This document is intended for new users of the pipeline feature to learn how to write and understand pipelines.

Why Pipeline?

Pipeline (formerly known as Workflow) was built with the community’s requirements for a flexible, extensible, and script-based CD pipeline capability for Jenkins in mind. To that end, Pipeline:

Can support complex, real-world, CD Pipeline requirements: pipelines can fork/join, loop, parallel, to name a few
Is Resilient: pipeline executions can survive master restarts
Is Pausable: pipelines can pause and wait for human input/approval
Is Efficient: pipelines can restart from saved checkpoints
Is Visualized: Pipeline StageView provides status at-a-glance dashboards including trending

Getting Started

Before you begin, ensure you have the following installed or running:

You must be running Jenkins 1.580.1 or later (1.609.1+ for latest features).
Ensure Pipeline is installed: navigate to Plugin Manager, install Pipeline and restart Jenkins.

Note: If you are running CloudBees Jenkins Enterprise 14.11 or later, you already have Pipeline (plus additional associated features).

If you want to play with Pipeline without installing Jenkins separately (or accessing your production system), try running the Docker demo.

Creating a Pipeline

To create a pipeline, perform the following steps:

Click New Item, pick a name for your job, select Pipeline, and click OK.

You will be taken to the configuration screen for the Pipeline. The Script text area is important as this is where your Pipeline script is defined. We'll start with a trivial script:

echo 'hello from Pipeline'

Note: if you are not a Jenkins administrator, click the Use Groovy Sandbox option (read here to learn more about this option).

Save your pipeline when you are done.
Click Build Now to run it. You should see #1 under Build History.
Click ▾ and select Console Output to see the output:

Started by user anonymous
[Pipeline] echo
hello from Pipeline
[Pipeline] End of Pipeline
Finished: SUCCESS

Understanding Pipeline Scripts

A pipeline is a Groovy script that tells Jenkins what to do when your Pipeline is run. You do not need to know much general Groovy to use Pipeline - relevant bits of syntax are introduced as needed.

Example In this example, echo is a step: a function defined in a Jenkins plugin and made available to all pipelines. Groovy functions can use a C/Java-like syntax such as:

echo("hello from Pipeline");

You can drop the semicolon (;), drop the parentheses (( and )), and use single quotes (') instead of double (") if you do not need to perform variable substitutions.

Comments in Groovy, as in Java, can use single-line or multiline styles:

/*
 * Copyright 2014 Yoyodyne, Inc.
 */
// FIXME write this

Creating a Simple Pipeline

The following sections guide you through creating a simple Pipeline.

Setting Up

To set up for creating a Pipeline, ensure you have the following:

First, you need a Maven installation available to do builds with. Go to Jenkins » Manage Jenkins » Configure System, click Add Maven, give it the name M3 and allow it to install automatically.
Only if you do not have Git installed on your Jenkins server: click Delete Git on the default Git installation and Add Git » JGit to replace it.
Click Save.

Checking out and Building Sources

Now, click on your Pipeline and Configure it to edit its script.

node {
  git url: 'https://github.com/jglick/simple-maven-project-with-tests.git'
  def mvnHome = tool 'M3'
  sh "${mvnHome}/bin/mvn -B verify"
}

When you run this script:

it should check out a Git repository and run Maven to build it.
it will run some tests that might (at random) pass, fail, or be skipped. If they fail, the mvn command will fail and your Pipeline run will end with:

ERROR: script returned exit code 1
Finished: FAILURE

Modifying for Windows Variations

This documentation assumes Jenkins is running on Linux or another Unix-like operating system. If your Jenkins server (or, later, slave) is running on Windows, try using bat in place of sh, and use backslashes as the file separator where needed (backslashes do generally need to be escaped inside strings).

Example: rather than:

sh "${mvnHome}/bin/mvn -B verify"

you could use:

bat "${mvnHome}\\bin\\mvn -B verify"

Understanding Syntax

A node is a step that schedules a task to run by adding it to the Jenkins build queue.

As soon as an executor slot is available on a node (the Jenkins master, or a slave), the task is run on that node.
A node also allocates a workspace (file directory) on that node for the duration of the task (more on this later).

Groovy functions accept closures (blocks of code) and some steps expect a block. In this case, the code between the braces ({ and }) is the body of the node step. Many steps (such as: git and sh in this example) can only run in the context of a node, so trying to run just:

sh 'echo oops'

as a Pipeline script will not work: Jenkins does not know what system to run commands on.

