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Answer: Create a three-node DynamoDB Accelerator (DAX) cluster. Configure an application to read data by using DAX and to write data directly to the DynamoDB table.
Option B suggests creating a three-node DynamoDB Accelerator (DAX) cluster and configuring the application to read data using DAX while writing data directly to the DynamoDB table. This approach improves read performance significantly by using DAX, which provides in-memory caching and reduces the response time for read-heavy workloads to microseconds. At the same time, writing directly to DynamoDB ensures data consistency and durability, as DAX is an eventually consistent read cache and not designed for write operations. The three-node cluster offers high availability and fault tolerance, as DAX is distributed across multiple Availability Zones (AZs). Therefore, this solution provides high read performance and ensures high availability with minimal latency, making it a suitable choice for the latency-sensitive trading platform.
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A company has a latency-sensitive trading platform that uses Amazon DynamoDB as a storage backend. The company configured the DynamoDB table to use on-demand capacity mode. A solutions architect needs to design a solution to improve the performance of the trading platform. The new solution must ensure high availability for the trading platform. Which solution will meet these requirements with the LEAST latency?
A
Create a two-node DynamoDB Accelerator (DAX) cluster. Configure an application to read and write data by using DAX.
B
Create a three-node DynamoDB Accelerator (DAX) cluster. Configure an application to read data by using DAX and to write data directly to the DynamoDB table.
C
Create a three-node DynamoDB Accelerator (DAX) cluster. Configure an application to read data directly from the DynamoDB table and to write data by using DAX.
D
Create a single-node DynamoDB Accelerator (DAX) cluster. Configure an application to read data by using DAX and to write data directly to the DynamoDB table.
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