[role="xpack"]
[[update-trained-model-deployment]]
= Update trained model deployment API

[subs="attributes"]
++++
<titleabbrev>Update trained model deployment</titleabbrev>
++++

Updates certain properties of a trained model deployment.

beta::[]

[[update-trained-model-deployment-request]]
== {api-request-title}

`POST _ml/trained_models/<deployment_id>/deployment/_update`


[[update-trained-model-deployments-prereqs]]
== {api-prereq-title}

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

[[update-trained-model-deployment-desc]]
== {api-description-title}

You can update a trained model deployment whose `assignment_state` is `started`.
You can either increase or decrease the number of allocations of such a deployment.

[[update-trained-model-deployments-path-parms]]
== {api-path-parms-title}

`<deployment_id>`::
(Required, string)
include::{es-ref-dir}/ml/ml-shared.asciidoc[tag=deployment-id]

[[update-trained-model-deployment-request-body]]
== {api-request-body-title}

`number_of_allocations`::
(Optional, integer)
The total number of allocations this model is assigned across {ml} nodes.
Increasing this value generally increases the throughput.


[[update-trained-model-deployment-example]]
== {api-examples-title}

The following example updates the deployment for a
 `elastic__distilbert-base-uncased-finetuned-conll03-english` trained model to have 4 allocations:

[source,console]
--------------------------------------------------
POST _ml/trained_models/elastic__distilbert-base-uncased-finetuned-conll03-english/deployment/_update
{
  "number_of_allocations": 4
}
--------------------------------------------------
// TEST[skip:TBD]

The API returns the following results:

[source,console-result]
----
{
    "assignment": {
        "task_parameters": {
            "model_id": "elastic__distilbert-base-uncased-finetuned-conll03-english",
            "model_bytes": 265632637,
            "threads_per_allocation" : 1,
            "number_of_allocations" : 4,
            "queue_capacity" : 1024
        },
        "routing_table": {
            "uckeG3R8TLe2MMNBQ6AGrw": {
                "current_allocations": 1,
                "target_allocations": 4,
                "routing_state": "started",
                "reason": ""
            }
        },
        "assignment_state": "started",
        "start_time": "2022-11-02T11:50:34.766591Z"
    }
}
----