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• Request
• Response

Create an Abnormal Profile

post

/api/metric/AbnormalProfiles

Creates an abnormal profile that can be used by abnormal thresholds and the Metric Abnormal Threshold Engine.

Request

There are no request parameters for this operation.

Supported Media Types

• application/json

Request Body - application/json ()

Root Schema : schema

Type: object

Show Source

• AbnormalProfileName: string
  Name of abnormal profile

  Example: Default Abnormal Profile
• Alpha: number
  The degree to which the confidence bands smooth a weighted average (more weight being given to recent observations, less to older observations). Values are from >0 to 1. The closer to 1 the Alpha value becomes, the closer the predicted value will be to the weighted average of the last n observations.

  Example: 0.999497
• Beta: number
  The degree to which the smoothing function considers the slope (amount of increase or decrease) of the weighted average of 2 adjacent data points. Values are from >0 to 1. The closer to 1 the Beta value gets, the more the Algorithm will consider the slope of the previous (n-1) data point to the current data point (n) when predicting the next data point (n+1).

  Example: 0.00224
• Delta: number
  Scaling factor, used to influence the width of the confidence bands generated by the Algorithm. Values are between 2 and 3.

  Example: 3
• Epsilon: number
  Epsilon scaling. Values are >0 to 1.

  Example: 0.492391
• FailureThreshold: integer
  Used with Window Length by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered "abnormal" and an event will be generated.

  Example: 3
• Gamma: number
  The degree to which the smoothing function considers seasonal data when forecasting a data point. Values are >0 to 1. The closer to 1 Gamma gets, the more the Algorithm will weight seasonal patterns when forecasting expected values.

  Example: 0.487092
• WindowLength: integer
  Used with Violation Threshold by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered "abnormal" and an event will be generated. Values are between 0 and 28.

  Example: 5

{
    "properties":{
        "AbnormalProfileName":{
            "description":"Name of abnormal profile",
            "type":"string",
            "example":"Default Abnormal Profile"
        },
        "Alpha":{
            "description":"The degree to which the confidence bands smooth a weighted average (more weight being given to recent observations, less to older observations). Values are from >0 to 1. The closer to 1 the Alpha value becomes, the closer the predicted value will be to the weighted average of the last n observations.",
            "type":"number",
            "example":"0.999497"
        },
        "Beta":{
            "description":"The degree to which the smoothing function considers the slope (amount of increase or decrease) of the weighted average of 2 adjacent data points. Values are from >0 to 1. The closer to 1 the Beta value gets, the more the Algorithm will consider the slope of the previous (n-1) data point to the current data point (n) when predicting the next data point (n+1).",
            "type":"number",
            "example":"0.00224"
        },
        "Gamma":{
            "description":"The degree to which the smoothing function considers seasonal data when forecasting a data point. Values are >0 to 1. The closer to 1 Gamma gets, the more the Algorithm will weight seasonal patterns when forecasting expected values.",
            "type":"number",
            "example":"0.487092"
        },
        "Delta":{
            "description":"Scaling factor, used to influence the width of the confidence bands generated by the Algorithm. Values are between 2 and 3.",
            "type":"number",
            "example":"3"
        },
        "Epsilon":{
            "description":"Epsilon scaling. Values are >0 to 1.",
            "type":"number",
            "example":"0.492391"
        },
        "WindowLength":{
            "description":"Used with Violation Threshold by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered \"abnormal\" and an event will be generated. Values are between 0 and 28.",
            "type":"integer",
            "example":"5"
        },
        "FailureThreshold":{
            "description":"Used with Window Length by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered \"abnormal\" and an event will be generated.",
            "type":"integer",
            "example":"3"
        }
    },
    "type":"object"
}

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Response

Supported Media Types

• application/json

200 Response

Successful operation

Body ()

Root Schema : schema

Match All

Show Source

• object SuccessfulAddOperation
• object type

{
    "allOf":[
        {
            "$ref":"#/components/schemas/SuccessfulAddOperation"
        },
        {
            "type":"object",
            "properties":{
                "total":{
                    "description":"The total number of results regardless of paging.",
                    "type":"integer",
                    "example":"1"
                },
                "data":{
                    "type":"array",
                    "items":{
                        "$ref":"#/components/schemas/metricAbnormalProfilesRead"
                    }
                }
            }
        }
    ]
}

Nested Schema : SuccessfulAddOperation

Type: object

Show Source

• message: string
  The response message.

  Example: Added record
• success: boolean
  Whether the operation was a success (true) or a failure (false).

  Example: true

{
    "properties":{
        "success":{
            "description":"Whether the operation was a success (<b>true</b>) or a failure (<b>false</b>).",
            "type":"boolean",
            "example":"true"
        },
        "message":{
            "description":"The response message.",
            "type":"string",
            "example":"Added record"
        }
    },
    "type":"object"
}

Nested Schema : type

Type: object

Show Source

• data: array data
• total: integer
  The total number of results regardless of paging.

