A company has an application that uses an Amazon DynamoDB table as its data store. During normal business days, the throughput requirements from the application are uniform and consist of 5 standard write calls per second to the DynamoDB table. Each write call has 2 KB of data.
For 1 hour each day, the company runs an additional automated job on the DynamoDB table that makes 20 write requests per second. No other application writes to the DynamoDB table. The DynamoDB table does not have to meet any additional capacity requirements.
How should a database specialist configure the DynamoDB table's capacity to meet these requirements MOST cost-effectively?
A. Use DynamoDB provisioned capacity with 5 WCUs and auto scaling.
B. Use DynamoDB provisioned capacity with 5 WCUs and a write-through cache that DynamoDB Accelerator (DAX) provides.
C. Use DynamoDB provisioned capacity with 10 WCUs and auto scaling.
D. Use DynamoDB provisioned capacity with 10 WCUs and no auto scaling.
For 1 hour each day, the company runs an additional automated job on the DynamoDB table that makes 20 write requests per second. No other application writes to the DynamoDB table. The DynamoDB table does not have to meet any additional capacity requirements.
How should a database specialist configure the DynamoDB table's capacity to meet these requirements MOST cost-effectively?
A. Use DynamoDB provisioned capacity with 5 WCUs and auto scaling.
B. Use DynamoDB provisioned capacity with 5 WCUs and a write-through cache that DynamoDB Accelerator (DAX) provides.
C. Use DynamoDB provisioned capacity with 10 WCUs and auto scaling.
D. Use DynamoDB provisioned capacity with 10 WCUs and no auto scaling.
