async def sample_create_detection_config_async():
# [START create_anomaly_detection_config_async]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential
from azure.ai.metricsadvisor.aio import MetricsAdvisorAdministrationClient
from azure.ai.metricsadvisor.models import (
ChangeThresholdCondition,
HardThresholdCondition,
SmartDetectionCondition,
SuppressCondition,
MetricDetectionCondition,
)
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
metric_id = os.getenv("METRICS_ADVISOR_METRIC_ID")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
change_threshold_condition = ChangeThresholdCondition(
anomaly_detector_direction="Both",
change_percentage=20,
shift_point=10,
within_range=True,
suppress_condition=SuppressCondition(
min_number=5,
min_ratio=2
)
)
hard_threshold_condition = HardThresholdCondition(
anomaly_detector_direction="Up",
upper_bound=100,
suppress_condition=SuppressCondition(
min_number=2,
min_ratio=2
)
)
smart_detection_condition = SmartDetectionCondition(
anomaly_detector_direction="Up",
sensitivity=10,
suppress_condition=SuppressCondition(
min_number=2,
min_ratio=2
)
)
async with client:
detection_config = await client.create_metric_anomaly_detection_configuration(
name="my_detection_config",
metric_id=metric_id,
description="anomaly detection config for metric",
whole_series_detection_condition=MetricDetectionCondition(
cross_conditions_operator="OR",
change_threshold_condition=change_threshold_condition,
hard_threshold_condition=hard_threshold_condition,
smart_detection_condition=smart_detection_condition
)
)
return detection_config
def _create_detection_config_for_update(self, name):
try:
data_feed = self._create_data_feed(name)
detection_config_name = create_random_name("testupdated")
detection_config = self.admin_client.create_detection_configuration(
name=detection_config_name,
metric_id=data_feed.metric_ids['cost'],
description="My test metric anomaly detection configuration",
whole_series_detection_condition=MetricDetectionCondition(
condition_operator="AND",
smart_detection_condition=SmartDetectionCondition(
sensitivity=50,
anomaly_detector_direction="Both",
suppress_condition=SuppressCondition(min_number=5,
min_ratio=5)),
hard_threshold_condition=HardThresholdCondition(
anomaly_detector_direction="Both",
suppress_condition=SuppressCondition(min_number=5,
min_ratio=5),
lower_bound=0,
upper_bound=100),
change_threshold_condition=ChangeThresholdCondition(
change_percentage=50,
shift_point=30,
within_range=True,
anomaly_detector_direction="Both",
suppress_condition=SuppressCondition(min_number=2,
min_ratio=2))),
series_detection_conditions=[
MetricSingleSeriesDetectionCondition(
series_key={
"city": "Shenzhen",
"category": "Jewelry"
},
smart_detection_condition=SmartDetectionCondition(
anomaly_detector_direction="Both",
sensitivity=63,
suppress_condition=SuppressCondition(
min_number=1, min_ratio=100)))
],
series_group_detection_conditions=[
MetricSeriesGroupDetectionCondition(
series_group_key={"city": "Sao Paulo"},
smart_detection_condition=SmartDetectionCondition(
anomaly_detector_direction="Both",
sensitivity=63,
suppress_condition=SuppressCondition(
min_number=1, min_ratio=100)))
])
return detection_config, data_feed
except Exception as e:
self.admin_client.delete_data_feed(data_feed.id)
raise e
async def create_detection_config(self, name):
detection_config_name = self.create_random_name(name)
if is_live():
self.variables["detection_config_name"] = detection_config_name
detection_config = await self.client.create_detection_configuration(
name=self.variables["detection_config_name"],
metric_id=self.variables["data_feed_metric_id"],
description="My test metric anomaly detection configuration",
whole_series_detection_condition=MetricDetectionCondition(
condition_operator="AND",
smart_detection_condition=SmartDetectionCondition(
sensitivity=50,
anomaly_detector_direction="Both",
suppress_condition=SuppressCondition(min_number=5,
min_ratio=5)),
hard_threshold_condition=HardThresholdCondition(
anomaly_detector_direction="Both",
suppress_condition=SuppressCondition(min_number=5,
min_ratio=5),
lower_bound=0,
upper_bound=100),
change_threshold_condition=ChangeThresholdCondition(
change_percentage=50,
shift_point=30,
within_range=True,
anomaly_detector_direction="Both",
suppress_condition=SuppressCondition(min_number=2,
min_ratio=2))),
series_detection_conditions=[
MetricSingleSeriesDetectionCondition(
series_key={
"region": "Beijing",
"category": "Shoes Handbags & Sunglasses"
},
smart_detection_condition=SmartDetectionCondition(
anomaly_detector_direction="Both",
sensitivity=63,
suppress_condition=SuppressCondition(min_number=1,
min_ratio=100)))
],
series_group_detection_conditions=[
MetricSeriesGroupDetectionCondition(
series_group_key={"region": "Beijing"},
smart_detection_condition=SmartDetectionCondition(
anomaly_detector_direction="Both",
sensitivity=63,
suppress_condition=SuppressCondition(min_number=1,
min_ratio=100)))
])
if is_live():
self.variables["detection_config_id"] = detection_config.id
return detection_config