A company runs an Amazon Aurora PostgreSQL DB cluster in a single AWS Region. The database team must capture and monitor all data activity across the databases. Which solution will accomplish this requirement?

The correct solution leverages Aurora's Database Activity Streams, which are designed specifically for capturing database activity. Enabling this feature publishes a stream of all DDL and DML events to an Amazon Kinesis data stream. Kinesis Data Firehose can then reliably consume this data stream and deliver it to Amazon S3 for long-term storage and analysis. Incorrect options: Using AWS DMS for CDC is generally for replicating data changes between databases, not primarily for monitoring all data activity in a stream for analysis. While it can capture changes, Database Activity Streams are purpose-built for this monitoring use case. Sending activity streams to Amazon EventBridge and then using a Lambda function to decrypt and write to S3 adds unnecessary complexity and latency. Database Activity Streams integrate directly with Kinesis for efficient streaming. Loading into Amazon Redshift via DMS and Kinesis Data Firehose is an option for analytical purposes, but for capturing all activity for monitoring and analysis, S3 is a more flexible and cost-effective initial destination, especially when the primary goal is simply to store the raw activity stream.