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Vert.x Micrometer Metrics

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This project is an implementation of the Vert.x Metrics Service Provider Interface (SPI). It uses Micrometer for managing metrics and reporting to several backends.

Features

  • Vert.x core tools monitoring: TCP/HTTP client and servers, DatagramSocket , EventBus and pools

  • User defined metrics through Micrometer

  • Reporting to any backend supported by Micrometer

  • Built-in options for InfluxDB, Prometheus and JMX reporting.

InfluxDB

Prerequisites

Follow the instructions to get InfluxDb up and running.

Getting started

The modules vertx-micrometer-metrics and micrometer-registry-influx must be present in the classpath.

Maven users should add this to their project POM file:

<dependency>
 <groupId>io.vertx</groupId>
 <artifactId>vertx-micrometer-metrics</artifactId>
 <version>3.6.2</version>
</dependency>
<dependency>
 <groupId>io.micrometer</groupId>
 <artifactId>micrometer-registry-influx</artifactId>
 <version>${micrometer.version}</version>
</dependency>

And Gradle users, to their build file:

compile 'io.vertx:vertx-micrometer-metrics:3.6.2'
compile 'io.micrometer:micrometer-registry-influx:${micrometer.version}'

Configuration examples

Vert.x does not enable SPI implementations by default. You must enable metric collection in the Vert.x options.

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    influxDbOptions = VertxInfluxDbOptions(
      enabled = true),
    enabled = true)))

Using a specific URI and database name

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    influxDbOptions = VertxInfluxDbOptions(
      enabled = true,
      uri = "http://influxdb.example.com:8888",
      db = "sales-department"),
    enabled = true)))

With authentication

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    influxDbOptions = VertxInfluxDbOptions(
      enabled = true,
      userName = "username",
      password = "password"),
    enabled = true)))

Prometheus

Prerequisites

Follow the instructions to get Prometheus up and running.

Getting started

The modules vertx-micrometer-metrics and micrometer-registry-prometheus must be present in the classpath. You may also probably need vertx-web, to expose the metrics.

Maven users should add this to their project POM file:

<dependency>
 <groupId>io.vertx</groupId>
 <artifactId>vertx-micrometer-metrics</artifactId>
 <version>3.6.2</version>
</dependency>
<dependency>
 <groupId>io.micrometer</groupId>
 <artifactId>micrometer-registry-prometheus</artifactId>
 <version>${micrometer.version}</version>
</dependency>

And Gradle users, to their build file:

compile 'io.vertx:vertx-micrometer-metrics:3.6.2'
compile 'io.micrometer:micrometer-registry-prometheus:${micrometer.version}'

Configuration examples

Vert.x does not enable SPI implementations by default. You must enable metric collection in the Vert.x options

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    prometheusOptions = VertxPrometheusOptions(
      enabled = true),
    enabled = true)))

Using an embedded HTTP server with custom endpoint

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    prometheusOptions = VertxPrometheusOptions(
      enabled = true,
      startEmbeddedServer = true,
      embeddedServerOptions = HttpServerOptions(
        port = 8080),
      embeddedServerEndpoint = "/metrics/vertx"),
    enabled = true)))

If the embedded server endpoint is not specified, it defaults to /metrics.

Binding metrics to an existing Vert.x Web router

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    prometheusOptions = VertxPrometheusOptions(
      enabled = true),
    enabled = true)))

// Later on, creating a router
var router = Router.router(vertx)
router.route("/metrics").handler(PrometheusScrapingHandler.create())
vertx.createHttpServer().requestHandler(router).listen(8080)

JMX

Getting started

The modules vertx-micrometer-metrics and micrometer-registry-jmx must be present in the classpath.

Maven users should add this to their project POM file:

<dependency>
 <groupId>io.vertx</groupId>
 <artifactId>vertx-micrometer-metrics</artifactId>
 <version>3.6.2</version>
</dependency>
<dependency>
 <groupId>io.micrometer</groupId>
 <artifactId>micrometer-registry-jmx</artifactId>
 <version>${micrometer.version}</version>
</dependency>

And Gradle users, to their build file:

compile 'io.vertx:vertx-micrometer-metrics:3.6.2'
compile 'io.micrometer:micrometer-registry-jmx:${micrometer.version}'

Configuration examples

Vert.x does not enable SPI implementations by default. You must enable metric collection in the Vert.x options

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    jmxMetricsOptions = VertxJmxMetricsOptions(
      enabled = true),
    enabled = true)))

With step and domain

In Micrometer, step refers to the reporting period, in seconds. domain is the JMX domain under which MBeans are registered.

