Grafana vs Nagios: What are the differences?
Grafana: Open source Graphite & InfluxDB Dashboard and Graph Editor. 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; Nagios: Complete monitoring and alerting for servers, switches, applications, and services. Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.
Grafana and Nagios belong to "Monitoring Tools" category of the tech stack.
Some of the features offered by Grafana are:
- Create, edit, save & search dashboards
- Change column spans and row heights
- Drag and drop panels to rearrange
On the other hand, Nagios provides the following key features:
- Monitor your entire IT infrastructure
- Spot problems before they occur
- Know immediately when problems arise
"Beautiful" is the primary reason why developers consider Grafana over the competitors, whereas "It just works" was stated as the key factor in picking Nagios.
Grafana and Nagios are both open source tools. It seems that Grafana with 29.7K GitHub stars and 5.63K forks on GitHub has more adoption than Nagios with 60 GitHub stars and 36 GitHub forks.
Uber Technologies, 9GAG, and Harvest are some of the popular companies that use Grafana, whereas Nagios is used by Uber Technologies, Dropbox, and 9GAG. Grafana has a broader approval, being mentioned in 577 company stacks & 325 developers stacks; compared to Nagios, which is listed in 177 company stacks and 40 developer stacks.
I learned a lot from Grafana, especially the issue of data monitoring, as it is easy to use, I learned how to create quick and simple dashboards. InfluxDB, I didn't know any other types of DBMS, I only knew about relational DBMS or not, but the difference was the scalability of both, but with influxDB, I knew how a time series DBMS works and finally, Telegraf, which is from the same company as InfluxDB, as I used the Windows Operating System, Telegraf tools was the first in the industry, in addition, it has complete documentation, facilitating its use, I learned a lot about connections, without having to make scripts to collect the data.
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.
- free open source
- modern interface and architecture
- large community
- extendable I knew Nagios for decades but it was really outdated (by its architecture) at some point. That's why Icinga started first as a fork, not with Icinga2 it is completely built from scratch but backward-compatible with Nagios plugins. Now it has reached a state with which I am confident.
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