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.
In this lab, you get hands-on practice with container creation and application deployment with GKE.
Objectives
In this lab you will learn how to:
Create a GKE cluster
Deploy an application to the cluster
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.
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 us-east4
Expected output:
Updated property [compute/region].
Set the default compute zone:
gcloud config set compute/zone us-east4-c
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.
Note: Cluster names must start with a letter and end with an alphanumeric, and cannot be longer than 40 characters.
Run the following command:
Create a cluster:
gcloud container clusters create --machine-type=e2-medium --zone=us-east4-c lab-cluster
You can ignore any warnings in the output. It might take several minutes to finish creating the cluster.
Expected output:
NAME: lab-cluster
LOCATION: us-east4-c
MASTER_VERSION: 1.22.8-gke.202
MASTER_IP: 34.67.240.12
MACHINE_TYPE: e2-medium
NODE_VERSION: 1.22.8-gke.202
NUM_NODES: 3
STATUS: RUNNING
Click Check my progress to verify the objective.
Create a GKE cluster
Check my progress
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
Check my progress
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
Check my progress
Task 5. Deleting the cluster
To delete the cluster, run the following command:
gcloud container clusters delete lab-cluster
When prompted, type Y to confirm.
Deleting the cluster can take a few minutes. For more information on deleted GKE clusters from the Google Kubernetes Engine (GKE) article, Deleting a cluster.
Click Check my progress to verify the objective.
Delete the cluster
Solution of Lab
export ZONE=
curl -LO raw.githubusercontent.com/quiccklabs/Labs_solutions/master/Google%20Kubernetes%20Engine%20Qwik%20Start/quicklabgsp100.sh
sudo chmod +x quicklabgsp100.sh
./quicklabgsp100.sh