Checkpoints
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: Qwik Start
GSP100
Overview
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.
Objectives
In this lab, you learn how to perform the following tasks:
- Create a GKE cluster.
- Deploy an application to the cluster.
- Create a Kubernetes service.
- Delete the cluster.
Cluster orchestration with Google Kubernetes Engine
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.
Kubernetes on Google Cloud
When you run a GKE cluster, you also gain the benefit of advanced cluster management features that Google Cloud provides. These include:
- Load balancing for Compute Engine instances
- Node pools to designate subsets of nodes within a cluster for additional flexibility
- Automatic scaling of your cluster's node instance count
- Automatic upgrades for your cluster's node software
- Node auto-repair to maintain node health and availability
- Logging and monitoring with Cloud Monitoring for visibility into your cluster
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.
Setup and requirements
Before you click the Start Lab button
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 will be made available to you.
This hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that you use to sign in and access Google Cloud for the duration of the lab.
To complete this lab, you need:
- Access to a standard internet browser (Chrome browser recommended).
- Time to complete the lab---remember, once you start, you cannot pause a lab.
How to start your lab and sign in to the Google Cloud console
-
Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is the Lab Details panel with the following:
- The Open Google Cloud console button
- Time remaining
- The temporary credentials that you must use for this lab
- Other information, if needed, to step through this lab
-
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.
Note: If you see the Choose an account dialog, click Use Another Account. -
If necessary, copy the Username below and paste it into the Sign in dialog.
{{{user_0.username | "Username"}}} You can also find the Username in the Lab Details panel.
-
Click Next.
-
Copy the Password below and paste it into the Welcome dialog.
{{{user_0.password | "Password"}}} You can also find the Password in the Lab Details panel.
-
Click Next.
Important: You must use the credentials the lab provides you. Do not use your Google Cloud account credentials. Note: Using your own Google Cloud account for this lab may incur extra charges. -
Click through the subsequent pages:
- Accept the terms and conditions.
- Do not add recovery options or two-factor authentication (because this is a temporary account).
- Do not sign up for free trials.
After a few moments, the Google Cloud console opens in this tab.
Activate Cloud Shell
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.
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.
- (Optional) You can list the active account name with this command:
- Click Authorize.
Output:
- (Optional) You can list the project ID with this command:
Output:
gcloud
, in Google Cloud, refer to the gcloud CLI overview guide.
Task 1. Set a default compute zone
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:
gcloud config set compute/region {{{project_0.startup_script.project_region|"REGION"}}} Expected output:
Updated property [compute/region]. -
Set the default compute zone:
gcloud config set compute/zone {{{project_0.startup_script.project_zone|"ZONE"}}} Expected output:
Updated property [compute/zone].
Task 2. Create a GKE cluster
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:
gcloud container clusters create --machine-type=e2-medium --zone={{{project_0.startup_script.project_zone|ZONE}}} lab-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.
Task 3. Get authentication credentials for the cluster
After creating your cluster, you need authentication credentials to interact with it.
-
Authenticate with the cluster:
gcloud container clusters get-credentials lab-cluster Expected output:
Fetching cluster endpoint and auth data. kubeconfig entry generated for my-cluster.
Task 4. Deploy an application to the cluster
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 thehello-app
container image, run the followingkubectl create
command:kubectl create deployment hello-server --image=gcr.io/google-samples/hello-app:1.0 Expected output:
deployment.apps/hello-server created 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.
Create a new Deployment: hello-server -
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:kubectl expose deployment hello-server --type=LoadBalancer --port 8080 In this command:
-
--port
specifies the port that the container exposes. -
type="LoadBalancer"
creates a Compute Engine load balancer for your container.
Expected output:
service/hello-server exposed -
-
To inspect the
hello-server
Service, runkubectl get
:kubectl get service Expected output:
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE hello-server loadBalancer 10.39.244.36 35.202.234.26 8080:31991/TCP 65s kubernetes ClusterIP 10.39.240.1 433/TCP 5m13s Note: It might take a minute for an external IP address to be generated. Run the previous command again if the 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 theEXTERNAL-IP
forhello-server
.http://[EXTERNAL-IP]:8080 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.
Create a Kubernetes Service
Task 5. Delete the cluster
-
To delete the cluster, run the following command:
gcloud container clusters delete lab-cluster -
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.
Delete the cluster
Congratulations!
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.
Next steps / Learn more
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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