DVA-C02 practice questions 451–460

1. Question 451 · 548 in bank

   A developer has a legacy application that is hosted on-premises. Other applications hosted on AWS depend on the on-premises application for proper functioning. In case of any application errors, the developer wants to be able to use Amazon CloudWatch to monitor and troubleshoot all applications from one place. How can the developer accomplish this?

   • AInstall an AWS SDK on the on-premises server to automatically send logs to CloudWatch.
   • BDownload the CloudWatch agent to the on-premises server. Configure the agent to use IAM user credentials with permissions for CloudWatch.
   • CUpload log files from the on-premises server to Amazon S3 and have CloudWatch read the files.
   • DUpload log files from the on-premises server to an Amazon EC2 instance and have the instance forward the logs to CloudWatch.

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   Answer: B

   Explanation

   A) Eliminated - Using the AWS SDK means you must write custom code to capture and send logs to CloudWatch via the PutLogEvents API. This is not automatic as mentioned in option B) CloudWatch agent is specifically designed for collecting logs and metrics from both AWS and on-premises environments. C) Eliminated - unnecessary complexity. D) Eliminated - unnecessarily complex and costly.

   Source: Adapted from community discussion — sumanshu

   References

   • AWS documentation
   • AWS documentation

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2. Question 452 · 548 in bank

   An AWS Lambda function generates a 3 MB JSON file and then uploads it to an Amazon S3 bucket daily. The file contains sensitive information, so the developer must ensure that it is encrypted before uploading to the bucket. Which of the following modifications should the developer make to ensure that the data is encrypted before uploading it to the bucket?

   • AUse the default AWS Key Management Service (AWS KMS) key for Amazon S3 in the Lambda function code.
   • BUse the S3 managed key and call the GenerateDataKey API to encrypt the file.
   • CUse the GenerateDataKey API, then use that data key to encrypt the file in the Lambda function code.
   • DUse an AWS Key Management Service (AWS KMS) customer managed key for Amazon S3 in the Lambda function code.

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   Answer: C

   Explanation

   generating a data key, then enc # Generate a data key response = kms.generate_data_key(KeyId=key_id, KeySpec='AES_256') plaintext_key = response['Plaintext'] ciphertext_key = response['CiphertextBlob']rypting and decrypting a small string using that data key

   Source: Adapted from community discussion — ShakthiGCP

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3. Question 453 · 548 in bank

   A company is building a social media application. A developer is modifying an AWS Lambda function that updates a database with data that tracks each user's online activity. A web application server uses the AWS SDK to invoke the Lambda function. The developer has tested the new Lambda code and is ready to deploy the code into production. However, the developer wants to allow only a small percentage of the invocations from the AWS SDK to call the new code. Which solution will meet these requirements?

   • AConfigure a Lambda version that has a specific weight value for the updated Lambda function.
   • BCreate an alias for the Lambda function. Configure a specific weight value for the updated version.
   • CCreate an Application Load Balancer. Specify weighted target groups for the original Lambda function and the updated Lambda function.
   • DCreate a Network Load Balancer. Specify weighted target groups for the original Lambda function and the updated Lambda function.

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   Answer: B

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4. Question 454 · 548 in bank

   An Amazon Data Firehose delivery stream is receiving customer data that contains personally identifiable information. A developer needs to remove pattern-based customer identifiers from the data and store the modified data in an Amazon S3 bucket. What should the developer do to meet these requirements?

   • AImplement Firehose data transformation as an AWS Lambda function. Configure the function to remove the customer identifiers. Set an Amazon S3 bucket as the destination of the delivery stream.
   • BLaunch an Amazon EC2 instance. Set the EC2 instance as the destination of the delivery stream. Run an application on the EC2 instance to remove the customer identifiers. Store the transformed data in an Amazon S3 bucket.
   • CCreate an Amazon OpenSearch Service instance. Set the OpenSearch Service instance as the destination of the delivery stream. Use search and replace to remove the customer identifiers. Export the data to an Amazon S3 bucket.
   • DCreate an AWS Step Functions workflow to remove the customer identifiers. As the last step in the workflow, store the transformed data in an Amazon S3 bucket. Set the workflow as the destination of the delivery stream.

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   Answer: A

   Explanation

   Data Anonymization: Remove or obfuscate sensitive information for compliance or security reasons. Example: Mask personally identifiable information (PII) like email addresses or phone numbers.

   Source: Adapted from community discussion — ShakthiGCP

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5. Question 455 · 548 in bank

   A developer is building a three-tier web application that should be able to handle a minimum of 5000 requests per minute. Requirements state that the web tier should be completely stateless while the application maintains session state for the users. How can session data be externalized, keeping latency at the LOWEST possible value?

   • ACreate an Amazon RDS instance, then implement session handling at the application level to leverage a database inside the RDS database instance for session data storage.
   • BImplement a shared file system solution across the underlying Amazon EC2 instances, then implement session handling at the application level to leverage the shared file system for session data storage.
   • CCreate an Amazon ElastiCache (Memcached) cluster, then implement session handling at the application level to leverage the cluster for session data storage.
   • DCreate an Amazon DynamoDB table, then implement session handling at the application level to leverage the table for session data storage.

