Data Science Model Deployments and Cloud Computing on GCP - Lab – Use Case Deployment - Part-2

The video tutorial covers setting up an API endpoint using Cloud Functions to fetch data from Google Datastore. It explains the process of querying Datastore, applying filters, and deploying the function using gcloud commands. The tutorial also demonstrates testing the function and validating the results. Finally, it provides resources for further learning about Datastore and its integration with Python.

What is the primary purpose of the API endpoint discussed in the video?

• To update data in Datastore

• To store data into Datastore

• To expose data from Datastore for downstream applications

• To delete data from Datastore

Which function is used to add filters when querying a Datastore entity?

• add_filter

• set_filter

• apply_filter

• filter_add

What is the main function discussed in the video that interacts with Datastore?

• count_wishlist_entries

• retrieve_wishlist_items

• get_wishlist_data

• fetch_wishlist_count

What command is used to deploy the Cloud Function?

• function deploy gcloud

• deploy gcloud function

• gcloud deploy function

• gcloud functions deploy

What is the initial wishlist count shown after deploying the function?

• 2

• 5

• 4

• 3

What happens when the wishlist status is set to 0?

• The count decreases

• The count increases

• The count remains the same

• The count resets to zero

Where can you find more examples and documentation on using Datastore with Python?

• google.com, Cloud samples

• datastore.com, Python docs

• python.org, Datastore examples

• cloud.google.com, Datastore docs, samples