Open-Source Observability · influxdata

telegraf

Telegraf is a lightweight, open-source agent written in Go that collects metrics, logs, and data from 300+ sources and sends them to backends like InfluxDB. It deploys as a single binary with no external dependencies, making it easy to integrate into monitoring and observability pipelines.

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Source: GitHub — github.com/influxdata/telegraf

17.7k

GitHub stars

5.8k

Forks

Primary language

MIT

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	influxdata/telegraf
Owner	influxdata
Primary language	Go
License	MIT — OSI-approved
Stars	17.7k
Forks	5.8k
Open issues	413
Latest release	v1.39.1 (2026-06-29)
Last updated	2026-07-07
Source	https://github.com/influxdata/telegraf

What telegraf is

Telegraf uses a plugin architecture (inputs, processors, outputs) configured via TOML to ingest time-series data, structured logs, and arbitrary payloads from devices (OPC UA, Modbus), message queues (Kafka, MQTT, AMQP), cloud APIs, and system metrics. It supports filtering, aggregation, and custom transformations before sending to InfluxDB, Prometheus, and other backends.

Quickstart

Get the telegraf source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/influxdata/telegraf.git2cd telegraf3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Centralized metrics & logs collection at scale

Deploy Telegraf across thousands of servers, containers, and edge devices to standardize metric collection (CPU, memory, disk, network) and forward to a central InfluxDB or observability platform without vendor lock-in.

Multi-source industrial/IoT data aggregation

Ingest telemetry from OPC UA, Modbus, SNMP, and gNMI-enabled equipment alongside Kafka/MQTT message streams, apply data transformation rules, and route to time-series databases or data lakes in a single agent.

Lightweight edge and embedded monitoring

Run Telegraf on resource-constrained devices (embedded Linux, Windows IoT) as a standalone static binary to collect local metrics and logs, then ship to remote backends without installing runtimes or package managers.

Implementation considerations

Plugin selection: 300+ plugins span widely differing maturity levels and active support; audit and test plugin stability and security posture early.
Configuration as code: TOML configuration is human-readable but scale and version control require automation; integrate with configuration management (Ansible, Terraform, etc.).
Resource overhead: lightweight compared to full agents (Datadog, New Relic), but data volume, sampling rate, and processor plugins directly impact CPU/memory; baseline in staging.
Output routing and buffering: failures to backends require local buffering; verify max buffer size and failure behavior aligns with data retention SLAs.
Metric cardinality and tag design: high-cardinality tags (host IDs, request paths) can overwhelm backends; design tag schemas and use processors (aggregation, sampling) to control cost.

When to avoid it — and what to weigh

Need a single commercial support contract with SLA guarantees — Telegraf is MIT-licensed open source; support is community-based (Slack, forums). InfluxData offers commercial support for InfluxDB platform bundles, but Telegraf's support model is not clearly defined in the data.
Require advanced CEP or stateful stream processing — Telegraf is designed for collection, basic filtering, and aggregation. Complex event correlation, windowing, and stateful transformations are beyond its scope; consider Flink, Kafka Streams, or dedicated CEP platforms.
Building a new observability platform or custom DSL — Telegraf is a data-collection agent, not a platform or query engine. If you need to design custom data models or query languages, fork/extend at significant cost or use a more extensible framework.
Operating in air-gapped or high-security environments without prior evaluation — Telegraf has 300+ plugins with varying maturity and external dependencies. Security posture of each plugin is Unknown; requires detailed review of plugins in use before deployment in regulated/air-gapped networks.

License & commercial use

MIT License. Permissive OSI-approved license allowing commercial use, modification, and distribution with minimal restrictions (retain license notice). No copyleft or patent clauses.

MIT License permits commercial use without explicit restrictions. However, support and commercial guarantees (SLA, security patches) are not stated in the data; clarify with InfluxData whether commercial support is available separately and under what terms. Evaluate risk of relying on community support for mission-critical deployments.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Low
DEV.co fit	Strong
Assessment confidence	High

Security considerations

Telegraf runs as an agent with access to system metrics and potentially sensitive data (logs, credentials in configs). Plugin security posture is Unknown; 300+ plugins have varying external dependencies and code review standards. Recommend: audit plugins in use, follow least-privilege deployment (systemd user accounts, container capabilities), store sensitive credentials (API keys) in secure vaults not config files, and monitor plugin dependencies for CVEs. No information on security advisory process or incident response timeline.

Alternatives to consider

Prometheus Node Exporter

Lightweight system metrics exporter for Unix/Linux; simpler single-purpose tool if only system metrics are needed. Lacks multi-protocol support (OPC UA, Modbus) and log collection.

Fluent Bit

Log collection and lightweight data processing; similar deployment model (static binary, low overhead). Stronger focus on log pipelines; weaker for time-series metrics and industrial protocols.

Logstash / Beats

Full Elastic Stack integration with rich data transformation (Grok parsing, filters). Heavier resource footprint and Elastic licensing (SSPL); broader for log-centric workflows.

Software development agency

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Telegraf simplifies data collection across hybrid infrastructure. Let Devco help you design and deploy a scalable observability strategy tailored to your stack.

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telegraf FAQ

Can Telegraf run on Windows?

Yes. README lists Windows-specific plugins (Event Log, WMI, Performance Counters). Binary builds for Windows are available; see install guide.

Does Telegraf require InfluxDB?

No. InfluxDB is one output target. Telegraf supports 300+ plugins and multiple outputs (Prometheus, Kafka, HTTP, Datadog, CloudWatch, etc.); configure any combination.

How do I extend Telegraf with custom metrics?

Use the Exec input plugin to call external scripts or binaries, or recompile Telegraf with custom input/processor plugins in Go. The former is simpler but slower; the latter requires Go development.

What is the recommended way to run Telegraf in production?

Typically systemd service on Linux, NSSM or Windows Service on Windows, or containers (Docker, Kubernetes). Use configuration management (Ansible, Terraform) for fleet deployment and version control configs in Git.

Work with a software development agency

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