Amazon Web Services SOA-C03 Exam Dumps - Actual Questions Answers

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

The correct answer is C. Create a store image task. Specify the image ID and the destination S3 bucket, because this is the only AWS-supported solution that allows an AMI to be backed up to Amazon S3 and later restored while preserving the original AMI ID. This capability is essential for regulatory and compliance requirements where immutable identifiers must be retained.

According to AWS CloudOps documentation for Amazon EC2 AMI lifecycle management, the AMI store and restore feature is specifically designed for long-term retention, audit, and compliance scenarios. When an AMI is stored using a store image task, AWS packages the AMI’s configuration, metadata, and associated snapshots and saves them as encrypted objects in an Amazon S3 bucket. When the AMI is restored, AWS explicitly states that the restored AMI retains the same AMI ID as the original image, ensuring continuity for compliance tracking and operational dependencies.

Option A is incorrect because copying an AMI always results in a new AMI ID, even when copied within the same AWS Region. Option B is incorrect because archiving snapshots to Amazon S3 does not preserve AMI metadata or identity; restoring from snapshots requires creating a new AMI with a different ID. Option D is incorrect because the copy-image command is intended for cross-Region or cross-account AMI duplication and also generates a new AMI ID.

AWS CloudOps best practices clearly identify store image tasks as the correct mechanism when AMI identity preservation is required for governance, auditability, and compliance controls.

AWS Secrets Manager rotation is an API-driven activity that is recorded as an audit event. When the secret rotation workflow is initiated, AWS API activity is captured by AWS CloudTrail, which provides an authoritative source of “who did what and when” for compliance evidence. By creating an Amazon EventBridge rule that matches the relevant CloudTrail event for the rotation operation, the company can automatically detect rotation activity and trigger downstream actions without building a polling system. EventBridge can route matched events directly to Amazon SNS, which then fan-outs the notification to email, SMS, chat integrations, or incident tooling used by the database team.

Option A fits the requirement because it creates an event-driven compliance notification path specifically tied to the rotation operation. It also allows more precise filtering than log scanning: the rule can match the event name and include conditions that reflect successful completion, reducing noise and false positives. EventBridge rules are managed, highly available, and require minimal operational work once configured.

Option B is not the best fit because Secrets Manager does not rely on a “native SNS rotation notification toggle” as a primary mechanism for compliance notifications in the way described; the standard event-driven pattern is to use EventBridge/CloudTrail signals rather than expecting Secrets Manager to publish directly to SNS for every rotation outcome. Options C and D propose filtering CloudWatch Logs, which adds operational overhead (log ingestion, metric filters or subscription filters, and parsing) and is less direct than matching structured API events. CloudWatch Logs filtering is also more brittle because it depends on log formats and correct log routing for the relevant services.

Therefore, using EventBridge to match CloudTrail rotation events and forward them to SNS is the most reliable and low-maintenance solution.

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

Amazon Aurora supports up to 15 Aurora Replicas that share the same storage volume and provide read scaling and improved availability. Official guidance states that replicas “offload read traffic from the writer” and that you should direct read-only workloads to the reader endpoint, reducing CPU pressure and connection counts on the primary. Aurora also supports Replica Auto Scaling through Application Auto Scaling policies using metrics such as CPU utilization or connections to add or remove replicas automatically. This design addresses both high CPU and maximum connections by moving reporting traffic to read replicas while keeping a single write primary for OLTP. Option B creates a separate cluster with independent storage, increasing operational overhead and data synchronization complexity. Options C and D introduce application-layer caching changes that may not guarantee data freshness or relieve the write node directly. Therefore, adding read replicas and routing reporting to the reader endpoint, with auto scaling based on load, is the least intrusive, CloudOps-aligned way to stabilize performance.