Data Science Model Deployments and Cloud Computing on GCP - Lab - Continuous Deployment Using Cloud Build and GitHub

This video tutorial covers the process of setting up continuous deployment using Cloud Build. It begins with creating a GitHub repository and uploading necessary files. The tutorial then guides through creating a Cloud Build trigger in Google Cloud Platform (GCP) and configuring IAM permissions. Finally, it demonstrates testing the deployment by making changes to the source code and observing the automated build and deployment process.

What is the first step in setting up continuous deployment using Cloud Build?

• Configure a virtual machine

• Create a new GitHub repository

• Set up a Jenkins server

• Install Docker

What is the purpose of the cloudbuild git.yaml file?

• To store Docker images

• To create virtual machines

• To define build steps and configurations

• To manage user permissions

Which file format is used for the Cloud Build configuration?

• JSON

• YAML

• CSV

• XML

What is the role of a trigger in Cloud Build?

• To create virtual networks

• To manage user authentication

• To deploy applications to App Engine

• To initiate builds based on repository changes

What must be enabled in GCP to assign permissions for Cloud Build?

• BigQuery API

• Compute Engine API

• IAM API

• Cloud Storage API

Which command is used to authenticate before running permission commands?

• gcloud auth login

• gcloud compute start

• gcloud iam enable

• gcloud build deploy

What happens when a change is made to the source code in the GitHub repository?

• The source code is deleted

• The repository is archived

• The build is triggered and the application is redeployed

• The application is automatically deployed to App Engine