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Web容量规划之美
book

Web容量规划之美

by Arun Kejariwal, John Allspaw
August 2019
Beginner to intermediate
232 pages
3h 50m
Chinese
China Electric Power Press Ltd.
Content preview from Web容量规划之美
146
4
困难,因为不是所有的瓶颈都很明显,而且你选中的度量指标会随着架构和硬件
承载能力的变化而变化。
在这个过程中,你可能注意到了季节性波动,大学秋季开学,可能有更多学生浏
览和他们学习相关的材料(或者只是为了避免去上课)。另一个示例,
11
月和
12
月的假期通常都是流量的高峰期,特别是对那些涉及零售的电商网站。在
Flickr
里,
这两种季节性影响我们都可以观察到。
显然这些季节性波动或节日波动应该是影响预测窗口宽窄的另一个因素。很明显,
你越频繁重新计算你的预测,你会准备得越好,而且你会更早注意到意外的波动。
对角线扩展时机
正如我们本章开始介绍的,容量预测需要两个基本信息:上限和历史数据。历史
数据是永久不变的,而上限则不是,每个上限都是和特定硬件配置对应的。性能
优化很有可能提高上限,但是升级更新的硬件和更好的技术也是一种选择。
正如我们在本书开始介绍的,新的技术(如多核处理器)能大大改变你能从单个
服务器中提升承载能力的多少。本章所示的预测过程不仅让你追踪在每个节点承
载能力上限的位置,还可以考虑架构中的哪些部分需要通过新增硬件来扩容。
小结
容量预测是一个持续的过程,它需要直觉和数学帮助你做出准确的预测。即使是
一个简单的
Web
应用程序也需要做容量预测,而且有些工作可能是非常乏味的。
尽可能多地自动化流程将有助于走在采购流程之前。花些时间建立度量指标收集
系统统计数据到趋势分析软件(如
cfityk
),这是非常有价值地,因为你开发了一
个很容易调整的容量规划。理想情况下,你想要某种容量仪表盘,并利用它在任
何时间及时通知进行采购、开发和业务决策。
容量预测的整体过程非常简单:
1.
确定、测量和绘制对每个资源定义的度量指标。
例如:
磁盘消耗。
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Publisher Resources

ISBN: 9787519831073