Open Source Integration
GroundWork Monitor integrates several open-source solutions into its platform.
For years the standard for system and network monitoring tools, Nagios™ is a significant block of the GroundWork Monitor suite.
Based on a fork of Nagios, Icinga 2 is an updated, streamlined, and modern enhancement that allows automated configuration and information harvesting with GroundWork Monitor.
A favorite of network administrators worldwide, Cacti™ provides a performance graphing engine ideal for data visualization with RRDtool. Groundwork uses SPINE, an enhanced SNMP poller, with Cacti to feed monitoring data to GroundWork Monitor installations, and Cacti to generate customized graphs.
Designed as a storage-neutral (never-growing) repository for time series data, RRDTool gives GroundWork a reliable place to store, age out, and graph the performance data from Nagios and other sources.
A component of the GroundWork Logbridge™ this tool provides a lightning fast storage engine for event-based data.
A component of the GroundWork Logbridge™ this tool provides a robust query engine for event-based data.
Long a favorite of administrators of clustered high-performance computing systems, Ganglia acts as a fast, efficient, compiled agent for gathering monitoring data. GroundWork taps into the Ganglia data stream to provide monitoring and alerting in the GroundWork Monitor unified console.
Designed as a web application testing tool, Selenium allows for the repeatable execution of scripted browser operations. As such it is an ideal tool for monitoring web applications, and reporting the performance from an end-user perspective.
A robust, storage-efficient data store for time series metrics, OpenTSDB has begun to be used as a standard back-end for monitoring tools. GroundWork uses it to store performance data in original detail (unsummarized), from multiple sources.
A hybrid of Kibana and Graphite, Grafana offers a powerful query engine and comparative graphing interface. GroundWork uses Grafana as a presentation layer for performance data analysis.