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    Deploy an application

    This document describes how to deploy an application on Google Distributed Cloud.

    Before you begin

    To deploy a workload, you must have a user, hybrid, or standalone cluster capable of running workloads.

    Create a Deployment

    The following steps create a Deployment on your cluster:

    1. Copy the following manifest to a file named my-deployment.yaml :

        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 
 : 
  
 "us-docker.pkg.dev/google-samples/containers/gke/hello-app:2.0"

    2. Use kubectl apply to create the Deployment:

       kubectl  
apply  
-f  
my-deployment.yaml  
--kubeconfig  
 CLUSTER_KUBECONFIG

      Replace CLUSTER_KUBECONFIG with the path of the kubeconfig file for your cluster.

    3. Get basic information about your Deployment to confirm it was created successfully:

       kubectl  
get  
deployment  
my-deployment  
--kubeconfig  
 CLUSTER_KUBECONFIG

      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

    4. List the Pods in your Deployment:

       kubectl  
get  
pods  
--kubeconfig  
 CLUSTER_KUBECONFIG

      The output shows that your Deployment has three running Pods:

       NAME                             READY   STATUS    RESTARTS   AGE
my-deployment-869f65669b-5259x   1/1     Running   0          34s
my-deployment-869f65669b-9xfrs   1/1     Running   0          34s
my-deployment-869f65669b-wn4ft   1/1     Running   0          34s

    5. Get detailed information about your Deployment:

       kubectl  
get  
deployment  
my-deployment  
--output  
yaml  
--kubeconfig  
 CLUSTER_KUBECONFIG

      The output shows details about the Deployment spec and status:

        apiVersion 
 : 
  
 apps/v1 
 kind 
 : 
  
 Deployment 
 metadata 
 : 
  
 ... 
  
 generation 
 : 
  
 1 
  
 name 
 : 
  
 my-deployment 
  
 namespace 
 : 
  
 default 
  
 ... 
 spec 
 : 
  
 ... 
  
 replicas 
 : 
  
 3 
  
 revisionHistoryLimit 
 : 
  
 10 
  
 selector 
 : 
  
 matchLabels 
 : 
  
 app 
 : 
  
 metrics 
  
 department 
 : 
  
 sales 
  
 ... 
  
 spec 
 : 
  
 containers 
 : 
  
 - 
  
 image 
 : 
  
 us-docker.pkg.dev/google-samples/containers/gke/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 
 : 
  
 "2023-06-29T16:17:17Z" 
  
 lastUpdateTime 
 : 
  
 "2023-06-29T16:17:17Z" 
  
 message 
 : 
  
 Deployment has minimum availability. 
  
 reason 
 : 
  
 MinimumReplicasAvailable 
  
 status 
 : 
  
 "True" 
  
 type 
 : 
  
 Available 
  
 - 
  
 lastTransitionTime 
 : 
  
 "2023-06-29T16:17:12Z" 
  
 lastUpdateTime 
 : 
  
 "2023-06-29T16:17:17Z" 
  
 message 
 : 
  
 ReplicaSet "my-deployment-869f65669b" has successfully progressed. 
  
 reason 
 : 
  
 NewReplicaSetAvailable 
  
 status 
 : 
  
 "True" 
  
 type 
 : 
  
 Progressing 
  
 observedGeneration 
 : 
  
 1 
  
 readyReplicas 
 : 
  
 3 
  
 replicas 
 : 
  
 3 
  
 updatedReplicas 
 : 
  
 3

    6. Describe your Deployment:

       kubectl  
describe  
deployment  
my-deployment  
--kubeconfig  
 CLUSTER_KUBECONFIG

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

        Name 
 : 
  
 my-deployment 
 Namespace 
 : 
  
 default 
 CreationTimestamp 
 : 
  
 Thu, 29 Jun 2023 16:17:12 +0000 
 Labels 
 : 
  
< none 
> Annotations:            deployment.kubernetes.io/revision 
 : 
  
 1 
 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 
 : 
  
 us-docker.pkg.dev/google-samples/containers/gke/hello-app:2.0 
  
 Port 
 : 
  
< none 
>  
 Host Port 
 : 
  
< none 
>  
 Environment 
 : 
  
< none 
>  
 Mounts 
 : 
  
< none 
>  
 Volumes 
 : 
  
< none 
> Conditions 
 : 
  
 Type           Status  Reason 
  
 ----           ------  ------ 
  
 Available      True    MinimumReplicasAvailable 
  
 Progressing    True    NewReplicaSetAvailable 
 OldReplicaSets 
 : 
  
< none 
> NewReplicaSet 
 : 
  
 my-deployment-869f65669b (3/3 replicas created) 
 Events 
 : 
  
 Type    Reason             Age    From                   Message 
  
 ----    ------             ----   ----                   ------- 
  
 Normal  ScalingReplicaSet  6m50s  deployment-controller  Scaled up replica set my-deployment-869f65669b to 3

    Create 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 .

