def sample_list_metric_series_definitions(): # [START list_metric_series_definitions] 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") metric_id = os.getenv("METRICS_ADVISOR_METRIC_ID") client = MetricsAdvisorClient( service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) results = client.list_metric_series_definitions( metric_id=metric_id, active_since=datetime.datetime(2020, 1, 1), ) for result in results: print(str(result))
def sample_list_metric_dimension_values(): # [START list_metric_dimension_values] 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") metric_id = os.getenv("METRICS_ADVISOR_METRIC_ID") dimension_name = "city" client = MetricsAdvisorClient( service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) results = client.list_metric_dimension_values( metric_id=metric_id, dimension_name=dimension_name, ) for result in results: print(str(result))
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))
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" client.update_hook(hook, emails_to_alert=["*****@*****.**"]) updated = client.get_hook(hook.id) print("Updated name: {}".format(updated.name)) print("Updated description: {}".format(updated.description)) print("Updated emails: {}".format(updated.emails_to_alert))
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))
async def sample_list_detection_configs_async(): # [START list_detection_configs_async] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import 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)) async with client: configs = client.list_detection_configurations(metric_id=metric_id) async for config in configs: print("Detection config name: {}".format(config.name)) print("Description: {}".format(config.description)) print("Metric ID: {}\n".format(config.metric_id))
async def sample_delete_data_feed_async(data_feed_id): # [START delete_data_feed_async] from azure.core.exceptions import ResourceNotFoundError from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import 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)) async with client: await client.delete_data_feed(data_feed_id) try: await client.get_data_feed(data_feed_id) except ResourceNotFoundError: print("Data feed successfully deleted.")
async def sample_get_data_feed_async(data_feed_id): # [START get_data_feed_async] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import 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)) async with client: data_feed = await 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))
async def sample_update_alert_config_async(alert_config): # [START update_alert_config_async] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import 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) async with client: updated = await 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_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_list_incidents_for_alert(): # [START list_incidents_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") alert_configuration_id = os.getenv("METRICS_ADVISOR_ALERT_CONFIGURATION_ID") alert_id = os.getenv("METRICS_ADVISOR_ALERT_ID") client = MetricsAdvisorClient(service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) results = client.list_incidents_for_alert( alert_configuration_id=alert_configuration_id, alert_id=alert_id, ) for result in results: print("Metric id: {}".format(result.metric_id)) print("Incident ID: {}".format(result.id)) print("Severity: {}".format(result.severity)) print("Status: {}".format(result.status))
def sample_list_incident_root_cause(): # [START list_incident_root_cause] 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") detection_configuration_id = os.getenv( "METRICS_ADVISOR_DETECTION_CONFIGURATION_ID") incident_id = os.getenv("METRICS_ADVISOR_INCIDENT_ID") client = MetricsAdvisorClient( service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) results = client.list_incident_root_causes( detection_configuration_id=detection_configuration_id, incident_id=incident_id, ) for result in results: print("Score: {}".format(result.score)) print("Description: {}".format(result.description))
async def sample_get_data_feed_ingestion_progress_async(): # [START get_data_feed_ingestion_progress_async] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import 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)) async with client: progress = await 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 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_list_incidents_for_detection_configuration(): # [START list_incidents_for_detection_configuration] 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") anomaly_detection_configuration_id = os.getenv("METRICS_ADVISOR_ANOMALY_DETECTION_CONFIGURATION_ID") client = MetricsAdvisorClient(service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) results = client.list_incidents_for_detection_configuration( detection_configuration_id=anomaly_detection_configuration_id, start_time=datetime.datetime(2020, 1, 1), end_time=datetime.datetime(2020, 9, 9), ) for result in results: print("Metric id: {}".format(result.metric_id)) print("Incident ID: {}".format(result.id)) print("Severity: {}".format(result.severity)) print("Status: {}".format(result.status))
async def sample_create_datasource_credential_async(): # [START create_datasource_credential_async] 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)) datasource_credential = await client.create_datasource_credential( datasource_credential=DatasourceSqlConnectionString( name="sql datasource credential", connection_string=connection_string, description="my datasource credential", )) return datasource_credential