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   Answer: C

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6. Question 456 · 548 in bank

   A developer has deployed an AWS Lambda function that is subscribed to an Amazon Simple Notification Service (Amazon SNS) topic. The developer must implement a solution to add a record of each Lambda function invocation to an Amazon Simple Queue Service (Amazon SQS) queue. Which solution will meet this requirement?

   • AConfigure the SQS queue as a dead-letter queue for the Lambda function.
   • BCreate code that uses the AWS SDK to call the SQS SendMessage operation to add the invocation details to the SQS queue. Add the code to the end of the Lambda function.
   • CAdd two asynchronous invocation destinations to the Lambda function: one destination for successful invocations and one destination for failed invocations. Configure the SQS queue as the destination for each type. Create an Amazon CloudWatch alarm based on the DestinationDeliveryFailures metric to catch any message that cannot be delivered.
   • DAdd a single asynchronous invocation destination to the Lambda function to capture successful invocations. Configure the SQS queue as the destination. Create an Amazon CloudWatch alarm based on the DestinationDeliveryFailures metric to catch any message that cannot be delivered.

   Show answer

   Answer: B

   Explanation

   B is the correct answer. When using asynchronous invocations, there are three types of potential states: success, failure and retryable failure. this option only logs first 2, not all. A is wrong because it only logs the failure invocations, not all. C is wrong because it only logs success and failure invocations, not all. D is wrong because it logs only successful invocations, not all.

   Source: Adapted from community discussion — Arad

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7. Question 457 · 548 in bank

   An AWS Lambda function that handles application requests uses the default Lambda logging mechanism to log the timestamp, processing time, and status of requests. A developer needs to create Amazon CloudWatch metrics based on the logs. The developer needs to write the metrics to a custom CloudWatch metrics namespace. Which solution will meet these requirements?

   • AUse Amazon CloudWatch Logs Insights to generate custom metrics from the logs by using CloudWatch embedded metric format (EMF).
   • BUse Amazon CloudWatch RUM to generate custom metrics from the logs by using CloudWatch embedded metric format (EMF).
   • CUse Amazon CloudWatch Logs Insights to generate custom metrics from the logs by using JSON format.
   • DUse the CloudWatch embedded metric format (EMF) for the structure of the log statements to generate custom CloudWatch metrics.

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   Answer: D

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8. Question 458 · 548 in bank

   A developer needs to configure an AWS Lambda function to make HTTP POST requests to an internal application. The application is in the same AWS account that hosts the function. The internal application runs on Amazon EC2 instances in a private subnet within a VPC. Which solution will meet these requirements?

   • AConfigure a VPC endpoint to connect to the private subnet. Attach the endpoint to the Lambda function.
   • BAttach the Lambda function to the VPC and to the private subnet.
   • CConfigure a VPN connection between the Lambda function and the private subnet. Attach the VPN to the Lambda function.
   • DConfigure the VPC route table to include the Lambda function’s IP address.

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   Answer: B

   Explanation

   When your Lambda function needs to access resources within a VPC, such as Amazon EC2 instances in a private subnet, you need to configure the Lambda function to run within that VPC. This is done by specifying the VPC, subnet(s), and security group(s) in the Lambda configuration. Once attached to the VPC and subnet, the Lambda function can make HTTP requests to the internal application running on the EC2 instances in the private subnet.

   Source: Adapted from community discussion — xdeveloper

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9. Question 459 · 548 in bank

   Two containerized microservices are hosted on Amazon EC2 ECS. The first microservice reads an Amazon RDS Aurora database instance, and the second microservice reads an Amazon DynamoDB table. How can each microservice be granted the minimum privileges?

   • ASet ECS_ENABLE_TASK_IAM_ROLE to false on EC2 instance boot in ECS agent configuration file. Run the first microservice with an IAM role for ECS tasks with read-only access for the Aurora database. Run the second microservice with an IAM role for ECS tasks with read-only access to DynamoDB.
   • BSet ECS_ENABLE_TASK_IAM ROLE to false on EC2 instance boot in the ECS agent configuration file. Grant the instance profile role read-only access to the Aurora database and DynamoDB.
   • CSet ECS_ENABLE_TASK_IAM ROLE to true on EC2 instance boot in the ECS agent configuration file. Run the first microservice with an IAM role for ECS tasks with read-only access for the Aurora database. Run the second microservice with an IAM role for ECS tasks with read-only access to DynamoDB.
   • DSet ECS_ENABLE_TASK_IAM_ROLE to true on EC2 instance boot in the ECS agent configuration file. Grant the instance profile role read-only access to the Aurora database and DynamoDB.

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   Answer: C

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10. Question 460 · 548 in bank

    A developer is writing a mobile application that allows users to view images from an S3 bucket. The users must be able to log in with their Amazon login, as well as supported social media accounts. How can the developer provide this authentication functionality?

    • AUse Amazon Cognito with web identity federation.
    • BUse Amazon Cognito with SAML-based identity federation.
    • CUse IAM access keys and secret keys in the application code to allow Get* on the S3 bucket.
    • DUse AWS STS AssumeRole in the application code and assume a role with Get* permissions on the S3 bucket.

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    Answer: A

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DVA-C02 practice, question 451. 548 questions available.