1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312
|
# 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.
# --------------------------------------------------------------------------
"""
FILE: sample_alert_configuration.py
DESCRIPTION:
This sample demonstrates how to create, get, list, query, update, and delete anomaly alert configurations
under your Metrics Advisor account.
USAGE:
python sample_alert_configuration.py
Set the environment variables with your own values before running the sample:
1) METRICS_ADVISOR_ENDPOINT - the endpoint of your Azure Metrics Advisor service
2) METRICS_ADVISOR_SUBSCRIPTION_KEY - Metrics Advisor service subscription key
3) METRICS_ADVISOR_API_KEY - Metrics Advisor service API key
4) METRICS_ADVISOR_DETECTION_CONFIGURATION_ID - the ID of an existing detection configuration
5) METRICS_ADVISOR_HOOK_ID - the ID of hook you would like to be associated with the alert configuration
"""
import os
def sample_create_alert_config():
# [START create_alert_config]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
from azure.ai.metricsadvisor.models import (
MetricAlertConfiguration,
MetricAnomalyAlertScope,
TopNGroupScope,
MetricAnomalyAlertConditions,
SeverityCondition,
MetricBoundaryCondition,
MetricAnomalyAlertSnoozeCondition,
)
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
detection_configuration_id = os.getenv("METRICS_ADVISOR_DETECTION_CONFIGURATION_ID")
hook_id = os.getenv("METRICS_ADVISOR_HOOK_ID")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
alert_config = client.create_alert_configuration(
name="my alert config",
description="alert config description",
cross_metrics_operator="AND",
metric_alert_configurations=[
MetricAlertConfiguration(
detection_configuration_id=detection_configuration_id,
alert_scope=MetricAnomalyAlertScope(
scope_type="WholeSeries"
),
alert_conditions=MetricAnomalyAlertConditions(
severity_condition=SeverityCondition(
min_alert_severity="Low",
max_alert_severity="High"
)
)
),
MetricAlertConfiguration(
detection_configuration_id=detection_configuration_id,
alert_scope=MetricAnomalyAlertScope(
scope_type="TopN",
top_n_group_in_scope=TopNGroupScope(
top=10,
period=5,
min_top_count=5
)
),
alert_conditions=MetricAnomalyAlertConditions(
metric_boundary_condition=MetricBoundaryCondition(
direction="Up",
upper=50
)
),
alert_snooze_condition=MetricAnomalyAlertSnoozeCondition(
auto_snooze=2,
snooze_scope="Metric",
only_for_successive=True
)
),
],
hook_ids=[hook_id]
)
return alert_config
# [END create_alert_config]
def sample_get_alert_config(alert_config_id):
# [START get_alert_config]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
config = client.get_alert_configuration(alert_config_id)
print("Alert config ID: {}".format(config.id))
print("Alert config name: {}".format(config.name))
print("Description: {}".format(config.description))
print("Ids of hooks associated with alert: {}".format(config.hook_ids))
print("Use {} operator for multiple alert conditions\n".format(config.cross_metrics_operator))
print("Alert uses detection configuration ID: {}".format(
config.metric_alert_configurations[0].detection_configuration_id
))
print("Alert scope type: {}".format(config.metric_alert_configurations[0].alert_scope.scope_type))
print("Alert severity condition: min- {}, max- {}".format(
config.metric_alert_configurations[0].alert_conditions.severity_condition.min_alert_severity,
config.metric_alert_configurations[0].alert_conditions.severity_condition.max_alert_severity,
))
print("\nAlert uses detection configuration ID: {}".format(
config.metric_alert_configurations[1].detection_configuration_id
))
print("Alert scope type: {}".format(config.metric_alert_configurations[1].alert_scope.scope_type))
print("Top N: {}".format(config.metric_alert_configurations[1].alert_scope.top_n_group_in_scope.top))
print("Point count used to look back: {}".format(
config.metric_alert_configurations[1].alert_scope.top_n_group_in_scope.period
))
print("Min top count: {}".format(
config.metric_alert_configurations[1].alert_scope.top_n_group_in_scope.min_top_count
))
print("Alert metric boundary condition direction: {}, upper bound: {}".format(
config.metric_alert_configurations[1].alert_conditions.metric_boundary_condition.direction,
config.metric_alert_configurations[1].alert_conditions.metric_boundary_condition.upper,
))
print("Alert snooze condition, snooze point count: {}".format(
config.metric_alert_configurations[1].alert_snooze_condition.auto_snooze,
))
print("Alert snooze scope: {}".format(
config.metric_alert_configurations[1].alert_snooze_condition.snooze_scope,
))
print("Snooze only for successive anomalies?: {}".format(
config.metric_alert_configurations[1].alert_snooze_condition.only_for_successive,
