Amazon Web Services SOA-C03 Practice Test Questions Answers

Amazon CloudWatch Application Signals is designed to provide built-in observability for containerized workloads, including Amazon EKS. It automatically collects golden signals such as latency, traffic, errors, and saturation without requiring complex instrumentation.

Application Signals supports SLO definition and SLI monitoring and correlates metrics, logs, and traces within CloudWatch. This significantly reduces operational overhead compared to manually configuring OpenTelemetry pipelines, Prometheus, and Grafana.

CloudWatch RUM and Synthetics focus on frontend monitoring, not backend service observability. Application Insights does not provide full SLO/SLI support for EKS workloads.

Therefore, CloudWatch Application Signals is the correct and least-effort solution.

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

To secure inbound web traffic over HTTPS when using an Application Load Balancer, AWS CloudOps best practices recommend terminating TLS at the load balancer. This is achieved by attaching an SSL/TLS certificate directly to the ALB listener. Therefore, option B is required. By terminating HTTPS at the ALB, traffic between clients and the load balancer is encrypted, and the ALB can then forward traffic to backend EC2 instances using HTTP or HTTPS based on design requirements.

The certificate used for a public-facing retail website must be trusted by internet browsers. AWS Certificate Manager (ACM) public certificates are specifically designed for this purpose and are trusted by common browsers and operating systems. Therefore, option D is required. ACM manages certificate provisioning, renewal, and deployment automatically, which significantly reduces operational overhead.

Option A is incorrect because attaching certificates to each EC2 instance is unnecessary and does not scale well. Option C is incorrect because private certificates are intended for internal use cases and are not trusted by public browsers. Option E is incorrect because ACM-managed public certificates cannot be exported; they must be attached directly to supported AWS services such as ALBs.

This approach aligns with AWS CloudOps guidance for secure, scalable, and highly available HTTPS architectures.

According to the AWS Cloud Operations and Deployment documentation, EC2 Image Builder is the AWS-managed service for automating the creation, maintenance, validation, and deployment of secure and compliant Amazon Machine Images (AMIs).

It allows CloudOps teams to define image pipelines that include only approved software modules and configuration scripts. EC2 Image Builder automatically tests and verifies these AMIs for compliance before deployment.

This process ensures configuration consistency, eliminates manual installation errors, and simplifies ongoing patch management. The service integrates with AWS Systems Manager, Amazon Inspector, and AWS CloudFormation for end-to-end automation.

In contrast:

Amazon Detective and GuardDuty (Options A & B) are security monitoring tools, not image management solutions.

Run Command (Option C) applies ad-hoc updates but does not create standard, reusable AMIs.

Therefore, Option D is correct—EC2 Image Builder provides the most operationally efficient and compliant way to create an approved baseline AMI for future deployments.

To analyze and visualize custom statistics such as the p90 latency (90th percentile), a CloudWatch metric must be generated from the log data. The correct method is to create a metric filter that extracts the latency value from each log event and publishes it as a CloudWatch metric. Once the metric is published, percentile statistics (p90, p95, etc.) can be displayed in CloudWatch dashboards or alarms.

AWS documentation states:

“You can use metric filters to extract numerical fields from log events and publish them as metrics in CloudWatch. CloudWatch supports percentile statistics such as p90 and p95 for these metrics.”

Contributor Insights (Option A) is for analyzing frequent contributors, not numeric distributions. Subscription filters (Option C) are used for log streaming, and Application Insights (Option D) provides monitoring of application health but not custom p90 statistics. Hence, Option B is the CloudOps-aligned, minimal-overhead solution for percentile latency monitoring.

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

To meet the requirement to log and audit any principal that publishes to SNS topics and interacts with SQS queues, the correct service is AWS CloudTrail, because CloudTrail records API activity (who did what, when, and from where). Enabling data events (where supported/required for deeper visibility) provides detailed records for operations such as publishing messages and sending/receiving messages. Delivering CloudTrail logs to Amazon S3 provides durable retention and supports querying workflows.

To ensure that communication uses VPC endpoints, the company should configure VPC endpoints for SNS and SQS and then validate usage by inspecting CloudTrail event records. CloudTrail includes endpoint-related context fields (for example, a VPC endpoint identifier) that allow auditors to confirm that the request path used a VPC endpoint rather than traversing the public internet. This directly addresses the “must use VPC endpoints” control with auditable evidence.

The other options do not satisfy both requirements. CloudWatch Logs does not automatically capture SNS/SQS API caller identity for publish/send/receive operations in the same authoritative way CloudTrail does. EventBridge can capture service events but is not the primary audit log of API calls and does not inherently prove VPC endpoint usage per request. Inspecting a VPC endpoint field in CloudWatch Logs is not the standard audit mechanism for these API calls.