INPUTS.md

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.
• To be available within Telegraf itself, plugins must register themselves using a file in github.com/influxdata/telegraf/plugins/inputs/all named according to the plugin name. Make sure you also add build-tags to conditionally build the plugin.
• Each plugin requires a file called sample.conf containing the sample configuration for the plugin in TOML format. Please consult the Sample Config page for the latest style guidelines.
• Each plugin README.md file should include the sample.conf file in a section describing the configuration by specifying a toml section in the form toml @sample.conf. The specified file(s) are then injected automatically into the Readme.
• Follow the recommended Code Style.

Typed Metrics

In addition to 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.

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 sample configuration in the README.md:

  ## 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.

Please note that this process applies only to internal plugins. For external plugins, the metrics are acknowledged regardless of the actual output.

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.

External Services

Plugins that connect or require the use of external services should ensure that those servers are active. When may depend on the type of input plugin:

For service input plugins, Init should be used to check for configuration issues (e.g. bad option) and for other non-recoverable errors. Then Start is used to create connections or other retry-able operations.

For normal inputs, Init should also be used to check for configuration issues as well as any other dependencies that the plugin will require. For example, any binaries that must exist for the plugin to function. If making a connection, this should also take place in Init.

Developers may find that they switch to using service input plugins more and more to take advantage of the error on retry behavior features. This allows the user to decide what to do on an error, like ignoring the plugin or retrying constantly.

Input Plugin Example

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

Register Plugin

Registration of the plugin on plugins/inputs/all/simple.go:

//go:build !custom || inputs || inputs.simple

package all

import _ "github.com/influxdata/telegraf/plugins/inputs/simple" // register plugin

The build-tags in the first line allow to selectively include/exclude your plugin when customizing Telegraf.

Plugin

Content of your plugin file e.g. simple.go

//go:generate ../../../tools/readme_config_includer/generator
package simple

import (
    _ "embed"

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

//go:embed sample.conf
var sampleConfig string

type Simple struct {
    Ok  bool            `toml:"ok"`
    Log telegraf.Logger `toml:"-"`
}

func (*Simple) SampleConfig() string {
    return sampleConfig
}

// Init is for setup, and validating config.
func (s *Simple) Init() error {
    return nil
}

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{} })
}