IPFS
IPFS
Plugin: python.d.plugin Module: ipfs
Overview
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
Auto-Detection
If the endpoint is accessible by the Agent, netdata will autodetect it
Limits
Calls to the following endpoints are disabled due to IPFS bugs:
/api/v0/stats/repo (https://github.com/ipfs/go-ipfs/issues/3874) /api/v0/pin/ls (https://github.com/ipfs/go-ipfs/issues/7528)
Performance Impact
The default configuration for this integration is not expected to impose a significant performance impact on the system.
Setup
Prerequisites
No action required.
Configuration
File
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
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 | The JOB’s name as it will appear at the dashboard (by default is the job_name) | job_name | False |
| url | URL to the IPFS API | no | True |
| repoapi | Collect repo metrics. | no | False |
| pinapi | Set status of IPFS pinned object polling. | no | False |
Examples
Basic (default out-of-the-box)
A basic example configuration, one job will run at a time. Autodetect mechanism uses it by default.
localhost:
name: 'local'
url: 'http://localhost:5001'
repoapi: no
pinapi: no
Multi-instance
Note: When you define multiple jobs, their names must be unique.
Collecting metrics from local and remote instances.
localhost:
name: 'local'
url: 'http://localhost:5001'
repoapi: no
pinapi: no
remote_host:
name: 'remote'
url: 'http://192.0.2.1:5001'
repoapi: no
pinapi: no
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 IPFS instance
These metrics refer to the entire monitored application.
This scope has no labels.
Metrics:
| Metric | Dimensions | Unit |
|---|---|---|
| ipfs.bandwidth | in, out | kilobits/s |
| ipfs.peers | peers | peers |
| ipfs.repo_size | avail, size | GiB |
| ipfs.repo_objects | objects, pinned, recursive_pins | objects |
Alerts
The following alerts are available:
| Alert name | On metric | Description |
|---|---|---|
| ipfs_datastore_usage | ipfs.repo_size | IPFS datastore utilization |
Troubleshooting
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.ddirectory, usually at/usr/libexec/netdata/plugins.d/. If that’s not the case on your system, opennetdata.confand look for thepluginssetting under[directories].cd /usr/libexec/netdata/plugins.d/ -
Switch to the
netdatauser.sudo -u netdata -s -
Run the
python.d.pluginto debug the collector:./python.d.plugin ipfs debug trace