Create a multi-tier web application with Redis and PHP

Autopilot Standard

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This tutorial demonstrates how to build a multi-tier web application using Google Kubernetes Engine (GKE).

In this tutorial, you do the following:

• Set up a web application with an external IP address and a load balancer.
• Create a Redis cluster with a single master (leader) and multiple replicas (followers).

The example describes the following Kubernetes concepts:

• Declarative configuration using YAML manifest files
• Deployments, which are Kubernetes resources that determine the configuration for a set of replicated Pods
• Services to create internal and external load balancers for a set of Pods

Objectives

To deploy and run the application on GKE:

1. Set up the Redis leader
2. Set up two Redis followers
3. Set up the web frontend
4. Visit the website
5. Scale up the web frontend

The following diagram shows you an overview of the cluster architecture you create by completing these objectives:

Costs

In this document, you use the following billable components of Google Cloud:

• GKE

To generate a cost estimate based on your projected usage, use the pricing calculator. New Google Cloud users might be eligible for a free trial.

When you finish the tasks that are described in this document, you can avoid continued billing by deleting the resources that you created. For more information, see Clean up.

Before you begin

Cloud Shell is preinstalled with the software you need for this tutorial, including kubectl and gcloud CLI. If you don't use Cloud Shell, you must install the gcloud CLI.

1. 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.
2. Install the Google Cloud CLI.

3. To initialize the gcloud CLI, run the following command:

   gcloud init

   Note: If you installed the gcloud CLI previously, make sure you have the latest version by running gcloud components update.

4. Create or select a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   • Create a Google Cloud project:

     gcloud projects create PROJECT_ID

     Replace PROJECT_ID with a name for the Google Cloud project you are creating.

   • Select the Google Cloud project that you created:

     gcloud config set project PROJECT_ID

     Replace PROJECT_ID with your Google Cloud project name.

5. Make sure that billing is enabled for your Google Cloud project.

6. Enable the GKE API:

   gcloud services enable container.googleapis.com

7. Install the Google Cloud CLI.

8. To initialize the gcloud CLI, run the following command:

   gcloud init

   Note: If you installed the gcloud CLI previously, make sure you have the latest version by running gcloud components update.

9. Create or select a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   • Create a Google Cloud project:

     gcloud projects create PROJECT_ID

     Replace PROJECT_ID with a name for the Google Cloud project you are creating.

   • Select the Google Cloud project that you created:

     gcloud config set project PROJECT_ID

     Replace PROJECT_ID with your Google Cloud project name.

10. Make sure that billing is enabled for your Google Cloud project.

11. Enable the GKE API:

    gcloud services enable container.googleapis.com

Prepare the environment

To set up your environment, follow these steps:

1. Set environment variables:

   export PROJECT_ID=PROJECT_ID
   export COMPUTE_LOCATION=COMPUTE_LOCATION
   

   Replace the following:

   • PROJECT_ID: your Google Cloud project ID
   • COMPUTE_LOCATION: a Compute Engine location, such as us-central1.

2. Clone the GitHub repository:

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

3. Change to the working directory:

   cd kubernetes-engine-samples/quickstarts/guestbook/
   

Create a GKE cluster

Create an Autopilot or Standard GKE cluster:

Autopilot

gcloud container clusters create-auto guestbook \
    --location=${COMPUTE_LOCATION} \

Standard

gcloud container clusters create guestbook \
    --location=${COMPUTE_LOCATION} \
    --num-nodes=4

Connect to the cluster

Configure kubectl to communicate with the cluster:

gcloud container clusters get-credentials guestbook \
    --location=${COMPUTE_LOCATION}

Set up the Redis leader

The application uses Redis to store its data. The application writes its data to a Redis leader instance and reads data from multiple Redis follower instances.

1. The following manifest describes a Kubernetes Deployment that runs a single replica Redis leader Pod:

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: redis-leader
     labels:
       app: redis
       role: leader
       tier: backend
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: redis
     template:
       metadata:
         labels:
           app: redis
           role: leader
           tier: backend
       spec:
         containers:
         - name: leader
           image: "docker.io/redis:6.0.5"
           resources:
             requests:
               cpu: 100m
               memory: 100Mi
           ports:
           - containerPort: 6379

   Apply the manifest to your cluster:

   kubectl apply -f redis-leader-deployment.yaml
   

2. Verify that the Redis leader Pod is running:

   kubectl get pods
   

   The output is similar to the following:

   NAME                           READY     STATUS    RESTARTS   AGE
   redis-leader-343230949-qfvrq   1/1       Running   0          43s
   

   It might take several minutes for STATUS to change from Pending to Running.

Create the Redis leader Service

The web application needs to communicate with the Redis leader to write its data. You can create a Service to proxy the traffic to the Redis leader Pod.

