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Amazon AWS Certified Developer - Associate Sample Questions (Q460-Q465):
NEW QUESTION # 460
An application is real-time processing millions of events that are received through an API.
What service could be used to allow multiple consumers to process the data concurrently and MOST cost-effectively?
- A. Amazon SNS with fanout to an SQS FIFO (first-in, first-out) queue for each application
- B. Amazon Kinesis Firehose
- C. Amazon Kinesis Data Streams
- D. Amazon SNS with fanout to an SQS queue for each application
Answer: C
Explanation:
Amazon Kinesis Data Streams is designed for real-time data streaming and allows multiple consumers to process data concurrently and in real-time. It can handle millions of events and provides a scalable and cost-effective solution for handling high-throughput data streams.
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NEW QUESTION # 461
A healthcare company uses AWS Amplify to host a patient management system. The system uses Amazon API Gateway to expose RESTful APIs. The backend logic of the system is handled by AWS Lambda functions.
One of the Lambda functions receives patient data that includes personally identifiable information (PII). The Lambda function sends the patient data to an Amazon DynamoDB table. The company must encrypt all patient data at rest and in transit before the data is stored in DynamoDB.
- A. Use an AWS Step Functions workflow to transfer the data to an Amazon SQS queue. Configure a Lambda function to encrypt the data in the queue before sending the data to the DynamoDB table.
- B. Configure a DynamoDB stream on the table to invoke a Lambda function. Configure the Lambda function to use an AWS KMS key to encrypt the DynamoDB table and to update the table.
- C. Configure the Lambda function to use AWS KMS keys with the AWS Database Encryption SDK to encrypt the patient data before sending the data to DynamoDB.
- D. Use AWS managed AWS KMS keys to encrypt the data in the DynamoDB table.
Answer: C
Explanation:
* Why Option A is Correct:Encrypting PII at rest and in transit before storing it in DynamoDB ensures end-to-end security. Using the AWS Database Encryption SDK with KMS keys allows the Lambda function to encrypt data before transmission, meeting security and compliance requirements.
* Why Other Options are Incorrect:
* Option B: While AWS-managed KMS keys encrypt DynamoDB data at rest, they do not encrypt data in transit.
* Option C: DynamoDB streams process updates after the data is written to the table, failing to encrypt PII in transit.
* Option D: Step Functions and SQS add unnecessary complexity and still require encryption logic for both transit and at rest.
* AWS Documentation References:
* Encrypting Data in DynamoDB
* AWS Database Encryption SDK
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NEW QUESTION # 462
A developer maintains a serverless application that uses an Amazon API Gateway REST API to invoke an AWS Lambda function by using a non-proxy integration. The Lambda function returns data, which is stored in Amazon DynamoDB.
Several application users begin to receive intermittent errors from the API. The developer examines Amazon CloudWatch Logs for the Lambda function and discovers several ProvisionedThroughputExceededException errors.
The developer needs to resolve the errors and ensure that the errors do not reoccur.
- A. Update the REST API to send requests on an Amazon SQS queue. Configure the Lambda function to process requests from the queue.
- B. Use provisioned capacity mode for the DynamoDB table, and assign sufficient capacity units. Configure the Lambda function to retry requests with exponential backoff.
- C. Update the REST API to invoke the Lambda function asynchronously.
- D. Configure a usage plan for the REST API.
Answer: B
Explanation:
Comprehensive and Detailed Step-by-Step
Option A: Provisioned Capacity with Exponential Backoff:
Using provisioned capacity ensures sufficient throughput for the DynamoDB table.
Configuring the Lambda function to implement exponential backoff retries reduces the chance of exceeding capacity during peak usage.
This combination addresses the root cause (ProvisionedThroughputExceededException) and prevents errors without overprovisioning.
Why Other Options Are Incorrect:
Option B: Using SQS adds unnecessary latency and complexity. The issue lies in DynamoDB throughput, not request management.
Option C: A usage plan for the API does not address throughput issues in DynamoDB.
Option D: Invoking the Lambda function asynchronously does not resolve the DynamoDB capacity issue and might lead to delayed processing.
Reference:
DynamoDB Provisioned Throughput Documentation
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NEW QUESTION # 463
A developer has written the following IAM policy to provide access to an Amazon S3 bucket:
Which access does the policy allow regarding the s3:GetObject and s3:PutObject actions?
- A. Access on all buckets except the "DOC-EXAMPLE-BUCKET" bucket
- B. Access on all buckets that start with "DOC-EXAMPLE-BUCKET" except the
"DOC-EXAMPLE-BUCKET/secrets" bucket - C. Access on all objects in the "DOC-EXAMPLE-BUCKET" bucket along with access to all S3 actions for objects in the "DOC-EXAMPLE-BUCKET" bucket that start with "secrets"
- D. Access on all objects in the "DOC-EXAMPLE-BUCKET" bucket except on objects that start with
"secrets"
Answer: D
Explanation:
Explanation
The IAM policy shown in the image is a resource-based policy that grants or denies access to an S3 bucket based on certain conditions. The first statement allows access to any S3 action on any object in the
"DOC-EXAMPLE-BUCKET" bucket when the request is made over HTTPS (the value of aws:SecureTransport is true). The second statement denies access to the s3:GetObject and s3:PutObject actions on any object in the "DOC-EXAMPLE-BUCKET/secrets" prefix when the request is made over HTTP (the value of aws:SecureTransport is false). Therefore, the policy allows access on all objects in the
"DOC-EXAMPLE-BUCKET" bucket except on objects that start with "secrets". Reference: Using IAM policies for Amazon S3
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NEW QUESTION # 464
A company is expanding the compatibility of its photo-sharing mobile app to hundreds of additional devices with unique screen dimensions and resolutions. Photos are stored in Amazon S3 in their original format and resolution. The company uses an Amazon CloudFront distribution to serve the photos. The app includes the dimension and resolution of the display as GET parameters with every request.
A developer needs to implement a solution that optimizes the photos that are served to each device to reduce load time and increase photo quality.
Which solution will meet these requirements MOST cost-effectively?
- A. Use S3 Batch Operations to invoke an AWS Lambda function to create new variants of the photos with the required dimensions and resolutions. Create a dynamic CloudFront origin that automatically maps the request of each device to the corresponding photo variant.
- B. Use S3 Batch Operations to invoke an AWS Lambda function to create new variants of the photos with the required dimensions and resolutions. Create a Lambda@Edge function to route requests to the corresponding photo variant by using request headers.
- C. Create a Lambda@Edge function that optimizes the photos upon request and returns the photos as a response. Change the CloudFront TTL cache policy to the maximum value possible.
- D. Create a Lambda@Edge function that optimizes the photos upon request and returns the photos as a response. In the same function, store a copy of the processed photos on Amazon S3 for subsequent requests.
Answer: D
Explanation:
https://aws.amazon.com/blogs/networking-and-content-delivery/resizing-images-with-amazon- cloudfront-lambdaedge-aws-cdn-blog/
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NEW QUESTION # 465
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