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|
# 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.
# --------------------------------------------------------------------------
import os
import uuid
import datetime
from devtools_testutils import AzureRecordedTestCase, is_live
from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential
from azure.ai.metricsadvisor.models import (
SqlServerDataFeedSource,
DataFeedSchema,
DataFeedMetric,
DataFeedDimension,
DataFeedGranularity,
DataFeedIngestionSettings,
DataFeedMissingDataPointFillSettings,
DataFeedRollupSettings,
MetricAlertConfiguration,
MetricAnomalyAlertScope,
MetricAnomalyAlertConditions,
MetricBoundaryCondition,
TopNGroupScope,
SeverityCondition,
MetricDetectionCondition,
MetricSeriesGroupDetectionCondition,
MetricSingleSeriesDetectionCondition,
SmartDetectionCondition,
SuppressCondition,
ChangeThresholdCondition,
HardThresholdCondition,
EmailNotificationHook,
WebNotificationHook,
)
# for pytest.parametrize
subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY", "metrics_advisor_subscription_key")
api_key = os.getenv("METRICS_ADVISOR_API_KEY", "metrics_advisor_api_key")
API_KEY = [MetricsAdvisorKeyCredential(subscription_key, api_key)]
AAD = ["AAD"]
CREDENTIALS = [MetricsAdvisorKeyCredential(subscription_key, api_key), "AAD"]
def ids(val):
if isinstance(val, MetricsAdvisorKeyCredential):
return "APIKey"
else:
return "AAD"
class MetricsAdvisorClientPreparer(object):
def __init__(self, client_cls, client_kwargs={}, **kwargs):
self.client_cls = client_cls
self.client_kwargs = client_kwargs
self.service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT", "https://fakeendpoint.cognitiveservices.azure.com")
self.data_feed = kwargs.pop("data_feed", False)
self.detection_config = kwargs.pop("detection_config", False)
self.alert_config = kwargs.pop("alert_config", False)
self.email_hook = kwargs.pop("email_hook", False)
self.web_hook = kwargs.pop("web_hook", False)
self.variables = kwargs.pop("variables", {})
def __call__(self, fn):
def _preparer_wrapper(test_class, credential, **kwargs):
self.create_test_client(credential)
self.create_resources(**kwargs)
if is_live():
fn(test_class, self.client, variables=self.variables)
else:
fn(test_class, self.client)
return _preparer_wrapper
def create_test_client(self, credential):
if credential == "AAD":
credential = AzureRecordedTestCase().get_credential(self.client_cls)
self.client = self.client_cls(self.service_endpoint, credential, **self.client_kwargs)
def create_resources(self, **kwargs):
if not is_live():
return kwargs
try:
if self.data_feed:
self.data_feed = self.create_data_feed("datafeed")
if self.detection_config:
self.detection_config = self.create_detection_config("detectionconfig")
if self.alert_config:
self.alert_config = self.create_alert_config("alertconfig")
if self.email_hook:
self.email_hook = self.create_email_hook("emailhook")
if self.web_hook:
self.web_hook = self.create_web_hook("web_hook")
except Exception as e:
try:
self.client.delete_data_feed(self.variables["data_feed_id"])
except KeyError:
pass
raise e
def create_random_name(self, name):
return name + str(uuid.uuid4())
def create_data_feed(self, name):
name = self.create_random_name(name)
if is_live():
self.variables["data_feed_name"] = name
data_feed = self.client.create_data_feed(
name=self.variables["data_feed_name"],
source=SqlServerDataFeedSource(
connection_string=os.getenv("METRICS_ADVISOR_SQL_SERVER_CONNECTION_STRING", "metrics_advisor_sql_server_connection_string"),
query="select * from adsample2 where Timestamp = @StartTime"
),
granularity=DataFeedGranularity(
granularity_type="Daily",
),
schema=DataFeedSchema(
metrics=[
DataFeedMetric(name="cost", description="the cost"),
DataFeedMetric(name="revenue", description="the revenue")
],
dimensions=[
DataFeedDimension(name="category"),
DataFeedDimension(name="region")
],
timestamp_column="Timestamp"
),
ingestion_settings=DataFeedIngestionSettings(
ingestion_begin_time=datetime.datetime(2019, 10, 1),
data_source_request_concurrency=0,
ingestion_retry_delay=-1,
ingestion_start_offset=-1,
stop_retry_after=-1,
),
admins=["yournamehere@microsoft.com"],
data_feed_description="my first data feed",
missing_data_point_fill_settings=DataFeedMissingDataPointFillSettings(
fill_type="SmartFilling"
),
rollup_settings=DataFeedRollupSettings(
rollup_type="NoRollup",
rollup_method="None",
),
viewers=["viewers"],
access_mode="Private",
