= Metrics

This project implements the Vert.x Metrics Service Provider Interface (SPI) reporting metrics to the
https://github.com/dropwizard/metrics[Dropwizard metrics] library.

== Features

A fairly simple API to retrieve metrics via the `link:../../scaladocs/io/vertx/scala/core/metrics/Measured.html[Measured]`
interface which is implemented by various Vert.x components like `link:../../scaladocs/io/vertx/scala/core/http/HttpServer.html[HttpServer]`,
`link:../../scaladocs/io/vertx/scala/core/net/NetServer.html[NetServer]`, and even `link:../../scaladocs/io/vertx/scala/core/Vertx.html[Vertx]` itself.

Configurable JMX reporting based on Dropwizard implementation, exposing Vert.x as JMX MBeans.

== Getting started

To enable metrics, add the following dependency to the _dependencies_ section of your build descriptor:

* Maven (in your `pom.xml`):

[source,xml,subs="+attributes"]
----
<dependency>
 <groupId>io.vertx</groupId>
 <artifactId>vertx-dropwizard-metrics</artifactId>
 <version>${maven.version}</version>
</dependency>
----

* Gradle (in your `build.gradle` file):

[source,groovy,subs="+attributes"]
----
compile 'io.vertx:vertx-dropwizard-metrics:${maven.version}'
----

Then when you create vertx enable metrics using the `link:../dataobjects.html#DropwizardMetricsOptions[DropwizardMetricsOptions]`:

[source,scala]
----
var vertx = Vertx.vertx(VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setEnabled(true)
  )
)

----

You can also enable JMX:

[source,scala]
----
var vertx = Vertx.vertx(VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setJmxEnabled(true)
  )
)

----

To see details about JMX see the <<jmx>> section at the bottom.

== Command line activation

When running Vert.x from the command line interface, metrics can be activated via JVM system properties. System
properties beginning with _vertx.metrics.options._ are transmitted to the metrics options.

The _vertx.metrics.options.enabled_ is a standard Vert.x Core option for enabling the metrics implementations, this
options must be set to `true`:

----
java -jar your-fat-jar -Dvertx.metrics.options.enabled=true
----

The `link:../dataobjects.html#DropwizardMetricsOptions#setRegistryName()[vertx.metrics.options.registryName]`
configures the <<dropwizard-registry,Dropwizard Registry>> to use:

----
java -jar your-fat-jar -Dvertx.metrics.options.enabled=true -Dvertx.metrics.options.registryName=my-registry
----

The `link:../dataobjects.html#DropwizardMetricsOptions#setJmxEnabled()[vertx.metrics.options.jmxEnabled]` and
`link:../dataobjects.html#DropwizardMetricsOptions#setJmxDomain()[vertx.metrics.options.jmxDomain]`
configures the <<jmx,JMX>> registration:

----
java -jar your-fat-jar -Dvertx.metrics.options.enabled=true -Dvertx.metrics.options.jmxEnabled=true ...
----

The `link:../dataobjects.html#DropwizardMetricsOptions#setConfigPath()[vertx.metrics.options.configPath]`
option allows to reconfigure the metrics from a property file.

== Metrics service

While Vert.x core defines an SPI for reporting metrics (implemented for instance in this project), it does not define
an API for retrieving metrics (because some metrics collectors just do reporting and nothing more).

The `link:../../scaladocs/io/vertx/scala/ext/dropwizard/MetricsService.html[MetricsService]` provides an API in front of the Dropwizard Registry to get
metrics data snapshots.

=== Naming

Each measured component listed below (except for Vertx) will have a base name associated with it. Each metric
can be retrieved by providing the fully qualified name <fqn> `baseName` + `.` + `metricName` from Vertx:

[source,scala]
----
var metrics = metricsService.getMetricsSnapshot(vertx)
metrics.getValue("vertx.eventbus.handlers")

----

or from the measured component itself using just the metric name:

[source,scala]
----
var eventBus = vertx.eventBus()
var metrics = metricsService.getMetricsSnapshot(eventBus)
metrics.getValue("handlers")

----

See more examples below on how to retrieve/use metrics for a specific component.

