Create a Guestbook with Redis and PHP

This tutorial demonstrates how to build a simple multi-tier web application using GKE. The tutorial application is a guestbook that allows visitors to enter text in a log and to see the last few logged entries.

The tutorial shows how to set up the guestbook web service on an external IP with a load balancer, and how to run a Redis cluster with a single master (leader) and multiple replicas (followers).

The example highlights a number of important GKE concepts:

Objectives

To deploy and run the guestbook application on GKE, you will:

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

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 Google Cloud project. Learn how to confirm billing is enabled for your project.

Install the following command-line tools used in this tutorial:

  • gcloud is used to create and delete Kubernetes Engine clusters. gcloud is included in the Google Cloud SDK.
  • kubectl is used to manage Kubernetes, the cluster orchestration system used by Kubernetes Engine. You can install kubectl using gcloud:
    gcloud components install kubectl

Set defaults for the gcloud command-line tool

To save time typing your project ID and Compute Engine zone options in the gcloud command-line tool, you can set the defaults:
gcloud config set project project-id
gcloud config set compute/zone compute-zone

Create a GKE cluster

The first step is to create a GKE cluster on which you'll run the guestbook application and the Redis service.

Create a GKE cluster named guestbook:

gcloud container clusters create guestbook --num-nodes=4

You can list the clusters running in your project using the following commands:

gcloud container clusters list
gcloud container clusters describe guestbook

Step 1: Set up the Redis leader

The guestbook application uses Redis to store its data. It writes its data to a Redis leader instance and reads data from multiple Redis follower instances. The first step is to deploy a Redis leader.

First, clone the sample manifests.

git clone https://github.com/GoogleCloudPlatform/kubernetes-engine-samples
cd kubernetes-engine-samples/guestbook
git checkout abbb383

Use the manifest file named redis-leader-deployment to deploy the Redis leader. This manifest file specifies 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

Run the following command to deploy the Redis leader:

kubectl apply -f redis-leader-deployment.yaml

Verify that the Redis leader Pod is running:

kubectl get pods
Output:
NAME                           READY     STATUS    RESTARTS   AGE
redis-leader-343230949-qfvrq   1/1       Running   0          43s

Run the following command to take a look at the logs from the Redis leader Pod:

kubectl logs deployment/redis-leader

Output:

1:M 24 Jun 2020 14:48:20.917 * Ready to accept connections

Create the Redis leader service

The guestbook application needs to communicate to Redis leader to write its data. You need to create a Service to proxy the traffic to the Redis leader Pod.

A Service is a Kubernetes abstraction which defines a logical set of Pods and a policy by which to access them. It is effectively a named load balancer that proxies traffic to one or more Pods. When you set up a Service, you tell it the Pods to proxy based on Pod labels.

Take a look at the redis-leader-service.yaml manifest file describing a Service resource 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 file creates a Service named redis-leader with 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 Step 1.

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

Start up the Redis leader Service by running:

kubectl apply -f redis-leader-service.yaml

Verify that the service is created:

kubectl get service
Output:
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

Step 2: 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.

Take a look at the redis-follower-deployment.yaml manifest file describing 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: gcr.io/google_samples/gb-redis-follower:v2
        resources:
          requests:
            cpu: 100m
            memory: 100Mi
        ports:
        - containerPort: 6379

To create the Redis follower Deployment, run:

kubectl apply -f redis-follower-deployment.yaml

Verify that the two Redis follower replicas are running by querying the list of Pods:

kubectl get pods
Output:
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

Get the Pod logs for one of the Redis followers.

kubectl logs deployment/redis-follower
Output:
1:M 24 Jun 2020 14:50:43.617 * Background saving terminated with success
1:M 24 Jun 2020 14:50:43.617 * Synchronization with replica 10.12.3.4:6379 succeeded

Create the Redis follower service

The guestbook application needs to communicate to Redis followers to read data. To make the Redis followers discoverable, you need to set up another Service.

The redis-follower-service.yaml defines the Service configuration 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 file defines a Service named redis-follower running on port 6379. Note that the selector field of the Service matches the Redis follower Pods created in the previous step.

Create the redis-follower Service by running:

kubectl apply -f redis-follower-service.yaml

Verify that the Service is created:

kubectl get service
Output:
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

Step 3: Set up the guestbook web frontend

Now that you have the Redis storage of your guestbook up and running, start the guestbook web servers. Like the Redis followers, the frontend will be deployed using a Kubernetes Deployment.

The guestbook app uses a simple PHP frontend. It is configured to talk to either the Redis follower or leader Services, depending on whether the request is a read or a write. The frontend exposes a simple JSON interface, and serves a jQuery-Ajax-based UX.

View the frontend-deployment.yaml manifest file describing the Deployment for the guestbook 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: gcr.io/google_samples/gb-frontend:v5
        env:
        - name: GET_HOSTS_FROM
          value: "dns"
        resources:
          requests:
            cpu: 100m
            memory: 100Mi
        ports:
        - containerPort: 80

To create the guestbook web frontend Deployment, run:

kubectl apply -f frontend-deployment.yaml

Verify that the three replicas are running by querying the list of the labels that identify the web frontend:

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

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

Expose frontend on an external IP address

The redis-follower and redis-leader Services you created in the previous steps are only accessible within the GKE cluster, because the default type for a Service is ClusterIP. ClusterIP provides a single IP address for the set of Pods the Service is pointing to. This IP address is accessible only within the cluster.

However, you need the guestbook web frontend Service to be externally visible. That is, you want a client to be able to request the Service from outside the GKE cluster. To accomplish this, you can specify type: LoadBalancer or type: NodePort in the Service configuration depending on your needs. In this example, you will use type: LoadBalancer. The frontend-service.yaml manifest file specifying this configuration looks like this:

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

When the frontend Service is created, GKE creates a load balancer and an external IP address. Note that these resources are subject to billing. 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 will route external traffic on port 80 to the port 80 of the containers in the frontend Deployment.

To create the Service, run the following command:

kubectl apply -f frontend-service.yaml

Step 4: Visit the guestbook website

To access the guestbook Service, you need to find the external IP of the Service you just set up by running the command:

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

Copy the IP address in EXTERNAL-IP column, and load the page in your browser:

Guestbook running on GKE

Try adding some guestbook entries by typing in a Message, and clicking Submit. You should see the Message you typed appear in the frontend. This indicates that data is successfully added to redis through the Services you created earlier.

Step 5: Scaling up the web frontend

Suppose your guestbook app 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 easily, since your servers are defined as a service that uses a Deployment controller.

Scale up the number of your frontend Pods to 5 by running:

kubectl scale deployment frontend --replicas=5

Output:

deployment.extensions/frontend scaled

The configuration for the Deployment is updated to specify that there should be 5 replicas running now. The Deployment adjusts the number of Pods it is running to match that. To verify, run the following command:

kubectl get pods
Output:
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 using the same command.

Cleaning up

To avoid incurring charges to your Google Cloud Platform account for the resources used in this tutorial:

Step 6: Cleanup

After completing this tutorial, follow these steps to remove the following resources to prevent unwanted charges incurring on your account:

  1. Delete the Service: This step will deallocate the Cloud Load Balancer created for the frontend Service:

    kubectl delete service frontend

  2. Wait for the Load Balancer provisioned for the frontend Service to be deleted: The load balancer is deleted asynchronously in the background when you run kubectl delete. Wait until the load balancer is deleted by watching the output of the following command:

    gcloud compute forwarding-rules list

  3. Delete the GKE cluster: This step will delete the resources that make up the GKE cluster, such as the compute instances, disks and network resources.

    gcloud container clusters delete guestbook

What's next