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To earn the DVA-C02 certification, candidates must pass a 130-minute exam consisting of 65 multiple-choice and multiple-response questions. DVA-C02 exam is available in English, Japanese, Korean, and Simplified Chinese. AWS Certified Developer - Associate certification is valid for three years, after which candidates must recertify to maintain their credentials.

The DVA-C02 Exam measures the candidate's knowledge in various aspects of AWS development, including AWS core services, AWS security, serverless applications, and deploying and managing AWS services. DVA-C02 exam consists of 65 multiple-choice and multiple-response questions, and the candidate has 130 minutes to complete the exam.

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Amazon DVA-C02 exam covers a wide range of AWS services and concepts, including AWS Lambda, AWS Elastic Beanstalk, AWS DynamoDB, AWS Simple Queue Service (SQS), and AWS Simple Notification Service (SNS). DVA-C02 exam also tests a candidate's knowledge of AWS security and compliance, cost optimization, and troubleshooting. DVA-C02 Exam consists of 65 multiple-choice and multiple-response questions and must be completed within 130 minutes.

Amazon AWS Certified Developer - Associate Sample Questions (Q550-Q555):

NEW QUESTION # 550
A company needs to set up secure database credentials for all its AWS Cloud resources. The company's resources include Amazon RDS DB instances Amazon DocumentDB clusters and Amazon Aurora DB instances. The company's security policy mandates that database credentials be encrypted at rest and rotated at a regular interval.
Which solution will meet these requirements MOST securely?

A. Store the database access credentials as an encrypted Amazon S3 object in an S3 bucket Block all public access on the S3 bucket. Use S3 server-side encryption to set up automatic rotation on the encryption key.
B. Set up IAM database authentication for token-based access. Generate user tokens to provide centralized access to RDS DB instances. Amazon DocumentDB clusters and Aurora DB instances.
C. Create an AWS Lambda function by using the SecretsManagerRotationTemplate template in the AWS Secrets Manager console. Create secrets for the database credentials in Secrets Manager Set up secrets rotation on a schedule.
D. Create parameters for the database credentials in AWS Systems Manager Parameter Store Set the Type parameter to Secure Sting. Set up automatic rotation on the parameters.

Answer: C

Explanation:
This solution will meet the requirements by using AWS Secrets Manager, which is a service that helps protect secrets such as database credentials by encrypting them with AWS Key Management Service (AWS KMS) and enabling automatic rotation of secrets. The developer can create an AWS Lambda function by using the SecretsManagerRotationTemplate template in the AWS Secrets Manager console, which provides a sample code for rotating secrets for RDS DB instances, Amazon DocumentDB clusters, and Amazon Aurora DB instances. The developer can also create secrets for the database credentials in Secrets Manager, which encrypts them at rest and provides secure access to them. The developer can set up secrets rotation on a schedule, which changes the database credentials periodically according to a specified interval or event.
Option A is not optimal because it will set up IAM database authentication for token-based access, which may not be compatible with all database engines and may require additional configuration and management of IAM roles or users. Option B is not optimal because it will create parameters for the database credentials in AWS Systems Manager Parameter Store, which does not support automatic rotation of secrets. Option C is not optimal because it will store the database access credentials as an encrypted Amazon S3 object in an S3 bucket, which may introduce additional costs and complexity for accessing and securing the data.
References: [AWS Secrets Manager], [Rotating Your AWS Secrets Manager Secrets]

NEW QUESTION # 551
A developer works in an environment with multiple AWS accounts that have AWS Lambda functions processing the same 100 KB payloads. The developer wants to centralize the point of origin of the payloads to one account and have all the Lambda functions be invoked whenever the initiating event occurs in the parent account.
How can the developer design the workflow in the MOST efficient way, so all the multi-account Lambda functions get invoked when the event occurs?

A. Create a Lambda function in the parent account and use cross-account IAM roles with the AWS STS AssumeRole API call to make AWS Lambda invoke the API call to invoke all the cross-account Lambda functions.
B. Use a worker on an Amazon EC2 instance to poll for the payload event. Invoke all Lambda functions using the Lambda Invoke API after using cross-account IAM roles with the AWS STS AssumeRole API call.
C. Subscribe all the multi-account Lambda functions to an Amazon SNS topic and make an SNS Publish API call with the payload to the SNS topic.
D. Set up an Amazon SQS queue with the queue policy permitting the ReceiveMessage action for multi- account Lambda functions. Then send the payload to the SQS queue using the sqs:SendMessage permission and poll the queue using multi-account Lambda functions.

Answer: C

Explanation:
Amazon SNS is the most efficient fanout service for this requirement. A single publish operation can distribute the same message payload to multiple subscribers, including Lambda functions. Because the payload is 100 KB, it is within the SNS message size limit, making direct fanout practical. This centralizes the event origin in the parent account and avoids custom orchestration code. Using STS AssumeRole and manually invoking every Lambda function creates unnecessary code, permissions management, and retry complexity. SQS is a queueing service where messages are consumed, not broadcast to all consumers; multiple Lambda functions polling the same queue would compete for messages rather than each receive every payload. An EC2 worker is the worst option because it adds server management and polling overhead.
SNS topic subscriptions are the intended pub/sub design.

