All Classes and Interfaces

Class
Description
Defines values for AlertQueryTimeMode.
The AnomalyAlert model.
Defines anomaly alerting configuration.
Configuration to detect anomalies in metric time series.
Defines values for AnomalyDetectorDirection.
Describes an incident detected in a time series or a time series group.
Defines values for AnomalyIncidentStatus.
Defines values for AnomalySeverity.
anomaly status only return for alerting anomaly result.
Defines values for AnomalyValue.
The AzureAppInsightsDataFeedSource model.
The AzureBlobDataFeedSource model.
The AzureCosmosDbDataFeedSource model.
The AzureDataExplorerDataFeedSource model.
The AzureDataLakeStorageGen2DataFeedSource model.
The AzureEventHubsDataFeedSource model.
The AzureLogAnalyticsDataFeedSource model.
The AzureTableDataFeedSource model.
Describes the direction of boundary used in anomaly boundary conditions.
The measure type that detector should use for measuring data-points when detecting anomalies using MetricBoundaryCondition.
Defines values for ChangePointValue.
Type that describes change-threshold parameters.
The Data feed metadata model.
Defines values for DataFeedAccessMode.
Defines values for DataFeedAutoRollUpMethod.
Type describing a dimension of a DataFeed.
The DataFeedGranularity model.
The DataFeedGranularityType model
The DataFeedIngestionProgress model.
The data feed ingestion settings model.
The DataFeedIngestionStatus model.
Type describing a metric of a DataFeed.
The DataFeedMissingDataPointFillSettings model.
Defines values for DataFeedMissingDataPointFillType.
The DataFeedOptions model.
The rollup settings for the data feed.
Defines values for DataFeedRollupType.
The DataFeedSchema model.
The DataFeedSource represents the base type for different types of data sources that service can ingest data and perform anomaly detection.
Defines values for all supported data sources types.
Defines values for DataFeedStatus.
Describes an anomaly detected in a metric series.
Defines values for DataSourceAuthenticationType.
The base credential type for different types of authentication that service uses to access the data sources DataFeedSource.
The shared key credential entity for DataLakeGen2.
The service principal credential entity for data source..
The service principal stored in a key vault representing the credential entity for a data source.
The connection credential entity for SQLServer.
The logical operator to apply across anomaly detection conditions.
Describes a Data Feed Metric dimension name-value pairs.
A hook that describes email based incident alerts notification.
The EnrichmentStatus model.
time mode to filter feedback.
feedback type.
Type that describes hard-threshold parameters.
The IncidentRootCause model
The InfluxDbDataFeedSource model.
Defines values for IngestionStatusType.
Describes the additional parameters for the API to list the alerts triggered.
Describes the additional parameters for the API to list anomalies in an alert.
Describes additional conditions to filter the anomalies while listing.
Describes the additional parameters for the API to list anomalies detected.
Additional parameters to set when listing anomaly alerting configurations.
Describes the additional parameters for the API to list values of a dimension that have anomalies.
Additional properties for filtering results on the listCredentialEntities operation.
Additional properties to filter result for data feed list operations.
Describes the additional parameters for the API to list data feed ingestion status.
Additional properties for filtering results on the listDataFeeds operation.
Additional parameters to set when listing anomaly detection configurations.
Describes the additional parameters for the API to list hooks.
Describes the additional parameters for the API to list incidents in an alert.
Describes the additional parameters for the API to list incidents detected.
Additional properties to set when using the API to list dimension values for a metric.
Additional parameters to set when listing enrichment status for a metric.
Additional properties to filter result for metric feedback list operations.
Additional properties for filtering results on the lisMetricFeedbacks operation.
Additional parameters for the API to list metric series definition information for a metric.
Defines alerting settings for anomalies detected by a detection configuration.
The logical operator to apply across multiple MetricAlertConfiguration.
Defines conditions to decide whether the detected anomalies should be included in an alert or not.
Defines scope for anomaly alert.
Defines the supported alert scopes.
Type that describes configuration for snoozing anomaly alerts.
A feedback to indicate a set of data points as Anomaly or NotAnomaly.
Defines the boundary conditions for the anomaly (abnormal data points) to be included in the alert.
The Feedback that allows the user to mark the exact change point when the time series has a trend change.
The feedback that allows adding comments in plain text providing more context about the data.
Enriched time series data which includes additional service computed values for the time series data points.
Users can submit various feedback for the anomaly detection that the service performed.
The Feedback that helps the service in estimating period(seasonality) of the time series.
This class provides asynchronous client to connect to the Metrics Advisor Azure Cognitive Service.
This class provides a synchronous client to connect to the Metrics Advisor Azure Cognitive Service.
This class provides a fluent builder API to help instantiation of MetricsAdvisorAdministrationClients and MetricsAdvisorAdministrationAsyncClient, call MetricsAdvisorAdministrationClientBuilder.buildClient() buildClient} and buildAsyncClient respectively to construct an instance of the desired client.
This class provides an asynchronous client to connect to the Metrics Advisor Azure Cognitive Service.
This class provides a synchronous client to connect to the Metrics Advisor Azure Cognitive Service.
This class provides a fluent builder API to help instantiation of MetricsAdvisorClients and MetricsAdvisorAsyncClients, call MetricsAdvisorClientBuilder.buildClient() buildClient} and buildAsyncClient respectively to construct an instance of the desired client.
The MetricsAdvisorError model.
The MetricsAdvisorKeyCredential class.
Represents a credential bag containing the subscription key and api key.
Exception thrown for an invalid response with ErrorCode information.
The versions of Azure Metrics Advisor supported by this client library.
The MetricSeriesData model.
The MetricSeriesDefinition model.
Conditions to detect anomalies in a group of time series.
Conditions to detect anomalies in a specific time series.
Conditions to detect anomalies in all time series of a metric.
The MongoDbDataFeedSource model.
The MySqlDataFeedSource model.
Describes a hook that receives anomaly incident alerts.
the type of setting period.
The PostgreSqlDataFeedSource model.
Type that describes severity range.
Type that describes smart-detection parameters.
Defines values for SnoozeScope.
The SQLServerDataFeedSource model.
Type that describes suppress condition for anomalies.
The type TopNGroupScope represents the parameters that defines TopN anomaly scope.
A hook that describes web-hook based incident alerts notification.