Spring Boot 2.0 HTTP request metrics with Micrometer


Brand new Spring Boot 2.0 has just been released and TouKs couldn’t wait to try it in the production. One of the newly added features that we investigated was metrics system based on Micrometer library (https://micrometer.io/). In this post I will cover some of our experiences with this so far.

The goal was to get basic HTTP request metrics, report them to InfluxDB and draw some fancy graphs in Grafana. In particular we needed:

  • Throughput – total number of requests in given time unit
  • Response status statistics – how many 200-like and 500-like response occurred
  • Response time statistics: mean, median, percentiles

What was wrong with Dropwizard metrics

Nothing that I am aware of. Metrics Spring integration however is a different story….

Last stable release of Metrics Spring (v. 3.1.3) was in late 2015 and it was compatible with Dropwizard Metrics (v. 3.1.2). From this time Dropwizard Metrics moved to version 4 and 5, but Metrics Spring literally died. This causes a couple of rather unpleasant facts:

  • There are some known bugs that will never be solved
  • You can’t benefit from Dropwizard Metrics improvements
  • Sooner or later you will use a library that depends on a different version of Dropwizard Metrics and it will hurt

As an InfluxDB user I was also facing some problems with reporting tags. After a couple of tries we ended up using an obscure Graphite interface that was luckily compatible with Influx.

Let’s turn on the metrics

Adding metrics to your Spring Boot project can be done in three very simple steps. First add a dependency to micrometer-registry-xxx, where xxx is your favourite metrics storage. In our case:



Now it is time for just a little bit of configuration in application.yml:

        uri: http://localhost:8086
        db: services
        step: 5s  ### <- (1)


And a proper configuration bean:

@Configuration public class MetricsConfig {
    private static final Duration HISTOGRAM_EXPIRY = Duration.ofMinutes(10);
    private static final Duration STEP = Duration.ofSeconds(5);
    ("${host_id}") private String hostId;
    ("${service_id}") private String serviceId;
    public MeterRegistryCustomizer < MeterRegistry > metricsCommonTags() { // (2)
        return registry - > registry.config()
        .commonTags("host", hostId, "service", serviceId) // (3)
        .meterFilter(MeterFilter.deny(id - > { // (4)
                String uri = id.getTag("uri");
                return uri != null && uri.startsWith("/swagger");
            .meterFilter(new MeterFilter() {
                public DistributionStatisticConfig configure(Meter.Id id, DistributionStatisticConfig config) {
                    return config.merge(DistributionStatisticConfig.builder().percentilesHistogram(true).percentiles(0.5, 0.75, 0.95) // (5)
                    .expiry(HISTOGRAM_EXPIRY) // (6)
                    .bufferLength((int)(HISTOGRAM_EXPIRY.toMillis() / STEP.toMillis())) // (7)


Simple as that. For sure it is not the minimal working example, but I believe some of our ideas are worth mentioning.

Dive into configuration

Config is rather self-explanatory, but let’s take a look at couple of interesting features.

(1) Step defines how often data is sent by reporter. This value should be related to your expected traffic, because you don’t want to see 90% of zeros.

(2) Be aware that there can be many reporters sharing the same config. Customising each behaviour can be done by using more specific type parameter e.g. InfluxMeterRegistry.

(3) Tags that will be added to every metric. As you can see it’s very handy for identifying hosts in a cluster.

(4) Skipping not important endpoints will limit unwanted data.

(5) A list of percentiles you would like to track

(6)(7) Histograms are calculated for some defined time window where more recent values have bigger impact on final value. The bigger time window you choose, the more accurate statistics are, but the less sudden will be changes of percentile value in case of very big or very small response time. It is also very important to increase buffer length as you increase expiry time.


We believe that migrating to Micrometer is worth spending time as configuration and reporting becomes simpler. The only thing that surprised us was reporting rate of throughput and status counts rather than cumulative values. But this is another story to be told…

Special thanks to Arek Burdach for support.

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CasperJS for Java developers

Why CasperJS

Being a Java developer is kinda hard these days. Java may not be dead yet, but when keeping in sync with all the hipster JavaScript frameworks could make us feel a bit outside the playground. It’s even hard to list JavaScript frameworks with latest releases on one website.

In my current project, we are using AngularJS. It’a a nice abstraction of MV* pattern in frontend layer of any web application (we use Grails underneath). Here is a nice article with an 8-point Win List of Angular way of handling AJAX calls and updating the view. So it’s not only a funny new framework but a truly helper of keeping your code clean and neat.

But there is also another area when you can put helpful JS framework in place of plan-old-java one - functional tests. Especially when you are dealing with one page app with lots of asynchronous REST/JSON communication.

Selenium and Geb

In Java/JVM project the typical is to use Selenium with some wrapper like Geb. So you start your project, setup your CI-functional testing pipeline and… after 1 month of coding your tests stop working and being maintainable. The frameworks itselves are not bad, but the typical setup is so heavy and has so many points of failure that keeping it working in a real life project is really hard.

Here is my list of common myths about Selenium: * It allows you to record test scripts via handy GUI - maybe some static request/response sites. In modern web applications with asynchronous REST/JSON communication your tests must contain a lot of “waitFor” statements and you cannot automate where these should be included. * It allows you to test your web app against many browsers - don’t try to automate IE tests! You have to manually open your app in IE to see how it actually bahaves! * It integrates well with continuous integration servers like Jenkins - you have to setup Selenium Grid on server with X installed to run tests on Chrome or Firefox and a Windows server for IE. And the headless HtmlUnit driver lacks a lot of JS support.

