How can the developer improve the performance of these requests?
(Choose two.)
Create an Amazon ElastiCache cluster. Configure the application to cache data in the cluster.
Create a DynamoDB Accelerator (DAX) cluster. Configure the application to use the DAX cluster for DynamoDB requests.
Configure the application to make strongly consistent read requests against the DynamoDB table.
Increase the read capacity of the DynamoDB table.
Enable DynamoDB adaptive capacity.
Explanations:
While creating an Amazon ElastiCache cluster can help with caching frequently accessed data and reduce the load on DynamoDB, it is not the optimal solution for improving performance specifically for DynamoDB requests. DAX is a more direct enhancement for DynamoDB read performance.
DynamoDB Accelerator (DAX) is designed specifically to improve the performance of read requests to DynamoDB. It provides a fully managed, in-memory cache that can significantly reduce read latencies, making it an effective choice for applications with a high volume of read requests against a small dataset.
Making strongly consistent read requests can result in higher latencies and reduced throughput, as strongly consistent reads require a read from the latest data and can impact performance. This is generally not a recommended approach for improving read performance in DynamoDB.
Increasing the read capacity of the DynamoDB table can improve performance, but it does not address the inherent latency issues associated with network calls and can lead to higher costs without guaranteeing a significant improvement in speed for read-heavy workloads.
Enabling DynamoDB adaptive capacity helps optimize the use of provisioned throughput by allocating more capacity to “hot” partitions, but it does not directly improve the performance of read requests. It’s more about efficiently managing existing capacity rather than enhancing speed for frequent reads.