306 lines
10 KiB
Markdown
306 lines
10 KiB
Markdown
## Steps for Contributing:
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1. [Sign the CLA](http://influxdb.com/community/cla.html)
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1. Make changes or write plugin (see below for details)
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1. Add your plugin to `plugins/inputs/all/all.go` or `plugins/outputs/all/all.go`
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1. If your plugin requires a new Go package,
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[add it](https://github.com/influxdata/telegraf/blob/master/CONTRIBUTING.md#adding-a-dependency)
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1. Write a README for your plugin, if it's an input plugin, it should be structured
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like the [input example here](https://github.com/influxdata/telegraf/blob/master/plugins/inputs/EXAMPLE_README.md).
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Output plugins READMEs are less structured,
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but any information you can provide on how the data will look is appreciated.
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See the [OpenTSDB output](https://github.com/influxdata/telegraf/tree/master/plugins/outputs/opentsdb)
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for a good example.
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1. **Optional:** Help users of your plugin by including example queries for populating dashboards. Include these sample queries in the `README.md` for the plugin.
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1. **Optional:** Write a [tickscript](https://docs.influxdata.com/kapacitor/v1.0/tick/syntax/) for your plugin and add it to [Kapacitor](https://github.com/influxdata/kapacitor/tree/master/examples/telegraf). Or mention @jackzampolin in a PR comment with some common queries that you would want to alert on and he will write one for you.
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## GoDoc
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Public interfaces for inputs, outputs, metrics, and the accumulator can be found
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on the GoDoc
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[![GoDoc](https://godoc.org/github.com/influxdata/telegraf?status.svg)](https://godoc.org/github.com/influxdata/telegraf)
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## Sign the CLA
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Before we can merge a pull request, you will need to sign the CLA,
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which can be found [on our website](http://influxdb.com/community/cla.html)
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## Adding a dependency
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Assuming you can already build the project, run these in the telegraf directory:
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1. `go get github.com/sparrc/gdm`
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1. `gdm restore`
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1. `GOOS=linux gdm save`
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## Input Plugins
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This section is for developers who want to create new collection inputs.
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Telegraf is entirely plugin driven. This interface allows for operators to
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pick and chose what is gathered and makes it easy for developers
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to create new ways of generating metrics.
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Plugin authorship is kept as simple as possible to promote people to develop
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and submit new inputs.
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### Input Plugin Guidelines
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* A plugin must conform to the `telegraf.Input` interface.
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* Input Plugins should call `inputs.Add` in their `init` function to register themselves.
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See below for a quick example.
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* Input Plugins must be added to the
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`github.com/influxdata/telegraf/plugins/inputs/all/all.go` file.
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* The `SampleConfig` function should return valid toml that describes how the
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plugin can be configured. This is include in `telegraf -sample-config`.
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* The `Description` function should say in one line what this plugin does.
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Let's say you've written a plugin that emits metrics about processes on the
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current host.
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### Input Plugin Example
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```go
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package simple
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// simple.go
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import (
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"github.com/influxdata/telegraf"
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"github.com/influxdata/telegraf/plugins/inputs"
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)
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type Simple struct {
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Ok bool
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}
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func (s *Simple) Description() string {
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return "a demo plugin"
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}
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func (s *Simple) SampleConfig() string {
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return "ok = true # indicate if everything is fine"
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}
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func (s *Simple) Gather(acc telegraf.Accumulator) error {
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if s.Ok {
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acc.AddFields("state", map[string]interface{}{"value": "pretty good"}, nil)
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} else {
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acc.AddFields("state", map[string]interface{}{"value": "not great"}, nil)
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}
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return nil
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}
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func init() {
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inputs.Add("simple", func() telegraf.Input { return &Simple{} })
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}
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```
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## Adding Typed Metrics
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In addition the the `AddFields` function, the accumulator also supports an
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`AddGauge` and `AddCounter` function. These functions are for adding _typed_
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metrics. Metric types are ignored for the InfluxDB output, but can be used
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for other outputs, such as [prometheus](https://prometheus.io/docs/concepts/metric_types/).
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## Input Plugins Accepting Arbitrary Data Formats
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Some input plugins (such as
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[exec](https://github.com/influxdata/telegraf/tree/master/plugins/inputs/exec))
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accept arbitrary input data formats. An overview of these data formats can
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be found
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[here](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md).
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In order to enable this, you must specify a `SetParser(parser parsers.Parser)`
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function on the plugin object (see the exec plugin for an example), as well as
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defining `parser` as a field of the object.
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You can then utilize the parser internally in your plugin, parsing data as you
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see fit. Telegraf's configuration layer will take care of instantiating and
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creating the `Parser` object.
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You should also add the following to your SampleConfig() return:
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```toml
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## Data format to consume.
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## Each data format has it's own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "influx"
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```
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Below is the `Parser` interface.
