• Home
  • Dynatrace API
  • Configuration
  • Anomaly detection
  • Metric event
  • GET an event

Metric events anomaly detection API - GET an event

Gets parameters of the specified metric event rule.

The request produces an application/json payload.

GETManagedDynatrace for Governmenthttps://{your-domain}/e/{your-environment-id}/api/config/v1/anomalyDetection/metricEvents/{id}
SaaShttps://{your-environment-id}.live.dynatrace.com/api/config/v1/anomalyDetection/metricEvents/{id}
Environment ActiveGatehttps://{your-activegate-domain}/e/{your-environment-id}/api/config/v1/anomalyDetection/metricEvents/{id}

Authentication

To execute this request, you need an access token with ReadConfig scope.

To learn how to obtain and use it, see Tokens and authentication.

Parameters

ParameterTypeDescriptionInRequired
idstring

The ID of the required metric event.

pathrequired

Response

To find all JSON models that depend on the type of the model, refer to JSON models.

Response codes

CodeTypeDescription
200MetricEvent

Success

Response body objects

The MetricEvent object

The configuration of the metric event.

ElementTypeDescription
metadataConfigurationMetadata

Metadata useful for debugging

idstring

The ID of the metric event.

metricIdstring

The ID of the metric evaluated by the metric event.

metricSelectorstring

The metric selector that should be executed.

namestring

The name of the metric event displayed in the UI.

descriptionstring

The description of the metric event.

aggregationTypestring

How the metric data points are aggregated for the evaluation.

The timeseries must support this aggregation.

The element can hold these values
  • AVG
  • COUNT
  • MAX
  • MEDIAN
  • MIN
  • P90
  • SUM
  • VALUE
severitystring

The type of the event to trigger on the threshold violation.

The CUSTOM_ALERT type is not correlated with other alerts. The INFO type does not open a problem.

The element can hold these values
  • AVAILABILITY
  • CUSTOM_ALERT
  • ERROR
  • INFO
  • PERFORMANCE
  • RESOURCE_CONTENTION
enabledboolean

The metric event is enabled (true) or disabled (false).

disabledReasonstring

The reason of automatic disabling.

The NONE means config was not disabled automatically.

The element can hold these values
  • METRIC_DEFINITION_INCONSISTENCY
  • NONE
  • TOO_MANY_DIMS
warningReasonstring

The reason of a warning set on the config.

The NONE means config has no warnings.

The element can hold these values
  • NONE
alertingScopeMetricEventAlertingScope[]

Defines the scope of the metric event. Only one filter is allowed per filter type, except for tags, where up to 3 are allowed. The filters are combined by conjunction.

metricDimensionsMetricEventDimensions[]

Defines the dimensions of the metric to alert on. The filters are combined by conjunction.

monitoringStrategyMetricEventMonitoringStrategy

A monitoring strategy for a metric event config.

This is the base version of the monitoring strategy, depending on the type, the actual JSON may contain additional fields.

primaryDimensionKeystring

Defines which dimension key should be used for the alertingScope.

queryOffsetinteger

Defines the query offset to adapt the evaluation timeframe for known metric latency.

The ConfigurationMetadata object

Metadata useful for debugging

ElementTypeDescription
configurationVersionsinteger[]

A sorted list of the version numbers of the configuration.

currentConfigurationVersionsstring[]

A sorted list of version numbers of the configuration.

clusterVersionstring

Dynatrace version.

The MetricEventAlertingScope object

A single filter for the alerting scope.

The actual set of fields depends on type of the filter. Find the list of actual objects in the description of the filterType field or see Metric events anomaly detection API - JSON models.

ElementTypeDescription
filterTypestring

Defines the actual set of fields depending on the value. See one of the following objects:

  • ENTITY_ID -> EntityIdAlertingScope
  • MANAGEMENT_ZONE -> ManagementZoneAlertingScope
  • TAG -> TagFilterAlertingScope
  • NAME -> NameAlertingScope
  • CUSTOM_DEVICE_GROUP_NAME -> CustomDeviceGroupNameAlertingScope
  • HOST_GROUP_NAME -> HostGroupNameAlertingScope
  • HOST_NAME -> HostNameAlertingScope
  • PROCESS_GROUP_ID -> ProcessGroupIdAlertingScope
  • PROCESS_GROUP_NAME -> ProcessGroupNameAlertingScope
The element can hold these values
  • CUSTOM_DEVICE_GROUP_NAME
  • ENTITY_ID
  • HOST_GROUP_NAME
  • HOST_NAME
  • MANAGEMENT_ZONE
  • NAME
  • PROCESS_GROUP_ID
  • PROCESS_GROUP_NAME
  • TAG

The MetricEventDimensions object

A single filter for the metrics dimensions.

