How can the company improve the cache behavior to increase application performance?
Increase the size of the DAX cluster.
Configure DAX to be an item cache with no query cache
Use eventually consistent reads instead of strongly consistent reads.
Create a new DAX cluster with a higher TTL for the item cache.
Explanations:
Increasing the size of the DAX cluster may help with handling more traffic or higher concurrency but does not address the issue of strongly consistent reads. Since the application does not require strong consistency, this option does not improve the cache performance.
Configuring DAX to be an item cache with no query cache does not resolve the issue of strong consistency affecting performance. Query caching can help reduce latency for query operations, and removing it could worsen performance for those queries.
Using eventually consistent reads instead of strongly consistent reads allows DAX to effectively cache the results, significantly improving response times. DAX is optimized for eventually consistent reads, which can provide faster access compared to strongly consistent reads that bypass the cache.
Creating a new DAX cluster with a higher TTL for the item cache does not address the fundamental issue of strongly consistent reads being processed slowly. A higher TTL would only affect how long items remain in the cache but does not change the caching behavior for strongly consistent queries.