Max running job capacity ” + localMaxAllowedRunningJobs + ” reached – How to solve this Elasticsearch error

Opster Team

July-20, Version: 1.7-8.0

Before you begin reading this guide, we recommend you try running the Elasticsearch Error Check-Up which analyzes 2 JSON files to detect many configuration errors.

To easily locate the root cause and resolve this issue try AutoOps for Elasticsearch & OpenSearch. It diagnoses problems by analyzing hundreds of metrics collected by a lightweight agent and offers guidance for resolving them.

This guide will help you check for common problems that cause the log ” max running job capacity ” + localMaxAllowedRunningJobs + ” reached ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin.


Log Context

Log “max running job capacity [” + localMaxAllowedRunningJobs + “] reached”classname  is AutodetectProcessManager.java We extracted the following from Elasticsearch source code for those seeking an in-depth context :

// Closing jobs can still be using some or all threads in MachineLearning.JOB_COMMS_THREAD_POOL_NAME
 // that an open job uses; so include them too when considering if enough threads are available.
 int currentRunningJobs = processByAllocation.size();
 // TODO: in future this will also need to consider jobs that are not anomaly detector jobs
 if (currentRunningJobs > localMaxAllowedRunningJobs) {
 throw new ElasticsearchStatusException("max running job capacity [" + localMaxAllowedRunningJobs + "] reached";
 RestStatus.TOO_MANY_REQUESTS);
 } 
 String jobId = jobTask.getJobId();
 notifyLoadingSnapshot(jobId; autodetectParams);

 

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