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

 Add a Deploy Stage to the Pipeline, Configure Amazon ECS as the Action Provider:

By adding a deploy stage to the pipeline and configuring Amazon ECS as the action provider, the pipeline can automatically deploy the new container image to the ECS cluster.

This ensures that the service is updated with the new image tag, making the new version of the service endpoint reachable.

Only the Organizations management account (or roles in that account) can call organizations:CreateAccount directly. When moving the Lambda function to a different (dedicated) account, the correct pattern is to perform cross-account role assumption into a role that resides in the management account and has tightly scoped Organizations permissions.

Option A describes exactly this:

Create an IAM role in the management account with only the required Organizations permissions (for example, organizations:CreateAccount and related read permissions).

Configure the trust policy on that role to allow it to be assumed by the Lambda execution role in the new account.

Update the Lambda code to call sts:AssumeRole into the management-account role before invoking the Organizations API.

This approach ensures that:

The Lambda function can create new accounts, but only via the management account.

The Lambda execution role in the dedicated account has no direct Organizations permissions; it only has permission to assume the specific role.

Option B is incorrect because “delegated administration for Organizations” in the generic sense is not how CreateAccount is exposed; account creation remains a management-account responsibility. Options C and D either misconfigure trust or introduce unnecessary Control Tower complexity. Cross-account assume-role from the dedicated account into the management account is the correct and least-privilege solution.

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.