Prometheus, a CNCF open-source project, is a service monitoring system founded in 2012 at CloudSound. It consists of monitoring, alerting, and a time-series database.
- Website
- https://prometheus.io[01]
- Source Code
- https://github.com/prometheus/prometheus[02]
- Developer
- Country of Origin
- DE
- Start Year
- 2012
- Project Type
- Open Source
- Written in
- Go
- Supported Languages
- Go
- License
- Apache v2
Prometheus' main features are:
- a user-defined multi-dimensional data model
- a powerful query language on multi-dimensional data (PromQL)
- time-series data are fetched through HTTP pull
- service discovery as well as static configuration
- visualization of metrics and dashboarding
Prometheus, a CNCF open-source project, is a service monitoring system founded in 2012 at CloudSound. It consists of monitoring, alerting, and a time-series database.
Prometheus' main features are:
- a user-defined multi-dimensional data model
- a powerful query language on multi-dimensional data (PromQL)
- time-series data are fetched through HTTP pull
- service discovery as well as static configuration
- visualization of metrics and dashboarding
History
- Nov 24, 2012: Prometheus was started at SoundCloud
- Jan 26, 2015: Public release as an open source project
- May 9, 2016: Joined Cloud Native Computing Foundation
- Jul 18, 2016: Prometheus released 1.0.0
- Aug 25, 2016: First Prometheus Conference at Berlin
- Nov 7, 2017: Prometheus released 2.0.0
Checkpoints[04]
Prometheus supports periodic checkpointing, which is done every two hours by default. Checkpointing in Prometheus is done by compacting segments in a given WAL. Therefore when Prometheus recovers from failure, it can replay the WAL to restore its status before crash.
Compression[05]
Prometheus has an efficient data compression format due to the fact that data samples in the same series often change very little. One of the compression algorithms that Prometheus uses is similar to that of Facebook's Gorilla time-series database, called delta-of-delta compression algorithm. Prometheus also has other customized compression algorithms.
With regard to integration with remote storage engines, Prometheus uses a snappy-compressed protocol buffer encoding over HTTP for both read and write protocols.
Concurrency Control[06]
Similar to many time-series databases, Prometheus is log-structured and is not designed for ACID transactions.
Citations
6 sources- Prometheus - Monitoring system & time series database prometheus.io
- GitHub - prometheus/prometheus: The Prometheus monitoring system and time series database. · GitHub github.com
- https://prometheus.io/docs/introduction/overview prometheus.io
- tsdb/checkpoint.go at master · prometheus-junkyard/tsdb · GitHub github.com
- http://www.vldb.org/pvldb/vol8/p1816-teller.pdf vldb.org
- https://prometheus.io/docs/prometheus/latest/storage prometheus.io