Karmada-Operator

A Karmada Operator based on the K8s Operator model built by DaoCloud, Karmada Operator(Kubernetes Armada operator) simplifies the deployment, operation and maintenance of Karmada.

TL;DR

Switch to the root directory of the repo.

helm install karmada-operator -n karmada-operator-system --create-namespace --dependency-update ./charts/karmada-operator

Prerequisites

• Kubernetes 1.16+
• helm v3+

Demo

Installing the Chart

To install the chart with the release name karmada-operator in namespace karmada-operator-system:

• local installation

Switch to the root directory of the repo.

helm install karmada-operator -n karmada-operator-system --create-namespace --dependency-update ./charts/karmada-operator

Tip: If you need to modify values.yaml, please refer to Configuration

• remote installation

First, add the Karmada-Operator chart repo to your local repository.

$ helm repo add karmada https://release.daocloud.io/chartrepo/karmada
$ helm repo list
NAME            URL
karmada   https://release.daocloud.io/chartrepo/karmada

With the repo added, available charts and versions can be viewed.

$ helm search repo karmada
NAME                    	CHART VERSION	APP VERSION	DESCRIPTION
karmada/karmada-operator	0.0.5        	0.0.5      	A Helm chart for karmada-operator

Install the chart and specify the version to install with the --version argument. Replace --version=<x.x.x> with your desired version. such as the above karmada/karmada-operator chart version 0.0.5 , so you can use --version=0.0.5.

$ helm --namespace karmada-operator-system upgrade -i karmada-operator karmada/karmada-operator --version=<x.x.x> --create-namespace
Release "karmada-operator" does not exist. Installing it now.
NAME: karmada-operator
LAST DEPLOYED: Thu Aug 11 15:24:01 2022
NAMESPACE: karmada-operator-system
STATUS: deployed
REVISION: 1
TEST SUITE: None
NOTES:
Thank you for installing karmada-operator.

Your release is named karmada-operator.

To learn more about the release, try:

  $ helm status karmada-operator -n karmada-operator-system
  $ helm get all karmada-operator -n karmada-operator-system

• example there is an example to install a karmada instance on current cluster.

Tip: List all releases using helm list

Create a KarmadaDeployment

After installing karmada-operator, use cr to create karmadaDeployment

Create cr using below command in the cluster where the karmada-operator install

Tip:

• If no secretRef is specified in cr, the karmada instance is installed in the cluster where karmada-operator is located
• If no namespace is specified in cr, the default install namespace is the same as the karmadaDeployment name

#deploy KarmadaDeployment demo-kmd in the cluster where the karmada-operator install 
$ kubectl apply -f https://github.com/DaoCloud/karmada-operator/blob/main/examples/karmadaDeployment.yaml

The process of deploying karmada may take a few minutes, check the operation of karmada's components

$ kubectl -n demo-kmd get pod
NAME                                                        READY   STATUS    RESTARTS      AGE
etcd-0                                                      1/1     Running   0             19m
karmada-demo-kmd-aggregated-apiserver-6fd745748-hjbq7       1/1     Running   0             19m
karmada-demo-kmd-apiserver-429bfb7c1-6fkrk                  1/1     Running   0             19m
karmada-demo-kmd-controller-manager-7b8f5699c-mvx8s         1/1     Running   3 (21m ago)   21m
karmada-demo-kmd-controller-manager-7b8f5699c-7fc8c         1/1     Running   2 (19m ago)   19m
karmada-demo-kmd-kube-controller-manager-9b56855fdc-699c5   1/1     Running   0             19m
karmada-demo-kmd-scheduler-685b997cb7-9467w                 1/1     Running   0             19m
karmada-demo-kmd-scheduler-685b997cb7-85c84                 1/1     Running   0             20m
karmada-demo-kmd-webhook-85c84d84c7-g6t9n                   1/1     Running   0             19m

ok, karmada installation is complete.

Create multiple KarmadaDeployments

karmada-operator supports creating multiple karmadaDeployment instances in the same cluster,You can deploy multiple karmada instances multiple times using the cr of KarmadaDeployment with different content.

