本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。

# 描述擴展活動以檢查擴展活動的狀態
<a name="endpoint-scaling-query-history"></a>

您可以透過描述擴展活動來檢查自動擴展端點的擴展活動狀態。Application Auto Scaling 提供過去六週內，具有指定之命名空間的擴展活動的描述性資訊。如需詳細資訊，請參閱《Application Auto Scaling 使用者指南》**中的[適用於 Application Auto Scaling 的擴展活動](https://docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-scaling-activities.html)。

若要檢查擴展活動的狀態，請使用 [describe-scaling-activities](https://docs.aws.amazon.com/cli/latest/reference/application-autoscaling/describe-scaling-activities.html) 命令。您無法透過主控台檢查擴展活動的狀態。

**Topics**
+ [描述擴展活動 (AWS CLI)](#endpoint-how-to)
+ [從執行個體配額中找出封鎖的擴展活動 (AWS CLI)](#endpoint-identify-blocked-autoscaling)

## 描述擴展活動 (AWS CLI)
<a name="endpoint-how-to"></a>

若要描述向 Application Auto Scaling 註冊的所有 SageMaker AI 資源的擴展活動，請使用 [describe-scaling-activities](https://docs.aws.amazon.com/cli/latest/reference/application-autoscaling/describe-scaling-activities.html) 命令，為 `--service-namespace` 選項指定 `sagemaker`。

```
aws application-autoscaling describe-scaling-activities \
  --service-namespace sagemaker
```

若要描述特定資源的擴展活動，請納入 `--resource-id` 選項。

```
aws application-autoscaling describe-scaling-activities \
  --service-namespace sagemaker \
  --resource-id endpoint/my-endpoint/variant/my-variant
```

下列範例顯示執行此命令時的輸出。

```
{
    "ActivityId": "activity-id",
    "ServiceNamespace": "sagemaker",
    "ResourceId": "endpoint/my-endpoint/variant/my-variant",
    "ScalableDimension": "sagemaker:variant:DesiredInstanceCount",
    "Description": "string",
    "Cause": "string",
    "StartTime": timestamp,
    "EndTime": timestamp,
    "StatusCode": "string",
    "StatusMessage": "string"
}
```

## 從執行個體配額中找出封鎖的擴展活動 (AWS CLI)
<a name="endpoint-identify-blocked-autoscaling"></a>

橫向擴充 (新增更多執行個體) 時，您可能會達到您的帳戶層級執行個體配額。您可以使用 [describe-scaling-activities](https://docs.aws.amazon.com/cli/latest/reference/application-autoscaling/describe-scaling-activities.html) 命令來檢查是否已達到執行個體配額。當您超出配額時，系統會封鎖自動擴展。

若要檢查是否已達到執行個體配額，請使用 [describe-scaling-activities](https://docs.aws.amazon.com/cli/latest/reference/application-autoscaling/describe-scaling-activities.html) 命令，並指定 `--resource-id` 選項的資源 ID。

```
aws application-autoscaling describe-scaling-activities \
    --service-namespace sagemaker \
    --resource-id endpoint/my-endpoint/variant/my-variant
```

在傳回語法中，檢查 [StatusCode](https://docs.aws.amazon.com/autoscaling/application/APIReference/API_ScalingActivity.html#autoscaling-Type-ScalingActivity-StatusCode) 和 [StatusMessage](https://docs.aws.amazon.com/autoscaling/application/APIReference/API_ScalingActivity.html#autoscaling-Type-ScalingActivity-StatusMessage) 鍵及其相關值。`StatusCode` 傳回 `Failed`。在 `StatusMessage` 內有一則訊息，指出已達到帳戶層級的服務配額。以下是訊息的範例：

```
{
    "ActivityId": "activity-id",
    "ServiceNamespace": "sagemaker",
    "ResourceId": "endpoint/my-endpoint/variant/my-variant",
    "ScalableDimension": "sagemaker:variant:DesiredInstanceCount",
    "Description": "string",
    "Cause": "minimum capacity was set to 110",
    "StartTime": timestamp,
    "EndTime": timestamp,
    "StatusCode": "Failed",
    "StatusMessage": "Failed to set desired instance count to 110. Reason: The 
    account-level service limit 'ml.xx.xxxxxx for endpoint usage' is 1000 
    Instances, with current utilization of 997 Instances and a request delta 
    of 20 Instances. Please contact AWS support to request an increase for this 
    limit. (Service: AmazonSageMaker; Status Code: 400; 
    Error Code: ResourceLimitExceeded; Request ID: request-id)."
}
```