Anomaly Detection Detection Job Structure
Configuration for an anomaly detection job that analyzes one or more time series using a specified algorithm and detection settings.
Type: object
Properties: 11
Required: 5
Anomaly DetectionArtificial IntelligenceData ScienceFraud DetectionMachine LearningMonitoringObservabilityOutlier DetectionPattern RecognitionSecurityTime Series
DetectionJob is a JSON Structure definition published by Anomaly Detection, describing 11 properties, of which 5 are required. It conforms to the https://json-structure.org/meta/core/v0/# meta-schema.
{
"$schema": "https://json-structure.org/meta/core/v0/#",
"$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"
}