SAP-C02 Exam Dumps - AWS Certified Solutions Architect - Professional

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Question # 73

A company uses an AWS CloudFormation template to deploy an Amazon ECS service into a production environment. The template includes an Amazon S3 bucket that is named by using a common prefix with the CloudFormation stack name.

The company uses the same template to create temporary environments for development and continuous integration. Developers can create environments successfully, but they receive errors from CloudFormation when they attempt to delete the environments. The developers often need to delete and recreate stacks with the same names as part of the development and testing process.

Which combination of steps should a solutions architect take to modify the solution to resolve this issue? (Select TWO.)

Associate an AWS Lambda function with a CloudFormation custom resource to delete all keys that are present in a given S3 bucket. Implement this custom resource as part of the application ' s CloudFormation template.

Modify the S3 bucket resource in the CloudFormation template by specifying Delete for the DeletionPolicy attribute. Specify the CAPABILITY_DELETE_NONEMPTY capability to process CloudFormation delete operations.

Modify the S3 bucket resource in the CloudFormation template by specifying Retain for the DeletionPolicy attribute. Configure an AWS Config custom rule to run every 24 hours to identify, empty, and delete buckets that are no longer owned by a CloudFormation stack.

Ensure that CloudFormation operations are being invoked by a role that has s3:DeleteObject permissions on all objects in the bucket.

Modify the S3 bucket resource in the CloudFormation template to configure a bucket policy that grants s3:DeleteObject permissions on all objects in the bucket.

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Answer:

Explanation:

CloudFormation cannot delete an S3 bucket that contains objects. When the developers attempt to delete temporary stacks, the delete operation fails if the associated S3 bucket still has objects. Because the bucket name is derived from the stack name, failed deletions can also prevent re-creation of stacks with the same names until the bucket is manually emptied and deleted. This causes friction for development and continuous integration workflows.

To resolve this, the solution must ensure that, during stack deletion, all objects are removed from the S3 bucket so that CloudFormation can delete the bucket successfully. CloudFormation does not natively support automatic deletion of bucket contents. However, CloudFormation custom resources can be used to perform custom actions during stack lifecycle events.

Option A proposes associating a Lambda function with a CloudFormation custom resource. The custom resource can be invoked during stack deletion to list and delete all objects (and object versions if versioning is enabled) in the specified bucket. Once the bucket is emptied by the Lambda function, the standard CloudFormation deletion process can successfully delete the bucket resource.

In addition to emptying the bucket, the IAM role used by CloudFormation must have permissions to delete objects in the bucket. If CloudFormation uses an execution role that lacks s3:DeleteObject (and potentially s3:ListBucket) permissions, the bucket-cleanup Lambda function or CloudFormation itself would not be able to remove objects. Option D ensures that CloudFormation operations are invoked by a role that has s3:DeleteObject permissions on bucket objects, enabling the custom resource to perform the deletions.

Option B is incorrect because, although DeletionPolicy can be set to Delete, there is no such capability as CAPABILITY_DELETE_NONEMPTY in CloudFormation, and DeletionPolicy alone does not override the S3 service requirement that buckets must be empty before deletion.

Option Câ€™s Retain DeletionPolicy leaves the bucket behind when the stack is deleted. While an external AWS Config rule could clean up stale buckets, it complicates the design and does not directly solve the problem of re-creating stacks with the same bucket name in a predictable, immediate way.

Option E configures a bucket policy to grant s3:DeleteObject permissions, but this is not sufficient alone. CloudFormation still must assume a role with the appropriate permissions. Bucket policy and IAM role permissions must both be considered, but the key action to resolve the deletion failure is to explicitly empty the bucket through a custom resource, as in option A, and ensure the execution role has delete permissions, as in option D.

Therefore, implementing a Lambda-backed custom resource to empty the S3 bucket during stack deletion (option A) and ensuring the CloudFormation execution role has s3:DeleteObject permissions (option D) resolves the deletion errors and allows developers to delete and recreate stacks freely.

[References:AWS documentation on CloudFormation behavior with S3 bucket deletion and the requirement that buckets must be empty before deletion.AWS documentation on CloudFormation custom resources and Lambda-backed custom resources for performing custom actions during stack operations., , ]

Question # 74

A company wants to containerize a multi-tier web application and move the application from an on-premises data center to AWS. The application includes web. application, and database tiers. The company needs to make the application fault tolerant and scalable. Some frequently accessed data must always be available across application servers. Frontend web servers need session persistence and must scale to meet increases in traffic.

Which solution will meet these requirements with the LEAST ongoing operational overhead?

Run the application on Amazon Elastic Container Service (Amazon ECS) on AWS Fargate. Use Amazon Elastic File System (Amazon EFS) for data that is frequently accessed between the web and application tiers. Store the frontend web server session data in Amazon Simple Queue Service (Amazon SOS).

Run the application on Amazon Elastic Container Service (Amazon ECS) on Amazon EC2. Use Amazon ElastiCache for Redis to cache frontend web server session data. Use Amazon Elastic Block Store (Amazon EBS) with Multi-Attach on EC2 instances that are distributed across multiple Availability Zones.

Run the application on Amazon Elastic Kubernetes Service (Amazon EKS). Configure Amazon EKS to use managed node groups. Use ReplicaSets to run the web servers and applications. Create an Amazon Elastic File System (Amazon EFS) Me system. Mount the EFS file system across all EKS pods to store frontend web server session data.

Deploy the application on Amazon Elastic Kubernetes Service (Amazon EKS) Configure Amazon EKS to use managed node groups. Run the web servers and application as Kubernetes deployments in the EKS cluster. Store the frontend web server session data in an Amazon DynamoDB table. Create an Amazon Elastic File System (Amazon EFS) volume that all applications will mount at the time of deployment.

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Question # 75

A company runs AWS workloads that are integrated with software as a service (SaaS) applications. The company needs to analyze the SaaS applications to identify unused licenses. Which solution will meet this requirement with the LEAST operational overhead?

Use AWS License Manager automated discovery to retrieve audit logs from the SaaS applications. Use Amazon Athena to analyze the data and to identify unused SaaS licenses.

Create an AWS Lambda function to retrieve audit logs from the SaaS applications and to store the data in Amazon S3. Use Amazon EMR to analyze the data and to identify unused SaaS licenses.

Use AWS AppFabric to ingest audit logs from the SaaS applications into Amazon S3. Use Amazon Athena to analyze the data and to identify unused SaaS licenses.

Use AWS App Runner to ingest audit logs from the SaaS applications into Amazon S3. Use Amazon EMR to analyze the data and to identify unused SaaS licenses.

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Question # 76

A company is hosting a monolithic REST-based API for a mobile app on five Amazon EC2 instances in public subnets of a VPC. Mobile clients connect to the API by using a domain name that is hosted on Amazon Route 53. The company has created a Route 53 multivalue answer routing policy with the IP addresses of all the EC2 instances. Recently, the app has been overwhelmed by large and sudden increases to traffic. The app has not been able to keep up with the traffic.

A solutions architect needs to implement a solution so that the app can handle the new and varying load.

Which solution will meet these requirements with the LEAST operational overhead?

Separate the API into individual AWS Lambda functions. Configure an Amazon API Gateway REST API with Lambda integration for the backend. Update the Route 53 record to point to the API Gateway API.

Containerize the API logic. Create an Amazon Elastic Kubernetes Service (Amazon EKS) cluster. Run the containers in the cluster by using Amazon EC2. Create a Kubernetes ingress. Update the Route 53 record to point to the Kubernetes ingress.

Create an Auto Scaling group. Place all the EC2 instances in the Auto Scaling group. Configure the Auto Scaling group to perform scaling actions that are based on CPU utilization. Create an AWS Lambda function that reacts to Auto Scaling group changes and updates the Route 53 record.

Create an Application Load Balancer (ALB) in front of the API. Move the EC2 instances to private subnets in the VPC. Add the EC2 instances as targets for the ALB. Update the Route 53 record to point to the ALB.

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Question # 77

A solutions architect needs to advise a company on how to migrate its on-premises data processing application to the AWS Cloud. Currently, users upload input files through a web portal. The web server then stores the uploaded files on NAS and messages the processing server over a message queue. Each media file can take up to 1 hour to process. The company has determined that the number of media files awaiting processing is significantly higher during business hours, with the number of files rapidly declining after business hours.

What is the MOST cost-effective migration recommendation?

Create a queue using Amazon SQS. Configure the existing web server to publish to the new queue. When there are messages in the queue, invoke an AWS Lambda function to pull requests from the queue and process the files. Store the processed files in an Amazon S3 bucket.

Create a queue using Amazon M. Configure the existing web server to publish to the new queue. When there are messages in the queue, create a new Amazon EC2 instance to pull requests from the queue and process the files. Store the processed files in Amazon EFS. Shut down the EC2 instance after the task is complete.

Create a queue using Amazon MO. Configure the existing web server to publish to the new queue. When there are messages in the queue, invoke an AWS Lambda function to pull requests from the queue and process the files. Store the processed files in Amazon EFS.

