Which solution will meet these requirements MOST cost-effectively?
Give the developers the ability to launch separate Amazon Aurora instances. Set up a process to shut down Aurora instances at the end of the workday and to start Aurora instances at the beginning of the next workday.
Develop an AWS Service Catalog product that enforces size restrictions for launching Amazon Aurora instances. Give the developers access to launch the product when they need a development database.
Create an Amazon Aurora Serverless cluster. Develop an AWS Service Catalog product to launch databases in the cluster with the default capacity settings. Grant the developers access to the product.
Monitor AWS Trusted Advisor checks for idle Amazon RDS databases. Create a process to terminate identified idle RDS databases.
Explanations:
While giving developers the ability to launch separate Amazon Aurora instances allows for flexibility, it may not be cost-effective as Aurora instances incur charges even when not in use. Additionally, manually shutting down and starting instances adds administrative overhead.
Developing an AWS Service Catalog product to enforce size restrictions is a good governance practice but does not address the issue of cost-effectiveness directly. Aurora instances would still incur costs when not in use.
Creating an Amazon Aurora Serverless cluster is the most cost-effective solution because it automatically scales up or down based on demand, meaning costs are incurred only during active use. Implementing a Service Catalog product provides ease of use for developers.
Monitoring idle Amazon RDS databases and terminating them is reactive rather than proactive. This method may lead to interruptions during development when databases are needed and may still incur costs when the databases are running, even if they are idle.