Running the PHP Bookshelf on Kubernetes Engine

This tutorial shows how to run the PHP Bookshelf Application on Kubernetes Engine. Follow this tutorial to containerize and deploy an existing PHP web application to Kubernetes Engine. You don't have to be familiar with the Bookshelf application to follow this tutorial, but if you would like to learn more, you can follow the tutorial for App Engine Flexible.

This tutorial assumes that you are familiar with PHP and that you have PHP 5.6, 7.0, or 7.1 installed. You also need to download Composer. This tutorial assumes the Composer executable is installed globally.

Objectives

  • Create a Kubernetes Engine cluster.
  • Containerize a PHP application.
  • Create a replicated front end for the Bookshelf application.
  • Create a replicated back end for the Bookshelf application.
  • Create a load-balanced service to route HTTP traffic to the Bookshelf front end.

Costs

This tutorial uses billable components of Cloud Platform, including:

  • Kubernetes Engine
  • Compute Engine
  • Cloud Storage
  • Cloud Datastore
  • Cloud Pub/Sub

Use the Pricing Calculator to generate a cost estimate based on your projected usage. New Cloud Platform users might be eligible for a free trial.

Before you begin

  1. Sign in to your Google Account.

    If you don't already have one, sign up for a new account.

  2. Select or create a GCP project.

    Go to the Manage resources page

  3. Make sure that billing is enabled for your project.

    Learn how to enable billing

  4. Enable the Cloud Datastore, Cloud Storage, and Cloud Pub/Sub APIs.

    Enable the APIs

  5. Install and initialize the Cloud SDK.
  6. Install Docker. Docker is used to build container images locally.
  7. Install kubectl:
    gcloud components install kubectl

Creating a Kubernetes Engine cluster

A Kubernetes Engine cluster is a managed set of Compute Engine virtual machines that operate as a single Kubernetes cluster. This tutorial needs a cluster with a minimum of two nodes, and these nodes will need access to all Google APIs. Replace [YOUR_GCP_ZONE] with the Cloud Platform zone where you want your cluster to be hosted.

  1. Create the cluster:

    gcloud container clusters create bookshelf \
        --scopes "cloud-platform" \
        --num-nodes 2 \
        --zone [YOUR_GCP_ZONE]
    
  2. Verify that you have access to the cluster:

    kubectl get nodes
    

    Running this command lists the nodes in your container cluster and indicates that your container cluster is up and running and you have access to it.

You'll use the kubectl command to create resources in a Kubernetes Engine Cluster. To learn more about kubectl, see Kubernetes Engine Cluster Operations. In general, you'll use gcloud to manage resources in your Google Cloud project and you'll use kubectl to manage resources within your Kubernetes Engine cluster. A single project can have multiple clusters, which makes it easy to have clusters that are made up of different machine types to satisfy different needs.

When you create a cluster with gcloud, it will automatically set up authentication for kubectl. Clusters created by using the Cloud Console can set up authentication using the gcloud container clusters get-credentials command.

Cloning the sample application

The sample application is available on GitHub at GoogleCloudPlatform/getting-started-php.

  1. Clone the repository:

    git clone https://github.com/GoogleCloudPlatform/getting-started-php.git
    
  2. Navigate to the sample directory:

    cd getting-started-php/optional-kubernetes-engine
    

Initializing Datastore

The Bookshelf application uses Cloud Datastore to store the books. To initialize Datastore in your project for the first time:

  1. Open the Datastore on GCP Console.

  2. Select a region for your datastore and click Continue. When you reach the “Create an Entity” page, you can close the window as the Bookshelf application is ready to create entities on Datastore.

Creating a Cloud Storage bucket

The Bookshelf application uses Google Cloud Storage to store image files.

The following instructions show how to create a Cloud Storage bucket. Buckets are the basic containers that hold your data in Cloud Storage.

Name your bucket the same as your project ID.

To create a bucket:

  1. Invoke the following command:

    gsutil mb gs://[YOUR-PROJECT-ID]

    Replace [YOUR-PROJECT-ID] with your project ID.

  2. Set the bucket's default ACL to public-read to enable users to see their uploaded images:

    gsutil defacl set public-read gs://[YOUR-PROJECT-ID]

    Replace [YOUR-PROJECT-ID] with your project ID.

