What is Checkmk?
It is a software developed for IT Infrastructure monitoring. It is used for the monitoring of servers, applications, networks, cloud infrastructures, containers, storage, databases and environment sensors.
Checkmk is a tool in the Monitoring Tools category of a tech stack.
Who uses Checkmk?
3 companies reportedly use Checkmk in their tech stacks, including Big Data Services, Interhyp AG, and DevOps.
6 developers on StackShare have stated that they use Checkmk.
nginx, Docker, Java, MySQL, and PostgreSQL are some of the popular tools that integrate with Checkmk. Here's a list of all 19 tools that integrate with Checkmk.
Why developers like Checkmk?
Here’s a list of reasons why companies and developers use Checkmk
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- State-based monitoring
- Log- and event-based monitoring
- Graphing and analytics
- Customizable GUI
- Business Intelligence
- Hardware and software inventory
- Notifications and alert handler
- Rule-based configuration, auto-discovery and agent deployment
Checkmk Alternatives & Comparisons
What are some alternatives to Checkmk?
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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.
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.
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 is a host/service/network monitoring program written in C and released under the GNU General Public License.
Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand