[AutoPR monitor/resource-manager] Add dynamic metric alert api

azure-mgmt-monitor/azure/mgmt/monitor/models/__init__.py

@@ -100,11 +100,13 @@
     from .metric_alert_status_properties_py3 import MetricAlertStatusProperties
     from .metric_alert_status_py3 import MetricAlertStatus
     from .metric_alert_status_collection_py3 import MetricAlertStatusCollection
-    from .metric_dimension_py3 import MetricDimension
     from .metric_criteria_py3 import MetricCriteria
     from .metric_alert_single_resource_multiple_metric_criteria_py3 import MetricAlertSingleResourceMultipleMetricCriteria
+    from .metric_dimension_py3 import MetricDimension
     from .multi_metric_criteria_py3 import MultiMetricCriteria
     from .metric_alert_multiple_resource_multiple_metric_criteria_py3 import MetricAlertMultipleResourceMultipleMetricCriteria
+    from .dynamic_threshold_failing_periods_py3 import DynamicThresholdFailingPeriods
+    from .dynamic_metric_criteria_py3 import DynamicMetricCriteria
     from .source_py3 import Source
     from .schedule_py3 import Schedule
     from .action_py3 import Action
@@ -216,11 +218,13 @@
     from .metric_alert_status_properties import MetricAlertStatusProperties
     from .metric_alert_status import MetricAlertStatus
     from .metric_alert_status_collection import MetricAlertStatusCollection
-    from .metric_dimension import MetricDimension
     from .metric_criteria import MetricCriteria
     from .metric_alert_single_resource_multiple_metric_criteria import MetricAlertSingleResourceMultipleMetricCriteria
+    from .metric_dimension import MetricDimension
     from .multi_metric_criteria import MultiMetricCriteria
     from .metric_alert_multiple_resource_multiple_metric_criteria import MetricAlertMultipleResourceMultipleMetricCriteria
+    from .dynamic_threshold_failing_periods import DynamicThresholdFailingPeriods
+    from .dynamic_metric_criteria import DynamicMetricCriteria
     from .source import Source
     from .schedule import Schedule
     from .action import Action
@@ -372,11 +376,13 @@
     'MetricAlertStatusProperties',
     'MetricAlertStatus',
     'MetricAlertStatusCollection',
-    'MetricDimension',
     'MetricCriteria',
     'MetricAlertSingleResourceMultipleMetricCriteria',
+    'MetricDimension',
     'MultiMetricCriteria',
     'MetricAlertMultipleResourceMultipleMetricCriteria',
+    'DynamicThresholdFailingPeriods',
+    'DynamicMetricCriteria',
     'Source',
     'Schedule',
     'Action',

