Overview
It contains a collection of Amazon EC2 instances that are treated as a logical grouping for the purposes of automatic scaling and management.
An Auto Scaling group also enables you to use EC2 Auto Scaling features such as health check replacements and scaling policies.
The size of an Auto Scaling group depends on the number of instances that you set as the desired capacity.
You can adjust its size to meet demand, either manually or by using automatic scaling.
An Auto Scaling group starts by launching enough instances to meet its desired capacity.
It maintains this number of instances by performing periodic health checks on the instances in the group.
The Auto Scaling group continues to maintain a fixed number of instances even if an instance becomes unhealthy.
If an instance becomes unhealthy, the group terminates the unhealthy instance and launches another instance to replace it.
You can use scaling policies to increase or decrease the number of instances in your group dynamically to meet changing conditions.
CloudWatch Metrics
A CloudWatch metric represents a time-ordered set of data points; it is like a variable to monitor, and the data points as representing the values of that variable over time.
You can use these metrics to verify that your system is performing as expected or scale in or scale out your EC2 Instances depending on a certain metric.
Default Termination Policy
The default termination policy is designed to help ensure that your instances span Availability Zones evenly for high availability.
The default policy is kept generic and flexible to cover a range of scenarios.
Within the selected Availability Zone, the default termination policy behaviour is as follows:
Determine which instances to terminate so as to align the remaining instances to the allocation strategy for the On-Demand or Spot Instance that is terminating.
Determine whether any of the instances use the oldest launch template or configuration.
After applying all of the above criteria, if there are multiple unprotected instances to terminate, determine which instances are closest to the next billing hour.
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