Amazon Web Services DOP-C02 Exam With Confidence Using Practice Dumps

Step 1: Reacting to RDS Storage Autoscaling Events Using Amazon EventBridgeAmazon RDS emits events when storage autoscaling occurs. To visualize these events in a CloudWatch dashboard, you can create an EventBridge rule that listens for these specific autoscaling events.

Action: Create an EventBridge rule that reacts to RDS storage autoscaling events from the RDS event stream.

Why: EventBridge allows you to listen to RDS events and route them to specific AWS services for processing.

Step 2: Creating a Custom CloudWatch Metric via LambdaOnce the EventBridge rule detects a storage autoscaling event, you can use a Lambda function to publish a custom metric to CloudWatch. This metric can then be visualized in a CloudWatch dashboard.

Action: Use a Lambda function to publish custom metrics to CloudWatch based on the RDS storage autoscaling events.

Why: Custom metrics allow you to track specific events like autoscaling and visualize them easily on a CloudWatch dashboard.

S3 RTC ensures ≤15-min replication SLA.

Multi-Region Access Point (MRAP) simplifies active-passive replication access.

SubmitMultiRegionAccessPointRoutes API manages routing changes during failover. This configuration follows AWS DR best practices for S3 active/passive architectures.

The company requires an organization-wide, centralized, and automated solution to detect sensitive data in Amazon S3, aggregate findings in one location, and quarantine affected objects with minimal operational overhead. AWS provides a native service specifically designed for this purpose: Amazon Macie .

Option A is essential because Amazon Macie automatically discovers and classifies sensitive data such as PII in S3 buckets using managed machine learning models. When enabled at the organization level , Macie scans buckets across all accounts and Regions. Integrating Macie with AWS Security Hub centralizes all findings in a single dashboard, allowing the company’s security officer to review and manage sensitive data alerts across the organization without building custom aggregation pipelines.

Detection alone is not sufficient; remediation is also required. Option C completes the solution by using Amazon EventBridge , which natively receives Macie findings in near real time. An EventBridge rule can trigger a Lambda function whenever Macie identifies sensitive data. The Lambda function can then copy the affected object to a quarantine S3 bucket and delete the original object, meeting the remediation requirement automatically and consistently.

Option D requires custom sensitive data detection logic, which is complex, error-prone, and unnecessary given Macie’s capabilities. Option E is invalid because SCPs cannot inspect or move data. Option B does not detect sensitive information.

Therefore, A and C together provide the most efficient, scalable, and AWS-recommended solution.