- (Exam Topic 2)
A company is developing a new on-demand video application that is based on microservices. The application will have 5 million users at launch and will have 30 million users after 6 months. The company has deployed the application on Amazon Elastic Container Service (Amazon ECS) on AWS Fargate. The company developed the application by using ECS services that use the HTTPS protocol.
A solutions architect needs to implement updates to the application by using blue/green deployments. The solution must distribute traffic to each ECS service through a load balancer. The application must automatically adjust the number of tasks in response to an Amazon CloudWatch alarm.
Which solution will meet these requirements?

1. A. Configure the ECS services to use the blue/green deployment type and a Network Load Balancer.Request increases to the service quota for tasks per service to meet the demand.
2. B. Configure the ECS services to use the blue/green deployment type and a Network Load Balancer.Implement an Auto Scaling group for each ECS service by using the Cluster Autoscaler.
3. C. Configure the ECS services to use the blue/green deployment type and an Application Load Balancer.Implement an Auto Seating group for each ECS service by using the Cluster Autoscaler.
4. D. Configure the ECS services to use the blue/green deployment type and an Application Load Balancer.Implement Service Auto Scaling for each ECS service.

Correct Answer: D
https://repost.aws/knowledge-center/ecs-fargate-service-auto-scaling

- (Exam Topic 1)
A company has developed a web application. The company is hosting the application on a group of Amazon EC2 instances behind an Application Load Balancer. The company wants to improve the security posture of the application and plans to use AWS WAF web ACLs. The solution must not adversely affect legitimate traffic to the application.
How should a solutions architect configure the web ACLs to meet these requirements?

1. A. Set the action of the web ACL rules to Coun
2. B. Enable AWS WAF logging Analyze the requests for false positives Modify the rules to avoid any false positive Over time change the action of the web ACL rules from Count to Block.
3. C. Use only rate-based rules in the web ACL
4. D. and set the throttle limit as high as possible Temporarily block all requests that exceed the limi
5. E. Define nested rules to narrow the scope of the rate tracking.
6. F. Set the action o' the web ACL rules to Bloc
7. G. Use only AWS managed rule groups in the web ACLs Evaluate the rule groups by using Amazon CloudWatch metrics with AWS WAF sampled requests or AWS WAF logs.
8. H. Use only custom rule groups in the web ACL
9. I. and set the action to Allow Enable AWS WAF logging Analyze the requests tor false positives Modify the rules to avoid any false positive Over time, change the action of the web ACL rules from Allow to Block.

Correct Answer: A
https://aws.amazon.com/premiumsupport/knowledge-center/waf-analyze-count-action-rules/

- (Exam Topic 1)
A company is planning to migrate 1,000 on-premises servers to AWS. The servers run on several VMware clusters in the company’s data center. As part of the migration plan, the company wants to gather server metrics such as CPU details, RAM usage, operating system information, and running processes. The company then wants to query and analyze the data.
Which solution will meet these requirements?

1. A. Deploy and configure the AWS Agentless Discovery Connector virtual appliance on the on-premises host
2. B. Configure Data Exploration in AWS Migration Hu
3. C. Use AWS Glue to perform an ETL job against the dat
4. D. Query the data by using Amazon S3 Select.
5. E. Export only the VM performance information from the on-premises host
6. F. Directly import the required data into AWS Migration Hu
7. G. Update any missing information in Migration Hu
8. H. Query the data by using Amazon QuickSight.
9. I. Create a script to automatically gather the server information from the on-premises host
10. J. Use the AWS CLI to run the put-resource-attributes command to store the detailed server data in AWS Migration Hu
11. K. Query the data directly in the Migration Hub console.
12. L. Deploy the AWS Application Discovery Agent to each on-premises serve
13. M. Configure Data Exploration in AWS Migration Hu
14. N. Use Amazon Athena to run predefined queries against the data in Amazon S3.

Correct Answer: D
it covers all the requirements mentioned in the question, it will allow collecting the detailed metrics, including process information and it provides a way to query and analyze the data using Amazon Athena.

- (Exam Topic 1)
A company has migrated its forms-processing application to AWS. When users interact with the application, they upload scanned forms as files through a web application. A database stores user metadata and references to files that are stored in Amazon S3. The web application runs on Amazon EC2 instances and an Amazon RDS for PostgreSQL database.
When forms are uploaded, the application sends notifications to a team through Amazon Simple Notification Service (Amazon SNS). A team member then logs in and processes each form. The team member performs data validation on the form and extracts relevant data before entering the information into another system that uses an API.
A solutions architect needs to automate the manual processing of the forms. The solution must provide accurate form extraction, minimize time to market, and minimize long-term operational overhead.
Which solution will meet these requirements?