Configuring the application

  1. Go to the getting-started-php/optional-kubernetes-engine directory, and copy the settings.yml.dist file:

    cp config/settings.yml.dist config/settings.yml
    
  2. Open config/settings.yml for editing.

  3. Replace YOUR_PROJECT_ID with your project ID.

  4. Set the value of bookshelf_backend to datastore.

  5. Save and close settings.yml.

Cloud Datastore is a fully managed service that is automatically initialized and connected to your App Engine app. No further configuration is required.

Containerizing the application

The sample application includes a Dockerfile, which is used create the application's Docker image. This Docker image is used to run the application on Kubernetes Engine.

# The Google App Engine php runtime is Debian Jessie with PHP installed
# and various os-level packages to allow installation of popular PHP
# libraries. The source is on github at:
#   https://github.com/GoogleCloudPlatform/php-docker
FROM gcr.io/google_appengine/php

# Add our NGINX and php.ini config
ENV DOCUMENT_ROOT=${APP_DIR}/web

# Workaround for AUFS-related permission issue:
# See https://github.com/docker/docker/issues/783#issuecomment-56013588
RUN cp -R ${APP_DIR} ${APP_DIR}-copy; rm -r ${APP_DIR}; mv ${APP_DIR}-copy ${APP_DIR}; chmod -R 550 ${APP_DIR}; chown -R root.www-data ${APP_DIR}
The sample application also includes a .dockerignore file that lists filepaths that will not be included in the resulting Docker container. Typically, this includes build artifacts and local dependency installations.

test/*
coverage/*

Build the application's Docker image:

docker build -t gcr.io/[YOUR_PROJECT_ID]/bookshelf .

Push the image to Google Container Registry so that your cluster can access the image:

gcloud docker -- push gcr.io/[YOUR_PROJECT_ID]/bookshelf

Containerizing the worker

The sample application includes a Dockerfile, which is used create the worker's Docker image. This Docker image is used to run the worker on Kubernetes Engine.

# The Google App Engine php runtime is Debian Jessie with PHP installed
# and various os-level packages to allow installation of popular PHP
# libraries. The source is on github at:
#   https://github.com/GoogleCloudPlatform/php-docker
FROM gcr.io/google_appengine/php

# override the default CMD for the pubsub worker
CMD php bin/pubsub/entrypoint.php

Build the application's Docker image:

docker build -t gcr.io/[YOUR_PROJECT_ID]/bookshelf-worker --file Dockerfile.worker .

Push the image to Google Container Registry so that your cluster can access the image:

gcloud docker -- push gcr.io/[YOUR_PROJECT_ID]/bookshelf-worker

Deploying the Bookshelf front end

The Bookshelf application has a front end server that handles the web requests and a backend worker that processes books and adds additional information.

The cluster resources needed to run the front end are defined in bookshelf-frontend.yaml. These resources are described as a Kubernetes Deployment. Deployments make it easy to create and update a replica set and its associated pods.

# This file configures the bookshelf application frontend. The frontend serves
# public web traffic.

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: bookshelf-frontend
  labels:
    app: bookshelf
# The bookshelf frontend replica set ensures that at least 3
# instances of the bookshelf app are running on the cluster.
# For more info about Pods see:
#   https://cloud.google.com/container-engine/docs/pods/
spec:
  replicas: 3
  template:
    metadata:
      labels:
        app: bookshelf
        tier: frontend
    spec:
      containers:
      - name: bookshelf-app
        # Replace $GCLOUD_PROJECT with your project ID or use `make template`.
        image: gcr.io/$GCLOUD_PROJECT/bookshelf
        # This setting makes nodes pull the docker image every time before
        # starting the pod. This is useful when debugging, but should be turned
        # off in production.
        imagePullPolicy: Always
        # The bookshelf process listens on port 8080 for web traffic by default.
        ports:
        - name: http-server
          containerPort: 8080
  1. In bookshelf-frontend.yaml, replace [YOUR_PROJECT_ID] with your project ID.
  2. Use kubectl to deploy the resources to the cluster:

    kubectl create -f bookshelf-frontend.yaml
    
  3. Track the status of the deployment:

    kubectl get deployments
    

    Once the deployment has the same number of available pods as desired pods, the deployment is complete. If you run into issues with the deployment, you can delete it and start over:

    kubectl delete deployments bookshelf-frontend
    
  4. Once the deployment is complete you can see the pods that the deployment created:

    kubectl get pods
    

Deploying the Bookshelf back end

The Bookshelf back end is deployed the same way as the front end.