Metrics names can also be listed:

[source,scala]
----
var metricsNames = metricsService.metricsNames()
metricsNames.foreach(metricsName => {
  println(s"Known metrics name ${metricsName}")
})


----

`baseName` defaults to `vertx`, but can be set to a custom value:

[source,scala]
----
var metricsOptions = DropwizardMetricsOptions()
  .setBaseName("foo")


----

=== Retrieving metrics

Once enabled, the `link:../../scaladocs/io/vertx/scala/ext/dropwizard/MetricsService.html[MetricsService]` allows to retrieve metrics snapshots from any
`link:../../scaladocs/io/vertx/scala/core/metrics/Measured.html[Measured]` object which provides a map of the metric name to the data,
represented by a `JsonObject`. So for example if we were to print out all metrics
for a particular Vert.x instance:
[source,scala]
----
var metricsService = MetricsService.create(vertx)
var metrics = metricsService.getMetricsSnapshot(vertx)
println(metrics)

----

NOTE: For details on the actual contents of the data (the actual metric) represented by the `JsonObject`
consult the implementation documentation like https://github.com/vert-x3/vertx-metrics[vertx-metrics]

Often it is desired that you only want to capture specific metrics for a particular component, like an http server
without having to know the details of the naming scheme of every metric (something which is left to the implementers of the SPI).

Since `link:../../scaladocs/io/vertx/scala/core/http/HttpServer.html[HttpServer]` implements `link:../../scaladocs/io/vertx/scala/core/metrics/Measured.html[Measured]`, you can easily grab all metrics
that are specific for that particular http server.

[source,scala]
----
var metricsService = MetricsService.create(vertx)
var server = vertx.createHttpServer()
// set up server
var metrics = metricsService.getMetricsSnapshot(server)

----

Metrics can also be retrieved using a base name:

[source,scala]
----
var metricsService = MetricsService.create(vertx)
var metrics = metricsService.getMetricsSnapshot("vertx.eventbus.message")

----

== Data

Below is how each dropwizard metric is represented in JSON. Please refer to the
https://github.com/dropwizard/metrics[Dropwizard metrics] documentation for detailed information on each metric.

[[gauge]]
=== Gauge

[source,javascript]
----
{
 "type"  : "gauge",
 "value" : value // any json value
}
----

[[counter]]
=== Counter

[source,scala]
----
{
 "type"  : "counter",
 "count" : 1 // number
}
----

[[histogram]]
=== Histogram

[source,javascript]
----
{
 "type"   : "histogram",
 "count"  : 1 // long
 "min"    : 1 // long
 "max"    : 1 // long
 "mean"   : 1.0 // double
 "stddev" : 1.0 // double
 "median" : 1.0 // double
 "75%"    : 1.0 // double
 "95%"    : 1.0 // double
 "98%"    : 1.0 // double
 "99%"    : 1.0 // double
 "99.9%"  : 1.0 // double
}
----

[[meter]]
=== Meter

[source,scala]
----
{
 "type"              : "meter",
 "count"             : 1 // long
 "meanRate"          : 1.0 // double
 "oneMinuteRate"     : 1.0 // double
 "fiveMinuteRate"    : 1.0 // double
 "fifteenMinuteRate" : 1.0 // double
 "rate"              : "events/second" // string representing rate
}
----

[[throughput_meter]]
=== ThroughputMeter

Extends a <<meter>> to provide an instant throughput.

[source,scala]
----
{
 "type"              : "meter",
 "count"             : 40 // long
 "meanRate"          : 2.0 // double
 "oneSecondRate"     : 3 // long - number of occurence for the last second
 "oneMinuteRate"     : 1.0 // double
 "fiveMinuteRate"    : 1.0 // double
 "fifteenMinuteRate" : 1.0 // double
 "rate"              : "events/second" // string representing rate
}
----

[[timer]]
=== Timer

A timer is basically a combination of Histogram + Meter.