A Service is a Kubernetes abstraction that defines a logical set of Pods and a policy to enable access to the Pods. When you create a Service, you describe which Pods to proxy based on Pod labels.

1. The following manifest describes a Service for the Redis leader:

   apiVersion: v1
   kind: Service
   metadata:
     name: redis-leader
     labels:
       app: redis
       role: leader
       tier: backend
   spec:
     ports:
     - port: 6379
       targetPort: 6379
     selector:
       app: redis
       role: leader
       tier: backend

   This manifest includes a set of label selectors. These labels match the set of labels that are deployed in the previous step. Therefore, this Service routes the network traffic to the Redis leader Pod created in a previous step.

   The ports section of the manifest declares a single port mapping. The Service routes the traffic on port: 6379 to the targetPort: 6379 of the containers that match the specified selector labels. The containerPort used in the Deployment must match the targetPort to route traffic to the Deployment.

   Apply the manifest to your cluster:

   kubectl apply -f redis-leader-service.yaml
   

2. Verify that GKE created the Service:

   kubectl get service
   

   The output is similar to the following:

   NAME           CLUSTER-IP      EXTERNAL-IP   PORT(S)    AGE
   kubernetes     10.51.240.1     <none>        443/TCP    42s
   redis-leader   10.51.242.233   <none>        6379/TCP   12s
   

Set up Redis followers

Although the Redis leader is a single Pod, you can make it highly available and meet traffic demands by adding a few Redis followers, or replicas.

1. The following manifest describes a Deployment for the Redis follower Pods:

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: redis-follower
     labels:
       app: redis
       role: follower
       tier: backend
   spec:
     replicas: 2
     selector:
       matchLabels:
         app: redis
     template:
       metadata:
         labels:
           app: redis
           role: follower
           tier: backend
       spec:
         containers:
         - name: follower
           image: us-docker.pkg.dev/google-samples/containers/gke/gb-redis-follower:v2
           resources:
             requests:
               cpu: 100m
               memory: 100Mi
           ports:
           - containerPort: 6379

2. Apply the manifest to your cluster:

   kubectl apply -f redis-follower-deployment.yaml
   

3. Verify that the two Redis follower replicas are running:

   kubectl get pods
   

   The output is similar to the following:

   NAME                              READY   STATUS    RESTARTS   AGE
   redis-follower-76588f55b7-bnsq6   1/1     Running   0          27s
   redis-follower-76588f55b7-qvtws   1/1     Running   0          27s
   redis-leader-dd446dc55-kl7nl      1/1     Running   0          119s
   

   It might take several minutes for STATUS to change from Pending to Running.

Create the Redis follower Service

The web application must communicate with the Redis followers to read data. To make the Redis followers discoverable, you must set up a Service.

1. The following manifest describes a Service for the Redis followers:

   apiVersion: v1
   kind: Service
   metadata:
     name: redis-follower
     labels:
       app: redis
       role: follower
       tier: backend
   spec:
     ports:
       # the port that this service should serve on
     - port: 6379
     selector:
       app: redis
       role: follower
       tier: backend

   This manifest specifies the Service runs on port 6379. The selector field of the Service matches the Redis follower Pods created in the previous step.

   Apply the manifest to your cluster:

   kubectl apply -f redis-follower-service.yaml
   

2. Verify GKE created the Service:

   kubectl get service
   

   The output is similar to the following:

   NAME           CLUSTER-IP      EXTERNAL-IP   PORT(S)    AGE
   kubernetes     10.51.240.1     <none>        443/TCP    1m
   redis-leader   10.51.242.233   <none>        6379/TCP   49s
   redis-follower 10.51.247.238   <none>        6379/TCP   3s
   

Set up the application web frontend

Now that you have Redis storage for your application, start the web servers. Like the Redis followers, the frontend is deployed using a Kubernetes Deployment.

The web application uses a PHP frontend, which is configured to communicate with either the Redis follower or leader Services, depending on whether the request is a read or a write. The frontend exposes a JSON interface, and serves a jQuery Ajax-based UI.

1. The following manifest describes a Deployment for the web server:

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: frontend
   spec:
     replicas: 3
     selector:
       matchLabels:
           app: guestbook
           tier: frontend
     template:
       metadata:
         labels:
           app: guestbook
           tier: frontend
       spec:
         containers:
         - name: php-redis
           image: us-docker.pkg.dev/google-samples/containers/gke/gb-frontend:v5
           env:
           - name: GET_HOSTS_FROM
             value: "dns"
           resources:
             requests:
               cpu: 100m
               memory: 100Mi
           ports:
           - containerPort: 80

   The manifest file specifies the environment variable GET_HOSTS_FROM=dns. When you provide the configuration to the web frontend application, the frontend application uses the hostnames redis-follower and redis-leader to performs a DNS lookup. The DNS lookup finds the IP addresses of the Services you created in the previous steps. This concept is called DNS service discovery.

