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

The company needs multi-Region data persistence with immediate propagation and minimal operational overhead. For S3, the correct mechanism is S3 replication (Cross-Region Replication or Same-Region Replication), which continuously and asynchronously replicates new objects as they are written. Configuring two-way replication between the primary and secondary Region buckets ensures that objects written in either Region are replicated to the other automatically without custom code.

For DynamoDB, the native solution for multi-Region replication is DynamoDB global tables . Global tables provide multi-master, multi-Region replication with low-latency reads and writes in each Region and automatic propagation of changes. Converting existing tables into global tables and adding the secondary Region as a replica gives immediate, managed cross-Region replication with minimal maintenance.

Option A combines these two fully managed features: two-way S3 replication and DynamoDB global tables. This yields the highest operational efficiency.

Options B, C, and D rely on S3 Batch Operations or DynamoDB Streams + Lambda to manually copy data cross-Region. These approaches add complexity, custom code, and operational risk, and they are less suitable when AWS provides managed replication mechanisms specifically designed for this purpose.

Therefore, Option A is the correct and most efficient solution.

Amazon CloudWatch metric streams are designed to deliver metrics in near real time to downstream services like Amazon Data Firehose with minimal configuration and management overhead. By configuring a metric stream to include all metrics , you ensure that any newly created performance or custom metrics are automatically included without needing to update filters or code when namespaces or metrics change.

Option B uses a CloudWatch metric stream → Firehose → Lambda → S3 pattern. Firehose natively supports invoking a Lambda function for in-flight transformation of the metric data before final delivery to S3. This satisfies the requirement to transform metrics before storing them and provides a fully managed, serverless pipeline with very little ongoing operational burden.

Option A mentions including metrics from “the application and the CloudWatch namespace,” which implies more manual selection and maintenance, potentially missing new metrics if not explicitly added. Options C and D work at the log level, not at the metric level, and would require building additional logic to derive metrics from logs. This is more complex and not aligned with “least operational overhead.”

Therefore, Option B is the most efficient and scalable solution.