Unlike user-defined functions, Pipeline steps always take named parameters. Thus:

git url: 'https://github.com/jglick/simple-maven-project-with-tests.git'

is passing one parameter named: url (the Git source code repository to check out). This parameter happens to be mandatory; it also takes some other optional parameters such as branch. You can pass as many as you need:

git url: 'https://github.com/jglick/simple-maven-project-with-tests.git', branch: 'master'

As before, Groovy lets you omit parentheses around function arguments. The named-parameter syntax is also a shorthand for creating a map, which in Groovy uses the syntax [key1: value1, key2: value2], so you could also write:

git([url: 'https://github.com/jglick/simple-maven-project-with-tests.git', branch: 'master'])

For convenience, when calling steps taking only one parameter (or only one mandatory parameter) you can omit the parameter name. For example:

sh 'echo hello'

is really shorthand for:

sh([script: 'echo hello'])

The tool step makes sure a tool with the given name (in this case, a specific version of the Maven build tool) is installed on the current node. But merely running this step does not do much good. The script needs to know where it was installed - so the tool can be run later. For this, you need a variable.

The def keyword in Groovy is the quickest way to define a new variable (with no specific type).

Here:

def mvnHome = tool 'M3'

ensures M3 is installed somewhere accessible to Jenkins and assigns the return value of the step (an installation path) to the mvnHome variable. You could also use a more Java-like syntax with a static type:

String mvnHome = tool("M3");

Finally, you run the Maven build. When Groovy encounters $ inside a double-quoted string:

"${mvnHome}/bin/mvn -B verify"

it replaces the ${mvnHome} part with the value of that expression (here, just the variable value). The more verbose Java-like syntax would be:

mvnHome + "/bin/mvn -B verify"

In the console output, you see the final command being run.

Example:

[Pipeline] Running shell script
+ /path/to/jenkins/tools/hudson.tasks.Maven_MavenInstallation/M3/bin/mvn -B verify

Managing the Environment

One way to use tools by default, is to add them to your executable path - by using the special variable env that is defined for all pipelines:

node {
  git url: 'https://github.com/jglick/simple-maven-project-with-tests.git'
  def mvnHome = tool 'M3'
  env.PATH = "${mvnHome}/bin:${env.PATH}"
  sh 'mvn -B verify'
}

Properties of this variable are environment variables on the current node.
You can override certain environment variables and the overrides are seen by subsequent sh steps (or anything else that pays attention to environment variables).
You can run mvn without a fully-qualified path.

Setting a variable such as PATH in this way is only safe if you are using a single slave for this build. As an alternative, you can use the withEnv step to set a variable within a scope:

node {
  git url: 'https://github.com/jglick/simple-maven-project-with-tests.git'
  withEnv(["PATH+MAVEN=${tool 'M3'}/bin"]) {
    sh 'mvn -B verify'
  }
}

Some environment variables are defined by Jenkins by default.

Example: env.BUILD_TAG can be used to get a tag like jenkins-projname-1 from Groovy code, or $BUILD_TAG can be used from a sh script.

See Help in the Snippet Generator for the withEnv step for more details on this topic.

Build Parameters

If you have configured your pipeline to accept parameters when it is built — Build with Parameters — they are accessible as Groovy variables of the same name.

Recording Test Results and Artifacts

Instead of failing the build if there are test failures, you want Jenkins to record them — and then proceed. If you want it saved, you must capture the JAR that you built.

node {
  git url: 'https://github.com/jglick/simple-maven-project-with-tests.git'
  def mvnHome = tool 'M3'
  sh "${mvnHome}/bin/mvn -B -Dmaven.test.failure.ignore verify"
  step([$class: 'ArtifactArchiver', artifacts: '**/target/*.jar', fingerprint: true])
  step([$class: 'JUnitResultArchiver', testResults: '**/target/surefire-reports/TEST-*.xml'])
}

If tests fail, the Pipeline is marked unstable (yellow ball), and you can browse the Test Result Trend to see the history.
You should see Last Successful Artifacts on the Pipeline index page.

Understanding Syntax

The Maven option -Dmaven.test.failure.ignore allows the mvn command to exit normally (status 0) — so that the Pipeline continues, even when test failures are recorded on disk.

