Uses of Class
com.azure.ai.metricsadvisor.administration.models.AnomalyDetectionConfiguration
Packages that use AnomalyDetectionConfiguration
Package
Description
Azure Metrics Advisor is a
cloud-based service provided by Microsoft Azure that is designed to help organizations monitor
and analyze metrics and time-series data from various sources.
Package containing model types for Metrics Advisor administration operations.
Package containing the data models for MetricsAdvisor.
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Uses of AnomalyDetectionConfiguration in com.azure.ai.metricsadvisor.administration
Methods in com.azure.ai.metricsadvisor.administration that return AnomalyDetectionConfigurationModifier and TypeMethodDescriptionMetricsAdvisorAdministrationClient.createDetectionConfig(String metricId, AnomalyDetectionConfiguration detectionConfiguration) Create a configuration to detect anomalies in the time series of a metric.MetricsAdvisorAdministrationClient.getDetectionConfig(String detectionConfigurationId) Get the anomaly detection configuration by its id.MetricsAdvisorAdministrationClient.updateDetectionConfig(AnomalyDetectionConfiguration detectionConfiguration) Update a configuration to detect anomalies in the time series of a metric.Methods in com.azure.ai.metricsadvisor.administration that return types with arguments of type AnomalyDetectionConfigurationModifier and TypeMethodDescriptionMetricsAdvisorAdministrationAsyncClient.createDetectionConfig(String metricId, AnomalyDetectionConfiguration detectionConfiguration) Create a configuration to detect anomalies in the time series of a metric.Mono<com.azure.core.http.rest.Response<AnomalyDetectionConfiguration>> MetricsAdvisorAdministrationAsyncClient.createDetectionConfigWithResponse(String metricId, AnomalyDetectionConfiguration detectionConfiguration) Create a configuration to detect anomalies in the time series of a metric.com.azure.core.http.rest.Response<AnomalyDetectionConfiguration> MetricsAdvisorAdministrationClient.createDetectionConfigWithResponse(String metricId, AnomalyDetectionConfiguration detectionConfiguration, com.azure.core.util.Context context) Create a configuration to detect anomalies in the time series of a metric.MetricsAdvisorAdministrationAsyncClient.getDetectionConfig(String detectionConfigurationId) Get the anomaly detection configuration by its id.Mono<com.azure.core.http.rest.Response<AnomalyDetectionConfiguration>> MetricsAdvisorAdministrationAsyncClient.getDetectionConfigWithResponse(String detectionConfigurationId) Get the anomaly detection configuration by its id.com.azure.core.http.rest.Response<AnomalyDetectionConfiguration> MetricsAdvisorAdministrationClient.getDetectionConfigWithResponse(String detectionConfigurationId, com.azure.core.util.Context context) Get the anomaly detection configuration by its id.com.azure.core.http.rest.PagedFlux<AnomalyDetectionConfiguration> MetricsAdvisorAdministrationAsyncClient.listDetectionConfigs(String metricId) Given a metric id, retrieve all anomaly detection configurations applied to it.com.azure.core.http.rest.PagedFlux<AnomalyDetectionConfiguration> MetricsAdvisorAdministrationAsyncClient.listDetectionConfigs(String metricId, ListDetectionConfigsOptions listDetectionConfigsOptions) Given a metric id, retrieve all anomaly detection configurations applied to it.com.azure.core.http.rest.PagedIterable<AnomalyDetectionConfiguration> MetricsAdvisorAdministrationClient.listDetectionConfigs(String metricId) Given a metric id, retrieve all anomaly detection configurations applied to it.com.azure.core.http.rest.PagedIterable<AnomalyDetectionConfiguration> MetricsAdvisorAdministrationClient.listDetectionConfigs(String metricId, ListDetectionConfigsOptions options, com.azure.core.util.Context context) Given a metric id, retrieve all anomaly detection configurations applied to it.MetricsAdvisorAdministrationAsyncClient.updateDetectionConfig(AnomalyDetectionConfiguration detectionConfiguration) Update a configuration to detect anomalies in the time series of a