Amazon Web Services Updated DOP-C02 Exam Questions and Answers by fabian

https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/SubscriptionFilters.html#LambdaFunctionExample

https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/SubscriptionFilters.html

Accessing a secret from AWS Secrets Manager that is encrypted with a customer managed KMS key requires two distinct permission layers to succeed:

Secrets Manager permissions (via IAM) such as secretsmanager:GetSecretValue for the IAM role assumed by the Kubernetes service account.

KMS key usage permissions in the KMS key policy, allowing the same IAM principal to perform kms:Decrypt (and possibly kms:GenerateDataKey) on the customer managed key.

In this scenario, the service account assumes an IAM role explicitly created to access the secrets. The symptom is an HTTP 403 “Access Denied” when retrieving the secret. If the IAM role has Secrets Manager permissions but the call still fails, the typical root cause is that the KMS key policy does not trust or allow that IAM role, so the decrypt operation fails.

Option B correctly identifies that the KMS key policy must include the Kubernetes service account IAM role as a principal with the appropriate KMS actions.

Option A and C refer to the EKS cluster IAM role, which is not the principal making the call. Option D is unrelated: the role’s ability to “access the EKS cluster” does not affect its ability to call Secrets Manager or KMS. The missing KMS key policy permission is the underlying cause.

Amazon S3 can generate server access logs that record detailed information about each request, including requester, bucket, key, operation, time, and status. These logs are written as objects to an S3 bucket. To analyze access patterns, the simplest and most serverless approach is to use Amazon Athena directly on those logs without building ingestion pipelines or databases.

Option B enables S3 server access logging and then creates an Athena external table over the log bucket. AWS provides standard log formats and even example schemas for S3 access logs. The analytics team can run ad hoc SQL queries to count the number of accesses per object per time period, filter by user, and perform aggregations, all without provisioning compute or managing databases.

Option A requires ingesting logs into Aurora, which adds ETL complexity and ongoing database management. Option C requires a Lambda function for every access event plus DB writes, which is more complex and potentially expensive at scale. Option D uses CloudWatch Logs and Managed Flink, which is more suited for streaming analytics and is significantly more complex than necessary for monthly summary reports.

Therefore, Option B provides the required analysis with the least development and operational effort.

To implement governance controls that restrict AWS service usage to within the United States and ensure alerts for any activity outside the governance policy, the following actions will meet the requirements:

A. Create an AWS Organizations SCP that denies access to all non-global services in non-US Regions. Attach the policy to the root of the organization. This action will effectively prevent users and roles in all accounts within the organization from accessing services in non-US Regions12.

B. Configure AWS CloudTrail to send logs to Amazon CloudWatch Logs and enable it for all Regions. Use a CloudWatch Logs metric filter to send an alert on any service activity in non-US Regions. This action will allow monitoring of all AWS Regions and will trigger alerts if any activity is detected in non-US Regions, ensuring that the governance team is notified as soon as possible3.

AWS Documentation on Service Control Policies (SCPs) and how they can be used to manage permissions and restrict access based on Regions12.

AWS Documentation on monitoring CloudTrail log files with Amazon CloudWatch Logs to set up alerts for specific activities3.