Quarkus Microservices Social Net

Simple Net - Backend

Simple social Network Backend builded using quarkus 3.0.

Technologies

This projects uses the following technologies stack

Development Stack

• Quarkus 3.0
• Java 17

Infra Stack

• Postgres
• Crunchy Data Postgres Cluster
• Openshift or Kubernetes

Load Testing Stack

• Grafana
• Prometheus
• K6 Load Testing

Insight Analysis Stack

• Jupyter Hub
• Open Data Hub
• Pandas
• Scikit Learn

Interface

All the code capabilities can be access using a rest interface, the documentation of the REST could be found in the swagger available running each service in dev mode, the annotations combined with the swagger plugin will provide all the necessary documentation for the services.

Running

The project could be run using two main ways:

Development Env

In development mode is possible to simple use the quarkus combined with its dev services, making possible a minimal configuration environment.

To run it, it’s just necessary the following command:

quarkus dev

Production Env

The production env is a little more complicated, mainly because this project tries to provide a good scalability, this will be possible by making a deploy on a orchestrated environment. Where this environment could be a Openshift or a Kubernetes.

To install the systems and all its dependencies is possible by running the script deploy.sh where it will give the two options kubernetes or openshift. For the script to work as intended is necessary that a session with the orchestration platform was already open, and the logged user must have the permissions to create namespaces and make deploys.

To run it on a kubernetes, it’s just necessary the following command:

sh deploy kubernetes

To run it on a openshift, it’s just necessary the following command:

sh deploy openshift

Contributing

If you want to contribute with the project this can be adding any of the features below, or by fixing some issues on the project.

• Create and test the kubernetes deploy
• Add the automated tests
• Add a coverage test on the git flags
• Implement the feed using kafka
• Add a infinity span to cache the feed requests
• Implement the authentication using keycloak
• Add the secrets on the jupyter hub deploy