Kubernetes Cluster API – Provision workload clusters on AWS

The past few months I have been following the progress of the Kubernetes Cluster API which is part of the Kubernetes SIG (special interest group) Cluster-Lifecycle because they made good progress and wanted to try out the AWS provider version to deploy Kubeadm clusters. There are multiple infrastructure / cloud providers available which can be used, have a look at supported providers.

RedHat has based the Machine API Operator for the OpenShift 4 platform on the Kubernetes Cluster API and forked some of the cloud provider integrations but in OpenShift 4 this has a different use-case for the cluster to managed itself without the need of a central management cluster. I actually like RedHat’s concept and adaptation of the Cluster API and I hope we will see something similar in the upstream project.

Bootstrapping workload clusters are pretty straight forward but before we can start with deploying the workload cluster we need a central Kubernetes management cluster for running the Cluster API components for your selected cloud provider. In The Cluster API Book for example they use a KinD (Kubernetes in Docker) cluster to provision the workload clusters.

To deploy the Cluster API components you need the clusterctl (Cluster API) and clusterawsadm (Cluster API AWS Provider) command-line utilities.

curl -L https://github.com/kubernetes-sigs/cluster-api/releases/download/v0.3.14/clusterctl-linux-amd64 -o clusterctl
chmod +x ./clusterctl
sudo mv ./clusterctl /usr/local/bin/clusterctl
curl -L https://github.com/kubernetes-sigs/cluster-api-provider-aws/releases/download/v0.6.4/clusterawsadm-linux-amd64 -o clusterawsadm
chmod +x ./clusterawsadm
sudo mv ./clusterawsadm /usr/local/bin/clusterawsadm

Let’s start to prepare to initialise the management cluster. You need a AWS IAM service account and in my example I enabled the experimental features-gates for MachinePool and ClusterResourceSets before running clusterawsadm to apply the required AWS IAM configuration.

$ export AWS_ACCESS_KEY_ID='<-YOUR-ACCESS-KEY->'
$ export AWS_SECRET_ACCESS_KEY='<-YOUR-SECRET-ACCESS-KEY->'
$ export EXP_MACHINE_POOL=true
$ export EXP_CLUSTER_RESOURCE_SET=true
$ clusterawsadm bootstrap iam create-cloudformation-stack
Attempting to create AWS CloudFormation stack cluster-api-provider-aws-sigs-k8s-io
I1206 22:23:19.620891  357601 service.go:59] AWS Cloudformation stack "cluster-api-provider-aws-sigs-k8s-io" already exists, updating

Following resources are in the stack: 

Resource                  |Type                                                                                |Status
AWS::IAM::InstanceProfile |control-plane.cluster-api-provider-aws.sigs.k8s.io                                  |CREATE_COMPLETE
AWS::IAM::InstanceProfile |controllers.cluster-api-provider-aws.sigs.k8s.io                                    |CREATE_COMPLETE
AWS::IAM::InstanceProfile |nodes.cluster-api-provider-aws.sigs.k8s.io                                          |CREATE_COMPLETE
AWS::IAM::ManagedPolicy   |arn:aws:iam::552276840222:policy/control-plane.cluster-api-provider-aws.sigs.k8s.io |CREATE_COMPLETE
AWS::IAM::ManagedPolicy   |arn:aws:iam::552276840222:policy/nodes.cluster-api-provider-aws.sigs.k8s.io         |CREATE_COMPLETE
AWS::IAM::ManagedPolicy   |arn:aws:iam::552276840222:policy/controllers.cluster-api-provider-aws.sigs.k8s.io   |CREATE_COMPLETE
AWS::IAM::Role            |control-plane.cluster-api-provider-aws.sigs.k8s.io                                  |CREATE_COMPLETE
AWS::IAM::Role            |controllers.cluster-api-provider-aws.sigs.k8s.io                                    |CREATE_COMPLETE
AWS::IAM::Role            |nodes.cluster-api-provider-aws.sigs.k8s.io                                          |CREATE_COMPLETE

This might take a few minutes before you can continue and run clusterctl to initialise the Cluster API components on your Kubernetes management cluster with the option –watching-namespace where you can apply the cluster deployment manifests.

$ export AWS_B64ENCODED_CREDENTIALS=$(clusterawsadm bootstrap credentials encode-as-profile)

WARNING: `encode-as-profile` should only be used for bootstrapping.

$ clusterctl init --infrastructure aws --watching-namespace k8s
Fetching providers
Installing cert-manager Version="v0.16.1"
Waiting for cert-manager to be available...
Installing Provider="cluster-api" Version="v0.3.14" TargetNamespace="capi-system"
Installing Provider="bootstrap-kubeadm" Version="v0.3.14" TargetNamespace="capi-kubeadm-bootstrap-system"
Installing Provider="control-plane-kubeadm" Version="v0.3.14" TargetNamespace="capi-kubeadm-control-plane-system"
Installing Provider="infrastructure-aws" Version="v0.6.3" TargetNamespace="capa-system"

Your management cluster has been initialized successfully!

