Telegraf

Telegraf is an open-source plugin-driven agent for collecting, processing, and sending metrics and events for time series and observability workloads (observability / telemetry collection).

• Agent for collecting metrics, events, and logs from systems, applications, databases, and network devices (observability).
• Plugin-based architecture with input, processor, aggregator, and output plugins for data collection and routing (extensibility framework).
• Supports multiple output targets including InfluxDB and other time series and monitoring systems (data integration).
• Lightweight, single-binary deployment suitable for servers, containers, and edge environments (infrastructure monitoring).
• Part of the InfluxData platform for time series data, integrating with InfluxDB and related tools (time series platform).

More About Telegraf

Telegraf is an open-source agent developed by InfluxData for collecting, processing, and exporting metrics and events within time series and observability platforms (observability / telemetry collection). It addresses the need for a unified, configurable data collection layer that can run across hosts, containers, and edge systems and feed time series databases and monitoring backends. Telegraf is designed to support environments where teams need to capture infrastructure, application, and service telemetry with a consistent operational model.

The project uses a plugin-based architecture (extensibility framework) that separates inputs, processors, aggregators, and outputs. Input plugins (data collection) gather metrics, events, and logs from operating systems, containers, applications, databases, message queues, and network devices. Processor plugins (data processing) mutate, filter, or enrich metrics in-flight, for example by transforming tags or dropping specific fields. Aggregator plugins (data aggregation) combine or downsample metrics over defined intervals before export. Output plugins (data export) send data to destinations such as InfluxDB, other time series databases, message queues, or monitoring backends.

Telegraf is commonly deployed as a single static binary (infrastructure agent) on Linux, Windows, and container platforms. This deployment model supports use in Kubernetes, virtual machines, bare-metal servers, and edge nodes. Configuration is typically managed through TOML files, which define enabled plugins and their parameters. This gives platform engineering and Site Reliability Engineering (SRE) teams a declarative way to manage telemetry pipelines alongside configuration management and Infrastructure-as-Code (IaC) tools.

Within the InfluxData ecosystem (time series platform), Telegraf serves as the primary data ingestion layer for InfluxDB, including cloud and enterprise deployments. It integrates with InfluxDB line protocol and supports tagging and field semantics aligned with InfluxDB’s data model (time series database). At the same time, its output plugin system enables Telegraf to interoperate with non-Influx destinations, so enterprises can route data to multiple monitoring, logging, or message bus systems from a single agent footprint.

For enterprise environments, Telegraf supports scenarios such as infrastructure monitoring, application performance monitoring, Internet of Things (IoT) and edge telemetry, and business metrics collection (observability, IoT). Its plugin catalog covers standard infrastructure sources like system metrics, container runtimes, cloud services, and network devices, allowing operators to consolidate diverse telemetry feeds. Because the same agent can handle input, transformation, aggregation, and export, Telegraf functions as a configurable pipeline component within broader observability architectures.

From a directory and taxonomy standpoint, Telegraf fits into categories such as observability agents, metrics collectors, and time series data shippers. It intersects with infrastructure monitoring, log and event collection, and streaming telemetry, while aligning closely with time series storage and analysis platforms through its relationship with InfluxDB and the InfluxData time series platform.