EDA Server Operator

A Kubernetes operator for Kubernetes built with Operator SDK and Ansible for deploying and maintaining the lifecycle of your EDA Server application.

Overview

This operator is meant to provide a more Kubernetes-native installation method for EDA Server via an EDA Custom Resource Definition (CRD). In the future, this operator will grow to be able to maintain the full life-cycle of an EDA Server deployment. Currently, it can handle fresh installs and upgrades.

Contributing

Please visit our contributing guide which has details about how to set up your development environment.

Prerequisites

Install the kubernetes-based cluster of your choice:
Deploy AWX using the awx-operator
Create an OAuth2 token for your user in the AWX UI

Install the EDA Server Operator

Before you begin, you need to have a k8s cluster up. If you don't already have a k8s cluster, you can use minikube to start a lightweight k8s cluster locally by following these minikube test cluster docs.

Once you have a running Kubernetes cluster, you can deploy EDA Server Operator into your cluster using Kustomize. Since kubectl version 1.14 kustomize functionality is built-in (otherwise, follow the instructions here to install the latest version of Kustomize: https://kubectl.docs.kubernetes.io/installation/kustomize/)

First, create a file called kustomization.yaml with the following content:

apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
resources:
  - config/default

# Set the image tags to match the git version from above
images:
  - name: quay.io/ansible/eda-server-operator
    newTag: 0.0.1

# Specify a custom namespace in which to install EDA
namespace: eda

You can use kustomize directly to dynamically modify things like the operator deployment at deploy time. For more info, see the kustomize install docs.

Install the manifests by running this:

$ kubectl apply -k .

Check that your operator pod is running, this may take about a minute.

$ kubectl get pods

Deploy EDA

EDA is designed to be used alongside the AWX project to trigger automation jobs in AWX. There is some configuration that needs to be done in AWX first so that EDA can AWX.

Create an access token in your AWX instance using these docs.
Now that your operator pod is up and running, you can create an EDA Server resource by applying the following YAML:

Warning At the moment, If you are using custom image eda-server and eda-ui images that are in a private registry, you will need to create and configure a pull secret.

# eda.yaml
apiVersion: eda.ansible.com/v1alpha1
kind: EDA
metadata:
  name: my-eda
spec:
  automation_server_url: https://awx-host

Now apply this yaml

$ kubectl apply -f eda.yaml

If you are using Openshift, you can take advantage of automatic Route configuration an EDA custom resource like this:

apiVersion: eda.ansible.com/v1alpha1
kind: EDA
metadata:
  name: eda-demo
spec:
  automation_server_url: https://awx-host
  service_type: ClusterIP
  ingress_type: Route
  image_pull_secrets:
    - pull_secret_name

Advanced Configuration

Deploying a specific version of EDA

There are a few variables that are customizable for eda the image management.

Name	Description	Default
image	Path of the image to pull	quay.io/ansible/eda-server
image_version	Image version to pull	main
image	Path of the image to pull	quay.io/ansible/eda-ui
image_version	Image version to pull	latest
image_pull_policy	The pull policy to adopt	IfNotPresent
image_pull_secrets	The pull secrets to use	None
redis_image	Path of the image to pull	redis
redis_image_version	Image version to pull	latest
postgres_image	Path of the image to pull	postgres
postgres_image_version	Image version to pull	latest

Example of customization could be:

---
spec:
  ...
  image: myorg/my-custom-eda
  image_version: latest
  image_web: myorg/my-custom-eda
  image_web_version: latest
  image_pull_policy: Always
  image_pull_secrets:
    - pull_secret_name

Note: The *_image and *_image_version variables are intended for local mirroring scenarios. Please note that using a version of EDA other than the one bundled with the eda-server-operator is not supported. For the default values, check the main.yml file.

Configuring an image pull secret

docker login quay.io -u <user> -p <token>

Then, create a k8s secret from your .docker/config.json file. This pull secret should be created in the same namespace you are installing the EDA Operator.

kubectl create secret generic redhat-operators-pull-secret \
  --from-file=.dockerconfigjson=.docker/config.json \
  --type=kubernetes.io/dockerconfigjson

Add that image pull secret to your EDA spec

---
spec:
  image_pull_secrets:
    - redhat-operators-pull-secret

rooftopcellist/aap-eda-operator