【prometheus介绍】

Prometheus 是由 SoundCloud 开源监控告警解决方案。

prometheus

prometheus存储的是时序数据，即按相同时序(相同名称和标签)，以时间维度存储连续的数据的集合。

时序(time series)是由名字(Metric)以及一组key/value标签定义的，具有相同的名字以及标签属于相同时序。

• metric名字：表示metric的功能，如http_request_total。时序的名字由 ASCII 字符，数字，下划线，以及冒号组成，它必须满足正则表达式 [a-zA-Z_:][a-zA-Z0-9_:]*, 其名字应该具有语义化，一般表示一个可以度量的指标，例如 http_requests_total, 可以表示 http 请求的总数。

• 标签：

• 样本：按照某个时序以时间维度采集的数据，称之为样本。实际的时间序列，每个序列包括一个float64的值和一个毫秒级的时间戳

  • 一个 float64 值

  • 一个毫秒级的 unix 时间戳

• 格式：Prometheus时序格式与OpenTSDB相似：

 

 

 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.