# Configure model auto scaling with the console
<a name="endpoint-auto-scaling-add-console"></a>

**Note**  
You configure auto scaling differently depending on the endpoint type. For a Single Model Endpoint (SME), follow the next procedure, which scales the number of instances for the production variant. For an endpoint that hosts Inference Components, follow the Inference Component procedure later in this section, which scales the number of copies of each Inference Component.

**To configure auto scaling for a model (console)**

1. Open the Amazon SageMaker AI console at [https://console.amazonaws.cn/sagemaker/](https://console.amazonaws.cn/sagemaker/).

1. On the navigation pane, choose **Inference**, and then choose **Endpoints**. 

1. Choose your endpoint, and then for **Endpoint runtime settings**, choose the variant.

1. Choose **Configure auto scaling**.

1. On the **Configure variant automatic scaling** page, for **Variant automatic scaling**, do the following:

   1. For **Minimum instance count**, type the minimum number of instances that you want the scaling policy to maintain. At least 1 instance is required.

   1. For **Maximum instance count**, type the maximum number of instances that you want the scaling policy to maintain.

1. For **Built-in scaling policy**, do the following:

   1. For the **Target metric**, `SageMakerVariantInvocationsPerInstance` is automatically selected for the metric and cannot be changed.

   1. For the **Target value**, type the average number of invocations per instance per minute for the model. To determine this value, follow the guidelines in [Load testing](endpoint-scaling-loadtest.md).

   1. (Optional) For **Scale-in cool down (seconds)** and **Scale-out cool down (seconds)**, enter the amount of time, in seconds, for each cool down period.

   1. (Optional) Select **Disable scale in** if you don’t want auto scaling to terminate instances when traffic decreases.

1. Choose **Save**.

This procedure registers a model as a scalable target with Application Auto Scaling. When you register a model, Application Auto Scaling performs validation checks to ensure the following:
+ The model exists
+ The permissions are sufficient
+ You aren't registering a variant with an instance that is a burstable performance instance such as T2
**Note**  
SageMaker AI doesn't support auto scaling for burstable instances such as T2, because they already allow for increased capacity under increased workloads. For information about burstable performance instances, see [Amazon EC2 instance types](http://www.amazonaws.cn/ec2/instance-types/).

For an endpoint that hosts Inference Components, you configure auto scaling for each Inference Component on the **Inference components** tab. Auto scaling adjusts the number of copies of the Inference Component in response to traffic.

**To configure auto scaling for an Inference Component (console)**

1. Open the Amazon SageMaker AI console at [https://console.amazonaws.cn/sagemaker/](https://console.amazonaws.cn/sagemaker/).

1. In the navigation pane, choose **Inference**, and then choose **Endpoints**.

1. Choose the endpoint.

1. Choose the **Inference components** tab.

1. Select the Inference Component, and then choose **Actions**.

1. Choose **Configure auto scaling**.

1. Set the minimum and maximum number of copies and the target value, and then choose **Save**.