Anomaly Detector v1.1

Anomaly Detector is an AI service with a set of APIs, which enables you to monitor and detect anomalies in your time series data with little ML knowledge, either batch validation or real-time inference. It includes the following features:

  • Univariate Anomaly Detection - Detect different types of anomalies in single variable.
  • Multivariate Anomaly Detection - Detect different types of anomalies in multiple variables from your equipment or system.

Univariate Anomaly Detection - Detect anomalies for the entire series in batch.

This operation generates a model using the points that you sent into the API, and based on all data to determine whether the last point is anomalous. The latest point detecting operation matches the scenario of real-time monitoring of business metrics.

Select the testing console in the region where you created your resource:

Open API testing console

Request URL

Request headers

string
Media type of the body sent to the API.
string
Subscription key which provides access to this API. Found in your Cognitive Services accounts.

Request body

Time series points and period if needed. Advanced model parameters can also be set in the request.

{
  "series": [
    {
      "timestamp": "string",
      "value": 0.0
    }
  ],
  "granularity": "yearly",
  "customInterval": 0,
  "period": 0,
  "maxAnomalyRatio": 0.0,
  "sensitivity": 0,
  "imputeMode": "auto",
  "imputeFixedValue": 0.0
}
{
  "type": "object",
  "description": "The request of entire or last anomaly detection.",
  "required": [
    "series"
  ],
  "properties": {
    "series": {
      "type": "array",
      "description": "Time series data points. Points should be sorted by timestamp in ascending order to match the anomaly detection result. If the data is not sorted correctly or there is duplicated timestamp, the API will not work. In such case, an error message will be returned.",
      "items": {
        "type": "object",
        "description": "The definition of input timeseries points.",
        "required": [
          "value"
        ],
        "properties": {
          "timestamp": {
            "type": "string",
            "format": "date-time",
            "description": "Optional argument, timestamp of a data point (ISO8601 format)."
          },
          "value": {
            "type": "number",
            "format": "float",
            "description": "The measurement of that point, should be float."
          }
        }
      }
    },
    "granularity": {
      "type": "string",
      "description": "Optional argument, can be one of yearly, monthly, weekly, daily, hourly, minutely, secondly, microsecond or none. If granularity is not present, it will be none by default. If granularity is none, the timestamp property in time series point can be absent.",
      "x-ms-enum": {
        "name": "TimeGranularity",
        "modelAsString": false,
        "values": [
          {
            "value": "yearly"
          },
          {
            "value": "monthly"
          },
          {
            "value": "weekly"
          },
          {
            "value": "daily"
          },
          {
            "value": "hourly"
          },
          {
            "name": "perMinute",
            "value": "minutely"
          },
          {
            "name": "perSecond",
            "value": "secondly"
          },
          {
            "value": "microsecond"
          },
          {
            "value": "none"
          }
        ]
      },
      "enum": [
        "yearly",
        "monthly",
        "weekly",
        "daily",
        "hourly",
        "minutely",
        "secondly",
        "microsecond",
        "none"
      ]
    },
    "customInterval": {
      "type": "integer",
      "format": "int32",
      "description": "Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as {\"granularity\":\"minutely\", \"customInterval\":5}."
    },
    "period": {
      "type": "integer",
      "format": "int32",
      "description": "Optional argument, periodic value of a time series. If the value is null or does not present, the API will determine the period automatically."
    },
    "maxAnomalyRatio": {
      "type": "number",
      "format": "float",
      "description": "Optional argument, advanced model parameter, max anomaly ratio in a time series."
    },
    "sensitivity": {
      "type": "integer",
      "format": "int32",
      "description": "Optional argument, advanced model parameter, between 0-99, the lower the value is, the larger the margin value will be which means less anomalies will be accepted."
    },
    "imputeMode": {
      "type": "string",
      "description": "Used to specify how to deal with missing values in the input series, it's used when granularity is not \"none\".",
      "x-ms-enum": {
        "name": "ImputeMode",
        "modelAsString": true,
        "values": [
          {
            "value": "auto"
          },
          {
            "value": "previous"
          },
          {
            "value": "linear"
          },
          {
            "value": "fixed"
          },
          {
            "value": "zero"
          },
          {
            "value": "notFill"
          }
        ]
      },
      "enum": [
        "auto",
        "previous",
        "linear",
        "fixed",
        "zero",
        "notFill"
      ]
    },
    "imputeFixedValue": {
      "type": "number",
      "format": "float",
      "description": "Used to specify the value to fill, it's used when granularity is not \"none\" and imputeMode is \"fixed\"."
    }
  }
}

