Exam AWS Certified Developer Associate topic 1 question 308 discussion

Ans: A Key points: "Read heavy", "access data quickly", "can tolerate stale data" To achieve: "FEWEST" possible (RCUs) For items up to 4 KB in size, one RCU can perform one strongly consistent read request per second. For items up to 4 KB in size, one RCU can perform two eventually consistent read requests per second. Transactional read requests require two RCUs to perform one read per second for items up to 4 KB. For example, a strongly consistent read of an 8 KB item would require two RCUs, an eventually consistent read of an 8 KB item would require one RCU, and a transactional read of an 8 KB item would require four RCUs. https://aws.amazon.com/dynamodb/pricing/provisioned/

I agree with A

A is the correct answer, I totally agree with you. In order to have a quick access to data and stale data can be tolerate, we can use an eventually consinstent read that will use half of RCUs compared to a strongly consistent read. The strongly consistent read ensure that the user retrive the most recent data even if the case is not updated but require more effort.

The correct solution is option A. Reading the table by using eventually consistent reads will meet the requirements with the fewest possible read capacity units (RCUs). When using eventually consistent reads, DynamoDB returns the latest data that it has in its cache, which may be slightly out of date. This is acceptable in this case because the microservice can tolerate stale data. Using eventually consistent reads will reduce the number of RCUs required to read the table because DynamoDB does not need to wait for all copies of the data to be updated before returning the data. Using strongly consistent reads or transactional reads would require more RCUs because these read modes require DynamoDB to wait for all copies of the data to be updated before returning the data. Using PartiQL queries would not be necessary because the requirements can be met using regular read operations.

A. Read the table by using eventually consistent reads.

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