Amazon Web Services Updated SOA-C03 Exam Questions and Answers by saint

Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Doocuments:

With simple scaling policies, an Auto Scaling group performs one scaling activity when the alarm condition is met, then observes a default cooldown period (300 seconds) before another scaling activity of the same type can begin. CloudOps guidance explains that cooldown prevents rapid successive scale-outs by allowing time for the newly launched instance(s) to register with the load balancer and impact the metric. Even if the alarm breaches multiple times during the cooldown window, the group waits until the cooldown completes before evaluating and acting again. In this case, although RequestCountPerTarget exceeded the threshold twice within 180 seconds, the group will launch a single instance and then wait for cooldown before any additional scale-out can occur. Options A, C, and D do not reflect the behavior of simple scaling with cooldowns; A describes step/target-tracking-like behavior, and C/D are not Auto Scaling mechanics.

According to AWS Cloud Operations and Governance documentation, AWS Trusted Advisor provides automated checks for security group rules across all accounts, including identifying ports open to 0.0.0.0/0.

When viewed in organizational mode, Trusted Advisor integrates with AWS Organizations, allowing administrators to access organization-wide security findings from a central management account. This approach requires no custom code, additional infrastructure, or manual inspection, providing immediate visibility and the lowest operational overhead.

AWS CLI scripts (Option A) or Lambda automation (Option C) introduce additional maintenance, and Amazon Inspector (Option D) is focused on instance-level vulnerabilities, not network access rules.

Therefore, Option B is the AWS-recommended CloudOps best practice for centralized and low-effort open-port auditing.

In the AWS Cloud Operations and Aurora documentation, when data loss occurs due to human error such as dropped tables, Point-in-Time Recovery (PITR) is the recommended method for restoration. PITR creates a new Aurora cluster restored to a specific time before the failure.

The restored cluster has a new endpoint that must be reconfigured in the application to resume normal operations. AWS does not support performing PITR directly on an existing production database because that would overwrite current data.

Aurora Backtrack (Option A) applies only to Aurora MySQL, not PostgreSQL. Option B is incorrect because PITR cannot be executed in place. Option D refers to an import process from S3, which is unrelated to time-based recovery.

Hence, Option C is correct and follows the AWS CloudOps standard recovery pattern for PostgreSQL workloads.

AWS Systems Manager Session Manager allows secure, auditable instance access without SSH keys or inbound ports. To control access based on instance tags, CloudOps best practices require two configurations:

Attach an IAM policy to users or groups granting ssm:StartSession, ssm:DescribeInstanceInformation, and ssm:DescribeSessions.

Include a Condition element in the IAM policy referencing instance tags, such as Condition: {"StringEquals": {"ssm:resourceTag/Environment": "Production"}}.

This ensures users can start sessions only with instances that have matching tags, providing fine-grained access control.

AWS CloudOps documentation under Security and Compliance states:

“Use IAM policies with resource tags in the Condition element to restrict which managed instances users can access using Session Manager.”

Options B and D incorrectly suggest attaching roles or service accounts that are not relevant to user-level access control. Option C (placement groups) pertains to networking and performance, not access management. Therefore, A and E together provide tag-based, least-privilege access as required.