Microsoft Azure Multivariate API

openapi: 3.2.0
info:
  title: Microsoft Azure Anomaly Detector Multivariate API
  version: v1.1
  description: The Anomaly Detector API detects anomalies automatically in time series data.
  x-typespec-generated:
  - emitter: '@azure-tools/typespec-autorest'
security:
- AnomalyDetectorApiKeyAuth: []
tags:
- name: Multivariate
paths:
  /multivariate/detect-batch/{resultId}:
    get:
      operationId: microsoftAzureMultivariateGetmultivariatebatchdetectionresult
      summary: Microsoft Azure Get Multivariate Anomaly Detection Result
      description: 'For asynchronous inference, get a multivariate anomaly detection result based on the

        resultId value that the BatchDetectAnomaly API returns.'
      parameters:
      - name: resultId
        in: path
        description: ID of a batch detection result.
        required: true
        schema:
          type: string
          format: uuid
      responses:
        '200':
          description: The request has succeeded.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.MultivariateDetectionResult'
        default:
          description: An unexpected error response.
          headers:
            x-ms-error-code:
              description: Error code.
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.ResponseError'
      x-ms-examples:
        Get multivariate batch detection result:
          $ref: ./examples/GetResult.json
      tags:
      - Multivariate
  /multivariate/models:
    get:
      operationId: microsoftAzureMultivariateListmultivariatemodels
      summary: Microsoft Azure List Multivariate Models
      description: List models of a resource.
      parameters:
      - $ref: '#/components/parameters/Azure.Core.SkipQueryParameter'
      - $ref: '#/components/parameters/Azure.Core.TopQueryParameter'
      responses:
        '200':
          description: The request has succeeded.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.ModelList'
        default:
          description: An unexpected error response.
          headers:
            x-ms-error-code:
              description: Error code.
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.ResponseError'
      x-ms-examples:
        List multivariate models:
          $ref: ./examples/ListModel.json
      x-ms-pageable:
        nextLinkName: nextLink
      tags:
      - Multivariate
    post:
      operationId: microsoftAzureMultivariateTrainmultivariatemodel
      summary: Microsoft Azure Train A Multivariate Anomaly Detection Model
      description: 'Create and train a multivariate anomaly detection model. The request must

        include a source parameter to indicate an Azure Blob

        Storage URI that''s accessible to the service. There are two types of data input. The Blob Storage URI can point to an Azure Blob

        Storage folder that contains multiple CSV files, where each CSV file has

        two columns, time stamp and variable. Or the Blob Storage URI can point to a single blob that contains a CSV file that has all the variables and a

        time stamp column.

        The model object will be created and returned in the response, but the

        training process happens asynchronously. To check the training status, call

        GetMultivariateModel with the modelId value and check the status field in the

        modelInfo object.'
      responses:
        '201':
          description: The request has succeeded and a new resource has been created as a result.
          headers:
            location:
              description: Location and ID of the model.
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.AnomalyDetectionModel'
        default:
          description: An unexpected error response.
          headers:
            x-ms-error-code:
              description: Error code.
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.ResponseError'
      x-ms-examples:
        Create and train multivariate model:
          $ref: ./examples/TrainModel.json
      tags:
      - Multivariate
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/Multivariate.ModelInfo'
        description: Model information.
        required: true
  /multivariate/models/{modelId}:
    get:
      operationId: microsoftAzureMultivariateGetmultivariatemodel
      summary: Microsoft Azure Get Multivariate Model
      description: 'Get detailed information about the multivariate model, including the training status

