This tutorial shows you how to package a web application in a Docker container image, and run that container image on a Google Kubernetes Engine (GKE) cluster. Then, you deploy the web application as a load-balanced set of replicas that can scale to the needs of your users ## Objectives - Package a sample web application into a Docker image - Upload the Docker image to Artifact Registry - Create a GKE cluster - Deploy the sample app to the cluster - Manage autoscaling for the deployment - Expose the sample app to the internet - Deploy a new version of the sample app ## Costs This tutorial uses the following billable components of Google Cloud: To generate a cost estimate based on your projected usage, use the pricing calculator When you finish this tutorial, you can avoid continued billing by deleting the resources you created. For more information, see Clean up ## Before you beginTake the following steps to enable the Kubernetes Engine API: - Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads - In the Google Cloud console, on the project selector page, select or create a Google Cloud project - Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project - Enable the Artifact Registry and Google Kubernetes Engine APIs - In the Google Cloud console, on the project selector page, select or create a Google Cloud project - Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project - Enable the Artifact Registry and Google Kubernetes Engine APIs Option A: Use Cloud Shell You can follow this tutorial using Cloud Shell, which comes preinstalled with the gcloud, docker, and kubectl command-line tools used in this tutorial. If you use Cloud Shell, you don't need to install these command-line tools on your workstation To use Cloud Shell: - Go to the Google Cloud console Click the Activate Cloud Shell button at the top of the Google Cloud console window A Cloud Shell session opens inside a new frame at the bottom of the Google Cloud console and displays a command-line prompt Option B: Use command-line tools locally If you prefer to follow this tutorial on your workstation, follow these steps to install the necessary tools Install the Google Cloud CLI Using the gcloud CLI, install the Kubernetes command-line tool kubectlis used to communicate with Kubernetes, which is the cluster orchestration system of GKE clusters: gcloud components install kubectl Install Docker Community Edition (CE) on your workstation. You use this to build a container image for the application Install the Git source control tool to fetch the sample application from GitHub ## Create a repository In this tutorial, you store an image in Artifact Registry and deploy it from the registry. Artifact Registry is the recommended container registry on Google Cloud. For this quickstart, you'll create a repository named hello-repo Set the PROJECT_IDenvironment variable to your Google Cloud project ID ( ). You'll use this environment variable when you build the container image and push it to your repository PROJECT_ID export PROJECT_ID= PROJECT_ID Confirm that the PROJECT_IDenvironment variable has the correct value: echo $PROJECT_ID Set your project ID for the Google Cloud CLI: gcloud config set project $PROJECT_ID Output: Updated property [core/project] Create the hello-reporepository with the following command: gcloud artifacts repositories create hello-repo \ --repository-format=docker \ --location= REGION\ --description="Docker repository" Replace with the a region for the repository, such as REGION us-west1. To see a list of available locations, run the command: gcloud artifacts locations list ## Building the container image In this tutorial, you deploy a sample web application called hello-app, a web server written in Go that responds to all requests with the message Hello, World! on port 8080 GKE accepts Docker images as the application deployment format Before deploying hello-app to GKE, you must package the hello-app source code as a Docker image To build a Docker image, you need source code and a Dockerfile. A Dockerfile contains instructions on how the image is built Download the hello-appsource code and Dockerfile by running the following commands: git clone httpsgithub.com/GoogleCloudPlatform/kubernetes-engine-samples cd kubernetes-engine-samples/hello-app Build and tag the Docker image for