Which solution will meet these requirements with the LEAST amount of operational overhead?
Set up a DynamoDB Accelerator (DAX) cluster. Route all read requests through DAX.
Set up Amazon ElastiCache for Redis between the DynamoDB table and the web application. Route all read requests through Redis.
Set up Amazon ElastiCache for Memcached between the DynamoDB table and the web application. Route all read requests through Memcached.
Set up Amazon DynamoDB Streams on the table, and have AWS Lambda read from the table and populate Amazon ElastiCache. Route all read requests through ElastiCache.
Explanations:
DynamoDB Accelerator (DAX) is specifically designed to improve the performance of DynamoDB by caching read requests, which directly decreases latency. It requires minimal operational overhead as it integrates seamlessly with DynamoDB and automatically manages the caching layer.
While Amazon ElastiCache for Redis can help reduce latency, it introduces additional complexity and operational overhead, as it requires setting up and managing the Redis cluster and maintaining synchronization with the DynamoDB data.
Similar to option B, Amazon ElastiCache for Memcached can also reduce latency, but it requires additional management and introduces operational overhead for cache maintenance and synchronization with DynamoDB, making it less optimal than DAX.
Setting up DynamoDB Streams and using AWS Lambda to populate ElastiCache adds unnecessary complexity and operational overhead. This solution requires more components to manage and does not provide the same seamless integration as DAX for reducing latency in read requests.
As far as I can tell, the answer is:
Set up a DynamoDB Accelerator (DAX) cluster. Route all read requests through DAX.
I design that the answer is:
Set up a DynamoDB Accelerator (DAX) cluster. Route all read requests through DAX.