        and variables used in the model.'
      parameters:
      - name: modelId
        in: path
        description: Model identifier.
        required: true
        schema:
          type: string
      responses:
        '200':
          description: The request has succeeded.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.AnomalyDetectionModel'
        default:
          description: An unexpected error response.
          headers:
            x-ms-error-code:
              description: Error code.
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.ResponseError'
      x-ms-examples:
        Get a multivariate model:
          $ref: ./examples/GetModel.json
      tags:
      - Multivariate
    delete:
      operationId: microsoftAzureMultivariateDeletemultivariatemodel
      summary: Microsoft Azure Delete Multivariate Model
      description: Delete an existing multivariate model according to the modelId value.
      parameters:
      - name: modelId
        in: path
        description: Model identifier.
        required: true
        schema:
          type: string
      responses:
        '204':
          description: 'There is no content to send for this request, but the headers may be useful. '
        default:
          description: An unexpected error response.
          headers:
            x-ms-error-code:
              description: Error code.
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.ResponseError'
      x-ms-examples:
        Delete multivariate model:
          $ref: ./examples/DeleteModel.json
      tags:
      - Multivariate
  /multivariate/models/{modelId}:detect-batch:
    post:
      operationId: microsoftAzureMultivariateDetectmultivariatebatchanomaly
      summary: Microsoft Azure Detect Multivariate Anomaly
      description: '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.'
      parameters:
      - name: modelId
        in: path
        description: Model identifier.
        required: true
        schema:
          type: string
      responses:
        '202':
          description: The request has been accepted for processing, but processing has not yet completed.
          headers:
            Operation-Id:
              description: ID of the detection result.
              schema:
                type: string
            Operation-Location:
              description: Location of the detection result.
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.MultivariateDetectionResult'
        default:
          description: An unexpected error response.
          headers:
            x-ms-error-code:
              description: Error code.
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.ResponseError'
      x-ms-examples:
        Detect multivariate batch anomaly:
          $ref: ./examples/DetectAnomaly.json
      tags:
      - Multivariate
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/Multivariate.MultivariateBatchDetectionOptions'
        description: Request of multivariate anomaly detection.
        required: true
  /multivariate/models/{modelId}:detect-last:
    post:
      operationId: microsoftAzureMultivariateDetectmultivariatelastanomaly
      summary: Microsoft Azure Detect Anomalies In The Last Point Of The Request Body
      description: 'Submit a multivariate anomaly detection task with the modelId value of a trained model

        and inference data. The inference data should be put into the request body in

        JSON format. The request will finish synchronously and return the detection

        immediately in the response body.'
      parameters:
      - name: modelId
        in: path
        description: Model identifier.
        required: true
        schema:
          type: string
      responses:
        '200':
          description: The request has succeeded.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.MultivariateLastDetectionResult'
        default:
          description: An unexpected error response.
          headers:
            x-ms-error-code:
              description: Error code.
              schema:
                type: string
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Multivariate.ResponseError'
      x-ms-examples:
        Detect multivariate last anomaly:
          $ref: ./examples/LastDetectAnomaly.json
      tags:
      - Multivariate
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/Multivariate.MultivariateLastDetectionOptions'
        description: Request of the last detection.
        required: true
components:
  schemas:
    Multivariate.MultivariateBatchDetectionResultSummary:
      type: object
      description: Multivariate anomaly detection status.
      properties:
        status:
          $ref: '#/components/schemas/Multivariate.MultivariateBatchDetectionStatus'
          description: Status of detection results.
        errors:
          type: array
          description: Error message when detection fails.
          items:
            $ref: '#/components/schemas/Multivariate.ErrorResponse'
          x-ms-identifiers: []
        variableStates:
          type: array
          description: Variable status.
          items:
            $ref: '#/components/schemas/Multivariate.VariableState'
          x-ms-identifiers: []
        setupInfo:
          $ref: '#/components/schemas/Multivariate.MultivariateBatchDetectionOptions'
          description: 'Detection request for batch inference. This is an asynchronous inference that

            will need another API to get detection results.'
      required:
      - status
      - setupInfo
    Multivariate.ModelStatus:
      type: string
      enum:
      - CREATED
      - RUNNING
      - READY
      - FAILED
      x-ms-enum:
        name: ModelStatus
        modelAsString: true
        values:
        - name: Created
          value: CREATED
          description: The model has been created. Training has been scheduled but not yet started.
        - name: Running
          value: RUNNING
          description: The model is being trained.
        - name: Ready
          value: READY
          description: The model has been trained and is ready to be used for anomaly detection.
        - name: Failed
          value: FAILED
          description: The model training failed.
    Multivariate.AlignPolicy:
      type: object
      description: Manner of aligning multiple variables.
      properties:
        alignMode:
          $ref: '#/components/schemas/Multivariate.AlignMode'
          description: 'Field that indicates how to align different variables to the same