The actual set of fields depends on type of the filter. Find the list of actual objects in the description of the filterType field or see Metric events anomaly detection API - JSON models.

ElementTypeDescription
filterTypestring

Defines the actual set of fields depending on the value. See one of the following objects:

  • ENTITY -> MetricEventEntityDimensions
  • STRING -> MetricEventStringDimensions
The element can hold these values
  • ENTITY
  • STRING
keystring

The dimensions key on the metric.

The MetricEventMonitoringStrategy object

A monitoring strategy for a metric event config.

This is the base version of the monitoring strategy, depending on the type, the actual JSON may contain additional fields.

ElementTypeDescription
typestring

Defines the actual set of fields depending on the value. See one of the following objects:

  • STATIC_THRESHOLD -> MetricEventStaticThresholdMonitoringStrategy
  • AUTO_ADAPTIVE_BASELINE -> MetricEventAutoAdaptiveBaselineMonitoringStrategy
The element can hold these values
  • AUTO_ADAPTIVE_BASELINE
  • STATIC_THRESHOLD

Response body JSON model

json
{ "metadata": { "configurationVersions": [ 4, 2 ], "clusterVersion": "Mock version" }, "metricId": "com.dynatrace.builtin:host.disk.bytesread", "name": "My metric event", "description": "This is the description for my metric event.", "aggregationType": "AVG", "severity": "CUSTOM_ALERT", "alertingScope": [ { "filterType": "ENTITY_ID", "entityId": "HOST-000000000001E240" }, { "filterType": "TAG", "tagFilter": { "context": "CONTEXTLESS", "key": "someKey", "value": "someValue" } } ], "metricDimensions": [ { "filterType": "ENTITY", "key": "dt.entity.disk", "nameFilter": { "value": "diskName", "operator": "EQUALS" } } ], "enabled": true, "disabledReason": "NONE", "warningReason": "NONE", "monitoringStrategy": { "type": "STATIC_THRESHOLD", "alertCondition": "ABOVE", "samples": 5, "violatingSamples": 3, "dealertingSamples": 5, "threshold": 80, "unit": "KILO_BYTE_PER_SECOND" } }

Example

In this example, the request lists the parameters of the High OS CPU usage custom metric event rule.

The API token is passed in the Authorization header.

The rule has the following parameters:

Metric event rule

Curl

bash
curl -X GET \ https://mySampleEnv.live.dynatrace.com/api/config/v1/anomalyDetection/metricEvents/dynatrace.remote.python.elasticsearch:node.os.cpu_percent:node.os.cpu_percent.high_usage \ -H 'Authorization: Api-Token dt0c01.abc123.abcdefjhij1234567890'

Request URL

plaintext
https://mySampleEnv.live.dynatrace.com/api/config/v1/anomalyDetection/metricEvents/dynatrace.remote.python.elasticsearch:node.os.cpu_percent:node.os.cpu_percent.high_usage

Response body

json
{ "metadata": { "clusterVersion": "1.164.0.20190211-085949", "configurationVersions": [ 2 ] }, "id": "dynatrace.remote.python.elasticsearch:node.os.cpu_percent:node.os.cpu_percent.high_usage", "metricId": "dynatrace.remote.python.elasticsearch:node.os.cpu_percent", "name": "High OS CPU usage", "description": "The OS CPU usage is {alert_condition} the threshold of {threshold}", "aggregationType": "AVG", "eventType": "PERFORMANCE", "alertCondition": "ABOVE", "samples": 5, "violatingSamples": 3, "dealertingSamples": 5, "threshold": 70, "enabled": true, "tagFilters": [] }

Response code

200

Related topics
  • Prediction-based anomaly detection

    Read how Dynatrace automatically learns each applications’ unique traffic patterns and is thereby able to forecast the application’s traffic.

  • Davis® AI

    Get familiar with the capabilities of Davis AI.