jueves, marzo 31, 2016

Continuous Stress Testing for your JAX-RS (and JavaEE) applications with Gatling + Gradle + Jenkins Pipeline

In this post I am going to explain how to use Gatling project to write stress tests for your JAX-RS Java EE endpoints, and how to integrate them with Gradle and Jenkins Pipeline, so instead of having a simple stress tests, what you have is a continuous stress testing, where each commit might fire these kind of tests automatically, providing automatic assertions and more important graphical feedback of each execution so you can monitorize how the performance is evolving in your application.

First thing to develop is the JAX-RS JavaEE service:

There is nothing special, this is an asynchronous JAX-RS endpoint that connects to swapi.co site, retrieves all the information of Star Wars planets, calculates the average of orbital period and finally it returns it in form of text. For sake of simplicity, I am not going to show you all the other classes but they are quite simple and at the end of the post I will provide you the github repository. 

The application is packaged inside a war file and deployed into an application server. In this case into an Apache TomEE 7 deployed inside the official Apache TomEE Docker image.

Next step is configuring Gradle build script with Gatling dependencies. Since Gatling is written in Scala you need to use Scala plugin.

After that, it is time to write our first stress test. It is important to notice that writing stress tests for Gatling is writing a Scala class using the provided DSL. Even for people who has never seen Scala is pretty intuitive how to use it.

So create a directory called src/test/scala and create a new class called AverageOrbitalPeriodSimulation.scala with next content:

Every simulation must extends Simulation object. This simulation takes base URL of the service from starwars_planets_url environment or system property, it creates the scenario pointing to the endpoint defined in JAX-RS,  and finally during 3 seconds it will gradually add users until 10 users are running at the same time. The test will pass only if all the requests succeed in less than 3 seconds.

Now we need to run this test. You will notice that this is not a JUnit test, so you cannot do a Run As JUnit test. What you need to do is use a runnable class provided by Gatling which requires you pass as argument the simulation class. This is really easy to do with Gradle.

We are defining a Gradle task of type JavaExec, since what we want is to run a runnable class. Then we make the life a bit easier for developer by automatically detect that if starwars_planets_url is not set, we are running this test into a machine that has Docker installed so probably this is the host to be used.
Finally we override the environment variable if it is required, we set the runnable class with required properties and we configure Gradle to execute this task every time the test task is executed (./gradlew test).

If you run it, you might see some output messages from Gatling, and after all a message like: please open the following file: /Users/..../stress-test/build/reports/gatling-results/averageorbitalperiodsimulation-1459413095563/index.html and this is where you can get the report. Notice that a random number is appended at the end of the directory and this is important as we are going to see later. The report might looks like:

At this time we have Gatling integrated with Gradle, but there is a missing piece here, and it is adding the continuous part on the equation. For adding continuous stress testing we are going to use Jenkins and Jenkins Pipeline as CI server so for each commit stress tests are executed among other tasks such as compile, run unit, integration tests, or code quality gate.

Historically Jenkins jobs were configured using web UI, requiring users to manually create jobs, fill the details of the job and create the pipeline through web browser. Also this makes keeping configuration of the job separated from the actual code being built.

With the introduction of Jenkins Pipeline plugin. This plugin is a Groovy DSL that let's implement you the entire build process in a file and store that alongside its code. Jenkins 2.0 comes by default with this plugin, but if you are using Jenkins 1.X you can install it as any other plugin (https://wiki.jenkins-ci.org/display/JENKINS/Pipeline+Plugin)

So now we can start coding our release plugin but for the purpose of this post only stress part is going to be covered. You need to create a file called Jenkinsfile (the name is not mandatory but it is the de-facto name) on the root of your project, and in this case with next content:

In this case we are defining a new stage which is called Stress Test. Stage step is only used as informative and it will be used for logging purposes. Next a node is defined. A node is a Jenkins executor where to execute the code. Inside this node, the source code is checked out from the same location where Jenkinsfile is placed, sets a new environment variable pointing out to the location where the application is deployed, and finally a shell step which executes the Gradle test task.

