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Amazon SOA-C03 Exam Syllabus Topics:

Topic	Details
Topic 1	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 2	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 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	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 5	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.

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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q140-Q145):

NEW QUESTION # 140
A school uses a web application to track student attendance. The application uses an Amazon API Gateway REST API and backend AWS Lambda functions. The application stores data in an Amazon DynamoDB table that is in on-demand capacity mode.
Teachers report slow application performance at the same time every weekday. A CloudOps engineer notices that the performance problems happen only when the application demand suddenly increases. The application can handle the peak load if the load increases gradually. The CloudOps engineer must modify the application to resolve the performance issue.
Which solution will meet this requirement?

A. Configure provisioned concurrency with scheduled auto scaling for the Lambda functions.
B. Change the DynamoDB table from on-demand capacity mode to provisioned capacity mode with auto scaling.
C. Change the DynamoDB table from on-demand capacity mode to provisioned capacity mode. Set the provisioned capacity to match peak usage.
D. Configure reserved concurrency with scheduled auto scaling for the Lambda functions.

Answer: C

Explanation:
DynamoDB on-demand mode can experience throttling when traffic suddenly increases beyond recent peak levels. For a predictable weekday spike, switching to provisioned capacity and setting the capacity to match expected peak usage ensures the table has enough read and write capacity available before the sudden demand occurs.

NEW QUESTION # 141
A CloudOps engineer needs to implement a backup strategy for Amazon EC2 resources and Amazon RDS resources. The backup strategy must meet the following retention requirements:
- Daily backups: must be kept for 6 days
- Weekly backups: must be kept for 4 weeks
- Monthly backups: must be kept for 11 months
- Yearly backups: must be kept for 7 years
Which backup strategy will meet these requirements with the LEAST administrative effort?

A. Use Amazon Data Lifecycle Manager to create an Amazon EBS snapshot policy. Create tags on each resource that needs to be backed up. Create multiple schedules according to the requirements within the policy. Set the appropriate frequency and retention period.
B. Use Amazon Data Lifecycle Manager to create an Amazon EBS snapshot policy. Create tags on each resource that needs to be backed up. Set up resource assignment by using the tags. Create multiple schedules according to the requirements within the policy. Set the appropriate frequency and retention period. In Amazon RDS, activate automated backups on the required DB instances.
C. Use AWS Backup to create a new backup plan for each retention requirement with a backup frequency of daily, weekly, monthly, or yearly. Set the retention period to match the requirement.
Create tags on each resource that needs to be backed up. Set up resource assignment by using the tags.
D. Create an AWS Lambda function. Program the Lambda function to use native tooling to take backups of file systems in Amazon EC2 and to make copies of databases in Amazon RDS.
Create an Amazon EventBridge rule to invoke the Lambda function.

Answer: C

Explanation:
AWS Backup provides centralized backup management for both Amazon EC2 and Amazon RDS resources. Separate backup plans can implement the required daily, weekly, monthly, and yearly schedules with matching retention periods, while tag-based resource assignments automatically include the appropriate resources. This provides the required retention strategy with the least administrative effort.

NEW QUESTION # 142
A company runs a business application on more than 300 Linux-based instances. Each instance has the AWS Systems Manager Agent (SSM Agent) installed. The company expects the number of instances to grow in the future. All business application instances have the same user-defined tag.
A CloudOps engineer wants to run a command on all the business application instances to download and install a package from a private repository. To avoid overwhelming the repository, the CloudOps engineer wants to ensure that no more than 30 downloads occur at one time.
Which solution will meet this requirement in the MOST operationally efficient way?

A. Use an AWS Lambda function to automatically run a Systems Manager Run Command document that roads a list of instance IDs that have the user-defined tag. Set reserved concurrency for the Lambda function to 30.
B. Use a secondary tag to create 10 batches of 30 instances each. Use a Systems Manager Run Command document to download and install the package. Specify the target as part of the Run Command document by using the secondary tag. Run each batch one time.
C. Use a parallel workflow state in AWS Step Functions to automatically run a Systems Manager Run Command document that reads a list of instance IDs that have the user-defined tag. Set the number of parallel states to 30. Run the Step Functions workflow 10 times.
D. Use a Systems Manager Run Command document to download and install the package. Use rate control to set concurrency to 30. Specify the target by using the user-defined tag as part of the Run Command document.

Answer: D

Explanation:
AWS Systems Manager Run Command supports rate control, where you can set max concurrency (e.g., 30) and target instances by tag. This lets you run the command on all tagged instances while automatically limiting concurrent executions to 30, avoiding repository overload and scaling cleanly as the number of instances grows, without extra scripting or manual batching.

NEW QUESTION # 143
A company runs a web application on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer (ALB).
A CloudOps engineer must implement deployments without any service interruptions. The company needs the ability to shift traffic between application versions and quickly revert to the previous version by redirecting traffic if issues occur.
Which deployment approach will meet these requirements?

A. Implement an in-place rolling update by using Auto Scaling instance refresh on the existing target group. Configure connection draining for each instance. Update the launch template. Rely on health checks during the replacement process.
B. Create a new AMI by using the updated application. Modify the Auto Scaling launch template.
Temporarily increase desired capacity to add new instances. Then terminate old instances while using ALB connection draining to manage the transition.
C. Design an AWS Step Functions workflow that creates a parallel Auto Scaling group and updates monitoring configurations. Configure the workflow to change instance registrations on the ALB and automatically terminate the previous fleet after a verification period.
D. Use AWS CodeDeploy blue/green deployment with two ALB target groups. Deploy the new version to a separate fleet. Shift traffic gradually to the new target group. Maintain the original fleet for immediate rollback if necessary.

Answer: D

Explanation:
AWS CodeDeploy blue/green deployment with separate ALB target groups supports deploying the new application version to a separate fleet while the original fleet continues serving traffic.
Traffic can be shifted gradually to the new version, and rollback can be performed quickly by redirecting traffic back to the original target group.

NEW QUESTION # 144
A company has an application that uses an Amazon EFS file system. A recent incident that involved an application logic error corrupted several files. The company wants to improve its ability to back up and recover the EFS file system. The company must be able to recover individual files rapidly. Which solution meets these requirements MOST cost-effectively?

A. Configure Amazon Data Lifecycle Manager (Amazon DLM) to archive a copy of the data to an Amazon S3 Glacier vault. Use S3 Glacier retrieval requests to retrieve individual files.
B. Create a second EFS file system in another AWS Region. Configure AWS DataSync to copy the data to the backup file system. Recover files by copying them from the backup EFS file system.
C. Enable AWS Backup in Amazon EFS to back up the file system to a backup vault. Use a partial restore job to retrieve individual files.
D. Enable AWS Backup in Amazon EFS to back up the file system to an Amazon S3 Glacier vault.
Use S3 Glacier retrieval requests to retrieve individual files.

Answer: C

Explanation:
AWS Backup is the managed service for backing up and restoring Amazon EFS file systems. It supports backup vaults and restore workflows without requiring a second live EFS file system.
This is more cost-effective than maintaining a duplicate EFS file system in another Region. AWS documentation explains that AWS Backup performs incremental backups of EFS file systems, reducing duplicate backup storage and improving cost efficiency. For file-level recovery, a partial restore job can restore selected files or directories rather than restoring the entire file system.
Amazon DLM is primarily used for EBS snapshots, not EFS file-level backup management. S3 Glacier retrieval is not the best fit for rapid individual file recovery because retrieval latency and restore workflow are unsuitable for quick operational recovery. Therefore, AWS Backup with partial restore is the right answer.

NEW QUESTION # 145
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