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

The correct answer is A.

Option A is correct because it meets the requirements with the most operational efficiency. Updating the ecommerce application to emit a JSON object to a CloudWatch log group for each processed transaction is a simple and cost-effective way to collect the data needed for the dashboard. Using CloudWatch Logs Insights to query the log group and to visualize the results in a pie chart format is also a convenient and integrated solution that leverages the existing CloudWatch dashboards. Attaching the results to the desired CloudWatch dashboard is straightforward and does not require any additional steps or services.

Option B is incorrect because it introduces unnecessary complexity and cost. Updating the ecommerce application to emit a JSON object to an Amazon S3 bucket for each processed transaction is a valid way to store the data, but it requires creating and managing an S3 bucket and its permissions. Using Amazon Athena to query the S3 bucket and to visualize the results in a pie chart format is also a valid way to analyze the data, but it incurs charges based on the amount of data scanned by each query. Exporting the results from Athena and attaching them to the desired CloudWatch dashboard is also an extra step that adds more overhead and latency.

Option C is incorrect because it uses AWS X-Ray for an inappropriate purpose. Updating the ecommerce application to use AWS X-Ray for instrumentation is a good practice for monitoring and tracing distributed applications, but it is not designed for aggregating product transaction details. Creating a new X-Ray subsegment and adding an annotation for each processed transaction is possible, but it would clutter the X-Ray service map and make it harder to debug performance issues. Using X-Ray traces to query the data and to visualize the results in a pie chart format is also possible, but it would require custom code and logic that are not supported by X-Ray natively. Attaching the results to the desired CloudWatch dashboard is also not supported by X-Ray directly, and would require additional steps or services.

Option D is incorrect because it introduces unnecessary complexity and cost. Updating the ecommerce application to emit a JSON object to a CloudWatch log group for each processed transaction is a simple and cost-effective way to collect the data needed for the dashboard, as in option A. However, creating an AWS Lambda function to aggregate and write the results to Amazon DynamoDB is redundant, as CloudWatch Logs Insights can already perform aggregation queries on log data. Creating a Lambda subscription filter for the log file is also redundant, as CloudWatch Logs Insights can already access log data directly. Attaching the results to the desired CloudWatch dashboard would also require additional steps or services, as DynamoDB does not support native integration with CloudWatch dashboards.

The condition is deterministic: maximum CPU utilization must be below 2% for the previous 24 one-hour periods. That requires a static threshold, not anomaly detection. Anomaly detection learns a normal band from historical behavior, which is useful for unusual patterns but not for a fixed business definition of “idle.” CloudWatch alarms use “Datapoints to Alarm” as an M-out-of-N evaluation model, so 24 out of 24 means all 24 hourly datapoints must breach the threshold. AWS also documents idle-instance alarm examples based on CPU utilization staying below a threshold for 24 consecutive periods. Option D would alarm if only one hour was below 2%, which is far too sensitive. Options A and C use the wrong threshold type.

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The correct answer is D because AWS Secrets Manager supports automatic secret rotation and provides built-in rotation templates for supported services, including Amazon ElastiCache for Redis OSS. This gives the least operational overhead for rotating the secret every 60 days.

The requirement also states that employees and applications must access secrets and parameters through AWS Systems Manager Parameter Store. Parameter Store can reference Secrets Manager secrets by using a reserved path, which allows the application to retrieve the secret through Parameter Store while the secret is actually stored and rotated in Secrets Manager.

Why the other options are incorrect:

A. This option correctly uses Secrets Manager rotation, but it does not specifically use the reserved Parameter Store reference path approach that satisfies the access requirement through Parameter Store as clearly as option D.

B. Parameter Store does not provide native automatic rotation for secrets in the same way that Secrets Manager does.

C. This option is possible, but it requires custom Lambda and EventBridge automation, which creates more operational overhead than using native Secrets Manager rotation with the provided template.