1. A. Develop custom libraries to perform optical character recognition (OCR) on the form
2. B. Deploy the libraries to an Amazon Elastic Kubernetes Service (Amazon EKS) cluster as an application tie
3. C. Use this tier to process the forms when forms are uploade
4. D. Store the output in Amazon S3. Parse this output by extracting the data into an Amazon DynamoDB tabl
5. E. Submit the data to the target system's AP
6. F. Host the new application tier on EC2 instances.
7. G. Extend the system with an application tier that uses AWS Step Functions and AWS Lambd
8. H. Configure this tier to use artificial intelligence and machine learning (AI/ML) models that are trained and hosted on an EC2 instance to perform optical character recognition (OCR) on the forms when forms are uploade
9. I. Store the output in Amazon S3. Parse this output by extracting the data that is required within the application tie
10. J. Submit the data to the target system's API.
11. K. Host a new application tier on EC2 instance
12. L. Use this tier to call endpoints that host artificial intelligence and machine learning (Al/ML) models that are trained and hosted in Amazon SageMaker to perform optical character recognition (OCR) on the form
13. M. Store the output in Amazon ElastiCach
14. N. Parse this output by extracting the data that is required within the application tie
15. O. Submit the data to the target system's API.
16. P. Extend the system with an application tier that uses AWS Step Functions and AWS Lambd
17. Q. Configure this tier to use Amazon Textract and Amazon Comprehend to perform optical character recognition (OCR) on the forms when forms are uploade
18. R. Store the output in Amazon S3. Parse this output by extracting the data that is required within the application tie
19. S. Submit the data to the target system's API.

Correct Answer: D
Extend the system with an application tier that uses AWS Step Functions and AWS Lambda. Configure this tier to use Amazon Textract and Amazon Comprehend to perform optical character recognition (OCR) on the forms when forms are uploaded. Store the output in Amazon S3. Parse this output by extracting the data that is required within the application tier. Submit the data to the target system's API. This solution meets the requirements of accurate form extraction, minimal time to market, and minimal long-term operational overhead. Amazon Textract and Amazon Comprehend are fully managed and serverless services that can perform OCR and extract relevant data from the forms, which eliminates the need to develop custom libraries or train and host models. Using AWS Step Functions and Lambda allows for easy automation of the process and the ability to scale as needed.

- (Exam Topic 3)
A company is planning to migrate an application to AWS. The application runs as a Docker container and uses an NFS version 4 file share.
A solutions architect must design a secure and scalable containerized solution that does not require provisioning or management of the underlying infrastructure.
Which solution will meet these requirements?

1. A. Deploy the application containers by using Amazon Elastic Container Service (Amazon ECS) with the Fargate launch typ
2. B. Use Amazon Elastic File System (Amazon EFS) for shared storag
3. C. Reference the EFS file system ID, container mount point, and EFS authorization IAM role in the ECS task definition.
4. D. Deploy the application containers by using Amazon Elastic Container Service (Amazon ECS) with the Fargate launch typ
5. E. Use Amazon FSx for Lustre for shared storag
6. F. Reference the FSx for Lustre file system ID, container mount point, and FSx for Lustre authorization IAM role in the ECS task definition.
7. G. Deploy the application containers by using Amazon Elastic Container Service (Amazon ECS) with the Amazon EC2 launch type and auto scaling turned o
8. H. Use Amazon Elastic File System (Amazon EFS) for shared storag
9. I. Mount the EFS file system on the ECS container instance
10. J. Add the EFS authorization IAM role to the EC2 instance profile.
11. K. Deploy the application containers by using Amazon Elastic Container Service (Amazon ECS) with the Amazon EC2 launch type and auto scaling turned o
12. L. Use Amazon Elastic Block Store (Amazon EBS) volumes with Multi-Attach enabled for shared storag
13. M. Attach the EBS volumes to ECS container instance
14. N. Add the EBS authorization IAM role to an EC2 instance profile.

Correct Answer: A
This option uses Amazon Elastic Container Service (Amazon ECS) with the Fargate launch type to deploy the application containers. Amazon ECS is a fully managed container orchestration service that allows running Docker containers on AWS at scale. Fargate is a serverless compute engine for containers that eliminates the need to provision or manage servers or clusters. With Fargate, the company only pays for the resources required to run its containers, which reduces costs and operational overhead. This option also uses Amazon Elastic File System (Amazon EFS) for shared storage. Amazon EFS is a fully managed file system that provides scalable, elastic, concurrent, and secure file storage for use with AWS cloud services. Amazon EFS supports NFS version 4 protocol, which is compatible with the application’s requirements. To use Amazon EFS with Fargate containers, the company needs to reference the EFS file system ID, container mount point, and EFS authorization IAM role in the ECS task definition.