Metricbeat vs Telegraf

Overview

Telegraf

Stacks290

Followers321

Votes16

GitHub Stars16.4K

Forks5.7K

Metricbeat

Stacks48

Followers125

Votes3

Metricbeat vs Telegraf: What are the differences?

Data Collection: Metricbeat primarily focuses on collecting metrics from various systems and services, while Telegraf is more versatile in that it can collect metrics as well as log data, making it a more comprehensive monitoring tool.
Data Shipper Options: Metricbeat is native to the Elastic Stack, making it a seamless choice for users of this ecosystem, whereas Telegraf offers a wider range of output options, including databases, messaging systems, and cloud services, providing more flexibility in data export.
Plugin Ecosystem: Telegraf has a vast library of plugins for collecting data from different sources, enabling users to quickly set up monitoring for various services, whereas Metricbeat has a more limited set of modules focused on specific metrics collection purposes.
Resource Utilization: Metricbeat is known for its lightweight nature, consuming minimal system resources and having lower network bandwidth usage compared to Telegraf, which can be advantageous in resource-constrained environments.
Configuration and Management: Telegraf offers more advanced configuration options, including the ability to define complex processing pipelines and routing rules, while Metricbeat provides a simpler, more user-friendly configuration setup suitable for beginners or those requiring streamlined monitoring.
Community Support: Both Metricbeat and Telegraf have strong communities, but Telegraf's community-driven development approach and active plugin contributions lead to faster updates and a broader range of features compared to Metricbeat.

In Summary, Metricbeat is ideal for basic metric monitoring within the Elastic Stack, while Telegraf offers a more versatile solution for gathering metrics and log data from a variety of sources.

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CLI (Node.js)

Manual

Advice on Telegraf, Metricbeat

Sunil

Team Lead at XYZ

Jun 15, 2020

Needs adviceon

Prometheus

Grafana

Linux

Hi, We have a situation, where we are using Prometheus to get system metrics from PCF (Pivotal Cloud Foundry) platform. We send that as time-series data to Cortex via a Prometheus server and built a dashboard using Grafana. There is another pipeline where we need to read metrics from a Linux server using Metricbeat, CPU, memory, and Disk. That will be sent to Elasticsearch and Grafana will pull and show the data in a dashboard.

Is it OK to use Metricbeat for Linux server or can we use Prometheus?

What is the difference in system metrics sent by Metricbeat and Prometheus node exporters?

Regards, Sunil.

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Comments

Detailed Comparison

Telegraf	Metricbeat
It is an agent for collecting, processing, aggregating, and writing metrics. 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.	Collect metrics from your systems and services. From CPU to memory, Redis to NGINX, and much more, It is a lightweight way to send system and service statistics.
-	System-Level Monitoring; system-level CPU usage statistics; Network IO statistics
Statistics
GitHub Stars 16.4K	GitHub Stars -
GitHub Forks 5.7K	GitHub Forks -
Stacks 290	Stacks 48
Followers 321	Followers 125
Votes 16	Votes 3
Pros & Cons
Pros 5 One agent can work as multiple exporter with min hndlng 5 Cohesioned stack for monitoring 2 Metrics 2 Open Source 1 Many hundreds of plugins	Pros 2 Simple 1 Easy to setup
Integrations
No integrations available	Redis Linux NGINX Windows

What are some alternatives to Telegraf, Metricbeat?

Grafana

Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.

Kibana

Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

Prometheus

Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

Netdata

Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps

Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

Sensu

Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.

Graphite

Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand

Lumigo

Lumigo is an observability platform built for developers, unifying distributed tracing with payload data, log management, and real-time metrics to help you deeply understand and troubleshoot your systems.

StatsD

It is a network daemon that runs on the Node.js platform and listens for statistics, like counters and timers, sent over UDP or TCP and sends aggregates to one or more pluggable backend services (e.g., Graphite).

Related Comparisons

Metricbeat vs Telegraf: What are the differences?

Data Collection: Metricbeat primarily focuses on collecting metrics from various systems and services, while Telegraf is more versatile in that it can collect metrics as well as log data, making it a more comprehensive monitoring tool.
Data Shipper Options: Metricbeat is native to the Elastic Stack, making it a seamless choice for users of this ecosystem, whereas Telegraf offers a wider range of output options, including databases, messaging systems, and cloud services, providing more flexibility in data export.
Plugin Ecosystem: Telegraf has a vast library of plugins for collecting data from different sources, enabling users to quickly set up monitoring for various services, whereas Metricbeat has a more limited set of modules focused on specific metrics collection purposes.
Resource Utilization: Metricbeat is known for its lightweight nature, consuming minimal system resources and having lower network bandwidth usage compared to Telegraf, which can be advantageous in resource-constrained environments.
Configuration and Management: Telegraf offers more advanced configuration options, including the ability to define complex processing pipelines and routing rules, while Metricbeat provides a simpler, more user-friendly configuration setup suitable for beginners or those requiring streamlined monitoring.
Community Support: Both Metricbeat and Telegraf have strong communities, but Telegraf's community-driven development approach and active plugin contributions lead to faster updates and a broader range of features compared to Metricbeat.

In Summary, Metricbeat is ideal for basic metric monitoring within the Elastic Stack, while Telegraf offers a more versatile solution for gathering metrics and log data from a variety of sources.

Metricbeat vs Telegraf

Overview