Run the step step twice. This step allows you to use certain build (or post-build) steps already defined in Jenkins for use in traditional projects. It takes one parameter (called delegate but omitted here) — this parameter value is a standard Jenkins build step.

You could create the delegate using Java constructor/method calls, using Groovy or Java syntax:

def aa = new hudson.tasks.ArtifactArchiver('**/target/*.jar')
aa.fingerprint = true // i.e., aa.setFingerprint(true)
step aa

but this is cumbersome and does not work well with Groovy sandbox security — so any object-valued argument to a step may instead be given as a map.

The following:

[$class: 'ArtifactArchiver', artifacts: '**/target/*.jar', fingerprint: true]

specifies the values of the artifacts and fingerprint properties (controls what files to save and records fingerprints for them).
$class is used to pick the kind of object to create. It may be a fully-qualified class name (hudson.tasks.ArtifactArchiver), but the simple name may be used when unambiguous.

In some cases, part of a step configuration will force an object to be of a fixed class. Thus, $class can be omitted entirely.

Example: rather than using the simple git step, you can use the more general checkout step and specify any complex configuration supported by the Git plugin:

checkout scm: [$class: 'GitSCM', branches: [[name: '*/master']], userRemoteConfigs: [[url: 'https://github.com/jglick/simple-maven-project-with-tests']]]

Here, [[name: '*/master']]is an array with one map element, [name: '*/master'], which is an object of type hudson.plugins.git.BranchSpec, but we can omit $class: 'BranchSpec' since branches can only hold this kind of object. Similarly, the elements of userRemoteConfigs are declared to be of type UserRemoteConfig, so this need not be mentioned.

Using Slaves

Thus far, pipeline has run only on the Jenkins master - assuming you had no slaves configured. You can even force it to run on the master by telling the node step the following:

node('master') {
    // as before
}

Here, you pass a value for the optional label parameter of the step, as well as a body block.

To create a simple slave:

Select Manage Jenkins » Manage Nodes » New Node and create a Dumb Slave. Leave # of executors as 1.
Pick a Remote root directory such as /tmp/slave.
Enter remote in the Labels field and set the Launch method to Launch slave agents via Java Web Start.
Save, then click on the new slave and Launch.
Now, go back to your Pipeline definition and request this slave’s label:

node('remote') {
    // as before
}

The parameter may be a slave name, or a single label, or even a label expression such as:

node('unix && 64bit') {
    // as before
}

When you Build Now, you see:

Running on <yourslavename> in /<slaveroot>/workspace/<jobname>

and the M3 Maven installation being unpacked to this slave root.

Pausing: Flyweight vs. Heavyweight Executors

Pause the script to take a better look at what is happening:

node('remote') {
  input 'Ready to go?'
  // rest as before
}

The input step pauses Pipeline execution. Its default message parameter gives a prompt, which is shown to a human. You can, optionally, request information back.

When you run a new build, you see:

Running: Input
Ready to go?
Proceed or Abort

If you click Proceed, the build will proceed as before. First, go to the Jenkins main page and look at the Build Executor Status widget.

You will see an unnumbered entry under master named jobname #10; executors #1 and #2 on the master are idle.
You will also see an entry under your slave, in a numbered row (probably #1) called Building part of jobname #10.

Why are there two executors consumed by one Pipeline build?

Every Pipeline build itself runs on the master, using a flyweight executor — an uncounted slot that is assumed to not take any significant computational power.
This executor represents the actual Groovy script, which is almost always idle, waiting for a step to complete.
Flyweight executors are always available.

When you run a node step:

A regular heavyweight executor is allocated on a node (usually a slave) matching the label expression, as soon as one is available. This executor represents the real work being done on the node.
If you start a second build of the Pipeline while the first is still paused with the one available executor, you will see both Pipeline builds running on master. But only the first will have grabbed the one available executor on the slave; the other part of jobname #11 will be shown in Build Queue (1). (shortly after, the console log for the second build will note that it is still waiting for an available executor).

To finish up, click the ▾ beside either executor entry for any running Pipeline and select Paused for Input, then click Proceed (you can also click the link in the console output).

Allocating Workspaces

In addition to waiting to allocate an executor on a node, the node step also automatically allocates a workspace: a directory specific to this job — where you can check out sources, run commands, and do other work. Workspaces are locked for the duration of the step: only one build at a time can use a given workspace. If multiple builds need a workspace on the same node, additional workspaces are allocated.

