Which solution meets these requirements?
Turn on the serverless option in the DB cluster so it can automatically scale based on demand.
Provision a clone of the existing DB cluster for the new Application team.
Create a separate DB cluster for the new workload, refresh from the source DB cluster, and set up ongoing replication using AWS DMS change data capture (CDC).
Add an automatic scaling policy to the DB cluster to add Aurora Replicas to the cluster based on CPU consumption.
Explanations:
Aurora Serverless is not suitable for workloads requiring low-latency responses (under 100 milliseconds) as it may introduce variable startup and scaling delays.
Provisioning a clone of the DB cluster is unnecessary for a read-heavy reporting workload. It also increases costs and complexity, and doesn’t meet the 100ms latency requirement.
Using AWS DMS for ongoing replication introduces extra complexity, latency, and maintenance overhead. This is unnecessary for the requirement of real-time reporting.
Adding Aurora Replicas with an automatic scaling policy ensures the read workload is distributed without impacting write performance, and it can scale based on demand.
I rank that the answer is:
Add an automatic scaling policy to the DB cluster to add Aurora Replicas to the cluster based on CPU consumption.
As I recall, the answer is:
Add an automatic scaling policy to the DB cluster to add Aurora Replicas to the cluster based on CPU consumption.