This tutorial shows you how to package a web application in a Docker container image, and run that container image on a Google Kubernetes Engine (GKE) cluster. Then, you deploy the web application as a load-balanced set of replicas that can scale to the needs of your 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.
Objectives
- Package a sample web application into a Docker image.
- Upload the Docker image to Artifact Registry.
- Create a GKE cluster.
- Deploy the sample app to the cluster.
- Manage autoscaling for the deployment.
- Expose the sample app to the internet.
- Deploy a new version of the sample app.
Costs
In this document, you use the following billable components of Google Cloud:
To generate a cost estimate based on your projected usage,
use the pricing calculator.
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
- 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.
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Make sure that billing is enabled for your Google Cloud project.
-
Enable the Compute Engine, Artifact Registry, and Google Kubernetes Engine APIs.
-
In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
-
Make sure that billing is enabled for your Google Cloud project.
-
Enable the Compute Engine, Artifact Registry, and Google Kubernetes Engine APIs.
Activate Cloud Shell
Cloud Shell comes preinstalled with the gcloud
, docker
, and
kubectl
command-line tools that are used in this tutorial.
- Go to the Google Cloud console.
Click the Activate Cloud Shell button at the top of the Google Cloud console window.
A Cloud Shell session opens inside a new frame at the bottom of the Google Cloud console and displays a command-line prompt.
Create a repository
In this tutorial, you store an image in Artifact Registry and deploy it
from the registry. For this quickstart, you'll create a repository named
hello-repo
.
Set the
PROJECT_ID
environment variable to your Google Cloud project ID (PROJECT_ID
). You'll use this environment variable when you build the container image and push it to your repository.export PROJECT_ID=PROJECT_ID
Confirm that the
PROJECT_ID
environment variable has the correct value:echo $PROJECT_ID
Set your project ID for the Google Cloud CLI:
gcloud config set project $PROJECT_ID
Output:
Updated property [core/project].
Create the
hello-repo
repository with the following command:gcloud artifacts repositories create hello-repo \ --repository-format=docker \ --location=REGION \ --description="Docker repository"
Replace
REGION
with the a region for the repository, such asus-west1
. To see a list of available locations, run the command:gcloud artifacts locations list
Building the container image
In this tutorial, you deploy a sample web
application called hello-app
, a web server written
in Go that responds to all requests with the message
Hello, World!
on port 8080.
GKE accepts Docker images as the application deployment format.
Before deploying hello-app
to GKE, you must package
the hello-app
source code as a Docker image.
To build a Docker image, you need source code and a Dockerfile. A Dockerfile contains instructions on how the image is built.
Download the
hello-app
source code and Dockerfile by running the following commands:git clone https://github.com/GoogleCloudPlatform/kubernetes-engine-samples cd kubernetes-engine-samples/quickstarts/hello-app
Build and tag the Docker image for
hello-app
:docker build -t REGION-docker.pkg.dev/${PROJECT_ID}/hello-repo/hello-app:v1 .
This command instructs Docker to build the image using the
Dockerfile
in the current directory, save it to your local environment, and tag it with a name, such asus-west1-docker.pkg.dev/my-project/hello-repo/hello-app:v1
. The image is pushed to Artifact Registry in the next section.- The
PROJECT_ID
variable associates the container image with thehello-repo
repository in your Google Cloud project. - The
us-west1-docker.pkg.dev
prefix refers to Artifact Registry, regional host for your repository.
- The
Run the
docker images
command to verify that the build was successful:docker images
Output:
REPOSITORY TAG IMAGE ID CREATED SIZE us-west1-docker.pkg.dev/my-project/hello-repo/hello-app v1 25cfadb1bf28 10 seconds ago 54 MB
Add IAM policy bindings to your service account:
gcloud artifacts repositories add-iam-policy-binding hello-repo \ --location=REGION \ --member=serviceAccount:PROJECT_NUMBER-compute@developer.gserviceaccount.com \ --role="roles/artifactregistry.reader"
Replace
PROJECT_NUMBER
with the project number of your project.
Running your container locally (optional)
Test your container image using your local Docker engine:
docker run --rm -p 8080:8080 REGION-docker.pkg.dev/${PROJECT_ID}/hello-repo/hello-app:v1
Click the Web Preview button and then select the
8080
port number. GKE opens the preview URL on its proxy service in a new browser window.
Pushing the Docker image to Artifact Registry
You must upload the container image to a registry so that your GKE cluster can download and run the container image. In this tutorial, you will store your container in Artifact Registry.
