1 Big Builds

Think of everything we have started to put into our automated builds:

• fetching and setup of 3rd party libraries
• static analysis
• compilation
• unit testing
• documentation generation
• static analysis reports
• packaging of artifacts
• deployment/publication of artifacts
• updating of project website

and, coming up, we will want to expand our testing to include

• integration testing
• test coverage reporting
• system testing

There’s a danger of the builds becoming so unwieldy and slow that programmers will start to look for ways to circumvent steps,

Do We Need to do All of Those Steps, All of the Time?

One possible breakdown:

This should provide someone actively working on a specific module/story the info they need, deferring some of the more time-consuming build activities.

How do we divide these steps in the build?

• Even the “occasional” activities may be done many times over the history of a project.

• So we want to keep them automated, both for ease of performing them and to ensure they are performed consistently each time.

• With make/ant/maven, we can have different targets/goals for the frequent and the occasional cases.

  • But we have to remember to use the proper targets at the right time.
    • Maybe not a bid deal…

• But there’s an opportunity here to do something much more interesting…

2 Continuous Integration

When we combine

• Automated testing (unit, integration, system, and regression)
• Centralized version control
  • or distributed VC with a central “official” repository
• Automated builds, capable of running tests, running analysis tools, and publishing the results on a project web site

we can rebuild and retest automatically as developers check in changes.

2.1 Key Ideas

Our project should have the characteristics:

• Version control with a clearly identified main branch or set of main development branches.

• Automated build is set up as usual.

• Developers commit frequently (maybe many times per day)

  • Commits to “private” branches (or local copies of a distributed repository) are ignored.
  • Every commit of a tracked branch to the main repository is built on a separate server
    • The build includes all integration-related tasks (for early detection of integration problems.
    • Can also include more time-consuming reporting tasks.

• Testing is done, ideally, in a clone of the production environment(s)

  • May differ from development environments
  • Probably not checked frequently under normal practice
  • Can use multiple remote machine “runners” to provide varying target operating systems and environments.

• Make the results highly visible

2.1.1 Advantages

2.2 Continuous Integration Systems

A CI system consists of a server/manager and one or more runners…

2.2.1 The Continuous Integration Server

A continuous integration server is a network-accessible machine that

• Can be told of development projects under way, including

  • location & access info to version control (VC) repository
  • which branch(es) to watch
  • how to build the project
  • what reports are produced by the build

• Monitors, in some fashion, the VC repository for commits

• When a commit (to a monitored branch) takes place, the CI server notifies one or more runners.

2.2.2 Continuous Integration Runners

A CI runner (a.k.a., nodes or slave processors) is a process on a machine that

• has the the necessary compilers and other tools for building a project.

• is managed by the CI server.

When notified by the server, the runner

1. Checks out a designated branch of a project from its version control system.

2. Runs the build.

3. Publishes reports on the results of the build(s).

• Runners are usually separate machines from the CI server.

• A CI project may launch several different runners, each with a different configuration environment (e.g., different operating systems) to test the build under multiple configurations.

3 Case study: Jenkins

3.1 Projects on Jenkins

When you set up a project on Jenkins you must supply:

• Basic project info:

  • name and description,
  • public/private,
  • who can access.

• Version control:

  • What kind of version control is used,
  • URL and access info to check out a copy of the project.

• Build management:

  • What build manager is used,
  • where the build file can be found within the project directories
  • what target/goal to use with the build

    (I usually add a special “jenkins” target to my Ant build.xml files.)

  • Which of Jenkin’s nodes can be used for the build.

• Reporting

  • What reports Jenkins should publish.
  • Where in your project directories the raw data for these reports can be found.

3.1.1 Jenkins and Project Reports

• Many report-generating programs (e.g., JUnit, FindBugs, etc.) have separate “collection” and “reporting” stages.

  • Typically the collection step writes raw data out in an XML format.

  • Normally, you then run a separate task to reformat that XML into HTML or some other readable format.

• Jenkins, however, has its own formatting functions for many common reports.

• Among other things, these often add “historical” reporting on how the collected data has varied over a period of time.

4 Case study: gitlab-ci

4.1 gitlab-ci setup

• Project must activate gitlab-ci by designating a runner, generally on a remote machine under the developer’s control.

• Add a file gitlab-ci.yml to the repository root directory.

  This is a YAML script that gets run after each new commit.

  Script can limit which branches it applies to

• Example:

  stages:
    - build
    - test
    - deploy
  
  build-job:
    tags:
      - atria
    stage: build
    script:
      - echo build number is $CI_BUILD_REF
      - cd report_accumulator
      - ./gradlew build deployReports -Dorg.gradle.project.buildNumber=$CI_BUILD_REF
  only:
      - master
  

• The “script:” part gives the build commands to be run on the runner machine.

• The “only” part limits these runs to checkins on the “master” branch.

4.2 gitlab-ci vs Jenkins

5 Related ideas