MetricsAdvisorClient Class

Represents an client that calls restful API of Azure Metrics Advisor service.

Inheritance

builtins.object

MetricsAdvisorClient

Constructor

MetricsAdvisorClient(endpoint: str, credential: Union[MetricsAdvisorKeyCredential, AsyncTokenCredential], **kwargs: Any)

Parameters

endpoint

str

Required

Supported Cognitive Services endpoints (protocol and hostname, for example: https://<resource-name>.cognitiveservices.azure.com).

credential

MetricsAdvisorKeyCredential or TokenCredential

Required

An instance of ~azure.ai.metricsadvisor.MetricsAdvisorKeyCredential. which requires both subscription key and API key. Or an object which can provide an access token for the vault, such as a credential from identity

Methods

add_feedback	Create a new metric feedback.
close	Close the MetricsAdvisorClient session.
get_feedback	Get a metric feedback by its id.
list_alerts	Query alerts under anomaly alert configuration.
list_anomalies	Query anomalies under a specific alert or detection configuration.
list_anomaly_dimension_values	Query dimension values of anomalies.
list_feedback	List feedback on the given metric.
list_incident_root_causes	Query root cause for incident.
list_incidents	Query incidents under a specific alert or detection configuration.
list_metric_dimension_values	List dimension from certain metric.
list_metric_enriched_series_data	Query series enriched by anomaly detection.
list_metric_enrichment_status	Query anomaly detection status.
list_metric_series_data	Get time series data from metric.
list_metric_series_definitions	List series (dimension combinations) from metric.

add_feedback

Create a new metric feedback.

async add_feedback(feedback: FeedbackUnion, **kwargs: Any) -> None

Parameters

feedback

AnomalyFeedback or ChangePointFeedback or CommentFeedback or PeriodFeedback

Required

metric feedback.

Exceptions

HttpResponseError

Examples

Add new feedback.

   from azure.ai.metricsadvisor import MetricsAdvisorKeyCredential
   from azure.ai.metricsadvisor.aio import MetricsAdvisorClient
   from azure.ai.metricsadvisor.models import AnomalyFeedback, ChangePointFeedback, CommentFeedback, PeriodFeedback

   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))

   anomaly_feedback = AnomalyFeedback(metric_id=metric_id,
                                      dimension_key={"Dim1": "Common Lime"},
                                      start_time=datetime.datetime(2020, 8, 5),
                                      end_time=datetime.datetime(2020, 8, 7),
                                      value="NotAnomaly")
   await client.add_feedback(anomaly_feedback)

   change_point_feedback = ChangePointFeedback(metric_id=metric_id,
                                               dimension_key={"Dim1": "Common Lime"},
                                               start_time=datetime.datetime(2020, 8, 5),
                                               end_time=datetime.datetime(2020, 8, 7),
                                               value="NotChangePoint")
   await client.add_feedback(change_point_feedback)

   comment_feedback = CommentFeedback(metric_id=metric_id,
                                      dimension_key={"Dim1": "Common Lime"},
                                      start_time=datetime.datetime(2020, 8, 5),
                                      end_time=datetime.datetime(2020, 8, 7),
                                      value="comment")
   await client.add_feedback(comment_feedback)

   period_feedback = PeriodFeedback(metric_id=metric_id,
                                    dimension_key={"Dim1": "Common Lime"},
                                    start_time=datetime.datetime(2020, 8, 5),
                                    end_time=datetime.datetime(2020, 8, 7),
                                    period_type="AssignValue",
                                    value=2)
   await client.add_feedback(period_feedback)

close

Close the MetricsAdvisorClient session.

async close() -> None

Exceptions

HttpResponseError

get_feedback

Get a metric feedback by its id.

async get_feedback(feedback_id: str, **kwargs: Any) -> Union[MetricFeedback, FeedbackUnion]

Parameters

feedback_id

str

Required

the id of the feedback.

