def sample_get_detection_config(detection_config_id): # [START get_detection_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_detection_configuration(detection_config_id) print("Detection config name: {}".format(config.name)) print("Description: {}".format(config.description)) print("Metric ID: {}".format(config.metric_id)) print("\nDetection conditions specified for configuration...") print("\nWhole Series Detection Conditions:\n") conditions = config.whole_series_detection_condition print("Use {} operator for multiple detection conditions".format( conditions.condition_operator)) print("Smart Detection Condition:") print("- Sensitivity: {}".format( conditions.smart_detection_condition.sensitivity)) print("- Detection direction: {}".format( conditions.smart_detection_condition.anomaly_detector_direction)) print( "- Suppress conditions: minimum number: {}; minimum ratio: {}".format( conditions.smart_detection_condition.suppress_condition.min_number, conditions.smart_detection_condition.suppress_condition.min_ratio)) print("Hard Threshold Condition:") print("- Lower bound: {}".format( conditions.hard_threshold_condition.lower_bound)) print("- Upper bound: {}".format( conditions.hard_threshold_condition.upper_bound)) print("- Detection direction: {}".format( conditions.smart_detection_condition.anomaly_detector_direction)) print( "- Suppress conditions: minimum number: {}; minimum ratio: {}".format( conditions.smart_detection_condition.suppress_condition.min_number, conditions.smart_detection_condition.suppress_condition.min_ratio)) print("Change Threshold Condition:") print("- Change percentage: {}".format( conditions.change_threshold_condition.change_percentage)) print("- Shift point: {}".format( conditions.change_threshold_condition.shift_point)) print("- Detect anomaly if within range: {}".format( conditions.change_threshold_condition.within_range)) print("- Detection direction: {}".format( conditions.smart_detection_condition.anomaly_detector_direction)) print( "- Suppress conditions: minimum number: {}; minimum ratio: {}".format( conditions.smart_detection_condition.suppress_condition.min_number, conditions.smart_detection_condition.suppress_condition.min_ratio))
def sample_get_data_feed(data_feed_id): # [START get_data_feed] 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)) data_feed = client.get_data_feed(data_feed_id) print("ID: {}".format(data_feed.id)) print("Data feed name: {}".format(data_feed.name)) print("Created time: {}".format(data_feed.created_time)) print("Status: {}".format(data_feed.status)) print("Source type: {}".format(data_feed.source.data_source_type)) print("Granularity type: {}".format(data_feed.granularity.granularity_type)) print("Data feed metrics: {}".format([metric.name for metric in data_feed.schema.metrics])) print("Data feed dimensions: {}".format([dimension.name for dimension in data_feed.schema.dimensions])) print("Data feed timestamp column: {}".format(data_feed.schema.timestamp_column)) print("Ingestion data starting on: {}".format(data_feed.ingestion_settings.ingestion_begin_time)) print("Data feed description: {}".format(data_feed.options.data_feed_description)) print("Data feed rollup type: {}".format(data_feed.options.rollup_settings.rollup_type)) print("Data feed rollup method: {}".format(data_feed.options.rollup_settings.rollup_method)) print("Data feed fill setting: {}".format(data_feed.options.missing_data_point_fill_settings.fill_type)) print("Data feed access mode: {}".format(data_feed.options.access_mode))
def sample_list_data_feeds(): # [START list_data_feeds] 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)) data_feeds = client.list_data_feeds() for feed in data_feeds: print("Data feed name: {}".format(feed.name)) print("ID: {}".format(feed.id)) print("Created time: {}".format(feed.created_time)) print("Status: {}".format(feed.status)) print("Source type: {}".format(feed.source.data_source_type)) print("Granularity type: {}".format(feed.granularity.granularity_type)) print("\nFeed metrics:") for metric in feed.schema.metrics: print(metric.name) print("\nFeed dimensions:") for dimension in feed.schema.dimensions: print(dimension.name)
def sample_update_data_feed(data_feed): # [START update_data_feed] 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)) # update data feed on the data feed itself or by using available keyword arguments data_feed.name = "updated name" data_feed.data_feed_description = "updated description for data feed" updated = client.update_data_feed(data_feed, access_mode="Public", fill_type="CustomValue", custom_fill_value=1) print("Updated name: {}".format(updated.name)) print("Updated description: {}".format(updated.data_feed_description)) print("Updated access mode: {}".format(updated.access_mode)) print("Updated fill setting, value: {}, {}".format( updated.missing_data_point_fill_settings.fill_type, updated.missing_data_point_fill_settings.custom_fill_value, ))