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    jmxMetricsOptions = VertxJmxMetricsOptions(
      enabled = true,
      step = 5,
      domain = "my.metrics.domain"),
    enabled = true)))

Other backends or combinations

Even if not all backends supported by Micrometer are implemented in Vert.x options, it is still possible to create any Micrometer registry and pass it to Vert.x.

The list of available backends includes Graphite, Ganglia, Atlas, etc. It also enables the Micrometer Composite Registry in order to report the same metrics to multiple backends.

In this example, metrics are reported both for JMX and Graphite:

var myRegistry = io.micrometer.core.instrument.composite.CompositeMeterRegistry()
myRegistry.add(io.micrometer.jmx.JmxMeterRegistry({ s ->
  null
}, io.micrometer.core.instrument.Clock.SYSTEM))
myRegistry.add(io.micrometer.graphite.GraphiteMeterRegistry({ s ->
  null
}, io.micrometer.core.instrument.Clock.SYSTEM))

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    micrometerRegistry = myRegistry,
    enabled = true)))

Advanced usage

Please refer to MicrometerMetricsOptions for an exhaustive list of options.

Averages and quantiles in Prometheus

By default, when using the Prometheus registry, histogram-kind metrics will not contain averages or quantile stats.

Averages don’t come out of the box but they are typically computed at query time, with promql. Example, for HTTP client response time average during the last 5 minutes:

 rate(vertx_http_client_responseTime_seconds_sum[5m])
/
 rate(vertx_http_client_responseTime_seconds_count[5m])

To compute quantiles, there are two options available. The first is to activate quantile stats globally and make them usable for Prometheus function histogram_quantile:

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    prometheusOptions = VertxPrometheusOptions(
      enabled = true,
      publishQuantiles = true),
    enabled = true)))

And then, for example the promql query for the HTTP client response time, 99th percentile over the last 5 minutes:

 histogram_quantile(0.99, sum(rate(vertx_http_client_responseTime_seconds_bucket[5m])) by (le))

The advantage of this option is that it can be leveraged in promql, aggregable across dimensions. The downside is that it creates a lot of timeseries for stats under the hood.

The second option is to create limited stats, non-aggregable across dimensions. It requires to access directly the Micrometer / Prometheus registry:

var registry = io.vertx.micrometer.backends.BackendRegistries.getDefaultNow()
registry.config().meterFilter(io.micrometer.core.instrument.config.MeterFilter())

See also, more on histograms and percentiles:

Furthermore, you can check some full working examples. They come along with few instructions to setup with Prometheus and view dashboards in Grafana.

Disable some metric domains

Restricting the Vert.x modules being monitored can be done using disabledMetricsCategories.

For a full list of domains, see MetricsDomain

User-defined metrics

The Micrometer registries are accessible, in order to create new metrics or fetch the existing ones. By default, an unique registry is used and will be shared across the Vert.x instances of the JVM:

var registry = io.vertx.micrometer.backends.BackendRegistries.getDefaultNow()

It is also possible to have separate registries per Vertx instance, by giving a registry name in metrics options. Then it can be retrieved specifically:

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    influxDbOptions = VertxInfluxDbOptions(
      enabled = true),
    registryName = "my registry",
    enabled = true)))

// Later on:
var registry = io.vertx.micrometer.backends.BackendRegistries.getNow("my registry")

As an example, here is a custom timer that will track the execution time of a piece of code that is regularly called:

var registry = io.vertx.micrometer.backends.BackendRegistries.getDefaultNow()
var timer = io.micrometer.core.instrument.Timer.builder("my.timer").description("a description of what this timer does").register(registry)

vertx.setPeriodic(1000, { l ->
  timer.record({
    // Running here some operation to monitor
  })
})

For more examples, documentation about the Micrometer registry and how to create metrics, check Micrometer doc.

Other instrumentation

Since plain access to Micrometer registries is provided, it is possible to leverage the Micrometer API. For instance, to instrument the JVM:

var registry = io.vertx.micrometer.backends.BackendRegistries.getDefaultNow()

io.micrometer.core.instrument.binder.jvm.ClassLoaderMetrics().bindTo(registry)
io.micrometer.core.instrument.binder.jvm.JvmMemoryMetrics().bindTo(registry)
io.micrometer.core.instrument.binder.jvm.JvmGcMetrics().bindTo(registry)
io.micrometer.core.instrument.binder.system.ProcessorMetrics().bindTo(registry)
io.micrometer.core.instrument.binder.jvm.JvmThreadMetrics().bindTo(registry)

From Micrometer documentation.

Labels and matchers

Vert.x Micrometer Metrics defines a set of labels (aka tags or fields) that are used to provide dimensionality to a metric. For instance, metrics related to event bus messages have an address label, which allows then to query timeseries for a specific event bus address, or compare timeseries per address, or perform any kind of aggregation that the query API allows.