            time range.'
        fillNAMethod:
          $ref: '#/components/schemas/Multivariate.FillNAMethod'
          description: Field that indicates how missing values will be filled.
        paddingValue:
          type: number
          format: float
          description: Field that's required when fillNAMethod is Fixed.
    Multivariate.CorrelationChanges:
      type: object
      description: Correlation changes among the anomalous variables.
      properties:
        changedVariables:
          type: array
          description: Correlated variables that have correlation changes under an anomaly.
          items:
            type: string
    Multivariate.ModelInfo:
      type: object
      description: 'Training result of a model, including its status, errors, and diagnostics

        information.'
      properties:
        dataSource:
          type: string
          format: uri
          description: '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.'
        dataSchema:
          $ref: '#/components/schemas/Multivariate.DataSchema'
          description: 'Data schema of the input data source. The default

            is OneTable.'
        startTime:
          type: string
          format: date-time
          description: 'Start date/time of training data, which should be

            in ISO 8601 format.'
        endTime:
          type: string
          format: date-time
          description: 'End date/time of training data, which should be

            in ISO 8601 format.'
        displayName:
          type: string
          description: 'Display name of the model. Maximum length is 24

            characters.'
          maxLength: 24
        slidingWindow:
          type: integer
          format: int32
          description: 'Number of previous time stamps that will be used to

            detect whether the time stamp is an anomaly or not.'
        alignPolicy:
          $ref: '#/components/schemas/Multivariate.AlignPolicy'
          description: Manner of aligning multiple variables.
        status:
          $ref: '#/components/schemas/Multivariate.ModelStatus'
          description: Model status.
          readOnly: true
        errors:
          type: array
          description: Error messages after failure to create a model.
          items:
            $ref: '#/components/schemas/Multivariate.ErrorResponse'
          readOnly: true
          x-ms-identifiers: []
        diagnosticsInfo:
          $ref: '#/components/schemas/Multivariate.DiagnosticsInfo'
          description: Diagnostics information to help inspect the states of a model or variable.
          readOnly: true
      required:
      - dataSource
      - startTime
      - endTime
    Multivariate.DataSchema:
      type: string
      description: Data schema of the input data source. The default is OneTable.
      enum:
      - OneTable
      - MultiTable
      x-ms-enum:
        name: DataSchema
        modelAsString: true
        values:
        - name: OneTable
          value: OneTable
          description: OneTable means that your input data is in one CSV file, which contains one time stamp column and several variable columns. The default DataSchema value is OneTable.
        - name: MultiTable
          value: MultiTable
          description: MultiTable means that your input data is separated in multiple CSV files. Each file contains one time stamp column and one variable column, and the CSV file name should indicate the name of the variable. The default DataSchema value is OneTable.
    Multivariate.MultivariateLastDetectionOptions:
      type: object
      description: Request of the last detection.
      properties:
        variables:
          type: array
          description: 'Contains the inference data, including the name, time stamps (ISO 8601), and

            values of variables.'
          items:
            $ref: '#/components/schemas/Multivariate.VariableValues'
          x-ms-identifiers: []
        topContributorCount:
          type: integer
          format: int32
          description: 'Number of top contributed

            variables for one anomalous time stamp in the response. The default is

            10.'
          default: 10
      required:
      - variables
    Multivariate.AlignMode:
      type: string
      enum:
      - Inner
      - Outer
      x-ms-enum:
        name: AlignMode
        modelAsString: true
    Azure.Core.uuid:
      type: string
      format: uuid
      description: Universally Unique Identifier
    Multivariate.AnomalyInterpretation:
      type: object
      description: Interpretation of the anomalous time stamp.
      properties:
        variable:
          type: string
          description: Variable.
        contributionScore:
          type: number
          format: float
          description: 'This score shows the percentage that contributes to the anomalous time stamp. It''s a

            number between 0 and 1.'
        correlationChanges:
          $ref: '#/components/schemas/Multivariate.CorrelationChanges'
          description: Correlation changes among the anomalous variables.
    Multivariate.MultivariateBatchDetectionStatus:
      type: string
      enum:
      - CREATED
      - RUNNING
      - READY
      - FAILED
      x-ms-enum:
        name: MultivariateBatchDetectionStatus
        modelAsString: true
        values:
        - name: Created
          value: CREATED
        - name: Running
          value: RUNNING
        - name: Ready
          value: READY
        - name: Failed
          value: FAILED
    Multivariate.AnomalyValue:
      type: object
      description: Detailed information of the anomalous time stamp.
      properties:
        isAnomaly:
          type: boolean
          description: True if an anomaly is detected at the current time stamp.
        severity:
          type: number
          format: float
          description: 'Indicates the significance of the anomaly. The higher the severity, the more