def sample_create_detection_config(): # [START create_detection_config] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, 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 ) ) detection_config = client.create_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 sample_get_alert_config(alert_config_id): # [START get_anomaly_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_anomaly_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, ))
def sample_create_data_feed(): # [START create_data_feed] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient from azure.ai.metricsadvisor.models import ( SQLServerDataFeed, DataFeedSchema, DataFeedMetric, DataFeedDimension, DataFeedOptions, DataFeedRollupSettings, DataFeedMissingDataPointFillSettings, ) service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT") subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY") api_key = os.getenv("METRICS_ADVISOR_API_KEY") sql_server_connection_string = os.getenv("METRICS_ADVISOR_SQL_SERVER_CONNECTION_STRING") query = os.getenv("METRICS_ADVISOR_SQL_SERVER_QUERY") client = MetricsAdvisorAdministrationClient(service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) data_feed = client.create_data_feed( name="My data feed", source=SQLServerDataFeed( connection_string=sql_server_connection_string, query=query, ), granularity="Daily", schema=DataFeedSchema( metrics=[ DataFeedMetric(name="cost", display_name="Cost"), DataFeedMetric(name="revenue", display_name="Revenue") ], dimensions=[ DataFeedDimension(name="category", display_name="Category"), DataFeedDimension(name="city", display_name="City") ], timestamp_column="Timestamp" ), ingestion_settings=datetime.datetime(2019, 10, 1), options=DataFeedOptions( data_feed_description="cost/revenue data feed", rollup_settings=DataFeedRollupSettings( rollup_type="AutoRollup", rollup_method="Sum", rollup_identification_value="__CUSTOM_SUM__" ), missing_data_point_fill_settings=DataFeedMissingDataPointFillSettings( fill_type="SmartFilling" ), access_mode="Private" ) ) return data_feed
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
def sample_update_detection_config(detection_config): # [START update_detection_config] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient from azure.ai.metricsadvisor.models import ( MetricSeriesGroupDetectionCondition, MetricSingleSeriesDetectionCondition, SmartDetectionCondition, SuppressCondition ) 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)) detection_config.name = "updated config name" detection_config.description = "updated with more detection conditions" smart_detection_condition = SmartDetectionCondition( anomaly_detector_direction="Up", sensitivity=10, suppress_condition=SuppressCondition( min_number=2, min_ratio=2 ) ) client.update_detection_configuration( detection_config, series_group_detection_conditions=[ MetricSeriesGroupDetectionCondition( series_group_key={"city": "Seoul"}, smart_detection_condition=smart_detection_condition ) ], series_detection_conditions=[ MetricSingleSeriesDetectionCondition( series_key={"city": "Osaka", "category": "Cell Phones"}, smart_detection_condition=smart_detection_condition ) ] ) updated = client.get_detection_configuration(detection_config.id) print("Updated detection name: {}".format(updated.name)) print("Updated detection description: {}".format(updated.description)) print("Updated detection condition for series group: {}".format( updated.series_group_detection_conditions[0].series_group_key )) print("Updated detection condition for series: {}".format( updated.series_detection_conditions[0].series_key ))
def sample_delete_datasource_credential(credential_id): # [START delete_datasource_credential] 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_datasource_credential(credential_id)
def sample_list_hooks(): # [START list_hooks] 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)) hooks = client.list_hooks() for hook in hooks: print("Hook type: {}".format(hook.hook_type)) print("Hook name: {}".format(hook.name)) print("Description: {}\n".format(hook.description))
async def sample_list_datasource_credentials_async(): # [START list_datasource_credentials_async] 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)) credentials = client.list_datasource_credentials() async for credential in credentials: print("Credential type: {}".format(credential.credential_type)) print("Credential name: {}".format(credential.name)) print("Description: {}\n".format(credential.description))
def authentication_administration_client_with_aad(): # [START administration_client_with_aad] from azure.ai.metricsadvisor import MetricsAdvisorAdministrationClient from azure.identity import DefaultAzureCredential service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT") credential = DefaultAzureCredential() client = MetricsAdvisorAdministrationClient(service_endpoint, credential)
def sample_refresh_data_feed_ingestion(): # [START refresh_data_feed_ingestion] import datetime 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") data_feed_id = os.getenv("METRICS_ADVISOR_DATA_FEED_ID") client = MetricsAdvisorAdministrationClient( service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) client.refresh_data_feed_ingestion(data_feed_id, datetime.datetime(2020, 9, 20), datetime.datetime(2020, 9, 25))
