Prometheus vs Zabbix
May 18, 2023 | Author: Michael Stromann
Prometheus and Zabbix are both popular monitoring systems used to track the performance and health of IT infrastructure, but they differ in their approach and capabilities. Prometheus is an open-source monitoring and alerting toolkit that specializes in collecting time-series data. It offers a flexible and scalable solution, allowing users to monitor and analyze metrics from a wide range of sources. Prometheus has a powerful querying language and a robust ecosystem of exporters and integrations. On the other hand, Zabbix is a comprehensive enterprise-level monitoring platform that provides monitoring, alerting, and visualization capabilities. It offers a centralized management system with features like auto-discovery, network monitoring, and distributed monitoring options. Zabbix is known for its extensive out-of-the-box monitoring templates and comprehensive reporting capabilities.
See also: Top 10 IT Monitoring software
See also: Top 10 IT Monitoring software
Prometheus vs Zabbix in our news:
2019. Zabbix 4.2 adds built-in support of Prometheus data collection
Zabbix Team has recently unveiled the launch of Zabbix 4.2. This latest version introduces a comprehensive monitoring system equipped with cutting-edge features, including data collection and processing, distributed monitoring, real-time problem and anomaly detection, alerting and escalations, visualization, and more. Zabbix 4.2 significantly enhances data collection capabilities, supporting diverse methods such as push and pull from various sources like JMX, SNMP, WMI, HTTP/HTTPS, RestAPI, XML Soap, SSH, Telnet, agents, scripts, and more. Notably, the integration with Prometheus has been added as a new feature, allowing native support for the PromQL language. Additionally, the utilization of dependent metrics empowers the Zabbix team to efficiently gather a vast amount of Prometheus metrics. By making a single HTTP call, all the required data can be retrieved and subsequently reused for relevant dependent metrics.