List Monitor Evaluations
forecastservice_list_monitor_evaluations | R Documentation |
Returns a list of the monitoring evaluation results and predictor events collected by the monitor resource during different windows of time¶
Description¶
Returns a list of the monitoring evaluation results and predictor events collected by the monitor resource during different windows of time.
For information about monitoring see predictor-monitoring. For more information about retrieving monitoring results see Viewing Monitoring Results.
Usage¶
Arguments¶
NextToken
If the result of the previous request was truncated, the response includes a
NextToken
. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.MaxResults
The maximum number of monitoring results to return.
MonitorArn
[required] The Amazon Resource Name (ARN) of the monitor resource to get results from.
Filters
An array of filters. For each filter, provide a condition and a match statement. The condition is either
IS
orIS_NOT
, which specifies whether to include or exclude the resources that match the statement from the list. The match statement consists of a key and a value.Filter properties
Condition
- The condition to apply. Valid values areIS
andIS_NOT
.Key
- The name of the parameter to filter on. The only valid value isEvaluationState
.Value
- The value to match. Valid values are onlySUCCESS
orFAILURE
.
For example, to list only successful monitor evaluations, you would specify:
"Filters": [ { "Condition": "IS", "Key": "EvaluationState", "Value": "SUCCESS" } ]
Value¶
A list with the following syntax:
list(
NextToken = "string",
PredictorMonitorEvaluations = list(
list(
ResourceArn = "string",
MonitorArn = "string",
EvaluationTime = as.POSIXct(
"2015-01-01"
),
EvaluationState = "string",
WindowStartDatetime = as.POSIXct(
"2015-01-01"
),
WindowEndDatetime = as.POSIXct(
"2015-01-01"
),
PredictorEvent = list(
Detail = "string",
Datetime = as.POSIXct(
"2015-01-01"
)
),
MonitorDataSource = list(
DatasetImportJobArn = "string",
ForecastArn = "string",
PredictorArn = "string"
),
MetricResults = list(
list(
MetricName = "string",
MetricValue = 123.0
)
),
NumItemsEvaluated = 123,
Message = "string"
)
)
)