You can now create your first workload cluster by running the following:

  clusterctl config cluster [name] --kubernetes-version [version] | kubectl apply -f -

Now we have finished deploying the needed Cluster API components and are ready to create your first Kubernetes workload cluster. I go through the different custom resources and configuration options for the cluster provisioning. This starts with the cloud infrastructure configuration as you see in the example below for the VPC setup. You don’t have to use all three Availability Zone and can start with a single AZ in a region.

---
apiVersion: infrastructure.cluster.x-k8s.io/v1alpha3
kind: AWSCluster
metadata:
  name: cluster-1
  namespace: k8s
spec:
  region: eu-west-1
  sshKeyName: default
  networkSpec:
    vpc:
      cidrBlock: "10.0.0.0/23"
    subnets:
    - availabilityZone: eu-west-1a
      cidrBlock: "10.0.0.0/27"
      isPublic: true
    - availabilityZone: eu-west-1b
      cidrBlock: "10.0.0.32/27"
      isPublic: true
    - availabilityZone: eu-west-1c
      cidrBlock: "10.0.0.64/27"
      isPublic: true
    - availabilityZone: eu-west-1a
      cidrBlock: "10.0.1.0/27"
    - availabilityZone: eu-west-1b
      cidrBlock: "10.0.1.32/27"
    - availabilityZone: eu-west-1c
      cidrBlock: "10.0.1.64/27"

Alternatively you can also provision the workload cluster into an existing VPC, in this case your cloud infrastructure configuration looks slightly different and you need to specify VPC and subnet IDs.

---
apiVersion: infrastructure.cluster.x-k8s.io/v1alpha3
kind: AWSCluster
metadata:
  name: cluster-1
  namespace: k8s
spec:
  region: eu-west-1
  sshKeyName: default
  networkSpec:
    vpc:
      id: vpc-0425c335226437144
    subnets:
    - id: subnet-0261219d564bb0dc5
    - id: subnet-0fdcccba78668e013
...

Next we define the Kubeadm control-plane configuration and start with the AWS Machine Template to define the instance type and custom node configuration. Then follows the Kubeadm control-plane config referencing the machine template and amounts of replicas and Kubernetes control-plane version:

---
apiVersion: infrastructure.cluster.x-k8s.io/v1alpha3
kind: AWSMachineTemplate
metadata:
  name: cluster-1
  namespace: k8s
spec:
  template:
    spec:
      iamInstanceProfile: control-plane.cluster-api-provider-aws.sigs.k8s.io
      instanceType: t3.small
      sshKeyName: default
---
apiVersion: controlplane.cluster.x-k8s.io/v1alpha3
kind: KubeadmControlPlane
metadata:
  name: cluster-1-control-plane
  namespace: k8s
spec:
  infrastructureTemplate:
    apiVersion: infrastructure.cluster.x-k8s.io/v1alpha3
    kind: AWSMachineTemplate
    name: cluster-1-control-plane
  kubeadmConfigSpec:
    clusterConfiguration:
      apiServer:
        extraArgs:
          cloud-provider: aws
      controllerManager:
        extraArgs:
          cloud-provider: aws
    initConfiguration:
      nodeRegistration:
        kubeletExtraArgs:
          cloud-provider: aws
        name: '{{ ds.meta_data.local_hostname }}'
    joinConfiguration:
      nodeRegistration:
        kubeletExtraArgs:
          cloud-provider: aws
        name: '{{ ds.meta_data.local_hostname }}'
  replicas: 1
  version: v1.20.4

We continue with the data-plane (worker) nodes which also starts with the AWS machine template, additionally we need a Kubeadm Config Template and then the Machine Deployment for the worker nodes with a number of replicas and used Kubernetes version.

---
apiVersion: infrastructure.cluster.x-k8s.io/v1alpha3
kind: AWSMachineTemplate
metadata:
  name: cluster-1-data-plane-0
  namespace: k8s
spec:
  template:
    spec:
      iamInstanceProfile: nodes.cluster-api-provider-aws.sigs.k8s.io
      instanceType: t3.small
      sshKeyName: default
---
apiVersion: bootstrap.cluster.x-k8s.io/v1alpha3
kind: KubeadmConfigTemplate
metadata:
  name: cluster-1-data-plane-0
  namespace: k8s
spec:
  template:
    spec:
      joinConfiguration:
        nodeRegistration:
          kubeletExtraArgs:
            cloud-provider: aws
          name: '{{ ds.meta_data.local_hostname }}'
---
apiVersion: cluster.x-k8s.io/v1alpha3
kind: MachineDeployment
metadata:
  name: cluster-1-data-plane-0
  namespace: k8s
spec:
  clusterName: cluster-1
  replicas: 1
  selector:
    matchLabels: null
  template:
    metadata:
      labels:
        "nodepool": "nodepool-0"
    spec:
      bootstrap:
        configRef:
          apiVersion: bootstrap.cluster.x-k8s.io/v1alpha3
          kind: KubeadmConfigTemplate
          name: cluster-1-data-plane-0
      clusterName: cluster-1
      infrastructureRef:
        apiVersion: infrastructure.cluster.x-k8s.io/v1alpha3
        kind: AWSMachineTemplate
        name: cluster-1-data-plane-0
      version: v1.20.4