[source,scala]
----
{
 "type": "timer",

 // histogram data
 "count"  : 1 // long
 "min"    : 1 // long
 "max"    : 1 // long
 "mean"   : 1.0 // double
 "stddev" : 1.0 // double
 "median" : 1.0 // double
 "75%"    : 1.0 // double
 "95%"    : 1.0 // double
 "98%"    : 1.0 // double
 "99%"    : 1.0 // double
 "99.9%"  : 1.0 // double

 // meter data
 "meanRate"          : 1.0 // double
 "oneMinuteRate"     : 1.0 // double
 "fiveMinuteRate"    : 1.0 // double
 "fifteenMinuteRate" : 1.0 // double
 "rate"              : "events/second" // string representing rate
}
----

[[throughput_timer]]
=== Throughput Timer

Extends a <<timer>> to provide an instant throughput metric.

[source,scala]
----
{
 "type": "timer",

 // histogram data
 "count"      : 1 // long
 "min"        : 1 // long
 "max"        : 1 // long
 "mean"       : 1.0 // double
 "stddev"     : 1.0 // double
 "median"     : 1.0 // double
 "75%"        : 1.0 // double
 "95%"        : 1.0 // double
 "98%"        : 1.0 // double
 "99%"        : 1.0 // double
 "99.9%"      : 1.0 // double

 // meter data
 "meanRate"          : 1.0 // double
 "oneSecondRate"     : 3 // long - number of occurence for the last second
 "oneMinuteRate"     : 1.0 // double
 "fiveMinuteRate"    : 1.0 // double
 "fifteenMinuteRate" : 1.0 // double
 "rate"              : "events/second" // string representing rate
}
----

== The metrics

The following metrics are currently provided.

=== Vert.x metrics

The following metrics are provided:

* `vertx.event-loop-size` - A <<gauge>> of the number of threads in the event loop pool
* `vertx.worker-pool-size` - A <<gauge>> of the number of threads in the worker pool
* `vertx.cluster-host` - A <<gauge>> of the cluster-host setting
* `vertx.cluster-port` - A <<gauge>> of the cluster-port setting
* `vertx.verticles` - A <<counter>> of the number of verticles currently deployed
* `vertx.verticles.<verticle-name>` - A <<counter>> of the number of deployment of a particular verticle

=== Event bus metrics

Base name: `vertx.eventbus`

* `handlers` - A <<counter>> of the number of event bus handlers
* `handlers.myaddress` - A <<timer>> representing the rate of which messages are being processed for the _myaddress_ handler
* `messages.bytes-read` - A <<meter>> of the number of bytes read when receiving remote messages
* `messages.bytes-written` - A <<meter>> of the number of bytes written when sending remote messages
* `messages.pending` - A <<counter>> of the number of messages received but not yet processed by an handler
* `messages.pending-local` - A <<counter>> of the number of messages locally received but not yet processed by an handler
* `messages.pending-remote` - A <<counter>> of the number of messages remotely received but not yet processed by an handler
* `messages.discarded` - A <<counter>> of the number of messages discarded by an handler
* `messages.discarded-local` - A <<counter>> of the number of messages locally discarded by an handler
* `messages.discarded-remote` - A <<counter>> of the number of messages remotely discarded by an handler
* `messages.received` - A <<throughput_meter>> representing the rate of which messages are being received
* `messages.received-local` - A <<throughput_meter>> representing the rate of which local messages are being received
* `messages.received-remote` - A <<throughput_meter>> representing the rate of which remote messages are being received
* `messages.delivered` - A <<throughput_meter>> representing the rate of which messages are being delivered to an handler
* `messages.delivered-local` - A <<throughput_meter>> representing the rate of which local messages are being delivered to an handler
* `messages.delivered-remote` - A <<throughput_meter>> representing the rate of which remote messages are being delivered to an handler
* `messages.sent` - A <<throughput_metert>> representing the rate of which messages are being sent
* `messages.sent-local` - A <<throughput_meter>> representing the rate of which messages are being sent locally
* `messages.sent-remote` - A <<throughput_meter>> representing the rate of which messages are being sent remotely
* `messages.published` - A <<throughput_meter>> representing the rate of which messages are being published
* `messages.published-local` - A <<throughput_meter>> representing the rate of which messages are being published locally
* `messages.published-remote` - A <<throughput_meter>> representing the rate of which messages are being published remotely
* `messages.reply-failures` - A <<meter>> representing the rate of reply failures

The monitored event bus handlers is configurable via a match performed on the handler registration address.
Vert.x can have potentially a huge amount of registered event bus, therefore the only good default for this
setting is to monitor zero handlers.

The monitored handlers can be configured in the `link:../dataobjects.html#DropwizardMetricsOptions[DropwizardMetricsOptions]` via
a specific address match or a regex match:

[source,scala]
----
var vertx = Vertx.vertx(VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setEnabled(true)
    .setMonitoredEventBusHandlers(Set(Match()
      .setValue("some-address")
    , Match()
      .setValue("business-.*")
      .setType(MatchType.REGEX)
    ))
  )
)

----

WARNING: if you use regex match, a wrong regex can potentially match a lot of handlers.

[[http-server-metrics]]
=== Http server metrics

Base name: `vertx.http.servers.<host>:<port>`

Http server includes all the metrics of a <<net-server-metrics,Net Server>> plus the following:

* `requests` - A <<throughput_timer>> of a request and the rate of it's occurrence
* `<http-method>-requests` - A <<throughput_timer>> of a specific http method request and the rate of it's occurrence
** Examples: `get-requests`, `post-requests`
* `<http-method>-requests./<uri>` - A <<throughput_timer>> of a specific http method & URI request and the rate of it's occurrence
** Examples: `get-requests./some/uri`, `post-requests./some/uri?foo=bar`
* `responses-1xx` - A <<throughput_meter>> of the 1xx response code
* `responses-2xx` - A <<throughput_meter>> of the 2xx response code
* `responses-3xx` - A <<throughput_meter>> of the 3xx response code
* `responses-4xx` - A <<throughput_meter>> of the 4xx response code
* `responses-5xx` - A <<throughput_meter>> of the 5xx response code
* `open-websockets` - A <<counter>> of the number of open web socket connections
* `open-websockets.<remote-host>` - A <<counter>> of the number of open web socket connections for a particular remote host

Http URI metrics must be explicitly configured in the options either by exact match or regex match:

[source,scala]
----
var vertx = Vertx.vertx(VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setEnabled(true)
    .setMonitoredHttpServerUris(Set(Match()
      .setValue("/")
    , Match()
      .setValue("/foo/.*")
      .setType(MatchType.REGEX)
    ))
  )
)

----

In case if the uri contains some path parameters like `/users/:userId` it might not make sense to have a separate entry in the registry for each user
id (like `get-requests./users/1`, `get-requests./users/2` and so on) but a summarized one. To achieve that you can set an alias to the match instance
in this case the alias will be used as a part of the registry name instead of uri like `<http-method>-requests.<alias>`.
In addition there will be separate counters for each response group for each defined alias like `responses-<code>.<alias>`.

[source,scala]
----
var vertx = Vertx.vertx(VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setEnabled(true)
    .setMonitoredHttpServerUris(Set(Match()
      .setValue("/users/.*")
      .setAlias("users")
      .setType(MatchType.REGEX)
    ))
  )
)

----

*For `bytes-read` and `bytes-written` the bytes represent the body of the request/response, so headers, etc are ignored.*

=== Http client metrics

Base name: `vertx.http.clients` (by default) or `vertx.http.clients.<id>` where `<id>` is a non empty string
configured by `link:../../vertx-core/dataobjects.html#HttpClientOptions#setMetricsName()[metricsName]`.

