https://azure.com/timeseries/last/detectThis operation generates a model using points before the latest one. With this method, only historical points are used to determine whether the target point is an anomaly. The latest point detecting operation matches the scenario of real-time monitoring of business metrics.
{
"success": true,
"data": {
"id": "abc123",
"created_at": "2025-01-01T00:00:00Z"
}
}{
"success": false,
"error": {
"code": "VALIDATION_ERROR",
"message": "Invalid request parameters"
}
}1curl --request POST \2 --url 'https://azure.com/timeseries/last/detect' \3 --header 'accept: application/json' \4 --header 'content-type: application/json'1{2 "success": true,3 "data": {4 "id": "abc123",5 "created_at": "2025-01-01T00:00:00Z"6 }7}https://azure.com/timeseries/last/detectThis operation generates a model using points before the latest one. With this method, only historical points are used to determine whether the target point is an anomaly. The latest point detecting operation matches the scenario of real-time monitoring of business metrics.
{
"success": true,
"data": {
"id": "abc123",
"created_at": "2025-01-01T00:00:00Z"
}
}{
"success": false,
"error": {
"code": "VALIDATION_ERROR",
"message": "Invalid request parameters"
}
}1curl --request POST \2 --url 'https://azure.com/timeseries/last/detect' \3 --header 'accept: application/json' \4 --header 'content-type: application/json'1{2 "success": true,3 "data": {4 "id": "abc123",5 "created_at": "2025-01-01T00:00:00Z"6 }7}