A workload cluster can be very easily upgraded by changing the .spec.version in the MachineDeployment and KubeadmControlPlane configuration. You can’t jump over a Kubernetes versions and can only upgrade to the next available version example: v1.18.4 to v1.19.8 or v1.19.8 to v1.20.4. See the list of supported AMIs and Kubernetes versions for the AWS provider.

At the beginning we enabled the feature-gates when we were initialising the management cluster to allow us to use ClusterResourceSets. This is incredible useful because I can define a set of resources which gets applied during the provisioning of the cluster. This only get executed one time during the bootstrap and will be not reconciled afterwards. In the configuration you see the reference to two configmaps for adding the Calico CNI plugin and the Nginx Ingress controller.

---
apiVersion: addons.cluster.x-k8s.io/v1alpha3
kind: ClusterResourceSet
metadata:
  name: cluster-1-crs-0
  namespace: k8s
spec:
  clusterSelector:
    matchLabels:
      cluster.x-k8s.io/cluster-name: cluster-1
  resources:
  - kind: ConfigMap
    name: calico-cni
  - kind: ConfigMap
    name: nginx-ingress

Example of the two configmaps which contain the YAML manifests:

apiVersion: v1
kind: ConfigMap
metadata:
  creationTimestamp: null
  name: calico-cni
  namespace: k8s
data:
  calico.yaml: |+
    ---
    # Source: calico/templates/calico-config.yaml
    # This ConfigMap is used to configure a self-hosted Calico installation.
    kind: ConfigMap
    apiVersion: v1
    metadata:
      name: calico-config
      namespace: kube-system
...
---
apiVersion: v1
data:
  deploy.yaml: |+
    ---
    apiVersion: v1
    kind: Namespace
    metadata:
      name: ingress-nginx
      labels:
        app.kubernetes.io/name: ingress-nginx
        app.kubernetes.io/instance: ingress-nginx
...

Without ClusterResourceSet you would need to manually apply the CNI and ingress controller manifests which is not great because you need the CNI plugin for all nodes to go into Ready state.

$ kubectl --kubeconfig=./cluster-1.kubeconfig   apply -f https://docs.projectcalico.org/v3.15/manifests/calico.yaml
$ kubectl --kubeconfig=./cluster-1.kubeconfig apply -f https://raw.githubusercontent.com/kubernetes/ingress-nginx/controller-v0.41.2/deploy/static/provider/aws/deploy.yaml

Finally after we have created the configuration of the workload cluster we can apply cluster manifest with the option for setting custom clusterNetwork and specify with service and pod IP range.

---
apiVersion: cluster.x-k8s.io/v1alpha3
kind: Cluster
metadata:
  name: cluster-1
  namespace: k8s
  labels:
    cluster.x-k8s.io/cluster-name: cluster-1
spec:
  clusterNetwork:
    services:
      cidrBlocks:
      - 172.30.0.0/16
    pods:
      cidrBlocks:
      - 10.128.0.0/14
  controlPlaneRef:
    apiVersion: controlplane.cluster.x-k8s.io/v1alpha3
    kind: KubeadmControlPlane
    name: cluster-1-control-plane
  infrastructureRef:
    apiVersion: infrastructure.cluster.x-k8s.io/v1alpha3
    kind: AWSCluster
    name: cluster-1

The provisioning of the workload cluster will take around 10 to 15 mins and you can follow the progress by checking the status of different configurations we have applied previously.

You can scale both Kubeadm control-plane and MachineDeployment afterwards to change the size of your cluster. MachineDeployment can be scaled down to zero to save cost.

$ kubectl scale KubeadmControlPlane cluster-1-control-plane --replicas=1
$ kubectl scale MachineDeployment cluster-1-data-plane-0 --replicas=0

After the provisioning is completed you can get kubeconfig of the cluster from the secret which got created during the bootstrap:

$ kubectl --namespace=k8s get secret cluster-1-kubeconfig    -o jsonpath={.data.value} | base64 --decode    > cluster-1.kubeconfig

Example check the node state.