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))
def sample_list_detection_configs(): # [START list_detection_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") metric_id = os.getenv("METRICS_ADVISOR_METRIC_ID") client = MetricsAdvisorAdministrationClient(service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) configs = client.list_detection_configurations(metric_id=metric_id) for config in configs: print("Detection config name: {}".format(config.name)) print("Description: {}".format(config.description)) print("Metric ID: {}\n".format(config.metric_id))
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={'city': '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 ))
def sample_update_datasource_credential(datasource_credential): # [START update_datasource_credential] 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)) datasource_credential.description = "updated description" updated = client.update_datasource_credential(datasource_credential) print("Credential type: {}".format(updated.credential_type)) print("Credential name: {}".format(updated.name)) print("Description: {}\n".format(updated.description))
def sample_get_hook(hook_id): # [START get_hook] 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)) hook = client.get_hook(hook_id) print("Hook name: {}".format(hook.name)) print("Description: {}".format(hook.description)) print("Emails to alert: {}".format(hook.emails_to_alert)) print("External link: {}".format(hook.external_link)) print("Admins: {}".format(hook.admin_emails))
def sample_get_data_feed_ingestion_progress(): # [START get_data_feed_ingestion_progress] 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") data_feed_id = os.getenv("METRICS_ADVISOR_DATA_FEED_ID") client = MetricsAdvisorAdministrationClient( service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) progress = client.get_data_feed_ingestion_progress(data_feed_id) print("Lastest active timestamp: {}".format( progress.latest_active_timestamp)) print("Latest successful timestamp: {}".format( progress.latest_success_timestamp))
def authentication_administration_client_with_metrics_advisor_credential(): # [START administration_client_with_metrics_advisor_credential] 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))
def sample_update_hook(hook): # [START update_hook] 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)) hook.name = "updated hook name" hook.description = "updated hook description" updated = client.update_hook(hook, emails_to_alert=["*****@*****.**"]) print("Updated name: {}".format(updated.name)) print("Updated description: {}".format(updated.description)) print("Updated emails: {}".format(updated.emails_to_alert))
def sample_list_data_feed_ingestion_status(): # [START list_data_feed_ingestion_status] import datetime 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") data_feed_id = os.getenv("METRICS_ADVISOR_DATA_FEED_ID") client = MetricsAdvisorAdministrationClient( service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) ingestion_status = client.list_data_feed_ingestion_status( data_feed_id, datetime.datetime(2020, 9, 20), datetime.datetime(2020, 9, 25)) for status in ingestion_status: print("Timestamp: {}".format(status.timestamp)) print("Status: {}".format(status.status)) print("Message: {}\n".format(status.message))
def sample_create_hook(): # [START create_hook] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient from azure.ai.metricsadvisor.models import EmailNotificationHook 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)) hook = client.create_hook( hook=EmailNotificationHook( name="email hook", description="my email hook", emails_to_alert=["*****@*****.**"], external_link="https://docs.microsoft.com/en-us/azure/cognitive-services/metrics-advisor/how-tos/alerts" ) ) return hook
def sample_create_hook(): # [START create_hook] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient from azure.ai.metricsadvisor.models import EmailNotificationHook 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)) hook = client.create_hook( hook=EmailNotificationHook( name="email hook", description="my email hook", emails_to_alert=["*****@*****.**"], external_link="https://adwiki.azurewebsites.net/articles/howto/alerts/create-hooks.html" ) ) return hook
def sample_create_datasource_credential(): # [START create_datasource_credential] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential, MetricsAdvisorAdministrationClient from azure.ai.metricsadvisor.models import DatasourceSqlConnectionString service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT") subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY") api_key = os.getenv("METRICS_ADVISOR_API_KEY") connection_string = os.getenv("SQL_SERVER_CONNECTION_STRING") client = MetricsAdvisorAdministrationClient( service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) credential = client.create_datasource_credential( datasource_credential=DatasourceSqlConnectionString( name="sql datasource credential", connection_string=connection_string, description="my datasource credential", )) return credential
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.")