Response 200

Successful operation.

{
  "period": 0,
  "expectedValues": [
    0.0
  ],
  "upperMargins": [
    0.0
  ],
  "lowerMargins": [
    0.0
  ],
  "isAnomaly": [
    true
  ],
  "isNegativeAnomaly": [
    true
  ],
  "isPositiveAnomaly": [
    true
  ],
  "severity": [
    0.0
  ]
}
{
  "type": "object",
  "description": "The response of entire anomaly detection.",
  "required": [
    "expectedValues",
    "isAnomaly",
    "isNegativeAnomaly",
    "isPositiveAnomaly",
    "lowerMargins",
    "period",
    "upperMargins"
  ],
  "properties": {
    "period": {
      "type": "integer",
      "format": "int32",
      "description": "Frequency extracted from the series, zero means no recurrent pattern has been found."
    },
    "expectedValues": {
      "type": "array",
      "description": "ExpectedValues contain expected value for each input point. The index of the array is consistent with the input series.",
      "items": {
        "type": "number",
        "format": "float"
      }
    },
    "upperMargins": {
      "type": "array",
      "description": "UpperMargins contain upper margin of each input point. UpperMargin is used to calculate upperBoundary, which equals to expectedValue + (100 - marginScale)*upperMargin. Anomalies in response can be filtered by upperBoundary and lowerBoundary. By adjusting marginScale value, less significant anomalies can be filtered in client side. The index of the array is consistent with the input series.",
      "items": {
        "type": "number",
        "format": "float"
      }
    },
    "lowerMargins": {
      "type": "array",
      "description": "LowerMargins contain lower margin of each input point. LowerMargin is used to calculate lowerBoundary, which equals to expectedValue - (100 - marginScale)*lowerMargin. Points between the boundary can be marked as normal ones in client side. The index of the array is consistent with the input series.",
      "items": {
        "type": "number",
        "format": "float"
      }
    },
    "isAnomaly": {
      "type": "array",
      "description": "IsAnomaly contains anomaly properties for each input point. True means an anomaly either negative or positive has been detected. The index of the array is consistent with the input series.",
      "items": {
        "type": "boolean"
      }
    },
    "isNegativeAnomaly": {
      "type": "array",
      "description": "IsNegativeAnomaly contains anomaly status in negative direction for each input point. True means a negative anomaly has been detected. A negative anomaly means the point is detected as an anomaly and its real value is smaller than the expected one. The index of the array is consistent with the input series.",
      "items": {
        "type": "boolean"
      }
    },
    "isPositiveAnomaly": {
      "type": "array",
      "description": "IsPositiveAnomaly contain anomaly status in positive direction for each input point. True means a positive anomaly has been detected. A positive anomaly means the point is detected as an anomaly and its real value is larger than the expected one. The index of the array is consistent with the input series.",
      "items": {
        "type": "boolean"
      }
    },
    "severity": {
      "type": "array",
      "description": "The severity score for each input point. The larger the value is, the more sever the anomaly is. For normal points, the \"severity\" is always 0.",
      "items": {
        "type": "number",
        "format": "float"
      }
    }
  }
}

Response 500

Error response.