$ kubectl --kubeconfig=./cluster-1.kubeconfig get nodes

When your cluster is provisioned and nodes are in Ready state you can apply the MachineHealthCheck for the data-plane (worker) nodes. This automatically remediate unhealthy nodes and provisions new nodes to join them into the cluster.

---
apiVersion: cluster.x-k8s.io/v1alpha3
kind: MachineHealthCheck
metadata:
  name: cluster-1-node-unhealthy-5m
  namespace: k8s
spec:
  # clusterName is required to associate this MachineHealthCheck with a particular cluster
  clusterName: cluster-1
  # (Optional) maxUnhealthy prevents further remediation if the cluster is already partially unhealthy
  maxUnhealthy: 40%
  # (Optional) nodeStartupTimeout determines how long a MachineHealthCheck should wait for
  # a Node to join the cluster, before considering a Machine unhealthy
  nodeStartupTimeout: 10m
  # selector is used to determine which Machines should be health checked
  selector:
    matchLabels:
      nodepool: nodepool-0 
  # Conditions to check on Nodes for matched Machines, if any condition is matched for the duration of its timeout, the Machine is considered unhealthy
  unhealthyConditions:
  - type: Ready
    status: Unknown
    timeout: 300s
  - type: Ready
    status: "False"
    timeout: 300s

I hope this is a useful article for getting started with the Kubernetes Cluster API.

Getting started with Kubernetes Operators in Go

In the past few weeks I started to learn Go and beginners like me can make quick progress once you understand the structure and some basics about the programming language. I felt that from all the learning and reading I’ve done on Go and Kubernetes operators, I had enough knowledge to start writing my own Kubernetes operator in Go.

At the beginning of last year, RedHat released the operator-sdk which helps to create the scaffolding for writing your own operators in Ansible, Helm or natively in Go. There has been quite a few changes along the way around the operator-sdk and it is maturing a lot over the course of the past year.

The instructions on how to install Go can be found on the Go website and we need the latest version of the operator-sdk:

$ wget https://github.com/operator-framework/operator-sdk/releases/download/v1.2.0/operator-sdk-v1.2.0-x86_64-linux-gnu
$ mv operator-sdk-v1.2.0-x86_64-linux-gnu operator-sdk
$ sudo mv operator-sdk /usr/local/bin/

Create a new folder and start to initialise the project. You see that I have already set the option --domain so all API groups will be <-group->.helloworld.io. The --repo option allows me to create the project folder outside of my $GOPATH environment. Infos about the folder structure you can find in the Kubebuilder documentation:

$ mkdir k8s-helloworld-operator
$ cd k8s-helloworld-operator
$ operator-sdk init --domain=helloworld.io --repo=github.com/berndonline/k8s-helloworld-operator

The last thing we need before we start writing the operator is to create a new API and Controller and this will scaffold the operator API at api/v1alpha1/operator_types.go and the controller at controllers/operator_controller.go.

$ operator-sdk create api --group app --version v1alpha1 --kind Operator
Create Resource [y/n]
y
Create Controller [y/n]
y
Writing scaffold for you to edit...
api/v1alpha1/operator_types.go
controllers/operator_controller.go
...
  • Define your API

Define your API for the operator custom resource by editing the Go type definitions at api/v1alpha1/operator_types.go

// OperatorSpec defines the desired state of Operator
type OperatorSpec struct {
	// INSERT ADDITIONAL SPEC FIELDS - desired state of cluster
	// Important: Run "make" to regenerate code after modifying this file

	// Foo is an example field of Operator. Edit Operator_types.go to remove/update
	Size     int32  `json:"size"`
	Image    string `json:"image"`
	Response string `json:"response"`
}
// OperatorStatus defines the observed state of Operator
type OperatorStatus struct {
	// INSERT ADDITIONAL STATUS FIELD - define observed state of cluster
	// Important: Run "make" to regenerate code after modifying this file
	Nodes []string `json:"nodes"`
}

// Operator is the Schema for the operators API
// +kubebuilder:subresource:status
type Operator struct {
	metav1.TypeMeta   `json:",inline"`
	metav1.ObjectMeta `json:"metadata,omitempty"`

	Spec   OperatorSpec   `json:"spec,omitempty"`
	Status OperatorStatus `json:"status,omitempty"`
}

After modifying the _types.go file you always need to run the following command to update the generated code for that resource type:

$ make generate 
/home/ubuntu/.go/bin/controller-gen object:headerFile="hack/boilerplate.go.txt" paths="./..."
  • Generate Custom Resource Definition (CRD) manifests

In the previous step we defined the API with spec and status fields of the CRD manifests, which can be generated and updated with the following command:

$ make manifests
/home/ubuntu/.go/bin/controller-gen "crd:trivialVersions=true" rbac:roleName=manager-role webhook paths="./..." output:crd:artifacts:config=config/crd/bases

