Telegraf Output Plugins

Telegraf Output Plugins are used to send metrics to a variety of datastores like InfluxDB.

Telegraf Plugin System Overview

Telegraf offers users hundreds of plugins to choose from. In this video, learn about the plugin ecosystem, the different types of plugins available, and walks through an example to explain how a plugin works.

Why use a Telegraf Output Plugin

Telegraf Output plugins are used to send metrics to a variety of datastores such as InfluxDB and Graphite, services such as Azure Data explorer, and messaging queues like Kafka.

Efficient data collector

Telegraf offers flexible processing to turn the messiest data into consistent clean data as it’s coming into your database on whatever time interval. You can filter and route specific metrics to a specific data source saving time and storage space.

Open source

Telegraf is an open source plugin-driven server agent for collecting and reporting metrics and is distributed under the MIT license. You can also build a plugin in your favorite language to extend your metric collection to include any custom metric you may have.

Native support for InfluxDB

Telegraf’s plugin-driven architecture and lightweight footprint requires no external dependencies. Telegraf can run directly on the server, VM, or container from which you wish to ingest metrics or in a centralized location that polls the desired services.

Telegraf Output Plugin key capabilities

Support for a variety of datastores

Telegraf output plugins are used to send metrics to a variety of datastores such as InfluxDB and Graphite, services such as Azure Data explorer, and Messaging queues like Kafka. You can use multiple outputs at the same time if you want to dual write data to different output destinations.

Flexible Parser

Telegraf enables flexible parsing and serializing for a variety of data formats. It takes data in format such as JSON, CSV and graphite, and can serialize them in InfluxDB line protocol and Prometheus to name a few.

Robust Scheduler

The Telegraf agent contains a robust scheduler that includes adjusting for clockdrift and making adjustments for job scheduling issues that may occur. It also contains an in-memory metric buffers to keeps things going if the downstream database is temporarily unavailable.