Which solution meets these requirements?
Create new Aurora Serverless DB clusters for development and reporting, then migrate to these new DB clusters.
Upgrade one of the DB clusters to a larger size, and consolidate development and reporting activities on this larger DB cluster.
Use existing DB clusters and stop/start the databases on a routine basis using scheduling tools.
Change the DB clusters to the burstable instance family.
Explanations:
Aurora Serverless is designed for variable workloads, and it automatically scales compute capacity based on demand, helping manage unpredictable spikes in latency while being cost-effective. Migrating to Aurora Serverless would meet the requirement of reducing costs and handling varying demand without significant rework.
Upgrading to a larger instance size does not address the fluctuating demands efficiently and would likely increase costs unnecessarily, as larger instances are more expensive. This also doesn’t solve the issue of momentary latency spikes or scalability for development and reporting workloads.
Stopping and starting databases on a routine basis introduces complexity and could lead to downtime or delays, which is not ideal for development or reporting purposes. Additionally, this doesn’t fully address cost control or scaling needs.
Burstable instances are suitable for workloads with occasional spikes, but they are not the best option for workloads with unpredictable, varying demands over time, especially when cost is a priority. Aurora Serverless would be a better fit for this use case.
I reckon the answer is:
Create new Aurora Serverless DB clusters for development and reporting, then migrate to these new DB clusters.
I chart that the answer is:
Create new Aurora Serverless DB clusters for development and reporting, then migrate to these new DB clusters.