As a built-in data query language of Prometheus, Prometheus Query Language (PromQL) can be used to query, aggregate, and perform logical operations on time series data. PromQL is widely used in the daily application scenarios of Prometheus, including data query, visualization, and alert handling. PromQL is also prevalent in monitoring systems built around Prometheus, where it filters data stored in databases. In actual application scenarios, PromQL is indispensable in Grafana dashboard configuration, recording rule configuration, and alerting and monitoring configuration. PromQL has the following characteristics:

Multidimensional query: PromQL supports multidimensional queries, which enable you to organize and filter your metric data by using multiple labels. This makes data analytics more flexible and fine-grained.

Built-in functions: PromQL offers many built-in functions, such as sum, average, and count, which can be used to easily process and aggregate metric data.

Visualization: PromQL can easily generate visual charts, which makes data analytics more intuitive and comprehensible.

tip

This topic briefly introduces the basic knowledge of PromQL, such as the glossary, metric types, basic usage, and commonly used query metrics of PromQL. As a supplement to the official documentation, this topic is used to help you quickly get started with PromQL. If you need to know more details about PromQL, it is recommended that you read the official documentation.

Last updated: 2026.07.10 11:37:29

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