azure-mgmt-monitor/azure/mgmt/monitor/models/dynamic_metric_criteria.py

@@ -0,0 +1,83 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from .multi_metric_criteria import MultiMetricCriteria
+
+
+class DynamicMetricCriteria(MultiMetricCriteria):
+    """Criterion for dynamic threshold.
+
+    All required parameters must be populated in order to send to Azure.
+
+    :param additional_properties: Unmatched properties from the message are
+     deserialized this collection
+    :type additional_properties: dict[str, object]
+    :param name: Required. Name of the criteria.
+    :type name: str
+    :param metric_name: Required. Name of the metric.
+    :type metric_name: str
+    :param metric_namespace: Namespace of the metric.
+    :type metric_namespace: str
+    :param time_aggregation: Required. the criteria time aggregation types.
+    :type time_aggregation: object
+    :param dimensions: List of dimension conditions.
+    :type dimensions: list[~azure.mgmt.monitor.models.MetricDimension]
+    :param criterion_type: Required. Constant filled by server.
+    :type criterion_type: str
+    :param operator: Required. The operator used to compare the metric value
+     against the threshold.
+    :type operator: object
+    :param alert_sensitivity: Required. The extent of deviation required to
+     trigger an alert. This will affect how tight the threshold is to the
+     metric series pattern.
+    :type alert_sensitivity: object
+    :param failing_periods: Required. The minimum number of violations
+     required within the selected lookback time window required to raise an
+     alert.
+    :type failing_periods:
+     ~azure.mgmt.monitor.models.DynamicThresholdFailingPeriods
+    :param ignore_data_before: Use this option to set the date from which to
+     start learning the metric historical data and calculate the dynamic
+     thresholds (in ISO8601 format)
+    :type ignore_data_before: datetime
+    """
+
+    _validation = {
+        'name': {'required': True},
+        'metric_name': {'required': True},
+        'time_aggregation': {'required': True},
+        'criterion_type': {'required': True},
+        'operator': {'required': True},
+        'alert_sensitivity': {'required': True},
+        'failing_periods': {'required': True},
+    }
+
+    _attribute_map = {
+        'additional_properties': {'key': '', 'type': '{object}'},
+        'name': {'key': 'name', 'type': 'str'},
+        'metric_name': {'key': 'metricName', 'type': 'str'},
+        'metric_namespace': {'key': 'metricNamespace', 'type': 'str'},
+        'time_aggregation': {'key': 'timeAggregation', 'type': 'object'},
+        'dimensions': {'key': 'dimensions', 'type': '[MetricDimension]'},
+        'criterion_type': {'key': 'criterionType', 'type': 'str'},
+        'operator': {'key': 'operator', 'type': 'object'},
+        'alert_sensitivity': {'key': 'alertSensitivity', 'type': 'object'},
+        'failing_periods': {'key': 'failingPeriods', 'type': 'DynamicThresholdFailingPeriods'},
+        'ignore_data_before': {'key': 'ignoreDataBefore', 'type': 'iso-8601'},
+    }
+
+    def __init__(self, **kwargs):
+        super(DynamicMetricCriteria, self).__init__(**kwargs)
+        self.operator = kwargs.get('operator', None)
+        self.alert_sensitivity = kwargs.get('alert_sensitivity', None)
+        self.failing_periods = kwargs.get('failing_periods', None)
+        self.ignore_data_before = kwargs.get('ignore_data_before', None)
+        self.criterion_type = 'DynamicThresholdCriterion'

azure-mgmt-monitor/azure/mgmt/monitor/models/dynamic_metric_criteria_py3.py

@@ -0,0 +1,83 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from .multi_metric_criteria_py3 import MultiMetricCriteria
+
+
+class DynamicMetricCriteria(MultiMetricCriteria):
+    """Criterion for dynamic threshold.
+
+    All required parameters must be populated in order to send to Azure.
+
+    :param additional_properties: Unmatched properties from the message are
+     deserialized this collection
+    :type additional_properties: dict[str, object]
+    :param name: Required. Name of the criteria.
+    :type name: str
+    :param metric_name: Required. Name of the metric.
+    :type metric_name: str
+    :param metric_namespace: Namespace of the metric.
+    :type metric_namespace: str
+    :param time_aggregation: Required. the criteria time aggregation types.
+    :type time_aggregation: object
+    :param dimensions: List of dimension conditions.
+    :type dimensions: list[~azure.mgmt.monitor.models.MetricDimension]
+    :param criterion_type: Required. Constant filled by server.
+    :type criterion_type: str
+    :param operator: Required. The operator used to compare the metric value
+     against the threshold.
+    :type operator: object
+    :param alert_sensitivity: Required. The extent of deviation required to
+     trigger an alert. This will affect how tight the threshold is to the
+     metric series pattern.
+    :type alert_sensitivity: object
+    :param failing_periods: Required. The minimum number of violations
+     required within the selected lookback time window required to raise an
+     alert.
+    :type failing_periods:
+     ~azure.mgmt.monitor.models.DynamicThresholdFailingPeriods
+    :param ignore_data_before: Use this option to set the date from which to
+     start learning the metric historical data and calculate the dynamic
+     thresholds (in ISO8601 format)
+    :type ignore_data_before: datetime
+    """
+
+    _validation = {
+        'name': {'required': True},
+        'metric_name': {'required': True},
+        'time_aggregation': {'required': True},
+        'criterion_type': {'required': True},
+        'operator': {'required': True},
+        'alert_sensitivity': {'required': True},
+        'failing_periods': {'required': True},
+    }
+
+    _attribute_map = {
+        'additional_properties': {'key': '', 'type': '{object}'},
+        'name': {'key': 'name', 'type': 'str'},
+        'metric_name': {'key': 'metricName', 'type': 'str'},
+        'metric_namespace': {'key': 'metricNamespace', 'type': 'str'},
+        'time_aggregation': {'key': 'timeAggregation', 'type': 'object'},
+        'dimensions': {'key': 'dimensions', 'type': '[MetricDimension]'},
+        'criterion_type': {'key': 'criterionType', 'type': 'str'},
+        'operator': {'key': 'operator', 'type': 'object'},
+        'alert_sensitivity': {'key': 'alertSensitivity', 'type': 'object'},
+        'failing_periods': {'key': 'failingPeriods', 'type': 'DynamicThresholdFailingPeriods'},
+        'ignore_data_before': {'key': 'ignoreDataBefore', 'type': 'iso-8601'},
+    }
+
+    def __init__(self, *, name: str, metric_name: str, time_aggregation, operator, alert_sensitivity, failing_periods, additional_properties=None, metric_namespace: str=None, dimensions=None, ignore_data_before=None, **kwargs) -> None:
+        super(DynamicMetricCriteria, self).__init__(additional_properties=additional_properties, name=name, metric_name=metric_name, metric_namespace=metric_namespace, time_aggregation=time_aggregation, dimensions=dimensions, **kwargs)
+        self.operator = operator
+        self.alert_sensitivity = alert_sensitivity
+        self.failing_periods = failing_periods
+        self.ignore_data_before = ignore_data_before
+        self.criterion_type = 'DynamicThresholdCriterion'