            significant the anomaly is.'
          minimum: 0
          maximum: 1
        score:
          type: number
          format: float
          description: Raw anomaly score of severity, to help indicate the degree of abnormality.
          minimum: 0
          maximum: 2
        interpretation:
          type: array
          description: Interpretation of this anomalous time stamp.
          items:
            $ref: '#/components/schemas/Multivariate.AnomalyInterpretation'
          x-ms-identifiers: []
      required:
      - isAnomaly
      - severity
      - score
    Multivariate.VariableValues:
      type: object
      description: Variable values.
      properties:
        variable:
          type: string
          description: Variable name of the last detection request.
        timestamps:
          type: array
          description: Time stamps of the last detection request.
          items:
            type: string
        values:
          type: array
          description: Values of variables.
          items:
            type: number
            format: float
      required:
      - variable
      - timestamps
      - values
    Multivariate.ModelList:
      type: object
      description: Response of listing models.
      properties:
        models:
          type: array
          description: List of models.
          items:
            $ref: '#/components/schemas/Multivariate.AnomalyDetectionModel'
          x-ms-identifiers: []
        currentCount:
          type: integer
          format: int32
          description: Number of trained multivariate models.
        maxCount:
          type: integer
          format: int32
          description: Maximum number of models that can be trained for this Anomaly Detector resource.
        nextLink:
          type: string
          description: Link to fetch more models.
      required:
      - models
      - currentCount
      - maxCount
    Multivariate.VariableState:
      type: object
      description: Variable status.
      properties:
        variable:
          type: string
          description: Variable name in variable states.
        filledNARatio:
          type: number
          format: float
          description: Proportion of missing values that need to be filled by fillNAMethod.
          minimum: 0
          maximum: 1
        effectiveCount:
          type: integer
          format: int32
          description: Number of effective data points before fillNAMethod is applied.
        firstTimestamp:
          type: string
          format: date-time
          description: First valid time stamp with a value of input data.
        lastTimestamp:
          type: string
          format: date-time
          description: Last valid time stamp with a value of input data.
    Multivariate.FillNAMethod:
      type: string
      description: Field that indicates how missing values will be filled.
      enum:
      - Previous
      - Subsequent
      - Linear
      - Zero
      - Fixed
      x-ms-enum:
        name: FillNAMethod
        modelAsString: true
    Multivariate.DiagnosticsInfo:
      type: object
      description: Diagnostics information to help inspect the states of a model or variable.
      properties:
        modelState:
          $ref: '#/components/schemas/Multivariate.ModelState'
          description: Model status.
        variableStates:
          type: array
          description: Variable status.
          items:
            $ref: '#/components/schemas/Multivariate.VariableState'
          x-ms-identifiers: []
    Multivariate.AnomalyDetectionModel:
      type: object
      description: Response of getting a model.
      properties:
        modelId:
          $ref: '#/components/schemas/Azure.Core.uuid'
          description: Model identifier.
        createdTime:
          type: string
          format: date-time
          description: Date and time (UTC) when the model was created.
        lastUpdatedTime:
          type: string
          format: date-time
          description: Date and time (UTC) when the model was last updated.
        modelInfo:
          $ref: '#/components/schemas/Multivariate.ModelInfo'
          description: 'Training result of a model, including its status, errors, and diagnostics

            information.'
      required:
      - modelId
      - createdTime
      - lastUpdatedTime
    Multivariate.ResponseError:
      type: object
      description: Error response.
      properties:
        code:
          type: string
          description: Error code.
        message:
          type: string
          description: Message that explains the error that the service reported.
      required:
      - code
      - message
    Multivariate.MultivariateBatchDetectionOptions:
      type: object
      description: 'Detection request for batch inference. This is an asynchronous inference that

