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Copy file name to clipboardExpand all lines: docs/dyn/monitoring_v3.projects.alertPolicies.html
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@@ -179,6 +179,9 @@ <h3>Method Details</h3>
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"duration": "A String", # The amount of time that a time series must violate the threshold to be considered failing. Currently, only values that are a multiple of a minute--e.g., 0, 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. When choosing a duration, it is useful to keep in mind the frequency of the underlying time series data (which may also be affected by any alignments specified in the aggregations field); a good duration is long enough so that a single outlier does not generate spurious alerts, but short enough that unhealthy states are detected and alerted on quickly.
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"evaluationMissingData": "A String", # A condition control that determines how metric-threshold conditions are evaluated when data stops arriving.
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"filter": "A String", # Required. A filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies which time series should be compared with the threshold.The filter is similar to the one that is specified in the ListTimeSeries request (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.timeSeries/list) (that call is useful to verify the time series that will be retrieved / processed). The filter must specify the metric type and the resource type. Optionally, it can specify resource labels and metric labels. This field must not exceed 2048 Unicode characters in length.
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"forecastOptions": { # Options used when forecasting the time series and testing the predicted value against the threshold. # When this field is present, the MetricThreshold condition forecasts whether the time series is predicted to violate the threshold within the forecast_horizion. When this field is not set, the MetricThreshold tests the current value of the timeseries against the threshold.
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"forecastHorizon": "A String", # Required. The length of time into the future to forecast whether a time series will violate the threshold. If the predicted value is found to violate the threshold, and the violation is observed in all forecasts made for the configured duration, then the time series is considered to be failing.
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},
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"thresholdValue": 3.14, # A value against which to compare the time series.
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"trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
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"count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
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"duration": "A String", # The amount of time that a time series must violate the threshold to be considered failing. Currently, only values that are a multiple of a minute--e.g., 0, 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. When choosing a duration, it is useful to keep in mind the frequency of the underlying time series data (which may also be affected by any alignments specified in the aggregations field); a good duration is long enough so that a single outlier does not generate spurious alerts, but short enough that unhealthy states are detected and alerted on quickly.
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"evaluationMissingData": "A String", # A condition control that determines how metric-threshold conditions are evaluated when data stops arriving.
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"filter": "A String", # Required. A filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies which time series should be compared with the threshold.The filter is similar to the one that is specified in the ListTimeSeries request (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.timeSeries/list) (that call is useful to verify the time series that will be retrieved / processed). The filter must specify the metric type and the resource type. Optionally, it can specify resource labels and metric labels. This field must not exceed 2048 Unicode characters in length.
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"forecastOptions": { # Options used when forecasting the time series and testing the predicted value against the threshold. # When this field is present, the MetricThreshold condition forecasts whether the time series is predicted to violate the threshold within the forecast_horizion. When this field is not set, the MetricThreshold tests the current value of the timeseries against the threshold.
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"forecastHorizon": "A String", # Required. The length of time into the future to forecast whether a time series will violate the threshold. If the predicted value is found to violate the threshold, and the violation is observed in all forecasts made for the configured duration, then the time series is considered to be failing.
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},
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"thresholdValue": 3.14, # A value against which to compare the time series.
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"trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
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"count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
@@ -442,6 +448,9 @@ <h3>Method Details</h3>
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"duration": "A String", # The amount of time that a time series must violate the threshold to be considered failing. Currently, only values that are a multiple of a minute--e.g., 0, 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. When choosing a duration, it is useful to keep in mind the frequency of the underlying time series data (which may also be affected by any alignments specified in the aggregations field); a good duration is long enough so that a single outlier does not generate spurious alerts, but short enough that unhealthy states are detected and alerted on quickly.
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"evaluationMissingData": "A String", # A condition control that determines how metric-threshold conditions are evaluated when data stops arriving.
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"filter": "A String", # Required. A filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies which time series should be compared with the threshold.The filter is similar to the one that is specified in the ListTimeSeries request (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.timeSeries/list) (that call is useful to verify the time series that will be retrieved / processed). The filter must specify the metric type and the resource type. Optionally, it can specify resource labels and metric labels. This field must not exceed 2048 Unicode characters in length.
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"forecastOptions": { # Options used when forecasting the time series and testing the predicted value against the threshold. # When this field is present, the MetricThreshold condition forecasts whether the time series is predicted to violate the threshold within the forecast_horizion. When this field is not set, the MetricThreshold tests the current value of the timeseries against the threshold.
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"forecastHorizon": "A String", # Required. The length of time into the future to forecast whether a time series will violate the threshold. If the predicted value is found to violate the threshold, and the violation is observed in all forecasts made for the configured duration, then the time series is considered to be failing.
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},
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"thresholdValue": 3.14, # A value against which to compare the time series.
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"trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
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"count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
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"duration": "A String", # The amount of time that a time series must violate the threshold to be considered failing. Currently, only values that are a multiple of a minute--e.g., 0, 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. When choosing a duration, it is useful to keep in mind the frequency of the underlying time series data (which may also be affected by any alignments specified in the aggregations field); a good duration is long enough so that a single outlier does not generate spurious alerts, but short enough that unhealthy states are detected and alerted on quickly.
