![](https://cdn.qwiklabs.com/assets/labs/start_lab-f45aca49782d4033c3ff688160387ac98c66941d.png)
Before you begin
- Labs create a Google Cloud project and resources for a fixed time
- Labs have a time limit and no pause feature. If you restart it, you'll have to start from the beginning.
- On the top left of your screen, click Start lab to begin
Creating a Kubernetes Engine cluster
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Create a new Deployment - hello-server
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Create a Kubernetes Service
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Clean up: Delete the cluster
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Google Kubernetes Engine (GKE) provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. The GKE environment consists of multiple machines (specifically Compute Engine instances) grouped to form a container cluster.
This lab provides hands-on practice of container creation and application deployment with GKE.
In this lab, you learn how to perform the following tasks:
Google Kubernetes Engine (GKE) clusters are powered by the Kubernetes open source cluster management system. Kubernetes provides the mechanisms through which you interact with your container cluster. You use Kubernetes commands and resources to deploy and manage your applications, perform administrative tasks, set policies, and monitor the health of your deployed workloads.
Kubernetes draws on the same design principles that run popular Google services and provides the same benefits: automatic management, monitoring and liveness probes for application containers, automatic scaling, rolling updates, and more. When you run your applications on a container cluster, you're using technology based on Google's 10+ years of experience with running production workloads in containers.
When you run a GKE cluster, you also gain the benefit of advanced cluster management features that Google Cloud provides. These include:
Now that you have a basic understanding of Kubernetes, you will learn how to deploy a containerized application with GKE in less than 30 minutes. Follow the steps below to set up your lab environment.
Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources are made available to you.
This hands-on lab lets you do the lab activities in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials you use to sign in and access Google Cloud for the duration of the lab.
To complete this lab, you need:
Click the Start Lab button. If you need to pay for the lab, a dialog opens for you to select your payment method. On the left is the Lab Details pane with the following:
Click Open Google Cloud console (or right-click and select Open Link in Incognito Window if you are running the Chrome browser).
The lab spins up resources, and then opens another tab that shows the Sign in page.
Tip: Arrange the tabs in separate windows, side-by-side.
If necessary, copy the Username below and paste it into the Sign in dialog.
You can also find the Username in the Lab Details pane.
Click Next.
Copy the Password below and paste it into the Welcome dialog.
You can also find the Password in the Lab Details pane.
Click Next.
Click through the subsequent pages:
After a few moments, the Google Cloud console opens in this tab.
Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.
Click Activate Cloud Shell at the top of the Google Cloud console.
Click through the following windows:
When you are connected, you are already authenticated, and the project is set to your Project_ID,
gcloud
is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.
Output:
Output:
gcloud
, in Google Cloud, refer to the gcloud CLI overview guide.
Your compute zone is an approximate regional location in which your clusters and their resources live. For example, us-central1-a
is a zone in the us-central1
region.
In your Cloud Shell session, run the following commands.
Set the default compute region:
Expected output:
Set the default compute zone:
Expected output:
A cluster consists of at least one cluster master 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.
Run the following command:
Create a cluster:
You can ignore any warnings in the output. It might take several minutes to finish creating the cluster.
Expected output:
Click Check my progress to verify the objective.
After creating your cluster, you need authentication credentials to interact with it.
Authenticate with the cluster:
Expected output:
You can now deploy a containerized application to the cluster. For this lab, you'll run hello-app
in your cluster.
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.
To create a new Deployment hello-server
from the hello-app
container image, run the following kubectl create
command:
Expected output:
This Kubernetes command creates a deployment object that represents hello-server
. In this case, --image
specifies a container image to deploy. 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 a version is not specified, the latest version is used.
Click Check my progress to verify the objective.
To create a Kubernetes Service, which is a Kubernetes resource that lets you expose your application to external traffic, run the following kubectl expose
command:
In this command:
--port
specifies the port that the container exposes.type="LoadBalancer"
creates a Compute Engine load balancer for your container.Expected output:
To inspect the hello-server
Service, run kubectl get
:
Expected output:
EXTERNAL-IP
column status is pending.
To view the application from your web browser, open a new tab and enter the following address, replacing [EXTERNAL IP]
with the EXTERNAL-IP
for hello-server
.
Expected output: The browser tab displays the message Hello, world! as well as the version and hostname.
Click Check my progress to verify the objective.
To delete the cluster, run the following command:
When prompted, type Y
and press Enter to confirm.
Deleting the cluster can take a few minutes. For more information, refer to the Google Kubernetes Engine (GKE) article on Deleting a cluster.
Click Check my progress to verify the objective.
You have just deployed a containerized application to Google Kubernetes Engine! In this lab, you created a GKE cluster, deployed a containerized application to the cluster, created a Kubernetes service, and deleted the cluster. You can now apply this knowledge to deploy your own applications with GKE.
This lab is part of a series of labs called Qwik Starts. These labs are designed to give you some experience with the many features available with Google Cloud. Search for "Qwik Starts" in the Google Cloud Skill Boost catalog to find the next lab you'd like to take!
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Manual Last Updated December 11, 2024
Lab Last Tested December 11, 2024
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