Description: The Jenkins Scripted Pipeline is a tool that allows developers to define and manage continuous integration and delivery (CI/CD) workflows in a more flexible and powerful way. Unlike declarative pipelines, which use a simpler and more structured syntax, the Scripted Pipeline employs a Groovy-based syntax, providing greater customization and control over the build and deployment process. This flexibility allows users to implement conditional logic, loops, and other programming structures, facilitating the creation of complex pipelines that adapt to the specific needs of various projects. Additionally, the use of scripts enables code reuse and the integration of various tools and services, optimizing workflow and improving development efficiency. In the context of Infrastructure as Code (IaC) and Configuration as Code (CaC), the Scripted Pipeline becomes an essential component for automating and versioning infrastructure and application configuration, ensuring that development, testing, and production environments are consistent and reproducible.
History: The concept of Pipeline in Jenkins was introduced in 2013 with the release of the ‘Pipeline’ plugin, allowing users to define CI/CD workflows more flexibly. Over time, two main approaches were developed: Declarative Pipeline and Scripted Pipeline. The Scripted Pipeline, based on Groovy, gained popularity for its customization and control capabilities, becoming a key tool for developers looking to implement complex workflows.
Uses: The Scripted Pipeline is primarily used in software development environments to automate build, test, and deployment processes. It allows development teams to define complex workflows that can include multiple stages, conditions, and task parallelization. It is also used to integrate third-party tools and manage infrastructure as code, facilitating the deployment of applications across different environments.
Examples: A practical example of using a Scripted Pipeline is automating the deployment process of a web application. In this case, the script may include stages to compile the code, run unit tests, create container images, and finally deploy the application to a production environment. Another example is integrating static code analysis tools, where the pipeline can run analyses at different stages of the development process.