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"evaluationMissingData": "A String", # A condition control that determines how metric-threshold conditions are evaluated when data stops arriving.
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"filter": "A String", # Required. A filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies which time series should be compared with the threshold.The filter is similar to the one that is specified in the ListTimeSeries request (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.timeSeries/list) (that call is useful to verify the time series that will be retrieved / processed). The filter must specify the metric type and the resource type. Optionally, it can specify resource labels and metric labels. This field must not exceed 2048 Unicode characters in length.
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"forecastOptions": { # Options used when forecasting the time series and testing the predicted value against the threshold. # When this field is present, the MetricThreshold condition forecasts whether the time series is predicted to violate the threshold within the forecast_horizion. When this field is not set, the MetricThreshold tests the current value of the timeseries against the threshold.
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"forecastHorizon": "A String", # Required. The length of time into the future to forecast whether a time series will violate the threshold. If the predicted value is found to violate the threshold, and the violation is observed in all forecasts made for the configured duration, then the time series is considered to be failing.
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},
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"thresholdValue": 3.14, # A value against which to compare the time series.
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"trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
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"count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
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"duration": "A String", # The amount of time that a time series must violate the threshold to be considered failing. Currently, only values that are a multiple of a minute--e.g., 0, 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. When choosing a duration, it is useful to keep in mind the frequency of the underlying time series data (which may also be affected by any alignments specified in the aggregations field); a good duration is long enough so that a single outlier does not generate spurious alerts, but short enough that unhealthy states are detected and alerted on quickly.
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"evaluationMissingData": "A String", # A condition control that determines how metric-threshold conditions are evaluated when data stops arriving.
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"filter": "A String", # Required. A filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies which time series should be compared with the threshold.The filter is similar to the one that is specified in the ListTimeSeries request (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.timeSeries/list) (that call is useful to verify the time series that will be retrieved / processed). The filter must specify the metric type and the resource type. Optionally, it can specify resource labels and metric labels. This field must not exceed 2048 Unicode characters in length.
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"forecastOptions": { # Options used when forecasting the time series and testing the predicted value against the threshold. # When this field is present, the MetricThreshold condition forecasts whether the time series is predicted to violate the threshold within the forecast_horizion. When this field is not set, the MetricThreshold tests the current value of the timeseries against the threshold.
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"forecastHorizon": "A String", # Required. The length of time into the future to forecast whether a time series will violate the threshold. If the predicted value is found to violate the threshold, and the violation is observed in all forecasts made for the configured duration, then the time series is considered to be failing.
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},
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"thresholdValue": 3.14, # A value against which to compare the time series.
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"trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
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"count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
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"duration": "A String", # The amount of time that a time series must violate the threshold to be considered failing. Currently, only values that are a multiple of a minute--e.g., 0, 60, 120, or 300 seconds--are supported. If an invalid value is given, an error will be returned. When choosing a duration, it is useful to keep in mind the frequency of the underlying time series data (which may also be affected by any alignments specified in the aggregations field); a good duration is long enough so that a single outlier does not generate spurious alerts, but short enough that unhealthy states are detected and alerted on quickly.
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"evaluationMissingData": "A String", # A condition control that determines how metric-threshold conditions are evaluated when data stops arriving.
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"filter": "A String", # Required. A filter (https://cloud.google.com/monitoring/api/v3/filters) that identifies which time series should be compared with the threshold.The filter is similar to the one that is specified in the ListTimeSeries request (https://cloud.google.com/monitoring/api/ref_v3/rest/v3/projects.timeSeries/list) (that call is useful to verify the time series that will be retrieved / processed). The filter must specify the metric type and the resource type. Optionally, it can specify resource labels and metric labels. This field must not exceed 2048 Unicode characters in length.
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"forecastOptions": { # Options used when forecasting the time series and testing the predicted value against the threshold. # When this field is present, the MetricThreshold condition forecasts whether the time series is predicted to violate the threshold within the forecast_horizion. When this field is not set, the MetricThreshold tests the current value of the timeseries against the threshold.
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"forecastHorizon": "A String", # Required. The length of time into the future to forecast whether a time series will violate the threshold. If the predicted value is found to violate the threshold, and the violation is observed in all forecasts made for the configured duration, then the time series is considered to be failing.
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},
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"thresholdValue": 3.14, # A value against which to compare the time series.
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"trigger": { # Specifies how many time series must fail a predicate to trigger a condition. If not specified, then a {count: 1} trigger is used. # The number/percent of time series for which the comparison must hold in order for the condition to trigger. If unspecified, then the condition will trigger if the comparison is true for any of the time series that have been identified by filter and aggregations, or by the ratio, if denominator_filter and denominator_aggregations are specified.
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"count": 42, # The absolute number of time series that must fail the predicate for the condition to be triggered.
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