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Amazon SOA-C03 Exam Syllabus Topics:

Section	Weight	Objectives
Security and Compliance	18%	- Identity and access management (IAM) - Security monitoring and auditing - Data protection and encryption
Deployment, Provisioning, and Automation	18%	- Infrastructure as Code using AWS CloudFormation - Configuration management and orchestration tools - Automated deployment pipelines
Cost and Performance Optimization	28%	- Right-sizing and capacity planning - Cost monitoring and optimization strategies - Resource performance tuning
Monitoring, Logging, and Remediation	20%	- Automated remediation and operational workflows - Centralized logging and log analysis with AWS services - Metrics and monitoring using Amazon CloudWatch
Reliability and Business Continuity	16%	- Backup and disaster recovery strategies - Data replication and recovery mechanisms - High availability and fault tolerance design

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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q192-Q197):

NEW QUESTION # 192
A company runs a workload in an Amazon VPC. The company configures Amazon CloudWatch Logs for the workload. The company needs a solution to automatically detect unusual API activity and security events in the company's AWS account.
Which solution will meet this requirement?

A. Use AWS Config automatic anomaly detection.
B. Implement AWS CloudTrail Insights.
C. Use Amazon Inspector to scan VPC flow logs.
D. Use Amazon GuardDuty to monitor CloudWatch logs.

Answer: D

Explanation:
Amazon GuardDuty continuously analyzes CloudTrail events, VPC Flow Logs, and DNS logs to automatically detect unusual API activity and security-related behavior, providing managed, real- time threat detection without requiring custom rules or manual analysis.

NEW QUESTION # 193
A company hosts an encrypted Amazon S3 bucket in the ap-southeast-2 Region. Users from the eu- west-2 Region access the S3 bucket through the internet. The users from eu-west-2 need faster transfers to and from the S3 bucket for large files.
Which solution will meet these requirements?

A. Configure and activate S3 Transfer Acceleration on the S3 bucket. Use the new S3 acceleration endpoint's domain name for access.
B. Create an S3 access point in eu-west-2 to use as the destination for S3 replication from ap- southeast-2. Ensure all users switch to the new S3 access point.
C. Create a new S3 bucket in eu-west-2. Copy all contents from ap-southeast-2 to the new bucket in eu-west-2. Create an S3 access point, and associate it with both buckets. Ensure users use the new S3 access point.
D. Create an Amazon Route 53 hosted zone with a geolocation routing policy. Choose the Alias to S3 website endpoint option. Specify the S3 bucket that is in ap-southeast-2 as the source bucket.

Answer: A

Explanation:
For users in eu-west-2 transferring large files to/from an S3 bucket in ap-southeast-2 over the public internet, S3 Transfer Acceleration is designed to improve performance by leveraging the AWS global edge network. With Transfer Acceleration enabled, users access the bucket via the acceleration endpoint. Requests enter AWS at the nearest edge location and then traverse the AWS backbone network to the bucket's Region, which typically reduces latency variability and can improve throughput for long-distance transfers.

NEW QUESTION # 194
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. Create an Application Load Balancer (ALB). Attach the ALB to the Auto Scaling group. Create a scheduled scaling policy for 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 target tracking scaling policy for the ALBRequestCountPerTarget metric to modify the Auto Scaling group.
D. 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.

Answer: D

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 # 195
A company uses AWS CloudFormation stacks to manage its infrastructure. The company's developers commit infrastructure changes to the company's Git repository. The company wants to automate updates to the CloudFormation stacks when developers commit changes. The company requires change set generation before deployment and notification of pending changes for approval. The solution must also minimize infrastructure maintenance overhead.
Which solution will meet these requirements?

A. Create an AWS Lambda function that creates the CloudFormation change sets, runs the change sets, and waits for approval. Set up an Amazon EventBridge rule to invoke the Lambda function when developers commit code to the Git repository.
B. Create a pipeline in AWS CodePipeline with GitHub as the source provider. Configure a CloudFormation deploy action to create change sets. Use Amazon SNS to send approval notifications.
C. Use CloudFormation Git sync to automatically deploy changes when developers push commits to the repository. Configure Amazon EventBridge to trigger an Amazon SNS notification after each deployment is complete.
D. Use AWS Systems Manager Automation to scan the Git repository for changes. Create a change set and deploy the CloudFormation stack.

Answer: B

Explanation:
AWS CodePipeline is the correct managed CI/CD service for automating infrastructure deployments from a Git repository while preserving approval gates. A pipeline can use GitHub or another supported source provider, create CloudFormation change sets, and include a manual approval action before executing the change set. Notifications can be sent through Amazon SNS so approvers are informed before deployment proceeds. This meets all requirements: automated updates, change set generation, approval notification, and low infrastructure maintenance. CloudFormation Git sync can automate stack updates from a repository, but the option describes notification only after deployment, which does not satisfy the pending approval requirement. A Lambda-based workflow would require custom orchestration and approval handling. Systems Manager Automation is not the standard Git-driven CloudFormation deployment pipeline tool. Therefore, CodePipeline with CloudFormation change sets is best.

NEW QUESTION # 196
A company deploys an application on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer (ALB). The company wants to protect the application from SQL injection attacks.
Which solution will meet this requirement?

A. Deploy AWS Shield Advanced in front of the ALB. Enable SQL injection filtering.
B. Deploy AWS WAF in front of the ALB. Subscribe to an AWS Managed Rule for SQL injection filtering.
C. Deploy a vulnerability scanner on each EC2 instance. Continuously scan the application code.
D. Deploy AWS Shield Standard in front of the ALB. Enable SQL injection filtering.

Answer: B

Explanation:
The AWS Cloud Operations and Security documentation confirms that AWS WAF (Web Application Firewall) is designed to protect web applications from application-layer threats, including SQL injection, cross-site scripting (XSS), and other OWASP Top 10 vulnerabilities.
When integrated with an Application Load Balancer, AWS WAF inspects incoming traffic using rule groups. The AWS Managed Rules for SQL Injection Protection provide preconfigured, continuously updated filters that detect and block malicious SQL patterns.
AWS Shield (Standard or Advanced) defends against DDoS attacks, not application-layer SQL attacks, and vulnerability scanners (Option C) only detect, not prevent, exploitation.
Thus, Option D provides the correct, managed, and automated protection aligned with AWS best practices.
Reference: AWS Cloud Operations & Security Guide - Protecting Applications from SQL Injection with AWS WAF Managed Rules

NEW QUESTION # 197
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