January 2018
Beginner to intermediate
234 pages
7h 8m
Chinese
Content preview from Kafka权威指南
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监控
Kafka
｜
173
在这些指标和属性中，哪些对于监控来说是比较重要的？我们至少要收集
Total Time
和
Requests Per Second
的平均值及较高的百分位（
99%
或
99.9%
），这样就可以获知发送请求
的整体性能。如果有可能，尽量为每一种请求类型收集其他
6
种时间度量指标，这样就可
以将性能问题细分到请求的各个阶段。
为时间度量指标设定告警阈值有一定的难度。例如，fetch 请求时间受各种因素的影响，
包括客户端等待消息的时间、主题的繁忙程度，以及客户端和
broker
之间的网络连接速
度。不过，对于 Produce 请求来说，可以为
Total Time
设定
99.9%
百分位度量基线值。
与非同步分区类似，Produce 请求的
99.9%
百分位数值快速增长说明出现了大规模的性
能问题。
10.2.3
主题和分区的度量指标
broker
的度量指标描述了
broker
的一般行为，除此之外，还有很多主题实例和分区实例的
度量指标。在大型的集群里，这样的度量指标会有很多，一般情况下，不太可能将它们
全部收集到一个度量指标系统里。不过，我们可以用它们来调试与客户端相关的问题。例
如，主题的度量指标可以用于识别出造成集群流量大量增长的主题。我们需要提供这些度
量指标，这样
Kafka
的生产者和消费者就可以使用它们。不管是否会收集这些度量指标，
都有必要知道它们的用处。
表
10-12
中所列的度量指标将使用主题名称“
TOPICNAME
”，分区
ID
为
0
。在实际中，
要把主题名称和分区
ID
替换成自己的名称和
ID
。
1. ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.