Quickstart

In this quickstart, you deploy a simple web server containerized application to a Google Kubernetes Engine (GKE) cluster. You will learn how to create a cluster, and how to deploy the application to the cluster so that it can be accessed by users.

This quickstart assumes a basic understanding of Kubernetes.

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.

Ensure you have the available quota for:

• 1 Compute Engine CPU in your cluster's region.
• 1 In-use IP address.

To check your available quota, use the Cloud Console.

Launch Cloud Shell

In this tutorial you will use Cloud Shell, which is a shell environment for managing resources hosted on Google Cloud.

Cloud Shell comes preinstalled with the gcloud command-line tool and kubectl command-line tool. The gcloud tool provides the primary command-line interface for Google Cloud, and kubectl provides the primary command-line interface for running commands against Kubernetes clusters.

Launch Cloud Shell:

1. Go to Google Cloud Console.

   Google Cloud Console

2. From the upper-right corner of the console, click the Activate Cloud Shell button:

A Cloud Shell session opens inside a frame lower on the console. You use this shell to run gcloud and kubectl commands.

Set default settings for the gcloud tool

Use the gcloud tool to configure the following default settings: your default project, compute zone, and compute region.

Your project has a project ID, which is its unique identifier. When you first create a project, you can use the automatically generated project ID or you can create your own.

Your compute zone is a location in the region where your clusters and their resources live. For example, us-west1-a is a zone in the us-west region. Your compute region is the region where your clusters and their resources live (for example, us-west).

Configuring these default settings makes it easier to run gcloud commands, because gcloud requires that you specify the project and location in which you want to work. You can also specify these settings or override default settings with flags, such as --project, --zone, --region, and --cluster, in your gcloud commands.

Note: The gcloud tool might return an error if these settings are either not configured or not specified.

When you create GKE resources after configuring your default project, zone, and region, the resources are automatically created in that project, zone, and region.

In Cloud Shell, perform the following steps:

1. Set the default project:

   gcloud config set project PROJECT_ID
   

   Replace PROJECT_ID with your project ID.

2. Set the default zone:

   gcloud config set compute/zone COMPUTE_ZONE
   

   Replace COMPUTE_ZONE with your compute zone, such as us-west1-a.

3. Set the default region:

   gcloud config set compute/region COMPUTE_REGION
   

   Replace COMPUTE_REGION with your compute region, such as us-west1.

Create a GKE cluster

A cluster consists of at least one cluster control plane machine and multiple worker machines called nodes. Nodes are Compute Engine virtual machine (VM) instances that run the Kubernetes processes necessary to make them part of the cluster. You deploy applications to clusters, and the applications run on the nodes.

To create clusters in GKE, you need to choose a mode of operation: Standard or Autopilot. If you use the Standard mode, your cluster is zonal (in this tutorial). If you use the Autopilot mode, your cluster is regional.

Standard

Create a one-node Standard cluster named hello-cluster:

gcloud container clusters create hello-cluster --num-nodes=1

Autopilot

Create an Autopilot cluster named hello-cluster:

 gcloud container clusters create-auto hello-cluster

It might take several minutes to finish creating the cluster.

Get authentication credentials for the cluster

After creating your cluster, you need to get authentication credentials to interact with the cluster:

gcloud container clusters get-credentials hello-cluster

This command configures kubectl to use the cluster you created.

Deploy an application to the cluster

Now that you have created a cluster, you can deploy a containerized application to it. For this quickstart, you can deploy our example web application, hello-app.

GKE uses Kubernetes objects to create and manage your cluster's resources. Kubernetes provides the Deployment object for deploying stateless applications like web servers. Service objects define rules and load balancing for accessing your application from the internet.

Create the Deployment

To run hello-app in your cluster, you need to deploy the application by running the following command:

kubectl create deployment hello-server --image=gcr.io/google-samples/hello-app:1.0

This Kubernetes command, kubectl create deployment, creates a Deployment named hello-server. The Deployment's Pod runs the hello-app container image.

In this command:

• --image specifies a container image to deploy. In this case, the command pulls the example image from a Container Registry bucket, gcr.io/google-samples/hello-app. :1.0 indicates the specific image version to pull. If you don't specify a version, the latest version is used.

