Amazon Forecast is no longer available to new customers. Existing customers of Amazon Forecast can continue to use the service as normal. [Learn more"](https://aws.amazon.com/blogs/machine-learning/transition-your-amazon-forecast-usage-to-amazon-sagemaker-canvas/)

# Enabling Predictor Monitoring
<a name="enabling-predictor-monitoring"></a>

You can enable predictor monitoring when you create the predictor, or you can enable it for an existing predictor. 

**Note**  
Predictor monitoring is only available for AutoPredictors. You can upgrade existing legacy predictors to AutoPredictor. See [Upgrading to AutoPredictor](howitworks-predictor.md#upgrading-autopredictor). 

**Topics**
+ [Enabling Predictor Monitoring for a New Predictor](#enabling-predictor-monitoring-new)
+ [Enabling Predictor Monitoring for an Existing Predictor](#enabling-predictor-monitoring-existing)

## Enabling Predictor Monitoring for a New Predictor
<a name="enabling-predictor-monitoring-new"></a>

You can enable predictor monitoring for a new predictor with the console, AWS CLI, AWS SDKs, and the [CreateAutoPredictor](API_CreateAutoPredictor.md) operation.

------
#### [ Console ]

**To enable Predictor monitoring**

1. Sign in to the AWS Management Console and open the Amazon Forecast console at [https://console.aws.amazon.com/forecast/](https://console.aws.amazon.com/forecast/).

1. From **Dataset groups**, choose your dataset group.

1. In the navigation pane, choose **Predictors**.

1. Choose **Train new predictor**.

1. In the **Predictor configuration** section, choose **Enable monitoring**.

1. Provide values for the following mandatory fields:
   + **Name** - a unique predictor name.
   + **Forecast frequency** - the granularity of your forecasts.
   + **Forecast horizon** - The number of time steps to forecast.

1. Choose **Start** to create an auto predictor with monitoring enabled. You’ll see monitoring results as you use the predictor to generate forecasts and then import more data.

------
#### [ Python ]

To enable predictor monitoring for a new predictor with the SDK for Python (Boto3), use the `create_auto_predictor` method and provide a monitor name in the `MonitoringConfig`. 

The following code creates an auto predictor that makes predictions for 24 (`ForecastHorizon`) days (`ForecastFrequency`) in the future, and specifies `MyPredictorMonitor` as the `MonitorName`. After you generate a forecast and then import more data, you can view the results of predictor monitoring. For more information about retrieving results, see [Viewing Monitoring Results](predictor-monitoring-results.md). 

 For information on required and optional parameters for creating a predictor see [CreateAutoPredictor](API_CreateAutoPredictor.md).

```
import boto3
                            
forecast = boto3.client('forecast')

create_predictor_response = forecast.create_auto_predictor(
    PredictorName = 'predictor_name',
    ForecastHorizon = 24,
    ForecastFrequency = 'D',
    DataConfig = {
        "DatasetGroupArn": "arn:aws:forecast:region:account:dataset-group/datasetGroupName"
    },
    MonitorConifg = {
        "MonitorName": "MyMonitorName"
    }
)
```

------

## Enabling Predictor Monitoring for an Existing Predictor
<a name="enabling-predictor-monitoring-existing"></a>

You can enable predictor monitoring for an existing predictor with the console, AWS CLI, and AWS SDKs.

------
#### [ Console ]

**To enable predictor monitoring**

1. Sign in to the AWS Management Console and open the Amazon Forecast console at [https://console.aws.amazon.com/forecast/](https://console.aws.amazon.com/forecast/).

1. From **Dataset groups**, choose your dataset group.

1. In the navigation pane, choose **Predictors**.

1. Choose your predictor.

1. Navigate to the **Monitoring** tab.

1. In the **Monitoring details** section, choose **Start monitoring** 

   When the **Monitoring status** is Active, predictor monitoring is enabled. After you generate a forecast and then import more data, you can view the results of predictor monitoring. For more information see [Viewing Monitoring Results](predictor-monitoring-results.md)

------
#### [ Python ]

To enable predictor monitoring for an existing predictor with the SDK for Python (Boto3), use the `create_monitor` method. Specify a name for the monitoring, and for `ResourceArn` specify the Amazon Resource Name (ARN) for the predictor to monitor. Use the `describe_monitor` method and provide the monitor ARN to get the status of the monitor. After you generate a forecast and then import more data, you can view the results of predictor monitoring. For more information see [Viewing Monitoring Results](predictor-monitoring-results.md). 

For information on required and optional parameters, see the [CreateMonitor](API_CreateMonitor.md) and [DescribeMonitor](API_DescribeMonitor.md). 

```
import boto3
                            
forecast = boto3.client('forecast')

create_monitor_response = forecast.create_monitor(
    MonitorName = 'monitor_name',
    ResourceArn = 'arn:aws:forecast:region:accountNumber:predictor/predictorName'
)

monitor_arn = create_monitor_response['MonitorArn']

describe_monitor_response = forecast.describe_monitor(
    MonitorArn = monitor_arn
)
print("Monitor status: " + describe_monitor_response['Status'])
```

------