### 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 and 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 [telegraf.Input][] interface.
- Input Plugins should call `inputs.Add` in their `init` 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 included in `telegraf config`.  Please
  consult the [SampleConfig][] page for the latest style
  guidelines.
- The `Description` function should say in one line what this plugin does.
- Follow the recommended [CodeStyle][].

Let's say you've written a plugin that emits metrics about processes on the
current host.

### Input Plugin Example

```go
package simple

// simple.go

import (
    "github.com/influxdata/telegraf"
    "github.com/influxdata/telegraf/plugins/inputs"
)

type Simple struct {
    Ok bool `toml:"ok"`
}

func (s *Simple) Description() string {
    return "a demo plugin"
}

func (s *Simple) SampleConfig() string {
    return `
  ## Indicate if everything is fine
  ok = true
`
}

func (s *Simple) Gather(acc telegraf.Accumulator) error {
    if s.Ok {
        acc.AddFields("state", map[string]interface{}{"value": "pretty good"}, nil)
    } else {
        acc.AddFields("state", map[string]interface{}{"value": "not great"}, nil)
    }

    return nil
}

func init() {
    inputs.Add("simple", func() telegraf.Input { return &Simple{} })
}
```

### Development

* Run `make static` followed by `make plugin-[pluginName]` to spin up a docker
  dev environment using docker-compose.
* ***[Optional]*** When developing a plugin, add a `dev` directory with a
  `docker-compose.yml` and `telegraf.conf` as well as any other supporting
  files, where sensible.

### Typed Metrics

In addition the the `AddFields` function, the accumulator also supports
functions to add typed metrics: `AddGauge`, `AddCounter`, etc.  Metric types
are ignored by the InfluxDB output, but can be used for other outputs, such as
[prometheus][prom metric types].

### Data Formats

Some input plugins, such as the [exec][] plugin, can accept any supported
[input data formats][].

In order to enable this, you must specify a `SetParser(parser parsers.Parser)`
function on the plugin object (see the exec plugin for an example), as well as
defining `parser` as a field of the object.

You can then utilize the parser internally in your plugin, parsing data as you
see fit. Telegraf's configuration layer will take care of instantiating and
creating the `Parser` object.

Add the following to the `SampleConfig()`:

```toml
  ## Data format to consume.
  ## Each data format has its own unique set of configuration options, read
  ## more about them here:
  ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
  data_format = "influx"
```

### 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.

To create a Service Input implement the [telegraf.ServiceInput][] interface.

### Metric Tracking

Metric Tracking provides a system to be notified when metrics have been
successfully written to their outputs or otherwise discarded.  This allows
inputs to be created that function as reliable queue consumers.

To get started with metric tracking begin by calling `WithTracking` on the
[telegraf.Accumulator][].  Add metrics using the `AddTrackingMetricGroup`
function on the returned [telegraf.TrackingAccumulator][] and store the
`TrackingID`.  The `Delivered()` channel will return a type with information
about the final delivery status of the metric group.

Check the [amqp_consumer][] for an example implementation.

[exec]: https://github.com/influxdata/telegraf/tree/master/plugins/inputs/exec
[amqp_consumer]: https://github.com/influxdata/telegraf/tree/master/plugins/inputs/amqp_consumer
[prom metric types]: https://prometheus.io/docs/concepts/metric_types/
[input data formats]: https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
[SampleConfig]: https://github.com/influxdata/telegraf/wiki/SampleConfig
[CodeStyle]: https://github.com/influxdata/telegraf/wiki/CodeStyle
[telegraf.Input]: https://godoc.org/github.com/influxdata/telegraf#Input
[telegraf.ServiceInput]: https://godoc.org/github.com/influxdata/telegraf#ServiceInput
[telegraf.Accumulator]: https://godoc.org/github.com/influxdata/telegraf#Accumulator
[telegraf.TrackingAccumulator]: https://godoc.org/github.com/influxdata/telegraf#Accumulator