Configure your slave, set # of executors to 2 and Save. Now start your build twice in a row. The log for the second build will show

Running on <yourslavename> in /<slaveroot>/workspace/<jobname>@2

The @2 shows that the build used a separate workspace from the first one, with which it ran concurrently. You should also have seen

Cloning the remote Git repository

since this new workspace required a new copy of the project sources.

You can also use the ws step to explicitly ask for another workspace on the current slave, without grabbing a new executor slot. Inside its body all commands run in the second workspace. The dir step can be used to run a block with a different working directory (typically a subdirectory of the workspace) without allocating a new workspace.

Adding More Complex Logic

Your Groovy script can include functions, conditional tests, loops, try/catch/finally blocks, and so on. Save this Pipeline definition:

node('remote') {
  git url: 'https://github.com/jglick/simple-maven-project-with-tests.git'
  def v = version()
  if (v) {
    echo "Building version ${v}"
  }
  def mvnHome = tool 'M3'
  sh "${mvnHome}/bin/mvn -B -Dmaven.test.failure.ignore verify"
  step([$class: 'ArtifactArchiver', artifacts: '**/target/*.jar', fingerprint: true])
  step([$class: 'JUnitResultArchiver', testResults: '**/target/surefire-reports/TEST-*.xml'])
}
def version() {
  def matcher = readFile('pom.xml') =~ '<version>(.+)</version>'
  matcher ? matcher[0][1] : null
}

Here, you use:

def keyword to define a function (you can also give a Java type in place of def to make it look more like a Java method)
=~ is Groovy syntax to match text against a regular expression
[0] looks up the first match
[1] the first (…) group within that match
readFile step loads a text file from the workspace and returns its content (do not try to use java.io.File methods — these will refer to files on the master where Jenkins is running, not in the current workspace).
There is also a writeFile step to save content to a text file in the workspace
fileExists step to check whether a file exists without loading it.

When you run the Pipeline you see:

Building version 1.0-SNAPSHOT

Note: Unless your Script Security plugin is version 1.11 or higher, you may see a RejectedAccessException error at this point. If so, a Jenkins administrator will need to navigate to Manage Jenkins » In-process Script Approval and Approve staticMethod org.codehaus.groovy.runtime.ScriptBytecodeAdapter findRegex java.lang.Object java.lang.Object. Then try running your script again and it should work.

Serializing Local Variables

If you tried inlining the version function as follows:

node('remote') {
  git url: 'https://github.com/jglick/simple-maven-project-with-tests.git'
  def matcher = readFile('pom.xml') =~ '<version>(.+)</version>'
  if (matcher) {
    echo "Building version ${matcher[0][1]}"
  }
  def mvnHome = tool 'M3'
  sh "${mvnHome}/bin/mvn -B -Dmaven.test.failure.ignore verify"
  step([$class: 'ArtifactArchiver', artifacts: '**/target/*.jar', fingerprint: true])
  step([$class: 'JUnitResultArchiver', testResults: '**/target/surefire-reports/TEST-*.xml'])
}

you would have noticed a problem:

java.io.NotSerializableException: java.util.regex.Matcher

This occurs because the matcher local variable is of a type (Matcher) not considered serializable by Java. Since pipelines must survive Jenkins restarts, the state of the running program is periodically saved to disk so it can be resumed later (saves occur after every step or in the middle of steps such as sh).
The “state” includes the whole control flow including: local variables, positions in loops, and so on. As such: any variable values used in your program should be numbers, strings, or other serializable types, not “live” objects such as network connections.
If you must use a nonserializable value temporarily: discard it before doing anything else. When you keep the matcher only as a local variable inside a function, it is automatically discarded as soon as the function returned.

