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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q210-Q215):
NEW QUESTION # 210
A financial services company stores customer images in an Amazon S3 bucket in the us-east-1 Region. To comply with regulations, the company must ensure that all existing objects are replicated to an S3 bucket in a second AWS Region. If an object replication fails, the company must be able to retry replication for the object.
What solution will meet these requirements?
- A. Use S3 Lifecycle rules to move objects to the destination bucket in a second Region.
- B. Configure Amazon S3 Cross-Region Replication (CRR). Use S3 Replication Time Control (S3 RTC) to replicate existing objects.
- C. Configure Amazon S3 Cross-Region Replication (CRR). Use Amazon S3 live replication to replicate existing objects.
- D. Configure Amazon S3 Cross-Region Replication (CRR). Use S3 Batch Replication to replicate existing objects.
Answer: D
Explanation:
Per the AWS Cloud Operations and S3 Data Management documentation, Cross-Region Replication (CRR) automatically replicates new objects between S3 buckets across Regions. However, CRR alone does not retroactively replicate existing objects created before replication configuration. To include such objects, AWS introduced S3 Batch Replication.
S3 Batch Replication scans the source bucket and replicates all existing objects that were not copied previously. Additionally, it can retry failed replication tasks automatically, ensuring regulatory compliance for complete dataset replication.
S3 Replication Time Control (S3 RTC) guarantees predictable replication times for new objects only-it does not cover previously stored data. S3 Lifecycle rules (Option D) move or transition objects between storage classes or buckets, but not in a replication context.
Therefore, the correct solution is to use S3 Cross-Region Replication (CRR) combined with S3 Batch Replication to ensure all current and future data is synchronized across Regions with retry capability.
NEW QUESTION # 211
A CloudOps engineer creates an AWS CloudFormation template to define an application stack that can be deployed in multiple AWS Regions. The CloudOps engineer also creates an Amazon CloudWatch dashboard by using the AWS Management Console. Each deployment of the application requires its own CloudWatch dashboard.
How can the CloudOps engineer automate the creation of the CloudWatch dashboard each time the application is deployed?
- A. Export the existing CloudWatch dashboard as JSON. Update the CloudFormation template to define an AWS::CloudWatch::Dashboard resource. Include the exported JSON in the resource's DashboardBody property.
- B. Create a script by using the AWS CLI to run the aws cloudformation put-dashboard command with the name of the dashboard. Run the command each time a new CloudFormation stack is created.
- C. Update the CloudFormation template to define an AWS::CloudWatch::Dashboard resource. Use the intrinsic Ref function to reference the ID of the existing CloudWatch dashboard.
- D. Update the CloudFormation template to define an AWS::CloudWatch::Dashboard resource. Specify the name of the existing dashboard in the DashboardName property.
Answer: A
Explanation:
According to CloudOps automation and monitoring best practices, CloudWatch dashboards should be provisioned as infrastructure-as-code (IaC) resources using AWS CloudFormation to ensure consistency, repeatability, and version control. AWS CloudFormation supports the AWS::CloudWatch::Dashboard resource, where the DashboardBody property accepts a JSON object describing widgets, metrics, and layout.
By exporting the existing dashboard configuration as JSON and embedding it into the CloudFormation template, every deployment of the application automatically creates its corresponding dashboard. This method aligns with the CloudOps requirement for automated deployment and operational visibility within the same stack lifecycle.
AWS documentation explicitly states:
"Use the AWS::CloudWatch::Dashboard resource to create a dashboard from your template. You can include the same JSON you use to define a dashboard in the console." Option A requires manual execution. Options C and D incorrectly reference or reuse existing dashboards, failing to produce unique, deployment-specific dashboards.
References:* AWS Certified CloudOps Engineer - Associate (SOA-C03) Exam Guide - Domain 1:
Monitoring and Logging* AWS CloudFormation User Guide - Resource Type: AWS::CloudWatch::
Dashboard* AWS Well-Architected Framework - Operational Excellence Pillar* Amazon CloudWatch - Automating Dashboards with Infrastructure as Code
NEW QUESTION # 212
A company needs to upload gigabytes of files daily to Amazon S3 and requires higher throughput and faster upload speeds.
Which action should a CloudOps engineer take?
- A. Create an Amazon CloudFront distribution with the GET HTTP method allowed and the S3 bucket as an origin.
- B. Set up AWS Global Accelerator and configure it with the S3 bucket.
