Container to Production in less than 5 minutes | Google Cloud Run | Google Cloud Platform

What are Containers?

A container packages up code and all its dependencies so the application can run on any computing environment

What is Cloud Run?

Cloud Run is a managed compute platform that enables you to run stateless containers that can be invoked by HTTP requests.

Steps to your container to Cloud Run:

1. Write a sample application
2. Containerize the application
3. Upload the app to Container Registry
4. Deploy to Cloud Run

1. Write a sample application

                              app.py
import os
 
 from flask import Flask
 
 app = Flask(__name__)
 
 @app.route(‘/’)
 def hello_world():
 return ‘Hello Google Cloud!\n’
 
 if __name__ == “__main__”:
 app.run(debug=True,host=’0.0.0.0',port=8080)))

2. Containerize the application

                           Dockerfile
FROM python:3.7
 
 # 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.
 CMD exec gunicorn — bind :$PORT — workers 1 — threads 8 app:app

3. Upload the app to Container Registry

Open Cloud shell and run the below given command. (change ‘PROJECT-ID’ with the project id of your GCP Project)

The last part of command i.e ‘helloworld’ is the container name, you can name it as per your wish.

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

4. Deploy to Cloud Run

The below command pushes the container to production.

gcloud beta run deploy — image gcr.io/[PROJECT-ID]/helloworld

Now you have a deployed your container on a completely managed, Auto scaled server with https encryption and a domain name for your application.

Benefits of Cloud Run:

Simple developer experience

Fast Auto-scaling

Fully Managed

Any language, Any library

Integrated logging and monitoring

Reach out to me on twitter: @IVaibhavMalpani

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