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Question 484

A utility company wants to collect usage data every 5 minutes from its smart meters to facilitate time-of-use metering. When a meter sends data to AWS, the data is sent to Amazon API Gateway, processed by an AWS Lambda function. and stored in an Amazon DynamoDB table. During the pilot phase, the Lambda functions took from 3 to 5 seconds to complete.

As more smart meters are deployed, the engineers notice the Lambda functions are taking from 1 to 2 minutes to complete. The functions are also increasing in duration as new types of metrics are collected from the devices. There are many ProvisionedThroughputExceededException errors while performing PUT operations on DynamoDB, and there are also many TooManyRequestsException errors from Lambda.

Which combination of changes will resolve these issues? (Choose two.)

    Correct Answer: A, D

    To resolve the issues faced by the utility company, increasing the write capacity units of the DynamoDB table will help in handling the increased load and avoiding ProvisionedThroughputExceededException errors. Streaming the data into an Amazon Kinesis data stream from API Gateway and processing the data in batches is also beneficial. This approach will reduce the load on the Lambda functions and optimize the data processing workflow, addressing both the TooManyRequestsException errors and the increased duration of Lambda executions.

Discussion
zapper1234

AB because the more memory a Lambda funtion has the faster it reacts

mifuneOptions: AD

I would go with Increasing the write capacity units to the DynamoDB table and Stream the data into an Amazon Kinesis data stream from API Gateway and process the data in batches. I think that processing the data in batches is much better than increasing the lambda functions memory.

wbedairOptions: AD

A and D

ujizane

need batch execution so i think AD is correct

vip2Options: AD

Kinesis allows to process data in batches, which can help reduce the number of requests and the load on your Lambda functions and DynamoDB.