Pass the Amazon Web Services AWS Certified Associate SOA-C03 Questions and answers with CertsForce

CloudWatch Logs data protection provides native redaction/masking of sensitive data at ingestion and query. AWS documentation states it can “detect and protect sensitive data in logs” using data identifiers, and that authorized users can “use the unmask action to view the original data.” Creating a data protection policy on the log group masks PII by default for all viewers, satisfying the requirement to redact personal information. Granting only the security team permission to invoke the unmask API operation ensures that unredacted content is restricted. Option B (KMS) encrypts at rest but does not redact fields; encryption alone does not prevent plaintext visibility to authorized readers. Options A and D add complexity and latency, move data out of CloudWatch, and do not provide default inline redaction/unmask controls in CloudWatch itself. Therefore, the CloudOps-aligned, managed solution is to use CloudWatch Logs data protection with appropriate data identifiers and unmask permissions limited to the security team.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Monitoring & Logging

• Amazon CloudWatch Logs – Data Protection (masking/redaction with data identifiers)

• CloudWatch Logs – Permissions for masking and unmasking sensitive data

• AWS Well-Architected Framework – Security and Operational Excellence (sensitive data handling)

According to the AWS Cloud Operations and Identity Management documentation, when configuring federation between IAM Identity Center (formerly AWS SSO) and an external SAML 2.0 identity provider, two key prerequisites are required:

The IAM Identity Center SAML metadata file — This is uploaded to the external IdP to establish trust, define SAML endpoints, and enable identity federation.

The IdP metadata (including the public X.509 certificate) — This information is imported into IAM Identity Center to validate authentication assertions and encryption signatures.

IAM Identity Center and the IdP exchange this metadata to mutually establish secure, bidirectional federation.

Network-level details such as IP addresses (Option C) are unnecessary. Root access (Option D) or permissions to member accounts (Option E) are not required; only Control Tower or IAM administrative permissions in the management account are needed for setup.

Thus, the correct answer is A and B — the SAML metadata from both sides is required for federation.

According to the AWS Cloud Operations and Compute Optimizer documentation, Compute Optimizer provides right-sizing recommendations by analyzing Amazon CloudWatch metrics and instance configuration data. However, AWS explicitly notes that only supported instance types are included in Compute Optimizer analyses. If an EC2 instance type is newly released or not yet supported by Compute Optimizer, it will not appear in the Compute Optimizer dashboard until official support is added.

The documentation explains that “Compute Optimizer analyses only supported resource types and instance families. Instances using unsupported or newly launched instance types will not appear in the Compute Optimizer console.” This ensures the service provides accurate recommendations based on sufficient performance history and benchmark data.

While CloudWatch metrics are required for analysis, the complete absence of instances from the dashboard — rather than “insufficient metric data” notifications — indicates unsupported instance types. Compute Optimizer would normally still display those with limited metrics but would flag them as “insufficient data,” not remove them entirely.

Therefore, the most accurate cause of missing instances in this case is that Compute Optimizer does not support the newly released instance types, making option B correct.

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.

The most secure pattern is to use an IAM role for Amazon EC2 with the minimum required permissions. AWS guidance states: “Use roles for applications that run on Amazon EC2 instances” and “grant least privilege by allowing only the actions required to perform a task.” By attaching a role to the instance, short-lived credentials are automatically provided through the instance metadata service; this removes the need to create long-term access keys or embed secrets. Granting only sqs:SendMessage, sqs:ReceiveMessage, and sqs:DeleteMessage against the specific SQS queues enforces least privilege and aligns with CloudOps security controls. Options A and B rely on IAM user access keys, which contravene best practices for workloads on EC2 and increase credential-management risk. Option C uses a role but grants sqs:*, violating least-privilege principles. Therefore, Option D meets the security requirement with scoped, temporary credentials and precise permissions.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Security & Compliance

• IAM Best Practices – “Use roles instead of long-term access keys,” “Grant least privilege”

• IAM Roles for Amazon EC2 – Temporary credentials for applications on EC2

• Amazon SQS – Identity and access management for Amazon SQS

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.

References (AWS CloudOps Documents / Study Guide):

• Amazon Aurora – Replicas and Reader Endpoint (Aurora User Guide)

• Aurora Replica Auto Scaling (Aurora & Application Auto Scaling Guides)

• AWS Well-Architected Framework – Reliability & Performance Efficiency

Tagging is essential for governance, cost management, and automation in CloudOps operations. The AWS Organizations tag policies feature allows centralized definition and enforcement of required tag keys and accepted values across all accounts in an organization. According to the AWS CloudOps study guide under Deployment, Provisioning, and Automation, tag policies enable automatic validation of tags, ensuring consistency with minimal manual overhead.

Once tagging consistency is enforced, enabling cost allocation tags in the AWS Billing and Cost Management console allows accurate cost distribution per business unit. AWS documentation states:

“Use AWS Organizations tag policies to standardize tags across accounts. You can activate cost allocation tags in the Billing console to track and allocate costs.”

Option B introduces unnecessary complexity with Lambda automation. Option C detects but does not enforce tagging. Option D limits flexibility to Service Catalog resources only. Therefore, Option A provides a centrally managed, automated, and low-overhead solution that meets CloudOps tagging and cost-tracking requirements.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Domain 3: Deployment, Provisioning and Automation

• AWS Organizations – Tag Policies

• AWS Billing and Cost Management – Cost Allocation Tags

• AWS Well-Architected Framework – Operational Excellence and Cost Optimization Pillars

According to the AWS Cloud Operations and Database Reliability documentation, Amazon RDS Multi-AZ deployments provide high availability and automatic failover by maintaining a synchronous standby replica in a different Availability Zone.

In the event of instance failure, planned maintenance, or Availability Zone outage, Amazon RDS automatically promotes the standby to primary with minimal downtime (typically less than 60 seconds). The failover is transparent to applications because the DB endpoint remains the same.

By contrast, read replicas (Option B) are asynchronous and do not provide automated failover. Auto Scaling (Option C) applies to EC2, not RDS. RDS Proxy (Option D) improves connection management but does not add redundancy.

Thus, Option A — converting the RDS instance into a Multi-AZ deployment — delivers the required high availability and business continuity with minimal operational effort.

According to the AWS Cloud Operations and Security documentation, AWS CloudTrail is the authoritative service for recording API activity across all AWS services within an account.

When an access key is compromised, CloudTrail logs all API requests made using that key, including details such as:

The user identity (access key ID) that made the request,

The service, operation, resource, and timestamp affected, and

The source IP address and region of the request.

By searching the CloudTrail event history for the specific access key ID, the CloudOps engineer can identify every action performed by that key during the suspected breach window.

Other options are incorrect:

EventBridge (A) is event-driven, not historical.

CloudWatch Logs (B) monitors system logs, not AWS API activity.

VPC Flow Logs (D) track network-level traffic, not API calls.

Therefore, the correct solution is Option C — using AWS CloudTrail event history to audit and trace all actions executed via the compromised access key.