Prometheus

Example list:

• 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.