AWS Certified Data Analytics Specialty 2021 - Hands-On! - [Exercise] Kinesis Firehose - Part 1

This video tutorial guides viewers through setting up an Amazon Kinesis Data Firehose stream to capture server log data from an Amazon EC2 instance and store it in an Amazon S3 data lake. The tutorial covers creating the Firehose stream, configuring its source and destination, setting buffer sizes and intervals, and establishing necessary IAM roles for permissions. It emphasizes the importance of understanding Firehose's near real-time capabilities and provides insights into optional data transformations and security settings.

What is the primary purpose of setting up a Kinesis Data Firehose stream in this course?

• To analyze data using Amazon EC2.

• To set up a virtual private cloud.

• To create a real-time data processing application.

• To capture data from a server log and publish it into a data lake in Amazon S3.

What is the first step in creating a Kinesis Firehose delivery stream?

• Select the data transformation method.

• Name the delivery stream.

• Choose the data source.

• Set the buffer size.

Which data source option is selected for the Kinesis Firehose stream in this tutorial?

• Amazon Kinesis Agent

• Amazon EC2

• Direct Put

• Amazon S3

What is the default destination for the Firehose delivery stream?

• Amazon EC2

• Amazon RDS

• Amazon S3

• Amazon DynamoDB

What is the minimum buffer interval that can be set for Kinesis Firehose?

• 300 seconds

• 60 seconds

• 120 seconds

• 30 seconds

What role does IAM play in the setup of a Kinesis Firehose stream?

• It provides security permissions for accessing the S3 bucket.

• It encrypts the data in the S3 bucket.

• It compresses the data before storage.

• It transforms the data into JSON format.

What is the purpose of enabling error logging in the Firehose setup?

• To encrypt the data.

• To track and log any errors during data delivery.

• To compress the data.

• To transform the data format.