Get up to speed with Prometheus, the metrics-based monitoring system used by tens of thousands of organizations in production. This practical guide provides application developers, sysadmins, and DevOps practitioners with a hands-on introduction to the most important aspects of Prometheus, including infrastructure and application monitoring, dashboarding and alerting, direct co...
Get up to speed with Prometheus, the metrics-based monitoring system used by tens of thousands of organizations in production. This practical guide provides application developers, sysadmins, and DevOps practitioners with a hands-on introduction to the most important aspects of Prometheus, including infrastructure and application monitoring, dashboarding and alerting, direct code instrumentation, and metric collection from third-party systems with exporters.
This open source system has gained popularity over the past few years for good reason. With its simple yet powerful data model and query language, Prometheus does one thing, and it does it well. Author and Prometheus developer Brian Brazil guides you through Prometheus setup, the Node exporter, and the Alertmanager, then demonstrates how to use them for application and infrastructure monitoring.
Know where and how much to apply instrumentation to your application code
Identify metrics with labels using unique key-value pairs
Get an introduction to Grafana, a popular tool for building dashboards
Learn how to use the Node Exporter to monitor your infrastructure
Use service discovery to provide different views of your machines and services
Use Prometheus with Kubernetes and examine exporters you can use with containers
Convert data from other monitoring systems into the Prometheus format
原文摘录
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* You should try to follow the metric name practices, in particular, avoiding the _count, _sum, _total, _bucket and _info suffixes unless the time series is part of a metric that is meant to contain such a time series.
* if a metric is a counter, don't forget to add the _total suffix.
* Where practical you should try to provide units for your metrics, and at the very least try to ensure that units are in the metric name... Seconds and bytes are always prefered.
* Labels should create a partition across a metric, and if you take a sum or average across a metric should be meaningful.
* As with direct instrumentation, you should not apply a label such as env="prod" to all metrics coming from your exporter, as that's what target labels are for .
* It's best to expose raw metrics to Promet... (查看原文)
黄小虎
中国电力出版社2020版
0 有用 吴叶磊 2022-03-31 21:38:51
若干年前的入门书
0 有用 稻谷的谷 2022-08-28 13:31:37 广东
读这本书是为了用 Prometheus 在系统中增加 metric。所以没有完全读完，重点在前 12 章。在内容中，很好地从 metric 系统到 Prometheus 进行了介绍，再到如何使用 Prometheus ，是非常好的入门书籍。另外，其中有作者很多的经验。直到现在搜索 Prometheus 相关的内容，很多也是去到作者的博客中。
0 有用 玉面飞龙 2019-07-17 03:23:36
从入门到精通了
0 有用 detailyang 2019-01-26 15:02:58
前几章意义比较有用
0 有用 执迷不悟 2019-10-31 16:12:14
不错的入门书，很全面，示范语言是python.对于大部分人来说，前几章节就够用了
0 有用 稻谷的谷 2022-08-28 13:31:37 广东
读这本书是为了用 Prometheus 在系统中增加 metric。所以没有完全读完，重点在前 12 章。在内容中，很好地从 metric 系统到 Prometheus 进行了介绍，再到如何使用 Prometheus ，是非常好的入门书籍。另外，其中有作者很多的经验。直到现在搜索 Prometheus 相关的内容，很多也是去到作者的博客中。
0 有用 Sarkar 2022-06-29 15:41:46
虽然是18年写的入门书，但还是很实用，尤其是当你不想直接啃官方文档的时候。
0 有用 吴叶磊 2022-03-31 21:38:51
若干年前的入门书
0 有用 iCoolSea 2021-06-16 17:36:59
第一本读完的英文原版书（严格说80%主要内容）。中规中矩，覆盖面广，适合入门
0 有用 猪蹄儿 2021-01-04 01:15:21
市面上关于Prometheus最值得看的书 没有废话