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Kafka消费者滞后监控可视化

[英]Kafka consumer lag monitoring visualization

I'm new to Kafka.我是卡夫卡的新手。 During study to kafka, I think monitoring consumer's lag is needed.在学习kafka的过程中,我认为需要监控消费者的滞后。 When I search from google and docs, I found few ways.当我从谷歌和文档搜索时,我发现了一些方法。

  1. Kafka - Prometheus - graphana卡夫卡-普罗米修斯-graphana
  2. kafka - burrow - someDB - graphana kafka - 洞穴 - someDB - graphana
  3. kafka - burrow_stat?(I can't understand what it is..) kafka - burrow_stat?(我不明白它是什么..)
  4. kafka - datadog what I want to ask is document says that burrow is for monitoring, can I visualize like graph(dashboard)? kafka - datadog 我想问的是文件说洞穴是用于监控的,我可以像图形(仪表板)一样可视化吗? without other tools like graphana or kibana or datadog??没有其他工具,如 graphana 或 kibana 或 datadog ?

I just trying to get less pipeline steps.我只是想减少管道步骤。 What should be the simple way to visualize consumer's lag?可视化消费者滞后的简单方法应该是什么?

If you are doing the setup in an organisation, datadog or prometheus is probably the way to go.如果您在组织中进行设置,datadog 或 prometheus 可能是 go 的方式。 You can capture other Kafka related metrics as well.您也可以捕获其他与 Kafka 相关的指标。 These agents also have integrations with many other tools beside Kafka and will be a good common choice for monitoring.这些代理还与 Kafka 之外的许多其他工具集成,将成为监控的一个很好的常见选择。

If you are just doing it for personal POC type of a project and you just want to view the lag, I find CMAK very useful ( https://github.com/yahoo/CMAK ).如果您只是为项目的个人 POC 类型而做,并且只想查看滞后,我发现 CMAK 非常有用( https://github.com/yahoo/CMAK )。 This does not have historical data, but provides a good current visual state of Kafka cluster including lag.没有历史数据,但提供了包括滞后在内的 Kafka 集群当前良好的可视化 state。

For cluster wide metrics you can use kafka_exporter ( https://github.com/danielqsj/kafka_exporter ) which exposes some very useful cluster metrics(including consumer lag) and is easy to integrate with prometheus and visualize using grafana.对于集群范围的指标,您可以使用 kafka_exporter ( https://github.com/danielqsj/kafka_exporter ),它公开了一些非常有用的集群指标(包括消费者滞后),并且易于与 prometheus 集成并使用 grafana 进行可视化。

Burrow is extremely effective and specialised in monitoring consumer lag.Burrow is good at caliberating consumer offset and more importantly validate if the lag is malicious or not. Burrow 非常有效,专门用于监控消费者滞后。Burrow 擅长校准消费者偏移,更重要的是验证滞后是否是恶意的。 It has integrations with pagerduty so that the alerts are pushed to the necessary parties.它与 pagerduty 集成,以便将警报推送给必要的各方。

https://community.cloudera.com/t5/Community-Articles/Monitoring-Kafka-with-Burrow-Part-1/ta-p/245987 https://community.cloudera.com/t5/Community-Articles/Monitoring-Kafka-with-Burrow-Part-1/ta-p/245987

What burrow has:洞穴有什么:

  • Non-threshold based lag monitoring algorithm capable to evaluate potential slow downs.基于非阈值的滞后监控算法能够评估潜在的减速。
  • Integration with pagerduty与 pagerduty 集成
  • Exporters for prometheus, AppD etc for historical metrics用于历史指标的 prometheus、AppD 等的导出器
  • Pluggable UI可插拔用户界面

If you are looking for quick solution you can deploy burrow followed by the burrow front end https://github.com/GeneralMills/BurrowUI如果您正在寻找快速解决方案,您可以部署 burrow,然后部署 burrow 前端https://github.com/GeneralMills/BurrowUI

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