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Plugin: python.d.plugin Module: beanstalk


Monitor Beanstalk metrics to enhance job queueing and processing efficiency. Track job rates, processing times, and queue lengths for better task management.

The collector uses the beanstalkc python module to connect to a beanstalkd service and gather metrics.

This collector is supported on all platforms.

This collector supports collecting metrics from multiple instances of this integration, including remote instances.

Default Behavior


If no configuration is given, module will attempt to connect to beanstalkd on address.


The default configuration for this integration does not impose any limits on data collection.

Performance Impact

The default configuration for this integration is not expected to impose a significant performance impact on the system.


Metrics grouped by scope.

The scope defines the instance that the metric belongs to. An instance is uniquely identified by a set of labels.

Per Beanstalk instance

These metrics refer to the entire monitored application.

This scope has no labels.


beanstalk.cpu_usageuser, systemcpu time
beanstalk.jobs_ratetotal, timeoutsjobs/s
beanstalk.commands_rateput, peek, peek-ready, peek-delayed, peek-buried, reserve, use, watch, ignore, delete, bury, kick, stats, stats-job, stats-tube, list-tubes, list-tube-used, list-tubes-watched, pause-tubecommands/s
beanstalk.current_jobsurgent, ready, reserved, delayed, buriedjobs
beanstalk.current_connectionswritten, producers, workers, waitingconnections
beanstalk.binlogwritten, migratedrecords/s

Per tube

Metrics related to Beanstalk tubes. Each tube produces its own set of the following metrics.

This scope has no labels.


beanstalk.jobsurgent, ready, reserved, delayed, buriedjobs
beanstalk.connectionsusing, waiting, watchingconnections
beanstalk.commandsdeletes, pausescommands/s
beanstalk.pausesince, leftseconds


The following alerts are available:

Alert nameOn metricDescription
beanstalk_server_buried_jobs beanstalk.current_jobsnumber of buried jobs across all tubes. You need to manually kick them so they can be processed. Presence of buried jobs in a tube does not affect new jobs.



beanstalkc python module

The collector requires the beanstalkc python module to be installed.



The configuration file name for this integration is python.d/beanstalk.conf.

You can edit the configuration file using the edit-config script from the Netdata config directory.

cd /etc/netdata 2>/dev/null || cd /opt/netdata/etc/netdata
sudo ./edit-config python.d/beanstalk.conf


There are 2 sections:

  • Global variables
  • One or more JOBS that can define multiple different instances to monitor.

The following options can be defined globally: priority, penalty, autodetection_retry, update_every, but can also be defined per JOB to override the global values.

Additionally, the following collapsed table contains all the options that can be configured inside a JOB definition.

Every configuration JOB starts with a job_name value which will appear in the dashboard, unless a name parameter is specified.

Config options
update_everySets the default data collection frequency.5no
priorityControls the order of charts at the netdata dashboard.60000no
autodetection_retrySets the job re-check interval in seconds.0no
penaltyIndicates whether to apply penalty to update_every in case of failures.yesno
nameJob name. This value will overwrite the job_name value. JOBS with the same name are mutually exclusive. Only one of them will be allowed running at any time. This allows autodetection to try several alternatives and pick the one that
hostIP or URL to a beanstalk service.
portPort to the IP or URL to a beanstalk service.11300no


Remote beanstalk server

A basic remote beanstalk server

name: 'beanstalk'
host: ''
port: 11300


Note: When you define multiple jobs, their names must be unique.

Collecting metrics from local and remote instances.

name: 'local_beanstalk'
host: ''
port: 11300

name: 'remote_beanstalk'
host: ''
port: 113000


Debug Mode

To troubleshoot issues with the beanstalk collector, run the python.d.plugin with the debug option enabled. The output should give you clues as to why the collector isn't working.

  • Navigate to the plugins.d directory, usually at /usr/libexec/netdata/plugins.d/. If that's not the case on your system, open netdata.conf and look for the plugins setting under [directories].

    cd /usr/libexec/netdata/plugins.d/
  • Switch to the netdata user.

    sudo -u netdata -s
  • Run the python.d.plugin to debug the collector:

    ./python.d.plugin beanstalk debug trace

Getting Logs

If you're encountering problems with the beanstalk collector, follow these steps to retrieve logs and identify potential issues:

  • Run the command specific to your system (systemd, non-systemd, or Docker container).
  • Examine the output for any warnings or error messages that might indicate issues. These messages should provide clues about the root cause of the problem.

System with systemd

Use the following command to view logs generated since the last Netdata service restart:

journalctl _SYSTEMD_INVOCATION_ID="$(systemctl show --value --property=InvocationID netdata)" --namespace=netdata --grep beanstalk

System without systemd

Locate the collector log file, typically at /var/log/netdata/collector.log, and use grep to filter for collector's name:

grep beanstalk /var/log/netdata/collector.log

Note: This method shows logs from all restarts. Focus on the latest entries for troubleshooting current issues.

Docker Container

If your Netdata runs in a Docker container named "netdata" (replace if different), use this command:

docker logs netdata 2>&1 | grep beanstalk

Do you have any feedback for this page? If so, you can open a new issue on our netdata/learn repository.