GSP092

Overview

In this lab you use Cloud Monitoring to view Cloud Run functions details in the Google Cloud console. The Cloud Run function details include execution times and counts, and memory usage.

Objectives

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

• Create a Cloud Run function.
• Create logs-based metric for a Cloud Run function.
• Use Metrics Explorer to view data for your Cloud Run function.
• Create charts on the Monitoring Overview window.

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 are made available to you.

This hands-on lab lets you do the lab activities in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials 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

1. Click the Start Lab button. If you need to pay for the lab, a dialog opens for you to select your payment method. On the left is the Lab Details pane 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

2. 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.

3. 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 pane.

4. Click Next.

5. 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 pane.

6. 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.

7. 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.

Note: To access Google Cloud products and services, click the Navigation menu or type the service or product name in the Search field.

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.

1. Click Activate Cloud Shell at the top of the Google Cloud console.

2. Click through the following windows:

   • Continue through the Cloud Shell information window.
   • Authorize Cloud Shell to use your credentials to make Google Cloud API calls.

When you are connected, you are already authenticated, and the project is set to your Project_ID, . The output contains a line that declares the Project_ID for this session:

gcloud is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.

3. (Optional) You can list the active account name with this command:

4. Click Authorize.

Output:

5. (Optional) You can list the project ID with this command:

Output:

Task 1. Viewing Cloud Run function logs & metrics in Cloud Monitoring

Before you collect logs and alerts, you need something to monitor. In this section, you create a Hello World Cloud Run function to monitor.

1. In the Cloud console, select Navigation menu () > Cloud Run, and then click Write a Function.

2. Set the following:

   • Service Name: helloworld
   • Region:
   • Runtime: Node.js 22
   • Authentication: select radio button next to Allow unauthenticated invocations

3. Expand Container(s), Volumes, Networking, Security and set the following:

   • Execution environment: select second generation.

   • Revision scaling, set the Maximum number of instances to 5.

4. Leave the rest of the fields as default. Click Create.

5. Click Save and Redeploy.

The function automatically deploys and is listed on the Cloud Run function page. This takes a few minutes. When you see a green check mark next to the name, the Cloud Run function is complete.

Test completed task

Click Check my progress to verify your performed task. If you have completed the task successfully you will be granted an assessment score.

6. Open a new Cloud Shell window by clicking the Activate Cloud Shell at the top of the Google Cloud console.

7. In Cloud Shell, run the following to get a tool called vegeta that will let you send some test traffic to your Cloud Run function:

8. Unpack the vegeta tool by running the following:

9. On the Cloud Run page, click your function name, then click the helloworld URL for your function.

If you see Hello World! in the new browser tab that opens, you're up and running!

10. Set and verify the Cloud Run URL link:

11. Now send traffic to your Cloud Run function:

12. Keep this running in the background while you complete the next sections.

Task 2. Create a logs-based metric

Now you'll create a Distribution type logs based metric to extract the value of latency from the log entries httpRequest.latency field.

1. In the console, select Navigation menu > View All Products > Observability > Logging > Logs Explorer. The Cloud Logging opens in the console.

2. To look at just the logs from your Cloud Run function, in the All resources dropdown, select Cloud Run Revision > helloWorld then click Apply.

3. Click Run query.

4. In Actions dropdown click Create metric.

5. In the Create log-based metric form:

• Change the Metric Type to Distribution.
• In Log-based metric name enter CloudRunFunctionLatency-Logs.
• Enter httpRequest.latency for Field name.

The log-based metric should look like this:

6. Click Create metric.

Now you'll see your user-defined metric added to your Logs-based Metrics page.

Test completed task

Click Check my progress to verify your performed task. If you have completed the task successfully you will be granted an assessment score.

Task 3. Metrics Explorer

Next, you'll use Metrics Explorer to look at the data for your Cloud Run function.

Create a Monitoring Metrics Scope

Set up a Monitoring Metrics Scope that's tied to your Google Cloud Project. The following steps create a new account that has a free trial of Monitoring.

• In the Cloud Console, click Navigation menu () > View All Products > Observability > Monitoring.

When the Monitoring Overview page opens, your metrics scope project is ready.

1. In the left menu, click Metrics explorer.

2. Click on Select a metric dropdown. Deselect the Active button.

3. Type CloudRunFunctionLatency-Logs in filter by resource or metric name and then select Cloud Run Revision > Logs-based metric > Logging/user/CloudRunFunctionLatency-Logs from the suggested metrics and click Apply.

If you encounter issues:

• Double-check that you have selected the correct resource and metric in Cloud Monitoring.
• Ensure that there are no filters applied in Cloud Monitoring.
• Verify that the time range is set correctly in Cloud Monitoring.
• Generate more traffic with the vegeta tool (increase the duration or rate).
• Wait for a longer period, as there may be delays in log processing.

4. On the top right corner change the widget type to Stacked bar chart using the dropdown menu.

5. Explore other graph options and try a different metric. For example, click your current Cloud Run Revision metric to open the dropdown, select Cloud Run Revision > Request Count, and change the widget type to Stacked area chart.

6. Continue to explore and experiment. For example, go back to the Cloud Run Revision metric and change the Aggregation to the 95th percentile. Select the widget type Line chart.

Task 4. Create charts on the Monitoring Overview window

Creating charts on the Monitoring Overview window is a great way to track metrics that are important to you. In this section, you set up the same charts you created in the previous section, but now they'll be saved into the Monitoring Overview window.

1. In the left menu, click Dashboards.

2. Click Create Custom Dashboard.

3. Click on Add widget.

4. Under Visualization, select Stacked bar.

5. Under Select a metric dropdown select the default Cloud Run Revision > Request Count metric to open the dropdown and change the metric. Click Apply on the top right.

6. Click Add widget. Under Visualization, select Heatmap.

7. Start typing Cloud Run Revision into the Select a metric dropdown, and then select Cloud Run Revision > Logs-based metric > Logging/user/CloudRunFunctionLatency-Logs from the suggested metrics and click Apply.

8. Click Add widget. Under Visualization, select Line.

9. Start typing Cloud Run Revision into the Select a metric dropdown, and then select Cloud Run Revision > Request_latency from the suggested metrics. Set the Aggregation to Mean and click Apply.

10. Click Add widget. Under Visualization, select Stacked bar.

11. Start typing Cloud Run Revision into the Select a metric dropdown, and then select Cloud Run Revision > Container > Container CPU Allocation from the suggested metrics. Click Apply.

By default, the charts name themselves after the metric you're using, but you can rename them.

12. Click the Dashboard name at the top it should start with New Dashboard - and rename it to Cloud Run Function Custom Dashboard.

For a quick reference, to see these charts click Dashboards in the left panel of the Monitoring page.

Task 5. Test your understanding

Below are multiple-choice questions to reinforce your understanding of this lab's concepts. Answer them to the best of your abilities.

Congratulations!

Congratulations! In this lab, you created a Cloud Run function, created a logs-based metric, used Metrics Explorer, and created charts on the Monitoring Overview window.

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Manual Last Updated March 5, 2025

Lab Last Tested March 5, 2025

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