Create a MetricBase model trigger

Model triggers execute when the time-series data deviates from expected values.

시작하기 전에

Role required: admin

이 태스크 정보

There are four model types supported: autoregressive integrated moving average (ARIMA), probabilistic exponentially weighted moving average (PEWMA), Holt-Winters, and seasonal trend decomposition using Loess (STL).  MetricBase  uses the model to create a definition of expected, normal values.

프로시저

1. Navigate to All > MetricBase > MetricBase Triggers > Trigger Definitions.
2. Select New.
3. On the MetricBase Trigger Creation form, select the Model Trigger option.
4. On the form, fill in the fields.

   The trigger levels are not initially visible on this form. You configure the levels later.

   Field	Description
   Name	Name the model trigger.
   Model	Trained model this trigger uses. See Create and train a predictive model.
   Metric	Table metric that you want to monitor. This value is set automatically based on the model, which means you cannot set it yourself.
   Table name	Table in the  MetricBase  database that contains the metric that you want to monitor. This value is set automatically based on the model, which means you cannot set it yourself.
   Active	Option to activate the trigger.
   Description	Description of the trigger.
   Spike Direction	Specify whether you want to trigger only on anomalies that occur above predicted values (upward), below predicted values (downward), or both (either).

5. Select Save.
   A new record is created.
6. In the MetricBase Model Trigger Levels area on the record you just created, double-click each cell to add values that specify trigger parameters.

   Column	Description
   Level	Numbers that indicate increasing severity. For example, you might define level 1 to be 2 standard deviations from the mean. Level 2 might be 4 standard deviations. Each level should trigger a different Workflow Studio flow. Level is often used in Condition Scripts. See Execute triggers conditionally.
   Function	Always Greater than or is, meaning that in order to trigger, the time-series metric must be greater than or equal to the number of standard deviations from the mean specified in Number of Standard Deviations.
   Number of Standard Deviation	Float value specifying the number of standard deviations the time-series metric must be away from the mean to trigger an alert at this level.

7. 옵션: Add rows to the table to create multi-layered triggering behavior.
   Typically, each additional row (level) indicates a more severe condition. The Workflow Studio flow associated with the level should warn with increasing severity.
8. Select Update.
9. 옵션: Add a triggering condition that determines whether a trigger executes a Workflow Studio flow.
   See Execute triggers conditionally.
10. Test your model and trigger on real data before deploying to production.

Model Trigger form

다음에 수행할 작업

Associate this trigger with a Workflow Studio flow. For more information, see Assign a trigger to a flow.