A company is building an application to accept data from customers. The data must be encrypted at rest and in transit.
The application uses an Amazon API Gateway API that resolves to AWS Lambda functions. The Lambda functions store the data in an Amazon Aurora MySQL DB cluster. The application worked properly during testing.
A developer configured an Amazon CloudFront distribution with field-level encryption that uses an AWS Key Management Service (AWS KMS) key. After the configuration of the distribution, the application behaved unexpectedly. All the data in the database changed from plaintext to ciphertext.
The developer must ensure that the data is not stored in the database as the ciphertext from the CloudFront field-level encryption.
Which solution will meet this requirement?

• A.Change the CloudFront Viewer protocol policy from "HTTP and HTTPS" to "HTTPS only."
• B.Add a Lambda function that uses the KMS key to decrypt the data fields before saving the data to the database.
• C.Enable encryption on the DB cluster by using the same KMS key that is used in CloudFront.
• D.Request and deploy a new SSL certificate to use with the CloudFront distribution.

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A developer warns to add request validation to a production environment Amazon API Gateway API. The developer needs to test the changes before the API is deployed to the production environment. For the lest the developer will send test requests to the API through a testing tool.
Which solution will meet these requirements with the LEAST operational overhead?

• A.Export the existing API to an OpenAPI file. Create a new API Import the OpenAPI file Modify the new API to add request validation. Perform the tests Modify the existing API to add request validation. Deploy the existing API to production.
• B.Modify the existing API to add request validation. Deploy the updated API to a new API Gateway stage Perform the tests Deploy the updated API to the API Gateway production stage.
• C.Create a new API Add the necessary resources and methods including new request validation. Perform the tests Modify the existing API to add request validation. Deploy the existing API to production.
• D.Clone the exiting API Modify the new API lo add request validation. Perform the tests Modify the existing API to add request validation Deploy the existing API to production.

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A developer is deploying a new application to Amazon Elastic Container Service (Amazon ECS). The developer needs to securely store and retrieve different types of variables. These variables include authentication information for a remote API, the URL for the API, and credentials. The authentication information and API URL must be available to all current and future deployed versions of the application across development, testing, and production environments.
How should the developer retrieve the variables with the FEWEST application changes?

• A.Update the application to retrieve the variables from AWS Systems Manager Parameter Store. Use unique paths in Parameter Store for each variable in each environment. Store the credentials in AWS Secrets Manager in each environment.
• B.Update the application to retrieve the variables from AWS Key Management Service (AWS KMS). Store the API URL and credentials as unique keys for each environment.
• C.Update the application to retrieve the variables from an encrypted file that is stored with the application. Store the API URL and credentials in unique files for each environment.
• D.Update the application to retrieve the variables from each of the deployed environments. Define the authentication information and API URL in the ECS task definition as unique names during the deployment process.

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A company is creating a new application that gives users the ability to upload and share short video files. The average size of the video files is 10 MB. After a user uploads a file, a message needs to be placed into an Amazon Simple Queue Service (Amazon SQS) queue so the file can be processed. The files need to be accessible for processing within 5 minutes.
Which solution will meet these requirements MOST cost-effectively?

• A.Write the files to Amazon S3 Glacier Deep Archive. Add the S3 location of the files to the SQS queue.
• B.Write the files to Amazon S3 Standard. Add the S3 location of the files to the SQS queue.
• C.Write the files to an Amazon Elastic Block Store (Amazon EBS) General Purpose SSD volume. Add the EBS location of the files to the SQS queue.
• D.Write messages that contain the contents of the uploaded files to the SQS queue.

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A developer is building a microservices-based application by using Python on AWS and several AWS services The developer must use AWS X-Ray The developer views the service map by using the console to view the service dependencies. During testing, the developer notices that some services are missing from the service map What can the developer do to ensure that all services appear in the X-Ray service map?

• A.Modify the X-Ray Python agent configuration in each service to increase the sampling rate
• B.Instrument the application by using the X-Ray SDK for Python. Install the X-Ray SDK for all the services that the application uses
• C.Enable X-Ray data aggregation in Amazon CloudWatch Logs for all the services that the application uses
• D.Increase the X-Ray service map timeout value in the X-Ray console

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