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Deploying your first application

This page shows how to deploy and application in your user cluster.

SSH into your admin workstation

SSH into your admin workstation:

ssh -i ~/.ssh/vsphere_workstation ubuntu@[IP_ADDRESS]

where [IP_ADDRESS] is the IP address of your admin workstation.

Do all of the remaining steps in this topic on your admin workstation.

Creating a Deployment

Here is a manifest for a Deployment:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-deployment
spec:
  selector:
    matchLabels:
      app: metrics
      department: sales
  replicas: 3
  template:
    metadata:
      labels:
        app: metrics
        department: sales
    spec:
      containers:
      - name: hello
        image: "gcr.io/google-samples/hello-app:2.0"

Copy the manifest to a file named my-deployment.yaml, and create the Deployment:

kubectl apply --kubeconfig [USER_CLUSTER_KUBECONFIG] -f my-deployment.yaml

where [USER_CLUSTER_KUBECONFIG] is the path of the kubeconfig file for your user cluster.

Get basic information about your Deployment:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] get deployment my-deployment

The output shows that the Deployment has three Pods that are all available:

NAME            READY   UP-TO-DATE   AVAILABLE   AGE
my-deployment   3/3     3            3           27s

List the Pods in your Deployment:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] get pods

The output shows that your Deployment has three running Pods:

NAME                             READY   STATUS    RESTARTS   AGE
my-deployment-54944c8d55-4srm2   1/1     Running   0          6s
my-deployment-54944c8d55-7z5nn   1/1     Running   0          6s
my-deployment-54944c8d55-j62n9   1/1     Running   0          6s

Get detailed information about your Deployment:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] get deployment my-deployment --output yaml

The output shows details about the Deployment spec and status:

kind: Deployment
metadata:
  ...
  generation: 1
  name: my-deployment
  namespace: default
  ...
spec:
  ...
  replicas: 3
  revisionHistoryLimit: 10
  selector:
    matchLabels:
      app: metrics
      department: sales
  ...
    spec:
      containers:
      - image: gcr.io/google-samples/hello-app:2.0
        imagePullPolicy: IfNotPresent
        name: hello
        resources: {}
        terminationMessagePath: /dev/termination-log
        terminationMessagePolicy: File
      dnsPolicy: ClusterFirst
      restartPolicy: Always
      schedulerName: default-scheduler
      securityContext: {}
      terminationGracePeriodSeconds: 30
status:
  availableReplicas: 3
  conditions:
  - lastTransitionTime: "2019-11-11T18:44:02Z"
    lastUpdateTime: "2019-11-11T18:44:02Z"
    message: Deployment has minimum availability.
    reason: MinimumReplicasAvailable
    status: "True"
    type: Available
  - lastTransitionTime: "2019-11-11T18:43:58Z"
    lastUpdateTime: "2019-11-11T18:44:02Z"
    message: ReplicaSet "my-deployment-54944c8d55" has successfully progressed.
    reason: NewReplicaSetAvailable
    status: "True"
    type: Progressing
  observedGeneration: 1
  readyReplicas: 3
  replicas: 3
  updatedReplicas: 3

Describe your Deployment:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] describe deployment my-deployment

The output shows nicely formatted details about the Deployment, including the associated ReplicaSet:

Name:                   my-deployment
Namespace:              default
CreationTimestamp:      Mon, 11 Nov 2019 10:43:58 -0800
Labels:                 
...
Selector:               app=metrics,department=sales
Replicas:               3 desired | 3 updated | 3 total | 3 available | 0 unavailable
StrategyType:           RollingUpdate
MinReadySeconds:        0
RollingUpdateStrategy:  25% max unavailable, 25% max surge
Pod Template:
  Labels:  app=metrics
           department=sales
  Containers:
   hello:
    Image:        gcr.io/google-samples/hello-app:2.0
    Port:         
    Host Port:    
    Environment:  
    Mounts:       
  Volumes:        
Conditions:
  Type           Status  Reason
  ----           ------  ------
  Available      True    MinimumReplicasAvailable
  Progressing    True    NewReplicaSetAvailable
OldReplicaSets:  
NewReplicaSet:   my-deployment-54944c8d55 (3/3 replicas created)

Creating a Service of type LoadBalancer

One way to expose your Deployment to clients outside your cluster is to create a Kubernetes Service of type LoadBalancer.

