Revert model snapshots APIedit

Reverts to a specific snapshot.


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


The machine learning feature in X-Pack reacts quickly to anomalous input, learning new behaviors in data. Highly anomalous input increases the variance in the models whilst the system learns whether this is a new step-change in behavior or a one-off event. In the case where this anomalous input is known to be a one-off, then it might be appropriate to reset the model state to a time before this event. For example, you might consider reverting to a saved snapshot after Black Friday or a critical system failure.

Before you revert to a saved snapshot, you must close the job.

Path parametersedit

job_id (required)
(string) Identifier for the job
snapshot_id (required)
(string) Identifier for the model snapshot

Request bodyedit

(boolean) If true, deletes the results in the time period between the latest results and the time of the reverted snapshot. It also resets the model to accept records for this time period. The default value is false.

If you choose not to delete intervening results when reverting a snapshot, the job will not accept input data that is older than the current time. If you want to resend data, then delete the intervening results.


You must have manage_ml, or manage cluster privileges to use this API. For more information, see Security privileges.


The following example reverts to the 1491856080 snapshot for the it_ops_new_kpi job:

  "delete_intervening_results": true

When the operation is complete, you receive the following results:

  "model": {
    "job_id": "it_ops_new_kpi",
    "min_version": "6.3.0",
    "timestamp": 1491856080000,
    "description": "State persisted due to job close at 2017-04-10T13:28:00-0700",
    "snapshot_id": "1491856080",
    "snapshot_doc_count": 1,
    "model_size_stats": {
      "job_id": "it_ops_new_kpi",
      "result_type": "model_size_stats",
      "model_bytes": 29518,
      "total_by_field_count": 3,
      "total_over_field_count": 0,
      "total_partition_field_count": 2,
      "bucket_allocation_failures_count": 0,
      "memory_status": "ok",
      "log_time": 1491856080000,
      "timestamp": 1455318000000
    "latest_record_time_stamp": 1455318669000,
    "latest_result_time_stamp": 1455318000000,
    "retain": false