Overview

Cloud Run is a managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. Cloud Run is serverless: it abstracts away all infrastructure management, so you can focus on what matters most — building great applications.

Cloud Run is built from Knative, letting you choose to run your containers either fully managed with Cloud Run, or in your Google Kubernetes Engine cluster with Cloud Run on GKE.

The goal of this lab is for you to build a simple containerized application image and deploy it to Cloud Run.

Objectives

In this lab, you learn to:

• Enable the Cloud Run API.
• Create a simple Node.js application that can be deployed as a serverless, stateless container.
• Containerize your application and upload to Artifact Registry.
• Deploy a containerized application on Cloud Run.
• Delete unneeded images to avoid incurring extra storage charges.

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. Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is the Lab Details panel 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 panel.

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 panel.

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 view a menu with a list of Google Cloud products and services, click the Navigation menu at the top-left, or type the service or product name in the Search field.

Activate Google Cloud Shell

Google 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.

Google Cloud Shell provides command-line access to your Google Cloud resources.

1. In Cloud console, on the top right toolbar, click the Open Cloud Shell button.

   

2. Click Continue.

It takes a few moments to provision and connect to the environment. When you are connected, you are already authenticated, and the project is set to your PROJECT_ID. For example:

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

• You can list the active account name with this command:

Output:

Example output:

• You can list the project ID with this command:

Output:

Example output:

Reference

Basic Linux Commands

Below you will find a reference list of a few very basic Linux commands which may be included in the instructions or code blocks for this lab.

Task 1. Enable the Cloud Run API and configure your Shell environment

1. From Cloud Shell, enable the Cloud Run API :

2. If you are asked to authorize the use of your credentials, do so. You should then see a successful message similar to this one:

3. Set the compute region:

4. Create a LOCATION environment variable:

Task 2. Write the sample application

In this task, you will build a simple express-based NodeJS application which responds to HTTP requests.

1. In Cloud Shell create a new directory named helloworld, then move your view into that directory:

2. Next you'll be creating and editing files. To edit files, use nano or the Cloud Shell Code Editor by clicking on the Open Editor button in Cloud Shell.

3. Create a package.json file, then add the following content to it:

Most importantly, the file above contains a start script command and a dependency on the Express web application framework.

4. Press CTRL+X, then Y, then Enter to save the package.json file.

5. Next, in the same directory, create an index.js file, and copy the following lines into it:

This code creates a basic web server that listens on the port defined by the PORT environment variable. Your app is now finished and ready to be containerized and uploaded to Artifact Registry.

6. Press CTRL+X, then Y, then Enter to save the index.js file

Task 3. Containerize your app and upload it to Artifact Registry

1. To containerize the sample app, create a new file named Dockerfile in the same directory as the source files, and add the following content:

2. Press CTRL+X, then Y, then Enter to save the Dockerfile file.

3. Now, build your container image using Cloud Build by running the following command from the directory containing the Dockerfile. (Note the $GOOGLE_CLOUD_PROJECT environmental variable in the command, which contains your lab's Project ID):

Cloud Build is a service that executes your builds on Google Cloud. It executes a series of build steps, where each build step is run in a Docker container to produce your application container (or other artifacts) and push it to Artifact Registry, all in one command.

Once pushed to the registry, you will see a SUCCESS message containing the image name (gcr.io/[PROJECT-ID]/helloworld). The image is stored in Artifact Registry and can be re-used if desired.

4. List all the container images associated with your current project using this command:

5. Register gcloud as the credential helper for all Google-supported Docker registries:

6. To run and test the application locally from Cloud Shell, start it using this standard docker command:

7. In the Cloud Shell window, click on Web preview and select Preview on port 8080.

This should open a browser window showing the "Hello World!" message. You could also simply use curl localhost:8080.

Task 4. Deploy to Cloud Run

1. Deploying your containerized application to Cloud Run is done using the following command adding your Project-ID:

The allow-unauthenticated flag in the command above makes your service publicly accessible.

2. When prompted confirm the service name by pressing Enter.

Wait a few moments until the deployment is complete.

On success, the command line displays the service URL:

You can now visit your deployed container by opening the service URL in any browser window.

Congratulations! You have just deployed an application packaged in a container image to Cloud Run. Cloud Run automatically and horizontally scales your container image to handle the received requests, then scales down when demand decreases. In your own environment, you only pay for the CPU, memory, and networking consumed during request handling.

For this lab you used the gcloud command-line. Cloud Run is also available via Cloud console.

• From the Navigation menu, in the Serverless section, click Cloud Run and you should see your helloworld service listed:

Task 5. Clean up

While Cloud Run does not charge when the service is not in use, you might still be charged for storing the built container image.

1. You can either decide to delete your Google Cloud project to avoid incurring charges, which will stop billing for all the resources used within that project, or simply delete your helloworld image using this command :

2. When prompted to continue type Y, and press Enter.

3. To delete the Cloud Run service, use this command :

4. When prompted to continue type Y, and press Enter.

End your lab

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

You will be given an opportunity to rate the lab experience. Select the applicable number of stars, type a comment, and then click Submit.

The number of stars indicates the following:

• 1 star = Very dissatisfied
• 2 stars = Dissatisfied
• 3 stars = Neutral
• 4 stars = Satisfied
• 5 stars = Very satisfied

You can close the dialog box if you don't want to provide feedback.

For feedback, suggestions, or corrections, please use the Support tab.

Congratulations!

You have completed this lab!

Next steps / learn more

For more information on building a stateless HTTP container suitable for Cloud Run from code source and pushing it to Artifact Registry, view:

• Developing Cloud Run services
• Building Containers

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