Here's a manifest for a Service of type LoadBalancer:

apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  selector:
    app: metrics
    department: sales
  type: LoadBalancer
  loadBalancerIP: [SERVICE_IP_ADDRESS]
  ports:
  - port: 80
    targetPort: 8080

For the purpose of this exercise, these are the important things to understand about the Service:

  • Any Pod that has the label app: metrics and the label department: sales is a member of the Service. Note that the Pods in my-deployment have these labels.

  • When a client sends a request to the Service on TCP port 80, the request is forwarded to a member Pod on TCP port 8080.

  • Every member Pod must have a container that is listening on TCP port 8080.

It happens that by default, the hello-app container listens on TCP port 8080. You can see this by looking at the Dockerfile and the source code for the app.

Replace [SERVICE_IP_ADDRESS] with an address that you own that is not already in use. For example, you could set this to a public IP address that your company owns. Or you could set it to a private address in your company network.

The address you choose must be routable from the location of any client that sends requests to the Service. For example, if you choose a private address, then external clients will not be able to send requests to the Service.

Save the manifest to a file named my-service.yaml, and create the Service:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] apply -f my-service.yaml

where [USER_CLUSTER_KUBECONFIG] is the path of your user cluster's kubeconfig file.

When you create the Service, GKE on-prem automatically configures the loadBalancerIP address on your F5 BIG-IP load balancer.

View your Service:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] get service my-service --output yaml

The output is similar to this:

apiVersion: v1
kind: Service
metadata:
  ...
  name: my-service
  namespace: default
  ...
spec:
  clusterIP: 10.107.84.202
  externalTrafficPolicy: Cluster
  loadBalancerIP: 21.0.133.48
  ports:
  - nodePort: 31919
    port: 80
    protocol: TCP
    targetPort: 8080
  selector:
    app: metrics
    department: sales
  sessionAffinity: None
  type: LoadBalancer
status:
  loadBalancer:
    ingress:
    - ip: 203.0.113.1

In the preceding output, you can see that your Service has a clusterIP, and a loadBalancerIP. It also has a nodePort, a port, and a targetPort.

The clusterIP is not relevant to this exercise. The loadBalancerIP is the IP address that you provided in my-service.yaml.

As an example, take the values shown in the preceding output. That is, suppose your Service has loadBalancerIP = 203.0.113.1, port = 80, nodePort = 31919, and targetPort = 8080.

A client sends a request to 203.0.113.1 on TCP port 80. The request gets routed to your F5 BIG-IP load balancer. The load balancer chooses one of your user cluster nodes, and forwards the request to [NODE_ADDRESS] on TCP port 31919. The iptables rules on the node forward the request to a member Pod on TCP port 8080.

Call your Service:

curl [SERVICE_IP_ADDRESS]

where [SERVICE_IP_ADDRESS] is the address that you specified for loadBalancerIP.

The output shows a Hello, world! message:

curl 21.0.133.48
Hello, world!
Version: 2.0.0
Hostname: my-deployment-dbd86c8c4-9wpbv

Deleting your Service

Delete your Service:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] delete service my-service

Verify that your Service has been deleted:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] get services

The output no longer shows my-service.

Deleting your Deployment

Delete your Deployment:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] delete deployment my-deployment

Verify that your Deployment has been deleted:

kubectl --kubeconfig [USER_CLUSTER_KUBECONFIG] get deployments

The output no longer shows my-deployment.