https://azure.com/timeseries/last/detectThe operation will generate a model using points before the latest one, In this method, only history points are used for determine whether the target point is an anomaly. Latest point detecting 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/detectThe operation will generate a model using points before the latest one, In this method, only history points are used for determine whether the target point is an anomaly. Latest point detecting 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}