Build and deploy a Python service

Learn how to create a simple Hello World application, package it into a container image, upload the container image to Container Registry, and then deploy the container image to Cloud Run. You can use other languages in addition to the ones shown.


For step-by-step guidance on this task directly in Cloud Shell Editor, click Guide me:

Guide me


The following sections take you through the same steps as clicking Guide me.

Before you begin

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. In the Google Cloud Console, on the project selector page, select or create a Google Cloud project.

    Go to project selector

  3. Make sure that billing is enabled for your Cloud project. Learn how to confirm that billing is enabled for your project.

  4. Install and initialize the Cloud SDK.

Writing the sample application

To write an application in Python:

  1. Create a new directory named helloworld and change directory into it:

    mkdir helloworld
    cd helloworld
    
  2. Create a file named main.py and paste the following code into it:

    import os
    
    from flask import Flask
    
    app = Flask(__name__)
    
    
    @app.route("/")
    def hello_world():
        name = os.environ.get("NAME", "World")
        return "Hello {}!".format(name)
    
    
    if __name__ == "__main__":
        app.run(debug=True, host="0.0.0.0", port=int(os.environ.get("PORT", 8080)))

    This code responds to requests with our "Hello World" greeting. HTTP handling is done by a Gunicorn web server in the container. When directly invoked for local use, this code creates a basic web server that listens on the port defined by the PORT environment variable.

Your app is finished and ready to be containerized and uploaded to Container Registry.

Containerizing an app and uploading it to Container Registry

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

The Python Dockerfile starts a Gunicorn web server that listens on the port defined by the PORT environment variable:


# Use the official lightweight Python image.
# https://hub.docker.com/_/python
FROM python:3.9-slim

# Allow statements and log messages to immediately appear in the Knative logs
ENV PYTHONUNBUFFERED True

# Copy local code to the container image.
ENV APP_HOME /app
WORKDIR $APP_HOME
COPY . ./

# Install production dependencies.
RUN pip install Flask gunicorn

# Run the web service on container startup. Here we use the gunicorn
# webserver, with one worker process and 8 threads.
# For environments with multiple CPU cores, increase the number of workers
# to be equal to the cores available.
# Timeout is set to 0 to disable the timeouts of the workers to allow Cloud Run to handle instance scaling.
CMD exec gunicorn --bind :$PORT --workers 1 --threads 8 --timeout 0 main:app

Add a .dockerignore file to exclude files from your container image.

Dockerfile
README.md
*.pyc
*.pyo
*.pyd
__pycache__
.pytest_cache

Build your container image using Cloud Build, by running the following command from the directory containing the Dockerfile:

gcloud builds submit --tag gcr.io/PROJECT-ID/helloworld

where PROJECT-ID is your GCP project ID. You can get it by running gcloud config get-value project.

Upon success, you will see a SUCCESS message containing the image name (gcr.io/PROJECT-ID/helloworld). The image is stored in Container Registry and can be re-used if desired.

Deploying to Cloud Run

To deploy the container image:

  1. Deploy using the following command:

    gcloud run deploy --image gcr.io/PROJECT-ID/helloworld

    If prompted to enable the API, Reply y to enable.

    Replace PROJECT-ID with your GCP project ID. You can view your project ID by running the command gcloud config get-value project.

    1. You will be prompted for the service name: press Enter to accept the default name, helloworld.
    2. You will be prompted for region: select the region of your choice, for example us-central1.
    3. You will be prompted to allow unauthenticated invocations: respond y .

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

  2. Visit your deployed container by opening the service URL in a web browser.

Cloud Run locations

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.

Meeting your latency, availability, or durability requirements are primary factors for selecting the region where your Cloud Run services are run. You can generally select the region nearest to your users but you should consider the location of the other Google Cloud products that are used by your Cloud Run service. Using Google Cloud products together across multiple locations can affect your service's latency as well as cost.

Cloud Run is available in the following regions:

Subject to Tier 1 pricing

  • asia-east1 (Taiwan)
  • asia-northeast1 (Tokyo)
  • asia-northeast2 (Osaka)
  • europe-north1 (Finland) leaf icon Low CO2
  • europe-west1 (Belgium)
  • europe-west4 (Netherlands)
  • us-central1 (Iowa) leaf icon Low CO2
  • us-east1 (South Carolina)
  • us-east4 (Northern Virginia)
  • us-west1 (Oregon) leaf icon Low CO2

Subject to Tier 2 pricing

  • asia-east2 (Hong Kong)
  • asia-northeast3 (Seoul, South Korea)
  • asia-southeast1 (Singapore)
  • asia-southeast2 (Jakarta)
  • asia-south1 (Mumbai, India)
  • asia-south2 (Delhi, India)
  • australia-southeast1 (Sydney)
  • australia-southeast2 (Melbourne)
  • europe-central2 (Warsaw, Poland)
  • europe-west2 (London, UK)
  • europe-west3 (Frankfurt, Germany)
  • europe-west6 (Zurich, Switzerland) leaf icon Low CO2
  • northamerica-northeast1 (Montreal) leaf icon Low CO2
  • southamerica-east1 (Sao Paulo, Brazil) leaf icon Low CO2
  • us-west2 (Los Angeles)
  • us-west3 (Las Vegas)
  • us-west4 (Salt Lake City)

If you already created a Cloud Run service, you can view the region in the Cloud Run dashboard in the Cloud Console.

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

Clean up

Removing your test project

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

  1. In the Cloud Console, go to the Manage resources page.

    Go to Manage resources

  2. In the project list, select the project that you want to delete, and then click Delete.
  3. In the dialog, type the project ID, and then click Shut down to delete the project.

What's next

For more information on building a container from code source and pushing to Container Registry, see: