The Prometheus support, dashboards and sample alerting rules do not only work with Kafka brokers. There are different ways to configure the JMX Exporter.Īnd while you are of course free to configure it according to your needs, it is important to follow our configuration if you want to use our dashboards and alerting rules. This section configures the JMX exporter and tells it how the JMX metrics should be converted to the Prometheus metrics. To enable the JMX Exporter in Strimzi, you have to specify the metrics section in the Strimzi Kafka, KafkaConnect and KafkaConnectS2I custom resources. ![]() To help with that, we use the Prometheus JMX Exporter project which takes the JMX metrics and exposes them as Prometheus endpoint.Īpart from integrating the JMX Exporter we also provide Grafana dashboards and sample Prometheus alerting rules which you can use and adapt to your own needs. Like many JVM based applications it uses JMX (Java Management Extensions) for exposing metrics.īut since our aim in the Strimzi project is to offer a Kubernetes-native experience when running Apache Kafka, we want to have the metrics exposed as a Prometheus endpoint. Apache Kafka and PrometheusĪpache Kafka doesn’t support Prometheus metrics natively by default. You can have your alerts sent to many different notification channels such as emails, Slack, PagerDuty and more. It will handle duplicates, silencing, inhibition and aggregation of alerts and send out notification to your system of choice. Prometheus will evaluate the rules against the metrics which it is scraping and when any of the rules is matched, it will send it to Alertmanager.Īlertmanager will be then responsible for managing these alerts. You can configure rules which should trigger alerts. Prometheus can also be used for alerting. One of the tools supporting it is Grafana, which can be used to visualize the data from the Prometheus database. The PromQL language is an API which other applications can use to query the metrics. Once the metrics are stored in the database, you can query them using the PromQL query language. There are many tools and libraries which make it easy for you to create the Prometheus endpoint in your application.Ĭheck the Instrumenting section of the Prometheus documentation to learn more about how to expose Prometheus metrics from your application. The interface from which Prometheus scrapes these data is a simple HTTP endpoint providing a text output with the metrics. Instead, Prometheus will scrape (collect) metrics from you applications and store them in its time-series database. Unlike many other monitoring systems, with Prometheus your applications do not have to push the metrics to Prometheus. Prometheus is an open source monitoring solution which has become the de-facto standard for metrics and alerting in the cloud native world. Kafka Exporter adds some additional metrics that are missing in Kafka brokers. ![]() Strimzi has supported Prometheus for Kafka metrics almost since the beginning.īut in 0.14.0 we have made some major improvements by adding support for the Kafka Exporter tool. We also have some significant improvements to Prometheus monitoring. 实际上,Collector.In our previous blog post we focused on tracing which was one of the new features in our 0.14.0 release.īut tracing is not the only improvement to the monitoring capabilities we did in 0.14.0. *** ASSERTION FAILED ***: "result" with message agent load/premain call failed at src/java.instrument/share/native/libinstrument/JPLISAgent.c line: 422įATAL ERROR in native method: processing of -javaagent failed, processJavaStart failed 复制 Uid=1000(appuser) gid=1000(appuser) groups=1000(appuser)Įxception in thread "main" Īt java.base/.invoke0(Native Method)Īt java.base/.invoke(NativeMethodAccessorImpl.java:62)Īt java.base/.invoke(DelegatingMethodAccessorImpl.java:43)Īt java.base/.invoke(Method.java:566)Īt java.instrument/(InstrumentationImpl.java:513)Īt java.instrument/(InstrumentationImpl.java:525)Ĭaused by: : UNKNOWNĪt io.$Rule.(JmxCollector.java:57)Īt io.(JmxCollector.java:214)Īt io.(JmxCollector.java:91)Īt io.(JavaAgent.java:29) PS D:\env\confluent-platform> docker logs connect -f
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