Configure the Docker command-line tool to authenticate to Artifact Registry:
gcloud auth configure-docker REGION-docker.pkg.dev
Push the Docker image that you just built to the repository:
docker push REGION-docker.pkg.dev/${PROJECT_ID}/hello-repo/hello-app:v1
Creating a GKE cluster
Now that the Docker image is stored in Artifact Registry, create a GKE
cluster
to run hello-app
. A GKE cluster consists of a pool of Compute Engine VM instances
running Kubernetes, the open source cluster orchestration
system that powers GKE.
Cloud Shell
Set your Compute Engine region:
gcloud config set compute/region REGION
For Standard zonal clusters, set a Compute Engine zone nearest to the Artifact Registry repository.
Create a cluster named
hello-cluster
:gcloud container clusters create-auto hello-cluster
It takes a few minutes for your GKE cluster to be created and health-checked. To run this tutorial on a GKE Standard cluster, use the
gcloud container clusters create
command instead.
Console
Go to the Google Kubernetes Engine page in the Google Cloud console.
Click add_box Create.
For GKE Autopilot, click Configure.
In the Name field, enter the name
hello-cluster
.Select a Compute Engine region from the Region drop-down list, such as
us-west1
.Click Create.
Wait for the cluster to be created. When the cluster is ready, a checkmark appears next to the cluster name.
Deploying the sample app to GKE
You are now ready to deploy the Docker image you built to your GKE cluster.
Kubernetes represents applications as Pods, which are scalable units holding one or more containers. The Pod is the smallest deployable unit in Kubernetes. Usually, you deploy Pods as a set of replicas that can be scaled and distributed together across your cluster. One way to deploy a set of replicas is through a Kubernetes Deployment.
In this section, you create a Kubernetes Deployment to run hello-app
on your
cluster. This Deployment has replicas (Pods). One Deployment Pod contains only
one container: the hello-app
Docker image.
You also create a HorizontalPodAutoscaler resource that scales the number
of Pods from 3 to a number between 1 and 5, based on CPU load.
Cloud Shell
Ensure that you are connected to your GKE cluster.
gcloud container clusters get-credentials hello-cluster --region REGION
Create a Kubernetes Deployment for your
hello-app
Docker image.kubectl create deployment hello-app --image=REGION-docker.pkg.dev/${PROJECT_ID}/hello-repo/hello-app:v1
Set the baseline number of Deployment replicas to 3.
kubectl scale deployment hello-app --replicas=3
Create a
HorizontalPodAutoscaler
resource for your Deployment.kubectl autoscale deployment hello-app --cpu-percent=80 --min=1 --max=5
To see the Pods created, run the following command:
kubectl get pods
Output:
NAME READY STATUS RESTARTS AGE hello-app-784d7569bc-hgmpx 1/1 Running 0 90s hello-app-784d7569bc-jfkz5 1/1 Running 0 90s hello-app-784d7569bc-mnrrl 1/1 Running 0 95s
Console
Go to the Workloads page in the Google Cloud console.
Click add_box Deploy.
In the Specify container section, select Existing container image.
In the Image path field, click Select.
In the Select container image pane, select the
hello-app
image you pushed to Artifact Registry and click Select.In the Container section, click Done, then click Continue.
In the Configuration section, under Labels, enter
app
for Key andhello-app
for Value.Under Configuration YAML, click View YAML. This opens a YAML configuration file representing the two Kubernetes API resources about to be deployed into your cluster: one Deployment, and one
HorizontalPodAutoscaler
for that Deployment.Click Close, then click Deploy.
When the Deployment Pods are ready, the Deployment details page opens.
Under Managed pods, note the three running Pods for the
hello-app
Deployment.
Exposing the sample app to the internet
While Pods do have individually-assigned IP addresses, those IPs can only be reached from inside your cluster. Also, GKE Pods are designed to be ephemeral, starting or stopping based on scaling needs. And when a Pod crashes due to an error, GKE automatically redeploys that Pod, assigning a new Pod IP address each time.
What this means is that for any Deployment, the set of IP addresses corresponding to the active set of Pods is dynamic. We need a way to 1) group Pods together into one static hostname, and 2) expose a group of Pods outside the cluster, to the internet.
Kubernetes Services solve for both of these problems.
Services group Pods
into one static IP address, reachable from any Pod inside the cluster.
GKE also assigns a DNS hostname
to that static IP. For example, hello-app.default.svc.cluster.local
.
The default Service type in GKE is called ClusterIP,
where the Service gets an IP address reachable only from inside the cluster.
To expose a Kubernetes Service outside the cluster, create a Service of
type LoadBalancer
.
This type of Service spawns an External Load Balancer IP for a set of Pods,
reachable through the internet.
In this section, you expose the hello-app
Deployment to the internet using a
Service of type LoadBalancer
.
