AuthThe Elastic Stack includes Elastic's core products such as Elasticsearch, Kibana, Logstash, and Beats.AvailabilityGenerally available since 5.4This functionality is generally available and ready for production usage.Unless stated otherwise on the page, this functionality is available when your Elastic Stack is deployed on Elastic Cloud Hosted, Elastic Cloud Enterprise, Elastic Cloud on Kubernetes, and self-managed environments.This documentation corresponds to the latest patch available for each minor version. If you're not using the latest patch, check the release notes for changes.
The machine learning features react 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.
You can specify empty as the <snapshot_id>. Reverting to the empty
snapshot means the anomaly detection job starts learning a new model from
scratch when it is started.
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. 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.
A numerical character string that uniquely identifies the job that the snapshot was created for.
latest_record_time_stampnumber
The timestamp of the latest processed record.
latest_result_time_stampnumber
The timestamp of the latest bucket result.
min_versionstringrequired
The minimum version required to be able to restore the model snapshot.
model_size_statsobject
Summary information describing the model.
bucket_allocation_failures_countnumberrequired
job_idstringrequired
log_timeuniononeOfrequired
One of:stringornumber
memory_statusenumrequired
Values:oksoft_limithard_limit
model_bytesnumber | stringrequired
model_bytes_exceedednumber | string
model_bytes_memory_limitnumber | string
output_memory_allocator_bytesnumber | string
peak_model_bytesnumber | string
assignment_memory_basisstring
result_typestringrequired
total_by_field_countnumberrequired
total_over_field_countnumberrequired
total_partition_field_countnumberrequired
categorization_statusenumrequired
Values:okwarn
categorized_doc_countnumberrequired
dead_category_countnumberrequired
failed_category_countnumberrequired
frequent_category_countnumberrequired
rare_category_countnumberrequired
total_category_countnumberrequired
timestampnumber
retainbooleanrequired
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.
snapshot_doc_countnumberrequired
For internal use only.
snapshot_idstringrequired
A numerical character string that uniquely identifies the model snapshot.