You can also explicitly discard a reference when you are done with it:

node('remote') {
  git url: 'https://github.com/jglick/simple-maven-project-with-tests.git'
  def matcher = readFile('pom.xml') =~ '<version>(.+)</version>'
  if (matcher) {
    echo "Building version ${matcher[0][1]}"
  }
  matcher = null
  def mvnHome = tool 'M3'
  sh "${mvnHome}/bin/mvn -B -Dmaven.test.failure.ignore verify"
  step([$class: 'ArtifactArchiver', artifacts: '**/target/*.jar', fingerprint: true])
  step([$class: 'JUnitResultArchiver', testResults: '**/target/surefire-reports/TEST-*.xml'])
}

However the safest approach is to isolate use of nonserializable state inside a method marked with the annotation @NonCPS. Such a method will be treated as “native” by the Pipeline engine, and its local variables never saved. However it may not make any calls to Pipeline steps, so the readFile call must be pulled out:

node('remote') {
  git url: 'https://github.com/jglick/simple-maven-project-with-tests.git'
  def v = version(readFile('pom.xml'))
  if (v) {
    echo "Building version ${v}"
  }
  def mvnHome = tool 'M3'
  sh "${mvnHome}/bin/mvn -B -Dmaven.test.failure.ignore verify"
  step([$class: 'ArtifactArchiver', artifacts: '**/target/*.jar', fingerprint: true])
  step([$class: 'JUnitResultArchiver', testResults: '**/target/surefire-reports/TEST-*.xml'])
}
@NonCPS
def version(text) {
  def matcher = text =~ '<version>(.+)</version>'
  matcher ? matcher[0][1] : null
}

Here the logic inside the version function is run by the normal Groovy runtime, so any local variables are permitted.

Creating Multiple Threads

Pipelines can use a parallel step to perform multiple actions at once. This special step takes a map as its argument; keys are “branch names” (labels for your own benefit), and values are blocks to run.

To see how this can be useful, install a new plugin: Parallel Test Executor (version 1.6 or later). This plugin includes a Pipeline step that lets you split apart slow test runs. Also make sure the JUnit plugin is at least version 1.3+.

Now create a new pipeline with the following script:

node('remote') {
  git url: 'https://github.com/jenkinsci/parallel-test-executor-plugin-sample.git'
  archive 'pom.xml, src/'
}
def splits = splitTests([$class: 'CountDrivenParallelism', size: 2])
def branches = [:]
for (int i = 0; i < splits.size(); i++) {
  def exclusions = splits.get(i);
  branches["split${i}"] = {
    node('remote') {
      sh 'rm -rf *'
      unarchive mapping: ['pom.xml' : '.', 'src/' : '.']
      writeFile file: 'exclusions.txt', text: exclusions.join("\n")
      sh "${tool 'M3'}/bin/mvn -B -Dmaven.test.failure.ignore test"
      step([$class: 'JUnitResultArchiver', testResults: 'target/surefire-reports/*.xml'])
    }
  }
}
parallel branches

Note: to enable the Groovy sandbox on this script, be sure to update the Script Security plugin to version 1.11 or later. Even so, you may see a RejectedAccessException error at this point. If so, a Jenkins administrator will need to go to Manage Jenkins » In-process Script Approval and Approve staticMethod org.codehaus.groovy.runtime.ScriptBytecodeAdapter compareLessThan java.lang.Object java.lang.Object. Then try running your script again and it should work. A later version of the plugin may remove the need for this workaround.

When you run this Pipeline for the first time, it will check out a project and run all of its tests in sequence. The second and subsequent times you run it, the splitTests task will partition your tests into two sets of roughly equal runtime. The rest of the Pipeline then runs these in parallel — so if you look at trend (in the Build History widget) you will see the second and subsequent builds taking roughly half the time of the first. If you only have the one slave configured with its two executors, this won't save time, but you may have multiple slaves on different hardware matching the same label expression.

This script is more complex than the previous ones so it bears some examination. You start by grabbing a slave, checking out sources, and making a copy of them using the archive step:

archive 'pom.xml, src/'

is shorthand for the more general:

step([$class: 'ArtifactArchiver', artifacts: 'pom.xml, src/'])

Later, unarchive these same files back into other workspaces. You could have just run git anew in each slave’s workspace, but this would result in duplicated changelog entries, as well as contacting the Git server twice.

A Pipeline build is permitted to run as many SCM checkouts as it needs to, which is useful for projects working with multiple repositories, but not what we want here.
More importantly, if anyone pushes a new Git commit at the wrong time, you might be testing different sources in some branches - which is prevented when you do the checkout just once and distribute sources to slaves yourself.

