Hello Cloud Run with Python

1. Introduction

Cloud Run is a managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It is built on the Knative open-source project, enabling portability of your workloads across platforms. Cloud Run is serverless: it abstracts away all infrastructure management, so you can focus on what matters most — building great applications.

The goal of this tutorial is to create a simple web application and deploy it to Cloud Run.

2. Setup and requirements

Self-paced environment setup

1. Sign-in to the Google Cloud Console and create a new project or reuse an existing one. If you don't already have a Gmail or Google Workspace account, you must create one.

• The Project name is the display name for this project's participants. It is a character string not used by Google APIs. You can always update it.
• The Project ID is unique across all Google Cloud projects and is immutable (cannot be changed after it has been set). The Cloud Console auto-generates a unique string; usually you don't care what it is. In most codelabs, you'll need to reference your Project ID (typically identified as PROJECT_ID). If you don't like the generated ID, you might generate another random one. Alternatively, you can try your own, and see if it's available. It can't be changed after this step and remains for the duration of the project.
• For your information, there is a third value, a Project Number, which some APIs use. Learn more about all three of these values in the documentation.

Caution: A project ID is globally unique and can't be used by anyone else after you've selected it. You are the only user of that ID. Even if a project is deleted, the ID can't be used again

Note: If you use a Gmail account, you can leave the default location set to No organization. If you use a Google Workspace account, choose a location that makes sense for your organization.

2. Next, you'll need to enable billing in the Cloud Console to use Cloud resources/APIs. Running through this codelab won't cost much, if anything at all. To shut down resources to avoid incurring billing beyond this tutorial, you can delete the resources you created or delete the project. New Google Cloud users are eligible for the $300 USD Free Trial program.

Start Cloud Shell

While Google Cloud can be operated remotely from your laptop, in this tutorial you will be using Cloud Shell, a command line environment running in the Cloud.

Activate Cloud Shell

1. From the Cloud Console, click Activate Cloud Shell .

If this is your first time starting Cloud Shell, you're presented with an intermediate screen describing what it is. If you were presented with an intermediate screen, click Continue.

It should only take a few moments to provision and connect to Cloud Shell.

This virtual machine is loaded with all the development tools needed. It offers a persistent 5 GB home directory and runs in Google Cloud, greatly enhancing network performance and authentication. Much, if not all, of your work in this codelab can be done with a browser.

Once connected to Cloud Shell, you should see that you are authenticated and that the project is set to your project ID.

2. Run the following command in Cloud Shell to confirm that you are authenticated:

gcloud auth list

Command output

 Credentialed Accounts
ACTIVE  ACCOUNT
*       <my_account>@<my_domain.com>

To set the active account, run:
    $ gcloud config set account `ACCOUNT`

Note: The gcloud command-line tool is the powerful and unified command-line tool in Google Cloud. It comes preinstalled in Cloud Shell. You will notice its support for tab completion. You may be prompted to authenticate the first time you run a command. For more information, see gcloud command-line tool overview.

3. Run the following command in Cloud Shell to confirm that the gcloud command knows about your project:

gcloud config list project

Command output

[core]
project = <PROJECT_ID>

If it is not, you can set it with this command:

gcloud config set project <PROJECT_ID>

Command output

Updated property [core/project].

Note: If you're completing this tutorial outside of Cloud Shell, follow Set up Application Default Credentials.

3. Enable the APIs

From Cloud Shell, enable the Artifact Registry, Cloud Build, and Cloud Run APIs:

gcloud services enable \
  artifactregistry.googleapis.com \
  cloudbuild.googleapis.com \
  run.googleapis.com

This outputs a success message similar to this one:

Operation "operations/..." finished successfully.

Under the hood, to deploy your application, Cloud Run pairs with the container ecosystem:

• Cloud Build automatically builds a container image from your source code and pushes it to Artifact Registry.
• Artifact Registry manages your container image.

Now, you're ready to start working and write your application...

4. Write the application

In this step, you'll build a simple Flask-based Python application responding to HTTP requests.

Working directory

Use Cloud Shell to create a working directory named helloworld-python and switch to it:

mkdir ~/helloworld-python
cd ~/helloworld-python

main.py

Create a file named main.py:

touch main.py

Edit the file with your preferred command line editor (nano, vim, or emacs) or by clicking the Cloud Shell Editor button:

To directly edit the file with Cloud Shell Editor, use this command:

cloudshell edit main.py

main.py

from flask import Flask, request

app = Flask(__name__)


@app.get("/")
def hello():
    """Return a friendly HTTP greeting."""
    who = request.args.get("who", default="World")
    return f"Hello {who}!\n"


if __name__ == "__main__":
    # Development only: run "python main.py" and open http://localhost:8080
    # When deploying to Cloud Run, a production-grade WSGI HTTP server,
    # such as Gunicorn, will serve the app.
    app.run(host="localhost", port=8080, debug=True)

This code creates a basic web service responding to HTTP GET requests with a friendly message.

requirements.txt

Add a file named requirements.txt to define the dependencies:

touch requirements.txt

To directly edit the file with Cloud Shell Editor, use this command:

cloudshell edit requirements.txt

requirements.txt

# https://pypi.org/project/flask
Flask==3.0.2

# https://pypi.org/project/gunicorn
gunicorn==21.2.0

Procfile

Finally, add a file named Procfile to specify how the application will be served:

touch Procfile

To directly edit the file with Cloud Shell Editor, use this command:

cloudshell edit Procfile

Procfile

web: gunicorn --bind :$PORT --workers 1 --threads 8 --timeout 0 main:app

Make sure all files are present under the working directory:

ls

This should list the following files:

main.py  Procfile  requirements.txt

Many other languages are documented to start with Cloud Run. You can find instructions for Go, Node.js, Java, C#, C++, PHP, Ruby, Shell scripts, and others here: https://cloud.google.com/run/docs/quickstarts/build-and-deploy

Your application is ready to be deployed, but let's test it first...

