anchor.diff:  and pull requests should be submitted there:
   https://github.com/quarkusio/quarkus/tree/main/docs/src/main/asciidoc
   ////
  +
   = SmallRye Metrics
   
   include::./attributes.adoc[]
   
  -This guide demonstrates how your Quarkus application can use https://github.com/smallrye/smallrye-metrics/[SmallRye Metrics],
  -an implementation of the https://github.com/eclipse/microprofile-metrics/[MicroProfile Metrics] specification.
  -
  -SmallRye Metrics allows applications to gather various metrics and statistics that provide
  -insights into what is happening inside the application.
  -
  -The metrics can be read remotely using JSON format or the OpenMetrics format, so that
  -they can be processed by additional tools such as Prometheus, and stored for analysis
  -and visualisation.
  -
  -Apart from application-specific metrics, which are described in this guide, you may also utilize built-in metrics
  -exposed by various Quarkus extensions. These are described in the guide for each particular extension that supports
  -built-in metrics.
  -
  -IMPORTANT: link:micrometer[Micrometer] is the recommended approach to metrics for Quarkus.
  -Use the SmallRye Metrics extension when it's required to retain MicroProfile specification compatibility.
  +The following guide demonstrates how a Quarkus application can use link:https://github.com/smallrye/smallrye-metrics/[SmallRye Metrics],
  +an implementation of the link:https://github.com/eclipse/microprofile-metrics/[MicroProfile Metrics] specification.
  +
  +SmallRye Metrics allows applications to gather metrics and statistics that provide insights into what is happening inside an application. The metrics can be read remotely using the JSON or OpenMetrics format to be processed by additional tools such as Prometheus and stored for analysis and visualization.
  +
  +Apart from application-specific metrics described in this guide, you may also use built-in metrics exposed by various Quarkus extensions. These are described in the guide for each particular extension that supports built-in metrics.
  +
  +IMPORTANT: link:micrometer[Micrometer] is the recommended approach to metrics for Quarkus. Use the SmallRye Metrics extension when it is required to retain MicroProfile specification compatibility.
   
   == Prerequisites
   
  -To complete this guide, you need:
  -
  -* less than 15 minutes
  -* an IDE
  -* JDK 11+ installed with `JAVA_HOME` configured appropriately
  -* Apache Maven {maven-version}
  +* Approximately 15 minutes.
  +* An IDE.
  +* JDK 11+ installed with `JAVA_HOME` configured appropriately.
   
   == Architecture
  -In this example, we build a very simple microservice which offers one REST endpoint and that endpoint serves
  -for determining whether a number is prime. The implementation class is annotated with some metric annotations
  -so that while responding to user's requests, some metrics are gathered. The meaning of each metric will be explained later.
  +
  +In this example, we build a very simple microservice that offers one REST endpoint. This endpoint serves for determining whether a number is prime. The implementation class is annotated with certain metric annotations so that while responding to users' requests, certain metrics are gathered. The meaning of each metric is explained later.
   
   == Solution
   
  -We recommend that you follow the instructions in the next sections and create the application step by step.
  -However, you can go right to the completed example.
  -
  -Clone the Git repository: `git clone {quickstarts-clone-url}`, or download an {quickstarts-archive-url}[archive].
  -
  -The solution is located in the `microprofile-metrics-quickstart` {quickstarts-tree-url}/microprofile-metrics-quickstart[directory].
  -
  -== Creating the Maven Project
  -
  -First, we need a new project. Create a new project with the following command:
  -
  +We recommend that you follow the instructions in the next sections and create the application step by step. However, you can skip to the completed example.
  +
  +. Clone the Git repository:
  ++
  +[source,bash,subs=attributes+]
  +----
  +git clone {quickstarts-clone-url}
  +----
  +
  +* Alternatively, download a {quickstarts-archive-url}[Quickstarts archive]. The solution is located in the `microprofile-metrics-quickstart` {quickstarts-tree-url}/microprofile-metrics-quickstart[directory] and follow with the xref:running-and-using-the-application_{context}[] section.
  +
  +[id="creating-a-maven-project_{context}"]
  +== Creating a Maven project
  +
  +. To create a new Maven project:
  ++
   [source,bash,subs=attributes+]
   ----
   mvn io.quarkus.platform:quarkus-maven-plugin:{quarkus-version}:create \
       -DprojectGroupId=org.acme \
       -DprojectArtifactId=microprofile-metrics-quickstart \
  -    -DclassName="org.acme.microprofile.metrics.PrimeNumberResource" \
  +    -DclassName="org.acme.microprofile.metrics.PrimeNumberChecker" \
       -Dpath="/" \
       -Dextensions="resteasy,smallrye-metrics"
   cd microprofile-metrics-quickstart
   ----
  -
  -This command generates a Maven project, importing the `smallrye-metrics`.
  -
  -If you already have your Quarkus project configured, you can add the `smallrye-metrics` extension
  -to your project by running the following command in your project base directory:
  -
  ++
  +This command generates a Maven-based Quarkus project that uses the `smallrye-metrics` extension.
  +
  +* If you already have your Quarkus project configured, you can add the `smallrye-metrics` extension to your project by running the following command in your project base directory:
  ++
   [source,bash]
   ----
   ./mvnw quarkus:add-extension -Dextensions="smallrye-metrics"
   ----
  -
  -This will add the following to your `pom.xml`:
  -
  ++
  +This adds the following to your `pom.xml` file:
  ++
   [source,xml]
   ----
   <dependency>
  
