A company wants to stream their log files from their EC2 Instances. You are using Kinesis streams and Firehose for this process. The data will be parsed using AWS Lambda and then the resultant data will be stored in AWS Redshift. After the process is complete the amount of data in S3 has increased, and you had to delete the data manually. Since this process will be triggered on a continual basis, you need to ensure the right step is taken to delete the data in S3. How can you accomplish this?

Answer options:

A.Create a Lifecycle policy for the S3 bucket
B.Use Redshift triggers to delete the data after the data has finished loading
C.Use S3 events to delete the data after the data has finished loading
D.Disable S3 logging since this is causing the increase in data

Answer - A
The AWS Documentation mentions the following
Kinesis Data Firehose delivers your data to your S3 bucket first and then issues an Amazon Redshift COPY command to load the data into your Amazon Redshift cluster. Specify an S3 bucket that you own where the streaming data should be delivered. Create a new S3 bucket or choose an existing bucket that you own.
Kinesis Data Firehose doesn`t delete the data from your S3 bucket after loading it to your Amazon Redshift cluster. You can manage the data in your S3 bucket using a lifecycle configuration.
Option B is incorrect because triggers don’t exist in Redshift
Option C is incorrect sinceS3 events would need to call a Lambda function and cannot conduct the clean-up automatically
Option D is incorrect since the data build is because the intermediate data from the Kinesis firehose process is stored in S3 first
For more information on using various destinations with Firehose, please visit the url
https://docs.aws.amazon.com/firehose/latest/dev/create-destination.html