Monitoring
API docs
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Vert.x Micrometer Metrics

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>5.0.0.CR2</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:5.0.0.CR2'
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.

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setInfluxDbOptions(new VertxInfluxDbOptions().setEnabled(true))
    .setEnabled(true)));

Using a specific URI

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setInfluxDbOptions(new VertxInfluxDbOptions().setEnabled(true)
      .setUri("http://influxdb.example.com:8888"))
    .setEnabled(true)));

Connecting to InfluxDB V2

Connecting to InfluxDB V2 requires that at least the org property is set.

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setInfluxDbOptions(new VertxInfluxDbOptions().setEnabled(true)
      .setOrg("my-org"))
    .setEnabled(true)));

Using a specific database name or bucket

To configure a specific database name:

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setInfluxDbOptions(new VertxInfluxDbOptions().setEnabled(true)
      .setDb("sales-department"))
    .setEnabled(true)));

For InfluxDB V2, you can use setBucket as well.

With authentication

Authentication can be configured with a username and a password:

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setInfluxDbOptions(new VertxInfluxDbOptions().setEnabled(true)
      .setUserName("username")
      .setPassword("password"))
    .setEnabled(true)));

Or it can be configured with a token:

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setInfluxDbOptions(new VertxInfluxDbOptions().setEnabled(true)
      .setToken(authToken))
    .setEnabled(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>5.0.0.CR2</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:5.0.0.CR2'
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

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setPrometheusOptions(new VertxPrometheusOptions().setEnabled(true))
    .setEnabled(true)));

Using an embedded HTTP server with custom endpoint

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setPrometheusOptions(new VertxPrometheusOptions().setEnabled(true)
      .setStartEmbeddedServer(true)
      .setEmbeddedServerOptions(new HttpServerOptions().setPort(8080))
      .setEmbeddedServerEndpoint("/metrics/vertx"))
    .setEnabled(true)));

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

Using a custom HTTP server

The PrometheusRequestHandler provides flexibility in scraping and serving Prometheus metrics.

vertx.createHttpServer()
  .requestHandler(PrometheusRequestHandler.create(prometheusMeterRegistry, "/metrics/prometheus"))
  .listen(8888);

Binding metrics to an existing Vert.x Web router

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setPrometheusOptions(new VertxPrometheusOptions().setEnabled(true))
    .setEnabled(true)));

// Later on, creating a router
Router 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>5.0.0.CR2</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:5.0.0.CR2'
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

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setJmxMetricsOptions(new VertxJmxMetricsOptions().setEnabled(true))
    .setEnabled(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.

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setJmxMetricsOptions(new VertxJmxMetricsOptions().setEnabled(true)
      .setStep(5)
      .setDomain("my.metrics.domain"))
    .setEnabled(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:

CompositeMeterRegistry myRegistry = new CompositeMeterRegistry();
myRegistry.add(new JmxMeterRegistry(s -> null, Clock.SYSTEM));
myRegistry.add(new GraphiteMeterRegistry(s -> null, Clock.SYSTEM));

Vertx vertx = Vertx.builder()
  .with(new VertxOptions()
    .setMetricsOptions(new MicrometerMetricsOptions()
      .setEnabled(true)))
  .withMetrics(new MicrometerMetricsFactory(myRegistry))
  .build();

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_response_time_seconds_sum[5m])
/
  rate(vertx_http_client_response_time_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:

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setPrometheusOptions(new VertxPrometheusOptions().setEnabled(true)
      .setPublishQuantiles(true))
    .setEnabled(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_response_time_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 time-series 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:

PrometheusMeterRegistry registry = (PrometheusMeterRegistry) BackendRegistries.getDefaultNow();
registry.config().meterFilter(
  new MeterFilter() {
    @Override
    public DistributionStatisticConfig configure(Meter.Id id, DistributionStatisticConfig config) {
      return DistributionStatisticConfig.builder()
        .percentiles(0.95, 0.99)
        .build()
        .merge(config);
    }
  });

See also, more on histograms and percentiles:

Furthermore, you can check some full working examples. They come along with few instructions to set up 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, a unique registry is used and will be shared across the Vert.x instances of the JVM:

MeterRegistry registry = 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:

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setInfluxDbOptions(new VertxInfluxDbOptions().setEnabled(true)) // or VertxPrometheusOptions
    .setRegistryName("my registry")
    .setEnabled(true)));

// Later on:
MeterRegistry registry = 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:

MeterRegistry registry = BackendRegistries.getDefaultNow();
Timer timer = 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.

