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

When using the awslogs log driver with Amazon ECS on EC2, CloudWatch Logs permissions must be granted to the ECS container instance IAM role, not the task definition or infrastructure role. The ECS agent running on the EC2 instances is responsible for creating log streams and pushing log events to Amazon CloudWatch Logs on behalf of the containers.

In this scenario, the task definition is correctly configured to automatically create the log group (awslogs-create-group: true) and send logs to the specified Region. However, the error occurs because the EC2 container instances do not have sufficient IAM permissions to perform the required CloudWatch Logs API calls. As a result, ECS cannot place the task, and it reports that no container instance meets the requirements.

According to AWS documentation, the container instance IAM role must include the following permissions when using the awslogs driver:

logs:CreateLogStream

logs:PutLogEvents

(and, when creating log groups automatically) logs:CreateLogGroup

Option C correctly addresses the root cause by updating the container instance IAM role. Option A is incorrect because the ECS infrastructure or service role is not used to write logs. Option B is unrelated to permissions and does not resolve the issue. Option D would fail because the log group does not already exist, causing task startup to fail.

Therefore, modifying the container instance IAM role is the correct solution.

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.