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.
This integration doesn’t support auto-detection.
The default configuration for this integration does not impose any limits on data collection.
The default configuration for this integration is not expected to impose a significant performance impact on the system.
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.
expvar
usage in a Go applicationThe expvar
package exposes metrics over HTTP and is very easy to use.
Consider this minimal sample below:
package main
import (
_ "expvar"
"net/http"
)
func main() {
http.ListenAndServe("127.0.0.1:8080", 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 (
"expvar"
"net/http"
"runtime"
"time"
)
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:
num_go.Set(int64(runtime.NumGoroutine()))
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:
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 |
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.
Example:
{
"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.
app1:
name : 'app1'
url : 'http://127.0.0.1:8080/debug/vars'
collect_memstats: true
extra_charts:
- id: "runtime_goroutines"
options:
name: num_goroutines
title: "runtime: number of goroutines"
units: goroutines
family: runtime
context: expvar.runtime.goroutines
chart_type: line
lines:
- {expvar_key: 'runtime.goroutines', expvar_type: int, id: runtime_goroutines}
- id: "foo_counters"
options:
name: counters
title: "some random counters"
units: awesomeness
family: counters
context: expvar.foo.counters
chart_type: line
lines:
- {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.
These metrics refer to the entire monitored application.
This scope has no labels.
Metrics:
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.
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
If you’re encountering problems with the go_expvar
collector, follow these steps to retrieve logs and identify potential issues:
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
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.
If your Netdata runs in a Docker container named “netdata” (replace if different), use this command:
docker logs netdata 2>&1 | grep go_expvar