Http client includes all the metrics of a <<http-server-metrics,Http Server>> plus the following:

* `connections.max-pool-size` - A <<gauge>> of the max connection pool size
* `connections.pool-ratio` - A ratio <<gauge>> of the open connections / max connection pool size
* `responses-1xx` - A <<meter>> of the 1xx response code
* `responses-2xx` - A <<meter>> of the 2xx response code
* `responses-3xx` - A <<meter>> of the 3xx response code
* `responses-4xx` - A <<meter>> of the 4xx response code
* `responses-5xx` - A <<meter>> of the 5xx response code

The http client manages a pool of connection for each remote endpoint with a queue of pending requests

Endpoint metrics are available too:

* `endpoint.<host:port>.queue-delay` - A <<timer>> of the wait time of a pending request in the queue
* `endpoint.<host:port>.queue-size` - A <<counter>> of the actual queue size
* `endpoint.<host:port>.open-netsockets` - A <<counter>> of the actual number of open sockets to the endpoint
* `endpoint.<host:port>.usage` - A <<timer>> of the delay between the request starts and the response ends
* `endpoint.<host:port>.in-use` - A <<counter>> of the actual number of request/response
* `endpoint.<host:port>.ttfb` - A <<timer>> of the wait time between the request ended and its response begins

where <host> is the endpoint host name possibly unresolved and <port> the TCP port.

The monitored endpoints are configurable via a match performed on the server `$host:$port`.
The default for this setting is to monitor no endpoints.

The monitored endpoints can be configured in the `link:../dataobjects.html#DropwizardMetricsOptions[DropwizardMetricsOptions]` via
a specific hostname match or a regex match:

[source,scala]
----
var vertx = Vertx.vertx(VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setEnabled(true)
    .setMonitoredHttpClientEndpoints(Set(Match()
      .setValue("some-host:80")
    , Match()
      .setValue("another-host:.*")
      .setType(MatchType.REGEX)
    ))
  )
)

----

[[net-server-metrics]]
=== Net server metrics

Base name: `vertx.net.servers.<host>:<port>`

* `open-netsockets` - A <<counter>> of the number of open net socket connections
* `open-netsockets.<remote-host>` - A <<counter>> of the number of open net socket connections for a particular remote host
* `connections` - A <<timer>> of a connection and the rate of it's occurrence
* `exceptions` - A <<counter>> of the number of exceptions
* `bytes-read` - A <<histogram>> of the number of bytes read.
* `bytes-written` - A <<histogram>> of the number of bytes written.

=== Net client metrics

Base name: `vertx.net.clients` (by default) or `vertx.net.clients.<id>` where `<id>` is a non empty string
configured by `link:../../vertx-core/dataobjects.html#NetClientOptions#setMetricsName()[metricsName]`.

Net client includes all the metrics of a <<net-server-metrics,Net Server>>

=== Datagram socket metrics

Base name: `vertx.datagram`

* `sockets` - A <<counter>> of the number of datagram sockets
* `exceptions` - A <<counter>> of the number of exceptions
* `bytes-written` - A <<histogram>> of the number of bytes written.
* `<host>:<port>.bytes-read` - A <<histogram>> of the number of bytes read.
** This metric will only be available if the datagram socket is listening

=== Pool metrics

Base name: `vertx.pools.<type>.<name>` where `type` is the type of the pool (e.g _worker_, _datasource_) and
`name` is the name of the pool (e.g `vert.x-worker-thread`).

Pools of type _worker_ are blocking worker pools. Vert.x exposes its worker as _vert.x-worker-thread_ and
_vert.x-internal-blocking_. Named worker executor created with `link:../../scaladocs/io/vertx/scala/core/WorkerExecutor.html[WorkerExecutor]` are exposed.

Datasource created with Vert.x JDBC clients are exposed as _datasource_.

* `queue-delay` - A <<timer>> measuring the duration of the delay to obtain the resource, i.e the wait time in the queue
* `queue-size` - A <<counter>> of the actual number of waiters in the queue
* `usage` - A <<timer>> measuring the duration of the usage of the resource
* `in-use` - A <<count>> of the actual number of resources used
* `pool-ratio` - A ratio <<gauge>> of the in use resource / pool size
* `max-pool-size` - A <<gauge>> of the max pool size

The `pool-ratio` and the `max_pool_size` won't be present when the measured pool's max pool size could not
be determined.

[[jmx]]
== JMX

JMX is disabled by default.

If you want JMX, then you need to enabled that:

[source,scala]
----
var vertx = Vertx.vertx(VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setJmxEnabled(true)
  )
)

----

If running Vert.x from the command line you can enable metrics and JMX by uncommented the JMX_OPTS line in the
`vertx` or `vertx.bat` script:

----
JMX_OPTS="-Dcom.sun.management.jmxremote -Dvertx.metrics.options.jmxEnabled=true"
----

You can configure the domain under which the MBeans will be created:

[source,scala]
----
var vertx = Vertx.vertx(VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setJmxEnabled(true)
    .setJmxDomain("mydomain")
  )
)

----

In the command line, just append the following system properties to your application (works for the `vertx` cli and
fat jars):

[source]
----
-Dvertx.metrics.options.jmxEnabled=true -Dvertx.metrics.options.jmxDomain=vertx
----

== Enabling remote JMX

If you want the metrics to be exposed remotely over JMX, then you need to set, at minimum the following system property:

`com.sun.management.jmxremote`

If running from the command line this can be done by editing the `vertx` or `vertx.bat` and uncommenting the
`JMX_OPTS` line.

Please see the http://docs.oracle.com/javase/8/docs/technotes/guides/management/agent.html[Oracle JMX documentation] for more information on configuring JMX

*If running Vert.x on a public server please be careful about exposing remote JMX access*

[[dropwizard-registry]]
== Accessing Dropwizard Registry

When configuring the metrics service, an optional registry name can be specified for registering the underlying
https://dropwizard.github.io/metrics/3.1.0/getting-started/#the-registry[Dropwizard Registry] in the
the https://dropwizard.github.io/metrics/3.1.0/apidocs/com/codahale/metrics/SharedMetricRegistries.html[Dropwizard Shared Registry]
so you can retrieve this registry and use according to your needs.

[source,scala]
----
var options = VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setEnabled(true)
    .setRegistryName("my-registry")
  )

var vertx = Vertx.vertx(options)
// Get the registry
var registry = com.codahale.metrics.SharedMetricRegistries.getOrCreate("my-registry")
// Do whatever you need with the registry
}
----

== Using already existing Dropwizard Registry
Optionally, it is possible to utilize already existing https://dropwizard.github.io/metrics/3.1.0/getting-started/#the-registry[Dropwizard Registry].
In order to do so pass `MetricRegistry` instance as parameter for `setMetricRegistry` function in `VertxOptions` object.

[source,java]
----
MetricRegistry metricRegistry = new MetricRegistry();
VertxOptions options = new VertxOptions().setMetricsOptions(
   new DropwizardMetricsOptions().setEnabled(true).setMetricRegistry(metricRegistry)
);
Vertx vertx = Vertx.vertx(options);
----

== Using Jolokia and Hawtio

https://jolokia.org/[Jolokia] is a JMX-HTTP bridge giving an alternative to JSR-160 connectors. It is an agent based
approach with support for many platforms. In addition to basic JMX operations it enhances JMX remoting with features
like bulk requests.

http://hawt.io/[Hawtio] is a modular web console consuming the data exposed by Jolokia. It lets you create dashboards
and retrieve data from JMX such as memory, cpu, or any vert.x metrics.

