EDA LoadBalancer Operator TESTING PUSPOSES NO PRODUCTION

This repository contains an operator developed for testing purposes. It is designed to manage the exposure of EDA (Event-Driven Ansible) services running in environments like K3s, mminikube, or kind, where pods are typically assigned ClusterIP addresses by default.

Problem Statement

When running EDA on environments such as K3s, minikube, or kind, the pods are often assigned ClusterIP addresses. This limits the accesibility to the cluster itself, making it hard to expose these services to other machines on the network. Without proper exposure (e.g., through port-forward or LoadBalancer services), external systems cannot easily interact with these pods.

The Image where is the Operator config

 ```bash
 docker pull fermendy/my-eda-worker-operatos:latest
 ```

Solution

This operator automatically manages the exposure of specific EDA pods thanks to the ARP of MetalLB. The operator monitors the namespace eda (or the one indicated in the deployment file) and automatically changes the service type from ClusterIP to LoadBalancer for any newly created pod that matches the naming pattern activation-job-*. The operator ensures that these services are accessible on port 80 from other machines on the network. Additionally, when the associated pod or rulebook is deleted, the corresponding service is automatically removed.

Key Features

Automatic Service Update: Converts services of EDA pods named activation-job-* from ClusterIP to LoadBalancer.
Port Configuration: The exposed port is automatically set to 80 for external access.
Auto Cleanup: The service is deleted automatically when the corresponding pod is removed.

Use Case

This operator is particularly useful when running EDA in a K3s cluster and needing to receive webhooks or interact with services from other machines on the network. It simplifies the network configuration by automatically exposing services as LoadBalancer without requiring manual intervention.

Deployment

To deploy the operator in your cluster:

Download the Deployment YAML:
- The deployment file is named eda-lb-deployment.yml.
Apply the Deployment:
- Use the following command to deploy the operator:
```
kubectl apply -f eda-lb-deployment.yml
```