Deploying a containerized web application

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 Container 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.

Before you begin

Take the following steps to enable the Kubernetes Engine API:

1. Visit the Kubernetes Engine page in the Google Cloud Console.
2. Create or select a project.
3. Wait for the API and related services to be enabled. This can take several minutes.

4. Make sure that billing is enabled for your Cloud project. Learn how to confirm that billing is enabled for your project.

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:

1. Go to the Google Cloud Console.

2. Click the Activate Cloud Shell button at the top of the Cloud Console window.

   A Cloud Shell session opens inside a new frame at the bottom of the 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.

Note: if you are using an existing environment where gcloud has already been installed, make sure gcloud is initialized with your user account.

1. Install the Cloud SDK, which includes the gcloud command-line tool.

2. Using the gcloud command line tool, install the Kubernetes command-line tool. kubectl is used to communicate with Kubernetes, which is the cluster orchestration system of GKE clusters:

   gcloud components install kubectl

3. Install Docker Community Edition (CE) on your workstation. You use this to build a container image for the application.

4. Install the Git source control tool to fetch the sample application from GitHub.

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.

1. Download the hello-app source code and Dockerfile by running the following commands:

   git clone https://github.com/GoogleCloudPlatform/kubernetes-engine-samples
   cd kubernetes-engine-samples/hello-app
   

2. Set the PROJECT_ID environment variable to your Google Cloud project ID (project-id). The PROJECT_ID variable associates the container image with your project's Container Registry.

   export PROJECT_ID=project-id
   

   Note: In this tutorial, you use a container image from Container Registry. Recently, Google launched Artifact Registry, a new universal package management service that supports containers and other formats. Artifact Registry provides greater flexibility and control over your artifacts. Learn more about the differences between these registries in Feature comparison.

3. Confirm that the PROJECT_ID environment variable has the correct value:

   echo $PROJECT_ID
   

4. Build and tag the Docker image for hello-app:

   docker build -t gcr.io/${PROJECT_ID}/hello-app:v1 .
   

   This command instructs Docker to build the image using the Dockerfile in the current directory and tag it with a name, such as gcr.io/my-project/hello-app:v1. The gcr.io prefix refers to Container Registry, where the image is hosted. Running this command does not upload the image.

   Note: If prompted, authorize Cloud Shell to make Google Cloud API calls.

5. Run the docker images command to verify that the build was successful:

   docker images
   

   Output:

   REPOSITORY                     TAG                 IMAGE ID            CREATED             SIZE
   gcr.io/my-project/hello-app    v1                  25cfadb1bf28        10 seconds ago      54 MB
   

Running your container locally (optional)

1. Test your container image using your local Docker engine:

   docker run --rm -p 8080:8080 gcr.io/${PROJECT_ID}/hello-app:v1
   

2. If you're using Cloud Shell, click the Web Preview button and then select the 8080 port number. GKE opens the preview URL on its proxy service in a new browser window.

3. 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 http://localhost:8080

   After you've seen a successful response, you can shut down the container by pressing Ctrl+C in the tab where the docker run command is running.

Pushing the Docker image to Container Registry

You must upload the container image to a registry so that your GKE cluster can download and run the container image. In Google Cloud, Container Registry is available by default.

1. Enable the Container Registry API for the Google Cloud project you are working on:

   gcloud services enable containerregistry.googleapis.com
   

2. Configure the Docker command-line tool to authenticate to Container Registry:

   gcloud auth configure-docker
   

3. Push the Docker image that you just built to Container Registry:

   docker push gcr.io/${PROJECT_ID}/hello-app:v1
   

Creating a GKE cluster

Now that the Docker image is stored in Container 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

1. Set your project ID option for the gcloud tool:

   gcloud config set project $PROJECT_ID
   

2. Set your 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 the zone or region that is closest to you.

   • Standard cluster, such as us-west1-a:

     gcloud config set compute/zone compute-zone
     

   • Autopilot cluster, such as us-west1:

     gcloud config set compute/region compute-region
     

3. Create a cluster named hello-cluster:

   • Standard cluster:

     gcloud container clusters create hello-cluster
     

   • Autopilot cluster:

     gcloud container clusters create-auto hello-cluster
     

   It takes a few minutes for your GKE cluster to be created and health-checked.

4. After the command completes, run the following command to see the cluster's three worker VM instances:

   gcloud compute instances list
   

   Output:

   NAME                                           ZONE        MACHINE_TYPE   PREEMPTIBLE  INTERNAL_IP  EXTERNAL_IP    STATUS
   gke-hello-cluster-default-pool-d8b498d3-0d6r  us-east1-b   e2-medium                   10.142.0.4   35.237.4.149   RUNNING
   gke-hello-cluster-default-pool-d8b498d3-k29m  us-east1-b   e2-medium                   10.142.0.3   34.75.248.193  RUNNING
   gke-hello-cluster-default-pool-d8b498d3-vcrj  us-east1-b   e2-medium                   10.142.0.2   35.196.51.235  RUNNING
   

Console

1. Visit the Google Kubernetes Engine menu in Cloud Console.

   Visit the Google Kubernetes Engine menu

2. Click Create.

3. Choose Standard or Autopilot mode and click Configure.

4. In the Name field, enter the name hello-cluster.

5. Select a zone or region:

   • Standard cluster: Under Location type, select Zonal and then select a Compute Engine zone from the Zone drop-down list, such as us-west1-a.