List multiple KarmadaDeployments：

$ kubectl get kmd
NAME         MODE   PHASE       STATUS   AGE
demo-kmd     Helm   Completed    true    2m42s
demo-kmd-1   Helm   Completed    true    2m57s
$ kubectl get pod -n demo-kmd-1
NAME                                                        	READY   STATUS    RESTARTS      AGE
etcd-0                                                      	1/1     Running   0             14m
karmada-demo-kmd-1-aggregated-apiserver-9b56855fd-gwrmf         1/1     Running   0             14m
karmada-demo-kmd-1-apiserver-6f9bbcb9c-vmxbq                    1/1     Running   0             14m
karmada-demo-kmd-1-controller-manager-5d6777b75-7rmq8           1/1     Running   2 (17m ago)   17m
karmada-demo-kmd-1-controller-manager-5d6777b75-g6xzd           1/1     Running   2 (16m ago)   16m
karmada-demo-kmd-1-kube-controller-manager-76b94fb97c-6lqwv     1/1     Running   0             14m
karmada-demo-kmd-1-scheduler-797b7b787b-klcs4                   1/1     Running   0             14m
karmada-demo-kmd-1-scheduler-797b7b787b-r829t                   1/1     Running   0             15m
karmada-demo-kmd-1-webhook-755d649cb4-wbx5h                     1/1     Running   0             15m
$ kubectl get pod -n demo-kmd
NAME                                                        READY   STATUS    RESTARTS      AGE
etcd-0                                                      1/1     Running   0             19m
karmada-demo-kmd-aggregated-apiserver-6fd745748-hjbq7       1/1     Running   0             19m
karmada-demo-kmd-apiserver-429bfb7c1-6fkrk                  1/1     Running   0             19m
karmada-demo-kmd-controller-manager-7b8f5699c-mvx8s         1/1     Running   3 (21m ago)   21m
karmada-demo-kmd-controller-manager-7b8f5699c-7fc8c         1/1     Running   2 (19m ago)   19m
karmada-demo-kmd-kube-controller-manager-9b56855fdc-699c5   1/1     Running   0             19m
karmada-demo-kmd-scheduler-685b997cb7-9467w                 1/1     Running   0             19m
karmada-demo-kmd-scheduler-685b997cb7-85c84                 1/1     Running   0             20m
karmada-demo-kmd-webhook-85c84d84c7-g6t9n                   1/1     Running   0             19m

Export Karmada KubeConfig

You can get karmada kubeconfig to view karmada instance information

$ KARMADA_CONFIG=$(kubectl get secret  -n ${your_karmada_operator_namespace} $(kubectl get kmd demo-kmd -o jsonpath='{.status.secretRef.name}') -o jsonpath='{.data.kubeconfig}')
$ echo $KARMADA_CONFIG | base64 -d > karmada-apiserver.config

You can export KUBECONFIG for easy login the karmada instance

export KUBECONFIG=./karmada-apiserver.config

We can simply test karmada-apiserver kubeconfig ,such as List namespaces

$ kubectl --kubeconfig karmada-apiserver.config get ns
NAME              STATUS   AGE
default           Active   124m
demo-kmd          Active   89m
karmada-cluster   Active   89m
kube-node-lease   Active   124m
kube-public       Active   124m
kube-system       Active   124m

Simple Karmada Demo

We can test karmada's multi-cloud capabilities with a simple demo

Join Clusters

1. Use kubectl karmada join cluster to Karmada.

Currently you need to download karmadactl to join cluster

Karmada provides kubectl-karmada plug-in download service since v1.2.1. You can choose proper plug-in version which fits your operator system form karmada release.

Take v1.2.1 that working with linux-arm64 os as an example:

$ wget https://github.com/karmada-io/karmada/releases/download/v1.2.1/karmadactl-linux-arm64.tgz

$ tar -zxf karmadactl-linux-arm64.tgz

$ cp karmadactl /usr/local/bin

then we join member1 and member2 cluster into karmada

--cluster-kubeconfig is your members kubeconfig.

