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Amazon EC2 Auto Scaling
Scaling Policies
Target tracking
A target tracking scaling policy automatically scales the capacity of your Auto Scaling group based on a target metric value. This allows your application to maintain optimal performance and cost efficiency without manual intervention.
With target tracking, you select a metric and a target value to represent the ideal average utilization or throughput level for your application. Amazon EC2 Auto Scaling creates and manages the CloudWatch alarms that invoke scaling events when the metric deviates from the target. As an example, this is similar to how a thermostat maintains a target temperature.
For example, let's say that you currently have an application that runs on two instances, and you want the CPU utilization of the Auto Scaling group to stay at around 50 percent when the load on the application changes. This gives you extra capacity to handle traffic spikes without maintaining an excessive number of idle resources.
When you create a target tracking scaling policy with a predefined metric type, you choose one metric from the following list of predefined metrics:
Step and simple scaling
Step scaling and simple scaling policies scale the capacity of your Auto Scaling group in predefined increments based on CloudWatch alarms. You can define separate scaling policies to handle scaling out (increasing capacity) and scaling in (decreasing capacity) when an alarm threshold is breached.
With step scaling and simple scaling, you create and manage the CloudWatch alarms that invoke the scaling process. When an alarm is breached, Amazon EC2 Auto Scaling initiates the scaling policy associated with that alarm.
To use step scaling, you first create a CloudWatch alarm that monitors a metric for your Auto Scaling group. Define the metric, threshold value, and number of evaluation periods that determine an alarm breach. Then, create a step scaling policy that defines how to scale your group when the alarm threshold is breached.
Add the step adjustments in the policy. You can define different step adjustments based on the breach size of the alarm. For example:
Similar to step scaling policies, simple scaling policies require you to create CloudWatch alarms for your scaling policies. In the policies that you create, you must also define whether to add or remove instances, and how many, or set the group to an exact size.
One of the main differences between step scaling policies and simple scaling policies is the step adjustments that you get with step scaling policies. With step scaling, you can make bigger or smaller changes to the size of the group based on the step adjustments that you specify.
Scheduled scaling
With scheduled scaling, you can set up automatic scaling for your application based on predictable load changes. You create scheduled actions that increase or decrease your group's desired capacity at specific times.
For example, you experience a regular weekly traffic pattern where load increases midweek and declines toward the end of the week. You can configure a scaling schedule in Amazon EC2 Auto Scaling that aligns with this pattern:
These scheduled scaling actions allow you to optimize costs and performance. Your application has sufficient capacity to handle the midweek traffic peak, but does not over-provision unneeded capacity at other times.
You can use scheduled scaling and scaling policies together to get the benefits of both approaches to scaling. After a scheduled scaling action runs, the scaling policy can continue to make decisions about whether to further scale capacity. This helps you ensure that you have sufficient capacity to handle the load for your application. While your application scales to match demand, current capacity must fall within the minimum and maximum capacity that was set by your scheduled action.
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