Describes an outlier type: What characterizes it, and how many were found during a period of time.
| Name | Type | Description | Notes |
|---|---|---|---|
| count | int | The number outliers found with the same characterization. | [optional] |
| type_diff_messages | bool | [optional] | |
| type_fails | bool | Outlier is characterized by a high rate of exceptions, or error types. | [optional] |
| type_new_messages | bool | Outlier is characterized by high volume of new activity. | [optional] |
| type_ongoing | bool | Outlier is characterized by an ongoing activity below the thresholds, in recent hours. | [optional] |
| type_volume | bool | Outlier is characterized by high volume of activity, in general. | [optional] |
| type_vulnerable_objects | bool | Outlier is characterized by a high activity rate on vulnerable object groups. | [optional] |
from ibm_gdsc_sdk_saas.models.outliersenginev3_outlier_type_stats import Outliersenginev3OutlierTypeStats
# TODO update the JSON string below
json = "{}"
# create an instance of Outliersenginev3OutlierTypeStats from a JSON string
outliersenginev3_outlier_type_stats_instance = Outliersenginev3OutlierTypeStats.from_json(json)
# print the JSON string representation of the object
print(Outliersenginev3OutlierTypeStats.to_json())
# convert the object into a dict
outliersenginev3_outlier_type_stats_dict = outliersenginev3_outlier_type_stats_instance.to_dict()
# create an instance of Outliersenginev3OutlierTypeStats from a dict
outliersenginev3_outlier_type_stats_from_dict = Outliersenginev3OutlierTypeStats.from_dict(outliersenginev3_outlier_type_stats_dict)