Briefly, this error occurs when Elasticsearch fails to deploy, possibly due to incorrect configuration settings, insufficient system resources, or network connectivity issues. To resolve this, ensure that your configuration files are correct and that your system has enough resources (CPU, memory, disk space). Also, check your network settings and firewall rules to ensure Elasticsearch can communicate with other nodes and services. If the problem persists, check the Elasticsearch logs for more detailed error messages.
This guide will help you check for common problems that cause the log ” [{}] Start deployment failed ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin, allocation.
Log Context
Log “[{}] Start deployment failed” classname is TrainedModelAllocationNodeService.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
TrainedModelDeploymentTask deployedTask = listener.actionGet();
// kicks off asynchronous cluster state update
handleLoadSuccess(deployedTask);
} catch (Exception ex) {
if (ExceptionsHelper.unwrapCause(ex) instanceof ResourceNotFoundException) {
logger.warn(new ParameterizedMessage("[{}] Start deployment failed"; modelId); ex);
handleLoadFailure(loadingTask; ExceptionsHelper.missingTrainedModel(modelId; ex));
} else if (ExceptionsHelper.unwrapCause(ex) instanceof SearchPhaseExecutionException) {
logger.trace(new ParameterizedMessage("[{}] Start deployment failed; will retry"; modelId); ex);
// A search phase execution failure should be retried; push task back to the queue
loadingToRetry.add(loadingTask);