This section explains how to configure your vert.x application to retrieve the metrics in Hawtio.

First, you need to configure your vert.x instance with the following options:

[source,scala]
----
var vertx = Vertx.vertx(VertxOptions()
  .setMetricsOptions(DropwizardMetricsOptions()
    .setEnabled(true)
    .setJmxEnabled(true)
    .setJmxDomain("vertx-metrics")
  )
)

----

You can change the domain to whatever you want. The same configuration can be used for clustered Vert.x instances.
This configuration instructs vertx-dropwizard-metrics to expose the metrics in the local MBean server, so
Jolokia can retrieve them.

Then you need, to _plug_ jolokia to expose the data. There are several ways to _plug_ jolokia. See
https://jolokia.org/reference/html/architecture.html[for further details]. Here, we explain how to use the
Jolokia agent with the default configuration. Refer to the https://jolokia.org/reference/html/[the jolokia
documentation] to configure it.

The agent can either be attached when you start the application or attached on a running JVM (you would need
special permission to access the process). In the first case, launch you application using:

[source]
----
java -javaagent:/.../agents/jolokia-jvm.jar=port=7777,host=localhost -jar ...
----

The `-javaagent` specifies the path to the jolokia agent jar file. You can configure the port and host from the
command line. Here it registers the REST endpoint on `http://localhost:7777`.

You can also attach the agent on a running JVM with:

[source]
----
java -jar jolokia-jvm.jar start PID
----

Replace `PID` with the process id of the JVM.

Once Jolokia is configured and launched, you can consume the data from Hawtio.

On Hawtio, enter the connection details as follows:

image::../../images/hawtio-connect.png[]

Then, you can go to the _JMX_ tab and you should find a _directory_ with the name you entered as JMX domain
in the Vert.x configuration:

image::../../images/hawtio-jmx.png[]

From this, you can configure your dashboard and retrieve any metric exposed by vert.x.

== Using Jolokia and JMX4Perl to expose metrics to Nagios

http://search.cpan.org/~roland/jmx4perl/scripts/check_jmx4perl[Check_jmx4perl] is a Nagios plugin using jmx4perl for
accessing JMX data remotely. It lets you expose the Vert.x metrics to Nagios.

First you need to start your application with the Jolokia JVM agent attached to it. There are several ways to
attach jolokia. See https://jolokia.org/reference/html/architecture.html[for further details]. Here, we explain how
to use the Jolokia agent with the default configuration. Refer to the https://jolokia.org/reference/html/[the jolokia
documentation] to configure it.

The agent can either be attached when you start the application or attached on a running JVM (you would need
special permission to access the process). In the first case, launch you application using:

[source]
----
java -javaagent:/.../agents/jolokia-jvm.jar=port=7777,host=localhost -jar ...
----

The `-javaagent` specifies the path to the jolokia agent jar file. You can configure the port and host from the
command line. Here it registers the REST endpoint on `http://localhost:7777`.

You can also attach the agent on a running JVM with:

[source]
----
java -jar jolokia-jvm.jar start PID
----

Replace `PID` with the process id of the JVM.

Once Jolokia is started, you can configure your Nagios check such as:

[source]
----
check_jmx4perl --url http://10.0.2.2:8778/jolokia --name eventloops --mbean vertx:name=vertx.event-loop-size
--attribute Value --warning 4
----

Check http://search.cpan.org/~roland/jmx4perl/scripts/check_jmx4perl[check_jmx4perl documentation] to get more
details about check configuration.

== Metrics commands via Telnet or SSH in Vert.x Shell service

To find out the available metrics commands you can use the _help_ builtin command:

* Available commands
.. metrics-ls: List the known metrics for the current Vert.x instance
.. metrics-info: Show metrics info for the current Vert.x instance in JSON format
.. metrics-histogram: Show histogram metrics table for the current Vert.x instance in real time