Update model snapshots API

Update model snapshots API

New API reference

For the most up-to-date API details, refer to Machine learning anomaly detection APIs.

Updates certain properties of a snapshot.

Request

POST _ml/anomaly_detectors/<job_id>/model_snapshots/<snapshot_id>/_update

Prerequisites

Requires the manage_ml cluster privilege. This privilege is included in the machine_learning_admin built-in role.

Path parameters

<job_id>

(Required, string) Identifier for the anomaly detection job.

<snapshot_id>

(Required, string) Identifier for the model snapshot.

Request body

The following properties can be updated after the model snapshot is created:

description

(Optional, string) A description of the model snapshot.

retain

(Optional, Boolean) If true, this snapshot will not be deleted during automatic cleanup of snapshots older than model_snapshot_retention_days. However, this snapshot will be deleted when the job is deleted. The default value is false.

Examples

resp = client.ml.update_model_snapshot(
    job_id="it_ops_new_logs",
    snapshot_id="1491852978",
    description="Snapshot 1",
    retain=True,
)
print(resp)

response = client.ml.update_model_snapshot(
  job_id: 'it_ops_new_logs',
  snapshot_id: 1_491_852_978,
  body: {
    description: 'Snapshot 1',
    retain: true
  }
)
puts response

const response = await client.ml.updateModelSnapshot({
  job_id: "it_ops_new_logs",
  snapshot_id: 1491852978,
  description: "Snapshot 1",
  retain: true,
});
console.log(response);

POST
_ml/anomaly_detectors/it_ops_new_logs/model_snapshots/1491852978/_update
{
  "description": "Snapshot 1",
  "retain": true
}

When the snapshot is updated, you receive the following results:

{
  "acknowledged": true,
  "model": {
    "job_id": "it_ops_new_logs",
    "timestamp": 1491852978000,
    "description": "Snapshot 1",
...
    "retain": true
  }
}