Target tracking scaling policies for Application Auto Scaling

Do not create, edit, or delete the CloudWatch alarms that are used with a target tracking scaling policy. Application Auto Scaling creates and manages the CloudWatch alarms that are associated with your target tracking scaling policies and deletes them when no longer needed.

To ensure application availability, Application Auto Scaling scales out proportionally to the metric as fast as it can, but scales in more gradually.

If the metric is missing data points, this causes the CloudWatch alarm state to change to INSUFFICIENT_DATA. When this happens, Application Auto Scaling cannot scale your scalable target until new data points are found. For information about creating alarms when there is insufficient data, see Monitoring with CloudWatch alarms.

You may see gaps between the target value and the actual metric data points. This is because Application Auto Scaling always acts conservatively by rounding up or down when it determines how much capacity to add or remove. This prevents it from adding insufficient capacity or removing too much capacity. However, for a scalable target with a small capacity, the actual metric data points might seem far from the target value.

For a scalable target with a larger capacity, adding or removing capacity causes less of a gap between the target value and the actual metric data points.

A target tracking scaling policy assumes that it should perform scale out when the specified metric is above the target value. You cannot use a target tracking scaling policy to scale out when the specified metric is below the target value.

You can have multiple target tracking scaling policies for a scalable target, provided that each of them uses a different metric. The intention of Application Auto Scaling is to always prioritize availability, so its behavior differs depending on whether the target tracking policies are ready for scale out or scale in. It will scale out the scalable target if any of the target tracking policies are ready for scale out, but will scale in only if all of the target tracking policies (with the scale-in portion enabled) are ready to scale in.

If multiple scaling policies instruct the scalable target to scale out or in at the same time, Application Auto Scaling scales based on the policy that provides the largest capacity for both scale in and scale out. This provides greater flexibility to cover multiple scenarios and ensures that there is always enough capacity to process your workloads.

You can disable the scale-in portion of a target tracking scaling policy. This feature provides the flexibility to use a different method for scale in than you use for scale out. For example, you can use a step scaling policy for scale in while using a target tracking scaling policy for scale out.

We recommend caution, however, when using target tracking scaling policies with step scaling policies because conflicts between these policies can cause undesirable behavior. For example, if the step scaling policy initiates a scale-in activity before the target tracking policy is ready to scale in, the scale-in activity will not be blocked. After the scale-in activity completes, the target tracking policy could instruct the scalable target to scale out again.

Not all metrics work for target tracking. This can be important when you are specifying a custom metric. The metric must be a valid utilization metric and describe how busy a scalable target is. The metric value must increase or decrease proportionally to the capacity of the scalable target so that the metric data can be used to proportionally scale the scalable target.

To use the ALBRequestCountPerTarget metric, you must specify the ResourceLabel parameter to identify the target group that is associated with the metric.

When a metric emits real 0 values to CloudWatch (for example, ALBRequestCountPerTarget), Application Auto Scaling can scale in to 0 when there is no traffic to your application. To have your scalable target scale in to 0 when no requests are routed it, the scalable target's minimum capacity must be set to 0.

When you create a target tracking scaling policy with a custom metric, you can use metric math to combine metrics. For more information, see Create a target tracking scaling policy for Application Auto Scaling using metric math.

To see whether the service you are using supports specifying a custom metric in the console, consult the documentation for that service.

With the scale-out cooldown period, the intention is to continuously (but not excessively) scale out. After Application Auto Scaling successfully scales out using a target tracking scaling policy, it starts to calculate the cooldown time. The scaling policy won't increase the desired capacity again unless either a larger scale out is triggered or the cooldown period ends. While the scale-out cooldown period is in effect, the capacity added by the initiating scale-out activity is calculated as part of the desired capacity for the next scale-out activity.

With the scale-in cooldown period, the intention is to scale in conservatively to protect your application's availability, so scale-in activities are blocked until the cooldown period has expired. However, if another alarm triggers a scale-out activity during the scale-in cooldown period, Application Auto Scaling scales out the target immediately. In this case, the scale-in cooldown period stops and doesn't complete.

register-scalable-target to register AWS or custom resources as scalable targets (a resource that Application Auto Scaling can scale), and to suspend and resume scaling.

put-scaling-policy to add or modify scaling policies for an existing scalable target.

describe-scaling-activities to return information about scaling activities in an AWS Region.

describe-scaling-policies to return information about scaling policies in an AWS Region.

delete-scaling-policy to delete a scaling-policy.

The scalable target can't be an Amazon EMR cluster. Target tracking scaling policies are not supported for Amazon EMR.

When an Amazon MSK cluster is the scalable target, scale in is disabled and cannot be enabled.

You cannot use the RegisterScalableTarget or PutScalingPolicy API operations to update an AWS Auto Scaling scaling plan. For information about using scaling plans, see the AWS Auto Scaling documentation.