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Input Plugins
This section is for developers who want to create new collection inputs. Telegraf is entirely plugin driven. This interface allows for operators to pick and chose what is gathered as well as makes it easy for developers to create new ways of generating metrics.
Plugin authorship is kept as simple as possible to promote people to develop and submit new inputs.
Input Plugin Guidelines
- A plugin must conform to the
inputs.Input
interface. - Input Plugins should call
inputs.Add
in theirinit
function to register themselves. See below for a quick example. - Input Plugins must be added to the
github.com/influxdata/telegraf/plugins/inputs/all/all.go
file. - The
SampleConfig
function should return valid toml that describes how the plugin can be configured. This is include intelegraf -sample-config
. - The
Description
function should say in one line what this plugin does.
Input interface
type Input interface {
SampleConfig() string
Description() string
Gather(Accumulator) error
}
type Accumulator interface {
Add(measurement string,
value interface{},
tags map[string]string,
timestamp ...time.Time)
AddFields(measurement string,
fields map[string]interface{},
tags map[string]string,
timestamp ...time.Time)
}
Accumulator
The way that a plugin emits metrics is by interacting with the Accumulator.
The Add
function takes 3 arguments:
- measurement: A string description of the metric. For instance
bytes_read
orfaults
. - value: A value for the metric. This accepts 5 different types of value:
- int: The most common type. All int types are accepted but favor using
int64
Useful for counters, etc. - float: Favor
float64
, useful for gauges, percentages, etc. - bool:
true
orfalse
, useful to indicate the presence of a state.light_on
, etc. - string: Typically used to indicate a message, or some kind of freeform information.
- time.Time: Useful for indicating when a state last occurred, for instance
light_on_since
.
- int: The most common type. All int types are accepted but favor using
- tags: This is a map of strings to strings to describe the where or who
about the metric. For instance, the
net
plugin adds a tag named"interface"
set to the name of the network interface, like"eth0"
.
Let's say you've written a plugin that emits metrics about processes on the current host.
Input Plugin Example
package simple
// simple.go
import "github.com/influxdata/telegraf/plugins/inputs"
type Simple struct {
Ok bool
}
func (s *Simple) Description() string {
return "a demo plugin"
}
func (s *Simple) SampleConfig() string {
return "ok = true # indicate if everything is fine"
}
func (s *Simple) Gather(acc inputs.Accumulator) error {
if s.Ok {
acc.Add("state", "pretty good", nil)
} else {
acc.Add("state", "not great", nil)
}
return nil
}
func init() {
inputs.Add("simple", func() inputs.Input { return &Simple{} })
}
Service Input Plugins
This section is for developers who want to create new "service" collection
inputs. A service plugin differs from a regular plugin in that it operates
a background service while Telegraf is running. One example would be the statsd
plugin, which operates a statsd server.
Service Input Plugins are substantially more complicated than a regular plugin, as they will require threads and locks to verify data integrity. Service Input Plugins should be avoided unless there is no way to create their behavior with a regular plugin.
Their interface is quite similar to a regular plugin, with the addition of Start()
and Stop()
methods.
Service Plugin Guidelines
- Same as the
Plugin
guidelines, except that they must conform to theinputs.ServiceInput
interface.
Service Plugin interface
type ServicePlugin interface {
SampleConfig() string
Description() string
Gather(Accumulator) error
Start() error
Stop()
}
Output Plugins
This section is for developers who want to create a new output sink. Outputs are created in a similar manner as collection plugins, and their interface has similar constructs.
Output Plugin Guidelines
- An output must conform to the
outputs.Output
interface. - Outputs should call
outputs.Add
in theirinit
function to register themselves. See below for a quick example. - To be available within Telegraf itself, plugins must add themselves to the
github.com/influxdata/telegraf/plugins/outputs/all/all.go
file. - The
SampleConfig
function should return valid toml that describes how the output can be configured. This is include intelegraf -sample-config
. - The
Description
function should say in one line what this output does.
Output interface
type Output interface {
Connect() error
Close() error
Description() string
SampleConfig() string
Write(points []*client.Point) error
}
Output Example
package simpleoutput
// simpleoutput.go
import "github.com/influxdata/telegraf/plugins/outputs"
type Simple struct {
Ok bool
}
func (s *Simple) Description() string {
return "a demo output"
}
func (s *Simple) SampleConfig() string {
return "url = localhost"
}
func (s *Simple) Connect() error {
// Make a connection to the URL here
return nil
}
func (s *Simple) Close() error {
// Close connection to the URL here
return nil
}
func (s *Simple) Write(points []*client.Point) error {
for _, pt := range points {
// write `pt` to the output sink here
}
return nil
}
func init() {
outputs.Add("simpleoutput", func() outputs.Output { return &Simple{} })
}
Service Output Plugins
This section is for developers who want to create new "service" output. A
service output differs from a regular output in that it operates a background service
while Telegraf is running. One example would be the prometheus_client
output,
which operates an HTTP server.
Their interface is quite similar to a regular output, with the addition of Start()
and Stop()
methods.
Service Output Guidelines
- Same as the
Output
guidelines, except that they must conform to theoutput.ServiceOutput
interface.
Service Output interface
type ServiceOutput interface {
Connect() error
Close() error
Description() string
SampleConfig() string
Write(points []*client.Point) error
Start() error
Stop()
}
Unit Tests
Execute short tests
execute make test-short
Execute long tests
As Telegraf collects metrics from several third-party services it becomes a difficult task to mock each service as some of them have complicated protocols which would take some time to replicate.
To overcome this situation we've decided to use docker containers to provide a fast and reproducible environment to test those services which require it. For other situations (i.e: https://github.com/influxdata/telegraf/blob/master/plugins/redis/redis_test.go) a simple mock will suffice.
To execute Telegraf tests follow these simple steps:
- Install docker following these instructions
- execute
make test
OSX users: you will need to install boot2docker
or docker-machine
.
The Makefile will assume that you have a docker-machine
box called default
to
get the IP address.
Unit test troubleshooting
Try cleaning up your test environment by executing make docker-kill
and
re-running