The go_expvar
module can monitor any Go application that exposes its metrics with the use of
expvar
package from the Go standard library.
go_expvar
produces charts for Go runtime memory statistics and optionally any number of custom charts.
For the memory statistics, it produces the following charts:
- Heap allocations in kB
- alloc: size of objects allocated on the heap
- inuse: size of allocated heap spans
- Stack allocations in kB
- inuse: size of allocated stack spans
- MSpan allocations in kB
- inuse: size of allocated mspan structures
- MCache allocations in kB
- inuse: size of allocated mcache structures
- Virtual memory in kB
- sys: size of reserved virtual address space
- Live objects
- live: number of live objects in memory
- GC pauses average in ns
- avg: average duration of all GC stop-the-world pauses
Netdata can be used to monitor running Go applications that expose their metrics with the use of the expvar package included in Go standard library.
The expvar
package exposes these 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, <ommited 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.
In the next section, we will cover how to monitor and chart these exposed stats with
the use of netdata
s go_expvar
module.
The go_expvar
module is disabled by default. To enable it, edit python.d.conf
(to edit it on your system run /etc/netdata/edit-config python.d.conf
), and change the go_expvar
variable to yes
:
# Enable / Disable python.d.plugin modules
#default_run: yes
#
# If "default_run" = "yes" the default for all modules is enabled (yes).
# Setting any of these to "no" will disable it.
#
# If "default_run" = "no" the default for all modules is disabled (no).
# Setting any of these to "yes" will enable it.
...
go_expvar: yes
...
Next, we need to edit the module configuration file (found at /etc/netdata/python.d/go_expvar.conf
by default)
(to edit it on your system run /etc/netdata/edit-config python.d/go_expvar.conf
).
The module configuration consists of jobs, where each job can be used to monitor a separate Go application.
Let's see a sample job configuration:
# /etc/netdata/python.d/go_expvar.conf
app1:
name : 'app1'
url : 'http://127.0.0.1:8080/debug/vars'
collect_memstats: true
extra_charts: {}
Let's go over each of the defined options:
name: 'app1'
This is the job name that will appear at the netdata dashboard. If not defined, the job_name (top level key) will be used.
url: 'http://127.0.0.1:8080/debug/vars'
This is the URL of the expvar endpoint. As the expvar handler can be installed in a custom path, the whole URL has to be specified. This value is mandatory.
collect_memstats: true
Whether to enable collecting stats about Go runtime's memory. You can find more information about the exposed values at the runtime package docs.
extra_charts: {}
Enables the user to specify custom expvars to monitor and chart. Will be explained in more detail below.
Note: if collect_memstats
is disabled and no extra_charts
are defined, the plugin will
disable itself, as there will be no data to collect!
Apart from these options, each job supports options inherited from netdata's python.d.plugin
and its base UrlService
class. These are:
update_every: 1 # the job's data collection frequency
priority: 60000 # the job's order on the dashboard
user: admin # use when the expvar endpoint is protected by HTTP Basic Auth
password: sekret # use when the expvar endpoint is protected by HTTP Basic Auth
Now, memory stats might be useful, but what if you want netdata to monitor some custom values
that your Go application exposes? The go_expvar
module can do that 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.
Configuration example
The configuration below matches the second Go application described above. Netdata will monitor and chart memory stats for the application, as well as a custom chart of running goroutines and two dummy counters.
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}
Netdata charts example
The images below show how do the final charts in netdata look.