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

Expose the Deployment

After deploying the application, you need to expose it to the internet so that users can access it. You can expose your application by creating a Service, a Kubernetes resource that exposes your application to external traffic.

To expose your application, run the following kubectl expose command:

kubectl expose deployment hello-server --type LoadBalancer --port 80 --target-port 8080

Passing in the --type LoadBalancer flag creates a Compute Engine load balancer for your container. The --port flag initializes public port 80 to the internet and the --target-port flag routes the traffic to port 8080 of the application.

Load balancers are billed per Compute Engine's load balancer pricing.

Inspect and view the application

1. Inspect the running Pods by using kubectl get pods:

   kubectl get pods
   

   You should see one hello-server Pod running on your cluster.

2. Inspect the hello-server Service by using kubectl get service:

   kubectl get service hello-server
   

   From this command's output, copy the Service's external IP address from the EXTERNAL-IP column.

   Note: You might need to wait several minutes before the Service's external IP address populates. If the application's external IP is <pending>, run kubectl get again.

3. View the application from your web browser by using the external IP address with the exposed port:

   http://EXTERNAL_IP
   

You have just deployed a containerized web application to GKE.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used in this quickstart, follow these steps.

1. Delete the application's Service by running kubectl delete:

   kubectl delete service hello-server
   

   This command deletes the Compute Engine load balancer that you created when you exposed the Deployment.

2. Delete your cluster by running gcloud container clusters delete:

   gcloud container clusters delete hello-cluster
   

   Note: If you did not set a default zone or region, pass your cluster's region (--region=COMPUTE_REGION) or zone (--zone=COMPUTE_ZONE) flags to the gcloud tool.

Optional: hello-app code review

hello-app is a simple web server application that consists of two files: main.go and a Dockerfile.

hello-app is packaged as a Docker container image. Container images are stored in any Docker image registry, such as Container Registry. We host hello-app in a Container Registry bucket named gcr.io/google-samples/hello-app.

main.go

main.go is a web server implementation written in the Go programming language. The server responds to any HTTP request with a "Hello, world!" message.

hello-app/main.go

View on GitHub

package main

import (
	"fmt"
	"log"
	"net/http"
	"os"
)

func main() {
	// register hello function to handle all requests
	mux := http.NewServeMux()
	mux.HandleFunc("/", hello)

	// use PORT environment variable, or default to 8080
	port := os.Getenv("PORT")
	if port == "" {
		port = "8080"
	}

	// start the web server on port and accept requests
	log.Printf("Server listening on port %s", port)
	log.Fatal(http.ListenAndServe(":"+port, mux))
}

// hello responds to the request with a plain-text "Hello, world" message.
func hello(w http.ResponseWriter, r *http.Request) {
	log.Printf("Serving request: %s", r.URL.Path)
	host, _ := os.Hostname()
	fmt.Fprintf(w, "Hello, world!\n")
	fmt.Fprintf(w, "Version: 1.0.0\n")
	fmt.Fprintf(w, "Hostname: %s\n", host)
}

Dockerfile

Dockerfile describes the image you want Docker to build, including all of its resources and dependencies, and specifies which network port the app should expose. For more information about how this file works, see Dockerfile reference in the Docker documentation.

hello-app/Dockerfile

View on GitHub

FROM golang:1.8-alpine
ADD . /go/src/hello-app
RUN go install hello-app

FROM alpine:latest
COPY --from=0 /go/bin/hello-app .
ENV PORT 8080
CMD ["./hello-app"]

What's next

• Learn more about creating clusters.
• Learn more about Kubernetes.
• Read the kubectl reference documentation.
• Learn how to package, host, and deploy a simple web server application.
• Deploy a Guestbook application with Redis and PHP.
• Deploy a stateful WordPress application with persistent storage and MySQL.
• Create and run a Kubernetes application with Cloud Code for VS Code or Cloud Code for IntelliJ.

Try it for yourself

If you're new to Google Cloud, create an account to evaluate how GKE performs in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

Try GKE free