  Example: 1

{
    "type":"object",
    "properties":{
        "total":{
            "description":"The total number of results regardless of paging.",
            "type":"integer",
            "example":"1"
        },
        "data":{
            "type":"array",
            "items":{
                "$ref":"#/components/schemas/metricAbnormalProfilesRead"
            }
        }
    }
}

Nested Schema : data

Type: array

Show Source

• Array of: object metricAbnormalProfilesRead

{
    "type":"array",
    "items":{
        "$ref":"#/components/schemas/metricAbnormalProfilesRead"
    }
}

Nested Schema : metricAbnormalProfilesRead

Type: object

Show Source

• AbnormalProfileID: integer
  Abnormal Profile ID

  Example: 1
• AbnormalProfileName: string
  Name of abnormal profile

  Example: Default Abnormal Profile
• Alpha: number
  The degree to which the confidence bands smooth a weighted average (more weight being given to recent observations, less to older observations). Values are from >0 to 1. The closer to 1 the Alpha value becomes, the closer the predicted value will be to the weighted average of the last n observations.

  Example: 0.999497
• Beta: number
  The degree to which the smoothing function considers the slope (amount of increase or decrease) of the weighted average of 2 adjacent data points. Values are from >0 to 1. The closer to 1 the Beta value gets, the more the Algorithm will consider the slope of the previous (n-1) data point to the current data point (n) when predicting the next data point (n+1).

  Example: 0.00224
• Delta: number
  Scaling factor, used to influence the width of the confidence bands generated by the Algorithm. Values are between 2 and 3.

  Example: 3
• Epsilon: number
  Epsilon scaling. Values are >0 to 1.

  Example: 0.492391
• FailureThreshold: integer
  Used with Window Length by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered "abnormal" and an event will be generated.

  Example: 3
• Gamma: number
  The degree to which the smoothing function considers seasonal data when forecasting a data point. Values are >0 to 1. The closer to 1 Gamma gets, the more the Algorithm will weight seasonal patterns when forecasting expected values.

  Example: 0.487092
• WindowLength: integer
  Used with Violation Threshold by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered "abnormal" and an event will be generated. Values are between 0 and 28.

  Example: 5

{
    "properties":{
        "AbnormalProfileID":{
            "description":"Abnormal Profile ID",
            "type":"integer",
            "example":"1"
        },
        "AbnormalProfileName":{
            "description":"Name of abnormal profile",
            "type":"string",
            "example":"Default Abnormal Profile"
        },
        "Alpha":{
            "description":"The degree to which the confidence bands smooth a weighted average (more weight being given to recent observations, less to older observations). Values are from >0 to 1. The closer to 1 the Alpha value becomes, the closer the predicted value will be to the weighted average of the last n observations.",
            "type":"number",
            "example":"0.999497"
        },
        "Beta":{
            "description":"The degree to which the smoothing function considers the slope (amount of increase or decrease) of the weighted average of 2 adjacent data points. Values are from >0 to 1. The closer to 1 the Beta value gets, the more the Algorithm will consider the slope of the previous (n-1) data point to the current data point (n) when predicting the next data point (n+1).",
            "type":"number",
            "example":"0.00224"
        },
        "Gamma":{
            "description":"The degree to which the smoothing function considers seasonal data when forecasting a data point. Values are >0 to 1. The closer to 1 Gamma gets, the more the Algorithm will weight seasonal patterns when forecasting expected values.",
            "type":"number",
            "example":"0.487092"
        },
        "Delta":{
            "description":"Scaling factor, used to influence the width of the confidence bands generated by the Algorithm. Values are between 2 and 3.",
            "type":"number",
            "example":"3"
        },
        "Epsilon":{
            "description":"Epsilon scaling. Values are >0 to 1.",
            "type":"number",
            "example":"0.492391"
        },
        "WindowLength":{
            "description":"Used with Violation Threshold by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered \"abnormal\" and an event will be generated. Values are between 0 and 28.",
            "type":"integer",
            "example":"5"
        },
        "FailureThreshold":{
            "description":"Used with Window Length by the Abnormal Thresholding Engine to determine whether to generate a threshold violation event. If Violation Threshold data points fall outside the confidence band within a Window Length number of points, then the data points are considered \"abnormal\" and an event will be generated.",
            "type":"integer",
            "example":"3"
        }
    },
    "type":"object"
}

Default Response

Failed operation

Body ()

Root Schema : schema

Type: object

Show Source

• errors: array errors
  The list of errors reported. Validation errors will be keyed by record field.
• message: string
  The response message.

  Example: Exception thrown
• success: boolean
  Whether the operation was a success (true) or a failure (false).

  Example: false

{
    "properties":{
        "success":{
            "description":"Whether the operation was a success (<b>true</b>) or a failure (<b>false</b>).",
            "type":"boolean",
            "example":"false"
        },
        "message":{
            "description":"The response message.",
            "type":"string",
            "example":"Exception thrown"
        },
        "errors":{
            "description":"The list of errors reported. Validation errors will be keyed by record field.",
            "type":"array",
            "items":{
                "type":"object"
            }
        }
    },
    "type":"object"
}

Nested Schema : errors

Type: array

The list of errors reported. Validation errors will be keyed by record field.

Show Source

• Array of: object items

{
    "description":"The list of errors reported. Validation errors will be keyed by record field.",
    "type":"array",
    "items":{
        "type":"object"
    }
}

Nested Schema : items

Type: object

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