See how Prometheus works and what you can do with it.
Prometheus fundamentally stores all data as time series: streams of timestamped values belonging to the same metric and the same set of labeled dimensions. Besides stored time series, Prometheus may generate temporary derived time series as the result of queries.
Prometheus provides a functional query language called PromQL (Prometheus Query Language) that lets the user select and aggregate time series data in real time. The result of an expression can either be shown as a graph, viewed as tabular data in Prometheus's expression browser, or consumed by external systems via the HTTP API.
Grafana supports querying Prometheus. The Grafana data source for Prometheus is included since Grafana 2.5.0 (2015-10-28). The following shows an example Grafana dashboard which queries Prometheus for data:
Prometheus is configured via command-line flags and a configuration file. While the command-line flags configure immutable system parameters (such as storage locations, amount of data to keep on disk and in memory, etc.), the configuration file defines everything related to scraping jobs and their instances, as well as which rule files to load.
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