Prometheus icon
Prometheus icon

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.

Prometheus screenshot 1

Cost / License

  • Free
  • Open Source

Platforms

  • Mac
  • Windows
  • Linux
  • Cloudron
  • Docker Hub
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No reviews
40likes
2comments
0news articles

Features

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

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Prometheus information

  • Developed by

    Prometheus Authors
  • Licensing

    Open Source and Free product.
  • Alternatives

    70 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 and this page was last updated .

Comments and Reviews

   
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GFBatmgN
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.

Review by a new / low-activity user.
csaltos
0

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

Review by a new / low-activity user.

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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