# Copyright 2015 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License

# This file configures the bookshelf task worker. The worker is responsible
# for processing book requests and updating book information.

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: bookshelf-worker
  labels:
    app: bookshelf
# The bookshelf worker replica set ensures that at least 2 instances of the
# bookshelf worker pod are running on the cluster.
# For more info about Pods see:
#   https://cloud.google.com/container-engine/docs/pods/
spec:
  replicas: 2
  template:
    metadata:
      labels:
        app: bookshelf
        tier: worker
    spec:
      containers:
      - name: bookshelf-app
        # Replace $GCLOUD_PROJECT with your project ID or use `make template`.
        image: gcr.io/$GCLOUD_PROJECT/bookshelf-worker
        # This setting makes nodes pull the docker image every time before
        # starting the pod. This is useful when debugging, but should be turned
        # off in production.
        imagePullPolicy: Always
        # The bookshelf process listens on port 8080 for web traffic by default.
        ports:
        - name: ratchet-server
          containerPort: 8080
  1. In bookshelf-worker.yaml, replace [YOUR_PROJECT_ID] with your project ID.
  2. Use kubectl to deploy the resources to the cluster:

    kubectl create -f bookshelf-worker.yaml
    
  3. Verify that the pods are running:

    kubectl get pods
    

Creating the Bookshelf service

Kubernetes Services are used to provide a single point of access to a set of pods. While it's possible to access a single pod, pods are ephemeral and it's usually more convenient to address a set of pods with a single endpoint. In the Bookshelf application, The Bookshelf service allows you to access the Bookshelf frontend pods from a single IP address. This service is defined in bookshelf-service.yaml

# The bookshelf service provides a load-balancing proxy over the bookshelf
# frontend pods. By specifying the type as a 'LoadBalancer', Container Engine
# will create an external HTTP load balancer.
# For more information about Services see:
#   https://cloud.google.com/container-engine/docs/services/
# For more information about external HTTP load balancing see:
#   https://cloud.google.com/container-engine/docs/load-balancer
apiVersion: v1
kind: Service
metadata:
  name: bookshelf-frontend
  labels:
    app: bookshelf
    tier: frontend
spec:
  type: LoadBalancer
  ports:
  - port: 80
    targetPort: http-server
  selector:
    app: bookshelf
    tier: frontend

Notice that the pods and the service that uses the pods are separate. Kubernetes uses labels to select the pods that a service addresses. With labels, you can have a service that addresses pods from different replica sets and have multiple services that point to an individual pod.

  1. Create the Bookshelf service:

    kubectl create -f bookshelf-service.yaml
    
  2. Get the service's external IP address:

    kubectl describe service bookshelf
    

    Note that it may take up to 60 seconds for the IP address to be allocated. The external IP address will be listed under LoadBalancer Ingress.

Accessing the Bookshelf application

You have now deployed all the resources needed to run the Bookshelf application on Kubernetes Engine. Use the external IP address from the previous step to load the application in your web browser and create books. If you deployed the worker, the books will be automatically updated with information from the Google Books API.

Cleaning up

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

Deleting the project

The easiest way to eliminate billing is to delete the project you created for the tutorial.

To delete the project:

  1. In the GCP Console, go to the Projects page.

    Go to the Projects page

  2. In the project list, select the project you want to delete and click Delete project. After selecting the checkbox next to the project name, click
      Delete project
  3. In the dialog, type the project ID, and then click Shut down to delete the project.

Deleting the cluster

Deleting the cluster removes all Kubernetes Engine and Compute Engine resources, but you need to manually remove any resources in Cloud Storage, Cloud Datastore, and Cloud Pub/Sub.

Delete the cluster using the following command. Replace [YOUR_GCP_ZONE] with the zone you used when creating the cluster.

gcloud container clusters delete bookshelf --zone [YOUR_GCP_ZONE]

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