    To create a Service of type LoadBalancer :

    1. Copy the following manifest to a file named my-service.yaml :

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

      Here are the important things to understand about the Service in this exercise:

      • Any Pod that has the label app: metrics and the label department: sales is a member of the Service. 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 .

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

    2. Use kubectl apply to create the Service on your cluster:

       kubectl  
apply  
-f  
my-service.yaml  
--kubeconfig  
 CLUSTER_KUBECONFIG

      Replace CLUSTER_KUBECONFIG with the path of the kubeconfig file for your cluster.

    3. View your Service:

       kubectl  
get  
service  
my-service  
--output  
yaml  
--kubeconfig  
 CLUSTER_KUBECONFIG

      The output is similar to the following:

        apiVersion 
 : 
  
 v1 
 kind 
 : 
  
 Service 
 metadata 
 : 
  
 ... 
  
 name 
 : 
  
 my-service 
  
 namespace 
 : 
  
 default 
  
 ... 
 spec 
 : 
  
 allocateLoadBalancerNodePorts 
 : 
  
 true 
  
 clusterIP 
 : 
  
 10.96.2.165 
  
 clusterIPs 
 : 
  
 - 
  
 10.96.2.165 
  
 externalTrafficPolicy 
 : 
  
 Cluster 
  
 internalTrafficPolicy 
 : 
  
 Cluster 
  
 ipFamilies 
 : 
  
 - 
  
 IPv4 
  
 ipFamilyPolicy 
 : 
  
 SingleStack 
  
 ports 
 : 
  
 - 
  
 nodePort 
 : 
  
 31565 
  
 port 
 : 
  
 80 
  
 protocol 
 : 
  
 TCP 
  
 targetPort 
 : 
  
 8080 
  
 selector 
 : 
  
 app 
 : 
  
 metrics 
  
 department 
 : 
  
 sales 
  
 sessionAffinity 
 : 
  
 None 
  
 type 
 : 
  
 LoadBalancer 
 status 
 : 
  
 loadBalancer 
 : 
  
 ingress 
 : 
  
 - 
  
 ip 
 : 
  
 192.168.1.13

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

      The clusterIP isn't relevant to this exercise. The external IP address ( status.loadBalancer.ingress.ip ) comes from the range of addresses that you specified when you defined load balancer address pools ( spec.loadBalancer.addressPools ) in the cluster configuration file.

      As an example, take the values shown in the preceding output for your Service:

      • External IP address: 192.168.1.13
      • port : 80
      • nodePort : 31565
      • targetPort : 8080

      A client sends a request to 192.168.1.13 on TCP port 80 . The request is routed to your load balancer, and from there it is forwarded to a member Pod on TCP port 8080 .

    4. Call your Service:

       curl  
 INGRESS_IP_ADDRESS

      Replace INGRESS_IP_ADDRESS with the ingress IP address in the status section of the Service that you retrieved in the preceding step ( status.loadBalancer.ingress ).

      The output shows a Hello, world! message:

       Hello, world!
Version: 2.0.0
Hostname: my-deployment-869f65669b-wn4ft

    LoadBalancer port limits

    The LoadBalancer type is an extension of the NodePort type. So a Service of type LoadBalancer has a cluster IP address and one or more nodePort values. By default, Kubernetes allocates node ports to Services of type LoadBalancer . These allocations can quickly exhaust available node ports from the 2,768 allotted to your cluster. To save node ports, disable load balancer node port allocation by setting the allocateLoadBalancerNodePorts field to false in the LoadBalancer Service spec. This setting prevents Kubernetes from allocating node ports to LoadBalancer Services. For more information, see Disabling load balancer NodePort allocation in the Kubernetes documentation.

    Here's a manifest to create a Service that doesn't use any node ports:

      apiVersion 
 : 
  
 v1 
 kind 
 : 
  
 Service 
 metadata 
 : 
  
 name 
 : 
  
 service-does-not-use-nodeports 
 spec 
 : 
  
 selector 
 : 
  
 app 
 : 
  
 my-app 
  
 type 
 : 
  
 LoadBalancer 
  
 ports 
 : 
  
 - 
  
 port 
 : 
  
 8000 
  
 # Set allocateLoadBalancerNodePorts to false 
   
 allocateLoadBalancerNodePorts 
 : 
  
 false

    Delete your Service

    To delete your Service:

    1. Use kubectl delete to delete your Service from your cluster:

       kubectl  
delete  
service  
my-service  
--kubeconfig  
 CLUSTER_KUBECONFIG

    2. Verify that your Service has been deleted:

       kubectl  
get  
services  
--kubeconfig  
 CLUSTER_KUBECONFIG

      The output no longer shows my-service .

    Delete your Deployment

    To delete your Deployment:

    1. Use kubectl delete to delete your Deployment from your cluster:

       kubectl  
delete  
deployment  
my-deployment  
--kubeconfig  
 CLUSTER_KUBECONFIG

      Verify that your Deployment has been deleted:

       kubectl  
get  
deployments  
--kubeconfig  
 CLUSTER_KUBECONFIG

      The output no longer shows my-deployment .

    What's next

    Create a Service and an Ingress

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