hello-app: docker build -t REGION-docker.pkg.devPROJECT_ID}/hello-repo/hello-app:v1 This command instructs Docker to build the image using the Dockerfilein the current directory, save it to your local environment, and tag it with a name, such as us-west1-docker.pkg.dev/my-project/hello-repo/hello-app:v1. The image is pushed to Artifact Registry in the next section - The PROJECT_IDvariable associates the container image with the hello-reporepository in your Google Cloud project - The us-west1-docker.pkg.devprefix refers to Artifact Registry, regional host for your repository - The Run the docker imagescommand to verify that the build was successful: docker images Output: REPOSITORY TAG IMAGE ID CREATED SIZE us-west1-docker.pkg.dev/my-project/hello-repo/hello-app v1 25cfadb1bf28 10 seconds ago 54 MB ## Running your container locally (optional) Test your container image using your local Docker engine: docker run --rm -p 8080:8080 REGION-docker.pkg.devPROJECT_ID}/hello-repo/hello-app:v1 If you're using Cloud Shell, click the Web Previewbutton and then select the 8080port number. GKE opens the preview URL on its proxy service in a new browser window Otherwise, open a new terminal window (or a Cloud Shell tab) and run the following command to verify that the container works and responds to requests with "Hello, World curl httplocalhost:8080 After you've seen a successful response, you candown the container by pressing Ctrl+Cin the tab where the docker runcommand is running ## Pushing the Docker image to Artifact Registry You must upload the container image to a registry so that your GKE cluster can download and run the container image. In this tutorial, you will store your container in Artifact Registry Configure the Docker command-line tool to authenticate to Artifact Registry: gcloud auth configure-docker REGION-docker.pkg.dev Push the Docker image that you just built to the repository: docker push REGION-docker.pkg.devPROJECT_ID}/hello-repo/hello-app:v1 ## Creating a GKE cluster Now that the Docker image is stored in Artifact Registry, create a GKE cluster to run hello-app. A GKE cluster consists of a pool of Compute Engine VM instances running Kubernetes, the open source cluster orchestration system that powers GKE Cloud Shell Set your Compute Engine zone or region. Depending on the mode of operation that you choose to use in GKE, specify a default zone or region. If you use the Standard mode, your cluster is zonal (for this tutorial), so set your default compute zone. If you use the Autopilot mode, your cluster is regional, so set your default compute region. Choose a zone or region that is closest to the Artifact Registry repository you created Standardcluster, such as us-west1-a: gcloud config set compute/zone COMPUTE_ZONE Autopilotcluster, such as us-west1: gcloud config set compute/region COMPUTE_REGION - Create a cluster named hello-cluster: Standardcluster: gcloud container clusters create hello-cluster Autopilotcluster: gcloud container clusters create-auto hello-cluster It takes a few minutes for your GKE cluster to be created and health-checked - After the command completes, run the following command to see the cluster's three Nodes: kubectl get nodes Output: NAME STATUS ROLES AGE VERSION gke-hello-cluster-default-pool-229c0700-cbtd Ready
92s v1.18.12-gke.1210 gke-hello-cluster-default-pool-229c0700-fc5j Ready 91s v1.18.12-gke.1210 gke-hello-cluster-default-pool-229c0700-n9l7 Ready 92s v1.18.12-gke.1210 Console Go to the Google Kubernetes Enginepage in the Google Cloud console Go to Google Kubernetes Engine Click Create Choose Standard or Autopilot mode and click Configure In the Namefield, enter the name hello-cluster Select a zone or region: Standardcluster: Under Location type, select Zonaland then select a Compute Engine zone from the Zonedrop-down list, such as us-west1-a Autopilotcluster: Select a Compute Engine region from the Regiondrop-down list, such as us-west1 - Click Create. This creates a GKE cluster Wait for the cluster to be created. When the cluster is ready, a green check mark appears next to the cluster name ## Deploying the sample app to GKE You are now ready to deploy the Docker image you built to your GKE cluster Kubernetes represents applications as Pods, which are scalable units holding one or more containers. The Pod is the