This makefile will invoke the controller-gen to generate the CRD manifests at config/crd/bases/app.helloworld.io_operators.yaml and below you see my custom resource example for the operator:

apiVersion: app.helloworld.io/v1alpha1
kind: Operator
metadata:
  name: operator-sample
spec:
  size: 1
  response: "Hello, World!"
  image: "ghcr.io/berndonline/k8s/go-helloworld:latest"
  • Controller

In the beginning when I created the API, the operator-sdk automatically created the controller file for me at controllers/operator_controller.go which we now start to modify and add the Go code. I will not go into every detail because the different resources you will create will all look very similar and repeat like you will see in example code. I will mainly focus on the Deployment for my Helloworld container image which I want to deploy using the operator.

Let’s start looking at the deploymentForOperator function which defines and returns the Kubernetes Deployment object. You see there that I invoke an imported Go packages like &appsv1.Deployment and the import is defined at the top of the controller file. You can find details about this in the Go Doc reference: godoc.org/k8s.io/api/apps/v1

// deploymentForOperator returns a operator Deployment object
func (r *OperatorReconciler) deploymentForOperator(m *appv1alpha1.Operator) *appsv1.Deployment {
	ls := labelsForOperator(m.Name)
	replicas := m.Spec.Size

	dep := &appsv1.Deployment{
		ObjectMeta: metav1.ObjectMeta{
			Name:      m.Name,
			Namespace: m.Namespace,
		},
		Spec: appsv1.DeploymentSpec{
			Replicas: &replicas,
			Selector: &metav1.LabelSelector{
				MatchLabels: ls,
			},
			Template: corev1.PodTemplateSpec{
				ObjectMeta: metav1.ObjectMeta{
					Labels: ls,
				},
				Spec: corev1.PodSpec{
					Containers: []corev1.Container{{
						Image:           m.Spec.Image,
						ImagePullPolicy: "Always",
						Name:            "helloworld",
						Ports: []corev1.ContainerPort{{
							ContainerPort: 8080,
							Name:          "operator",
						}},
						Env: []corev1.EnvVar{{
							Name:  "RESPONSE",
							Value: m.Spec.Response,
						}},
						EnvFrom: []corev1.EnvFromSource{{
							ConfigMapRef: &corev1.ConfigMapEnvSource{
								LocalObjectReference: corev1.LocalObjectReference{
									Name: m.Name,
								},
							},
						}},
						VolumeMounts: []corev1.VolumeMount{{
							Name:      m.Name,
							ReadOnly:  true,
							MountPath: "/helloworld/",
						}},
					}},
					Volumes: []corev1.Volume{{
						Name: m.Name,
						VolumeSource: corev1.VolumeSource{
							ConfigMap: &corev1.ConfigMapVolumeSource{
								LocalObjectReference: corev1.LocalObjectReference{
									Name: m.Name,
								},
							},
						},
					}},
				},
			},
		},
	}

	// Set Operator instance as the owner and controller
	ctrl.SetControllerReference(m, dep, r.Scheme)
	return dep
}

We have defined the deploymentForOperator function and now we can look into the Reconcile function and add the step to check if the deployment already exists and, if not, to create the new deployment:

// Check if the deployment already exists, if not create a new one
found := &appsv1.Deployment{}
err = r.Get(ctx, types.NamespacedName{Name: operator.Name, Namespace: operator.Namespace}, found)
if err != nil && errors.IsNotFound(err) {
	// Define a new deployment
	dep := r.deploymentForOperator(operator)
	log.Info("Creating a new Deployment", "Deployment.Namespace", dep.Namespace, "Deployment.Name", dep.Name)
	err = r.Create(ctx, dep)
	if err != nil {
		log.Error(err, "Failed to create new Deployment", "Deployment.Namespace", dep.Namespace, "Deployment.Name", dep.Name)
		return ctrl.Result{}, err
	}
	// Deployment created successfully - return and requeue
	return ctrl.Result{Requeue: true}, nil
} else if err != nil {
	log.Error(err, "Failed to get Deployment")
	return ctrl.Result{}, err
}

Unfortunately this isn’t enough because this will only check if the deployment exists or not and create a new deployment, but it will not update the deployment if the custom resource is changed.

We need to add two more steps to check if the created Deployment Spec.Template matches the Spec.Template from the  deploymentForOperator function and the Deployment Spec.Replicas the defined size from the custom resource. I will make use of the defined variable found := &appsv1.Deployment{} from the previous step when I checked if the deployment exists.