metric.Mono<com.azure.core.http.rest.Response<AnomalyDetectionConfiguration>> MetricsAdvisorAdministrationAsyncClient.updateDetectionConfigWithResponse(AnomalyDetectionConfiguration detectionConfiguration) Update a configuration to detect anomalies in the time series of a metric.com.azure.core.http.rest.Response<AnomalyDetectionConfiguration> MetricsAdvisorAdministrationClient.updateDetectionConfigWithResponse(AnomalyDetectionConfiguration detectionConfiguration, com.azure.core.util.Context context) Update a configuration to detect anomalies in the time series of a metric.Methods in com.azure.ai.metricsadvisor.administration with parameters of type AnomalyDetectionConfigurationModifier and TypeMethodDescriptionMetricsAdvisorAdministrationAsyncClient.createDetectionConfig(String metricId, AnomalyDetectionConfiguration detectionConfiguration) Create a configuration to detect anomalies in the time series of a metric.MetricsAdvisorAdministrationClient.createDetectionConfig(String metricId, AnomalyDetectionConfiguration detectionConfiguration) Create a configuration to detect anomalies in the time series of a metric.Mono<com.azure.core.http.rest.Response<AnomalyDetectionConfiguration>> MetricsAdvisorAdministrationAsyncClient.createDetectionConfigWithResponse(String metricId, AnomalyDetectionConfiguration detectionConfiguration) Create a configuration to detect anomalies in the time series of a metric.com.azure.core.http.rest.Response<AnomalyDetectionConfiguration> MetricsAdvisorAdministrationClient.createDetectionConfigWithResponse(String metricId, AnomalyDetectionConfiguration detectionConfiguration, com.azure.core.util.Context context) Create a configuration to detect anomalies in the time series of a metric.MetricsAdvisorAdministrationAsyncClient.updateDetectionConfig(AnomalyDetectionConfiguration detectionConfiguration) Update a configuration to detect anomalies in the time series of a metric.MetricsAdvisorAdministrationClient.updateDetectionConfig(AnomalyDetectionConfiguration detectionConfiguration) Update a configuration to detect anomalies in the time series of a metric.Mono<com.azure.core.http.rest.Response<AnomalyDetectionConfiguration>> MetricsAdvisorAdministrationAsyncClient.updateDetectionConfigWithResponse(AnomalyDetectionConfiguration detectionConfiguration) Update a configuration to detect anomalies in the time series of a metric.com.azure.core.http.rest.Response<AnomalyDetectionConfiguration> MetricsAdvisorAdministrationClient.updateDetectionConfigWithResponse(AnomalyDetectionConfiguration detectionConfiguration, com.azure.core.util.Context context) Update a configuration to detect anomalies in the time series of a metric. -
Uses of AnomalyDetectionConfiguration in com.azure.ai.metricsadvisor.administration.models
Methods in com.azure.ai.metricsadvisor.administration.models that return AnomalyDetectionConfigurationModifier and TypeMethodDescriptionAnomalyDetectionConfiguration.addSeriesGroupDetectionCondition(MetricSeriesGroupDetectionCondition groupCondition) Adds anomaly detection condition for a specific group of time series.AnomalyDetectionConfiguration.addSingleSeriesDetectionCondition(MetricSingleSeriesDetectionCondition seriesCondition) Adds anomaly detection condition for a specific time series.AnomalyDetectionConfiguration.removeSeriesGroupDetectionCondition(DimensionKey seriesGroupKey) Removes anomaly detection condition for a specific group of time series.AnomalyDetectionConfiguration.removeSingleSeriesDetectionCondition(DimensionKey seriesKey) Removes anomaly detection condition for a specific time series.AnomalyDetectionConfiguration.setDescription(String description) Sets the configuration description.Sets the configuration name.AnomalyDetectionConfiguration.setWholeSeriesDetectionCondition(MetricWholeSeriesDetectionCondition wholeSeriesCondition) Sets the common anomaly detection conditions for all time series of the metric. -
Uses of AnomalyDetectionConfiguration in com.azure.ai.metricsadvisor.models
Methods in com.azure.ai.metricsadvisor.models that return AnomalyDetectionConfigurationModifier and TypeMethodDescriptionMetricAnomalyFeedback.getDetectionConfiguration()Get the corresponding anomaly detection configuration of this feedback.