Returns

The feedback object

Return type

MetricFeedback,

AnomalyFeedback,

ChangePointFeedback,

CommentFeedback,

PeriodFeedback

Exceptions

HttpResponseError

Examples

Get a metric feedback by its id.

   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")
   feedback_id = os.getenv("METRICS_ADVISOR_FEEDBACK_ID")

   client = MetricsAdvisorClient(service_endpoint,
                                 MetricsAdvisorKeyCredential(subscription_key, api_key))

   result = await client.get_feedback(feedback_id=feedback_id)
   print("Type: {}; Id: {}".format(result.feedback_type, result.id))

list_alerts

Query alerts under anomaly alert configuration.

list_alerts(alert_configuration_id: str, start_time: Union[str, datetime.datetime], end_time: Union[str, datetime.datetime], time_mode: Union[str, azure.ai.metricsadvisor._generated.models._microsoft_azure_metrics_advisor_restapi_open_ap_iv2_enums.TimeMode], **kwargs: Any) -> azure.core.async_paging.AsyncItemPaged[azure.ai.metricsadvisor.models._models.AnomalyAlert]

Parameters

alert_configuration_id

str

Required

anomaly alert configuration unique id.

datetime.datetime] start_time

<xref:Union>[<xref:str,>

Required

start time.

datetime.datetime] end_time

<xref:Union>[<xref:str,>

Required

end time.

time_mode

str or <xref:azure.ai.metricsadvisor.models.AlertQueryTimeMode>

Required

time mode. Possible values include: "AnomalyTime", "CreatedTime", "ModifiedTime".

skip

int

Returns

AnomalyAlerts under anomaly alert configuration.

Return type

AsyncItemPaged[AnomalyAlert]

Exceptions

HttpResponseError

Examples

Query anomaly detection results.

   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")

   client = MetricsAdvisorClient(service_endpoint,
                                 MetricsAdvisorKeyCredential(subscription_key, api_key))

   async with client:
       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",
       )
       tolist = []
       async for result in results:
           tolist.append(result)
           print("Alert id: {}".format(result.id))
           print("Create time: {}".format(result.created_time))
       return tolist

list_anomalies

Query anomalies under a specific alert or detection configuration.

list_anomalies(alert_configuration_id: str, alert_id: str, **kwargs: Any) -> AsyncItemPaged[DataPointAnomaly]

Parameters

alert_configuration_id

str

anomaly alert configuration unique id.

alert_id

str

alert id.

detection_configuration_id

str

anomaly detection configuration unique id.

datetime.datetime] start_time

<xref:Union>[<xref:str,>

start time filter under chosen time mode.

datetime.datetime] end_time

<xref:Union>[<xref:str,>

end time filter under chosen time mode.

skip

int

filter

DetectionAnomalyFilterCondition

Returns

Anomalies under a specific alert or detection configuration.

Return type

AsyncItemPaged[DataPointAnomaly]

Exceptions

HttpResponseError

list_anomaly_dimension_values

Query dimension values of anomalies.

list_anomaly_dimension_values(detection_configuration_id: str, dimension_name: str, start_time: Union[str, datetime.datetime], end_time: Union[str, datetime.datetime], **kwargs: Any) -> azure.core.async_paging.AsyncItemPaged[str]

Parameters

detection_configuration_id

str

Required

anomaly detection configuration unique id.

dimension_name

str

Required

dimension to query.

datetime.datetime] start_time

<xref:Union>[<xref:str,>

Required

start time filter under chosen time mode.

datetime.datetime] end_time

<xref:Union>[<xref:str,>

Required

end time filter under chosen time mode.

skip

int

str] dimension_filter

<xref:Dict>[<xref:str,>

filter specfic dimension name and values.

Returns

Dimension values of anomalies.

Return type

AsyncItemPaged[str]

Exceptions

HttpResponseError

Examples

Query dimension values.