   Apply the manifest to your cluster:

   kubectl apply -f frontend-deployment.yaml
   

2. Verify that the replicas are running:

   kubectl get pods -l app=guestbook -l tier=frontend
   

   The output is similar to the following:

   NAME                        READY   STATUS    RESTARTS   AGE
   frontend-7b78458576-8kp8s   1/1     Running   0          37s
   frontend-7b78458576-gg86q   1/1     Running   0          37s
   frontend-7b78458576-hz87g   1/1     Running   0          37s
   

Expose the frontend on an external IP address

With the current configuration, the redis-follower and redis-leader Services that you created in the previous steps are only accessible within the GKE cluster because the default type for a Service is ClusterIP.

A ClusterIP Service provides a single IP address for the set of Pods where the Service is pointing. This IP address is accessible only within the cluster.

To make the web frontend Service externally accessible, you can specify type: LoadBalancer or type: NodePort in the Service configuration depending on your requirements.

The following manifest describes a Service of type LoadBalancer:

apiVersion: v1
kind: Service
metadata:
  name: frontend
  labels:
    app: guestbook
    tier: frontend
spec:
  type: LoadBalancer
  ports:
    # the port that this service should serve on
  - port: 80
  selector:
    app: guestbook
    tier: frontend

The port declaration under the ports section specifies port: 80 and the targetPort is not specified. When you omit the targetPort property, it defaults to the value of the port field. In this case, this Service routes external traffic on port 80 to the port 80 of the containers in the frontend Deployment.

Apply the manifest to your cluster:

kubectl apply -f frontend-service.yaml

When the frontend Service is created, GKE creates a load balancer and an external IP address. These resources are subject to billing.

Visit the application website

To access the application website, get the external IP address of the frontend Service:

kubectl get service frontend

The output is similar to the following:

NAME       CLUSTER-IP      EXTERNAL-IP        PORT(S)        AGE
frontend   10.51.242.136   109.197.92.229     80:32372/TCP   1m

The EXTERNAL-IP column might show <pending> while the load balancer is being created. This might take several minutes. If you see errors such as Does not have minimum availability, wait a few minutes. This temporary error occurs because GKE re-creates the nodes to make the changes.

Copy the IP address and open the page in your browser:

Try adding some entries by typing in a message, and clicking Submit. The message you typed appears in the frontend. This message indicates that data is successfully added to Redis through the Services that you created.

Scale up the web frontend

Suppose your application has been running for a while, and it gets a sudden burst of publicity. You decide it would be a good idea to add more web servers to your frontend. You can do this by increasing the number of Pods.

1. Scale up the number of frontend Pods:

   kubectl scale deployment frontend --replicas=5
   

   The output is similar to the following:

   deployment.extensions/frontend scaled
   

2. Verify the number of replicas that are running:

   kubectl get pods
   

   The output is similar to the following:

   NAME                             READY     STATUS    RESTARTS   AGE
   frontend-88237173-3s3sc          1/1       Running   0          1s
   frontend-88237173-twgvn          1/1       Running   0          1s
   frontend-88237173-5p257          1/1       Running   0          23m
   frontend-88237173-84036          1/1       Running   0          23m
   frontend-88237173-j3rvr          1/1       Running   0          23m
   redis-leader-343230949-qfvrq     1/1       Running   0          54m
   redis-follower-132015689-dp23k   1/1       Running   0          37m
   redis-follower-132015689-xq9v0   1/1       Running   0          37m
   

   You can scale down the number of frontend Pods by using the same command, replacing 5 with 1.

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 project

Caution: Deleting a project has the following effects:

• Everything in the project is deleted. If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.
• Custom project IDs are lost. When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an appspot.com URL, delete selected resources inside the project instead of deleting the whole project.

If you plan to explore multiple architectures, tutorials, or quickstarts, reusing projects can help you avoid exceeding project quota limits.

Delete a Google Cloud project:

gcloud projects delete PROJECT_ID

Delete the individual resources

If you used an existing project and you don't want to delete it, delete the individual resources.

1. Delete the frontend Service:

   kubectl delete service frontend
   

2. Delete the GKE cluster:

   gcloud container clusters delete guestbook
   

What's next

• Learn how to configure horizontal Pod autoscaling.
• Learn how to deploy WordPress on GKE with Persistent Disk and Cloud SQL.
• Learn how to Configure domain names with static IP addresses.
• Explore other Kubernetes Engine tutorials.