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Pipeline Groovy Plugin

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A key component of the Pipeline plugin suite, this provides the standard execution engine for Pipeline steps, based on a custom Groovy interpreter that runs inside the Jenkins master process.

(In principle other execution engines could be supported, with FlowDefinition being the API entry point, but none has been prototyped and it would likely be a very substantial effort to write one.)

Pipeline Groovy script code such as

retry(3) {
for (int i = 0; i < 10; i++) {
  branches["branch${i}"] = {
    node {
      retry(3) {
        checkout scm
      sh 'make world'
parallel branches

gets run as a Groovy program, with certain special function calls called steps performing Jenkins-specific operations. In this example the step parallel is defined in this plugin, while node, retry, checkout, and sh are defined in other plugins in the Pipeline suite. The scm global variable is defined in the Pipeline Multibranch plugin.

Unlike a regular Groovy program run from a command line, the complete state of a Pipeline build’s program is saved to disk every time an asynchronous operation is performed, which includes most Pipeline steps. Jenkins may be restarted while a build is running, and will resume running the program where it left off. This is not intended to be efficient, and so should be limited to high-level “glue” code directly related to Jenkins features; your project’s own build logic should be run from external programs on a build node, in a sh or bat step.

Known limitations

The Pipeline Groovy epic in JIRA covers some known limitations in the Groovy interpreter. These issues stem from the fact that Pipeline cannot run Groovy directly, but must intercept each operation to save the program state.

The Pipeline Sandbox epic covers issues with the Groovy sandbox used to prevent malicious Pipeline scripts from taking control of Jenkins. Scripts run with the sandbox disabled can make direct calls to Jenkins internal APIs, which can be a useful workaround for missing step functionality, but for security reasons only administrators can approve such scripts.

The Pipeline Snippet Generator epic covers issues with the tool used to provide samples of step syntax based on live configuration forms.

Technical design

The plugin uses the Groovy CPS library to implement a continuation-passing style transformation on the program as it is compiled. The standard Groovy compiler is used to create the AST, but generation of bytecode is intercepted by a CompilationCustomizer which replaces most operations with variants that throw a special “error”, CpsCallableInvocation. This is then caught by the engine, which uses information from it (such as arguments about to be passed to a method call) to pass control on to the next continuation.

Pipeline scripts may mark designated methods with the annotation @NonCPS. These are then compiled normally (except for sandbox security checks), and so behave much like “binary” methods from the Java Platform, Groovy runtime, or Jenkins core or plugin code. @NonCPS methods may safely use non-Serializable objects as local variables, though they should not accept nonserializable parameters or return or store nonserializable values. You may not call regular (CPS-transformed) methods, or Pipeline steps, from a @NonCPS method, so they are best used for performing some calculations before passing a summary back to the main script. Note in particular that @Overrides of methods defined in binary classes, such as Object.toString(), should in general be marked @NonCPS since it will commonly be binary code calling them.

Some kinds of objects are intrinsically not safe to serialize as such, yet we want to retain a reference to them in the program graph. An example is the Executor (~ executor slot on a master or agent node) which is part of the context passed by a node step to any step in its block, especially sh/bat. Pipeline uses the Pickle API to substitute serialization-safe versions of these objects. When a WorkflowRun is loaded from disk after a restart, the program state is deserialized, and pickles are deserialized (“rehydrated”) in parallel. If and when all pickles are successfully deserialized and the resulting objects placed back in the program state, the program begins running again, and StepExecution.onResume is called to restore timers and the like.

All program logic is run inside a “CPS VM thread”, which is just a Java thread pool that can run binary methods and figure out which continuation to do next. The parallel step uses “green threads” (also known as coöperative multitasking): it records logical thread (~ branch) names for various actions, but does not literally run them simultaneously. The program may seem to perform tasks concurrently, but only because most steps run asynchronously, while the VM thread is idle, and they may overlap in time. No Java thread is consumed except during the typically brief intervals when Groovy code is actually being run on the VM thread. The executor widget only displays an entry for the “flyweight” executor on the master node when the VM thread is busy; normally it is hidden.