DVA-C02 practice questions 211–220

1. Question 211 · 548 in bank

   A company runs an application on AWS. The application uses an AWS Lambda function that is configured with an Amazon Simple Queue Service (Amazon SQS) queue called high priority queue as the event source. A developer is updating the Lambda function with another SQS queue called low priority queue as the event source. The Lambda function must always read up to 10 simultaneous messages from the high priority queue before processing messages from low priority queue. The Lambda function must be limited to 100 simultaneous invocations. Which solution will meet these requirements?

   • ASet the event source mapping batch size to 10 for the high priority queue and to 90 for the low priority queue.
   • BSet the delivery delay to 0 seconds for the high priority queue and to 10 seconds for the low priority queue.
   • CSet the event source mapping maximum concurrency to 10 for the high priority queue and to 90 for the low priority queue.
   • DSet the event source mapping batch window to 10 for the high priority queue and to 90 for the low priority queue.

   Show answer

   Answer: C

   Explanation

   You can use the maximum concurrency setting to control scaling behavior for your SQS event sources. The maximum concurrency setting limits the number of concurrent instances of the function that an Amazon SQS event source can invoke. Maximum concurrency is an event source-level setting. If you have multiple Amazon SQS event sources mapped to one function, each event source can have a separate maximum concurrency setting. You can use maximum concurrency to prevent one queue from using all of the function's reserved concurrency or the rest of the account's concurrency quota. There is no charge for configuring maximum concurrency on an Amazon SQS event source.

   Source: Adapted from community discussion — preachr

   References

   • AWS documentation

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2. Question 212 · 548 in bank

   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?

   • AConfigure AWS Secrets Manager versions to store different copies of the same credentials across multiple environments.
   • BCreate a new parameter version in AWS Systems Manager Parameter Store for each environment. Store the environment-specific credentials in the parameter version.
   • CConfigure the environment variables in the application code. Use different names for each environment type.
   • DConfigure AWS Secrets Manager to create a new secret for each environment type. Store the environment-specific credentials in the secret.

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   Answer: D

   Explanation

   D. Configure AWS Secrets Manager to create a new secret for each environment type. Store the environment-specific credentials in the secret. AWS Secrets Manager supports the encryption of secrets (including sensitive credentials) and allows for automatic rotation of these secrets. By creating a new secret for each environment (development, staging, pre-production, and production), you can manage and access the environment-specific credentials securely. This approach facilitates operational efficiency by leveraging AWS Secrets Manager's built-in capabilities for encryption and rotation, without the need for manual intervention or complex configurations. Secrets Manager also provides a straightforward way to retrieve the correct version of the credentials for each specific environment, simplifying the management of sensitive data across different stages of application deployment.

   Source: Adapted from community discussion — SerialiDr

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3. Question 213 · 548 in bank

   Select 2

   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.)

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

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   Answer: AD

   References

   • AWS documentation

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4. Question 214 · 548 in bank

   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?

   • AStore 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.
   • BStore 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.
   • CStore 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.
   • DStore 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.

   Show answer

   Answer: A

   References

   • AWS documentation

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5. Question 215 · 548 in bank

   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?

   • AModify the CloudFormation stack to set the deletion policy to Retain for the Parameter Store parameters.
   • BCreate 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.
   • CCreate 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.
   • DModify the CloudFormation stack policy to deny updates on Parameter Store parameters.

   Show answer

   Answer: A

   Explanation

   A. Modify the CloudFormation stack to set the deletion policy to Retain for the Parameter Store parameters. This solution allows the developer to avoid resetting the parameter values stored in AWS Systems Manager Parameter Store when updating the CloudFormation stack. By setting the deletion policy to Retain for those parameters, CloudFormation will preserve their values during stack updates instead of deleting and recreating them. It changes the way the company deploys the CloudFormation stack by modifying the deletion policy for the relevant parameters. It avoids resetting the parameter values outside the stack, as the values modified by the application will be retained during stack updates.

   Source: Adapted from community discussion — SerialiDr

   References

   • AWS documentation
   • AWS documentation

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6. Question 216 · 548 in bank

   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?

   • AUse Amazon DynamoDB Accelerator (DAX) in front of the RDS database to provide a caching layer for the high volume of rapidly changing data.
   • BSet up Amazon S3 Transfer Acceleration on the RDS database to enhance the speed of data transfer from the databases to the application.
   • CAdd an Amazon CloudFront distribution in front of the RDS database to provide a caching layer for the high volume of rapidly changing data.
   • DCreate an Amazon ElastiCache for Redis cluster. Update the application code to use a write-through caching strategy and read the data from Redis.

   Show answer

   Answer: D

   Explanation

   This option is the most suitable for the described scenario. Amazon ElastiCache for Redis can act as a high-performance, in-memory data store and cache, which is ideal for applications that require fast access to data. Implementing a write-through caching strategy ensures that data is written to the cache and the primary data store (RDS) simultaneously, keeping the cache up to date. Reading data from the cache can significantly reduce latency and the load on the RDS database, making it an optimal solution for applications with high read demand.

   Source: Adapted from community discussion — SerialiDr

   References

   • AWS documentation

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7. Question 217 · 548 in bank

   A developer created an AWS Lambda function that performs a series of operations that involve multiple AWS services. The function's duration time is higher than normal. To determine the cause of the issue, the developer must investigate traffic between the services without changing the function code. Which solution will meet these requirements?

