Prometheus icon
Prometheus icon

Prometheus

 40 likes

Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. Since its inception in 2012, many companies and organizations have adopted Prometheus, and the project has a very active developer and user community.

Prometheus screenshot 1

License model

  • FreeOpen Source

Country of Origin

  • International

Platforms

  • Mac
  • Windows
  • Linux
  • Cloudron
  • Docker Hub
4.5 / 5 Avg rating (2)
40likes
2comments
0news articles

Features

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  1.  Performance Monitoring
  2.  Hardware Monitoring
  3.  Log storage
  4.  Metrics
  5.  Data monitoring

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Prometheus information

  • Developed by

    Prometheus Authors
  • Licensing

    Open Source and Free product.
  • Rating

    Average rating of 4.5
  • Alternatives

    67 alternatives listed
  • Supported Languages

    • English

AlternativeTo Categories

Network & AdminOS & UtilitiesSystem & Hardware

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Our users have written 2 comments and reviews about Prometheus, and it has gotten 40 likes

Prometheus was added to AlternativeTo by AlternativeSteve on May 12, 2016 and this page was last updated May 11, 2025.

Comments and Reviews

   
 Post comment/review
Top Positive Comment
GFBatmgN
Mar 20, 2023
0

Simple. Fast. Scales fantastically. Lots of support. Not good for keeping historical data. No downsampling. Only good for real time data, seek other time series databases if you want to store with a specific timestamp.

csaltos
Jul 1, 2020
0

A really good product, simple, powerful, the best metrics tool ... and ... open source free !!

What is Prometheus?

Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud. Since its inception in 2012, many companies and organizations have adopted Prometheus, and the project has a very active developer and user community. It is now a standalone open source project and maintained independently of any company.

Prometheus's main features are:

  • A multi-dimensional data model (time series identified by metric name and key/value pairs).
  • A flexible query language to leverage this dimensionality.
  • No reliance on distributed storage; single server nodes are autonomous.
  • Time series collection happens via a pull model over HTTP.
  • Pushing time series is supported via an intermediary gateway.
  • Targets are discovered via service discovery or static configuration.
  • Multiple modes of graphing and dashboarding support.

Official Links