Data Science Model Deployments and Cloud Computing on GCP - Lab - Python Application Deployment Using Cloud Build

This video tutorial guides viewers through deploying a Python application using Flask to Google Cloud Run. It covers setting up necessary files, handling CSV data, creating a BigQuery table, and understanding the cloudbuild.yaml file. The tutorial concludes with executing the deployment and verifying the results in Google Cloud Platform.

Which file contains the application logic for the Cloud Run deployment?

• requirements.txt

• main.py

• Dockerfile

• cloudbuild.yaml

What framework is used in the main.py file for the application logic?

• FastAPI

• Bottle

• Flask

• Django

What is the purpose of the CSV file in the application?

• To store application logs

• To define API endpoints

• To provide data for loading into BigQuery

• To configure environment variables

What is the first step in setting up BigQuery for this project?

• Create a new project

• Enable Cloud Run

• Create a dataset

• Upload the CSV file

Which command is used to build the Docker image in the cloudbuild.yaml file?

• docker start

• docker compose

• docker build

• docker run

What is the final step in the deployment process using Cloud Build?

• Push the image to Docker Hub

• Deploy the image to Cloud Run

• Create a new GCP project

• Run the application locally

What happens when you hit the endpoint of the deployed application?

• The application logs are displayed

• The application crashes

• The CSV data is ingested into BigQuery

• A new Docker image is built