))
# [END get_alert_config]
def sample_list_alert_configs():
# [START list_alert_configs]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
detection_configuration_id = os.getenv("METRICS_ADVISOR_DETECTION_CONFIGURATION_ID")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
configs = client.list_alert_configurations(detection_configuration_id)
for config in configs:
print("Alert config name: {}".format(config.name))
print("Alert description: {}".format(config.description))
print("Ids of hooks associated with alert: {}\n".format(config.hook_ids))
# [END list_alert_configs]
def sample_list_alerts(alert_config_id):
# [START list_alerts]
import datetime
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorClient
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
client = MetricsAdvisorClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
results = client.list_alerts(
alert_configuration_id=alert_config_id,
start_time=datetime.datetime(2021, 1, 1),
end_time=datetime.datetime(2021, 9, 9),
time_mode="AnomalyTime",
)
tolist = []
for result in results:
tolist.append(result)
print("Alert id: {}".format(result.id))
print("Create time: {}".format(result.created_time))
return tolist
# [END list_alerts]
def sample_list_anomalies_for_alert(alert_config_id, alert_id):
# [START list_anomalies_for_alert]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorClient
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
client = MetricsAdvisorClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
results = client.list_anomalies(
alert_configuration_id=alert_config_id,
alert_id=alert_id,
)
for result in results:
print("Create time: {}".format(result.created_time))
print("Severity: {}".format(result.severity))
print("Status: {}".format(result.status))
# [END list_anomalies_for_alert]
def sample_update_alert_config(alert_config):
# [START update_alert_config]
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
from azure.ai.metricsadvisor.models import (
MetricAlertConfiguration,
MetricAnomalyAlertScope,
MetricAnomalyAlertConditions,
MetricBoundaryCondition
)
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
detection_configuration_id = os.getenv("METRICS_ADVISOR_DETECTION_CONFIGURATION_ID")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
alert_config.name = "updated config name"
additional_alert = MetricAlertConfiguration(
detection_configuration_id=detection_configuration_id,
alert_scope=MetricAnomalyAlertScope(
scope_type="SeriesGroup",
series_group_in_scope={'region': 'Shenzhen'}
),
alert_conditions=MetricAnomalyAlertConditions(
metric_boundary_condition=MetricBoundaryCondition(
direction="Down",
lower=5
)
)
)
alert_config.metric_alert_configurations.append(additional_alert)
updated = client.update_alert_configuration(
alert_config,
cross_metrics_operator="OR",
description="updated alert config"
)
print("Updated alert name: {}".format(updated.name))
print("Updated alert description: {}".format(updated.description))
print("Updated cross metrics operator: {}".format(updated.cross_metrics_operator))
print("Updated alert condition configuration scope type: {}".format(
updated.metric_alert_configurations[2].alert_scope.scope_type
))
# [END update_alert_config]
def sample_delete_alert_config(alert_config_id):
# [START delete_alert_config]
from azure.core.exceptions import ResourceNotFoundError
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient
service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT")
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY")
api_key = os.getenv("METRICS_ADVISOR_API_KEY")
client = MetricsAdvisorAdministrationClient(service_endpoint,
MetricsAdvisorKeyCredential(subscription_key, api_key))
client.delete_alert_configuration(alert_config_id)
try:
client.get_alert_configuration(alert_config_id)
except ResourceNotFoundError:
print("Alert configuration successfully deleted.")
# [END delete_alert_config]
if __name__ == '__main__':
print("---Creating anomaly alert configuration...")
alert_config = sample_create_alert_config()
print("Anomaly alert configuration successfully created...")
print("\n---Get an anomaly alert configuration...")
sample_get_alert_config(alert_config.id)
print("\n---List anomaly alert configurations...")
sample_list_alert_configs()
print("\n---Query anomaly detection results...")
alerts = sample_list_alerts(alert_config.id)
if len(alerts) > 0:
print("\n---Query anomalies using alert id...")
alert_id = alerts[0].id
print("alert_id: " + alert_id)
sample_list_anomalies_for_alert(alert_config.id, alert_id)
print("\n---Update an anomaly alert configuration...")
sample_update_alert_config(alert_config)
print("\n---Delete an anomaly alert configuration...")
sample_delete_alert_config(alert_config.id)
|