- C. Create an Amazon ElastiCache cluster and enable caching for the S3 bucket.
- D. Enable S3 Transfer Acceleration and use the acceleration endpoint when uploading files.
Answer: D
Explanation:
The AWS Cloud Operations and Storage documentation confirms that S3 Transfer Acceleration is designed to increase upload speed for objects transferred to S3 buckets over long distances.
It uses AWS Global Edge Network and Amazon CloudFront edge locations to route data through optimized network paths, reducing latency and achieving higher throughput compared to standard S3 uploads.
After enabling Transfer Acceleration on the bucket, users upload files to the accelerated endpoint (e.g., bucketname.s3-accelerate.amazonaws.com). This feature requires no changes to application logic besides endpoint modification and provides immediate performance improvement.
CloudFront (Option A) is for content delivery, not uploads. ElastiCache (Option B) and Global Accelerator (Option C) are unrelated to S3 upload performance.
Thus, Option D is correct - enable S3 Transfer Acceleration for faster, optimized file uploads.
NEW QUESTION # 213
A company has an internal web application that runs on Amazon EC2 instances behind an Application Load Balancer. The instances run in an Amazon EC2 Auto Scaling group in a single Availability Zone. A CloudOps engineer must make the application highly available.
Which action should the CloudOps engineer take to meet this requirement?
- A. Update the Auto Scaling group to launch new instances in an Availability Zone in a second AWS Region.
- B. Update the Auto Scaling group to launch new instances in a second Availability Zone in the same AWS Region.
- C. Increase the minimum number of instances in the Auto Scaling group to meet the capacity that is required at peak usage.
- D. Increase the maximum number of instances in the Auto Scaling group to meet the capacity that is required at peak usage.
Answer: B
Explanation:
High availability for an EC2-based web application behind an ALB is primarily achieved by eliminating single points of failure at the infrastructure layer. A single Availability Zone (AZ) deployment is vulnerable to AZ-level impairment (power/network issues, facility events, or service disruptions). The most direct and standard AWS approach is to distribute the Auto Scaling group across multiple AZs within the same Region.
Updating the Auto Scaling group to use subnets in at least two AZs allows instances to be launched across AZs automatically. The ALB is built to route traffic across targets in multiple AZs, and Auto Scaling can replace unhealthy instances in any enabled AZ. This provides resilience without the complexity of multi- Region architectures.
Options A and B address capacity for peak load but do not address the core availability requirement. Even with more instances, a full AZ outage would still take the entire application down if all instances are in the same AZ.
Option D (multi-Region) can improve resilience further, but it introduces significantly more operational overhead: cross-Region traffic routing, data replication, DNS failover strategy, application state handling, and potentially active-active or active-passive designs. For "make the application highly available" from a single- AZ baseline, multi-AZ in the same Region is the standard, least-overhead improvement.
NEW QUESTION # 214
A finance company stores confidential data in an Amazon S3 bucket. The company uses Amazon QuickSight to analyze the data and create dashboard reports. The company requires that all data access and connections to QuickSight remain within the company's VPC network boundary.
Which solution will meet these requirements?
- A. Set up a VPC endpoint for QuickSight. Use an Amazon EC2 instance as a proxy to establish a direct connection between the VPC and QuickSight. Create a manifest file that points to the S3 data. Store the manifest on the EC2 instance. Grant QuickSight permission to access the EC2 instance.
- B. Configure an Amazon S3 VPC gateway endpoint. Route all data from QuickSight through the endpoint to transfer data. Grant QuickSight permission to access the S3 bucket.
- C. Create an interface VPC endpoint for QuickSight. Configure the endpoint to connect to QuickSight within the VPC by using AWS PrivateLink. Create a manifest file that points to the S3 data. Grant QuickSight permission to access the S3 bucket.
- D. Configure a NAT gateway in the company's VPC. Route all data from QuickSight through the NAT gateway to transfer data. Grant QuickSight permission to access the S3 bucket.
Answer: C
Explanation:
To keep all QuickSight traffic and data access within the VPC boundary, you must use an interface VPC endpoint for QuickSight via AWS PrivateLink. This provides a private connection from your VPC to the QuickSight service without traversing the public internet. Then QuickSight can read data from S3 (referenced via a manifest file) while staying within the VPC path, as long as the proper S3 permissions are granted.
NEW QUESTION # 215
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