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Prometheus collects data in the form of time series. The time series are built through a pull model: the Prometheus server queries a list of data sources (sometimes called exporters) at a specific polling frequency. Each of the data sources serves the current values of the metrics for that data source at the endpoint queried by Prometheus.
The company was founded in 1976 as Prometheus Software Development in Sydney, Australia. [3] [4] Originally trading under the name 'Prometheus Software', the company was sold to Sausage Software in 1999. [3] The name was then changed to 'Pronto Software' following a management buyout in 2002. [3]
The software automatically discovers hosts or network devices it is connected to. Agentless The product does not rely on a software agent that must run on hosts it is monitoring, so that data can be pushed back to a central server. "Supported" means that an agent may be used, but is not mandatory. An SNMP daemon does not count as an agent. SNMP
(Reuters) - Oil major BP's former CEO Bernard Looney is set to chair Prometheus Hyperscale, the U.S.-based data company said on Sunday. Looney, who resigned in 2023 after four years in the British ...
Free and open-source software portal; Grafana is a multi-platform open source analytics and interactive visualization web application.It can produce charts, graphs, and alerts for the web when connected to supported data sources.
The commercial Checkmk editions use their own metric and graphing system. Time series metrics can be analysed over long intervals using interactive HTML5 graphs. The maximum resolution is one second. Data can be imported from a variety of data sources and metrics formats (JSON, XML, SNMP etc.) and stored on the disk of a long-term data storage ...
Water Resource Specialist. The average salary for a water resource specialist is $157,740 per year. And the Bureau of Labor Statistics (BLS) estimates 8% job growth, which is much higher than average.
Since metrics are cardinality-limited, they are often used to represent aggregate values (for example: average page load time, or 5-second average of the request rate). Without external context, it is impossible to correlate between events (such as user requests) and distinct metric values.