Free AWS Certified Developer Associate Exam Braindumps
AWS Certified Developer - Associate DVA-C02 Questions 291–295 (page: 60)

Updated On: 10-Feb-2026

A data visualization company wants to strengthen the security of its core applications. The applications are deployed on AWS across its development, staging, pre-production, and production environments. The company needs to encrypt all of its stored sensitive credentials. The sensitive credentials need to be automatically rotated. A version of the sensitive credentials need to be stored for each environment.
Which solution will meet these requirements in the MOST operationally efficient way?

  1. Configure AWS Secrets Manager versions to store different copies of the same credentials across multiple environments.
  2. Create a new parameter version in AWS Systems Manager Parameter Store for each environment. Store the environment-specific credentials in the parameter version.
  3. Configure the environment variables in the application code. Use different names for each environment type.
  4. Configure AWS Secrets Manager to create a new secret for each environment type. Store the environment-specific credentials in the secret.

Answer(s): D



A developer is investigating an issue in part of a company's application. In the application, messages are sent to an Amazon Simple Queue Service (Amazon SQS) queue. The AWS Lambda function polls messages from the SQS queue and sends email messages by using Amazon Simple Email Service (Amazon SES). Users have been receiving duplicate email messages during periods of high traffic.
Which reasons could explain the duplicate email messages? (Choose two.)

  1. Standard SQS queues support at-least-once message delivery.
  2. Standard SQS queues support exactly-once processing, so the duplicate email messages are because of user error.
  3. Amazon SES has the DomainKeys Identified Mail (DKIM) authentication incorrectly configured.
  4. The SQS queue's visibility timeout is lower than or the same as the Lambda function's timeout.
  5. The Amazon SES bounce rate metric is too high.

Answer(s): A,D



A developer is deploying a company's application to Amazon EC2 instances. The application generates gigabytes of data files each day. The files are rarely accessed, but the files must be available to the application's users within minutes of a request during the first year of storage. The company must retain the files for 7 years.
How can the developer implement the application to meet these requirements MOST cost-effectively?

  1. Store the files in an Amazon S3 bucket. Use the S3 Glacier Instant Retrieval storage class. Create an S3 Lifecycle policy to transition the files to the S3 Glacier Deep Archive storage class after 1 year.
  2. Store the files in an Amazon S3 bucket. Use the S3 Standard storage class. Create an S3 Lifecycle policy to transition the files to the S3 Glacier Flexible Retrieval storage class after 1 year.
  3. Store the files on an Amazon Elastic Block Store (Amazon EBS) volume. Use Amazon Data Lifecycle Manager (Amazon DLM) to create snapshots of the EBS volumes and to store those snapshots in Amazon S3.
  4. Store the files on an Amazon Elastic File System (Amazon EFS) mount. Configure EFS lifecycle management to transition the files to the EFS Standard- Infrequent Access (Standard-IA) storage class after 1 year.

Answer(s): A



A company's developer has deployed an application in AWS by using AWS CloudFormation. The CloudFormation stack includes parameters in AWS Systems Manager Parameter Store that the application uses as configuration settings. The application can modify the parameter values.
When the developer updated the stack to create additional resources with tags, the developer noted that the parameter values were reset and that the values ignored the latest changes made by the application. The developer needs to change the way the company deploys the CloudFormation stack. The developer also needs to avoid resetting the parameter values outside the stack.
Which solution will meet these requirements with the LEAST development effort?

  1. Modify the CloudFormation stack to set the deletion policy to Retain for the Parameter Store parameters.
  2. Create an Amazon DynamoDB table as a resource in the CloudFormation stack to hold configuration data for the application. Migrate the parameters that the application is modifying from Parameter Store to the DynamoDB table.
  3. Create an Amazon RDS DB instance as a resource in the CloudFormation stack. Create a table in the database for parameter configuration. Migrate the parameters that the application is modifying from Parameter Store to the configuration table.
  4. Modify the CloudFormation stack policy to deny updates on Parameter Store parameters.

Answer(s): A



A company has a social media application that receives large amounts of traffic. User posts and interactions are continuously updated in an Amazon RDS database. The data changes frequently, and the data types can be complex. The application must serve read requests with minimal latency.
The application's current architecture struggles to deliver these rapid data updates efficiently. The company needs a solution to improve the application's performance.
Which solution will meet these requirements?

  1. Use Amazon DynamoDB Accelerator (DAX) in front of the RDS database to provide a caching layer for the high volume of rapidly changing data.
  2. Set up Amazon S3 Transfer Acceleration on the RDS database to enhance the speed of data transfer from the databases to the application.
  3. Add an Amazon CloudFront distribution in front of the RDS database to provide a caching layer for the high volume of rapidly changing data.
  4. Create an Amazon ElastiCache for Redis cluster. Update the application code to use a write-through caching strategy and read the data from Redis.

Answer(s): D



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