5. Test the application

To test the application, create a virtual environment:

virtualenv venv

Activate the virtual environment:

source venv/bin/activate

Install the dependencies:

pip install -r requirements.txt

You should get a confirmation message like the following:

...
Successfully installed Flask ... gunicorn ...

Start the application:

python main.py

The logs show that you are in development mode:

 * Serving Flask app 'main'
 * Debug mode: on
   WARNING: This is a development server.
   Do not use it in a production deployment.
   Use a production WSGI server instead.
 * Running on http://localhost:8080
   Press CTRL+C to quit
...

In the Cloud Shell window, click the Web Preview icon and select Preview on port 8080:

This should open a browser window showing the Hello World! message.

You can also open another Cloud Shell session (a new terminal tab) by clicking the + icon and sending a web request to the application running locally:

curl localhost:8080

You should receive the following answer:

Hello World!

When you're done, go back to the main Cloud Shell session and stop the python main.py command with CTRL+C.

Exit the virtual environment:

deactivate

Finally, remove the virtual environment directory:

rm -r venv/

Your application works as expected: let's deploy it...

6. Deploy to Cloud Run

Cloud Run is regional, which means the infrastructure that runs your Cloud Run services is located in a specific region and is managed by Google to be redundantly available across all the zones within that region. Define the region you'll use for your deployment, for example:

REGION="europe-west9"

For the list of currently supported regions, see Cloud Run (fully managed) locations.

Make sure you are still in the working directory:

ls

This should list the following files:

main.py  Procfile  requirements.txt

Deploy the application to Cloud Run:

gcloud run deploy helloworld-python \
  --source . \
  --platform managed \
  --region $REGION \
  --allow-unauthenticated

• You can define a default region with this command: gcloud config set run/region $REGION
• You can also make Cloud Run managed by default with this command: gcloud config set run/platform managed
• The --allow-unauthenticated option makes the service publicly available. To avoid unauthenticated requests, use --no-allow-unauthenticated instead.

To check all options, use gcloud run deploy --help.

The first time, you'll get a prompt to create an Artifact Registry repository. Tap Enter to validate:

Deploying from source requires an Artifact Registry Docker repository to store
built containers. A repository named [cloud-run-source-deploy] in region [REGION]
will be created.

Do you want to continue (Y/n)?

This launches the upload of your source code to the Artifact Registry repository and the build of your container image:

Building using Buildpacks and deploying container ...
* Building and deploying new service... Building Container.           
  OK Creating Container Repository...
  OK Uploading sources...
  * Building Container... Logs are available at ...

Cloud Build uses Buildpacks which automatically detects the language of your source code and creates a container image based on the latest stable version of the Python interpreter (Python 3.12 at the time of writing). If needed, you can pin the build to a specific version by including a .python-version file in your source directory. For details, see Building a Python application.

Then, wait a moment until the deployment is complete. On success, the command line displays the service URL:

...
OK Building and deploying new service... Done.
  OK Creating Container Repository...
  OK Uploading sources...
  OK Building Container... Logs are available at ...
  OK Creating Revision... Creating Service.
  OK Routing traffic...
  OK Setting IAM Policy...
Done.
Service [SERVICE]... has been deployed and is serving 100 percent of traffic.
Service URL: https://SERVICE-PROJECTHASH-REGIONID.a.run.app

You can get the service URL with this command:

SERVICE_URL=$( \
  gcloud run services describe helloworld-python \
  --platform managed \
  --region $REGION \
  --format "value(status.url)" \
)
echo $SERVICE_URL

This should display something like the following:

https://helloworld-python-PROJECTHASH-REGIONID.a.run.app

You can now use your application by opening the service URL in a web browser:

You can also call the application from Cloud Shell:

curl $SERVICE_URL?who=me

This should give you the expected greeting:

Hello me!

While this short lab was done using the gcloud command-line, Cloud Run is available via Cloud Console ( console.cloud.google.com/run). You should see your helloworld service listed:

You can also use the console to deploy Cloud Run services.

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

7. Clean up

While Cloud Run does not charge when the service is not in use, you might still be charged for storing the container image in Artifact Registry. You can delete your repository or delete your Cloud project to avoid incurring charges. Deleting your Cloud project stops billing for all the resources used within that project.

To delete your container image repository:

gcloud artifacts repositories delete cloud-run-source-deploy \
  --location $REGION

To delete your Cloud Run service:

gcloud run services delete helloworld-python \
  --platform managed \
  --region $REGION

To delete your Google Cloud project,

1. Retrieve your current project ID:

PROJECT_ID=$(gcloud config get-value core/project)

2. Make sure this is the project you wish to delete:

echo $PROJECT_ID

3. Delete the project:

gcloud projects delete $PROJECT_ID

8. Congratulations!

You created a simple web application and deployed it to Cloud Run!

Learn more

• Check out the Cloud Run documentation
• Complete Dev to Prod in Three Easy Steps with Cloud Run, to explore more options
• Complete Django on Cloud Run, to create a Cloud SQL DB, manage credentials with Secret Manager, and deploy Django
• Check out more Cloud Run codelabs...

License

This work is licensed under a Creative Commons Attribution 2.0 Generic License.