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_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(2020, 1, 1), end_time=datetime.datetime(2020, 9, 9), time_mode="AnomalyTime", ) for result in results: print("Alert id: {}".format(result.id)) print("Create on: {}".format(result.created_on)) return results
async def sample_list_metric_enrichment_status_async(): # [START list_metric_enrichment_status_async] import datetime from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import MetricsAdvisorClient 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 = MetricsAdvisorClient(service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) async with client: results = client.list_metric_enrichment_status( metric_id=metric_id, start_time=datetime.datetime(2020, 1, 1), end_time=datetime.datetime(2020, 10, 21), ) async for result in results: print(str(result))
def sample_list_metric_enriched_series_data(): # [START list_metric_enriched_series_data] 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") detection_configuration_id = os.getenv( "METRICS_ADVISOR_DETECTION_CONFIGURATION_ID") series_identity = {"city": "Los Angeles"} client = MetricsAdvisorClient( service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) results = client.list_metric_enriched_series_data( detection_configuration_id=detection_configuration_id, start_time=datetime.datetime(2020, 9, 1), end_time=datetime.datetime(2020, 11, 1), series=[series_identity]) for result in results: print(str(result))
async def sample_list_dimension_values_async(): # [START list_dimension_values_async] import datetime from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import MetricsAdvisorClient 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") dimension_name = "city" client = MetricsAdvisorClient(service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) async with client: results = client.list_dimension_values( detection_configuration_id=detection_configuration_id, dimension_name=dimension_name, start_time=datetime.datetime(2020, 1, 1), end_time=datetime.datetime(2020, 10, 21), ) async for result in results: print(str(result))
def sample_list_metrics_series_data(): # [START list_metrics_series_data] 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") metric_id = os.getenv("METRICS_ADVISOR_METRIC_ID") client = MetricsAdvisorClient( service_endpoint, MetricsAdvisorKeyCredential(subscription_key, api_key)) results = client.list_metrics_series_data( metric_id=metric_id, start_time=datetime.datetime(2020, 1, 1), end_time=datetime.datetime(2020, 10, 21), series_to_filter=[{ "city": "Los Angeles", "category": "Homemade" }]) for result in results: print(str(result))
async def sample_create_detection_config_async(): # [START create_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_detection_configuration( name="my_detection_config", metric_id=metric_id, description="anomaly detection config for metric", whole_series_detection_condition=MetricDetectionCondition( condition_operator="OR", change_threshold_condition=change_threshold_condition, hard_threshold_condition=hard_threshold_condition, smart_detection_condition=smart_detection_condition ) ) return detection_config
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
async def sample_get_detection_config_async(detection_config_id): # [START get_detection_config_async] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import 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)) async with client: config = await 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.cross_conditions_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))
async def sample_get_alert_config_async(alert_config_id): # [START get_alert_config_async] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import 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)) async with client: config = await 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, ))
async def sample_create_alert_config_async(): # [START create_anomaly_alert_config_async] from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential from azure.ai.metricsadvisor.aio import MetricsAdvisorAdministrationClient from azure.ai.metricsadvisor.models import ( MetricAlertConfiguration, MetricAnomalyAlertScope, TopNGroupScope, MetricAnomalyAlertConditions, SeverityCondition, MetricBoundaryCondition, MetricAnomalyAlertSnoozeCondition, AnomalyAlertConfiguration ) service_endpoint = os.getenv("METRICS_ADVISOR_ENDPOINT") subscription_key = os.getenv("METRICS_ADVISOR_SUBSCRIPTION_KEY") api_key = os.getenv("METRICS_ADVISOR_API_KEY") anomaly_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)) anomaly_alert_configuration = AnomalyAlertConfiguration( name="my alert config", description="alert config description", cross_metrics_operator="AND", metric_alert_configurations=[ MetricAlertConfiguration( detection_configuration_id=anomaly_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=anomaly_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] ) async with client: alert_config = await client.create_anomaly_alert_configuration(anomaly_alert_configuration) return alert_config
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 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, DataFeedGranularity, DataFeedIngestionSettings, DataFeed ) 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 = DataFeed( name="My data feed", source=SQLServerDataFeed( connection_string=sql_server_connection_string, query=query, ), granularity=DataFeedGranularity("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=DataFeedIngestionSettings( ingestion_begin_time=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" ) ) my_sql_data_feed = client.create_data_feed(data_feed) return my_sql_data_feed