SOA-C03 Dumps With Exact Questions and Answers

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.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Domain 1: Monitoring and Logging

• Amazon CloudWatch Logs – Metric Filters

• AWS Well-Architected Framework – Operational Excellence Pillar

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.

Per the AWS Cloud Operations and EventBridge documentation, when events are sent across AWS accounts — particularly from multiple accounts in an AWS Organization — the target event bus in the receiver account must include a resource-based policy that explicitly allows events:PutEvents API calls from the sender accounts or the organization ID.

Even if the sender accounts have IAM permissions to call PutEvents, the receiving event bus must trust those accounts via a resource policy. Without this configuration, EventBridge automatically rejects incoming cross-account events, and those events never reach the target Lambda function for processing.

AWS guidance states that “Cross-account event delivery requires a resource-based policy on the event bus that grants permissions to the source accounts or organization.” The policy can include either individual AWS account IDs or the organization’s root ID.

In this scenario, because the events originate from multiple accounts and there is no resource policy on the target event bus to authorize those sender accounts, the events are not delivered.

Therefore, the correct cause is C – the resource-based policy on the target event bus must be modified to allow PutEvents API calls from the sender accounts.