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.
If no configuration is given, module will attempt to connect to beanstalkd on 127.0.0.1:11300 address.
The default configuration for this integration does not impose any limits on data collection.
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_usage||user, system||cpu time|
|beanstalk.commands_rate||put, 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-tube||commands/s|
|beanstalk.current_jobs||urgent, ready, reserved, delayed, buried||jobs|
|beanstalk.current_connections||written, producers, workers, waiting||connections|
Metrics related to Beanstalk tubes. Each tube produces its own set of the following metrics.
This scope has no labels.
|beanstalk.jobs||urgent, ready, reserved, delayed, buried||jobs|
|beanstalk.connections||using, waiting, watching||connections|
The following alerts are available:
|Alert name||On metric||Description|
|beanstalk_server_buried_jobs||beanstalk.current_jobs||number 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
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.
|update_every||Sets the default data collection frequency.||5||no|
|priority||Controls the order of charts at the netdata dashboard.||60000||no|
|autodetection_retry||Sets the job re-check interval in seconds.||0||no|
|penalty||Indicates whether to apply penalty to update_every in case of failures.||yes||no|
|name||Job name. This value will overwrite the ||no|
|host||IP or URL to a beanstalk service.||127.0.0.1||no|
|port||Port to the IP or URL to a beanstalk service.||11300||no|
Remote beanstalk server
A basic remote beanstalk server
Note: When you define multiple jobs, their names must be unique.
Collecting metrics from local and remote instances.
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.ddirectory, usually at
/usr/libexec/netdata/plugins.d/. If that's not the case on your system, open
netdata.confand look for the
Switch to the
sudo -u netdata -s
python.d.pluginto debug the collector:
./python.d.plugin beanstalk debug trace
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