smallest deployable unit in Kubernetes. Usually, you deploy Pods as a set of replicas that can be scaled and distributed together across your cluster. One way to deploy a set of replicas is through a Kubernetes Deployment In this section, you create a Kubernetes Deployment to run hello-app on your cluster. This Deployment has replicas (Pods). One Deployment Pod contains only one container: the hello-app Docker image You also create a HorizontalPodAutoscaler resource that scales the number of Pods from 3 to a number between 1 and 5, based on CPU load Cloud Shell Ensure that you are connected to your GKE cluster gcloud container clusters get-credentials hello-cluster --zone COMPUTE_ZONE Create a Kubernetes Deployment for your hello-appDocker image kubectl create deployment hello-app --image= REGION-docker.pkg.devPROJECT_ID}/hello-repo/hello-app:v1 Set the baseline number of Deployment replicas to 3 kubectl scale deployment hello-app --replicas=3 Create a HorizontalPodAutoscalerresource for your Deployment kubectl autoscale deployment hello-app --cpu-percent=80 --min=1 --max=5 To see the Pods created, run the following command: kubectl get pods Output: NAME READY STATUS RESTARTS AGE hello-app-784d7569bc-hgmpx 1/1 Running 0 10s hello-app-784d7569bc-jfkz5 1/1 Running 0 10s hello-app-784d7569bc-mnrrl 1/1 Running 0 15s Console Go to the Workloadspage in the Google Cloud console Click Deploy In the Specify containersection, select Existing container image In the Image pathfield, click Select In the Select container imagepane, select the hello-appimage you pushed to Artifact Registry and click Select In the Containersection, click Done, then click Continue In the Configurationsection, under Labels, enter appfor Keyand hello-appfor Value Under Configuration YAML, click View YAML. This opens a YAML configuration file representing the two Kubernetes API resources about to be deployed into your cluster: one Deployment, and one HorizontalPodAutoscalerfor that Deployment Click Close, then click Deploy When the Deployment Pods are ready, the Deployment detailspage opens Under Managed pods, note the three running Pods for the hello-appDeployment ## Exposing the sample app to the internet While Pods do have individually-assigned IP addresses, those IPs can only be reached from inside your cluster. Also, GKE Pods are designed to be ephemeral, starting or stopping based on scaling needs. And when a Pod crashes due to an error, GKE automatically redeploys that Pod, assigning a new Pod IP address each time What this means is that for any Deployment, the set of IP addresses corresponding to the active set of Pods is dynamic. We need a way to 1) group Pods together into one static hostname, and 2) expose a group of Pods outside the cluster, to the internet Kubernetes Services solve for both of these problems Services group Pods into one static IP address, reachable from any Pod inside the cluster GKE also assigns a DNS hostname to that static IP. For example, hello-app.default.svc.cluster.local The default Service type in GKE is called ClusterIP, where the Service gets an IP address reachable only from inside the cluster To expose a Kubernetes Service outside the cluster, create a Service of type LoadBalancer This type of Service spawns an External Load Balancer IP for a set of Pods, reachable through the internet In this section, you expose the hello-app Deployment to the internet using a Service of type LoadBalancer Cloud Shell Use the kubectl exposecommand to generate a Kubernetes Service for the hello-appdeployment: kubectl expose deployment hello-app --name=hello-app-service --type=LoadBalancer --port 80 --target-port 8080 Here, the --portflag specifies the port number configured on the Load Balancer, and the --target-portflag specifies the port number that the hello-appcontainer is listening on Run the following command to get the Service details for hello-app-service: kubectl get service Output: NAME CLUSTER-IP EXTERNAL-IP PORT(S) AGE hello-app-service 10.3.251.122 203.0.113.0 80:30877/TCP 10s Copy the EXTERNAL_IPaddress to the clipboard (for instance: 203.0.113.0) Console Go to the Workloadspage in the Google Cloud console Click hello-app From the Deployment details page, click Actions > Expose In the Exposedialog, set the Target portto 8080. This is the port the hello-appcontainer