// Check if the deployment Spec.Template, matches the found Spec.Template
deploy := r.deploymentForOperator(operator)
if !equality.Semantic.DeepDerivative(deploy.Spec.Template, found.Spec.Template) {
	found = deploy
	log.Info("Updating Deployment", "Deployment.Namespace", found.Namespace, "Deployment.Name", found.Name)
	err := r.Update(ctx, found)
	if err != nil {
		log.Error(err, "Failed to update Deployment", "Deployment.Namespace", found.Namespace, "Deployment.Name", found.Name)
		return ctrl.Result{}, err
	}
	return ctrl.Result{Requeue: true}, nil
}

// Ensure the deployment size is the same as the spec
size := operator.Spec.Size
if *found.Spec.Replicas != size {
	found.Spec.Replicas = &size
	err = r.Update(ctx, found)
	if err != nil {
		log.Error(err, "Failed to update Deployment", "Deployment.Namespace", found.Namespace, "Deployment.Name", found.Name)
		return ctrl.Result{}, err
	}
	// Spec updated - return and requeue
	return ctrl.Result{Requeue: true}, nil
}

The SetupWithManager() function in controllers/operator_controller.go specifies how the controller is built to watch a custom resource and other resources that are owned and managed by that controller.

func (r *OperatorReconciler) SetupWithManager(mgr ctrl.Manager) error {
	return ctrl.NewControllerManagedBy(mgr).
		For(&appv1alpha1.Operator{}).
		Owns(&appsv1.Deployment{}).
		Owns(&corev1.ConfigMap{}).
		Owns(&corev1.Service{}).
		Owns(&networkingv1beta1.Ingress{}).
		Complete(r)
}

Basically that’s all I need to write for the controller to deploy my Helloworld container image using an Kubernetes operator. In my code example you will find that I also create a Kubernetes Service, Ingress and ConfigMap but you see that this mostly repeats what I have done with the Deployment object.

  • RBAC permissions

Before we can start running the operator, we need to define the RBAC permissions the controller needs to interact with the resources it manages otherwise your controller will not work. These are specified via [RBAC markers] like these:

// +kubebuilder:rbac:groups=app.helloworld.io,resources=operators,verbs=get;list;watch;create;update;patch;delete
// +kubebuilder:rbac:groups=app.helloworld.io,resources=operators/status,verbs=get;update;patch
// +kubebuilder:rbac:groups=app.helloworld.io,resources=operators/finalizers,verbs=update
// +kubebuilder:rbac:groups=apps,resources=deployments,verbs=get;list;watch;create;update;patch;delete
// +kubebuilder:rbac:groups=core,resources=services,verbs=get;list;watch;create;update;patch;delete
// +kubebuilder:rbac:groups=core,resources=configmaps,verbs=get;list;watch;create;update;patch;delete
// +kubebuilder:rbac:groups=networking.k8s.io,resources=ingresses,verbs=get;list;watch;create;update;patch;delete
// +kubebuilder:rbac:groups=core,resources=pods,verbs=get;list;watch

The ClusterRole manifest at config/rbac/role.yaml is generated from the above markers via controller-gen with the following command:

$ make manifests 
/home/ubuntu/.go/bin/controller-gen "crd:trivialVersions=true" rbac:roleName=manager-role webhook paths="./..." output:crd:artifacts:config=config/crd/bases
  • Running the Operator

We need a Kubernetes cluster and admin privileges to run the operator. I will use Kind which will run a lightweight Kubernetes cluster in your local Docker engine, which is all I need to run and test my Helloworld operator:

$ ./scripts/create-kind-cluster.sh 
Creating cluster "kind" ...
 ✓ Ensuring node image (kindest/node:v1.19.1) 🖼 
 ✓ Preparing nodes 📦  
 ✓ Writing configuration 📜 
 ✓ Starting control-plane 🕹️ 
 ✓ Installing CNI 🔌 
 ✓ Installing StorageClass 💾 
Set kubectl context to "kind-kind"
You can now use your cluster with:

kubectl cluster-info --context kind-kind

Have a question, bug, or feature request? Let us know! https://kind.sigs.k8s.io/#community 🙂

Before running the operator the custom resource Definition must be registered with the Kubernetes apiserver:

$ make install
/home/ubuntu/.go/bin/controller-gen "crd:trivialVersions=true" rbac:roleName=manager-role webhook paths="./..." output:crd:artifacts:config=config/crd/bases
/usr/bin/kustomize build config/crd | kubectl apply -f -
Warning: apiextensions.k8s.io/v1beta1 CustomResourceDefinition is deprecated in v1.16+, unavailable in v1.22+; use apiextensions.k8s.io/v1 CustomResourceDefinition
customresourcedefinition.apiextensions.k8s.io/operators.app.helloworld.io created

We can now run the operator locally on my workstation:

