[Cacti手册译文]Chapter 5. Principles of Operation{第5章.

[Cacti手册译文]--Chapter 5. Principles of Operation{第5章.运行原理}

(源自：杨志刚 博客 http://yangzhigang.cublog.cn)

 

注：因本人英语水平是相当的一般，所以希望有误之处，请谅解，指正。只是希望对想了解和学习cacti的人有些许的帮助，有转载请指明“(源自：杨志刚 博客 http://yangzhigang.cublog.cn)”。

 

Chapter 5. Principles of Operation{第5章.运行原理}
Cacti operation may be divided into three different tasks:{Cacti的原理可以分为三个不同的任务：}

 

5.1. Data Retrieval{数据撷取}
First task is to retrieve data. Cacti will do so using its Poller. The Poller is executed from the operating system’s scheduler, e.g. crontab for Unix flavored OSes.
{首要任务是撷取数据，Cacti用其轮询器完成。轮询器是操作系统一个可可执行的计划任务，如类Unix操作系统的Crontab。}

In current IT installations, you’re dealing with lots of devices of different kind, e.g. servers, network equipment, appliances and the like. To retrieve data from remote targets/hosts, cacti will mainly use the Simple Network Management Protocol SNMP. Thus, all devices capable of using SNMP will be eligible to be monitored by cacti.
{在当前的IT安装环境，你可能要处理大量不同的设备，如服务器、网络设备、应用等等。要从远程目标/主机撷取数据，Cacti大体上主要用SNMP协议，因此，在被监控设备启用SNMP将是很合适的方式。}

Later on, we demonstrate how to extend cacti’s capabilities of retrieving data to scripts, script queries and more.
{稍后，我们展示如何扩展Cacti用脚本、脚本查询等撷取数据的能力。}

5.2. Data Storage{5.2 数据存储}
There are lots of different approaches for this task. Some may use an (SQL) database, others flat files. Cacti uses RRDTool 1 to store data.
{对于这个任务有大量不同的途径实现。有些用SQL数据库，其它扁平的文件，Cacti是用RRDTool来存储数据的。}

RRD is the acronym for Round Robin Database. RRD is a system to store and display time-series data (i.e. network
bandwidth, machine-room temperature, server load average). It stores the data in a very compact way that will not
expand over time, and it can create beautiful graphs. This keeps storage requirements at bay.
{RRD是环形数据库的缩写。RRD是存储和显示时间序列数据的一个系统（如网络带宽、操作间温度、服务器负载）。RRD是简洁存储数据的方法，随着时间的变化而不用进行扩展，并且它可以创建美丽迷人的图形。这可以保证存储需求。}

Likewise, rrdtool will perform some specific tasks. It performs consolidation to combine raw data (a primary data point in rrdtool lingo) to consolidated data (a consolidated data point). This way, historical data is compressed to save space. rrdtool knows different consolidation functions: AVERAGE, MAXIMUM, MINIMUM and LAST.
{同样的，rrdtool将完成一些特定任务。它对原始数据（在rrdtool术语中一个原始数据点）进行合并，形成合并数据（一个合并数据点）。这点办法，历史数据将被压缩以节省空间。Rrdtool知道不同的合并功能：平均值、最大值、最小值和最后数值。}

5.3. Data Presentation{5.3数据呈现}
One of the most appreciated features of RRDTool 2 is the built-in graphing function. This comes in useful when combining this with some commonly used webserver. Such, it is possible to access the graphs from merely any browser
on any plattform.
{RRDTool很让人欣赏特征之一就是内建图形功能。当结合一些Web服务器时，这很有用，这样一来，可以在任何平台的浏览器上访问浏览这些图形。}

Graphing can be done in very different ways. It is possible, to graph one or many items in one graph. Autoscaling is supported and logarithmic y-axis as well. You may stack items onto another and print pretty legends denoting characteristics such as minimum, average, maximum and lots more.
{有很不同的方法来完成绘图，在一个图形中，可能有一个或多个数据项。支持自动调整大小实现很好的Y轴坐标，你可以将一此数据项堆叠到另一个之上，并且很好的表示如最小、平均、最大等等的数据图例。}

Notes{说明}
{关于RRDTool的相关内容可以参看以下URL：}
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