Deploy an app to a GKE cluster

Deploy an app to a GKE cluster

Autopilot Standard

---

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

This page is for Operators and Developers who provision and configure cloud resources and deploy apps and services. To learn more about common roles and example tasks that we reference in Google Cloud content, see Common GKE Enterprise user roles and tasks.

Before reading this page, ensure that you're familiar with Kubernetes.

Before you begin

Take the following steps to enable the Kubernetes Engine API:

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. In the Google Cloud console, on the project selector page, select or create 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.

   Go to project selector

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

4. Enable the Artifact Registry and Google Kubernetes Engine APIs.

   Enable the APIs

5. In the Google Cloud console, on the project selector page, select or create 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.

   Go to project selector

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

7. Enable the Artifact Registry and Google Kubernetes Engine APIs.

   Enable the APIs

Required roles

Grant roles to your user account. Run the following command once for each of the following IAM roles: roles/container.admin

gcloud projects add-iam-policy-binding PROJECT_ID --member="user:USER_IDENTIFIER" --role=ROLE

• Replace PROJECT_ID with your project ID.

• Replace USER_IDENTIFIER with the identifier for your user account. For example, user:[e-mail].

• Replace ROLE with each individual role.

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 Google Cloud CLI and kubectl command-line tool. The gcloud CLI 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 the 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. Before you run commands, set your default project in the Google Cloud CLI using the following command:

gcloud config set project PROJECT_ID

Replace PROJECT_ID with your project ID.

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.

This section shows you how to create a cluster in Autopilot mode, which is the recommended cluster mode for most production use cases. You could alternatively use a GKE Standard mode cluster to do these steps.

Create an Autopilot cluster named hello-cluster:

gcloud container clusters create-auto hello-cluster \
    --location=us-central1

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 \
    --location us-central1

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=us-docker.pkg.dev/google-samples/containers/gke/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 an Artifact Registry repository, us-docker.pkg.dev/google-samples/containers/gke/hello-app. :1.0 indicates the specific image version to pull. If you don't specify a version, the image with the default latest tag is used.

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.

To track and organize your GKE resources in an application-centric way, you can add your resources as Services and workloads to App Hub applications.

For more information on resources that App Hub supports, see Supported resources.

To learn how to set up App Hub on your project, see Set up App Hub.

Clean up

To avoid incurring charges to your Google Cloud account for the resources used on this page, delete the Google Cloud project with the resources.

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 \
       --location us-central1
   

Optional: hello-app code review

hello-app is a 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 Artifact Registry. We host hello-app in a Artifact Registry repository at us-docker.pkg.dev/google-samples/containers/gke/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.

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.

FROM golang:1.23.2 as builder
WORKDIR /app
RUN go mod init hello-app
COPY *.go ./
RUN CGO_ENABLED=0 GOOS=linux go build -o /hello-app

FROM gcr.io/distroless/base-debian11
WORKDIR /
COPY --from=builder /hello-app /hello-app
ENV PORT 8080
USER nonroot:nonroot
CMD ["/hello-app"]

What's next

• Learn more about creating clusters.
• Learn more about Kubernetes.
• Learn how to package, host, and deploy a simple web server application.
• Deploy a Kubernetes application with Cloud Code for VS Code or Cloud Code for IntelliJ.
• Learn how to Replatform Linux applications to containers.

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