Which solution will achieve this goal?
Set up an AWS Database Migration Service (AWS DMS) change data capture (CDC) task. Specify the Aurora DB cluster as the source. Specify Amazon Kinesis Data Firehose as the target. Use Kinesis Data Firehose to upload the data into an Amazon OpenSearch Service cluster for further analysis.
Start a database activity stream on the Aurora DB cluster to capture the activity stream in Amazon EventBridge. Define an AWS Lambda function as a target for EventBridge. Program the Lambda function to decrypt the messages from EventBridge and to publish all database activity to Amazon S3 for further analysis.
Start a database activity stream on the Aurora DB cluster to push the activity stream to an Amazon Kinesis data stream. Configure Amazon Kinesis Data Firehose to consume the Kinesis data stream and to deliver the data to Amazon S3 for further analysis.
Set up an AWS Database Migration Service (AWS DMS) change data capture (CDC) task. Specify the Aurora DB cluster as the source. Specify Amazon Kinesis Data Firehose as the target. Use Kinesis Data Firehose to upload the data into an Amazon Redshift cluster. Run queries on the Amazon Redshift data to determine database activities on the Aurora database.
Explanations:
AWS DMS change data capture (CDC) is primarily used for replicating data to other databases and is not designed to monitor database activity directly. Additionally, using Kinesis Data Firehose for analysis in OpenSearch does not provide a direct monitoring solution for capturing all data activity.
While starting a database activity stream can capture database activity, using Amazon EventBridge and a Lambda function to publish to S3 does not provide a real-time monitoring solution. This method adds complexity and may introduce latency in capturing activity.
Starting a database activity stream on the Aurora DB cluster and pushing it to an Amazon Kinesis data stream is an effective solution for real-time monitoring. Kinesis Data Firehose can then deliver this stream to Amazon S3 for further analysis, providing an efficient and scalable way to monitor all database activity.
Similar to option A, using AWS DMS CDC for monitoring database activity is not appropriate. This option focuses on replicating data to Amazon Redshift, which is not a direct method of monitoring data activity and may not capture all database events efficiently.
I categorize that the answer is:
Start a database activity stream on the Aurora DB cluster to push the activity stream to an Amazon Kinesis data stream. Configure Amazon Kinesis Data Firehose to consume the Kinesis data stream and to deliver the data to Amazon S3 for further analysis.