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README.md
Telegraf - A native agent for InfluxDB
Telegraf is an agent written in Go for collecting metrics from the system it's running on or from other services and writing them into InfluxDB.
Design goals are to have a minimal memory footprint with a plugin system so that developers in the community can easily add support for collecting metrics from well known services (like Hadoop, or Postgres, or Redis) and third party APIs (like Mailchimp, AWS CloudWatch, or Google Analytics).
We'll eagerly accept pull requests for new plugins and will manage the set of plugins that Telegraf supports. See the bottom of this doc for instructions on writing new plugins.
Quickstart
- Build from source or download telegraf:
Linux packages for Debian/Ubuntu and RHEL/CentOS:
http://get.influxdb.org/telegraf/telegraf_0.1.4_amd64.deb
http://get.influxdb.org/telegraf/telegraf-0.1.4-1.x86_64.rpm
OSX via Homebrew:
brew update
brew install telegraf
How to use it:
- Run
telegraf -sample-config > telegraf.toml
to create an initial configuration - Edit the configuration to match your needs
- Run
telegraf -config telegraf.toml -test
to output one full measurement sample to STDOUT - Run
telegraf -config telegraf.toml
to gather and send metrics to InfluxDB
Telegraf Options
Telegraf has a few options you can configure under the agent
section of the config. If you don't see an agent
section run telegraf -sample-config > telegraf.toml
to create a valid initial configuration:
- hostname: The hostname is passed as a tag. By default this will be the value retured by
hostname
on the machine running Telegraf. You can override that value here. - interval: How ofter to gather metrics. Uses a simple number + unit parser, ie "10s" for 10 seconds or "5m" for 5 minutes.
- debug: Set to true to gather and send metrics to STDOUT as well as InfluxDB.
Supported Plugins
Telegraf currently has support for collecting metrics from:
- System (memory, CPU, network, etc.)
- Docker
- MySQL
- Prometheus (client libraries and exporters)
- PostgreSQL
- Redis
- RethinkDB
- Kafka
We'll be adding support for many more over the coming months. Read on if you want to add support for another service or third-party API.
Plugin Options
There are 3 configuration options that are configurable per plugin:
- pass: An array of strings that is used to filter metrics generated by the current plugin. Each string in the array is tested as a prefix against metrics and if it matches, the metric is emitted.
- drop: The inverse of pass, if a metric matches, it is not emitted.
- interval: How often to gather this metric. Normal plugins use a single global interval, but if one particular plugin should be run less or more often, you can configure that here.
Plugins
This section is for developers that want to create new collection plugins. 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 plugins.
Guidelines
- A plugin must conform to the
plugins.Plugin
interface. - Telegraf promises to run each plugin's Gather function serially. This means developers don't have to worry about thread safety within these functions.
- Each generated metric automatically has the name of the plugin that generated it prepended. This is to keep plugins honest.
- Plugins should call
plugins.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/influxdb/telegraf/plugins/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.
Plugin interface
type Plugin interface {
SampleConfig() string
Description() string
Gather(Accumulator) error
}
type Accumulator interface {
Add(measurement string, value interface{}, tags map[string]string)
AddValuesWithTime(measurement string, values 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"
.
The AddValuesWithTime
allows multiple values for a point to be passed. The values
used are the same type profile as value above. The timestamp argument
allows a point to be registered as having occurred at an arbitrary time.
Let's say you've written a plugin that emits metrics about processes on the current host.
type Process struct {
CPUTime float64
MemoryBytes int64
PID int
}
func Gather(acc plugins.Accumulator) error {
for _, process := range system.Processes() {
tags := map[string]string {
"pid": fmt.Sprintf("%d", process.Pid),
}
acc.Add("cpu", process.CPUTime, tags)
acc.Add("memory", process.MemoryBytes, tags)
}
}
Example
package simple
// simple.go
import "github.com/influxdb/telegraf/plugins"
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 plugins.Accumulator) error {
if s.Ok {
acc.Add("state", "pretty good", nil)
} else {
acc.Add("state", "not great", nil)
}
return nil
}
func init() {
plugins.Add("simple", func() plugins.Plugin { return &Simple{} })
}