Exam AWS Certified Solutions Architect - Professional SAP-C02 topic 1 question 485 discussion

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.

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

By increasing the DynamoDB write capacity units and streaming the data into a Kinesis data stream for batch processing, you can address the throughput limitations, reduce Lambda invocation overhead, and improve the overall performance and scalability of the smart meter data processing pipeline. The other options are either not applicable or may not resolve the issues effectively: B. Increasing the memory available to the Lambda functions may not resolve the issues caused by the high volume of concurrent requests and the need for batching. C. Increasing the payload size from the smart meters is not necessary and may even exacerbate the issues by increasing the processing overhead for each data point. E. Collecting data in an Amazon SQS FIFO queue and triggering a Lambda function for each message would still result in a high number of Lambda invocations and may not provide significant performance improvements compared to processing data in batches from a Kinesis data stream.

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

A and D

need batch execution so i think AD is correct