While setting up metrics options, you can specify which labels you want to enable or not:

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    prometheusOptions = VertxPrometheusOptions(
      enabled = true),
    labels = java.util.EnumSet.of(Label.REMOTE, Label.LOCAL, Label.HTTP_CODE, Label.HTTP_PATH),
    enabled = true)))

The full list of labels is detailed here: Label.

Warning
 Enabling labels may result in a high cardinality in values, which can cause troubles on the metrics backend and affect performances. So it must be used with care. In general, it is fine to enable labels when the set of possible values is bounded.

For that reason, labels enabled by default are restricted to the ones with known bounded values.

It is possible to interact with labels further than just enabling/disabling. There are two ways for that:

Using Matchers

Match objects can be used to filter or rename some label value by matching it with either an exact string or a regular expression (the former being more efficient).

Here is an example to restrict HTTP server metrics to those with label local=localhost:8080 only:

var vertx = Vertx.vertx(VertxOptions(
  metricsOptions = MicrometerMetricsOptions(
    prometheusOptions = VertxPrometheusOptions(
      enabled = true),
    labelMatchs = listOf(Match(
      domain = MetricsDomain.HTTP_SERVER,
      label = "local",
      value = "localhost:8080")),
    enabled = true)))

When an alias is specified in the Match, it will be used to rename value instead of filtering.

Matchers are especially useful to control labelling through configuration as they are set via MicrometerMetricsOptions.

Using Micrometer’s MeterFilter

Micrometer’s MeterFilter API can be accessed directly in order to define rules on labels. Compared to Matchers, it offers more features in manipulating the labels, but cannot be defined from configuration. So both have their advantages.

Here is an example to replace the actual path label of HTTP requests with a generic form using regex:

var registry = io.vertx.micrometer.backends.BackendRegistries.getDefaultNow()
var pattern = java.util.regex.Pattern.compile("/foo/bar/.*")

registry.config().meterFilter(io.micrometer.core.instrument.config.MeterFilter.replaceTagValues(Label.HTTP_PATH.toString(), { actualPath ->
  var m = pattern.matcher(actualPath)
  if (m.matches()) {
    return "/foo/bar/:id"
  }
  return actualPath
}, ""))
Note
 Matchers use MeterFilters under the hood.

Snapshots

A MetricsService can be created out of a Measured object in order to take a snapshot of its related metrics and measurements. The snapshot is returned as a JsonObject.

A well known Measured object is simply Vertx:

var metricsService = MetricsService.create(vertx)
var metrics = metricsService.getMetricsSnapshot()
println(metrics)

Other components, such as an EventBus or a HttpServer are measurable:

var server = vertx.createHttpServer()
var metricsService = MetricsService.create(server)
var metrics = metricsService.getMetricsSnapshot()
println(metrics)

Finally it is possible to filter the returned metrics from their base names:

var metricsService = MetricsService.create(vertx)
// Client + server
var metrics = metricsService.getMetricsSnapshot("vertx.http")
println(metrics)

Vert.x core tools metrics

This section lists all the metrics generated by monitoring the Vert.x core tools.

Note
 The metric backends may have different conventions or rules for naming metrics. The names described below are given with underscore separators, but the actual names may vary depending on the backend used.

Net Client

Metric type Metric name Description

Gauge

vertx_net_client_connections{local=<local address>,remote=<remote address>}

Number of connections to the remote host currently opened.

Summary

vertx_net_client_bytesReceived{local=<local address>,remote=<remote address>}

Number of bytes received from the remote host.

Summary

vertx_net_client_bytesSent{local=<local address>,remote=<remote address>}

Number of bytes sent to the remote host.

Counter

vertx_net_client_errors{local=<local address>,remote=<remote address>,class=<class>}

Number of errors.

HTTP Client

Metric type Metric name Description

Gauge

vertx_http_client_connections{local=<local address>,remote=<remote address>}

Number of connections to the remote host currently opened.

Summary

vertx_http_client_bytesReceived{local=<local address>,remote=<remote address>}

Number of bytes received from the remote host.

Summary

vertx_http_client_bytesSent{local=<local address>,remote=<remote address>}

Number of bytes sent to the remote host.

Counter

vertx_http_client_errors{local=<local address>,remote=<remote address>,class=<class>}

Number of errors.

Gauge

vertx_http_client_requests{local=<local address>,remote=<remote address>}

Number of requests waiting for a response.

Counter

vertx_http_client_requestCount{local=<local address>,remote=<remote address>,method=<http method>}

Number of requests sent.

