Jenkins: Freestyle vs pipeline jobs

Let’s look at some of the differences between Jenkins freestyle and pipeline jobs.

Freestyle Jobs

You configure a freestyle job in Jenkins using the GUI by adding steps to the build. Freestyle jobs give you a lot of flexibility. But, you will struggle to configure complex continuous delivery scenarios.

Pipeline Jobs

Pipeline jobs allow you to create a set of instructions using code. You can also easily visualize different stages in one place. Most importantly, you can keep all the code stored in a code repository. This will, in turn, allow you to version, audit, and keep track of changes.

Pipeline jobs are created using a Jenkinsfile. And Jenkinsfiles uses Apache Groovy as the scripting language.

A Jenkinsfile can use either of the following two syntaxes:

  • Declarative Pipelines – The declarative pipeline requires the Blue Ocean plugin. This plugin provides a graphical pipeline editor.
  • Scripted Pipelines – The scripted pipeline allows you to use the Jenkinsfile. But here you can use standard Jenkins.

Also, a Jenkins pipeline consists of many components.

These are:

  • Steps are single tasks that tell Jenkins what to do.
  • Stages groupings of steps like build, test and deploy.

For example, we can have a stage called “test”. And the “test” can, in turn, run many steps to test our code, the deployments, and more.

Wrapping up Jenkins freestyle vs pipeline jobs

As you can see, you set up freestyle jobs in Jenkins with the GUI. But, you use pipeline jobs to code more complex jobs using Jenkisfiles.

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Having started his career in 1999 as a Desktop Support Engineer, Anto soon changed paths and became a developer. After several years of development experience, he transitioned into a consultant. As an enterprise application consultant for a leading SaaS software provider, Anto specializes in AWS's serverless technologies. By day, Anto focuses on helping customers leverage the power of serverless technologies. By night, he indulges his passion for cloud computing by playing with Python and trying out things that are currently beyond the scope of his work. Sometimes Anto needs help as there are not enough hours at night. So Anto relies on a team of fellow Cloud enthusiasts to help him out. Each one is a Cloud expert in their own right, and Anto takes great pride in helping them learn and grow.

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