GSP821

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.

What you'll learn to do

In this lab you will learn how to:

• Deploy an application to the GKE 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 15 minutes. Follow the steps below to set up your lab environment.

Setup and requirements

• Labs are timed and cannot be paused. The timer starts when you click Start Lab.
• The included cloud terminal is preconfigured with the gcloud SDK.
• Use the terminal to execute commands and then click Check my progress to verify your work.

Pre-configured resource:

• You have a pre-created GKE cluster for this lab named lab-cluster.

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 terminal, run the following commands.

1. Set the default compute region:

   gcloud config set compute/region {{{project_0.default_region|"REGION"}}}

   Expected output:

   Updated property [compute/region].

2. Set the default compute zone:

   gcloud config set compute/zone {{{project_0.default_zone|"ZONE"}}}

   Expected output:

   Updated property [compute/zone].

Task 2. Get authentication credentials for the GKE cluster

You need authentication credentials to interact with your cluster.

• Use the following gcloud command to retrieve the cluster credentials:

  gcloud container clusters get-credentials lab-cluster

  Expected output:

  Fetching cluster endpoint and auth data. kubeconfig entry generated for lab-cluster.

  This command is used to authenticate your kubectl client to a specific Google Kubernetes Engine (GKE) cluster so that you can interact with the cluster. This command fetches the cluster's credentials and updates your kubectl configuration with the necessary information.

Task 3. Deploy an application to the GKE cluster

You can now deploy a containerized application to the cluster. For this lab, you'll deploy hello-app on 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.

1. To create a new Deployment named hello-server from the hello-app container image, run the following kubectl 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

2. 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

3. To inspect the hello-server Service, run kubectl 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.

4. 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.

   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

Congratulations!

You have just deployed a containerized application to Google Kubernetes Engine! In this lab, you deployed a containerized application to the GKE cluster. You can now apply this knowledge to deploy your own applications with GKE.

Next steps / Learn more

Learn more about the Google Kubernetes Engine:

• Learn more about GKE Cluster
• About the node pools

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Manual Last Updated January 9, 2025

Lab Last Tested November 19, 2024

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