Nagios vs Shinken: What are the differences?
What is 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.
What is Shinken? Nagios compatible monitoring framework, written in Python. Shinken's main goal is to give users a flexible architecture for their monitoring system that is designed to scale to large environments. Shinken is backwards-compatible with the Nagios configuration standard and plugins. It works on any operating system and architecture that supports Python, which includes Windows, GNU/Linux and FreeBSD.
Nagios and Shinken belong to "Monitoring Tools" category of the tech stack.
Some of the features offered by Nagios are:
- Monitor your entire IT infrastructure
- Spot problems before they occur
- Know immediately when problems arise
On the other hand, Shinken provides the following key features:
- Easy to install : install is mainly done with pip but some packages are available (deb / rpm) and we are planning to provide nightly build
- Easy for new users : once installed, Shinken provide a simple command line interface to install new module and packs
- Easy to migrate from Nagios : we want Nagios configuration and plugins to work in Shinken so that it is a “in place” replacement
Nagios and Shinken are both open source tools. Shinken with 1.08K GitHub stars and 355 forks on GitHub appears to be more popular than Nagios with 60 GitHub stars and 36 GitHub forks.
Uber Technologies, Dropbox, and 9GAG are some of the popular companies that use Nagios, whereas Shinken is used by In Sun We Trust, Koolicar, and Flock. Nagios has a broader approval, being mentioned in 177 company stacks & 40 developers stacks; compared to Shinken, which is listed in 3 company stacks and 3 developer stacks.
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Why we spent several years building an open source, large-scale metrics alerting system, M3, built for Prometheus:
By late 2014, all services, infrastructure, and servers at Uber emitted metrics to a Graphite stack that stored them using the Whisper file format in a sharded Carbon cluster. We used Grafana for dashboarding and Nagios for alerting, issuing Graphite threshold checks via source-controlled scripts. While this worked for a while, expanding the Carbon cluster required a manual resharding process and, due to lack of replication, any single node’s disk failure caused permanent loss of its associated metrics. In short, this solution was not able to meet our needs as the company continued to grow.
To ensure the scalability of Uber’s metrics backend, we decided to build out a system that provided fault tolerant metrics ingestion, storage, and querying as a managed platform...
(GitHub : https://github.com/m3db/m3)
We use Nagios to monitor our stack and alert us when problems arise. Nagios allows us to monitor every aspect of each of our servers such as running processes, CPU usage, disk usage, and more. This means that as soon as problems arise, we can detect them and call out an engineer to resolve the issues as soon as possible.
We use Nagios to monitor customer instances of Bridge and proactively alert us about issues like queue sizes, downed services, errors in logs, etc.
We use nagios based OpsView to monitor our server farm and keep everything running smoothly.