listens on From the Service typedrop-down list, select Load balancer Click Exposeto create a Kubernetes Service for hello-app When the Load Balancer is ready, the Service detailspage opens Scroll down to the External endpointsfield, and copy the IP address Now that the hello-app Pods are exposed to the internet through a Kubernetes Service, you can open a new browser tab, and navigate to the Service IP address you copied to the clipboard. A Hello, World! message appears, along with a Hostname field. The Hostname corresponds to one of the three hello-app Pods serving your HTTP request to your browser ## Deploying a new version of the sample app In this section, you upgrade hello-app to a new version by building and deploying a new Docker image to your GKE cluster GKE's rolling update feature lets you update your Deployments without downtime. During a rolling update, your GKE cluster incrementally replaces the existing hello-app Pods with Pods containing the Docker image for the new version During the update, your load balancer service routes traffic only into available Pods Return to Cloud Shell, where you have cloned the hello app source code and Dockerfile. Update the function hello()in the main.gofile to report the new version 2.0.0 Build and tag a new hello-appDocker image docker build -t REGION-docker.pkg.devPROJECT_ID}/hello-repo/hello-app:v2 Push the image to Artifact Registry docker push REGION-docker.pkg.devPROJECT_ID}/hello-repo/hello-app:v2 Now you're ready to update your hello-app Kubernetes Deployment to use a new Docker image Cloud Shell Apply a rolling update to the existing hello-appDeployment with an image update using the kubectl set imagecommand: kubectl set image deployment/hello-app hello-app= REGION-docker.pkg.devPROJECT_ID}/hello-repo/hello-app:v2 Watch the running Pods running the v1image stop, and new Pods running the v2image start watch kubectl get pods Output: NAME READY STATUS RESTARTS AGE hello-app-89dc45f48-5bzqp 1/1 Running 0 2m42s hello-app-89dc45f48-scm66 1/1 Running 0 2m40s In a separate tab, navigate again to the hello-app-serviceExternal IP. You should now see the Versionset to 2.0.0 Console Go to the Workloadspage in the Google Cloud console Click hello-app On the Deployment detailspage, click Actions > Rolling update In the Rolling updatedialog, set the Image of hello-appfield to REGION-docker.pkg.dev/ PROJECT_ID/hello-repo/hello-app:v2 Click Update On the Deployment detailspage, inspect the Active Revisionssection. You should now see two Revisions, 1 and 2. Revision 1 corresponds to the initial Deployment you created earlier. Revision 2 is the rolling update you just started After a few moments, refresh the page. Under Managed pods, all of the replicas of hello-appnow correspond to Revision 2 In a separate tab, navigate again to the Service IP address you copied. The Versionshould be 2.0.0 ## Clean up To avoid incurring charges to your Google Cloud account for the resources used in this tutorial, either delete the project that contains the resources, or keep the project and delete the individual resources Delete the Service:This deallocates the Cloud Load Balancer created for your Service: kubectl delete service hello-app-service Delete the cluster:This deletes the resources that make up the cluster, such as the compute instances, disks, and network resources: gcloud container clusters delete hello-cluster --zone COMPUTE_ZONE Delete your container images:This deletes the Docker images you pushed to Artifact Registry gcloud artifacts docker images delete \ REGION-docker.pkg.devPROJECT_ID}/hello-repo/hello-app:v1 \ --delete-tags --quiet gcloud artifacts docker images delete \ REGION-docker.pkg.devPROJECT_ID}/hello-repo/hello-app:v2 \ --delete-tags --quiet ## What's next Learn about Pricing for GKE and use the Pricing Calculator to estimate costs Read the Load Balancers tutorial, which demonstrates advanced load balancing configurations for web applications Configure a static IP and domain name for your application Explore other Kubernetes Engine tutorials Explore reference architectures, diagrams, tutorials, and best practices about Google Cloud. Take a look at our Cloud Architecture Center ## Try it for yourself If you're new to Google Cloud, create an account to evaluate how GKE performs in real-world scenarios.