#PROJECT BRUTALITY 3.0 TEST BUILD HOW TO#
#PROJECT BRUTALITY 3.0 TEST BUILD INSTALL#
#PROJECT BRUTALITY 3.0 TEST BUILD SOFTWARE#
#PROJECT BRUTALITY 3.0 TEST BUILD CODE#

You'll also want to download and install Apache Tomcat.

The WAR file can be deployed to any servlet container. Because I'm on a Mac, the install automatically downloaded a pkg file, which placed a jenkins.war in my Application/Jenkins folder. Start by downloading Jenkins and selecting the Long-Term Support (LTS) release from the Jenkins homepage.

#PROJECT BRUTALITY 3.0 TEST BUILD HOW TO#

I'll show you how to setup both the local install and the Docker test installation.

Setup Jenkins in a test installation using Docker.

Leverage a Jenkins cloud provider such as CloudBees.

Setup a virtual machine in a public cloud like AWS and host Jenkins there.

Download a WAR file and install it on a servlet container on your local computer.

You customize the delivery pipeline depending on your need. It consists of an automation engine and a plugin ecosystem that supports continuous integration, automated testing, and continuous delivery. Jenkins is a continuous integration server and more. Jenkins is probably the most popular CI/CD product, and it pairs well with Docker. In some environments, CD goes all the way to production.Д¬ontinuous Integration is typically done using a tool like Jenkins, Bamboo, or TeamCity, which orchestrates your build steps into an integration pipeline. CI typically encompasses the building-and-testing phases of the development lifecycle, whereas CD extends that process to deploying a build artifact to a server for testing. These steps are all types of activities that you might perform as part of a CI/CD process.

Deploy your application to a User Acceptance Testing Environment (UAT).

Execute a load test against your application.

Deploy your application to a performance test environment.

Deploy your application to an integration test environment.

Publish your build artifacts to a repository, such as Artifactory or Sonatype Nexus.

#PROJECT BRUTALITY 3.0 TEST BUILD CODE#

Execute static code analysis, such as code coverage, code complexity, checks for common bugs, etc.

Merge your feature branch back into your main or master branch once the committed code passed the unit test.

While the source code was being built, the server could execute any number of additional actions: In a typical Maven build configuration, it would execute a fresh set of unit tests as part of the build command. On detecting code changes, your CI server could respond by executing a mvn clean install. Take a Java application built using Maven as an example. For continuous integration to work, you need a CI server like Jenkins, which is able to monitor your source code repository for new changes and respond in configurable ways. In a continuous Integration process, code that has been checked into a source code repository can be automatically checked out, built, tested in a variety of ways, and published to a repository. You'll also install and run a handful of popular Jenkins plugins for static code analysis testing and reporting. You'll learn how to build and unit test the project in Jenkins with JUnit, as well as how to troubleshoot build failures. We'll begin with an overview of the CI and CD process, then setup a Java web project using Maven and Jenkins. This installment of Open source Java projects introduces continuous integration with Jenkins, a leading automation server for CI/CD.

#PROJECT BRUTALITY 3.0 TEST BUILD SOFTWARE#

Whatever the designation, CD is a process that moves software from code check-in to staging, or even production deployments. These days many dev teams have moved beyond CI to CD, which stands for either continuous delivery or continuous deployment. It's no exaggeration to say that CI tamed the 'build' side of the build-and-deploy cycle. With continuous integration we could detect errors more quickly and release code much faster than we had done in previous years. Many test-driven developers also started doing integration testing and performance testing in a secondary CI process. With these techniques we could automatically build source code whenever a developer checked it into a source repository, executing an exhaustive unit test suite to ensure that an application was working properly. Over a decade ago, agile developers began to embrace and promote test-driven development and continuous integration (CI). The most consistent thing about this style of development was inconsistency-in process and in results. When the dev team was satisfied with the build, we would manually deploy the application into production. In those days, a software development lifecycle consisted of running builds on a local machine, manually copying the artifacts to a staging server, and manually testing each application through multiple iterations. Looking back at how software was built and deployed even 15 years ago, it seems surprising that our applications actually worked.

Project brutality 3.0 test build