azure-mgmt-monitor/azure/mgmt/monitor/models/dynamic_threshold_failing_periods.py

@@ -0,0 +1,44 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from msrest.serialization import Model
+
+
+class DynamicThresholdFailingPeriods(Model):
+    """The minimum number of violations required within the selected lookback time
+    window required to raise an alert.
+
+    All required parameters must be populated in order to send to Azure.
+
+    :param number_of_evaluation_periods: Required. The number of aggregated
+     lookback points. The lookback time window is calculated based on the
+     aggregation granularity (windowSize) and the selected number of aggregated
+     points.
+    :type number_of_evaluation_periods: float
+    :param min_failing_periods_to_alert: Required. The number of violations to
+     trigger an alert. Should be smaller or equal to numberOfEvaluationPeriods.
+    :type min_failing_periods_to_alert: float
+    """
+
+    _validation = {
+        'number_of_evaluation_periods': {'required': True},
+        'min_failing_periods_to_alert': {'required': True},
+    }
+
+    _attribute_map = {
+        'number_of_evaluation_periods': {'key': 'numberOfEvaluationPeriods', 'type': 'float'},
+        'min_failing_periods_to_alert': {'key': 'minFailingPeriodsToAlert', 'type': 'float'},
+    }
+
+    def __init__(self, **kwargs):
+        super(DynamicThresholdFailingPeriods, self).__init__(**kwargs)
+        self.number_of_evaluation_periods = kwargs.get('number_of_evaluation_periods', None)
+        self.min_failing_periods_to_alert = kwargs.get('min_failing_periods_to_alert', None)

azure-mgmt-monitor/azure/mgmt/monitor/models/dynamic_threshold_failing_periods_py3.py

