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.
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.
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.
Config options
Name | Description | Default | Required |
---|---|---|---|
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 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. | no | |
control_addr | Tor control IP address | 127.0.0.1 | no |
control_port | Tor control port. Can be either a tcp port, or a path to a socket file. | 9051 | no |
password | Tor control password | no |
Examples
Local TCP
A basic TCP configuration. local_addr
is ommited and will default to 127.0.0.1
Config
local_tcp:
name: 'local'
control_port: 9051
password: <password> # if required
Local socket
A basic local socket configuration
Config
local_socket:
name: 'local'
control_port: '/var/run/tor/control'
password: <password> # if required
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, opennetdata.conf
and look for theplugins
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
Do you have any feedback for this page? If so, you can open a new issue on our netdata/learn repository.