You are the new IT architect in a company that operates a mobile sleep tracking application. When activated at night, the mobile app sends collected data points of 1 KB every 5 minutes to your middleware. The middleware layer takes care of authenticating the user and writing the data points into an Amazon DynamoDB table. Every morning, you scan the table to extract and aggregate last night’s data on a per-user basis and store the results in Amazon S3. Users are notified via Amazon SMS mobile push notifications that new data is available, parsed, and visualized by the mobile app. The old data is not required by the end-users. Currently, you have around 100k users. You have been tasked to optimize the architecture of the middleware system to lower the cost. What would you recommend?<br>
(Select TWO)

Answer options:

A.Store the data in the DynamoDB table with a Time to Live (TTL) and the data will be deleted automatically.
B.Have the mobile app access Amazon DynamoDB directly instead of JSON files stored on Amazon S3.
C.Introduce an Amazon SQS queue to buffer writes to the Amazon DynamoDB table and reduce provisioned write throughput.
D.Introduce Amazon Elasticache to cache reads from the Amazon DynamoDB table and reduce provisioned read throughput.
E.Write data directly into an Amazon Redshift cluster replacing both Amazon DynamoDB and Amazon S3.

Answer – A and C
Option A is CORRECT because (a) The data stored would be old/obsolete anyways and need not be stored; hence, lowering the cost, and (b) Storing the data in DynamoDB is expensive. Hence, you can set an expiry date so that the data gets deleted automatically.
Option B is incorrect because (a) Storing the data in DynamoDB is more expensive than S3, and (b) giving the app access to DynamoDB to read the data is an operational overhead.
Option C is CORRECT because (a) it uses SQS which reduces the provisioned output cutting down on the costs, and (b) acts as a buffer that absorbs sudden higher load, eliminating going over the provisioned capacity.
Option D is incorrect because the data is only read once before it is stored to S3. The cache would only be useful if you read things multiple times. Also, in this scenario optimizing "write" operations is most desired, not "read" ones.
Option E is incorrect because (a) Amazon Redshift cluster is primarily used for OLAP transactions, not OLTP; hence, not suitable for this scenario, and (b) moving the storage to Redshift cluster means deploying a large number of EC2 instances that are continuously running, which is not a cost-effective solution.
For complete guidelines on working with DynamoDB, please visit the below URL-
http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/GuidelinesForTables.html
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/howitworks-ttl.html