So I decided to try something different and introduce a bit of JavaScript tooling in our project by using CasperJS.


CasperJS is simple but powerful navigation scripting & testing utility for PhantomJS - scritable headless WebKit (which is an rendering engine used by Safari and Chrome). In short - CasperJS allows you to navigate and make assertions about web pages as they’d been rendered in Google Chrome. It is enough for me to automate the functional tests of my application.

If you want a gentle introduction to the world of CasperJS I suggest you to read: * Official website, especially installation guide and API * Introductionary article from CasperJS creator Nicolas Perriault * Highlevel testing with CasperJS by Kevin van Zonneveld * grails-angular-scaffolding plugin by Rob Fletcher with some working CasperJS tests

Full example

I run my test suite via following script:

casperjs test --direct --log-level=debug --testhost=localhost:8080 --includes=test/casper/includes/casper-angular.coffee,test/casper/includes/pages.coffee test/casper/specs/


casper.test.on "fail", (failure) ->

testhost   = casper.cli.get "testhost"
screenshot = 'test-fail.png'

    .log("Using testhost: #{testhost}", "info")
    .log("Using screenshot: #{screenshot}", "info")

casper.waitUntilVisible = (selector, message, callback) ->
    @waitFor ->
        @visible selector
    , callback, (timeout) ->
        @log("Selector [#{selector}] not visible, failing")
        withParentSelector selector, (parent) ->
            casper.log("Output of parent selector [#{parent}]")
        @echo message, "RED_BAR"
        @test.fail(f("Wait timeout occured (%dms)", timeout))

withParentSelector = (selector, callback) ->
    if selector.lastIndexOf(" ") > 0
       parent = selector[0..selector.lastIndexOf(" ")-1]

Sample pages.coffee:

x = require('casper').selectXPath

class EditDocumentPage

    assertAt: ->
        casper.test.assertSelectorExists("div.customerAccountInfo", 'at EditDocumentPage')

    templatesTreeFirstCategory: 'ul.tree li label'
    templatesTreeFirstTemplate: 'ul.tree li a'
    closePreview: '.closePreview a'
    smallPreview: '.smallPreviewContent img'
    bigPreview: 'img.previewImage'
    confirmDelete: x("//div[@class='modal-footer']/a[1]")

casper.editDocument = new EditDocumentPage()

End a test script:

testhost = casper.cli.get "testhost" or 'localhost:8080'

casper.start "http://#{testhost}/app", ->
    @test.assertHttpStatus 302
    @test.assertUrlMatch /\/fakeLogin/, 'auto login'
    @test.assert @visible('input#Create'), 'mock login button'
    @click 'input#Create'

casper.then ->
    @test.assertUrlMatch /document#\/edit/, 'new document'
    @waitUntilVisible @editDocument.templatesTreeFirstCategory, 'template categories not visible', ->
        @click @editDocument.templatesTreeFirstCategory
        @waitUntilVisible @editDocument.templatesTreeFirstTemplate, 'template not visible', ->
            @click @editDocument.templatesTreeFirstTemplate

casper.then ->
    @waitUntilVisible @editDocument.smallPreview, 'small preview not visible', ->
        # could be dblclick / whatever
        @mouseEvent('click', @editDocument.smallPreview)

casper.then ->
    @waitUntilVisible @editDocument.bigPreview, 'big preview should be visible', ->
        @test.assertEvalEquals ->
        , '1/1', 'page counter should be visible'
        @click @editDocument.closePreview

casper.then ->
    @click 'button.cancel'
    @waitUntilVisible '.modal-footer', 'delete confirmation not visible', ->
        @click @editDocument.confirmDelete

casper.run ->

Here is a list of CasperJS features/caveats used here:

  • Using CoffeeScript is a huge win for your test code to look neat
  • When using casper test command, beware of different (than above articles) logging setup. You can pass --direct --log-level=debug from commandline for best results. Logging is essential here since Phantom often exists without any error and you do want to know what just happened.
  • Extract your helper code into separate files and include them by using --includes switch.
  • When passing server URL as a commandline switch remember that in CoffeeScript variables are not visible between multiple source files (unless getting them via window object)
  • It’s good to override standard waitUntilVisible with capting a screenshot and making a proper log statement. In my version I also look for a parent selector and debugHTML the content of it - great for debugging what is actually rendered by the browser.
  • Selenium and Geb have a nice concept of Page Objects - an abstract models of pages rendered by your application. Using CoffeeScript you can write your own classes, bind selectors to properties and use then in your code script. Assigning the objects to casper instance will end up with quite nice syntax like @editDocument.assertAt().
  • There is some issue with CSS :first and :last selectors. I cannot get them working (but maybe I’m doing something wrong?). But in CasperJS you can also use XPath selectors which are fine for matching n-th child of some element (x("//div[@class='modal-footer']/a[1]")).
    Update: :first and :last are not CSS3 selectors, but JQuery ones. Here is a list of CSS3 selectors, all of these are supported by CasperJS. So you can use nth-child(1) is this case. Thanks Andy and Nicolas for the comments!

Working with CasperJS can lead you to a few hour stall, but after getting things working you have a new, cool tool in your box!

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