Google Cloud Bigtable is a fully managed, scalable NoSQL database service for large-scale workloads. One use case for Bigtable is Internet of Things (IoT) applications. This lab is based on an IoT traffic monitoring application that uses sensors to record vehicle speeds along freeways. Although this scenario is the focus of this, generalizations of the data pipeline are also mentioned.
In the lab, you will explore the cloud services and application code that are used to collect the sensor data, store it in Bigtable, and read data from Bigtable. Once data is streaming into Cloud Bigtable, you will also learn how to back up and restore the table for your recovery needs.
Learning Objectives
Upon completion of this intermediate-level lab, you will be able to:
- Describe how to import data into Cloud Bigtable
- Use the Cloud Bigtable CLI (
cbt) to query a table - Back up and restore a Cloud Bigtable table
Intended Audience
This lab is intended for:
- Google Professional Cloud Database Engineer exam candidates
- Google Cloud data engineers
Prerequisites
You should possess:
-
A basic understanding of the following Google Cloud services:
- Cloud Bigtable
- Cloud Dataflow
The following content can fulfill the prerequisites:
Logan has been involved in software development and research since 2007 and has been in the cloud since 2012. He is an AWS Certified DevOps Engineer - Professional, AWS Certified Solutions Architect - Professional, Microsoft Certified Azure Solutions Architect Expert, MCSE: Cloud Platform and Infrastructure, Google Cloud Certified Associate Cloud Engineer, Certified Kubernetes Security Specialist (CKS), Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), and Certified OpenStack Administrator (COA). He earned his Ph.D. studying design automation and enjoys all things tech.