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```go
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// Parser is an interface defining functions that a parser plugin must satisfy.
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type Parser interface {
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// Parse takes a byte buffer separated by newlines
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// ie, `cpu.usage.idle 90\ncpu.usage.busy 10`
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// and parses it into telegraf metrics
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Parse(buf []byte) ([]telegraf.Metric, error)
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// ParseLine takes a single string metric
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// ie, "cpu.usage.idle 90"
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// and parses it into a telegraf metric.
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ParseLine(line string) (telegraf.Metric, error)
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}
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```
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And you can view the code
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[here.](https://github.com/influxdata/telegraf/blob/henrypfhu-master/plugins/parsers/registry.go)
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## Service Input Plugins
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This section is for developers who want to create new "service" collection
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inputs. A service plugin differs from a regular plugin in that it operates
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a background service while Telegraf is running. One example would be the `statsd`
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plugin, which operates a statsd server.
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Service Input Plugins are substantially more complicated than a regular plugin, as they
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will require threads and locks to verify data integrity. Service Input Plugins should
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be avoided unless there is no way to create their behavior with a regular plugin.
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Their interface is quite similar to a regular plugin, with the addition of `Start()`
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and `Stop()` methods.
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### Service Plugin Guidelines
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* Same as the `Plugin` guidelines, except that they must conform to the
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`inputs.ServiceInput` interface.
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## Output Plugins
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This section is for developers who want to create a new output sink. Outputs
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are created in a similar manner as collection plugins, and their interface has
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similar constructs.
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### Output Plugin Guidelines
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* An output must conform to the `outputs.Output` interface.
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* Outputs should call `outputs.Add` in their `init` function to register themselves.
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See below for a quick example.
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* To be available within Telegraf itself, plugins must add themselves to the
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`github.com/influxdata/telegraf/plugins/outputs/all/all.go` file.
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* The `SampleConfig` function should return valid toml that describes how the
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output can be configured. This is include in `telegraf -sample-config`.
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* The `Description` function should say in one line what this output does.
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### Output Example
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```go
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package simpleoutput
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// simpleoutput.go
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import (
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"github.com/influxdata/telegraf"
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"github.com/influxdata/telegraf/plugins/outputs"
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)
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type Simple struct {
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Ok bool
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}
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func (s *Simple) Description() string {
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return "a demo output"
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}
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func (s *Simple) SampleConfig() string {
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return "url = localhost"
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}
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func (s *Simple) Connect() error {
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// Make a connection to the URL here
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return nil
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}
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func (s *Simple) Close() error {
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// Close connection to the URL here
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return nil
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}
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func (s *Simple) Write(metrics []telegraf.Metric) error {
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for _, metric := range metrics {
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// write `metric` to the output sink here
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}
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return nil
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}
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func init() {
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outputs.Add("simpleoutput", func() telegraf.Output { return &Simple{} })
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}
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```
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## Output Plugins Writing Arbitrary Data Formats
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Some output plugins (such as
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[file](https://github.com/influxdata/telegraf/tree/master/plugins/outputs/file))
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can write arbitrary output data formats. An overview of these data formats can
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be found
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[here](https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md).
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In order to enable this, you must specify a
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`SetSerializer(serializer serializers.Serializer)`
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function on the plugin object (see the file plugin for an example), as well as
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defining `serializer` as a field of the object.
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You can then utilize the serializer internally in your plugin, serializing data
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before it's written. Telegraf's configuration layer will take care of
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instantiating and creating the `Serializer` object.
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You should also add the following to your SampleConfig() return:
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```toml
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## Data format to output.
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## Each data format has it's own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
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data_format = "influx"
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```
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## Service Output Plugins
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This section is for developers who want to create new "service" output. A
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service output differs from a regular output in that it operates a background service
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while Telegraf is running. One example would be the `prometheus_client` output,
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which operates an HTTP server.
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Their interface is quite similar to a regular output, with the addition of `Start()`
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and `Stop()` methods.
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### Service Output Guidelines
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* Same as the `Output` guidelines, except that they must conform to the
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`output.ServiceOutput` interface.
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## Unit Tests
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### Execute short tests
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execute `make test-short`
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### Execute long tests
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As Telegraf collects metrics from several third-party services it becomes a
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difficult task to mock each service as some of them have complicated protocols
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which would take some time to replicate.
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To overcome this situation we've decided to use docker containers to provide a
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fast and reproducible environment to test those services which require it.
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For other situations
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(i.e: https://github.com/influxdata/telegraf/blob/master/plugins/inputs/redis/redis_test.go)
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a simple mock will suffice.
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To execute Telegraf tests follow these simple steps:
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- Install docker following [these](https://docs.docker.com/installation/)
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instructions
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- execute `make test`
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### Unit test troubleshooting
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Try cleaning up your test environment by executing `make docker-kill` and
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re-running
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