Overview

Nagios

Stacks828

Followers1.1K

Votes102

GitHub Stars57

Forks38

Grafana

Stacks18.4K

Followers14.6K

Votes415

GitHub Stars70.7K

Forks13.1K

Grafana vs Nagios: What are the differences?

Introduction:

Grafana and Nagios are both popular monitoring tools used in the IT industry. However, they differ in several key aspects that make them suitable for different use cases. The following are the key differences between Grafana and Nagios.

Data Visualization and Dashboarding: Grafana is primarily focused on data visualization and creating interactive dashboards. It provides a wide range of graphing options, charts, and widgets to represent data in a visually appealing manner. On the other hand, Nagios is more focused on monitoring and alerting, with limited options for data visualization.
Plug-in Ecosystem: Grafana has an extensive plug-in ecosystem that allows users to extend its functionality. Users can create custom data sources, panels, and apps to integrate with various data systems and services. Nagios, on the other hand, has a more limited plug-in ecosystem, which may require more effort for customization and integration.
Supported Monitoring Protocols: Nagios is known for its extensive support for monitoring protocols, including SNMP, NRPE, and others. It can monitor a wide range of devices and services using these protocols. Grafana, on the other hand, primarily relies on data sources that provide metrics in a compatible format, such as Prometheus, InfluxDB, or Graphite.
Alerting and Notification: Nagios is well-known for its advanced alerting and notification capabilities. It supports complex alert rules, thresholds, and escalation methods, allowing users to define different levels of alert severity. Grafana, on the other hand, has basic alerting capabilities but relies more on integrations with external alerting tools such as Prometheus Alertmanager.
Ease of Use: Grafana provides a user-friendly interface and intuitive configuration options, making it easier for users to set up and manage. It offers a visual query builder and drag-and-drop dashboard editor, simplifying the process of creating dashboards. Nagios, on the other hand, has a steeper learning curve and requires more technical expertise to configure and customize.
Community and Support: Nagios has a strong and established community with extensive documentation, plugins, and user forums available for support. It has been widely used for years and has a large user base. Grafana, although newer compared to Nagios, also has a growing community and active support channels. However, it may not have the same level of maturity and extensive community resources as Nagios.

In summary, Grafana is more focused on data visualization and creating interactive dashboards, with a rich plug-in ecosystem and ease of use. Nagios, on the other hand, excels in monitoring protocols, alerting capabilities, and has a strong community support. The choice between the two depends on specific monitoring requirements and preferences of the users.

Advice on Nagios, Grafana

Matt

Senior Software Engineering Manager at PayIt

May 3, 2021

Decidedon

Grafana

Prometheus

Kubernetes

Grafana and Prometheus together, running on Kubernetes , is a powerful combination. These tools are cloud-native and offer a large community and easy integrations. At PayIt we're using exporting Java application metrics using a Dropwizard metrics exporter, and our Node.js services now use the prom-client npm library to serve metrics.

1.1M views1.1M

Comments

Leonardo Henrique da

Pleno QA Enginneer at SolarMarket

Dec 8, 2020

Decided

The objective of this work was to develop a system to monitor the materials of a production line using IoT technology. Currently, the process of monitoring and replacing parts depends on manual services. For this, load cells, microcontroller, Broker MQTT, Telegraf, InfluxDB, and Grafana were used. It was implemented in a workflow that had the function of collecting sensor data, storing it in a database, and visualizing it in the form of weight and quantity. With these developed solutions, he hopes to contribute to the logistics area, in the replacement and control of materials.

402k views402k

Comments

StackShare

Jun 25, 2019

Needs advice

From a StackShare Community member: “We need better analytics & insights into our Elasticsearch cluster. Grafana, which ships with advanced support for Elasticsearch, looks great but isn’t officially supported/endorsed by Elastic. Kibana, on the other hand, is made and supported by Elastic. I’m wondering what people suggest in this situation."

663k views663k

Comments

Detailed Comparison

Nagios	Grafana
Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.	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.
Monitor your entire IT infrastructure;Spot problems before they occur;Know immediately when problems arise;Share availability data with stakeholders;Detect security breaches;Plan and budget for IT upgrades;Reduce downtime and business losses	Create, edit, save & search dashboards;Change column spans and row heights;Drag and drop panels to rearrange;Use InfluxDB or Elasticsearch as dashboard storage;Import & export dashboard (json file);Import dashboard from Graphite;Templating
Statistics
GitHub Stars 57	GitHub Stars 70.7K
GitHub Forks 38	GitHub Forks 13.1K
Stacks 828	Stacks 18.4K
Followers 1.1K	Followers 14.6K
Votes 102	Votes 415
Pros & Cons
Pros 53 It just works 28 The standard 12 Customizable 8 The Most flexible monitoring system 1 Huge stack of free checks/plugins to choose from	Pros 89 Beautiful 68 Graphs are interactive 57 Free 56 Easy 34 Nicer than the Graphite web interface Cons 1 No interactive query builder
Integrations
No integrations available	Graphite InfluxDB

What are some alternatives to Nagios, Grafana?

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.

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).

Jaeger

Jaeger, a Distributed Tracing System

Telegraf

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.