SOA-C03 AWS Certified CloudOps Engineer - Associate Questions and Answers

Per the AWS Cloud Operations and S3 Data Management documentation, Cross-Region Replication (CRR) automatically replicates new objects between S3 buckets across Regions. However, CRR alone does not retroactively replicate existing objects created before replication configuration. To include such objects, AWS introduced S3 Batch Replication.

S3 Batch Replication scans the source bucket and replicates all existing objects that were not copied previously. Additionally, it can retry failed replication tasks automatically, ensuring regulatory compliance for complete dataset replication.

S3 Replication Time Control (S3 RTC) guarantees predictable replication times for new objects only—it does not cover previously stored data. S3 Lifecycle rules (Option D) move or transition objects between storage classes or buckets, but not in a replication context.

Therefore, the correct solution is to use S3 Cross-Region Replication (CRR) combined with S3 Batch Replication to ensure all current and future data is synchronized across Regions with retry capability.

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.

When an Amazon EBS volume is resized, the new storage capacity is immediately available to the attached EC2 instance. However, EBS does not automatically extend the file system. The CloudOps engineer must manually extend the file system within the operating system to utilize the additional space.

AWS documentation for EC2 and EBS specifies:

“After you increase the size of an EBS volume, use file system–specific tools to extend the file system so that the operating system can use the new storage capacity.”

On Windows instances, this can be achieved through Disk Management or diskpart commands. On Linux systems, utilities such as growpart and resize2fs are used.

Options B and C do not modify file system metadata and are ineffective. Option D unnecessarily replaces the volume, which adds risk and downtime. Thus, Option A aligns with the Monitoring and Performance Optimization practices of AWS CloudOps by properly extending the file system to recognize the new capacity.

References (AWS CloudOps Documents / Study Guide):

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

• Amazon EBS – Modifying EBS Volumes

• Amazon EC2 User Guide – Extending a File System After Resizing a Volume

• AWS Well-Architected Framework – Performance Efficiency Pillar

Per the AWS Cloud Operations, Networking, and Security documentation, the best practice for serving private S3 content securely to end users is to use Amazon CloudFront with Origin Access Control (OAC).

OAC enables CloudFront to access S3 buckets privately, even when Block Public Access settings are enabled at the account level. This allows content to be delivered globally and securely without making the S3 bucket public. The bucket policy explicitly allows access only from the CloudFront distribution, ensuring that users can retrieve PDF files only via CloudFront URLs.

This configuration offers:

Automatic scalability through CloudFront caching,

Improved security via private access control,

Minimal administration effort with fully managed services.

Other options require manual handling or make the bucket public, violating AWS security best practices.

Therefore, Option B—using CloudFront with Origin Access Control and a restrictive bucket policy—provides the most secure, efficient, and low-maintenance CloudOps solution.

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.

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

Use Amazon S3 Event Notifications with AWS Lambda to trigger image processing on object creation. S3 natively supports invoking Lambda for events such as s3:ObjectCreated:*, providing a serverless, low-latency pipeline without managing additional services. AWS operational guidance states that “Amazon S3 can directly invoke a Lambda function in response to object-created events,” allowing you to pass event metadata (bucket/key) to the function for resizing and writing results back to S3. This approach minimizes operational overhead, scales automatically with upload volume, and integrates with standard retry semantics. SNS or SQS can be added for fan-out or buffering patterns, but they are not required when the requirement is simply “invoke the Lambda function on upload.” CloudWatch alarms do not detect individual S3 object uploads and cannot directly satisfy per-object triggers. Therefore, configuring S3 → Lambda event notifications meets the requirement most directly and aligns with CloudOps best practices for event-driven, serverless automation.

References (AWS CloudOps Documents / Study Guide):

• Using AWS Lambda with Amazon S3 (Lambda Developer Guide)

• Amazon S3 Event Notifications (S3 User Guide)

• AWS Well-Architected – Serverless Applications (Operational Excellence)

An alias record is the recommended Route 53 record type to map domain names (e.g., example.com) to AWS-managed resources such as an Application Load Balancer. Alias records are extension types of A or AAAA records that support AWS resources directly, providing automatic DNS integration and no additional query costs.

AWS documentation states:

“Use alias records to map your domain or subdomain to an AWS resource such as an Application Load Balancer, CloudFront distribution, or S3 website endpoint.”

A and AAAA records are used for static IP addresses, not load balancers. CNAME records cannot be used at the root domain (e.g., example.com). Thus, Option C is correct as it meets CloudOps networking best practices for scalable, managed DNS resolution to ALBs.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Domain 5: Networking and Content Delivery

• Amazon Route 53 Developer Guide – Alias Records

• AWS Well-Architected Framework – Reliability and Performance Efficiency Pillars

• Elastic Load Balancing – Integrating with Route 53

Per the AWS Cloud Operations, Monitoring, and Automation documentation, the correct workflow for automated operational remediation is:

Amazon CloudWatch Agent is installed on each EC2 instance (Option A) to collect local log data and push it to Amazon CloudWatch Logs.

A CloudWatch Metric Filter (Option C) is then defined to identify specific error strings or patterns within those logs (e.g., “HTTP 5xx” or “Service Unavailable”). When such an event occurs, CloudWatch Alarms are triggered.

Upon alarm activation, Amazon EventBridge rules (Option E) are configured to respond automatically by invoking an AWS Systems Manager Automation runbook, which executes an action to restart the web server process on the affected instance via SSM Agent.

This approach aligns directly with AWS’s recommended CloudOps remediation pattern, known as event-driven automation, which ensures minimal downtime and eliminates manual intervention.

