Stop trained model deployment API
editStop trained model deployment API
editStops a trained model deployment.
This functionality is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.
Request
editPOST _ml/trained_models/<model_id>/deployment/_stop
Prerequisites
editRequires the manage_ml
cluster privilege. This privilege is included in the
machine_learning_admin
built-in role.
Description
editDeployment is required only for trained models that have a PyTorch model_type
.
Path parameters
edit-
<model_id>
- (Required, string) The unique identifier of the trained model.
Query parameters
edit-
allow_no_match
-
(Optional, Boolean) Specifies what to do when the request:
- Contains wildcard expressions and there are no deployments that match.
-
Contains the
_all
string or no identifiers and there are no matches. - Contains wildcard expressions and there are only partial matches.
The default value is
true
, which returns an empty array when there are no matches and the subset of results when there are partial matches. If this parameter isfalse
, the request returns a404
status code when there are no matches or only partial matches. -
force
- (Optional, Boolean) If true, the deployment is stopped even if it is referenced by ingest pipelines. You can’t use these pipelines until you restart the model deployment.