   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_anomaly_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))

list_feedback

List feedback on the given metric.

list_feedback(metric_id: str, **kwargs: Any) -> AsyncItemPaged[Union[MetricFeedback, FeedbackUnion]]

Parameters

metric_id

str

Required

filter feedbacks by metric id

skip

int

dimension_key

dict[str, str]

filter specfic dimension name and values

feedback_type

str or FeedbackType

filter feedbacks by type. Possible values include: "Anomaly", "ChangePoint", "Period", "Comment".

datetime.datetime] start_time

<xref:Union>[<xref:str,>

start time filter under chosen time mode.

datetime.datetime] end_time

<xref:Union>[<xref:str,>

end time filter under chosen time mode.

time_mode

str or FeedbackQueryTimeMode

time mode to filter feedback. Possible values include: "MetricTimestamp", "FeedbackCreatedTime".

Returns

Pageable list of MetricFeedback

Return type

AsyncItemPaged[<xref:Union>[MetricFeedback, AnomalyFeedback, ChangePointFeedback, CommentFeedback, PeriodFeedback]]

Exceptions

HttpResponseError

Examples

List feedback on the given metric.

   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))

   results = client.list_feedback(metric_id=metric_id)
   async for result in results:
       print("Type: {}; Id: {}".format(result.feedback_type, result.id))

list_incident_root_causes

Query root cause for incident.

list_incident_root_causes(detection_configuration_id: str, incident_id: str, **kwargs: Any) -> azure.core.async_paging.AsyncItemPaged[azure.ai.metricsadvisor.models._models.IncidentRootCause]

Parameters

detection_configuration_id

str

Required

anomaly detection configuration unique id.

incident_id

str

Required

incident id.

Returns

Pageable of root cause for incident

Return type

AsyncItemPaged[IncidentRootCause]

Exceptions

HttpResponseError

Examples

Query incident root causes.

   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")
   incident_id = os.getenv("METRICS_ADVISOR_INCIDENT_ID")

   client = MetricsAdvisorClient(service_endpoint,
                                 MetricsAdvisorKeyCredential(subscription_key, api_key))
   async with client:
       results = client.list_incident_root_causes(
           detection_configuration_id=detection_configuration_id,
           incident_id=incident_id,
       )
       async for result in results:
           print("Score: {}".format(result.score))
           print("Description: {}".format(result.description))

list_incidents

Query incidents under a specific alert or detection configuration.

list_incidents(alert_configuration_id: str, alert_id: str, **kwargs: Any) -> AsyncItemPaged[AnomalyIncident]

Parameters

alert_configuration_id

str

anomaly alerting configuration unique id.

alert_id

str

alert id.

detection_configuration_id

str

anomaly detection configuration unique id.

datetime.datetime] start_time

<xref:Union>[<xref:str,>

start time filter under chosen time mode.

datetime.datetime] end_time

<xref:Union>[<xref:str,>

end time filter under chosen time mode.

skip

int

filter

DetectionAnomalyFilterCondition

Returns

AnomalyIncidents under a specific alert.

Return type

AsyncItemPaged[AnomalyIncident]

Exceptions

HttpResponseError

list_metric_dimension_values

List dimension from certain metric.

list_metric_dimension_values(metric_id: str, dimension_name: str, **kwargs: Any) -> azure.core.async_paging.AsyncItemPaged[str]

Parameters

metric_id

str

Required

metric unique id.

dimension_name

str

Required

the dimension name

skip

int

dimension_value_filter

str

dimension value to be filtered.

Returns

Dimension from certain metric.

Return type

AsyncItemPaged[str]

Exceptions

HttpResponseError

Examples

Query metric dimension values.