{
  "code": "InvalidCustomInterval",
  "message": "string"
}
{
  "type": "object",
  "description": "Error information returned by the API.",
  "properties": {
    "code": {
      "description": "The error code.",
      "enum": [
        "InvalidCustomInterval",
        "BadArgument",
        "InvalidGranularity",
        "InvalidPeriod",
        "InvalidModelArgument",
        "InvalidSeries",
        "InvalidJsonFormat",
        "RequiredGranularity",
        "RequiredSeries",
        "InvalidImputeMode",
        "InvalidImputeFixedValue"
      ],
      "x-ms-enum": {
        "name": "AnomalyDetectorErrorCodes",
        "modelAsString": true
      }
    },
    "message": {
      "description": "A message explaining the error reported by the service.",
      "type": "string"
    }
  }
}

Code samples

@ECHO OFF

curl -v -X POST "https://francecentral.api.cognitive.microsoft.com/anomalydetector/v1.1/timeseries/entire/detect"
-H "Content-Type: application/json"
-H "Ocp-Apim-Subscription-Key: {subscription key}"

--data-ascii "{body}" 

using System;
using System.Net.Http.Headers;
using System.Text;
using System.Net.Http;
using System.Web;

namespace CSHttpClientSample
{
    static class Program
    {
        static void Main()
        {
            MakeRequest();
            Console.WriteLine("Hit ENTER to exit...");
            Console.ReadLine();
        }
        
        static async void MakeRequest()
        {
            var client = new HttpClient();
            var queryString = HttpUtility.ParseQueryString(string.Empty);

            // Request headers
            client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "{subscription key}");

            var uri = "https://francecentral.api.cognitive.microsoft.com/anomalydetector/v1.1/timeseries/entire/detect?" + queryString;

            HttpResponseMessage response;

            // Request body
            byte[] byteData = Encoding.UTF8.GetBytes("{body}");

            using (var content = new ByteArrayContent(byteData))
            {
               content.Headers.ContentType = new MediaTypeHeaderValue("< your content type, i.e. application/json >");
               response = await client.PostAsync(uri, content);
            }

        }
    }
}	
// // This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
import java.net.URI;
import org.apache.http.HttpEntity;
import org.apache.http.HttpResponse;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.utils.URIBuilder;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;

public class JavaSample 
{
    public static void main(String[] args) 
    {
        HttpClient httpclient = HttpClients.createDefault();

        try
        {
            URIBuilder builder = new URIBuilder("https://francecentral.api.cognitive.microsoft.com/anomalydetector/v1.1/timeseries/entire/detect");


            URI uri = builder.build();
            HttpPost request = new HttpPost(uri);
            request.setHeader("Content-Type", "application/json");
            request.setHeader("Ocp-Apim-Subscription-Key", "{subscription key}");


            // Request body
            StringEntity reqEntity = new StringEntity("{body}");
            request.setEntity(reqEntity);

            HttpResponse response = httpclient.execute(request);
            HttpEntity entity = response.getEntity();

            if (entity != null) 
            {
                System.out.println(EntityUtils.toString(entity));
            }
        }
        catch (Exception e)
        {
            System.out.println(e.getMessage());
        }
    }
}


<!DOCTYPE html>
<html>
<head>
    <title>JSSample</title>
    <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js"></script>
</head>
<body>

<script type="text/javascript">
    $(function() {
        var params = {
            // Request parameters
        };
      
        $.ajax({
            url: "https://francecentral.api.cognitive.microsoft.com/anomalydetector/v1.1/timeseries/entire/detect?" + $.param(params),
            beforeSend: function(xhrObj){
                // Request headers
                xhrObj.setRequestHeader("Content-Type","application/json");
                xhrObj.setRequestHeader("Ocp-Apim-Subscription-Key","{subscription key}");
            },
            type: "POST",
            // Request body
            data: "{body}",
        })
        .done(function(data) {
            alert("success");
        })
        .fail(function() {
            alert("error");
        });
    });
</script>
</body>
</html>

#import <Foundation/Foundation.h>

int main(int argc, const char * argv[])
{
    NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
    
    NSString* path = @"https://francecentral.api.cognitive.microsoft.com/anomalydetector/v1.1/timeseries/entire/detect";
    NSArray* array = @[
                         // Request parameters
                         @"entities=true",
                      ];
    
