Shinken vs collectd

Overview

collectd

Stacks98

Followers156

Votes5

GitHub Stars3.3K

Forks1.3K

Shinken

Stacks17

Followers39

Votes0

collectd vs Shinken: What are the differences?

Developers describe collectd as "System and applications metrics collector". collectd gathers statistics about the system it is running on and stores this information. Those statistics can then be used to find current performance bottlenecks (i.e. performance analysis) and predict future system load (i.e. capacity planning). Or if you just want pretty graphs of your private server and are fed up with some homegrown solution you're at the right place, too. On the other hand, Shinken is detailed as "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.

collectd and Shinken can be categorized as "Monitoring" tools.

Some of the features offered by collectd are:

fast
simple
integrated

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

collectd and Shinken are both open source tools. It seems that collectd with 2.26K GitHub stars and 1.08K forks on GitHub has more adoption than Shinken with 1.08K GitHub stars and 355 GitHub forks.

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Advice on collectd, Shinken

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.

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Detailed Comparison

collectd	Shinken
collectd gathers statistics about the system it is running on and stores this information. Those statistics can then be used to find current performance bottlenecks (i.e. performance analysis) and predict future system load (i.e. capacity planning). Or if you just want pretty graphs of your private server and are fed up with some homegrown solution you're at the right place, too.	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.
fast;simple;integrated;easy to operate	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; Plugins provide great flexibility and are a big legacy codebase to use. It would be a shame not to use all this community work Multi-platform : python is available in a lot of OS. We try to write generic code to keep this possible; Utf8 compliant : python is here to do that. For now Shinken is compatible with 2.6-2.7 version but python 3.X is even more character encoding friendly; Independent from other monitoring solution : our goal is to provide a modular tool that can integrate with others through standard interfaces). Flexibility first; Flexible : in an architecture point view. It is very close to our scalability wish. Cloud computing is make architecture moving a lot, we have to fit to it; Fun to code : python ensure good code readability. Adding code should not be a pain when developing;
Statistics
GitHub Stars 3.3K	GitHub Stars -
GitHub Forks 1.3K	GitHub Forks -
Stacks 98	Stacks 17
Followers 156	Followers 39
Votes 5	Votes 0
Pros & Cons
Pros 2 Modular, plugins 2 Open Source 1 KISS	No community feedback yet
Integrations
No integrations available	Nagios

What are some alternatives to collectd, Shinken?

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

Some of the features offered by collectd are:

fast
simple
integrated

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

Shinken vs collectd