Options involving CloudTrail (B) or SES notifications (D) are incorrect because they are unrelated to log-based application monitoring and automated remediation workflows.

According to the AWS Cloud Operations and Elastic Load Balancing documentation, Application Load Balancer (ALB) supports multiple routing algorithms to distribute requests among targets:

Round robin (default)

Least outstanding requests (LOR)

Weighted random

When applications require session affinity, AWS recommends using “least outstanding requests” as the load balancing algorithm because it reduces latency, distributes load evenly, and ensures consistent target responsiveness during high traffic.

Using weighted random routing with sticky sessions can cause sessions to be routed inconsistently if one target’s capacity fluctuates, leading to session mismatches and application errors — especially when user sessions rely on instance-specific state.

Disabling cross-zone balancing (Option C) or adjusting deregistration delay (Option D) does not address routing inconsistency. Anomaly mitigation (Option B) protects against target performance degradation, not sticky-session misrouting.

Therefore, the correct solution is Option A — changing the target group’s routing algorithm to least outstanding requests ensures smoother, predictable session handling and resolves random application errors.

According to CloudOps automation and monitoring best practices, CloudWatch dashboards should be provisioned as infrastructure-as-code (IaC) resources using AWS CloudFormation to ensure consistency, repeatability, and version control. AWS CloudFormation supports the AWS::CloudWatch::Dashboard resource, where the DashboardBody property accepts a JSON object describing widgets, metrics, and layout.

By exporting the existing dashboard configuration as JSON and embedding it into the CloudFormation template, every deployment of the application automatically creates its corresponding dashboard. This method aligns with the CloudOps requirement for automated deployment and operational visibility within the same stack lifecycle.

AWS documentation explicitly states:

“Use the AWS::CloudWatch::Dashboard resource to create a dashboard from your template. You can include the same JSON you use to define a dashboard in the console.”

Option A requires manual execution. Options C and D incorrectly reference or reuse existing dashboards, failing to produce unique, deployment-specific dashboards.

References (AWS CloudOps Documents / Study Guide):

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

• AWS CloudFormation User Guide – Resource Type: AWS::CloudWatch::Dashboard

• AWS Well-Architected Framework – Operational Excellence Pillar

• Amazon CloudWatch – Automating Dashboards with Infrastructure as Code

The combination of geoproximity routing and DNS failover health checks provides global low-latency routing with high availability.

Geoproximity routing in Route 53 routes users to the AWS Region closest to their geographic location, optimizing latency. For automatic failover, Route 53 health checks can monitor CloudWatch alarms tied to the health of the ALB in each Region. When a Region becomes unhealthy, Route 53 reroutes traffic to the next available Region automatically.

AWS documentation states:

“Use geoproximity routing to direct users to resources based on geographic location, and configure health checks to provide DNS failover for high availability.”

Option B incorrectly monitors EC2 instances directly, which is not efficient at scale. Option C uses private IPs, which cannot be globally health-checked. Option E (simple routing) does not support geographic or failover routing. Hence, A and D together meet both the proximity and failover requirements.

References (AWS CloudOps Documents / Study Guide):

• AWS Certified CloudOps Engineer – Associate (SOA-C03) Exam Guide – Domain 5: Networking and Content Delivery

• Amazon Route 53 Developer Guide – Geoproximity Routing and DNS Failover

• AWS Well-Architected Framework – Reliability Pillar

• Amazon CloudWatch Alarms – Integration with Route 53 Health Checks

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.

The AWS Cloud Operations and Storage documentation confirms that S3 Transfer Acceleration is designed to increase upload speed for objects transferred to S3 buckets over long distances.

It uses AWS Global Edge Network and Amazon CloudFront edge locations to route data through optimized network paths, reducing latency and achieving higher throughput compared to standard S3 uploads.

After enabling Transfer Acceleration on the bucket, users upload files to the accelerated endpoint (e.g., bucketname.s3-accelerate.amazonaws.com). This feature requires no changes to application logic besides endpoint modification and provides immediate performance improvement.

CloudFront (Option A) is for content delivery, not uploads. ElastiCache (Option B) and Global Accelerator (Option C) are unrelated to S3 upload performance.

Thus, Option D is correct — enable S3 Transfer Acceleration for faster, optimized file uploads.

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.

As per the AWS Cloud Operations and Event Monitoring documentation, the most efficient method for event-driven notification is to use Amazon EventBridge to detect specific EC2 API events and trigger a Simple Notification Service (SNS) alert.

EventBridge continuously monitors AWS service events, including RunInstances, which signals the creation of new EC2 instances. When such an event occurs, EventBridge sends it to an SNS topic, which then immediately emails subscribed recipients — in this case, the architecture team.

This combination provides real-time, serverless notifications with minimal management. SQS (Option C) is designed for queue-based processing, not direct user alerts. User data scripts (Option A) and custom polling with Lambda (Option D) introduce unnecessary operational complexity and latency.

Hence, Option B is the correct and AWS-recommended CloudOps design for immediate launch notifications.

The AWS Cloud Operations and Monitoring documentation states that Amazon CloudWatch Logs Insights provides a purpose-built query engine for analyzing and visualizing log data directly within CloudWatch. For Lambda, all invocation results (including errors) are automatically logged to CloudWatch Logs.

By querying these logs with CloudWatch Logs Insights, the CloudOps engineer can efficiently count the number of “ERROR” or “Exception” occurrences over the past 7 days using simple SQL-like commands. This method is serverless, cost-efficient, and real-time.

Athena (Options A and B) would require exporting data to Amazon S3, and OpenSearch (Option D) adds unnecessary operational complexity.

Thus, Option C provides the most efficient and native AWS CloudOps approach for rapid Lambda error analysis.