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Tor

Tor

Plugin: python.d.plugin Module: tor

Overview

This collector monitors Tor bandwidth traffic .

It connects to the Tor control port to collect traffic statistics.

This collector is supported on all platforms.

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

Default Behavior

Auto-Detection

If no configuration is provided the collector will try to connect to 127.0.0.1:9051 to detect a running tor instance.

Limits

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.

Setup

Prerequisites

Required python module

The stem python library needs to be installed.

Required Tor configuration

Add to /etc/tor/torrc:

ControlPort 9051

For more options please read the manual.

Configuration

File

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

Options

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.

Name Description Default Required
update_every Sets the default data collection frequency. 5 False
priority Controls the order of charts at the netdata dashboard. 60000 False
autodetection_retry Sets the job re-check interval in seconds. 0 False
penalty Indicates whether to apply penalty to update_every in case of failures. yes False
name Job 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 works. False
control_addr Tor control IP address 127.0.0.1 False
control_port Tor control port. Can be either a tcp port, or a path to a socket file. 9051 False
password Tor control password False

Examples

Local TCP

A basic TCP configuration. local_addr is ommited and will default to 127.0.0.1

local_tcp:
 name: 'local'
 control_port: 9051
 password: <password> # if required

Local socket

A basic local socket configuration

local_socket:
 name: 'local'
 control_port: '/var/run/tor/control'
 password: <password> # if required

Metrics

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 Tor instance

These metrics refer to the entire monitored application.

This scope has no labels.

Metrics:

Metric Dimensions Unit
tor.traffic read, write KiB/s

Alerts

There are no alerts configured by default for this integration.

Troubleshooting

Debug Mode

To troubleshoot issues with the tor 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 tor debug trace
    

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