action_link_template="action link template"
)
if is_live():
self.variables["data_feed_id"] = data_feed.id
self.variables["data_feed_metric_id"] = data_feed.metric_ids['cost']
return data_feed
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 = 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
def create_alert_config(self, name):
alert_config_name = self.create_random_name(name)
if is_live():
self.variables["alert_config_name"] = alert_config_name
alert_config = self.client.create_alert_configuration(
name=self.variables["alert_config_name"],
cross_metrics_operator="AND",
metric_alert_configurations=[
MetricAlertConfiguration(
detection_configuration_id=self.variables["detection_config_id"],
alert_scope=MetricAnomalyAlertScope(
scope_type="TopN",
top_n_group_in_scope=TopNGroupScope(
top=5,
period=10,
min_top_count=9
)
),
alert_conditions=MetricAnomalyAlertConditions(
metric_boundary_condition=MetricBoundaryCondition(
direction="Both",
companion_metric_id=self.variables["data_feed_metric_id"],
lower=1.0,
upper=5.0
)
)
),
MetricAlertConfiguration(
detection_configuration_id=self.variables["detection_config_id"],
alert_scope=MetricAnomalyAlertScope(
scope_type="SeriesGroup",
series_group_in_scope={'region': 'Beijing'}
),
alert_conditions=MetricAnomalyAlertConditions(
severity_condition=SeverityCondition(
min_alert_severity="Low",
max_alert_severity="High"
)
)
),
MetricAlertConfiguration(
detection_configuration_id=self.variables["detection_config_id"],
alert_scope=MetricAnomalyAlertScope(
scope_type="WholeSeries"
),
alert_conditions=MetricAnomalyAlertConditions(
severity_condition=SeverityCondition(
min_alert_severity="Low",
max_alert_severity="High"
)
)
)
],
hook_ids=[]
)
if is_live():
self.variables["alert_config_id"] = alert_config.id
return alert_config
def create_email_hook(self, name):
email_hook_name = self.create_random_name(name)
if is_live():
self.variables["email_hook_name"] = email_hook_name
email_hook = self.client.create_hook(
hook=EmailNotificationHook(
name=self.variables["email_hook_name"],
emails_to_alert=["yournamehere@microsoft.com"],
description="my email hook",
external_link="external link"
)
)
if is_live():
self.variables["email_hook_id"] = email_hook.id
return email_hook
def create_web_hook(self, name):
web_hook_name = self.create_random_name(name)
if is_live():
self.variables["web_hook_name"] = web_hook_name
web_hook = self.client.create_hook(
hook=WebNotificationHook(
name=self.variables["web_hook_name"],
endpoint="https://httpbin.org/post",
description="my web hook",
external_link="external link",
username="krista",
password="123"
)
)
if is_live():
self.variables["web_hook_id"] = web_hook.id
return web_hook
class TestMetricsAdvisorClientBase(AzureRecordedTestCase):
@property
def service_endpoint(self):
return os.getenv("METRICS_ADVISOR_ENDPOINT", "https://fakeendpoint.cognitiveservices.azure.com")
@property
def subscription_key(self):
return os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY", "metrics_advisor_subscription_key")
@property
def api_key(self):
return os.getenv("METRICS_ADVISOR_API_KEY", "metrics_advisor_api_key")
@property
def sql_server_connection_string(self):
return os.getenv("METRICS_ADVISOR_SQL_SERVER_CONNECTION_STRING", "metrics_advisor_sql_server_connection_string")
@property
def data_feed_id(self):
return os.getenv("METRICS_ADVISOR_DATA_FEED_ID", "metrics_advisor_data_feed_id")
@property
def anomaly_detection_configuration_id(self):
return os.getenv("METRICS_ADVISOR_ANOMALY_DETECTION_CONFIGURATION_ID", "metrics_advisor_anomaly_detection_configuration_id")
@property
def anomaly_alert_configuration_id(self):
return os.getenv("METRICS_ADVISOR_ANOMALY_ALERT_CONFIGURATION_ID", "metrics_advisor_anomaly_alert_configuration_id")
@property
def metric_id(self):
return os.getenv("METRICS_ADVISOR_METRIC_ID", "metrics_advisor_metric_id")
@property
def incident_id(self):
return os.getenv("METRICS_ADVISOR_INCIDENT_ID", "metrics_advisor_incident_id")
@property
def feedback_id(self):
return os.getenv("METRICS_ADVISOR_FEEDBACK_ID", "metrics_advisor_feedback_id")
@property
def alert_id(self):
return os.getenv("METRICS_ADVISOR_ALERT_ID", "metrics_advisor_alert_id")
def clean_up(self, delete_func, variables, key=None):
try:
id_to_delete = variables[key] if key else variables["data_feed_id"]
delete_func(id_to_delete)
except KeyError:
pass
def create_random_name(self, name):
return name + str(uuid.uuid4())
|
