Which option would ensure that the correct nodes are always available for the appropriate workload while meeting these requirements?

A company has a heterogeneous six-node production Amazon Aurora DB cluster that handles online transaction processing (OLTP) for the core business and OLAP reports for the human resources department. To match compute resources to the use case, the company has decided to have the reporting workload for the human resources department be directed to two small nodes in the Aurora DB cluster, while every other workload goes to four large nodes in the same DB cluster.

Which option would ensure that the correct nodes are always available for the appropriate workload while meeting these requirements?
A . Use the writer endpoint for OLTP and the reader endpoint for the OLAP reporting workload.
B . Use automatic scaling for the Aurora Replica to have the appropriate number of replicas for the desired workload.
C . Create additional readers to cater to the different scenarios.
D . Use custom endpoints to satisfy the different workloads.

View Answer

Answer: D

Explanation:

https://aws.amazon.com/about-aws/whats-new/2018/11/amazon-aurora-simplifies-workload-management-with-custom-endpoints/

You can now create custom endpoints for Amazon Aurora databases. This allows you to distribute and load balance workloads across different sets of database instances in your Aurora cluster. For example, you may provision a set of Aurora Replicas to use an instance type with higher memory capacity in order to run an analytics workload. A custom endpoint can then help you route the analytics workload to these appropriately-configured instances, while keeping other instances in your cluster isolated from this workload. As you add or remove instances from the custom endpoint to match your workload, the endpoint helps spread the load around.