Prometheus

Prometheus, a Cloud Native Computing Foundation project, is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.

Prometheus’ main distinguishing features as compared to other monitoring systems are:

• a multi-dimensional data model (timeseries defined by metric name and set of key/value dimensions)
• a flexible query language to leverage this dimensionality
• no dependency on distributed storage; single server nodes are autonomous
• timeseries collection happens via a pull model over HTTP
• pushing timeseries is supported via an intermediary gateway
• targets are discovered via service discovery or static configuration
• multiple modes of graphing and dashboarding support
• support for hierarchical and horizontal federation

Feature

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
PromQL 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 PromQL 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.

Changelog v2.14

• [SECURITY/BUGFIX] UI: Ensure warnings from the API are escaped. #6279
• [FEATURE] API: /api/v1/status/runtimeinfo and /api/v1/status/buildinfo endpoints added for use by the React UI. #6243
• [FEATURE] React UI: implement the new experimental React based UI. #5694 and many more
  • Can be found by under /new.
  • Not all pages are implemented yet.
• [FEATURE] Status: Cardinality statistics added to the Runtime & Build Information page. #6125
• [ENHANCEMENT/BUGFIX] Remote write: fix delays in remote write after a compaction. #6021
• [ENHANCEMENT] UI: Alerts can be filtered by state. #5758
• [BUGFIX] API: lifecycle endpoints return 403 when not enabled. #6057
• [BUGFIX] Build: Fix Solaris build. #6149
• [BUGFIX] Promtool: Remove false duplicate rule warnings when checking rule files with alerts. #6270
• [BUGFIX] Remote write: restore use of deduplicating logger in remote write. #6113
• [BUGFIX] Remote write: do not reshard when unable to send samples. #6111
• [BUGFIX] Service discovery: errors are no longer logged on context cancellation. #6116, #6133
• [BUGFIX] UI: handle null response from API properly. #6071

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© Prometheus Authors 2014-2019