Overview

In this lab, you create a deployment using Deployment Manager and use it to maintain a consistent state of your deployment. You will also view resource usage in a VM instance using Cloud Monitoring.

Objectives

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

• Create a Deployment Manager deployment.
• Update a Deployment Manager deployment.
• View the load on a VM instance using Cloud Monitoring.

Task 1. Sign in to the Google Cloud Platform (GCP) Console

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 2. Confirm that needed APIs are enabled

1. Make a note of the name of your GCP project. This value is shown in the top bar of the Google Cloud Platform Console. It will be of the form qwiklabs-gcp- followed by hexadecimal numbers.

2. In the GCP Console, on the Navigation menu (), click APIs & services.

3. Scroll down in the list of enabled APIs, and confirm that these APIs are enabled:

• Cloud Deployment Manager v2 API
• Cloud Runtime Configuration API
• Stackdriver monitoring API

4. If one or more APIs is missing, click the Enable APIs and Services button at top. Search for the above APIs by name and enable each for your current project. (You noted the name of your GCP project above.)

Task 3. Create a Deployment Manager deployment

1. In GCP console, on the top right toolbar, click the Activate Cloud Shell button (). Click Continue.

2. For your convenience, place the zone that Google Skills assigned you to into an environment variable called MY_ZONE. At the Cloud Shell prompt, type this partial command:

followed by the zone that Google Skills assigned you to. Your complete command will look similar to this:

3. At the Cloud Shell prompt, download an editable Deployment Manager template:

4. In the Cloud Shell, use the sed command to replace the PROJECT_ID placeholder string with your Google Cloud Platform project ID using this command:

5. In the Cloud Shell, use the sed command to replace the ZONE placeholder string with your Google Cloud Platform zone using this command:

6. In the Cloud Shell, use the sed command to replace the n1-standard-1 machine type to e2-medium using this command:

7. View the mydeploy.yaml file, with your modifications, with this command:

The file will look something like this:

8. Build a deployment from the template:

When the deployment operation is complete, the gcloud command displays a list of the resources named in the template and their current state.

9. Confirm that the deployment was successful. In the GCP Console, on the Navigation menu (), click Compute Engine > VM instances. You will see that a VM instance called my-vm has been created, as specified by the template.

10. Click on the VM instance's name to open its VM instance details screen.

11. Scroll down to the Custom metadata section. Confirm that the startup script you specified in your Deployment Manager template has been installed.

Click Check my progress to verify the objective. Create a Deployment Manager deployment

Task 4. Update a Deployment Manager deployment

1. Return to your Cloud Shell prompt. Launch the nano text editor to edit the mydeploy.yaml file:

2. Find the line that sets the value of the startup script, value: "apt-get update", and edit it so that it looks like this:

Do not disturb the spaces at the beginning of the line. The YAML templating language relies on indented lines as part of its syntax. As you edit the file, be sure that the v in the word value in this new line is immediately below the k in the word key on the line above it.

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

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

5. Return to your Cloud Shell prompt. Enter this command to cause Deployment Manager to update your deployment to install the new startup script:

Wait for the gcloud command to display a message confirming that the update operation was completed successfully.

6. In the GCP console, on the Navigation menu (), click Compute Engine > VM instances.

7. Click on the my-vm VM instance's name to open its VM instance details pane.

8. Scroll down to the Custom metadata section. Confirm that the startup script has been updated to the value you declared in your Deployment Manager template.

Click Check my progress to verify the objective. Update the Deployment Manager deployment

Task 5. View the Load on a VM using Cloud Monitoring

1. In the GCP Console, on the Navigation menu (), click Compute Engine > VM instances.

2. Select the checkbox for my-vm and click on STOP.

3. Click on STOP again to confirm.

4. Click on the VM instance's name to open its VM instance details screen.

5. Click on EDIT (pencil icon).

6. Scroll down to the bottom of the page and select Compute Engine default service account from Service account dropdown.

7. Select Allow full access to all Cloud APIs for Access scopes.

8. Click on Save.

9. Now, restart the VM by clicking on Start at the top of the VM instance details screen page.

10. Click on START again to confirm.

11. In the GCP Console, on the Navigation menu (), click Compute Engine > VM instances.

12. To open a command prompt on the my-vm instance, click SSH in its row in the VM instances list.

13. In the ssh session on my-vm, execute this command to create a CPU load:

This Linux pipeline forces the CPU to work on compressing a continuous stream of random data.

Create a Monitoring workspace

You will now setup a Monitoring workspace that's tied to your Google Cloud Project. The following steps create a new account that has a free trial of Monitoring.

1. In the Cloud Console, click on Navigation menu > Monitoring.

2. Wait for your workspace to be provisioned.

When the Monitoring dashboard opens, your workspace is ready.

3. Click on Settings option from the left panel and confirm that the GCP project created for you is shown under the GCP Projects section.

4. Run the commands shown on screen in the SSH window of your VM instance to install both the Monitoring and Logging agents.

5. Once both of the agents have been installed on your project's VM, click Metrics Explorer under the main Cloud Monitoring menu on the far left.

6. In the Metrics Explorer pane, Click on Select a Metric dropdown under Resource & Metric and then select VM instance > Instance > CPU usage.

7. Click Apply.

In the resulting graph, notice that CPU usage increased sharply a few minutes ago.

8. Terminate your workload generator. Return to your ssh session on my-vm and enter this command:

End your lab

When you have completed your lab, click End Lab. Google Skills removes the resources you’ve used and cleans the account for you.

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