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Detect Multivariate Anomaly

Submit a multivariate anomaly detection task with the modelId value of a trained model and inference data. The input schema should be the same with the training request. The request will finish asynchronously and return a resultId value to query the detection result. The request should be a source link to indicate an externally accessible Azure Storage URI that either points to an Azure Blob Storage folder or points to a CSV file in Azure Blob Storage.

post/multivariate/models/{modelId}:detect-batch

Path parameters

modelIdstring required

Model identifier.

Request body

dataSourcestring uri required

Source link to the input data to indicate an accessible Azure Storage URI. It either points to an Azure Blob Storage folder or points to a CSV file in Azure Blob Storage, based on your data schema selection. The data schema should be exactly the same as those used in the training phase. The input data must contain at least slidingWindow entries preceding the start time of the data to be detected.

topContributorCountinteger

Number of top contributed variables for one anomalous time stamp in the response.

startTimestring date-time required

Start date/time of data for detection, which should be in ISO 8601 format.

endTimestring date-time required

End date/time of data for detection, which should be in ISO 8601 format.

Response

The request has been accepted for processing, but processing has not yet completed.

resultIdstring uuid required

Universally Unique Identifier

Changes

Changed in 1 of the 2 revisions of this API.1