The command splitTests returns a list of lists of strings. From each (list) entry, you construct one branch to run; the label (map key) is akin to a thread name, and will appear in the build log. The Maven project is set up to expect a file exclusions.txt at its root, and it will run all tests not mentioned there, which we set up via the writeFile step. When you run the parallel step, each branch is started at the same time, and the overall step completes when all the branches finish: “fork & join”.

There are several new ideas at work here:

A single Pipeline build allocates several executors, potentially on different slaves, at the same time. You can see these starting and finishing in the Jenkins executor widget on the main screen.
Each call to node gets its own workspace. This kind of flexibility is impossible in a freestyle project, each build of which is tied to exactly one workspace.The Parallel Test Executor plugin works around that for its freestyle build step by triggering multiple builds of the project, making the history hard to follow.

Do not use env in this case:

env.PATH = "${mvnHome}/bin:${env.PATH}"

because environment variable overrides are limited to being global to a pipeline run, not local to the current thread (and thus slave). You could, however, use the withEnv step as noted above.

You may also have noticed that you are running JUnitResultArchiver several times, something that is not possible in a freestyle project. The test results recorded in the build are cumulative.

When you view the log for a build with multiple branches, the output from each will be intermixed. It can be useful to click on the Pipeline Steps link on the build’s sidebar. This will display a tree-table view of all the steps run so far in the build, grouped by logical block, for example parallel branch. You can click on individual steps and get more details, such as the log output for that step in isolation, the workspace associated with a node step, and so on.

Creating Stages

By default, Pipeline builds can run concurrently. The stage command lets you mark certain sections of a build as being constrained by limited concurrency (or, later, unconstrained). Newer builds are always given priority when entering such a throttled stage; older builds will simply exit early if they are preëmpted.

A concurrency of one is useful to let you lock a singleton resource, such as deployment to a single target server. Only one build will deploy at a given time: the newest which passed all previous stages.

A finite concurrency ≥1 can also be used to prevent slow build stages such as integration tests from overloading the system. Every SCM push can still trigger a separate build of a quicker earlier stage as compilation and unit tests. Yet each build runs linearly and can even retain a single workspace, avoiding the need to identify and copy artifacts between builds. (Even if you dispose of a workspace from an earlier stage, you can retain information about it using simple local variables.)

Consult the Docker demo for an example of a Pipeline using multiple stages.

Loading Script Text from Version Control

Complex Pipelines would be cumbersome to write and maintain in the textarea provided in the Jenkins job configuration. Therefore it makes sense to load the program from another source, one that you can maintain using version control and standalone Groovy editors.

Building Entire Script from SCM

The easiest way to do this is to select Pipeline script from SCM when defining the pipeline.

In that case you do not enter any Groovy code in the Jenkins UI; you just indicate where in source code you want to retrieve the program. If you update this repository, a new build will be triggered, so long as your job is configured with an SCM polling trigger.

Triggering Manual Loading

For some cases, you may prefer to explicitly load Groovy script text from some source. The standard Groovy evaluate function can be used, but most likely you will want to load a Pipeline definition from a workspace. For this purpose, you can use the load step, which takes a filename in the workspace and runs it as Groovy source text.

The loaded file can contain statements at top level, which are run immediately. That is fine if you only want to use a single executor and workspace, and do not mind hard-coding the slave label in the Jenkins job. For more complex cases, though, you want to leave the external script in full control of slave allocation. In that case the main script defined in the job can just load and run a closure (block of code to be run later):

node {
    git '…'
    load 'pipeline.groovy'
}()

The subtle part here is that we actually have to do a bit of work with the node and git steps just to check out a source repository into a workspace so that we can load something. Once we have loaded the code, we exit the initial node block to release the temporary workspace, so it is not locked for the duration of the build. The return value of the load step also becomes the return value of the node step, which we run as a closure with the parentheses ().

Here pipeline.groovy could look like:

{ ->
  node('special-slave') {
    hello 'world'
  }
}
def hello(whom) {
  echo "hello ${whom}"
}

Note: While it can contain helper functions, the only code at top level is a Groovy Closure, which is the return value of the script, and thus of the main script’s load step.

The helper script can alternately define functions and return this, in which case the result of the load step can be used to invoke those functions like object methods. An older version of the Docker demo showed this technique in practice:

def pipeline
node('slave') {
    git '…'
    pipeline = load 'pipeline.groovy'
    pipeline.devQAStaging()
}
pipeline.production()

where pipeline.groovy defines devQAStaging and production functions (among others) before ending with

return this;

In this case devQAStaging runs on the same node as the main source code checkout, while production runs outside of that block (and in fact allocates a different node).

