AWS Certified Data Analytics Specialty 2021 – Hands-On - (Exercise) Kinesis Data Streams

The video tutorial covers the use of AWS Kinesis Data Streams to build an order history app. It explains how to set up a data stream, configure EC2 instances, and use the Kinesis Agent to process and monitor data in real-time. The tutorial also highlights the differences between on-demand and provisioned capacity modes, and provides a step-by-step guide to creating and testing a Kinesis Data Stream.

What is the primary purpose of using Kinesis Data Streams in the order history app?

• To reduce data size

• To replace EC2 instances

• To provide real-time data access

• To store data permanently

When creating a Kinesis Data Stream, what is an important consideration for naming?

• It should be in lowercase

• It must be unique globally

• It should include numbers

• Spelling and capitalization matter

What is a key advantage of using the on-demand mode for Kinesis Data Streams?

• It provides unlimited storage

• It automatically adjusts capacity

• It requires no setup

• It is free of charge

What is the role of the Kinesis Agent in the EC2 setup?

• To convert JSON to CSV

• To connect EC2 to Kinesis Firehose

• To facilitate data flow to Kinesis Data Stream

• To monitor EC2 performance

How does the Kinesis Agent handle CSV data for the Lambda function?

• It encrypts the data

• It compresses the data

• It converts CSV to JSON

• It deletes unnecessary fields

What should you do if the Kinesis Agent fails to restart?

• Increase the instance size

• Check the configuration file for errors

• Reboot the EC2 instance

• Contact AWS support

What is the significance of monitoring the Kinesis Data Stream in the AWS console?

• To delete old data

• To ensure data is being processed correctly

• To increase the data retention period

• To change the stream name