Topic 1 Question 485
2 つ選択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?
Increase the write capacity units to the DynamoDB table.
Increase the memory available to the Lambda functions.
Increase the payload size from the smart meters to send more data.
Stream the data into an Amazon Kinesis data stream from API Gateway and process the data in batches.
Collect data in an Amazon SQS FIFO queue, which triggers a Lambda function to process each message
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コメント(6)
- 正解だと思う選択肢: 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.
👍 6mifune2024/06/27 AB because the more memory a Lambda funtion has the faster it reacts
👍 5zapper12342024/06/25- 正解だと思う選択肢: 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.
👍 4vip22024/07/06
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