Last step in Jenkins is to create a new job of type Pipeline and set the location of the Jenkinsfile. So go to Jenkins > New Item > Pipeline and give a name to the job.

Then you only need to go to Pipeline section and configure the SCM repository where the project is stored.

And then if you have correctly configured the hooks from Jenkins and your SCM server, this job is going to be executed for every commit, so your stress tests are going to run continuously.

Of course probably you have noticed that stress tests are executed but no reports are published in Jenkins, so you have no way to see or compare results from different executions. For this reason you can use publishHtml plugin to store the generated reports in Jenkins. If you don't have the plugin installed yet, you need to install it as any other Jenkins plugin.

PublishHtml plugin allows us to publish some html files generated by our build tool to Jenkins so they are available to users and also categorised by build number. You need to configure the location of the directory of files to publish, and here we find the first problem, do you remember that Gatling generates a directory with a random number? So we need to fix this first. You can follow different strategies, but the easiest one is simply rename the directory to a known static name after the tests.

Open Gradle build file and add next content.

We are creating a new task executed at the end of test task that renames the last created directory to averageorbitalperiodsimulation.

Final step is add after shell call in Jenkinsfile next call:

publishHTML(target: [reportDir:'stress-test/build/reports/gatling-results/averageorbitalperiodsimulation', reportFiles: 'index.html', reportName: 'Gatling report', keepAll: true])

After that you might see a link in the job page that points to the report.

And that's all, thanks of Gradle and Jenkins you can implement a continuous stress testing strategy in an easy way and just using code the language all developers speak.

We keep learning,
I can live whatever way I please, I move around among the seven seas, No one will miss me when the sun goes down, and in the morning I'be out of town (Movin' Cruisin' - The Fantastic Oceans)

Music: https://www.youtube.com/watch?v=Byg5Xq_pb74
Source Code: https://github.com/lordofthejars/starwars

lunes, marzo 07, 2016

Docker and Jenkins - Orchestrating Continuous Delivery

Past week I had the honour of speaking in Docker Barcelona Meetup about how to use Jenkins for doing typical Docker tasks like creating images, publishing them or having a trace of what has occurred on them. Finally I introduced the new (or not so new) Jenkins Pipeline plugin which allows you to create your continuous delivery pipeline by coding it using a Groovy DSL instead of relaying on static steps like happens when you use FreeStyle jobs. At the end I showed how to use it with Docker.

You can see the slides in slideshare or as html.

We keep learning,

Hello, it's me, I was wondering if after all these years you'd like to meet, To go over everything, They say that time's supposed to heal ya (Hello - Adele)

Music: https://www.youtube.com/watch?v=YQHsXMglC9A

viernes, enero 08, 2016

Container Object pattern. A new pattern for your tests.

If you search for a description of what Page Object is, you’ll find that The Page Object Pattern gives us a common sense way to model content in a reusable and maintainable way.

And also points that: Within your web app’s UI there are areas that your tests interact with. A Page Object simply models these as objects within the test code.
This reduces the amount of duplicated code and means that if the UI changes, the fix need only be applied in one place.

As you can see, Page Object applies to UI elements. We (the Arquillian community) has coined a new pattern following Page Object pattern logic called Container Object pattern.
You can think about Container Object as areas of a container (for now Docker container) that your test might interact with. For example some of these areas could be:
  • To get the host IP where container is running.
  • The bounded port for a given exposed port.
  • Any parameter configured inside the configuration file (Dockerfile) like a user or password to access to the service which the container exposes.
  • Definition of the containers.
A Container Object might contain an aggregation of more than one Container Object inside it. This effectively builds a relation ship (link) between containers.

An example of configuration parameters might be for example, in case of running a MySQL database in a container, it could be the user and password to access to database. 
Notice that nothing prevents you to generate the correct URL for accessing to the service from the test, or execute commands against container like retrieving an internal file.

And of course as Page Object does, Container Object gives you a way to build a model content that can be reused for several projects.

