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数据库可靠性工程:数据库系统设计与运维指南
book

数据库可靠性工程:数据库系统设计与运维指南

by Laine Campbell, Charity Majors
November 2020
Beginner to intermediate
214 pages
5h 10m
Chinese
Posts & Telecom Press
Content preview from 数据库可靠性工程:数据库系统设计与运维指南
18
|
第
2
章
可用性
SLO
样例的迭代版本如下。
•
一周内的可用性为
99.9%
。
•
单次故障不超过
10.08
分钟。
•
如果超过
5%
的用户受影响,则视为宕机。
•
允许每年
4
小时的宕机时间,如果:
–
至少提前两周与用户沟通;
–
每次影响不超过
10%
的用户。
2.3.3
 吞吐量指标
作为服务级别指标,吞吐量应该列出服务必须能够支持的峰值,同时保持与其对应的延时
和可用性
SLO
。你可能会说:“莱恩和夏丽蒂,为什么还需要吞吐量指标呢?难道延时和
可用性还不够吗?”我们中的一个会这样回答:“无畏的新手,问得好!”然后她会若有
所思地吸起烟斗……
有时可能会出现瓶颈,给吞吐量设置了上限,但不至于影响性能或可用性。也许系统中存
在锁,限制系统每秒
50
个查询。这种响应可能很快,但是如果有
1000
人等待运行该查
询,就有问题了。因为有时无法测量端到端的延时,所以吞吐量指标通常可以作为系统是
否满足业务需求的一种额外验证。
当使用平均值和更粗粒度的样本时,吞吐量可能会遇到类似于延时的可见性问题,监控时
需要记住这一点。
1.
成本
/
效率指标
当考虑系统成本的有效指标时,最大的变量是采用什么指标来考量成本。这实际上是一个
业务决策,但是你应该选择在服务中驱动价值的因素。如果你是在线杂志之类的内容提供
者,那么交付的页面至关重要;如果你是软件即服务(
SaaS
)平台提供商,那么服务订阅
指标是有意义的;如果你是零售商,则交易量是合适的指标。
2.
注意事项
数据库工程师为什么需要知道这些?你管理的是服务的一个组件,为何必须关注整体需
求?在故障频发的日子里,可能已经为你设定了数据存储目标 ...
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Publisher Resources

ISBN: 9787115548863