        will need another API to get detection results.'
      properties:
        dataSource:
          type: string
          format: uri
          description: '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.'
        topContributorCount:
          type: integer
          format: int32
          description: Number of top contributed variables for one anomalous time stamp in the response.
          default: 10
        startTime:
          type: string
          format: date-time
          description: 'Start date/time of data for detection, which should

            be in ISO 8601 format.'
        endTime:
          type: string
          format: date-time
          description: 'End date/time of data for detection, which should

            be in ISO 8601 format.'
      required:
      - dataSource
      - startTime
      - endTime
    Multivariate.ModelState:
      type: object
      description: Model status.
      properties:
        epochIds:
          type: array
          description: 'Number of passes of the entire training dataset that the

            algorithm has completed.'
          items:
            type: integer
            format: int32
        trainLosses:
          type: array
          description: 'List of metrics used to assess how the model fits the training data for each

            epoch.'
          items:
            type: number
            format: float
        validationLosses:
          type: array
          description: 'List of metrics used to assess how the model fits the validation set for each

            epoch.'
          items:
            type: number
            format: float
        latenciesInSeconds:
          type: array
          description: Latency for each epoch.
          items:
            type: number
            format: float
    Multivariate.ErrorResponse:
      type: object
      description: Error information that the API returned.
      properties:
        code:
          type: string
          description: Error code.
        message:
          type: string
          description: Message that explains the error that the service reported.
      required:
      - code
      - message
    Multivariate.MultivariateLastDetectionResult:
      type: object
      description: Results of the last detection.
      properties:
        variableStates:
          type: array
          description: Variable status.
          items:
            $ref: '#/components/schemas/Multivariate.VariableState'
          x-ms-identifiers: []
        results:
          type: array
          description: Anomaly status and information.
          items:
            $ref: '#/components/schemas/Multivariate.AnomalyState'
          x-ms-identifiers: []
    Multivariate.MultivariateDetectionResult:
      type: object
      description: Detection results for the resultId value.
      properties:
        resultId:
          $ref: '#/components/schemas/Azure.Core.uuid'
          description: Result identifier that's used to fetch the results of an inference call.
        summary:
          $ref: '#/components/schemas/Multivariate.MultivariateBatchDetectionResultSummary'
          description: Multivariate anomaly detection status.
        results:
          type: array
          description: Detection result for each time stamp.
          items:
            $ref: '#/components/schemas/Multivariate.AnomalyState'
          x-ms-identifiers: []
      required:
      - resultId
      - summary
      - results
    Multivariate.AnomalyState:
      type: object
      description: Anomaly status and information.
      properties:
        timestamp:
          type: string
          format: date-time
          description: Time stamp for this anomaly.
        value:
          $ref: '#/components/schemas/Multivariate.AnomalyValue'
          description: Detailed value of this anomalous time stamp.
        errors:
          type: array
          description: Error message for the current time stamp.
          items:
            $ref: '#/components/schemas/Multivariate.ErrorResponse'
          x-ms-identifiers: []
      required:
      - timestamp
  parameters:
    Azure.Core.TopQueryParameter:
      name: top
      in: query
      description: The number of result items to return.
      required: false
      x-ms-parameter-location: method
      schema:
        type: integer
        format: int32
    Azure.Core.SkipQueryParameter:
      name: skip
      in: query
      description: The number of result items to skip.
      required: false
      x-ms-parameter-location: method
      schema:
        type: integer
        format: int32
        default: 0
  securitySchemes:
    AnomalyDetectorApiKeyAuth:
      type: apiKey
      description: The secret key for your Azure Cognitive Services subscription.
      name: Ocp-Apim-Subscription-Key
      in: header
x-ms-parameterized-host:
  hostTemplate: '{Endpoint}/anomalydetector/{ApiVersion}'
  useSchemePrefix: false
  parameters:
  - name: Endpoint
    in: path
    description: 'Supported Azure Cognitive Services endpoints (protocol and host name, such as

      https://westus2.api.cognitive.microsoft.com).'
    required: true
    type: string
  - name: ApiVersion
    in: path
    description: Api Version
    required: true
    type: string
    enum:
    - v1.1
    x-ms-enum:
      name: APIVersion
      modelAsString: true
      values:
      - name: v1_1
        value: v1.1