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Undeploy a model
To undeploy a model from memory, use the undeploy operation.
For information about user access for this API, see Model access control considerations.
Path and HTTP methods
POST /_plugins/_ml/models/<model_id>/_undeploy
Example request: Undeploying a model from all ML nodes
POST /_plugins/_ml/models/MGqJhYMBbbh0ushjm8p_/_undeploy
Example request: Undeploying specific models from specific nodes
POST /_plugins/_ml/models/_undeploy
{
"node_ids": ["sv7-3CbwQW-4PiIsDOfLxQ"],
"model_ids": ["KDo2ZYQB-v9VEDwdjkZ4"]
}
Example request: Undeploying specific models from all nodes
{
"model_ids": ["KDo2ZYQB-v9VEDwdjkZ4"]
}
Example response
{
"sv7-3CbwQW-4PiIsDOfLxQ" : {
"stats" : {
"KDo2ZYQB-v9VEDwdjkZ4" : "UNDEPLOYED"
}
}
}
Automatically undeploy a model based on TTL
Starting with OpenSearch 2.14, models can be automatically undeployed from memory based on the predefined time-to-live (TTL) when the model was last accessed or used. To define a TTL that automatically undeploys a model, include the following ModelDeploySetting
in your machine learning (ML) model. Note that model TTLs are checked periodically by a syn_up
cron job, so the maximum time that a model lives in memory could be TTL + the sync_up_job_
interval. The default cron job interval is 10 seconds. To update the cron job internally, use the following cluster setting:
PUT /_cluster/settings
{
"persistent": {
"plugins.ml_commons.sync_up_job_interval_in_seconds": 10
}
}
Example request: Creating a model with a TTL
POST /_plugins/_ml/models/_register
{
"name": "Sample Model Name",
"function_name": "remote",
"description": "test model",
"connector_id": "-g1nOo8BOaAC5MIJ3_4R",
"deploy_setting": {"model_ttl_minutes": 100}
}
Example request: Updating a model with a TTL when the model is undeployed
PUT /_plugins/_ml/models/COj7K48BZzNMh1sWedLK
{
"deploy_setting": {"model_ttl_minutes" : 100}
}