Use Amazon Aurora Auto Scaling Expand Aurora

• In order to meet your connection and workload requirements, Aurora Auto Scaling Dynamic Adjustment is a preset Aurora copy of the Aurora database cluster Number. Aurora Auto Scaling is available for Aurora MySQL and Aurora PostgreSQL. By using Aurora Auto Scaling, Aurora database clusters can handle sudden increases in connections or workloads. When connections or workloads decrease, Aurora Auto Scaling deletes unwanted copies of Aurora so that you don’t have to pay for unused configuration database instances.
• You can define a scaling strategy and apply it to the Aurora database cluster. Scaling strategy defines the minimum and maximum number of Aurora replicas that Aurora Auto Scaling can manage. According to this strategy, Aurora Auto Scaling adjusts the number of Aurora replicas up or down in response to the actual workload, which is determined using Amazon CloudWatch metrics and target values.
• You can use the AWS Management Console to apply scaling strategies based on predefined metrics. Alternatively, you can use the AWS CLI or Aurora Auto Scaling API to apply scaling strategies based on predefined or custom metrics.

https://docs.aws.amazon.com/zh_cn/AmazonRDS/latest/AuroraUserGuide/Aurora.Integrating.AutoScaling.html

Use predefined metrics

By using predefined metrics, you can quickly define target tracking scaling strategies for Aurora database clusters. It is very suitable for Aurora Auto Scaling. Target tracking and dynamic expansion.

Currently, Aurora supports the following predefined indicators in Aurora Auto Scaling:

• RDSReaderAverageCPUUtilization – The average value of the CPUUtilization metric in CloudWatch across all Aurora replicas in the Aurora database cluster.

• RDSReaderAverageDatabaseConnections – The index of DatabaseConnections in CloudWatch is in the Aurora database cluster The average value across all Aurora copies.