Manual threshold object

A Manual threshold object represents a manually configured threshold for a metric across the authenticated environment or for one specific node and metric pair.

Notes

• target.statTypeId uses the same metric identifier exposed as metrics[].id in Node definition objects and as metric-id in Get metric data
• When target.nodeId is omitted, the threshold applies to all nodes that expose the metric in the authenticated environment
• When target.nodeId is present, the threshold applies only to that node and metric pair

Attributes

Field	Type	Description
id	string	Manual threshold identifier used in delete requests
target	object	Metric target that the threshold applies to
mode	string	Threshold mode. Supported values: CAPPED, STATIC. See Mode behavior.
bounds	object	Required lower and upper bound values for the threshold
createdAt	ISO 8601 datetime	Timestamp when the threshold entry was created
updatedAt	ISO 8601 datetime	Timestamp when the threshold entry was last updated

Target attributes

Field	Type	Description
target.statTypeId	string	Required metric identifier to attach the threshold to
target.nodeId	integer	Optional node identifier for a node-specific threshold

Bounds attributes

Field	Type	Description
bounds.upper	number	Required upper bound value
bounds.lower	number	Required lower bound value

Mode behavior

Mode	Behavior
CAPPED	Caps the machine-learning baseline corridor with the provided bounds. This can tighten the existing corridor, but it does not expand it.
STATIC	Disables machine-learning baselines for the target and uses the provided bounds directly for manual baseline alerting.

For CAPPED, the effective lower bound is the higher of the machine-learning lower bound and bounds.lower, and the effective upper bound is the lower of the machine-learning upper bound and bounds.upper.

Examples:

• If machine learning produces lower=20 and upper=100, and the manual threshold is lower=25 and upper=50, the effective bounds become lower=25 and upper=50
• If machine learning produces lower=20 and upper=100, and the manual threshold is lower=10 and upper=50, the effective bounds become lower=20 and upper=50

Example

{
  "id": "64b64b64b64b64b64b64b64c",
  "target": {
    "statTypeId": "11111111-1111-1111-1111-111111111111",
    "nodeId": 123
  },
  "mode": "STATIC",
  "bounds": {
    "upper": 30,
    "lower": 10
  },
  "createdAt": "2025-02-01T00:00:00.000Z",
  "updatedAt": "2025-02-01T00:00:00.000Z"
}