@@ -0,0 +1,44 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from msrest.serialization import Model
+
+
+class DynamicThresholdFailingPeriods(Model):
+    """The minimum number of violations required within the selected lookback time
+    window required to raise an alert.
+
+    All required parameters must be populated in order to send to Azure.
+
+    :param number_of_evaluation_periods: Required. The number of aggregated
+     lookback points. The lookback time window is calculated based on the
+     aggregation granularity (windowSize) and the selected number of aggregated
+     points.
+    :type number_of_evaluation_periods: float
+    :param min_failing_periods_to_alert: Required. The number of violations to
+     trigger an alert. Should be smaller or equal to numberOfEvaluationPeriods.
+    :type min_failing_periods_to_alert: float
+    """
+
+    _validation = {
+        'number_of_evaluation_periods': {'required': True},
+        'min_failing_periods_to_alert': {'required': True},
+    }
+
+    _attribute_map = {
+        'number_of_evaluation_periods': {'key': 'numberOfEvaluationPeriods', 'type': 'float'},
+        'min_failing_periods_to_alert': {'key': 'minFailingPeriodsToAlert', 'type': 'float'},
+    }
+
+    def __init__(self, *, number_of_evaluation_periods: float, min_failing_periods_to_alert: float, **kwargs) -> None:
+        super(DynamicThresholdFailingPeriods, self).__init__(**kwargs)
+        self.number_of_evaluation_periods = number_of_evaluation_periods
+        self.min_failing_periods_to_alert = min_failing_periods_to_alert

azure-mgmt-monitor/azure/mgmt/monitor/models/metric_criteria.py

@@ -20,53 +20,48 @@ class MetricCriteria(MultiMetricCriteria):
     :param additional_properties: Unmatched properties from the message are
      deserialized this collection
     :type additional_properties: dict[str, object]
-    :param criterion_type: Required. Constant filled by server.
-    :type criterion_type: str
     :param name: Required. Name of the criteria.
     :type name: str
     :param metric_name: Required. Name of the metric.
     :type metric_name: str
     :param metric_namespace: Namespace of the metric.
     :type metric_namespace: str
-    :param operator: Required. the criteria operator.
-    :type operator: object
     :param time_aggregation: Required. the criteria time aggregation types.
     :type time_aggregation: object
+    :param dimensions: List of dimension conditions.
+    :type dimensions: list[~azure.mgmt.monitor.models.MetricDimension]
+    :param criterion_type: Required. Constant filled by server.
+    :type criterion_type: str
+    :param operator: Required. the criteria operator.
+    :type operator: object
     :param threshold: Required. the criteria threshold value that activates
      the alert.
     :type threshold: float
-    :param dimensions: List of dimension conditions.
-    :type dimensions: list[~azure.mgmt.monitor.models.MetricDimension]
     """
 
     _validation = {
-        'criterion_type': {'required': True},
         'name': {'required': True},
         'metric_name': {'required': True},
-        'operator': {'required': True},
         'time_aggregation': {'required': True},
+        'criterion_type': {'required': True},
+        'operator': {'required': True},
         'threshold': {'required': True},
     }
 
     _attribute_map = {
         'additional_properties': {'key': '', 'type': '{object}'},
-        'criterion_type': {'key': 'criterionType', 'type': 'str'},
         'name': {'key': 'name', 'type': 'str'},
         'metric_name': {'key': 'metricName', 'type': 'str'},
         'metric_namespace': {'key': 'metricNamespace', 'type': 'str'},
-        'operator': {'key': 'operator', 'type': 'object'},
         'time_aggregation': {'key': 'timeAggregation', 'type': 'object'},
-        'threshold': {'key': 'threshold', 'type': 'float'},
         'dimensions': {'key': 'dimensions', 'type': '[MetricDimension]'},
+        'criterion_type': {'key': 'criterionType', 'type': 'str'},
+        'operator': {'key': 'operator', 'type': 'object'},
+        'threshold': {'key': 'threshold', 'type': 'float'},
     }
 
     def __init__(self, **kwargs):
         super(MetricCriteria, self).__init__(**kwargs)
-        self.name = kwargs.get('name', None)
-        self.metric_name = kwargs.get('metric_name', None)
-        self.metric_namespace = kwargs.get('metric_namespace', None)
         self.operator = kwargs.get('operator', None)
-        self.time_aggregation = kwargs.get('time_aggregation', None)
         self.threshold = kwargs.get('threshold', None)
-        self.dimensions = kwargs.get('dimensions', None)
         self.criterion_type = 'StaticThresholdCriterion'