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Amazon SOA-C03 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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.
Topic 3	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 4	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 5	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.

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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q17-Q22):

NEW QUESTION # 17
A company runs a worker process on three Amazon EC2 instances. The instances are in an Auto Scaling group that is configured to use a simple scaling policy. The instances process messages from an Amazon SQS queue. Random periods of increased messages are causing a decrease in the performance of the worker process. A CloudOps engineer must scale the instances to accommodate the increased number of messages.
Which solution will meet these requirements?

A. Use CloudWatch to create a metric math expression to calculate the approximate number of messages visible in the SQS queue for each instance. Create a target tracking scaling policy for the metric math expression to modify the Auto Scaling group.
B. Use CloudWatch to create a metric math expression to calculate the approximate age of the oldest message in the SQS queue. Create a target tracking scaling policy for the metric math expression to modify the Auto Scaling group.
C. Create an Application Load Balancer (ALB). Attach the ALB to the Auto Scaling group. Create a scheduled scaling policy for the Auto Scaling group.
D. Create an Application Load Balancer (ALB). Attach the ALB to the Auto Scaling group. Create a target tracking scaling policy for the ALBRequestCountPerTarget metric to modify the Auto Scaling group.

Answer: A

Explanation:
For SQS-backed worker fleets, the most useful scaling signal is backlog per instance, calculated as the approximate number of visible messages divided by the number of running instances. This metric shows whether each worker instance has too much work to process and is therefore a strong target tracking metric.
Target tracking scaling is better than simple scaling for this pattern because it continuously adjusts capacity to keep the selected metric near the desired value. Option A uses the age of the oldest message, which can indicate delay but does not directly express workload per instance. Options C and D are wrong because an ALB request metric applies to HTTP request routing, not SQS message processing. Scheduled scaling is also unsuitable because the spikes are random and unpredictable. Therefore, option B is the correct performance optimization solution.

NEW QUESTION # 18
A user working in the Amazon EC2 console increased the size of an Amazon Elastic Block Store (Amazon EBS) volume attached to an Amazon EC2 Windows instance. The change is not reflected in the file system.
What should a CloudOps engineer do to resolve this issue?

A. Reboot the EC2 instance that is attached to the EBS volume.
B. Extend the file system with operating system-level tools to use the new storage capacity.
C. Reattach the EBS volume to the EC2 instance.
D. Take a snapshot of the EBS volume. Replace the original volume with a volume that is created from the snapshot.

Answer: B

Explanation:
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.
"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.

NEW QUESTION # 19
A company's security policy prohibits connecting to Amazon EC2 instances through SSH and RDP. Instead, staff must use AWS Systems Manager Session Manager. Users report they cannot connect to one Ubuntu instance, even though they can connect to others.
What should a CloudOps engineer do to resolve this issue?

A. Add an inbound rule for port 22 in the security group associated with the Ubuntu instance.
B. Generate a new key pair, configure Session Manager to use this new key pair, and provide the private key to the users.
C. Assign the AmazonSSMManagedInstanceCore managed policy to the EC2 instance profile for the Ubuntu instance.
D. Configure the SSM Agent to log in with a user name of "ubuntu".

Answer: C

Explanation:
According to AWS Cloud Operations and Systems Manager documentation, Session Manager requires that each managed instance be associated with an IAM instance profile that grants Systems Manager core permissions. The required permissions are provided by the AmazonSSMManagedInstanceCore AWS-managed policy.
If this policy is missing or misconfigured, the Systems Manager Agent (SSM Agent) cannot communicate with the Systems Manager service, causing connection failures even if the agent is installed and running. This explains why other instances work-those instances likely have the correct IAM role attached.
Enabling port 22 (Option A) violates the company's security policy, while configuring user names (Option C) and key pairs (Option D) are irrelevant because Session Manager operates over secure API channels, not SSH keys.
Therefore, the correct resolution is to attach or update the instance profile with the AmazonSSMManagedInstanceCore policy, restoring Session Manager connectivity.

NEW QUESTION # 20
A CloudOps engineer created a VPC with a private subnet, a security group allowing all outbound traffic, and an endpoint for EC2 Instance Connect in the private subnet. The EC2 instance was launched without an SSH key pair, using the same subnet and security group. However, the engineer cannot connect via EC2 Instance Connect endpoint.
How can the CloudOps engineer connect to the instance?

A. Create an inbound rule in the security group to allow SSH traffic on port 22 from the private subnet.
B. Create an IAM instance profile that allows AWS Systems Manager Session Manager to access the EC2 instance. Associate the instance profile with the instance.
C. Recreate the EC2 instance. Associate an SSH key pair with the instance.
D. Create an inbound rule in the security group to allow HTTPS traffic on port 443 from the private subnet.

Answer: B

Explanation:
According to the AWS Cloud Operations and EC2 Connectivity documentation, EC2 Instance Connect Endpoint allows access to instances without internet exposure or open SSH ports. However, for successful connectivity, the EC2 instance must have Systems Manager permissions through an IAM instance profile.
If no IAM instance profile is attached, the instance cannot establish a control channel with the Systems Manager service, and EC2 Instance Connect cannot authenticate the session.
Opening port 22 (Option B) is unnecessary and contradicts the private subnet design. HTTPS rules (Option A) are irrelevant because EC2 Instance Connect communicates through AWS APIs, not direct HTTPS connections. Recreating the instance with a key pair (Option D) bypasses the intended keyless connection mechanism.
Therefore, Option C - attaching an IAM instance profile with Systems Manager permissions - enables secure, private access through EC2 Instance Connect Endpoint.

NEW QUESTION # 21
A SysOps administrator needs to implement a solution that protects credentials for an Amazon RDS for MySQL DB instance. The solution must rotate the credentials automatically one time every week.
Which combination of steps will meet these requirements? (Select TWO.)

A. Create an AWS Systems Manager Automation runbook to rotate the credentials.
B. Add the credentials to AWS Secrets Manager.
C. Configure an RDS proxy to store the credentials.
D. Add the credentials to AWS Systems Manager Parameter Store.
E. Create an AWS Lambda function to rotate the credentials.

Answer: B,E

Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Documents:
The correct answers are B and D. AWS CloudOps documentation clearly states that AWS Secrets Manager is the recommended service for storing and managing database credentials securely. Secrets Manager integrates natively with Amazon RDS and supports automatic, scheduled secret rotation.
To rotate credentials weekly, Secrets Manager requires a Lambda rotation function. AWS provides managed rotation templates for Amazon RDS for MySQL that update the database password and the stored secret atomically. This combination ensures credentials are protected, rotated automatically, and audited with minimal operational effort.
Option A is incorrect because RDS Proxy does not store or rotate credentials; it only retrieves them from Secrets Manager. Option C is incorrect because Systems Manager Parameter Store does not support native automatic rotation. Option E is incorrect because Automation runbooks are not the recommended mechanism for secrets rotation and add unnecessary complexity.
AWS CloudOps best practices strongly recommend Secrets Manager with Lambda-based rotation for database credential protection and compliance.
References:
AWS Secrets Manager User Guide - Automatic Rotation
Amazon RDS User Guide - Credential Management
AWS SysOps Administrator Study Guide - Secrets and Key Management

NEW QUESTION # 22
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