Go applications (EXPVAR) icon

Go applications (EXPVAR)

Go applications (EXPVAR)

Plugin: python.d.plugin Module: go_expvar


This collector monitors Go applications that expose their metrics with the use of the expvar package from the Go standard library. It produces charts for Go runtime memory statistics and optionally any number of custom charts.

It connects via http to gather the metrics exposed via the expvar package.

This collector is supported on all platforms.

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

Default Behavior


This integration doesn’t support auto-detection.


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.



Enable the go_expvar collector

The go_expvar collector is disabled by default. To enable it, use edit-config from the Netdata config directory, which is typically at /etc/netdata, to edit the python.d.conf file.

cd /etc/netdata   # Replace this path with your Netdata config directory, if different
sudo ./edit-config python.d.conf

Change the value of the go_expvar setting to yes. Save the file and restart the Netdata Agent with sudo systemctl restart netdata, or the appropriate method for your system.

Sample expvar usage in a Go application

The expvar package exposes metrics over HTTP and is very easy to use. Consider this minimal sample below:

package main

import (
        _ "expvar"

func main() {
        http.ListenAndServe("", nil)

When imported this way, the expvar package registers a HTTP handler at /debug/vars that exposes Go runtime’s memory statistics in JSON format. You can inspect the output by opening the URL in your browser (or by using wget or curl).

Sample output:

"cmdline": ["./expvar-demo-binary"],
"memstats": {"Alloc":630856,"TotalAlloc":630856,"Sys":3346432,"Lookups":27, <omitted for brevity>}

You can of course expose and monitor your own variables as well. Here is a sample Go application that exposes a few custom variables:

package main

import (

func main() {

    tick := time.NewTicker(1 * time.Second)
    num_go := expvar.NewInt("runtime.goroutines")
    counters := expvar.NewMap("counters")
    counters.Set("cnt1", new(expvar.Int))
    counters.Set("cnt2", new(expvar.Float))

    go http.ListenAndServe(":8080", nil)

    for {
        select {
        case <- tick.C:
            counters.Add("cnt1", 1)
            counters.AddFloat("cnt2", 1.452)

Apart from the runtime memory stats, this application publishes two counters and the number of currently running Goroutines and updates these stats every second.



The configuration file name for this integration is python.d/go_expvar.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/go_expvar.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. Each JOB can be used to monitor a different Go application.

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
url the URL and port of the expvar endpoint. Please include the whole path of the endpoint, as the expvar handler can be installed in a non-standard location. yes
user If the URL is password protected, this is the username to use. no
pass If the URL is password protected, this is the password to use. no
collect_memstats Enables charts for Go runtime’s memory statistics. no
extra_charts Defines extra data/charts to monitor, please see the example below. no


Monitor a Go app1 application

The example below sets a configuration for a Go application, called app1. Besides the memstats, the application also exposes two counters and the number of currently running Goroutines and updates these stats every second.

The go_expvar collector can monitor these as well with the use of the extra_charts configuration variable.

The extra_charts variable is a YaML list of Netdata chart definitions. Each chart definition has the following keys:

id:         Netdata chart ID
options:    a key-value mapping of chart options
lines:      a list of line definitions

Note: please do not use dots in the chart or line ID field. See this issue for explanation.

Please see these two links to the official Netdata documentation for more information about the values:

Line definitions

Each chart can define multiple lines (dimensions). A line definition is a key-value mapping of line options. Each line can have the following options:

# mandatory
expvar_key: the name of the expvar as present in the JSON output of /debug/vars endpoint
expvar_type: value type; supported are "float" or "int"
id: the id of this line/dimension in Netdata

# optional - Netdata defaults are used if these options are not defined
name: ''
algorithm: absolute
multiplier: 1
divisor: 100 if expvar_type == float, 1 if expvar_type == int
hidden: False

Please see the following link for more information about the options and their default values: External plugins - dimensions

Apart from top-level expvars, this plugin can also parse expvars stored in a multi-level map; All dicts in the resulting JSON document are then flattened to one level. Expvar names are joined together with ‘.’ when flattening.


    "counters": {"cnt1": 1042, "cnt2": 1512.9839999999983},
    "runtime.goroutines": 5

In the above case, the exported variables will be available under runtime.goroutines, counters.cnt1 and counters.cnt2 expvar_keys. If the flattening results in a key collision, the first defined key wins and all subsequent keys with the same name are ignored.

 name : 'app1'
 url  : ''
 collect_memstats: true
   - id: "runtime_goroutines"
       name: num_goroutines
       title: "runtime: number of goroutines"
       units: goroutines
       family: runtime
       context: expvar.runtime.goroutines
       chart_type: line
       - {expvar_key: 'runtime.goroutines', expvar_type: int, id: runtime_goroutines}
   - id: "foo_counters"
       name: counters
       title: "some random counters"
       units: awesomeness
       family: counters
       context: expvar.foo.counters
       chart_type: line
       - {expvar_key: 'counters.cnt1', expvar_type: int, id: counters_cnt1}
       - {expvar_key: 'counters.cnt2', expvar_type: float, id: counters_cnt2}


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 Go applications (EXPVAR) instance

These metrics refer to the entire monitored application.

This scope has no labels.


Metric Dimensions Unit
expvar.memstats.heap alloc, inuse KiB
expvar.memstats.stack inuse KiB
expvar.memstats.mspan inuse KiB
expvar.memstats.mcache inuse KiB
expvar.memstats.live_objects live objects
expvar.memstats.sys sys KiB
expvar.memstats.gc_pauses avg ns


There are no alerts configured by default for this integration.


Debug Mode

To troubleshoot issues with the go_expvar 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 go_expvar debug trace

Getting Logs

If you’re encountering problems with the go_expvar collector, follow these steps to retrieve logs and identify potential issues:

  • Run the command specific to your system (systemd, non-systemd, or Docker container).
  • Examine the output for any warnings or error messages that might indicate issues. These messages should provide clues about the root cause of the problem.

System with systemd

Use the following command to view logs generated since the last Netdata service restart:

journalctl _SYSTEMD_INVOCATION_ID="$(systemctl show --value --property=InvocationID netdata)" --namespace=netdata --grep go_expvar

System without systemd

Locate the collector log file, typically at /var/log/netdata/collector.log, and use grep to filter for collector’s name:

grep go_expvar /var/log/netdata/collector.log

Note: This method shows logs from all restarts. Focus on the latest entries for troubleshooting current issues.

Docker Container

If your Netdata runs in a Docker container named “netdata” (replace if different), use this command:

docker logs netdata 2>&1 | grep go_expvar

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