Cloud Bigtable can store petabytes of data — and Cloud Functions can access any of that data, parse it, and send it on to another service. In this hands-on lab, you’ll first create a Bigtable instance as well as a table and populate it with test data. Then you’ll build an HTTP-triggered Cloud Function to read specific elements of that data and output it for verification.
Successfully complete this lab by achieving the following learning objectives:
- Enable APIs
Enable the APIs necessary for creating a Cloud Function.
- Create and Prepare the Cloud Bigtable Instance
Create a Cloud Bigtable instance and then connect to it in the Cloud Shell so that you can create a test table and populate it with sample data.
- Retrieve the Working Files
Clone a Github repository to access the source files for the Cloud Function.
- Create and Test the Cloud Function
Create, deploy, and test a Cloud Function, triggered by HTTP, to read and output selected data from Cloud Bigtable.