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Amazon SOA-C03 Exam Syllabus Topics:

Topic	Details
Topic 1	Networking and Content Delivery: This section measures skills of Cloud Network Engineers and focuses on VPC configuration, subnets, routing, network ACLs, and gateways. It includes optimizing network cost and performance, configuring DNS with Route 53, using CloudFront and Global Accelerator for content delivery, and troubleshooting network and hybrid connectivity using logs and monitoring tools.
Topic 2	Reliability and Business Continuity: This section measures the skills of System Administrators and focuses on maintaining scalability, elasticity, and fault tolerance. It includes configuring load balancing, auto scaling, Multi-AZ deployments, implementing backup and restore strategies with AWS Backup and versioning, and ensuring disaster recovery to meet RTO and RPO goals.
Topic 3	Deployment, Provisioning, and Automation: This section measures the skills of Cloud Engineers and covers provisioning and maintaining cloud resources using AWS CloudFormation, CDK, and third-party tools. It evaluates automation of deployments, remediation of resource issues, and managing infrastructure using Systems Manager and event-driven processes like Lambda or S3 notifications.
Topic 4	Security and Compliance: This section measures skills of Security Engineers and includes implementing IAM policies, roles, MFA, and access controls. It focuses on troubleshooting access issues, enforcing compliance, securing data at rest and in transit using AWS KMS and ACM, protecting secrets, and applying findings from Security Hub, GuardDuty, and Inspector.
Topic 5	Monitoring, Logging, Analysis, Remediation, and Performance Optimization: This section of the exam measures skills of CloudOps Engineers and covers implementing AWS monitoring tools such as CloudWatch, CloudTrail, and Prometheus. It evaluates configuring alarms, dashboards, and notifications, analyzing performance metrics, troubleshooting issues using EventBridge and Systems Manager, and applying strategies to optimize compute, storage, and database performance.

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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q183-Q188):

NEW QUESTION # 183
A company runs on-premises workloads that need to use AWS hosted DNS services. The company requires high availability for DNS queries to ensure continuous DNS resolution for critical applications. Which solution will meet these requirements?

A. Deploy Amazon Route 53 Resolver inbound endpoints to multiple Availability Zones. Configure on-premises DNS resolvers to use the endpoint IP addresses in a failover configuration.
B. Configure an Amazon Route 53 private hosted zone. Associate the private hosted zone with the on-premises network.
C. Deploy Amazon Route 53 Resolver outbound endpoints to multiple Availability Zones. Associate the endpoints with the on-premises DNS resolvers.
D. Use Amazon Route 53 latency-based routing to ensure that DNS queries from on-premises systems are directed to the closest resolver endpoint.

Answer: A

Explanation:
Route 53 Resolver inbound endpoints allow DNS queries from an on-premises network to resolve AWS-hosted DNS records, such as records in Route 53 private hosted zones. Deploying inbound endpoints across multiple Availability Zones and configuring the on-premises resolvers to use the endpoint IPs provides high availability for DNS resolution.

NEW QUESTION # 184
A company runs an application that logs user data to an Amazon CloudWatch Logs log group.
The company discovers that personal information the application has logged is visible in plain text in the CloudWatch logs.
The company needs a solution to redact personal information in the logs by default. Unredacted information must be available only to the company's security team. Which solution will meet these requirements?

A. Create an Amazon S3 bucket. Create an export task from appropriate log groups in CloudWatch.
Export the logs to the S3 bucket. Configure an Amazon Macie scan to discover personal data in the S3 bucket. Invoke an AWS Lambda function to move identified personal data to a second S3 bucket.
Update the S3 bucket policies to grant only the security team access to both buckets.
B. Create an Amazon CloudWatch data protection policy for the application log group. Configure data identifiers for the types of personal information that the application logs. Ensure that the security team has permission to call the unmask API operation on the application log group.
C. Create a customer managed AWS KMS key. Configure the KMS key policy to allow only the security team to perform decrypt operations. Associate the KMS key with the application log group.
D. Create an OpenSearch domain. Create an AWS Glue workflow that runs a Detect PII transform job and streams the output to the OpenSearch domain. Configure the CloudWatch log group to stream the logs to AWS Glue. Modify the OpenSearch domain access policy to allow only the security team to access the domain.

Answer: B

Explanation:
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.

NEW QUESTION # 185
An errant process is known to use an entire processor and run at 100%. A CloudOps engineer wants to automate restarting an Amazon EC2 instance when the problem occurs for more than 2 minutes.
How can this be accomplished?