def __init__(self, method_name): super(TestMetricsAdvisorAdministrationClientBase, self).__init__(method_name) self.vcr.match_on = ["path", "method", "query"] if self.is_live: service_endpoint = self.get_settings_value("METRICS_ADVISOR_ENDPOINT") subscription_key = self.get_settings_value("METRICS_ADVISOR_SUBSCRIPTION_KEY") api_key = self.get_settings_value("METRICS_ADVISOR_API_KEY") self.sql_server_connection_string = self.get_settings_value("METRICS_ADVISOR_SQL_SERVER_CONNECTION_STRING") self.azure_table_connection_string = self.get_settings_value("METRICS_ADVISOR_AZURE_TABLE_CONNECTION_STRING") self.azure_blob_connection_string = self.get_settings_value("METRICS_ADVISOR_AZURE_BLOB_CONNECTION_STRING") self.azure_cosmosdb_connection_string = self.get_settings_value("METRICS_ADVISOR_COSMOS_DB_CONNECTION_STRING") self.http_request_get_url = self.get_settings_value("METRICS_ADVISOR_HTTP_GET_URL") self.http_request_post_url = self.get_settings_value("METRICS_ADVISOR_HTTP_POST_URL") self.application_insights_api_key = self.get_settings_value("METRICS_ADVISOR_APPLICATION_INSIGHTS_API_KEY") self.azure_data_explorer_connection_string = self.get_settings_value("METRICS_ADVISOR_AZURE_DATA_EXPLORER_CONNECTION_STRING") self.influxdb_connection_string = self.get_settings_value("METRICS_ADVISOR_INFLUX_DB_CONNECTION_STRING") self.influxdb_password = self.get_settings_value("METRICS_ADVISOR_INFLUX_DB_PASSWORD") self.azure_datalake_account_key = self.get_settings_value("METRICS_ADVISOR_AZURE_DATALAKE_ACCOUNT_KEY") self.mongodb_connection_string = self.get_settings_value("METRICS_ADVISOR_AZURE_MONGO_DB_CONNECTION_STRING") self.mysql_connection_string = self.get_settings_value("METRICS_ADVISOR_MYSQL_CONNECTION_STRING") self.postgresql_connection_string = self.get_settings_value("METRICS_ADVISOR_POSTGRESQL_CONNECTION_STRING") self.elasticsearch_auth_header = self.get_settings_value("METRICS_ADVISOR_ELASTICSEARCH_AUTH_HEADER") self.anomaly_detection_configuration_id = self.get_settings_value("METRICS_ADVISOR_ANOMALY_DETECTION_CONFIGURATION_ID") self.data_feed_id = self.get_settings_value("METRICS_ADVISOR_DATA_FEED_ID") self.metric_id = self.get_settings_value("METRICS_ADVISOR_METRIC_ID") self.scrubber.register_name_pair( self.sql_server_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.azure_table_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.azure_blob_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.azure_cosmosdb_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.http_request_get_url, "connectionstring" ) self.scrubber.register_name_pair( self.http_request_post_url, "connectionstring" ) self.scrubber.register_name_pair( self.application_insights_api_key, "connectionstring" ) self.scrubber.register_name_pair( self.azure_data_explorer_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.influxdb_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.influxdb_password, "connectionstring" ) self.scrubber.register_name_pair( self.azure_datalake_account_key, "connectionstring" ) self.scrubber.register_name_pair( self.mongodb_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.mysql_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.postgresql_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.elasticsearch_auth_header, "connectionstring" ) self.scrubber.register_name_pair( self.metric_id, "metric_id" ) self.scrubber.register_name_pair( self.data_feed_id, "data_feed_id" ) self.scrubber.register_name_pair( self.anomaly_detection_configuration_id, "anomaly_detection_configuration_id" ) else: service_endpoint = "https://endpointname.cognitiveservices.azure.com" subscription_key = "METRICS_ADVISOR_SUBSCRIPTION_KEY" api_key = "METRICS_ADVISOR_API_KEY" self.sql_server_connection_string = "SQL_SERVER_CONNECTION_STRING" self.azure_table_connection_string = "AZURE_TABLE_CONNECTION_STRING" self.azure_blob_connection_string = "AZURE_BLOB_CONNECTION_STRING" self.azure_cosmosdb_connection_string = "COSMOS_DB_CONNECTION_STRING" self.http_request_get_url = "METRICS_ADVISOR_HTTP_GET_URL" self.http_request_post_url = "METRICS_ADVISOR_HTTP_POST_URL" self.application_insights_api_key = "METRICS_ADVISOR_APPLICATION_INSIGHTS_API_KEY" self.azure_data_explorer_connection_string = "METRICS_ADVISOR_AZURE_DATA_EXPLORER_CONNECTION_STRING" self.influxdb_connection_string = "METRICS_ADVISOR_INFLUXDB_CONNECTION_STRING" self.influxdb_password = "******" self.azure_datalake_account_key = "METRICS_ADVISOR_AZURE_DATALAKE_ACCOUNT_KEY" self.mongodb_connection_string = "METRICS_ADVISOR_AZURE_MONGODB_CONNECTION_STRING" self.mysql_connection_string = "METRICS_ADVISOR_MYSQL_CONNECTION_STRING" self.postgresql_connection_string = "METRICS_ADVISOR_POSTGRESQL_CONNECTION_STRING" self.elasticsearch_auth_header = "METRICS_ADVISOR_ELASTICSEARCH_AUTH" self.anomaly_detection_configuration_id = "anomaly_detection_configuration_id" self.metric_id = "metric_id" self.data_feed_id = "data_feed_id" self.admin_client = MetricsAdvisorAdministrationClient(service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key))
class TestMetricsAdvisorAdministrationClientBase(AzureTestCase): FILTER_HEADERS = ReplayableTest.FILTER_HEADERS + ['Ocp-Apim-Subscription-Key', 'x-api-key'] def __init__(self, method_name): super(TestMetricsAdvisorAdministrationClientBase, self).__init__(method_name) self.vcr.match_on = ["path", "method", "query"] if self.is_live: service_endpoint = self.get_settings_value("METRICS_ADVISOR_ENDPOINT") subscription_key = self.get_settings_value("METRICS_ADVISOR_SUBSCRIPTION_KEY") api_key = self.get_settings_value("METRICS_ADVISOR_API_KEY") self.sql_server_connection_string = self.get_settings_value("METRICS_ADVISOR_SQL_SERVER_CONNECTION_STRING") self.azure_table_connection_string = self.get_settings_value("METRICS_ADVISOR_AZURE_TABLE_CONNECTION_STRING") self.azure_blob_connection_string = self.get_settings_value("METRICS_ADVISOR_AZURE_BLOB_CONNECTION_STRING") self.azure_cosmosdb_connection_string = self.get_settings_value("METRICS_ADVISOR_COSMOS_DB_CONNECTION_STRING") self.http_request_get_url = self.get_settings_value("METRICS_ADVISOR_HTTP_GET_URL") self.http_request_post_url = self.get_settings_value("METRICS_ADVISOR_HTTP_POST_URL") self.application_insights_api_key = self.get_settings_value("METRICS_ADVISOR_APPLICATION_INSIGHTS_API_KEY") self.azure_data_explorer_connection_string = self.get_settings_value("METRICS_ADVISOR_AZURE_DATA_EXPLORER_CONNECTION_STRING") self.influxdb_connection_string = self.get_settings_value("METRICS_ADVISOR_INFLUX_DB_CONNECTION_STRING") self.influxdb_password = self.get_settings_value("METRICS_ADVISOR_INFLUX_DB_PASSWORD") self.azure_datalake_account_key = self.get_settings_value("METRICS_ADVISOR_AZURE_DATALAKE_ACCOUNT_KEY") self.mongodb_connection_string = self.get_settings_value("METRICS_ADVISOR_AZURE_MONGO_DB_CONNECTION_STRING") self.mysql_connection_string = self.get_settings_value("METRICS_ADVISOR_MYSQL_CONNECTION_STRING") self.postgresql_connection_string = self.get_settings_value("METRICS_ADVISOR_POSTGRESQL_CONNECTION_STRING") self.elasticsearch_auth_header = self.get_settings_value("METRICS_ADVISOR_ELASTICSEARCH_AUTH_HEADER") self.anomaly_detection_configuration_id = self.get_settings_value("METRICS_ADVISOR_ANOMALY_DETECTION_CONFIGURATION_ID") self.data_feed_id = self.get_settings_value("METRICS_ADVISOR_DATA_FEED_ID") self.metric_id = self.get_settings_value("METRICS_ADVISOR_METRIC_ID") self.scrubber.register_name_pair( self.sql_server_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.azure_table_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.azure_blob_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.azure_cosmosdb_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.http_request_get_url, "connectionstring" ) self.scrubber.register_name_pair( self.http_request_post_url, "connectionstring" ) self.scrubber.register_name_pair( self.application_insights_api_key, "connectionstring" ) self.scrubber.register_name_pair( self.azure_data_explorer_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.influxdb_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.influxdb_password, "connectionstring" ) self.scrubber.register_name_pair( self.azure_datalake_account_key, "connectionstring" ) self.scrubber.register_name_pair( self.mongodb_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.mysql_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.postgresql_connection_string, "connectionstring" ) self.scrubber.register_name_pair( self.elasticsearch_auth_header, "connectionstring" ) self.scrubber.register_name_pair( self.metric_id, "metric_id" ) self.scrubber.register_name_pair( self.data_feed_id, "data_feed_id" ) self.scrubber.register_name_pair( self.anomaly_detection_configuration_id, "anomaly_detection_configuration_id" ) else: service_endpoint = "https://endpointname.cognitiveservices.azure.com" subscription_key = "METRICS_ADVISOR_SUBSCRIPTION_KEY" api_key = "METRICS_ADVISOR_API_KEY" self.sql_server_connection_string = "SQL_SERVER_CONNECTION_STRING" self.azure_table_connection_string = "AZURE_TABLE_CONNECTION_STRING" self.azure_blob_connection_string = "AZURE_BLOB_CONNECTION_STRING" self.azure_cosmosdb_connection_string = "COSMOS_DB_CONNECTION_STRING" self.http_request_get_url = "METRICS_ADVISOR_HTTP_GET_URL" self.http_request_post_url = "METRICS_ADVISOR_HTTP_POST_URL" self.application_insights_api_key = "METRICS_ADVISOR_APPLICATION_INSIGHTS_API_KEY" self.azure_data_explorer_connection_string = "METRICS_ADVISOR_AZURE_DATA_EXPLORER_CONNECTION_STRING" self.influxdb_connection_string = "METRICS_ADVISOR_INFLUXDB_CONNECTION_STRING" self.influxdb_password = "******" self.azure_datalake_account_key = "METRICS_ADVISOR_AZURE_DATALAKE_ACCOUNT_KEY" self.mongodb_connection_string = "METRICS_ADVISOR_AZURE_MONGODB_CONNECTION_STRING" self.mysql_connection_string = "METRICS_ADVISOR_MYSQL_CONNECTION_STRING" self.postgresql_connection_string = "METRICS_ADVISOR_POSTGRESQL_CONNECTION_STRING" self.elasticsearch_auth_header = "METRICS_ADVISOR_ELASTICSEARCH_AUTH" self.anomaly_detection_configuration_id = "anomaly_detection_configuration_id" self.metric_id = "metric_id" self.data_feed_id = "data_feed_id" self.admin_client = MetricsAdvisorAdministrationClient(service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) def _create_data_feed(self, name): name = create_random_name(name) return self.admin_client.create_data_feed( DataFeed( name=name, source=SQLServerDataFeed( connection_string=self.sql_server_connection_string, query='select * from adsample2 where Timestamp = @StartTime' ), granularity=DataFeedGranularity( granularity_type="Daily", ), schema=DataFeedSchema( metrics=[ DataFeedMetric(name="cost"), DataFeedMetric(name="revenue") ], dimensions=[ DataFeedDimension(name="category"), DataFeedDimension(name="city") ], timestamp_column="Timestamp" ), ingestion_settings=DataFeedIngestionSettings( ingestion_begin_time=datetime.datetime(2019, 10, 1), ) ) ) def _create_data_feed_and_anomaly_detection_config(self, name): data_feed = self._create_data_feed(name) detection_config_name = create_random_name(name) detection_config = self.admin_client.create_metric_anomaly_detection_configuration( AnomalyDetectionConfiguration( name=detection_config_name, metric_id=data_feed.metric_ids[0], description="testing", whole_series_detection_condition=MetricDetectionCondition( smart_detection_condition=SmartDetectionCondition( sensitivity=50, anomaly_detector_direction="Both", suppress_condition=SuppressCondition( min_number=50, min_ratio=50 ) ) ) ) ) return detection_config, data_feed def _create_data_feed_for_update(self, name): data_feed_name = create_random_name(name) return self.admin_client.create_data_feed( DataFeed( name=data_feed_name, source=SQLServerDataFeed( connection_string=self.sql_server_connection_string, query='select * from adsample2 where Timestamp = @StartTime' ), granularity=DataFeedGranularity( granularity_type="Daily", ), schema=DataFeedSchema( metrics=[ DataFeedMetric(name="cost", display_name="display cost", description="the cost"), DataFeedMetric(name="revenue", display_name="display revenue", description="the revenue") ], dimensions=[ DataFeedDimension(name="category", display_name="display category"), DataFeedDimension(name="city", display_name="display city") ], 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, ), options=DataFeedOptions( admin_emails=["*****@*****.**"], 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", ), viewer_emails=["viewers"], access_mode="Private", action_link_template="action link template" ) ) ) def _create_anomaly_alert_config_for_update(self, name): detection_config, data_feed = self._create_data_feed_and_anomaly_detection_config(name) alert_config_name = create_random_name(name) alert_config = self.admin_client.create_anomaly_alert_configuration( AnomalyAlertConfiguration( name=alert_config_name, cross_metrics_operator="AND", metric_alert_configurations=[ MetricAlertConfiguration( detection_configuration_id=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=data_feed.metric_ids[0], lower=1.0, upper=5.0 ) ) ), MetricAlertConfiguration( detection_configuration_id=detection_config.id, alert_scope=MetricAnomalyAlertScope( scope_type="SeriesGroup", series_group_in_scope={'city': 'Shenzhen'} ), alert_conditions=MetricAnomalyAlertConditions( severity_condition=SeverityCondition( min_alert_severity="Low", max_alert_severity="High" ) ) ), MetricAlertConfiguration( detection_configuration_id=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=[] ) ) return alert_config, data_feed, detection_config def _create_detection_config_for_update(self, name): data_feed = self._create_data_feed(name) detection_config_name = create_random_name("testupdated") detection_config = self.admin_client.create_metric_anomaly_detection_configuration( AnomalyDetectionConfiguration( name=detection_config_name, metric_id=data_feed.metric_ids[0], description="My test metric anomaly detection configuration", whole_series_detection_condition=MetricDetectionCondition( cross_conditions_operator="AND", smart_detection_condition=SmartDetectionCondition( sensitivity=50, anomaly_detector_direction="Both", suppress_condition=SuppressCondition( min_number=50, min_ratio=50 ) ), 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 def _create_email_hook_for_update(self, name): return self.admin_client.create_hook( hook=EmailNotificationHook( name=name, emails_to_alert=["*****@*****.**"], description="my email hook", external_link="external link" ) ) def _create_web_hook_for_update(self, name): return self.admin_client.create_hook( hook=WebNotificationHook( name=name, endpoint="https://httpbin.org/post", description="my web hook", external_link="external link", username="******", password="******" ) )