Kapacitor

2019-11-24 本文已影响0人酱油王0901

Kapacitor

为什么要使用`Kapacitor`?

Action-oriented
- Kapacitor的告警系统是遵循publish-subscribe设计模式。Alerts能publish到相应的topcis，而handlers来subsribe相应的topic。
Streaming analytics
Anomaly detection

Introduction

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Kapacitor是一个实时的流数据处理引擎。
Kapacitor可以实时地通过TICK脚本处理InfluxDB中的流数据以及批处理数据。

数据处理模型
- Kapacitor是一种处理时间序列数据的框架，它遵循基于工作流的编程模型(flow based programing model)。数据流从一个node到另一个node，每个node是一个黑盒的过程，它能以任意方式处理数据。nodes是以有向无环图(directed acyclic graph)的方式分布的。
- Tasks
  - Task是通过TICK脚本来定义的。
  - Task有三种状态：
    - disabled
    - enabled not executing
    - enabled executing
Data Flow
- 传输数据的数据模型有两种: batch data takes multiple data points as an input and looks at them as a whole. Streams accept a single point at a time, folding each new point into the mix and re-evaluating thresholds each time.
  - Stream
    - Data points are passed as single entities.
    - 数据立即被transfer，并且每次只transfer一个data point
  - Batch
    - Data points are passed in groups of data.
    - 将多个data points看作一个整体输入
- data point
  - data point由时间戳timestamp，一系列的属性fileds和tags组成。
- Edges
  - 数据传输通过有向无环图的边来进行，从parent node到child node。
  - Edge是有类型的，指定的边只传输指定的类型。

Componets

Server Daemon (kapacitord)
- ● Config for inputs/outputs/services/ etc.
CLI (kapacitor)
- ● Calls for HTTP API or server
- ● Not interactive
Tasks - units of work
- ● Defined by a TICKscript
- ● Stream or Batch
- ● DAG - pipeline
Recordings - saved data
- ● Useful for isolated testing
Templates -
- ● Building many instances of a templated task
Topics & topics handlers
- ● Generic rules for all alters

References

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