$ make run
/home/ubuntu/.go/bin/controller-gen object:headerFile="hack/boilerplate.go.txt" paths="./..."
go fmt ./...
go vet ./...
/home/ubuntu/.go/bin/controller-gen "crd:trivialVersions=true" rbac:roleName=manager-role webhook paths="./..." output:crd:artifacts:config=config/crd/bases
go run ./main.go
2020-11-22T18:12:49.023Z	INFO	controller-runtime.metrics	metrics server is starting to listen	{"addr": ":8080"}
2020-11-22T18:12:49.024Z	INFO	setup	starting manager
2020-11-22T18:12:49.025Z	INFO	controller-runtime.manager	starting metrics server	{"path": "/metrics"}
2020-11-22T18:12:49.025Z	INFO	controller	Starting EventSource	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "source": "kind source: /, Kind="}
2020-11-22T18:12:49.126Z	INFO	controller	Starting EventSource	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "source": "kind source: /, Kind="}
2020-11-22T18:12:49.226Z	INFO	controller	Starting EventSource	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "source": "kind source: /, Kind="}
2020-11-22T18:12:49.327Z	INFO	controller	Starting EventSource	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "source": "kind source: /, Kind="}
2020-11-22T18:12:49.428Z	INFO	controller	Starting EventSource	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "source": "kind source: /, Kind="}
2020-11-22T18:12:49.528Z	INFO	controller	Starting Controller	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator"}
2020-11-22T18:12:49.528Z	INFO	controller	Starting workers	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "worker count": 1}

Let’s open a new terminal and apply the custom resource example:

$ kubectl apply -f config/samples/app_v1alpha1_operator.yaml 
operator.app.helloworld.io/operator-sample created

Going back to the terminal where the operator is running, you see the log messages that it invoke the different functions to deploy the defined resource objects:

2020-11-22T18:15:30.412Z	INFO	controllers.Operator	Creating a new Deployment	{"operator": "default/operator-sample", "Deployment.Namespace": "default", "Deployment.Name": "operator-sample"}
2020-11-22T18:15:30.446Z	INFO	controllers.Operator	Creating a new ConfigMap	{"operator": "default/operator-sample", "ConfigMap.Namespace": "default", "ConfigMap.Name": "operator-sample"}
2020-11-22T18:15:30.453Z	INFO	controllers.Operator	Creating a new Service	{"operator": "default/operator-sample", "Service.Namespace": "default", "Service.Name": "operator-sample"}
2020-11-22T18:15:30.470Z	INFO	controllers.Operator	Creating a new Ingress	{"operator": "default/operator-sample", "Ingress.Namespace": "default", "Ingress.Name": "operator-sample"}
2020-11-22T18:15:30.927Z	DEBUG	controller	Successfully Reconciled	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "name": "operator-sample", "namespace": "default"}
2020-11-22T18:15:30.927Z	DEBUG	controller	Successfully Reconciled	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "name": "operator-sample", "namespace": "default"}
2020-11-22T18:15:33.776Z	DEBUG	controller	Successfully Reconciled	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "name": "operator-sample", "namespace": "default"}
2020-11-22T18:15:35.181Z	DEBUG	controller	Successfully Reconciled	{"reconcilerGroup": "app.helloworld.io", "reconcilerKind": "Operator", "controller": "operator", "name": "operator-sample", "namespace": "default"}

In the default namespace where I applied the custom resource you will see the deployed resources by the operator:

$ kubectl get operators.app.helloworld.io 
NAME              AGE
operator-sample   6m11s
$ kubectl get all
NAME                                   READY   STATUS    RESTARTS   AGE
pod/operator-sample-767897c4b9-8zwsd   1/1     Running   0          2m59s

NAME                      TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)    AGE
service/kubernetes        ClusterIP   10.96.0.1               443/TCP    29m
service/operator-sample   ClusterIP   10.96.199.188           8080/TCP   2m59s

NAME                              READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/operator-sample   1/1     1            1           2m59s

NAME                                         DESIRED   CURRENT   READY   AGE
replicaset.apps/operator-sample-767897c4b9   1         1         1       2m59s

There is not much else to do other than to build the operator image and push to an image registry so that I can run the operator on a Kubernetes cluster.

$ make docker-build IMG=ghcr.io/berndonline/k8s/helloworld-operator:latest
$ make docker-push IMG=ghcr.io/berndonline/k8s/helloworld-operator:latest
$ kustomize build config/default | kubectl apply -f -

I hope this article is useful for getting you started on writing your own Kubernetes operator in Go.

Running Istio Service Mesh on Amazon EKS

I have not spend too much time with Istio in the last weeks but after my previous article about running Istio Service Mesh on OpenShift I wanted to do the same and deploy Istio Service Mesh on an Amazon EKS cluster. This time I did the recommended way of using a helm template to deploy Istio which is more flexible then the Ansible operator for the OpenShift deployment.