    NSString* string = [array componentsJoinedByString:@"&"];
    path = [path stringByAppendingFormat:@"?%@", string];

    NSLog(@"%@", path);

    NSMutableURLRequest* _request = [NSMutableURLRequest requestWithURL:[NSURL URLWithString:path]];
    [_request setHTTPMethod:@"POST"];
    // Request headers
    [_request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
    [_request setValue:@"{subscription key}" forHTTPHeaderField:@"Ocp-Apim-Subscription-Key"];
    // Request body
    [_request setHTTPBody:[@"{body}" dataUsingEncoding:NSUTF8StringEncoding]];
    
    NSURLResponse *response = nil;
    NSError *error = nil;
    NSData* _connectionData = [NSURLConnection sendSynchronousRequest:_request returningResponse:&response error:&error];

    if (nil != error)
    {
        NSLog(@"Error: %@", error);
    }
    else
    {
        NSError* error = nil;
        NSMutableDictionary* json = nil;
        NSString* dataString = [[NSString alloc] initWithData:_connectionData encoding:NSUTF8StringEncoding];
        NSLog(@"%@", dataString);
        
        if (nil != _connectionData)
        {
            json = [NSJSONSerialization JSONObjectWithData:_connectionData options:NSJSONReadingMutableContainers error:&error];
        }
        
        if (error || !json)
        {
            NSLog(@"Could not parse loaded json with error:%@", error);
        }
        
        NSLog(@"%@", json);
        _connectionData = nil;
    }
    
    [pool drain];

    return 0;
}

<?php
// This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
require_once 'HTTP/Request2.php';

$request = new Http_Request2('https://francecentral.api.cognitive.microsoft.com/anomalydetector/v1.1/timeseries/entire/detect');
$url = $request->getUrl();

$headers = array(
    // Request headers
    'Content-Type' => 'application/json',
    'Ocp-Apim-Subscription-Key' => '{subscription key}',
);

$request->setHeader($headers);

$parameters = array(
    // Request parameters
);

$url->setQueryVariables($parameters);

$request->setMethod(HTTP_Request2::METHOD_POST);

// Request body
$request->setBody("{body}");

try
{
    $response = $request->send();
    echo $response->getBody();
}
catch (HttpException $ex)
{
    echo $ex;
}

?>
########### Python 2.7 #############
import httplib, urllib, base64

headers = {
    # Request headers
    'Content-Type': 'application/json',
    'Ocp-Apim-Subscription-Key': '{subscription key}',
}

params = urllib.urlencode({
})

try:
    conn = httplib.HTTPSConnection('francecentral.api.cognitive.microsoft.com')
    conn.request("POST", "/anomalydetector/v1.1/timeseries/entire/detect?%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################

########### Python 3.2 #############
import http.client, urllib.request, urllib.parse, urllib.error, base64

headers = {
    # Request headers
    'Content-Type': 'application/json',
    'Ocp-Apim-Subscription-Key': '{subscription key}',
}

params = urllib.parse.urlencode({
})

try:
    conn = http.client.HTTPSConnection('francecentral.api.cognitive.microsoft.com')
    conn.request("POST", "/anomalydetector/v1.1/timeseries/entire/detect?%s" % params, "{body}", headers)
    response = conn.getresponse()
    data = response.read()
    print(data)
    conn.close()
except Exception as e:
    print("[Errno {0}] {1}".format(e.errno, e.strerror))

####################################
require 'net/http'

uri = URI('https://francecentral.api.cognitive.microsoft.com/anomalydetector/v1.1/timeseries/entire/detect')
uri.query = URI.encode_www_form({
})

request = Net::HTTP::Post.new(uri.request_uri)
# Request headers
request['Content-Type'] = 'application/json'
# Request headers
request['Ocp-Apim-Subscription-Key'] = '{subscription key}'
# Request body
request.body = "{body}"

response = Net::HTTP.start(uri.host, uri.port, :use_ssl => uri.scheme == 'https') do |http|
    http.request(request)
end

puts response.body