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Plugin: python.d.plugin Module: ipfs


This collector monitors IPFS server metrics about its quality and performance.

It connects to an http endpoint of the IPFS server to collect the 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 the endpoint is accessible by the Agent, netdata will autodetect it


Calls to the following endpoints are disabled due to IPFS bugs:

/api/v0/stats/repo ( /api/v0/pin/ls (

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 IPFS instance

These metrics refer to the entire monitored application.

This scope has no labels.


ipfs.bandwidthin, outkilobits/s
ipfs.repo_sizeavail, sizeGiB
ipfs.repo_objectsobjects, pinned, recursive_pinsobjects


The following alerts are available:

Alert nameOn metricDescription
ipfs_datastore_usage ipfs.repo_sizeIPFS datastore utilization



No action required.



The configuration file name for this integration is python.d/ipfs.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/ipfs.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_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
nameThe JOB's name as it will appear at the dashboard (by default is the job_name)job_nameno
urlURL to the IPFS APInoyes
repoapiCollect repo metrics.nono
pinapiSet status of IPFS pinned object polling.nono


Basic (default out-of-the-box)

A basic example configuration, one job will run at a time. Autodetect mechanism uses it by default.

name: 'local'
url: 'http://localhost:5001'
repoapi: no
pinapi: no


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

Collecting metrics from local and remote instances.

name: 'local'
url: 'http://localhost:5001'
repoapi: no
pinapi: no

name: 'remote'
url: ''
repoapi: no
pinapi: no


Debug Mode

To troubleshoot issues with the ipfs 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 ipfs debug trace

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