Trained model is not deployed – How to solve this Elasticsearch exception

Opster Team

August-23, Version: 8-8.5

Briefly, this error occurs when an attempt is made to use a machine learning model in Elasticsearch that has not been deployed yet. This could be due to the model not being fully trained or not being properly deployed. To resolve this issue, ensure that the model has been fully trained and then deploy it correctly. If the model is already trained, check the deployment process and make sure it was successful. If the problem persists, consider retraining and redeploying the model.

This guide will help you check for common problems that cause the log ” Trained model [{}] is not deployed. ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin.

Log Context

Log “Trained model [{}] is not deployed.” class name is ModelLoadingService.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :

 );
 return;
 }
 handleLoadFailure(
 modelId;
 new ElasticsearchStatusException("Trained model [{}] is not deployed."; RestStatus.BAD_REQUEST; modelId)
 );
 return;
 }
 auditNewReferencedModel(modelId);
 trainedModelCircuitBreaker.addEstimateBytesAndMaybeBreak(trainedModelConfig.getModelSize(); modelId);

 

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