Before looking at how this pattern is implemented in Arquillian Cube, let’s go thorough an example:

Suppose all of your applications need to send a file to an FTP server. To write an integration/component test you might need a FTP server to send the file and check that the file was correctly sent.
One way to do this is using Docker to start a FTP server just before executing the test, then execute the test using this Docker container for FTP server, before stopping the container check that the file is there, and finally stop the container.

So all these operations that involves the FTP server and container could be joined inside a Container Object. This container object might contain information of:
  • Which image is used
  • IP and bounded port of host where this FTP server is running
  • Username and password to access to the FTP server
  • Methods for asserting the existence of a file
Then from the point of view of test, it only communicate with this object instead of directly hard coding all information inside the test.
Again as in Page Object, any change on the container only affects the Container Object and not the test itself.

Now let’s see how Arquillian Cube implements Container Object pattern with a very simple example:

Arquillian Cube and Container Object

Let’s see a simple example on how you can implement a Container Object in Cube. Suppose you want to create a container object that encapsulates a ping pong server running inside Docker.
The Container Object will be like a simple POJO with special annotations:

In previous example you must pay attention at next lines:
  1. @Cube annotation configures Container Object.
  2. A Container Object can be enriched with Arquillian enrichers.
  3. Bounded port is injected for given exposed port.
  4. Container Object hides how to connect to PingPong server.
@Cube annotation is used to configure this Container Object. Initially you set that the started container will be named pingpong and the port binding information for the container instance, in this case 5000→8080/tcp.
Notice that this can be an array to set more than one port binding definition.

Next annotation is @CubeDockerFile which configure how Container is created. In this case using a Dockerfile located at default classpath location. The default location is the package+classname, so for example in previous case, Dockerfile should be placed at org/superbiz/containerobject/PingPongContainer directory.
Of course you can set any other class path location by passing as value of the annotation. CubeDockerFile annotation sets the location where the Dockerfile is found and not the file itself.
Also this location should be reachable from ClassLoader, so it means it should be loaded from classpath in order to find it.

Any Cube can be enriched with any client side enricher, in this case with @HostIp enricher, but it could be enriched with DockerClient using @ArquillianResource as well.

Finally the @HostPort is used to translate the exposed port to bound port.
So in this example port value will be 5000. You are going to learn briefly why this annotation is important.

And then you can start using this container object in your test:

The most important thing here is that you need to set Container Object as a field of the class and annotate with @Cube.

It is very important to annotate the field with Cube, so before Arquillian runs the test, it can detect that it needs to start a new Cube (Docker container), create the Container Object and inject it in the test.

Notice that this annotation is exactly the same as used when you defined the Container Object.
And it is in this way because you can override any property of the Container Object from the test side. This is why @HostPort annotation is important, since port can be changed from the test definition, you need to find a way to inject the correct port inside the container object.

In this post I have introduced Container Object pattern and how can be used in Arquillian Cube. But this is only an small taste, you can read more about Arquillian Cube and Container Object integration at https://github.com/arquillian/arquillian-cube#arquillian-cube-and-container-object

Also a running examples can be found at https://github.com/arquillian/arquillian-cube/tree/master/docker/ftest-docker-containerobject

We keep learning,

It's time to see what I can do, To test the limits and break through, No right, no wrong, no rules for me, I'm free! (Let It Go - Idina Menzel) 

Music: https://www.youtube.com/watch?v=moSFlvxnbgk

miércoles, noviembre 25, 2015

Java EE, Gradle and Integration Tests

In the last years Apache Maven has become the de-facto build tool for Java and Java EE projects. But from two years back Gradle is gaining more and more users. Following my previous post (http://www.lordofthejars.com/2015/10/gradle-and-java-ee.html), In this post you are going to see how to use Gradle for writing integration tests for Java EE using Arquillian.

Gradle is a build automation tool like Ant or Maven but introducing a Groovy-based DSL language instead of XML. So as you might expect the build file is a Groovy file. You can read in my previous post (http://www.lordofthejars.com/2015/10/gradle-and-java-ee.html) how to install Gradle.

To write integration tests for Java EE, the de-facto tool is Arquillan. If you want to know what Arquillian is, you can get a Getting Start Guide in (http://arquillian.org/guides/getting_started/) or in book Arquillian In Action.