Timer

vertx_http_client_responseTime{local=<local address>,remote=<remote address>}

Response time.

Counter

vertx_http_client_responseCount{local=<local address>,remote=<remote address>,code=<response code>}

Number of received responses.

Gauge

vertx_http_client_wsConnections{local=<local address>,remote=<remote address>}

Number of websockets currently opened.

Datagram socket

Metric type Metric name Description

Summary

vertx_datagram_bytesReceived{local=<local>,remote=<remote>}

Total number of bytes received on the <host>:<port> listening address.

Summary

vertx_datagram_bytesSent{remote=<remote>}

Total number of bytes sent to the remote host.

Counter

vertx_datagram_errors{class=<class>}

Total number of errors.

Net Server

Metric type Metric name Description

Gauge

vertx_net_server_connections{local=<local address>}

Number of opened connections to the Net Server.

Summary

vertx_net_server_bytesReceived{local=<local address>}

Number of bytes received by the Net Server.

Summary

vertx_net_server_bytesSent{local=<local address>}

Number of bytes sent by the Net Server.

Counter

vertx_net_server_errors{local=<local address>,class=<class>}

Number of errors.

HTTP Server

Metric type Metric name Description

Gauge

vertx_http_server_connections{local=<local address>}

Number of opened connections to the HTTP Server.

Summary

vertx_http_server_bytesReceived{local=<local address>}

Number of bytes received by the HTTP Server.

Summary

vertx_http_server_bytesSent{local=<local address>}

Number of bytes sent by the HTTP Server.

Counter

vertx_http_server_errors{local=<local address>,class=<class>}

Number of errors.

Gauge

vertx_http_server_requests{local=<local address>}

Number of requests being processed.

Counter

vertx_http_server_requestCount{local=<local address>,method=<http method>,code=<response code>}

Number of processed requests.

Counter

vertx_http_server_requestResetCount{local=<local address>}

Number of requests reset.

Timer

vertx_http_server_processingTime{local=<local address>}

Request processing time.

Gauge

vertx_http_client_wsConnections{local=<local address>}

Number of websockets currently opened.

Event Bus

Metric type Metric name Description

Gauge

vertx_eventbus_handlers{address=<address>}

Number of event bus handlers in use.

Counter

vertx_eventbus_errors{address=<address>,class=<class>}

Number of errors.

Summary

vertx_eventbus_bytesWritten{address=<address>}

Total number of bytes sent while sending messages to event bus cluster peers.

Summary

vertx_eventbus_bytesRead{address=<address>}

Total number of bytes received while reading messages from event bus cluster peers.

Gauge

vertx_eventbus_pending{address=<address>,side=<local/remote>}

Number of messages not processed yet. One message published will count for N pending if N handlers are registered to the corresponding address.

Counter

vertx_eventbus_published{address=<address>,side=<local/remote>}

Number of messages published (publish / subscribe).

Counter

vertx_eventbus_sent{address=<address>,side=<local/remote>}

Number of messages sent (point-to-point).

Counter

vertx_eventbus_received{address=<address>,side=<local/remote>}

Number of messages received.

Counter

vertx_eventbus_delivered{address=<address>,side=<local/remote>}

Number of messages delivered to handlers.

Counter

vertx_eventbus_replyFailures{address=<address>,failure=<failure name>}

Number of message reply failures.

Timer

vertx_eventbus_processingTime{address=<address>}

Processing time for handlers listening to the address.

Vert.x pool metrics

This section lists all the metrics generated by monitoring Vert.x pools.

There are two types currently supported:

  • worker (see WorkerExecutor)

  • datasource (created with Vert.x JDBC client)

Note
 Vert.x creates two worker pools upfront, worker-thread and internal-blocking.
Metric type Metric name Description

Timer

vertx_pool_queue_delay{pool_type=<type>,pool_name=<name>}

Time waiting for a resource (queue time).

Gauge

vertx_pool_queue_size{pool_type=<type>,pool_name=<name>}

Number of elements waiting for a resource.

Timer

vertx_pool_usage{pool_type=<type>,pool_name=<name>}

Time using a resource (i.e. processing time for worker pools).

Gauge

vertx_pool_inUse{pool_type=<type>,pool_name=<name>}

Number of resources used.

Counter

vertx_pool_completed{pool_type=<type>,pool_name=<name>}

Number of elements done with the resource (i.e. total number of tasks executed for worker pools).

Gauge

vertx_pool_ratio{pool_type=<type>,pool_name=<name>}

Pool usage ratio, only present if maximum pool size could be determined.

Verticle metrics

Metric type Metric name Description

Gauge

vertx_verticle_deployed{name=<name>}

Number of verticle instances deployed.