elasticsearch-js/docs/reference/api/MlTrainedModelDeploymentStats.md

MlTrainedModelDeploymentStats [interface-MlTrainedModelDeploymentStats]

Name	Type	Description
adaptive_allocations	MlAdaptiveAllocationsSettings
allocation_status	MlTrainedModelDeploymentAllocationStatus	The detailed allocation status for the deployment.
cache_size	ByteSize
deployment_id	Id	The unique identifier for the trained model deployment.
error_count	integer	The sum of error_count for all nodes in the deployment.
inference_count	integer	The sum of inference_count for all nodes in the deployment.
model_id	Id	The unique identifier for the trained model.
nodes	MlTrainedModelDeploymentNodesStats[]	The deployment stats for each node that currently has the model allocated. In serverless, stats are reported for a single unnamed virtual node.
number_of_allocations	integer	The number of allocations requested.
peak_throughput_per_minute	long
priority	MlTrainingPriority
queue_capacity	integer	The number of inference requests that can be queued before new requests are rejected.
reason	string	The reason for the current deployment state. Usually only populated when the model is not deployed to a node.
rejected_execution_count	integer	The sum of rejected_execution_count for all nodes in the deployment. Individual nodes reject an inference request if the inference queue is full. The queue size is controlled by the queue_capacity setting in the start trained model deployment API.
start_time	EpochTime<UnitMillis>	The epoch timestamp when the deployment started.
state	MlDeploymentAssignmentState	The overall state of the deployment.
threads_per_allocation	integer	The number of threads used be each allocation during inference.
timeout_count	integer	The sum of timeout_count for all nodes in the deployment.