Cloud Shell
Use the
kubectl expose
command to generate a Kubernetes Service for thehello-app
deployment:kubectl expose deployment hello-app --name=hello-app-service --type=LoadBalancer --port 80 --target-port 8080
Here, the
--port
flag specifies the port number configured on the Load Balancer, and the--target-port
flag specifies the port number that thehello-app
container is listening on.Run the following command to get the Service details for
hello-app-service
:kubectl get service
Output:
NAME CLUSTER-IP EXTERNAL-IP PORT(S) AGE hello-app-service 10.3.251.122 203.0.113.0 80:30877/TCP 10s
Copy the
EXTERNAL_IP
address to the clipboard (for instance:203.0.113.0
).
Console
Go to the Workloads page in the Google Cloud console.
Click hello-app.
From the Deployment details page, click list Actions > Expose.
In the Expose dialog, set the Target port to
8080
. This is the port thehello-app
container listens on.From the Service type drop-down list, select Load balancer.
Click Expose to create a Kubernetes Service for
hello-app
.When the Load Balancer is ready, the Service details page opens.
Scroll down to the External endpoints field, and copy the IP address.
Now that the hello-app
Pods are exposed to the internet through a Kubernetes Service,
you can open a new browser tab, and navigate to the Service IP address you copied
to the clipboard. A Hello, World!
message appears, along with a Hostname
field. The Hostname
corresponds to one of the three hello-app
Pods serving your
HTTP request to your browser.
Deploying a new version of the sample app
In this section, you upgrade hello-app
to a new version by building and deploying
a new Docker image to your GKE cluster.
Kubernetes
rolling update
lets you update your Deployments without downtime. During a rolling update, your GKE cluster
incrementally replaces the existing hello-app
Pods with Pods containing the Docker image for the new version.
During the update, your load balancer service routes traffic only into available Pods.
Return to Cloud Shell, where you have cloned the hello app source code and Dockerfile. Update the function
hello()
in themain.go
file to report the new version2.0.0
.Build and tag a new
hello-app
Docker image.docker build -t REGION-docker.pkg.dev/${PROJECT_ID}/hello-repo/hello-app:v2 .
Push the image to Artifact Registry.
docker push REGION-docker.pkg.dev/${PROJECT_ID}/hello-repo/hello-app:v2
Now you're ready to update your hello-app
Kubernetes Deployment to use a new Docker image.
Cloud Shell
Apply a rolling update to the existing
hello-app
Deployment with an image update using thekubectl set image
command:kubectl set image deployment/hello-app hello-app=REGION-docker.pkg.dev/${PROJECT_ID}/hello-repo/hello-app:v2
Watch the running Pods running the
v1
image stop, and new Pods running thev2
image start.watch kubectl get pods
Output:
NAME READY STATUS RESTARTS AGE hello-app-89dc45f48-5bzqp 1/1 Running 0 2m42s hello-app-89dc45f48-scm66 1/1 Running 0 2m40s
In a separate tab, navigate again to the
hello-app-service
External IP. You should now see theVersion
set to2.0.0.
Console
Go to the Workloads page in the Google Cloud console.
Click hello-app.
On the Deployment details page, click list Actions > Rolling update.
In the Rolling update dialog, set the Image of hello-app field to
REGION-docker.pkg.dev/PROJECT_ID/hello-repo/hello-app:v2
.Click Update.
On the Deployment details page, inspect the Active Revisions section. You should now see two Revisions, 1 and 2. Revision 1 corresponds to the initial Deployment you created earlier. Revision 2 is the rolling update you just started.
After a few moments, refresh the page. Under Managed pods, all of the replicas of
hello-app
now correspond to Revision 2.In a separate tab, navigate again to the Service IP address you copied. The
Version
should be2.0.0.
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 Service: This deallocates the Cloud Load Balancer created for your Service:
kubectl delete service hello-app-service
Delete the cluster: This deletes the resources that make up the cluster, such as the compute instances, disks, and network resources:
gcloud container clusters delete hello-cluster --region REGION
Delete your container images: This deletes the Docker images you pushed to Artifact Registry.
gcloud artifacts docker images delete \ REGION-docker.pkg.dev/${PROJECT_ID}/hello-repo/hello-app:v1 \ --delete-tags --quiet gcloud artifacts docker images delete \ REGION-docker.pkg.dev/${PROJECT_ID}/hello-repo/hello-app:v2 \ --delete-tags --quiet
What's next
Learn about Pricing for GKE and use the Pricing Calculator to estimate costs.
Read the Load Balancers tutorial, which demonstrates advanced load balancing configurations for web applications.
Configure a static IP and domain name for your application.
Explore other Kubernetes Engine tutorials.
Explore reference architectures, diagrams, and best practices about Google Cloud. Take a look at our Cloud Architecture Center.
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