To reduce the amount of boilerplate needed in the master script, you can try the Workflow Remote File Loader plugin.

Retaining Global Libraries

Plugins inject function and class names into a Pipeline before it runs. The plugin bundled with Pipeline allows you to eliminate the above boilerplate and keep the whole script (except one “bootstrap” line) in a Git server hosted by Jenkins. A separate document has details on this system.

Creating Multibranch Projects

The Pipeline: Multibranch plugin offers a better way of versioning your Pipeline and managing your project. You need to create a distinct project type, Multibranch Pipeline.

When you have a multibranch pipeline, the configuration screen will resemble Pipeline script from SCM in that your Pipeline script comes from source control, not the Jenkins job configuration. The difference is that you do not configure a single branch, but a set of branches, and Jenkins creates a subproject for each branch it finds in your repository.

For example, if you select Git as the branch source (Subversion and Mercurial are also supported already), you will be prompted for the usual connection information, but then rather than a fixed refspec you will enter a branch name pattern (use the defaults to look for any branch). Jenkins expects to find a script named Jenkinsfile in branches it can build. From this script, the command checkout scm suffices to check out your project’s source code inside some node {}.

Say you start with just a master branch, then you want to experiment with some changes, so you git checkout -b newfeature and push some commits. Jenkins automatically detects the new branch in your repository and creates a new subproject for it—with its own build history unrelated to trunk, so no one will mind if it has red/yellow balls for a while. If you choose, you can ask for the subproject to be automatically removed after the branch is merged and deleted.

If you want to change your Pipeline script—for example, to add a new Jenkins publisher step corresponding to reports your Makefile/pom.xml/etc. is newly creating—you just edit Jenkinsfile in your change. The Pipeline script is always synchronized with the rest of the source code you are working on: checkout scm checks out the same revision as the script is loaded from.

Exploring the Snippet Generator

There are a number of Pipeline steps not discussed in this document, and plugins can add more. Even steps discussed here can take various special options that can be added from release to release. To browse all available steps and their syntax, a help tool is built into the Pipeline definition screen.

Click Snippet Generator beneath your script text area. You see a list of installed steps. Some will have a help icon () at the top which you can click to see general information. There are also UI controls to help you configure the step — in some cases with auto completion and other features found in Jenkins configuration screens. Click help icons to see all.

When you are done, click Generate Groovy to see a Groovy snippet that will run the step exactly as you have configured it. This lets you see the function name used for the step, the names of any parameters it takes (if not a default parameter), and their syntax. You can copy and paste the generated code right into your Pipeline, or use it as a starting point (perhaps trimming some unnecessary optional parameters).

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

TUTORIAL.md

TUTORIAL.md

Why Pipeline?

Getting Started

Creating a Pipeline

Understanding Pipeline Scripts

Creating a Simple Pipeline

Setting Up

Checking out and Building Sources

Modifying for Windows Variations

Understanding Syntax

Managing the Environment

Build Parameters

Recording Test Results and Artifacts

Understanding Syntax

Using Slaves

Pausing: Flyweight vs. Heavyweight Executors

Allocating Workspaces

Adding More Complex Logic

Serializing Local Variables

Creating Multiple Threads

Creating Stages

Loading Script Text from Version Control

Building Entire Script from SCM

Triggering Manual Loading

Retaining Global Libraries

Creating Multibranch Projects

Exploring the Snippet Generator

Files

TUTORIAL.md

Latest commit

History

TUTORIAL.md

File metadata and controls

Why Pipeline?

Getting Started

Creating a Pipeline

Understanding Pipeline Scripts

Creating a Simple Pipeline

Setting Up

Checking out and Building Sources

Modifying for Windows Variations

Understanding Syntax

Managing the Environment

Build Parameters

Recording Test Results and Artifacts

Understanding Syntax

Using Slaves

Pausing: Flyweight vs. Heavyweight Executors

Allocating Workspaces

Adding More Complex Logic

Serializing Local Variables

Creating Multiple Threads

Creating Stages

Loading Script Text from Version Control

Building Entire Script from SCM

Triggering Manual Loading

Retaining Global Libraries

Creating Multibranch Projects

Exploring the Snippet Generator