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# From metrics to insight

Power your metrics and alerting with a leading
open-source monitoring solution.

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Join us at PromCon in Munich on August 9 & 10, 2018 — CfP & tickets

## Dimensional data

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

## Powerful queries

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

## Great visualization

Prometheus has multiple modes for visualizing data: a built-in expression browser, Grafana integration, and a console template language.

## Efficient storage

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

## Simple operation

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

## Precise alerting

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

## Many client libraries

Client libraries allow easy instrumentation of services. Over ten languages are supported already and custom libraries are easy to implement.

## Many integrations

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

«Even though Borgmon remains internal to Google, the idea of treating time-series data as a data source for generating alerts is now accessible to everyone through those open source tools like Prometheus [...]»

— Site Reliability Engineering: How Google Runs Production Systems (O'Reilly Media)

# Open Source

Prometheus is 100% open source and community-driven. All components are available under the Apache 2 License on GitHub.

We are a Cloud Native Computing Foundation member project.

Some of our users include:
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