentication, routing, pagination, and more.

We've gone to great lengths to adhere to the Hexagon community styleguides & best practices.

For more information on how to this works with other frontends/backends, head over to the RealWorld.

How it works

The project has a Gradle multi-module layout. Deployment code is located at the deploy folder. The goal is to code a full stack application providing a module for the back-end, the front-end (TBD) and the Mobile application (TBD).

Docker Compose is used to build images for each module (if applies) and publish them to the Docker Registry.

Getting started

The source code has the bare minimum formatting rules inside the .editorconfig file.

Gradle is the tool used to automate build tasks locally.

For image creation, Docker builds binaries (using Gradle) in a first stage. The outcome of this stage is used to create the application image (check backend/Dockerfile for more details).

Docker Compose is used to build all modules (from their Dockerfile) and run them inside containers.

To be sure that everything works before pushing changes, you can link the deploy/pre-push.sh file to the .git/hooks directory:

ln -s $(pwd)/deploy/pre-push.sh .git/hooks/pre-push

However, you can use git push --no-verify to skip these checks.

Useful build commands:

• Build: ./gradlew installDist. Generates:

  • Application directory: backend/build/install/backend
  • Packaged application: backend/build/distributions
  • Web application: backend/build/libs/ROOT.war
  • Single JAR with dependencies: backend/build/libs/<module>-all-<version>.jar
  • Application specifications: backend/build/reports/cucumber

• Rebuild: ./gradlew clean installDist

• Documentation: ./gradlew doc. Creates:

  • API documentation: backend/build/dokka/backend
  • Coverage report: backend/build/reports/jacoco/test/html

• Generate everything (binaries and documentation): ./gradlew all

• Run: ./gradlew run

• Watch: ./gradlew --no-daemon --continuous runService

• Build local container images: docker-compose build

• Start application inside containers: docker-compose up -d

Testing

The HTTPie and jq tools are used for testing the application manually in some scripts.

Postman is also used to perform requests interactively: backend/src/test/resources/postman/*.

Continuous Integration

The build pipeline is implemented using Travis CI, it takes care of checking the tests (including Postman collection tests) and the following tasks:

Release

Tagging of source code and container images should be done upon Pull Request merge on live branches. This is still to be implemented by the CI/CD pipeline using Travis.

Publish

Published artifacts are Docker images. They are published to a Docker registry. For Minikube and Docker Compose, the local image store is used instead a registry.

Build repository container images: registry="<repository>" docker-compose build The <repository> value MUST end with '/'. Ie: registry="example.com/" docker-compose build

Deployment

To deploy the application services. The services' images must be published in their corresponding repositories.

Minikube

Prior to deploying to Minikube, VirtualBox and HTTPie must be installed also. The deployment script has to be run from project root: minikube.sh it initializes a Minikube instance and deploy the application service.

You can find more information inside the script file.

Heroku

To deploy the WAR in Heroku. First setup the Heroku CLI tool and project:

heroku login
heroku plugins:install heroku-cli-deploy
heroku create realworld

And then build and upload the binary:

gw clean assemble
heroku war:deploy backend/build/libs/ROOT.war --app realworld

• Add npm to GitHub Actions cache
• Publish in Docker Registry
• Deploy on GCP
• Add requests' bodies validation returning as many errors as wrong fields
• Code stress tests using Gatling.io against local, container, or deployed service
• Generate a documentation site (use Orchid or JBake)
• Create native executable using GraalVM
• Document code (Dokka)
• Publish front end in GitHub pages
• Migrate readme.md API documentation to Swagger
• Add unit tests to cover all code (using mocks), this may shape the future hexagon_test module