Once you have created your EKS cluster you can start, there are not many prerequisite for EKS so you can basically create the istio namespace and create a secret for Kiali, and start to deploy the helm template:

kubectl create namespace istio-system

USERNAME=$(echo -n 'admin' | base64)
PASSPHRASE=$(echo -n 'supersecretpassword!!' | base64)
NAMESPACE=istio-system

cat <<EOF | kubectl apply -n istio-system -f -
apiVersion: v1
kind: Secret
metadata:
  name: kiali
  namespace: $NAMESPACE
  labels:
    app: kiali
type: Opaque
data:
  username: $USERNAME
  passphrase: $PASSPHRASE
EOF

You then create the Custom Resource Definitions (CRDs) for Istio:

helm template istio-1.1.4/install/kubernetes/helm/istio-init --name istio-init --namespace istio-system | kubectl apply -f -  

# Check the created Istio CRDs 
kubectl get crds -n istio-system | grep 'istio.io\|certmanager.k8s.io' | wc -l

At this point you can deploy the main Istio Helm template. See the installation options for more detail about customizing the installation:

helm template istio-1.1.4/install/kubernetes/helm/istio --name istio --namespace istio-system  --set grafana.enabled=true --set tracing.enabled=true --set kiali.enabled=true --set kiali.dashboard.secretName=kiali --set kiali.dashboard.usernameKey=username --set kiali.dashboard.passphraseKey=passphrase | kubectl apply -f -
 
# Validate and see that all components start
kubectl get pods -n istio-system -w  

The Kiali service has the type clusterIP which we need to change to type LoadBalancer:

kubectl patch svc kiali -n istio-system --patch '{"spec": {"type": "LoadBalancer" }}'

# Get the create AWS ELB for the Kiali service
$ kubectl get svc kiali -n istio-system --no-headers | awk '{ print $4 }'
abbf8224773f111e99e8a066e034c3d4-78576474.eu-west-1.elb.amazonaws.com

Now we are able to access the Kiali dashboard and login with the credentials I have specified earlier in the Kiali secret.

We didn’t deploy anything else yet so the default namespace is empty:

I recommend having a look at the Istio-Sidecar injection. If your istio-sidecar containers are not getting deployed you might forgot to allow TCP port 443 from your control-plane to worker nodes. Have a look at the Github issue about this: Admission control webhooks (e.g. sidecar injector) don’t work on EKS.

We can continue and deploy the Google Hipster Shop example.

# Label default namespace to inject Envoy sidecar
kubectl label namespace default istio-injection=enabled

# Check istio sidecar injector label
kubectl get namespace -L istio-injection

# Deploy Google hipster shop manifests
kubectl create -f https://raw.githubusercontent.com/berndonline/aws-eks-terraform/master/example/istio-hipster-shop.yml
kubectl create -f https://raw.githubusercontent.com/berndonline/aws-eks-terraform/master/example/istio-manifest.yml

# Wait a few minutes before deploying the load generator
kubectl create -f https://raw.githubusercontent.com/berndonline/aws-eks-terraform/master/example/istio-loadgenerator.yml

We can check again the Kiali dashboard once the application is deployed and healthy. If there are issues with the Envoy sidecar you will see a warning “Missing Sidecar”:

We are also able to see the graph which shows detailed traffic flows within the microservice application.

Let’s get the hostname for the istio-ingressgateway service and connect via the web browser:

$ kubectl get svc istio-ingressgateway -n istio-system --no-headers | awk '{ print $4 }'
a16f7090c74ca11e9a1fb02cd763ca9e-362893117.eu-west-1.elb.amazonaws.com

Before you destroy your EKS cluster you should remove all installed components because Kubernetes service type LoadBalancer created AWS ELBs which will not get deleted and stay behind when you delete the EKS cluster:

kubectl label namespace default istio-injection-
kubectl delete -f https://raw.githubusercontent.com/berndonline/aws-eks-terraform/master/example/istio-loadgenerator.yml
kubectl delete -f https://raw.githubusercontent.com/berndonline/aws-eks-terraform/master/example/istio-hipster-shop.yml
kubectl delete -f https://raw.githubusercontent.com/berndonline/aws-eks-terraform/master/example/istio-manifest.yml

Finally to remove Istio from EKS you run the same Helm template command but do kubectl delete:

helm template istio-1.1.4/install/kubernetes/helm/istio --name istio --namespace istio-system  --set grafana.enabled=true --set tracing.enabled=true --set kiali.enabled=true --set kiali.dashboard.secretName=kiali --set kiali.dashboard.usernameKey=username --set kiali.dashboard.passphraseKey=passphrase | kubectl delete -f -

Very simple to get started with Istio Service Mesh on EKS and if I find some time I will give the Istio Multicluster a try and see how this works to span Istio service mesh across multiple Kubernetes clusters.