To start using Arquillian, you need to add Arquillian dependencies, which comes in form of BOM. Gradle does not support BOM artefacts out of the box, but you can use dependency-management-plugin Gradle plugin to have support to define BOMs.

Moreover Gradle offers the possibility to add more test source sets apart from the default one which as in Maven is src/test/java and src/test/resources. The idea is that you can define a new test source set where you are going to put all integration tests. With this approach each kind of tests are clearly separated into different source sets. You can write Groovy code in Gradle script to achieve this or you can just use gradle-testsets-plugin which it is the easiest way to proceed.

So to register both plugins (dependency and testsets) you need to add next elements in build.gradle script file:

buildscript {
    repositories {
    dependencies {
        classpath "io.spring.gradle:dependency-management-plugin:0.5.3.RELEASE"
        classpath 'org.unbroken-dome.gradle-plugins:gradle-testsets-plugin:1.2.0'

apply plugin: "io.spring.dependency-management"
apply plugin: 'org.unbroken-dome.test-sets'

Now it is time to add Arquillian dependencies. You need to add the Arquillian BOM, and two dependencies, one that sets that we are going to use Arquillian with JUnit, and another one that sets Apache TomEE application server as target for deploying the application during test runs.

build.gradle with Arquillian, TomEE and Java EE dependency might look like:

dependencyManagement {
    imports {
        mavenBom 'org.arquillian:arquillian-universe:1.0.0.Alpha1'

dependencies {
    testCompile group: 'org.arquillian.universe', name: 'arquillian-junit', ext: 'pom'
    testCompile group: 'org.apache.openejb', name: 'arquillian-tomee-embedded', version:'1.7.2'
    testCompile group: 'junit', name: 'junit', version:'4.12'
    providedCompile group: 'org.apache.openejb',name: 'javaee-api', version:'6.0-6'


Finally you can configure the new integration test folder as source set by adding next section:

testSets {

Where integrationTest is the name of the test set. testSets automatically creates and configures next elements:
  • src/integrationTests/java and src/integrationTests/resources as valid source set folders.
  • A dependency configuration named integrationTestsCompile which extends from testCompile, and another one called integrationTestRuntime which extends from testRuntime.
  • A Test task named integrationTests which runs the tests in the set.
  • A Jar task named integrationTestsJar which packages the tests. 
Notice that you can change the integrationTests to any other value like intTests and Gradle would configure previous elements automatically to the value set it inside testSets, such as src/intTests/java or for example the test task would be called intTests.

Next step is creating the integration tests using Arquillian inside integrationTests test set. For example an Arquillian test for validating that you can POST a color in a REST API and it is returned when GET method is called, would look like:

You can now run integration tests by simply executing gradlew integrationTests

You'll notice that if you run gradlew build, the integration test task is not run. This happens because task is not registered within the default build lifecycle. If you want to add integrationTests task to be executed automatically during build you need to add next lines:

check.dependsOn integrationTest
integrationTest.mustRunAfter test

Ensure that integration tests are run before the check task and that the check task fails the build if there are failing integration tests and also ensures that unit tests are run before integration tests. This guarantees that unit tests are run even if integration tests fails.

So now when you run gradlew build, the integration tests are going to be executed as well.

And finally, what's happen if you are running JaCoCo plugin for code coverage? You will get two JaCoCo files, one for the unit test executions and another one for the integrationTests execution. But probably you want to see an aggregated code coverage report of both runs into one file, so you can inspect the code coverage degree of the application after the execution of all kind of tests. To achieve it you only need to add next task:

task jacocoRootTestReport(type: JacocoReport) {
    sourceSets sourceSets.main
    executionData files([
    reports {
        xml.enabled false
        csv.enabled false

In this case you are creating a task which aggregates the coverage results of test.exec file (which comes from unit tests) and integrationTests.exec which comes from integration tests.

And to generate the reports you need to explicitly call the jacocoRootTestReport task when you run Gradle

So it is so simple to write a Gradle script for running Java EE tests and more important the final script file looks very compact and readable without being tight to any static convention at all.

