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## Data model

Prometheus implements a highly dimensional data model. Time series are identified by a metric name and a set of key-value pairs.

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## Query language

A flexible query language allows slicing and dicing of collected time series data in order to generate ad-hoc graphs, tables, and alerts.

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## Visualization

Prometheus has multiple modes for visualizing data: a built-in expression browser, a GUI-based dashboard builder, and a console template language.

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## Storage

Prometheus stores time series in memory and on local disk in an efficient custom format. Scaling is achieved by functional sharding and federation.

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## Operation

Each server is independent for reliability, relying only on local storage. Written in Go, all binaries are statically linked and easy to deploy.

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## Client libraries

Client libraries allow easy instrumentation of services. Currently, Go, Java, and Ruby are supported. Custom libraries are easy to implement.

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## Alerting

Alerts are defined based on Prometheus's flexible query language and maintain dimensional information. An alertmanager handles notifications and silencing.

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## Exporters

Existing exporters allow bridging of third-party data into Prometheus. Examples: system statistics, as well as Docker, HAProxy, StatsD, and JMX metrics.

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