positive.code: }
  ----
  
  == Running and using the application
  
  To run the microservice in dev mode, use `./mvnw clean compile quarkus:dev`
  
  === Generate some values for the metrics
  First, ask the endpoint whether some numbers are prime numbers.
  
  [source,bash]
  ----
  curl localhost:8080/350
  ----
  
  The application will respond that 350 is not a prime number because it can be divided by 2.
  
  Now for some large prime number so that the test takes a bit more time:
  
  [source,bash]
  ----
  curl localhost:8080/629521085409773
  ----
  
  The application will respond that 629521085409773 is a prime number.
  If you want, try some more calls with numbers of your choice.
  
  === Review the generated metrics
  To view the metrics, execute `curl -H"Accept: application/json" localhost:8080/q/metrics/application`
  You will receive a response such as:
  
  [source,json]
  ----
  {
    "org.acme.microprofile.metrics.PrimeNumberChecker.checksTimer" : {
      "p50": 217.231273,
      "p75": 217.231273,
      "p95": 217.231273,
      "p98": 217.231273,
      "p99": 217.231273,
      "p999": 217.231273,
      "min": 0.58961,
      "mean": 112.15909190834819,
      "max": 217.231273,
      "stddev": 108.2721053982776,
      "count": 2,
      "meanRate": 0.04943519091742238,
      "oneMinRate": 0.2232140583080189,
      "fiveMinRate": 0.3559527083952095,
      "fifteenMinRate": 0.38474303050928976
    },
    "org.acme.microprofile.metrics.PrimeNumberChecker.performedChecks" : 2,
    "org.acme.microprofile.metrics.PrimeNumberChecker.highestPrimeNumberSoFar" : 629521085409773
  }
  ----
  
  Let's explain the meaning of each metric:
  
  * `performedChecks`: A counter which is increased by one each time the user asks about a number.
  * `highestPrimeNumberSoFar`: This is a gauge that stores the highest number that was asked about by the user and which was determined to be prime.
  * `checksTimer`: This is a timer, therefore a compound metric that benchmarks how much time the primality tests take. All durations are measured in milliseconds. It consists of these values:
  ** `min`: The shortest duration it took to perform a primality test, probably it was performed for a small number.
  ** `max`: The longest duration, probably it was with a large prime number.
  ** `mean`: The mean value of the measured durations.
  ** `stddev`: The standard deviation.
  ** `count`: The number of observations (so it will be the same value as `performedChecks`).
  ** `p50, p75, p95, p99, p999`: Percentiles of the durations. For example the value in `p95` means that 95 % of the measurements were faster than this duration.
  ** `meanRate, oneMinRate, fiveMinRate, fifteenMinRate`: Mean throughput and one-, five-, and fifteen-minute exponentially-weighted moving average throughput.
  
  If you prefer an OpenMetrics export rather than the JSON format, remove the `-H"Accept: application/json"` argument from your command line.
  
  == Configuration Reference
  
  include::{generated-dir}/config/quarkus-smallrye-metrics.adoc[opts=optional, leveloffset=+1]
  
negative.code: </dependency>
  ----
  
  [id="writing-an-application_{context}"]
  == Writing an application
  
  The following procedures create a Maven-based Quarkus application that consists of a single class that implements an algorithm for checking whether a number is prime. This algorithm is exposed over a REST interface. Additionally, specific annotations are required to ensure that the desired metrics are calculated over time and can be exported for manual analysis or processing by additional tooling.
  
  The application will gather the following metrics:
  
  * `performedChecks`: A counter that increases by one each time the user asks about a number.
  * `highestPrimeNumberSoFar`: A gauge that stores the highest number asked about by the user if the number was determined to be prime.
  * `checksTimer`: A compound metric that benchmarks how much time the primality tests take. Additional details are provided later.
  
  The full source code looks as follows:
  [source,java]
  ----
  package org.acme.microprofile.metrics;
  