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h1. Connecting to Petals JMX Luckily Prometheus maintains [jmx_exporter|https://github.com/prometheus/jmx_exporter] which exposes metrics on HTTP. It can either act as a java agent injected into the [JVM|https://en.wikipedia.org/wiki/Java_virtual_machine] during Petals ESB startup or an independent server connecting to Petals ESB by [RMI|https://en.wikipedia.org/wiki/Java_remote_method_invocation].
h2. Installing jmx_exporter as java agent :
...{code}
* Add the following line to *petals-esb.sh*, just before the “_exec_” command at the very end of the script. If necessary, change the version number to match the jar file you downloaded. _8585_ is the port number on which HTTP metrics will be exposed (once gathered by the jmx_exporter), set is as you see fit.{code}JAVA_OPTS="$JAVA_OPTS -javaagent:${PETALS_LIB_DIR}/jmx_prometheus_javaagent-0.3.1.jar=8585:${PETALS_CONF_DIR}/prometheus-jmx.yaml"{code}
* Add the following line to *petals-esb.sh*, just before the “_exec_” command at the very end of the script. If necessary, change the version number to match the jar file you downloaded. _8585_ is the port number on which HTTP metrics will be exposed (once gathered by the jmx_exporter), set is as you see fit.{code}JAVA_OPTS="$JAVA_OPTS -javaagent:${PETALS_LIB_DIR}/jmx_prometheus_javaagent-0.3.1.jar=8585:${PETALS_CONF_DIR}/prometheus-jmx.yaml"{code}
* Run _petals-esb.sh_
* Metrics are available at *[http://localhost:8585/metrics|http://localhost:8484/metrics*]*
* Metrics are available at *[http://localhost:8585/metrics|http://localhost:8484/metrics*]*
h3. Alternate jmx_exporter install: as HTTP server
* Download [jmx_prometheus_httpserver|https://mvnrepository.com/artifact/io.prometheus.jmx/jmx_prometheus_httpserver]. Be careful about the confusing version number, check the date to have the last version.
* Adapt the *prometheus-jmx.yaml* config file to connect by RMI. You can use either *jmxUrl* or *hostPort*, *username* and *password* are mandatory. {code}
startDelaySeconds: 0
# jmxUrl: service:jmx:rmi:///jndi/rmi://localhost:7700/PetalsJMX
hostPort: localhost:7700
username: petals
password: petals
rules:
- pattern: ".*"
{code}
* Start the server, with the exposition HTTP *ip:port* and config file as argument : {code}java \-jar jmx_prometheus_httpserver-0.3.1-jar-with-dependencies.jar localhost:8585 prometheus-jmx.yaml{code}
* Adapt the *prometheus-jmx.yaml* config file to connect by RMI. You can use either *jmxUrl* or *hostPort*, *username* and *password* are mandatory. {code}
startDelaySeconds: 0
# jmxUrl: service:jmx:rmi:///jndi/rmi://localhost:7700/PetalsJMX
hostPort: localhost:7700
username: petals
password: petals
rules:
- pattern: ".*"
{code}
* Start the server, with the exposition HTTP *ip:port* and config file as argument : {code}java \-jar jmx_prometheus_httpserver-0.3.1-jar-with-dependencies.jar localhost:8585 prometheus-jmx.yaml{code}
h2. Install Prometheus
...Note that :
* Only *numeric values* are supported by Prometheus (though string can me interpreted as regexp to extract numeric values)
* Custom and complex objects may not be exported by the exporter, *having ‘\- pattern “.*”’ as only rule will return every metric available\* (useful for testing).
* Container MBeans are all typed as Map, so are ignored by the jmx agent. To have
* Petals ESB container MBeans metrics are all typed as Map, so are ignored by the jmx agent. As is, *you can monitor some components metrics but cannot monitor container metrics with Prometheus.*
* Rules order is important: Eventually, a *a single MBean is processed by a single rule*\! To decide which rule is applied: MBeans will be parsed by each rule (in order) until a pattern matches, then this rule is applied to the MBean. In other words, all rules are tested against each MBean the first one to match is kept for the MBean. So very specific rules should be put first, and generic/default rules last.
* Prometheus can make extensive use of *labels* through queries to determine *metrics* sources. Think about your needs when designing your labels, more explanations on [the official documentation|https://prometheus.io/docs/concepts/data_model/] or [this blog post.|https://pierrevincent.github.io/2017/12/prometheus-blog-series-part-1-metrics-and-labels/]
* Metrics can be typed (conceptually, as gauge, counter or histogram) for Prometheus to know how to handle them. More details on the [official documentation|https://prometheus.io/docs/concepts/metric_types/].
* Metrics can be typed (conceptually, as gauge, counter or histogram) for Prometheus to know how to handle them. More details on the [official documentation|https://prometheus.io/docs/concepts/metric_types/].
Rule samples :
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