Overview

In this lab, you deploy a simple Windows app to Docker running on a Compute Engine instance. You will then push the same app into Google Container Registry and deploy it to Google Kubernetes Engine.

Objectives

In this lab, you learn how to perform the following tasks:

• Create a simple Windows app.
• Containerize the app using Docker.
• Create your Kubernetes cluster on Kubernetes Engine.
• Deploy your app to a pod.
• Allow external traffic to your pod.

Setup and requirements

For each lab, you get a new Google Cloud project and set of resources for a fixed time at no cost.

1. Sign in to Google Skills using an incognito window.

2. Note the lab's access time (for example, 1:15:00), and make sure you can finish within that time. There is no pause feature. You can restart if needed, but you have to start at the beginning.

3. When ready, click Start lab.

4. Note your lab credentials (Username and Password). You will use them to sign in to the Google Cloud Console.

5. Click Open Google Console.

6. Click Use another account and copy/paste credentials for this lab into the prompts. If you use other credentials, you'll receive errors or incur charges.

7. Accept the terms and skip the recovery resource page.

Task 1. Enable Google Container Registry API

1. On the Google Cloud menu, click Activate Cloud Shell () icon then click Continue.

2. Make sure the Google Container Registry API is enabled, by running the following command:

Task 2. RDP into the Windows VM

1. On the Navigation menu (), click Compute Engine > VM instances.

2. Click the Drop down arrow icon next to RDP button and select Set Windows password.

3. Copy and save the Username value and click SET.

4. Copy and save the New Windows Password and click CLOSE.

5. Log into the Windows VM by clicking the RDP button of the VM:

6. Use credentials created in previous steps.

Once inside the Windows VM, you'll notice that it's a bare-minimum OS with minimal UI.

In the Windows command prompt (C:\Users\gcpstagingXXXXX_stud>), run the following to see the images that are installed by default:

Output:

Task 3. Create a Windows container app

For the app inside the Windows container, use an IIS Web Server. IIS has an image for Windows Server 2019. You can use the image as is and it will serve the default IIS page, but fot this lab, do something more interesting and have IIS serve a page you define.

1. Create a folder called my-windows-app and enter into the directory:

2. Create folder named content:

3. Create a file named index.html in the content folder:

4. Edit index.html:

5. Add the following content to index.html:

6. Save the index.html. This is the page IIS will serve.

Task 4. Build Docker image

1. Create a Dockerfile for the Docker image:

2. Edit the dockerfile:

3. Add the following contents in the Dockerfile:

4. Save the Dockerfile.

5. Build the Docker image and tag it with Google Container Registry (GCR) and your project id. This will be useful when we push the image to GCR later (replace [PROJECT_ID] with your Google Skills project id):

6. Once the Docker image is built, you can see it along with its IIS dependency:

Sample output:

7. Run the following command to run the Windows container from your VM instance:

8. Return to the Cloud Console. On the Navigation menu (), click Compute Engine > VM instances.

9. Open a browser window enter the External IP of the Compute Engine instance to see the app:

Click Check my progress below to verify you're on track in this lab.

Task 5. Push container image to Google Container Registry

1. Configure Docker to point to Google Container Registry (GCR):

2. When prompted enter Y.

The output should look like this:

3. Push the image to Google Container Repository. Remember to replace [PROJECT_ID] with your Google Skills project id:

4. If you return to the Cloud Console and go Google Container Repository in the Navigation Menu you can see the image.

Task 6. Start a Kubernetes Engine cluster

1. On the Google Cloud menu, click Activate Cloud Shell () icon then click Continue.

2. Run the following command to set your environment variables for the project and zones and to set them as default:

3. Start a Kubernetes cluster managed by Kubernetes Engine. Name the cluster win-cluster and configure it to run 2 nodes:

It takes several minutes to create a cluster as Kubernetes Engine provisions virtual machines for you. Eventually, the cluster should be created.

Example output:

4. After the cluster is created, check your installed version of Kubernetes using the kubectl version command:

The gcloud container clusters create command automatically authenticated kubectl for you.

5. View your running nodes in the Cloud Console. On the Navigation menu (), click Compute Engine > VM Instances.

   Your Kubernetes cluster is now ready for use.

Click Check my progress to verify the objective. Start a Kubernetes Engine cluster

Task 7. Add Windows Node to cluster

• Once we have the basic GKE cluster, we can go ahead and add a Windows pool for Windows nodes to it:

For Windows Server containers in GKE, you're already licensed for underlying Windows host VMs – containers need no additional licensing.

In the end, the GKE cluster is ready with 2 Linux nodes and 3 Windows nodes.

Task 8. Verify cluster initialization

Before running our Windows container as a pod on GKE, make sure the cluster is initialized.

1. In Cloud Shell run the following command:

kubectl is now setup to manage our cluster.

2. Before using the cluster, wait for several seconds until windows.config.common-webhooks.networking.gke.io is created. This webhook adds scheduling tolerations to Pods created with the kubernetes.io/os: windows (or beta.kubernetes.io/os: windows) node selector to ensure they are allowed to run on Windows Server nodes. It also validates the Pod to ensure that it only uses features supported on Windows.

Output:

Click Check my progress below to verify you're on track in this lab.

Task 9. Run Windows container as a pod in GKE

1. Create and open a file called iis-site-windows.yaml with nano using the following command:

2. Once nano has opened, paste following into the file (Remember to replace [PROJECT_ID] with your Google Skills project id):

3. Press Ctrl+O, and then press Enter to save your edited file.

4. Press Ctrl+X to exit the nano text editor.

5. Create a deployment for the cluster with the following command:

6. Check the deployment with the following command:

After a few minutes, you should see the deployment created and pods running:

Task 10. Create a Kubernetes service

1. To make pods accessible to the outside world, we need to create a Kubernetes service with LoadBalancer type:

In a few minutes, you should see a new service with an external IP:

You should see an output like this:

2. Open a browser window and go to the external IP of the load balancer, you will see the app:

Congratulations!

You have successfully configured and deployed a GKE cluster running a Windows Server workload.

In this lab, you learned how to perform the following tasks:

• Create a simple Windows app.
• Containerize the app using Docker.
• Create your Kubernetes cluster on Kubernetes Engine.
• Deploy your app to a pod.
• Allow external traffic to your pod.

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