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Free AWS Certified Developer Associate Exam Braindumps
AWS Certified Developer - Associate DVA-C02 Questions 251–255 (page: 52)

Updated On: 10-Feb-2026
Page 52 of 113
PDF with 610 Questions

A developer has created a data collection application that uses Amazon API Gateway, AWS Lambda, and Amazon S3. The application’s users periodically upload data files and wait for the validation status to be reflected on a processing dashboard. The validation process is complex and time-consuming for large files.
Some users are uploading dozens of large files and have to wait and refresh the processing dashboard to see if the files have been validated. The developer must refactor the application to immediately update the validation result on the user’s dashboard without reloading the full dashboard.
What is the MOST operationally efficient solution that meets these requirements?

  1. Integrate the client with an API Gateway WebSocket API. Save the user-uploaded files with the WebSocket connection ID. Push the validation status to the connection ID when the processing is complete to initiate an update of the user interface.
  2. Launch an Amazon EC2 micro instance, and set up a WebSocket server. Send the user-uploaded file and user detail to the EC2 instance after the user uploads the file. Use the WebSocket server to send updates to the user interface when the uploaded file is processed.
  3. Save the user’s email address along with the user-uploaded file. When the validation process is complete, send an email notification through Amazon Simple Notification Service (Amazon SNS) to the user who uploaded the file.
  4. Save the user-uploaded file and user detail to Amazon DynamoDB. Use Amazon DynamoDB Streams with Amazon Simple Notification Service (Amazon SNS) push notifications to send updates to the browser to update the user interface.

Answer(s): A



A company’s developer is creating an application that uses Amazon API Gateway. The company wants to ensure that only users in the Sales department can use the application. The users authenticate to the application by using federated credentials from a third-party identity provider (IdP) through Amazon Cognito. The developer has set up an attribute mapping to map an attribute that is named Department and to pass the attribute to a custom AWS Lambda authorizer.
To test the access limitation, the developer sets their department to Engineering in the IdP and attempts to log in to the application. The developer is denied access. The developer then updates their department to Sales in the IdP and attempts to log in. Again, the developer is denied access. The developer checks the logs and discovers that access is being denied because the developer’s access token has a department value of Engineering.
Which of the following is a possible reason that the developer’s department is still being reported as Engineering instead of Sales?

  1. Authorization caching is enabled in the custom Lambda authorizer.
  2. Authorization caching is enabled on the Amazon Cognito user pool.
  3. The IAM role for the custom Lambda authorizer does not have a Department tag.
  4. The IAM role for the Amazon Cognito user pool does not have a Department tag.

Answer(s): A



A company has migrated an application to Amazon EC2 instances. Automatic scaling is working well for the application user interface. However, the process to deliver shipping requests to the company’s warehouse staff is encountering issues. Duplicate shipping requests are arriving, and some requests are lost or arrive out of order.
The company must avoid duplicate shipping requests and must process the requests in the order that the requests arrive. Requests are never more than 250 KB in size and take 5-10 minutes to process. A developer needs to rearchitect the application to improve the reliability of the delivery and processing of the requests.
What should the developer do to meet these requirements?

  1. Create an Amazon Kinesis Data Firehose delivery stream to process the requests. Create an Amazon Kinesis data stream. Modify the application to write the requests to the Kinesis data stream.
  2. Create an AWS Lambda function to process the requests. Create an Amazon Simple Notification Service (Amazon SNS) topic. Subscribe the Lambda function to the SNS topic. Modify the application to write the requests to the SNS topic.
  3. Create an AWS Lambda function to process the requests. Create an Amazon Simple Queue Service (Amazon SQS) standard queue. Set the SQS queue as an event source for the Lambda function. Modify the application to write the requests to the SQS queue.
  4. Create an AWS Lambda function to process the requests. Create an Amazon Simple Queue Service (Amazon SQS) FIFO queue. Set the SQS queue as an event source for the Lambda function. Modify the application to write the requests to the SQS queue.

Answer(s): D



A developer is creating a machine learning (ML) pipeline in AWS Step Functions that contains AWS Lambda functions. The developer has configured an Amazon Simple Queue Service (Amazon SQS) queue to deliver ML model parameters to the ML pipeline to train ML models. The developer uploads the trained models are uploaded to an Amazon S3 bucket.
The developer needs a solution that can locally test the ML pipeline without making service integration calls to Amazon SQS and Amazon S3.
Which solution will meet these requirements?

  1. Use the Amazon CodeGuru Profiler to analyze the Lambda functions used in the AWS Step Functions pipeline.
  2. Use the AWS Step Functions Local Docker Image to run and locally test the Lambda functions.
  3. Use the AWS Serverless Application Model (AWS SAM) CLI to run and locally test the Lambda functions.
  4. Use AWS Step Functions Local with mocked service integrations.

Answer(s): D



A company runs a batch processing application by using AWS Lambda functions and Amazon API Gateway APIs with deployment stages for development, user acceptance testing, and production. A development team needs to configure the APIs in the deployment stages to connect to third-party service endpoints.
Which solution will meet this requirement?

  1. Store the third-party service endpoints in Lambda layers that correspond to the stage.
  2. Store the third-party service endpoints in API Gateway stage variables that correspond to the stage.
  3. Encode the third-party service endpoints as query parameters in the API Gateway request URL.
  4. Store the third-party service endpoint for each environment in AWS AppConfig.

Answer(s): B



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