   • Autopilot cluster: Select a Compute Engine region from the Region drop-down list, such as us-west1.

6. Click Create. This creates a GKE cluster.

7. 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

1. Create a Kubernetes Deployment for your hello-app Docker image.

   kubectl create deployment hello-app --image=gcr.io/${PROJECT_ID}/hello-app:v1
   

2. Set the baseline number of Deployment replicas to 3.

   kubectl scale deployment hello-app --replicas=3
   

3. Create a HorizontalPodAutoscaler resource for your Deployment.

   kubectl autoscale deployment hello-app --cpu-percent=80 --min=1 --max=5
   

4. 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

1. Visit the GKE Workloads menu in Cloud Console.

   Visit the Workloads menu

2. Click Deploy.

3. In the Container section, select Existing container image.

4. In the Image path field, click Select.

5. In the Select container image pane, select the hello-app image you pushed to Container Registry and click Select.

6. In the Container section, click Done, then click Continue.

7. In the Configuration section, under Labels, enter app for Key and hello-app for Value.

8. 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 HorizontalPodAutoscaler for that Deployment.

9. Click Close, then click Deploy.

10. When the Deployment Pods are ready, the Deployment details page opens.

11. Under Managed pods, note the three running Pods for the hello-app Deployment.

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 instance: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.

Note: External Load Balancers are (subject to billing) separate from GKE's costs.

Cloud Shell

1. Use the kubectl expose command to generate a Kubernetes Service for the hello-app deployment.

   kubectl expose deployment hello-app --name=hello-app-service --type=LoadBalancer --port 80 --target-port 8080
   

   Here, the --port flag specifies the port number configured on the Load Balancer, and the --target-port flag specifies the port number that the hello-app container is listening on.

2. 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
   

3. Copy the EXTERNAL_IP address to the clipboard (for instance: 203.0.113.0).

   Note: It might take a few minutes for the Load Balancer to be provisioned. Until the Load Balancer is provisioned, you might see a <pending> IP address.

Console

1. Visit the Google Kubernetes Engine Workloads menu in Cloud Console.

   Visit the Workloads menu

2. Click hello-app.

3. From the Deployment details page, click Actions > Expose.

4. In the Expose dialog, set the Target port to 8080. This is the port the hello-app container listens on.

5. From the Service type drop-down list, select Load balancer.

6. Click Expose to create a Kubernetes Service for hello-app.

7. When the Load Balancer is ready, the Service details page opens.

8. Scroll down to the External endpoints field, 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 to 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.

1. Return to Cloud Shell, where you have cloned the hello app source code and Dockerfile. Update the function hello() in the main.go file to report the new version 2.0.0.

2. Build and tag a new hello-app Docker image.

   docker build -t gcr.io/${PROJECT_ID}/hello-app:v2 .
   

3. Push the image to Container Registry.

   docker push gcr.io/${PROJECT_ID}/hello-app:v2
   

Now you're ready to update your hello-app Kubernetes Deployment to use a new Docker image.

Note: Because you created a HorizontalPodAutoscaler earlier, the number of hello-app Pods running in this section might be fewer than the three Pods initially deployed. Your GKE cluster might have scaled down the number of Pods based on low CPU usage.

Cloud Shell

1. Apply a rolling update to the existing Deployment with an image update:

   kubectl set image deployment/hello-app hello-app=gcr.io/${PROJECT_ID}/hello-app:v2
   

2. Watch the running Pods running the v1 image stop, and new Pods running the v2 image 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
   

3. In a separate tab, navigate again to the hello-app-service External IP. You should now see the Version set to 2.0.0.

Console

1. Visit the Google Kubernetes Engine Workloads menu in Cloud Console.

   Visit the Workloads menu

2. Click hello-app.

3. On the Deployment details page, click Actions > Rolling update.

4. In the Rolling update dialog, set the Image of hello-app field to gcr.io/PROJECT_ID/hello-app:v2, replacing PROJECT_ID with your project ID.

5. Click Update.

6. On the Deployment details page, inspect the Active Revisions section. 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.

7. After a few moments, refresh the page. Under Managed pods, all of the replicas of hello-app now correspond to Revision 2.

8. In a separate tab, navigate again to the Service IP address you copied. The Version should be 2.0.0.

Cleaning 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.

1. Delete the Service: This deallocates the Cloud Load Balancer created for your Service:

   kubectl delete service hello-app-service

2. 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

3. Delete your container images: This deletes the Docker images you pushed to Container Registry.

    gcloud container images delete gcr.io/${PROJECT_ID}/hello-app:v1  --force-delete-tags --quiet
    gcloud container images delete gcr.io/${PROJECT_ID}/hello-app:v2  --force-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.

• Try out other Google Cloud features for yourself. Have a look at our tutorials.