Reusing an existing registry

It is possible to reuse an existing Micrometer registry (or CollectorRegistry from the Prometheus Java client), and inject it into the Vert.x instance using a VertxBuilder:

PrometheusMeterRegistry registry = new PrometheusMeterRegistry(PrometheusConfig.DEFAULT);

// You could also reuse an existing registry from the Prometheus Java client:
PrometheusRegistry prometheusClientRegistry = new PrometheusRegistry();
registry = new PrometheusMeterRegistry(PrometheusConfig.DEFAULT, prometheusClientRegistry, Clock.SYSTEM);

// It's reused in MicrometerMetricsOptions.
// Prometheus options configured here, such as "setPublishQuantiles(true)", will affect the whole registry.
Vertx.builder()
  .with(new VertxOptions().setMetricsOptions(
    new MicrometerMetricsOptions()
      .setPrometheusOptions(new VertxPrometheusOptions().setEnabled(true)
        .setPublishQuantiles(true))
      .setEnabled(true)))
  .withMetrics(new MicrometerMetricsFactory(registry))
  .build();

Vert.x Micrometer Metrics registers meter filters for label matching. Since Micrometer 1.13, a warning is logged when a MeterFilter is configured after a meter is registered.

To avoid this warning, make sure to register your own meters only after Vert.x Micrometer Metrics has been initialized.

JVM and system metrics

Vert.x Micrometer Metrics can be configured to collect JVM and system metrics:

metricsOptions.setJvmMetricsEnabled(true);

Netty metrics

Vert.x relies on Netty for the networking layer.

Vert.x Micrometer Metrics can be configured to collect Netty metrics:

metricsOptions.setNettyMetricsEnabled(true);

The metric data collected is related to Vert.x specific byte buffer allocators and event loop groups.

Other instrumentations

Since plain access to Micrometer registries is provided, it is possible to leverage the Micrometer API:

MeterRegistry registry = BackendRegistries.getDefaultNow();
DiskSpaceMetrics metrics = new DiskSpaceMetrics(new File("/opt/myapp/data"));
metrics.bindTo(registry);

Metric names

Each metric that Vert.x provides can be renamed through the metrics options, using MetricsNaming and setMetricsNaming. The default metric names were changed in Vert.x 4 to better align with backend conventions, but it is still possible to retrieve the names used in Vert.x 3.x for compatibility:

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setPrometheusOptions(new VertxPrometheusOptions().setEnabled(true))
    .setMetricsNaming(MetricsNaming.v3Names())
    .setEnabled(true)));

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 time-series for a specific event bus address, or compare time-series 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:

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setPrometheusOptions(new VertxPrometheusOptions().setEnabled(true))
    .setLabels(EnumSet.of(Label.REMOTE, Label.LOCAL, Label.HTTP_CODE, Label.HTTP_PATH))
    .setEnabled(true)));

The full list of labels is detailed here: Label.

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:

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setPrometheusOptions(new VertxPrometheusOptions().setEnabled(true))
    .addLabelMatch(new Match()
      // Restrict HTTP server metrics to those with label "local=localhost:8080" only
      .setDomain(MetricsDomain.HTTP_SERVER)
      .setLabel("local")
      .setValue("localhost:8080"))
    .setEnabled(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:

MeterRegistry registry = BackendRegistries.getDefaultNow();
Pattern pattern = Pattern.compile("/foo/bar/.*");

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

Custom tags provider

You can define a function that generates additional tags (or labels) for HTTP server or client metrics. Such function takes an HttpRequest object as a parameter, and returns an Iterable of Tag.

As an example, here is how to map the x-user header to a custom label user in both server and client metrics:

Vertx vertx = Vertx.vertx(new VertxOptions().setMetricsOptions(
  new MicrometerMetricsOptions()
    .setPrometheusOptions(new VertxPrometheusOptions().setEnabled(true))
    .setServerRequestTagsProvider(req -> {
      String user = req.headers().get("x-user");
      return Collections.singletonList(Tag.of("user", user));
    })
    .setClientRequestTagsProvider(req -> {
      String user = req.headers().get("x-user");
      return Collections.singletonList(Tag.of("user", user));
    })
    .setEnabled(true)));

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:

MetricsService metricsService = MetricsService.create(vertx);
JsonObject metrics = metricsService.getMetricsSnapshot();
System.out.println(metrics);

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

HttpServer server = vertx.createHttpServer();
MetricsService metricsService = MetricsService.create(server);
JsonObject metrics = metricsService.getMetricsSnapshot();
System.out.println(metrics);

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

MetricsService metricsService = MetricsService.create(vertx);
// Client + server
JsonObject metrics = metricsService.getMetricsSnapshot("vertx.http");
System.out.println(metrics);

Vert.x core metrics

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

The metric backends may have different conventions or rules for naming metrics. The names described below are the default ones used in Vert.x 4, using underscore separators. The actual names may vary depending on the metrics backend.