We keep  learning,
There must be more to life than this, There must be more to life than this, How do we cope in a world without love (There Must Be More To Life Than This - Freddie Mercury - Michael Jackson)

miércoles, octubre 07, 2015

Gradle and Java EE

In the last years Apache Maven has become the de-facto build tool for Java and Java EE projects. But from two years back Gradle is gaining more and more users. In this post you are going to see how to use Gradle for Java EE projects.

Gradle is a build automation tool like Ant or Maven but introducing a Groovy-based DSL language instead of XML. So as you might expect the build file is a Groovy file.

There are different ways to install Gradle, but for me the best way is using sdkman tool. To install sdkman tool simply run:

$ curl -s get.sdkman.io | bash

After that you can init sdkman by running:

$ source "$HOME/.sdkman/bin/sdkman-init.sh"

With sdkman installed, installing Gradle is as easier as running:

$ sdk install gradle

Now you can start creating the build script. The first thing to do is creating a settings.gradle where in this case we are going to set the name of the project.

This file is also used in case of multiple module projects.

Last file you might need is one called build.gradle which manages all the build process.

Notice that the first line indicates that what you are going to build is a war project.  Then project properties are set like the group, version, description or Java compilation options. Finally only one dependency is required and with provided scope since the implementation is provided by the application server.

Note that providedCompile scope is only available if you are using the war plugin. If you are using another plugin like java, then you will need to implement this function by yourself (at least at the time of writing this post with Gradle  2.7).

And that's all, pretty compact, only 16 lines and no verbose information. Of course, now you will need to add more dependencies like JUnit or Arquillian with testCompile scope or any other extra library required in your code like the well known apache-commons dependency; But this is an story for another post.

We keep learning,

Sun's in your eyes the heat is in your hair. They seem to hate you. Because you're there.  (Wonderful Life - Black)

martes, agosto 11, 2015

Arquillian Cube: Write Tests Once, Run Them Everywhere

Arquillian Cube is an Arquillian extension that can be used to manage Docker containers from Arquillian. Basically it starts all Docker containers required for your tests, deploys the application (or micro-application) which can be Java based or not, runs the tests and finally stops all of them.

Thanks of Arquillian Cube you can run your integration tests from your local IDE in similar situation as in production environment since in both cases everything is running inside Docker.

But you can go one step forward and you can instruct Arquillian Cube to not start Docker container instances locally (or inside your local boot2docker) but start them in external locations such as your preproduction infrastructure.

Thanks of Digital Ocean that has provided us a free account with some money, we can show you in next screencast how by simply changing one attribute (which could be automated with maven-resources-plugin or just using system properties), we are running the same test against local Docker instance or remotely to Digital Ocean infrastructure.

You can read more about Arquillian and Arquillian Cube in book Arquillian In Action (www.manning.com/sotobueno).

We keep learning,
You’re a shooting star I see, A vision of ecstasy, When you hold me, I’m alive, We’re like diamonds in the sky (Diamonds - Rihanna)
Music: https://www.youtube.com/watch?v=lWA2pjMjpBs

lunes, agosto 03, 2015

Arquillian in Action goes MEAP

Currently  I am co-writing Arquillian in Action book with my colleague Jason Porter. Last week the book just entered into MEAP stage.

Arquillian in Action teaches you how to to build in-container tests using Arquillian. This practical hands-on guide begins with showing you how to find and squash your first bug. You'll move on to building persistence tests, and then discover how to write tests for front-end and RESTful services. Using carefully-designed examples, the book shows you how to write integration tests for Java EE, Spring, and Docker. Along the way, you'll also learn how to build functional, infrastructure, performance, and security tests.

You can visit http://www.manning.com/sotobueno, read the first chapter for free or you can buy it and start reading the first three chapters of the book.

It is time to start zapping all these bugs with Arquillian.

We keep learning,

Algo lo que me invade, todo viene de dentro, Nunca lo que me sacie, siempre quiero, lobo hambriento. (Por la boca vive el pez - Fito & Fitipaldis)

Music:  https://www.youtube.com/watch?v=iUXs4Nt3Y7Y

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