   • AEnable AWS X-Ray active tracing in the Lambda function. Review the logs in X-Ray.
   • BConfigure AWS CloudTrail. View the trail logs that are associated with the Lambda function.
   • CReview the AWS Config logs in Amazon CloudWatch.
   • DReview the Amazon CloudWatch logs that are associated with the Lambda function.

   Show answer

   Answer: A

   Explanation

   A. Enable AWS X-Ray active tracing in the Lambda function. Review the logs in X-Ray. X-Ray provides insights into the duration and performance of each component, helping you identify the root cause of performance issues without modifying the function code.

   Source: Adapted from community discussion — hungnv6_rikkei

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8. Question 218 · 548 in bank

   Select 2

   A company has on-premises data centers that run an image processing service. The service consists of containerized applications that run on Kubernetes clusters. All the applications have access to the same NFS share for files and data storage. The company is running out of NFS capacity in the data centers and needs to migrate to AWS as soon as possible. The Kubernetes clusters must be highly available on AWS. Which combination of actions will meet these requirements? (Choose two.)

   • ATransfer the information that is in the NFS share to an Amazon Elastic Block Store (Amazon EBS) volume. Upload the container images to Amazon Elastic Container Registry (Amazon ECR).
   • BTransfer the information that is in the NFS share to an Amazon Elastic File System (Amazon EFS) volume. Upload the container images to Amazon Elastic Container Registry (Amazon ECR).
   • CCreate an Amazon Elastic Container Service (Amazon ECS) cluster to run the applications. Configure each node of the cluster to mount the Amazon Elastic Block Store (Amazon EBS) volume at the required path for the container images.
   • DCreate an Amazon Elastic Kubernetes Service (Amazon EKS) cluster to run the applications. Configure each node of the cluster to mount the Amazon Elastic Block Store (Amazon EBS) volume at the required path for the container images.
   • ECreate an Amazon Elastic Kubernetes Service (Amazon EKS) cluster to run the applications. Configure each node of the cluster to mount the Amazon Elastic File System (Amazon EFS) volume at the required path for the container images.

   Show answer

   Answer: BE

   References

   • AWS documentation

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9. Question 219 · 548 in bank

   A company has an analytics application that uses an AWS Lambda function to process transaction data asynchronously. A developer notices that asynchronous invocations of the Lambda function sometimes fail. When failed Lambda function invocations occur, the developer wants to invoke a second Lambda function to handle errors and log details. Which solution will meet these requirements?

   • AConfigure a Lambda function destination with a failure condition. Specify Lambda function as the destination type. Specify the error-handling Lambda function's Amazon Resource Name (ARN) as the resource.
   • BEnable AWS X-Ray active tracing on the initial Lambda function. Configure X-Ray to capture stack traces of the failed invocations. Invoke the error-handling Lambda function by including the stack traces in the event object.
   • CConfigure a Lambda function trigger with a failure condition. Specify Lambda function as the destination type. Specify the error-handling Lambda function's Amazon Resource Name (ARN) as the resource.
   • DCreate a status check alarm on the initial Lambda function. Configure the alarm to invoke the error-handling Lambda function when the alarm is initiated. Ensure that the alarm passes the stack trace in the event object.

   Show answer

   Answer: A

   Explanation

   Lambda destinations allow you to configure what happens to Lambda function invocation records when an invocation is successful or, in this case, when it fails. By setting a destination for failed invocations, you can specify another Lambda function to handle errors. This setup enables automatic error handling without requiring changes to the application code or the use of additional services for monitoring and triggering error-handling mechanisms. The error-handling Lambda function can then log details, send notifications, or take corrective actions as needed.

   Source: Adapted from community discussion — SerialiDr

   References

   • AWS documentation

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10. Question 220 · 548 in bank

    A company introduced a new feature that should be accessible to only a specific group of premium customers. A developer needs the ability to turn the feature on and off in response to performance and feedback. The developer needs a solution to validate and deploy these configurations quickly without causing any disruptions. What should the developer do to meet these requirements?

    • AUse AWS AppConfig to manage the feature configuration and to validate and deploy changes. Use feature flags to turn the feature on and off.
    • BUse AWS Secrets Manager to securely manage and validate the feature configurations. Enable lifecycle rules to turn the feature on and off.
    • CUse AWS Config to manage the feature configuration and validation. Set up AWS Config rules to turn the feature on and off based on predefined conditions.
    • DUse AWS Systems Manager Parameter Store to store and validate the configuration settings for the feature. Enable lifecycle rules to turn the feature on and off.

    Show answer

    Answer: A

    Explanation

    AWS AppConfig is part of AWS Systems Manager and is designed specifically for managing application configurations and feature toggles in a safe and controlled manner. It allows developers to validate changes before deployment, minimizing the risk of impacting application stability and user experience. Using feature flags with AppConfig enables the developer to turn features on or off without deploying new code, making it an ideal solution for controlling access to new features based on various criteria, including user groups or performance metrics. This method provides a quick and non-disruptive way to manage application features.

    Source: Adapted from community discussion — SerialiDr

    References

    • AWS documentation

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DVA-C02 practice, question 211. 548 questions available.