A. Create an Amazon CloudWatch alarm for the EC2 instance with detailed monitoring. Add an action to restart the instance.
B. Create an AWS Lambda function to restart the EC2 instance, invoked on a scheduled basis every
2 minutes.
C. Create an AWS Lambda function to restart the EC2 instance, invoked by EC2 health checks.
D. Create an Amazon CloudWatch alarm for the EC2 instance with basic monitoring. Add an action to restart the instance.

Answer: A

Explanation:
With detailed monitoring enabled, CloudWatch collects EC2 metrics (such as CPUUtilization) at
1-minute intervals, allowing accurate detection of sustained 100% CPU usage. You can then configure a CloudWatch alarm that triggers when CPU utilization remains above a threshold (e.g.,
99%) for more than 2 consecutive minutes and set the alarm action to automatically restart the EC2 instance. This provides a fully automated, low-maintenance solution.

NEW QUESTION # 186
A company has deployed Amazon EC2 instances from custom Amazon Machine Images (AMIs) in two AWS Regions. The company registered all the instances with AWS Systems Manager.
The company discovers that the operating system on some instances has a significant zero-day exploit.
However, the company does not know how many instances are affected.
A CloudOps engineer must implement a solution to deploy operating system patches for the affected EC2 instances.
Which solution will meet this requirement with the LEAST operational overhead?

A. Use AWS Config to identify the affected instances. Update the existing EC2 AMIs with the desired patch. Manually launch instances from the new AMIs to replace the affected instances in both Regions.
B. Use AWS Config to identify the affected instances. Define a patch baseline in Systems Manager Patch Manager. Use the Patch Now option in Patch Manager to update the affected instances.
C. Create an Amazon EventBridge rule to react to Systems Manager Compliance events. Configure the EventBridge rule to run a patch baseline on the affected instances.
D. Define a patch baseline in Systems Manager Patch Manager. Use a Patch Manager scan to identify the affected instances. Use the Patch Now option in each Region to update the affected instances.

Answer: D

Explanation:
Because all instances are already managed by AWS Systems Manager, the lowest-overhead approach is to use Systems Manager Patch Manager end-to-end. Patch Manager is built specifically to scan managed instances for missing patches and to apply operating system patches according to defined rules. By defining a patch baseline, the CloudOps engineer establishes which patches are approved (and how quickly critical patches are approved), plus any exclusions and compliance rules. A Patch Manager scan can then be run to determine which instances are noncompliant and therefore likely affected by the vulnerability, without the engineer needing to manually inventory hosts.
After identifying affected (noncompliant) instances through the scan results, Patch Manager can apply patches directly using Patch Now (or an equivalent on-demand patch operation) in each Region. This matches the multi-Region requirement while keeping operations simple: no custom code, no additional services, and no complex event orchestration. It also produces compliance visibility in Systems Manager, which helps track remediation status for incident response.
Option B adds AWS Config unnecessarily. AWS Config is useful for recording and evaluating configuration changes and can report compliance against configuration rules, but it is not the most direct tool for identifying missing OS patches on instances already under Systems Manager management. Option C introduces additional moving parts (EventBridge rules and event-driven automation). While it can be powerful, it is more complex than a straightforward Patch Manager scan-and-patch workflow, and it assumes the right compliance events exist for this scenario before remediation begins. Option D is the highest operational burden because it requires rebuilding AMIs, launching replacement instances, and coordinating replacements across two Regions. That approach aligns to immutable infrastructure patterns, but it is not the least overhead for rapid remediation of existing instances.
Therefore, using Patch Manager with a patch baseline, scanning to identify affected instances, and applying patches in each Region is the simplest and most operationally efficient solution.

NEW QUESTION # 187
A company runs an application on Amazon EC2 that connects to an Amazon Aurora PostgreSQL database. A developer accidentally drops a table from the database, causing application errors. Two hours later, a CloudOps engineer needs to recover the data and make the application functional again.
Which solution will meet this requirement?

A. Create a new Aurora cluster. Choose the Restore data from S3 bucket option. Choose log files up to the failure time 2 hours in the past.
B. Perform a point-in-time recovery on the existing database to restore the database to a specified point in time, 2 hours in the past.
C. Perform a point-in-time recovery and create a new database to restore the database to a specified point in time, 2 hours in the past. Reconfigure the application to use a new database endpoint.
D. Use the Aurora Backtrack feature to rewind the database to a specified time, 2 hours in the past.

Answer: C

Explanation:
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.
Reference: AWS Cloud Operations & Aurora Guide - Section: Performing Point-in-Time Recovery for Aurora PostgreSQL Clusters

NEW QUESTION # 188
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