TCP Client

Metric name Labels Type Description

vertx_net_client_bytes_read

local, remote

Counter

Number of bytes received from the remote host.

vertx_net_client_bytes_written

local, remote

Counter

Number of bytes sent to the remote host.

vertx_net_client_active_connections

local, remote

Gauge

Number of connections to the remote host currently opened.

vertx_net_client_errors

local, remote, class

Counter

Number of errors.

HTTP Client

Metric name Labels Type Description

vertx_http_client_bytes_read

local, remote

Counter

Number of bytes received from the remote host.

vertx_http_client_bytes_written

local, remote

Counter

Number of bytes sent to the remote host.

vertx_http_client_active_connections

local, remote

Gauge

Number of connections to the remote host currently opened.

vertx_http_client_errors

local, remote, class

Counter

Number of errors.

vertx_http_client_active_requests

local, remote, path, method

Gauge

Number of requests being processed, waiting for a response.

vertx_http_client_requests_total

local, remote, path, method

Counter

Number of requests sent.

vertx_http_client_request_bytes

local, remote, path, method

Summary

Size in bytes of the requests.

vertx_http_client_response_time_seconds

local, remote, path, method, code

Timer

Response time in seconds.

vertx_http_client_responses_total

local, remote, path, method, code

Counter

Number of received responses.

vertx_http_client_response_bytes

local, remote, path, method, code

Summary

Size in bytes of the responses.

vertx_http_client_active_ws_connections

local, remote

Gauge

Number of websockets currently opened.

TCP Server

Metric name Labels Type Description

vertx_net_server_bytes_read

local, remote

Counter

Number of bytes received by the Net Server.

vertx_net_server_bytes_written

local, remote

Counter

Number of bytes sent by the Net Server.

vertx_net_server_active_connections

local, remote

Gauge

Number of opened connections to the Net Server.

vertx_net_server_errors

local, remote, class

Counter

Number of errors.

HTTP Server

Metric name Labels Type Description

vertx_http_server_bytes_read

local, remote

Counter

Number of bytes received by the HTTP Server.

vertx_http_server_bytes_written

local, remote

Counter

Number of bytes sent by the HTTP Server.

vertx_http_server_active_connections

local, remote

Gauge

Number of opened connections to the HTTP Server.

vertx_http_server_errors

local, remote, class

Counter

Number of errors.

vertx_http_server_active_requests

local, remote, path, method

Gauge

Number of requests being processed.

vertx_http_server_requests_total

local, remote, path, method, code, route

Counter

Number of processed requests.

vertx_http_server_request_resets_total

local, remote, path, method

Counter

Number of request resets.

vertx_http_server_request_bytes

local, remote, path, method

Summary

Size in bytes of the requests.

vertx_http_server_response_time_seconds

local, remote, path, method, code, route

Timer

Request processing time in seconds.

vertx_http_server_response_bytes

local, remote, path, method, code, route

Summary

Size in bytes of the responses.

vertx_http_server_active_ws_connections

local, remote

Gauge

Number of websockets currently opened.

Datagram sockets

Metric name Labels Type Description

vertx_datagram_bytes_read

local

Summary

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

vertx_datagram_bytes_written

(none)

Summary

Total number of bytes sent to the remote host.

vertx_datagram_errors

class

Counter

Total number of errors.

