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| Topic | Details |
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| Topic 1 | - 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.
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| 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.
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| Topic 3 | - 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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| 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.
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| Topic 5 | - 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.
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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q197-Q202):
NEW QUESTION # 197
A CloudOps engineer has an Amazon ECS service that runs a transaction processing application.
The CloudOps engineer needs to deploy a new feature on the ECS service. The feature cannot have downtime during deployment. The feature must also have the ability to run an immediate one-step rollback if a performance-degrading bug is detected. Which solution will meet these requirements?
- A. Set the ECS service's desired count to double the current size. Manually terminate the old tasks after the new tasks are registered.
- B. Configure a canary deployment by using an AWS CodeDeploy linear traffic shift with a 10% increment over 10 minutes.
- C. Configure the ECS service with a minimum healthy percentage of 100%. Use the default rolling update deployment type.
- D. Implement a blue/green deployment by using AWS CodeDeploy.
Answer: D
Explanation:
Blue/green deployment with AWS CodeDeploy is the correct strategy for Amazon ECS when zero downtime and fast rollback are required. In a blue/green deployment, the current production task set remains active while a new task set is created and validated. Traffic can then be shifted safely to the new version. If the new version causes performance degradation, CodeDeploy can roll back by redirecting traffic to the previous task set. AWS ECS documentation describes blue/green deployment as a method that reduces downtime and risk by running two production environments and validating revisions before routing production traffic. Rolling updates do not provide the same immediate one-step rollback. Canary or linear traffic shifting gradually moves traffic but does not match the requirement for immediate rollback as directly as blue/green.
Manual scaling is operationally weak.
NEW QUESTION # 198
A company stores critical files in an Amazon S3 bucket in the us-east-1 AWS Region. To comply with disaster recovery requirements, all new objects in the bucket must automatically replicate to a bucket in the us-west-2 Region. Which solution will meet this requirement with the LEAST operational overhead?
- A. Enable Cross-Origin Resource Sharing (CORS) on both the us-east-1 bucket and the us-west-2 bucket.
- B. Enable Cross-Region Replication (CRR) on the source bucket. Specify the destination bucket in the us-west-2 Region. Enable versioning on the source bucket.
- C. Enable S3 Lifecycle policies to transition objects to a different storage class in the us-west-2 Region.
- D. Create an AWS Lambda function that copies the object to the destination bucket. Configure an Amazon EventBridge rule to run the Lambda function for each object that is created.
Answer: B
Explanation:
Amazon S3 Cross-Region Replication automatically replicates new objects from a source bucket to a destination bucket in another AWS Region. Versioning must be enabled on the source and destination buckets for replication to work, making CRR the lowest-overhead managed solution for this disaster recovery requirement.
NEW QUESTION # 199
A CloudOps engineer is troubleshooting an AWS CloudFormation template whereby multiple Amazon EC2 instances are being created. The template is working in us-east-1, but it is failing in us-west-2 with the error code:
AMI [ami-12345678] does not exist
How should the CloudOps engineer ensure that the AWS CloudFormation template is working in every Region?
- A. Modify the AWS CloudFormation template by including the AMI IDs in the Mappings section.Refer to the proper mapping within the template for the proper AMI ID.
- B. Copy the source Region's Amazon Machine Image (AMI) to the destination Region and assign it the same ID.
- C. Edit the AWS CloudFormation template to specify the Region code as part of the fully qualified AMI ID.
- D. Edit the AWS CloudFormation template to offer a drop-down list of all AMIs to the user by using the AWS::EC2::AMI::ImageId control.
Answer: A
Explanation:
AMI IDs are Region-specific. An AMI ID that exists in us-east-1 does not automatically exist in us- west-2, and even copied AMIs receive different AMI IDs in the destination Region. The correct CloudFormation pattern is to define Region-specific AMI IDs in the Mappings section and use Fn::FindInMap with AWS::Region to select the correct AMI for the deployment Region.
NEW QUESTION # 200
A web application runs on Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer (ALB). During rolling updates, application initialization and cold starts cause 30-second latency spikes. A CloudOps engineer needs to keep latency flat by pre-initializing capacity. The CloudOps engineer must reuse instances across waves without extending the maintenance window.
Which solution will meet these requirements?
- A. Enable predictive scaling with a 7-day forecast on the Auto Scaling group. Overlay a CPU target- tracking policy with a 300-second instance warmup. Add scheduled actions for the rollout window.Maintain zero-surge instance refresh with standard ALB health checks.
- B. Configure an Auto Scaling group warm pool with stopped instances that are pre-initialized through user data. Enable instance reuse. Set a target tracking policy with an instance warmup value. Run instance refresh in batches so the replacements pull from the warm pool.
- C. Double the health-check grace period. Disable connection draining. Use step scaling to absorb spikes during each wave. Move to more and smaller instances.
- D. Place a Network Load Balancer in front of the ALB to absorb burst connections. Keep the Auto Scaling group maximum unchanged. Configure zero-surge rolling replacements. Disable instance reuse.
Answer: B
Explanation:
An Auto Scaling warm pool keeps pre-initialized instances ready before they are placed into service. This is exactly what the scenario needs because cold starts during rolling updates are causing latency spikes. By using stopped instances that have already completed initialization, replacement capacity can join the Auto Scaling group faster and with less runtime warmup impact. Instance reuse also allows instances to return to the warm pool after scale-in or refresh waves, reducing repeated initialization overhead. Target tracking with instance warmup prevents scaling decisions from being distorted while new instances stabilize. Options B, C, and D do not directly pre-initialize application capacity. Predictive scaling forecasts demand, but it does not solve cold-start latency during controlled deployment waves. Warm pools are the purpose-built CloudOps feature for this requirement.
NEW QUESTION # 201
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 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.
- B. 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. - 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: A
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.
References:* AWS Certified CloudOps Engineer - Associate (SOA-C03) Exam Guide - Monitoring & Logging* Amazon CloudWatch Logs - Data Protection (masking/redaction with data identifiers)* CloudWatch Logs - Permissions for masking and unmasking sensitive data* AWS Well-Architected Framework - Security and Operational Excellence (sensitive data handling)
NEW QUESTION # 202
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