   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")
   dimension_name = "city"

   client = MetricsAdvisorClient(service_endpoint,
                                 MetricsAdvisorKeyCredential(subscription_key, api_key))

   async with client:
       results = client.list_metric_dimension_values(
           metric_id=metric_id,
           dimension_name=dimension_name,
       )
       async for result in results:
           print(str(result))

list_metric_enriched_series_data

Query series enriched by anomaly detection.

list_metric_enriched_series_data(detection_configuration_id: str, series: Union[List[azure.ai.metricsadvisor._generated.models._models_py3.SeriesIdentity], List[Dict[str, str]]], start_time: Union[str, datetime.datetime], end_time: Union[str, datetime.datetime], **kwargs: Any) -> azure.core.async_paging.AsyncItemPaged[azure.ai.metricsadvisor.models._models.MetricEnrichedSeriesData]

Parameters

detection_configuration_id

str

Required

anomaly alerting configuration unique id.

series

SeriesIdentity or list[dict[str, str]]

Required

List of dimensions specified for series.

datetime.datetime] start_time

<xref:Union>[<xref:str,>

Required

start time filter under chosen time mode.

datetime.datetime] end_time

<xref:Union>[<xref:str,>

Required

end time filter under chosen time mode.

Returns

Pageable of MetricEnrichedSeriesData

Return type

AsyncItemPaged[MetricEnrichedSeriesData]

Exceptions

HttpResponseError

Examples

Query metric enriched series data.

   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")
   series_identity = {"city": "Los Angeles"}

   client = MetricsAdvisorClient(service_endpoint,
                                 MetricsAdvisorKeyCredential(subscription_key, api_key))

   async with client:
       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]
       )
       async for result in results:
           print(str(result))

list_metric_enrichment_status

Query anomaly detection status.

list_metric_enrichment_status(metric_id: str, start_time: Union[str, datetime.datetime], end_time: Union[str, datetime.datetime], **kwargs: Any) -> AsyncItemPaged[EnrichmentStatus]

Parameters

metric_id

str

Required

filter feedbacks by metric id.

datetime.datetime] start_time

<xref:Union>[<xref:str,>

Required

start time filter under chosen time mode.

datetime.datetime] end_time

<xref:Union>[<xref:str,>

Required

end time filter under chosen time mode.

skip

int

Returns

Anomaly detection status.

Return type

AsyncItemPaged[EnrichmentStatus]

Exceptions

HttpResponseError

Examples

Query metric enrichment status.

   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))

list_metric_series_data

Get time series data from metric.

list_metric_series_data(metric_id: str, series_keys: List[Dict[str, str]], start_time: Union[str, datetime.datetime], end_time: Union[str, datetime.datetime], **kwargs: Any) -> azure.core.async_paging.AsyncItemPaged[azure.ai.metricsadvisor.models._models.MetricSeriesData]

Parameters

metric_id

str

Required

metric unique id.

series_keys

list[dict[str, str]]

Required

query specific series.

datetime.datetime] start_time

<xref:Union>[<xref:str,>

Required

start time filter under chosen time mode.

datetime.datetime] end_time

<xref:Union>[<xref:str,>

Required

end time filter under chosen time mode.

Returns

Time series data from metric.

Return type

AsyncItemPaged[MetricSeriesData]

Exceptions

HttpResponseError

Examples

Query metrics series data.

   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_series_data(
               metric_id=metric_id,
               start_time=datetime.datetime(2020, 1, 1),
               end_time=datetime.datetime(2020, 10, 21),
               series_keys=[
                   {"city": "Los Angeles", "category": "Homemade"}
               ]
           )
       async for result in results:
           print(str(result))

list_metric_series_definitions

List series (dimension combinations) from metric.

list_metric_series_definitions(metric_id: str, active_since: datetime.datetime, **kwargs: Any) -> AsyncItemPaged[MetricSeriesDefinition]

Parameters

metric_id

str

Required

metric unique id.

active_since

datetime

Required

Required. query series ingested after this time, the format should be yyyy-MM-ddTHH:mm:ssZ.

skip

int

dimension_filter

dict[str, list[str]]

filter specfic dimension name and values.

Returns

Series (dimension combinations) from metric.

Return type

AsyncItemPaged[<xref:azure.ai.metricsadvisor.models.MetricSeriesDefinition>]

Exceptions

HttpResponseError

Examples

Query metric series definitions.

   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_series_definitions(
               metric_id=metric_id,
               active_since=datetime.datetime(2020, 1, 1),
           )
       async for result in results:
           print(str(result))