--kubeconfig is your karmada apiserver kubeconfig

$ karmadactl --kubeconfig ${your_karmada_apiserver_config} join member1 --cluster-kubeconfig=${your_member1_kubeconfig}
$ karmadactl --kubeconfig ${your_karmada_apiserver_config} join member2 --cluster-kubeconfig=${your_member2_kubeconfig}

2. Show members of karmada

$ kubectl  --kubeconfig ${your_karmada_apiserver_config} get clusters
NAME         VERSION    MODE   READY   AGE
member1      v1.21.12   Push   True    2m53s
member2      v1.22.6    Push   True    21s

Propagate a deployment by Karmada

1. Create nginx deployment in Karmada

First, create a deployment named nginx:

# create a deployment name nginx
$ kubectl create -f https://github.com/DaoCloud/karmada-operator/blob/main/examples/nginx/deployment.yaml --kubeconfig ${your_karmada_apiserver_config}

2. Create PropagationPolicy that will propagate nginx to member cluster

Then, we need to create a policy to propagate the deployment to our member cluster.

# create a PropagationPolicy 
$ kubectl create -f https://github.com/DaoCloud/karmada-operator/blob/main/examples/nginx/propagationpolicy.yaml --kubeconfig ${your_karmada_apiserver_config}

3. Check the deployment status from Karmada

You can check deployment status from Karmada, don't need to access member cluster:

$ kubectl get deployment --kubeconfig ${your_karmada_apiserver_config}
NAME    READY   UP-TO-DATE   AVAILABLE   AGE
nginx   2/2     2            2           20s

Configuration

Global parameters

Name	Description	Value
global.imageRegistry	Global Docker image registry	""
global.imagePullSecrets	Global Docker registry secret names as an array	[]

Common parameters

Name	Description	Value
controllerManager.labels	deployment labels of the karmada-operator-controller-manager	"app: karmada-operator-controller-manager"
controllerManager.replicaCount	replicas of the karmada-operator-controller-manager deployment	2
controllerManager.podAnnotations	pod Annotations of the karmada-operator-controller-manager	{}
controllerManager.podLabels	pod Labels of the karmada-operator-controller-manager	{}
controllerManager.image.registry	Image registry of the karmada-operator-controller-manager	release.daocloud.io
controllerManager.image.repository	Image repository of the karmada-operator-controller-manager	kairship/karmada-operator-controller-manager
controllerManager.image.tag	Image tag of the karmada-operator-controller-manager	"v0.0.1"
controllerManager.image.pullPolicy	Image registry of the karmada-operator-controller-manager	"IfNotPresent"
controllerManager.image.pullSecrets	Image pullSecrets of the karmada-operator-controller-manager	[]
controllerManager.resources	resources of the karmada-operator-controller-manager	{}
controllerManager.nodeSelector	nodeSelector of the karmada-operator-controller-manager	{}
controllerManager.affinity	affinity of the karmada-operator-controller-manager	{}
controllerManager.tolerations	tolerations of the karmada-operator-controller-manager	key: node-role.kubernetes.io/master operator: Exists
controllerManager.kubeconfigPath	kubeconfig Path of the karmada-operator-controller-manager	"/root/.kube"
controllerManager.localKubeconfig	Image registry of the karmada-operator-controller-manager	"true"

Uninstalling

Uninstalling the KarmadaDeployment

Deleting karmadaDeployment is a dangerous operation and needs to be deleted carefully. Please delete it according to the following process.

Only Delete KarmadaDeployment CR

When you want to remove CR but keep the instance on the environment，you can execute the following command

# patch disable-cascading-deletion label
$ kubectl label --overwrite kmd demo-kmd karmada.install.io/disable-cascading-deletion="true"
# disable cascade delete KarmadaDeployment
$ kubectl delete kmd demo-kmd -n demo-kmd

Delete KarmadaDeployment CR and Instance

When you want to remove CR and the instance in your environment，you can execute the following command

# cascade delete KarmadaDeployment
$ kubectl delete kmd demo-kmd -n demo-kmd

Uninstalling the Karmada-Operator

To uninstall/delete the karmada-operator helm release in namespace karmada-operator-system:

helm uninstall karmada-operator -n karmada-operator-system

The command removes all the Kubernetes components associated with the chart and deletes the release.

kubectl delete ns karmada-operator-system