Amazon Web Services Data-Engineer-Associate Exam With Confidence Using Practice Dumps

To prevent unintentional file deletions and meet the requirement with minimal operational overhead, enabling S3 Versioning is the best solution.

S3 Versioning:

S3 Versioning allows multiple versions of an object to be stored in the same S3 bucket. When a file is deleted or overwritten, S3 preserves the previous versions, which means you can recover from accidental deletions or modifications.

Enabling versioning requires minimal overhead, as it is a bucket-level setting and does not require additional backup processes or data replication.

Users can recover specific versions of files that were unintentionally deleted, meeting the needs of the data engineer to avoid accidental data loss.

Option B is the best answer because Amazon EventBridge is designed to route events based on matching rules, and each rule can use a specific event pattern to match only the relevant error type and then send that event to the correct target. AWS states that EventBridge event buses receive events and deliver them to targets, and that rules can match on event details and route matching events accordingly. This makes it ideal for real-time error classification with very little custom code. An SNS topic per team then provides immediate push-based notification delivery.

Option A adds unnecessary operational overhead because Lambda would be doing routing logic that EventBridge rules already handle natively. Option C is weaker because SQS is pull-based; teams must poll queues, which is not the best fit for “without any delay” notifications. AWS documentation explicitly describes SQS consumption through polling. Option D is also not the best fit because CloudWatch alarms are threshold-based metric monitors, not event routers for per-message error classification.

This aligns with the study guide’s emphasis on using managed AWS services to automate and orchestrate pipeline actions with the least overhead.

Problem Analysis:

The company must log all user activities and connection activities in Amazon Redshift for security compliance.

Key Considerations:

Redshift supports audit logging, which can be configured to write logs to an S3 bucket.

S3 provides durable, scalable, and cost-effective storage for logs.

Solution Analysis:

Option A: S3 for Logging

Standard approach for storing Redshift logs.

Easy to set up and manage with minimal cost.

Option B: Amazon EFS

EFS is unnecessary for this use case and less cost-efficient than S3.

Option C: Aurora MySQL

Using a database to store logs increases complexity and cost.

Option D: EBS Volume

EBS is not a scalable option for log storage compared to S3.

Final Recommendation:

Enable Redshift audit logging and specify an S3 bucket as the destination.

Amazon Redshift Audit Logging

Storing Logs in Amazon S3