Anomaly Detection Detection Job Structure

{
  "$schema": "https://json-structure.org/meta/core/v0/#",
  "$id": "https://raw.githubusercontent.com/api-evangelist/anomaly-detection/refs/heads/main/json-structure/anomaly-detection-detection-job-structure.json",
  "description": "Configuration for an anomaly detection job that analyzes one or more time series using a specified algorithm and detection settings.",
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Unique identifier for the detection job.",
      "example": "job-500456"
    },
    "name": {
      "type": "string",
      "description": "Human-readable name for the detection job.",
      "example": "Production API Latency Anomaly Detector"
    },
    "description": {
      "type": "string",
      "description": "Description of what this detection job monitors and why.",
      "example": "Monitors API p99 latency for anomalies using daily seasonality."
    },
    "status": {
      "type": "string",
      "enum": [
        "pending",
        "running",
        "paused",
        "closed",
        "failed"
      ],
      "description": "Current operational status of the detection job.",
      "example": "running"
    },
    "algorithm": {
      "type": "string",
      "enum": [
        "basic",
        "agile",
        "robust",
        "iforest",
        "lof",
        "ocsvm",
        "autoencoder",
        "sr-cnn",
        "sarima",
        "graph-attention-network"
      ],
      "description": "The anomaly detection algorithm used by this job.",
      "example": "agile"
    },
    "mode": {
      "type": "string",
      "enum": [
        "batch",
        "streaming",
        "multivariate"
      ],
      "description": "Detection mode \u2014 batch retrospective, streaming real-time, or multivariate correlation-based.",
      "example": "streaming"
    },
    "sensitivity": {
      "type": "double",
      "minimum": 0,
      "maximum": 10,
      "description": "Sensitivity level controlling the anomaly detection threshold. Higher values detect more subtle anomalies.",
      "example": 3
    },
    "seasonality": {
      "type": "string",
      "enum": [
        "hourly",
        "daily",
        "weekly",
        "none",
        "auto"
      ],
      "description": "Seasonality pattern used for baseline modeling.",
      "example": "daily"
    },
    "series_ids": {
      "type": "array",
      "description": "List of time series identifiers analyzed by this job.",
      "items": {
        "type": "string"
      },
      "example": [
        "ts-api-latency-p99",
        "ts-api-error-rate"
      ]
    },
    "created_at": {
      "type": "datetime",
      "description": "Timestamp when the job was created.",
      "example": "2026-04-01T00:00:00Z"
    },
    "modified_at": {
      "type": "datetime",
      "description": "Timestamp when the job was last modified.",
      "example": "2026-04-19T00:00:00Z"
    }
  },
  "required": [
    "id",
    "name",
    "status",
    "algorithm",
    "mode"
  ],
  "name": "DetectionJob"
}