Create a queue using Amazon SOS. Configure the existing web server to publish to the new queue. Use Amazon EC2 instances in an EC2 Auto Scaling group to pull requests from the queue and process the files. Scale the EC2 instances based on the SOS queue length. Store the processed files in an Amazon S3 bucket.

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Question # 78

A company is running a critical stateful web application on two Linux Amazon EC2 instances behind an Application Load Balancer (ALB) with an Amazon RDS for MySQL database The company hosts the DNS records for the application in Amazon Route 53 A solutions architect must recommend a solution to improve the resiliency of the application

The solution must meet the following objectives:

â€¢ Application tier RPO of 2 minutes. RTO of 30 minutes

â€¢ Database tier RPO of 5 minutes RTO of 30 minutes

The company does not want to make significant changes to the existing application architecture The company must ensure optimal latency after a failover

Which solution will meet these requirements?

Configure the EC2 instances to use AWS Elastic Disaster Recovery Create a cross-Region read replica for the RDS DB instance Create an ALB in a second AWS Region Create an AWS Global Accelerator endpoint and associate the endpoint with the ALBs Update DNS records to point to the Global Accelerator endpoint

Configure the EC2 instances to use Amazon Data Lifecycle Manager (Amazon DLM) to take snapshots of the EBS volumes Configure RDS automated backups Configure backup replication to a second AWS Region Create an ALB in the second Region Create an AWS Global Accelerator endpoint, and associate the endpoint with the ALBs Update DNS records to point to the Global Accelerator endpoint

Create a backup plan in AWS Backup for the EC2 instances and RDS DB instance Configure backup replication to a second AWS Region Create an ALB in the second Region Configure an Amazon CloudFront distribution in front of the ALB Update DNS records to point to CloudFront

Configure the EC2 instances to use Amazon Data Lifecycle Manager (Amazon DLM) to take snapshots of the EBS volumes Create a cross-Region read replica for the RDS DB instance Create an ALB in a second AWS Region Create an AWS Global Accelerator endpoint and associate the endpoint with the ALBs

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Question # 79

A company has an asynchronous HTTP application that is hosted as an AWS Lambda function. A public Amazon API Gateway endpoint invokes the Lambda function. The Lambda function and the API Gateway endpoint reside in the us-east-1 Region. A solutions architect needs to redesign the application to support failover to another AWS Region.

Which solution will meet these requirements?

Create an API Gateway endpoint in the us-west-2 Region to direct traffic to the Lambda function in us-east-1. Configure Amazon Route 53 to use a failover routing policy to route traffic for the two API Gateway endpoints.

Create an Amazon Simple Queue Service (Amazon SQS) queue. Configure API Gateway to direct traffic to the SQS queue instead of to the Lambda function. Configure the Lambda function to pull messages from the queue for processing.

Deploy the Lambda function to the us-west-2 Region. Create an API Gateway endpoint in us-west-2 to direct traffic to the Lambda function in us-west-2. Configure AWS Global Accelerator and an Application Load Balancer to manage traffic across the two API Gateway endpoints.

Deploy the Lambda function and an API Gateway endpoint to the us-west-2 Region. Configure Amazon Route 53 to use a failover routing policy to route traffic for the two API Gateway endpoints.

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Question # 80

A company is hosting an application on AWS for a project that will run for the next 3 years. The application consists of 20 Amazon EC2 On-Demand Instances that are registered in a target group for a Network Load Balancer (NLB). The instances are spread across two Availability Zones. The application is stateless and runs 24 hours a day, 7 days a week.

The company receives reports from users who are experiencing slow responses from the application. Performance metrics show that the instances are at 10% CPU utilization during normal application use. However, the CPU utilization increases to 100% at busy times, which typically last for a few hours.

The company needs a new architecture to resolve the problem of slow responses from the application.

Which solution will meet these requirements MOST cost-effectively?

Create an Auto Scaling group. Attach the Auto Scaling group to the target group of the NLB. Set the minimum capacity to 20 and the desired capacity to 28. Purchase Reserved Instances for 20 instances.

Create a Spot Fleet that has a request type of request. Set the TotalTargetCapacity parameter to 20. Set the DefaultTargetCapacityType parameter to On-Demand. Specify the NLB when creating the Spot Fleet.

Create a Spot Fleet that has a request type of maintain. Set the TotalTargetCapacity parameter to 20. Set the DefaultTargetCapacityType parameter to Spot. Replace the NLB with an Application Load Balancer.

Create an Auto Scaling group. Attach the Auto Scaling group to the target group of the NLB. Set the minimum capacity to 4 and the maximum capacity to 28. Purchase Reserved Instances for four instances.

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