Event Bus

Metric name Labels Type Description

vertx_eventbus_bytes_read

address

Summary

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

vertx_eventbus_bytes_written

address

Summary

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

vertx_eventbus_handlers

address

Gauge

Number of event bus handlers in use.

vertx_eventbus_pending

address,side (local/remote)

Gauge

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

vertx_eventbus_processed

address,side (local/remote)

Counter

Number of processed messages.

vertx_eventbus_published

address,side (local/remote)

Counter

Number of messages published (publish / subscribe).

vertx_eventbus_discarded

address,side (local/remote)

Counter

Number of discarded messages (e.g. still pending messages while handler is unregistered, or overflowing messages).

vertx_eventbus_sent

address,side (local/remote)

Counter

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

vertx_eventbus_received

address,side (local/remote)

Counter

Number of messages received.

vertx_eventbus_delivered

address,side (local/remote)

Counter

Number of messages delivered to handlers.

vertx_eventbus_reply_failures

address,failure

Counter

Number of message reply failures.

Worker pool metrics

The Vert.x worker pool expose metrics as defined by the pool metrics.

The type of pool (pool_type) is worker.

Vert.x creates two worker pools upfront, worker-thread and internal-blocking.

Generic metrics

Pool metrics

Vert.x clients, other than the core HTTP clients, may expose pool metrics.

Metric name Labels Type Description

vertx_pool_queue_time_seconds

pool_type,pool_name

Timer

Time spent in queue before being processed, in seconds.

vertx_pool_queue_pending

pool_type,pool_name

Gauge

Number of pending elements in queue.

vertx_pool_usage

pool_type,pool_name

Timer

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

vertx_pool_in_use

pool_type,pool_name

Gauge

Number of resources used.

vertx_pool_completed

pool_type,pool_name

Counter

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

vertx_pool_ratio

pool_type,pool_name

Gauge

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

Client metrics

Vert.x clients, other than the core HTTP / Net clients, may implement a standard set of client metrics.

Such client metrics are named after a "client type" identifier, displayed as $TYPE in the table below.

The meaning of the namespace label is left to the discretion of the client implementation.

Metric name Labels Type Description

vertx_$TYPE_queue_pending

remote, namespace

Gauge

Number of pending elements in queue.

vertx_$TYPE_queue_time_seconds

remote, namespace

Timer

Time spent in queue before being processed, in seconds.

vertx_$TYPE_processing_pending

remote, namespace

Gauge

Number of elements being processed.

vertx_$TYPE_processing_time_seconds

remote, namespace

Timer

Processing time, from request start to response end, in seconds.

vertx_$TYPE_resets_total

remote, namespace

Counter

Total number of resets.

Database clients metrics

The following clients expose client metrics as well as optionally pool metrics.

  • Vert.x SQL client

  • Vert.x Redis client

  • …​

The pool metrics carry a pool_type, e.g. the SQL client uses the sql type

  • vertx.pool.queue.pending with pool_type=sql

  • vertx.pool.queue.time with pool_type=sql

  • vertx.pool.usage with pool_type=sql

  • vertx.pool.ratio pool_type=sql

  • vertx.pool.completed pool_type=sql

  • vertx.pool.in.use pool_type=sql

The client metrics type appears in the metrics name

  • vertx.sql.processing.pending

  • vertx.sql.processing.time

In order to distinguish pools, you can set a pool name on the PoolOptions, exposed as a label

  • vertx.pool.queue.pending with pool_type=sql and pool_name=the-pool-name

  • vertx.pool.queue.time with pool_type=sql and pool_name=the-pool-name

  • vertx.pool.usage with pool_type=sql and pool_name=the-pool-name

  • vertx.pool.ratio pool_type=sql and pool_name=the-pool-name

  • vertx.pool.completed pool_type=sql and pool_name=the-pool-name

  • vertx.pool.in.use pool_type=sql and pool_name=the-pool-name

Likewise, client metrics use a namespace with distinguish between them

  • vertx.sql.processing.pending with client_namespace=the-client-name

  • vertx.sql.processing.time with client_namespace=the-client-name

Micrometer must be configured to expose these labels

micrometerMetricsOptions.addLabels(Label.POOL_NAME);
micrometerMetricsOptions.addLabels(Label.NAMESPACE);

Vert.x SQL client

Vert.x SQL client uses the sql type.

Use PoolOptions#setName(String) to name the pool

poolOptions.setName("the-pool-name");

Likewise, use SqlConnectOptions#setMetricsName(String) to scope the client metrics

connectOptions.setMetricsName("the-client-name");

Vert.x Redis client

Vert.x SQL client uses the redis type.

Use RedisOptions#setPoolName(String) to name the pool

redisOptions.setPoolName("the-pool-name");

Likewise, use RedisOptions#setMetricsName(String) to scope the client metrics

redisOptions.setMetricsName("the-client-name");