elasticsearch/docs/reference/ml/df-analytics/apis/get-trained-model-deployment-stats.asciidoc

[role="xpack"]
[testenv="basic"]
[[get-trained-model-deployment-stats]]
= Get trained model deployment statistics API
[subs="attributes"]
++++
<titleabbrev>Get trained model deployment stats</titleabbrev>
++++

Retrieves usage information for trained model deployments.


[[ml-get-trained-model-deployment-stats-request]]
== {api-request-title}

`GET _ml/trained_models/<model_id>/deployment/_stats` +

`GET _ml/trained_models/<model_id>,<model_id_2>/deployment/_stats` +

`GET _ml/trained_models/<model_id_pattern*>,<model_id_2>/deployment/_stats`

[[ml-get-trained-model-deployment-stats-prereq]]
== {api-prereq-title}

Requires the `monitor_ml` cluster privilege. This privilege is included in the
`machine_learning_user` built-in role.


[[ml-get-trained-model-deployment-stats-desc]]
== {api-description-title}

You can get deployment information for multiple trained models in a single API
request by using a comma-separated list of model IDs or a wildcard expression.


[[ml-get-trained-model-deployment-stats-path-params]]
== {api-path-parms-title}

`<model_id>`::
(Optional, string)
include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=model-id]


[[ml-get-trained-model-deployment-stats-query-params]]
== {api-query-parms-title}

`allow_no_match`::
(Optional, Boolean)
include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=allow-no-match-models]

[role="child_attributes"]
[[ml-get-trained-model-deployment-stats-results]]
== {api-response-body-title}

`count`::
(integer)
The total number of deployment statistics that matched the requested ID
patterns.

`deployment_stats`::
(array)
An array of trained model deployment statistics, which are sorted by the `model_id` value
in ascending order.
+
.Properties of trained model deployment stats
[%collapsible%open]
====
`model_id`:::
(string)
include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=model-id]

`model_size`:::
(<<byte-units,byte value>>)
The size of the loaded model in bytes.

`state`:::
(string)
The overall state of the deployment. The values may be:
+
--
* `starting`: The deployment has recently started but is not yet usable as the model is not allocated on any nodes.
* `started`: The deployment is usable as at least one node has the model allocated.
* `stopping`: The deployment is preparing to stop and un-allocate the model from the relevant nodes.
--

`allocation_status`:::
(object)
The detailed allocation status given the deployment configuration.
+
.Properties of allocation stats
[%collapsible%open]
=====
`allocation_count`:::
(integer)
The current number of nodes where the model is allocated.

`target_allocation_count`:::
(integer)
The desired number of nodes for model allocation.

`state`:::
(string)
The detailed allocation state related to the nodes.
+
--
* `starting`: Allocations are being attempted but no node currently has the model allocated.
* `started`: At least one node has the model allocated.
* `fully_allocated`: The deployment is fully allocated and satisfies the `target_allocation_count`.
--
=====

`nodes`:::
(array of objects)
The deployment stats for each node that currently has the model allocated.
+
.Properties of node stats
[%collapsible%open]
=====
`average_inference_time_ms`:::
(double)
The average time for each inference call to complete on this node.

`inference_count`:::
(integer)
The total number of inference calls made against this node for this model.

`last_access`:::
(long)
The epoch time stamp of the last inference call for the model on this node.

`node`:::
(object)
Information pertaining to the node.
+
.Properties of node
[%collapsible%open]
======
`attributes`:::
(object)
include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=node-attributes]

`ephemeral_id`:::
(string)
include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=node-ephemeral-id]

`id`:::
(string)
include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=node-id]

`name`:::
(string) The node name.

`transport_address`:::
(string)
include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=node-transport-address]
======

`routing_state`:::
(object)
The current routing state and reason for the current routing state for this allocation.
+
--
* `starting`: The model is attempting to allocate on this model, inference calls are not yet accepted.
* `started`: The model is allocated and ready to accept inference requests.
* `stopping`: The model is being de-allocated from this node.
* `stopped`: The model is fully de-allocated from this node.
* `failed`: The allocation attempt failed, see `reason` field for the potential cause.
--

`reason`:::
(string)
The reason for the current state. Usually only populated when the `routing_state` is `failed`.

=====
====

[[ml-get-trained-model-deployment-stats-response-codes]]
== {api-response-codes-title}

`404` (Missing resources)::
  If `allow_no_match` is `false`, this code indicates that there are no
  resources that match the request or only partial matches for the request.

[[ml-get-trained-model-deployment-stats-example]]
== {api-examples-title}

The following example gets deployment information for all currently started model deployments:

[source,console]
--------------------------------------------------
GET _ml/trained_models/*/deployment/_stats
--------------------------------------------------
// TEST[skip:TBD]


The API returns the following results:

[source,console-result]
----
{
    "count": 2,
    "deployment_stats": [
        {
            "model_id": "elastic__distilbert-base-uncased-finetuned-conll03-english",
            "model_size": "253.3mb",
            "state": "started",
            "allocation_status": {
                "allocation_count": 1,
                "target_allocation_count": 1,
                "state": "fully_allocated"
            },
            "nodes": [
                {
                    "node": {
                        "6pzZQ9OmQUWAaswMlwVEwg": {
                            "name": "runTask-0",
                            "ephemeral_id": "aI1OwkPMRCiAJ_1XkEAqdw",
                            "transport_address": "127.0.0.1:9300",
                            "attributes": {
                                "ml.machine_memory": "68719476736",
                                "xpack.installed": "true",
                                "testattr": "test",
                                "ml.max_open_jobs": "512",
                                "ml.max_jvm_size": "4181590016"
                            },
                            "roles": [
                                "data",
                                "data_cold",
                                "data_content",
                                "data_frozen",
                                "data_hot",
                                "data_warm",
                                "ingest",
                                "master",
                                "ml",
                                "remote_cluster_client",
                                "transform"
                            ]
                        }
                    },
                    "routing_state": {
                        "routing_state": "started"
                    },
                    "inference_count": 9,
                    "average_inference_time_ms": 51,
                    "last_access": 1632855681069
                }
            ]
        },
        {
            "model_id": "typeform__distilbert-base-uncased-mnli",
            "model_size": "255.5mb",
            "state": "started",
            "allocation_status": {
                "allocation_count": 1,
                "target_allocation_count": 1,
                "state": "fully_allocated"
            },
            "nodes": [
                {
                    "node": {
                        "6pzZQ9OmQUWAaswMlwVEwg": {
                            "name": "runTask-0",
                            "ephemeral_id": "aI1OwkPMRCiAJ_1XkEAqdw",
                            "transport_address": "127.0.0.1:9300",
                            "attributes": {
                                "ml.machine_memory": "68719476736",
                                "xpack.installed": "true",
                                "testattr": "test",
                                "ml.max_open_jobs": "512",
                                "ml.max_jvm_size": "4181590016"
                            },
                            "roles": [
                                "data",
                                "data_cold",
                                "data_content",
                                "data_frozen",
                                "data_hot",
                                "data_warm",
                                "ingest",
                                "master",
                                "ml",
                                "remote_cluster_client",
                                "transform"
                            ]
                        }
                    },
                    "routing_state": {
                        "routing_state": "started"
                    },
                    "inference_count": 0,
                    "average_inference_time_ms": 0
                }
            ]
        }
    ]
}
----
// NOTCONSOLE