A marketing push will drive more traffic to a web application that uses API Gateway and Lambda. The app stores data in an Amazon Aurora MySQL cluster with one Aurora Replica. Read/write ratio is about 95% reads and 5% writes. How should a SysOps administrator configure the database to scale for the expected higher load?

The correct option is to enable Aurora Auto Scaling to add or remove Aurora Replicas based on the average CPU utilization of the Aurora Replicas. Aurora Replicas are designed for read scaling, and with a 95% read ratio, adding more replicas will effectively distribute the read load. Aurora Auto Scaling automates this process by dynamically adjusting the number of replicas based on predefined metrics like CPU utilization, ensuring the database can handle increased traffic without manual intervention. The other options are incorrect because: Changing the instance class (scaling up/down) of Aurora Replicas is less efficient for read-heavy workloads than adding more replicas. Using AWS Auto Scaling to monitor the Aurora cluster is not the native or most efficient way; Aurora Auto Scaling is purpose-built for this. Monitoring the primary instance's CPU utilization for adding read replicas is not ideal, as read replicas handle read traffic, and their own CPU utilization is the most relevant metric for scaling read capacity.