NEW QUESTION # 552
A developer is building an application to process a stream of customer orders. The application sends processed orders to an Amazon Aurora MySQL database. The application needs to process the orders in batches.
The developer needs to configure a workflow that ensures each record is processed before the application sends each order to the database.
Which solution meets these requirements?

A. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the orders. Use an Amazon EC2 instance to process the orders. Configure an event source mapping for the EC2 instance, and increase the payload size limit to 36 MB.
B. Use Amazon SQS to stream the orders. Use an AWS Lambda function to process the orders.
Configure an event source mapping for the Lambda function, and set the
MaximumBatchingWindowInSeconds setting to 0.
C. Use Amazon Kinesis Data Streams to stream the orders. Use an AWS Lambda function to process the orders. Configure an event source mapping for the Lambda function, and set the MaximumBatchingWindowInSeconds setting to 300.
D. Use Amazon DynamoDB Streams to stream the orders. Use an Amazon ECS cluster on AWS Fargate to process the orders. Configure an event source mapping for the cluster, and set the BatchSize setting to 1.

Answer: C

Explanation:
Amazon Kinesis Data Streams supports ordered and batched data processing. By using a Lambda function with event source mapping and setting MaximumBatchingWindowInSeconds, the developer can batch records over a time window (up to 300 seconds) before sending them to the Aurora MySQL database. This meets the requirement for batch processing and ensures each record is processed before being sent, with low operational overhead.

NEW QUESTION # 553
A developer at a company recently created a serverless application to process and show data from business reports. The application's user interface (UI) allows users to select and start processing the files. The Ul displays a message when the result is available to view. The application uses AWS Step Functions with AWS Lambda functions to process the files. The developer used Amazon API Gateway and Lambda functions to create an API to support the UI.
The company's Ul team reports that the request to process a file is often returning timeout errors because of the see or complexity of the files. The Ul team wants the API to provide an immediate response so that the Ul can deploy a message while the files are being processed. The backend process that is invoked by the API needs to send an email message when the report processing is complete.
What should the developer do to configure the API to meet these requirements?

A. Change the API Gateway route to add an X-Amz-Invocation-Type header win a sialic value of 'Event' in the integration request Deploy the API Gateway stage to apply the changes.
B. Change the configuration of the Lambda function that implements the request to process a file. Configure the maximum age of the event so that the Lambda function will ion asynchronously.
C. Change the API Gateway timeout value to match the Lambda function ominous value. Deploy the API Gateway stage to apply the changes.
D. Change the API Gateway route to add an X-Amz-Target header with a static value of 'A sync' in the integration request Deploy me API Gateway stage to apply the changes.

Answer: A

Explanation:
This solution allows the API to invoke the Lambda function asynchronously, which means that the API will return an immediate response without waiting for the function to complete. The X-Amz-Invocation-Type header specifies the invocation type of the Lambda function, and setting it to 'Event' means that the function will be invoked asynchronously. The function can then use Amazon Simple Email Service (SES) to send an email message when the report processing is complete.

NEW QUESTION # 554
A developer is creating an application that will give users the ability to store photos from their cellphones in the cloud. The application needs to support tens of thousands of users. The application uses an Amazon API Gateway REST API that is integrated with AWS Lambda functions to process the photos. The application stores details about the photos in Amazon DynamoDB.
Users need to create an account to access the application. In the application, users must be able to upload photos and retrieve previously uploaded photos. The photos will range in size from 300 KB to 5 MB.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use Amazon Cognito user pools to manage user accounts. Create an Amazon Cognito user pool authorizer in API Gateway to control access to the API. Use the Lambda function to store the photos and details in the DynamoDB table. Retrieve previously uploaded photos directly from the DynamoDB table.
B. Use Amazon Cognito user pools to manage user accounts. Create an Amazon Cognito user pool authorizer in API Gateway to control access to the API. Use the Lambda function to store the photos in Amazon S3. Store the object's S3 key as part of the photo details in the DynamoDB table. Retrieve previously uploaded photos by querying DynamoDB for the S3 key.
C. Create a users table in DynamoDB. Use the table to manage user accounts. Create a Lambda authorizer that validates user credentials against the users table. Integrate the Lambda authorizer with API Gateway to control access to the API. Use the Lambda function to store the photos in Amazon S3. Store the object's S3 key as par of the photo details in the DynamoDB table. Retrieve previously uploaded photos by querying DynamoDB for the S3 key.
D. Create an IAM user for each user of the application during the sign-up process. Use IAM authentication to access the API Gateway API. Use the Lambda function to store the photos in Amazon S3. Store the object's S3 key as part of the photo details in the DynamoDB table. Retrieve previously uploaded photos by querying DynamoDB for the S3 key.

Answer: B

NEW QUESTION # 555
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