give me list of 20 question / answser about this "Pipeline as code with Jenkins
This chapter covers  How pipeline as code works with Jenkins  An overview of Jenkinsfile structure and syntax  Introduction to Blue Ocean, the new Jenkins user experience  Declarative versus scripted Jenkins pipelines  Integration of a GitFlow model within Jenkins projects  Tips for productivity and efficiency while writing Jenkinsfiles for complex CI/CD pipeline

There’s no doubt that cloud computing has had a major impact on the way companies build, scale, and maintain technology products. The ability to click a few buttons to provision machines, databases, and other infrastructure has led to an increase in developer productivity we’ve never seen before. 
→ cloud = increase agility in software teams 
While it was easy to spin up simple cloud architectures, mistakes can easily be made while provisioning complex ones. Human error will always be present, especially when you can launch cloud infrastructure by clicking buttons on the cloud provider’s web console.

The only way to avoid these kinds of errors is through automation, and infrastructure as code (IaC) is helping engineers automatically launch cloud environments quickly and without mistakes. The growth of DevOps and the adoption of its practices have led to more tooling that can implement the IaC paradigm to a larger degree.

 In the past, setting up CI/CD workflow has been a manual process. It was commonly done via defining a series of individual jobs for the various pipeline tasks. Each job was configured via web forms—filling in text boxes, selecting entries from dropdown lists, and so forth. And then the series of jobs were strung together, each triggering the next, into a pipeline.
Jenkins somewhat lagged in this area until the release of Jenkins 2. Although widely used and a primary workflow tool for creating CI/CD pipelines, this way of creating and connecting Jenkins jobs to form a pipeline was challenging. It did not meet the definition of IaC. Job configurations were stored only as Extensible Markup Language (XML) files within the Jenkins configuration area. This meant that the files were not easily readable or directly modifiable. And the Jenkins application itself provided the user’s primary view and access to them.
NOTE Jenkins 2 is the name we are generally applying to newer versions that support the pipeline-as-code functionality, as well as other features. 
→ from jenkins 2 version the concept of pipeline as code is introduced 

Introducing the Jenkinsfile Pipeline as code (PaC) describes a set of features that allow Jenkins users to define pipelined job processes with code, stored and versioned in a source repository. These features allow Jenkins to discover, manage, and run jobs for multiple source repositories and branches—eliminating the need for manual job creation and management.

PaC helps you automate the CI/CD workflows in a repeatable, consistent manner, which has many benefits:  Speed—You can quickly and easily write a CI/CD workflow for sandbox, staging, and production environments, which can help you deliver your product on time.  Consistency—PaC completely standardizes the setup of CI/CD, so there’s a reduced possibility of any human errors or deviations.  Risk management—Because the pipeline can be version-controlled, PaC allows every change to your CI/CD workflow to be documented, logged, tracked, and tested just like application code. Hence, you can revert to a working version in case of failure.  Efficiency—It minimizes the introduction of human errors and helps your application’s deployment run more smoothly.

The bottom line is simple: adopting the PaC paradigm will create a culture that generates better software, and will save you a lot of money, time, and headaches trying to implement complex CI/CD workflows through UIs and web forms. So how does PaC work with Jenkins?
→ adopting Pac paradigm will create a culture that generates better software 
→ save mony 
→ save times 
—> and headaches 
The core ideas presented about using Pipeline as Code (PaC) with Jenkins are:
Jenkinsfile for PaC: Projects using Jenkins for CI/CD should have a Jenkinsfile at the root of their repository. This file defines the pipeline.
Stages Define the Pipeline: The Jenkinsfile contains stages, which are the individual steps or tasks in the CI/CD process (e.g., build, test, deploy).
Automated Pipeline Execution: Whenever code is pushed to the repository, Jenkins automatically executes the pipeline defined in the Jenkinsfile. This is the core of continuous integration.
Jenkinsfile Under Version Control: The Jenkinsfile lives alongside the source code and is treated like any other code file. This enables:
Versioning: Track changes to the pipeline process itself.
Collaboration: Multiple developers can work on and improve the pipeline.
Rollback: Revert to earlier versions of the pipeline if necessary.


Code Reviews for Pipelines: Just like application code, the Jenkinsfile can undergo code reviews. This ensures quality, consistency, and best practices in the pipeline definition.
In essence, the passage emphasizes that using a Jenkinsfile brings the CI/CD pipeline under version control, making it more manageable, collaborative, and reliable. It treats the pipeline as code, subject to the same best practices as application code.
Jenkinsfile uses a domain-specific language (DSL) based on the Groovy programming language to define the entire CI/CD workflow. Figure 2.1 is an example of a classic CI/CD workflow.
—> Jenkinsfile use domain-specific language (DSL) based on the Groovy programming language 
Those phases can be described in a Jenkinsfile by using the stage keyword. A stage is a block that contains a series of steps. It can be used to visualize the pipeline process. The following listing is an example of a simple Jenkinsfile for figure 2.1.
→ stage is a block that contains a series of steps ,
→ it can be visualize as the pipeline process 
The following listing is an example of a simple Jenkinsfile for figure 2.1. node('workers'){ try { stage('Checkout'){ checkout scm } stage('Quality Test'){ echo "Running quality tests" } stage('Unit Test'){ echo "Running unit tests" } stage('Security Test'){ echo "Running security checks" } stage('Build'){ echo "Building artifact" } stage('Push'){ echo "Storing artifact" } Listing 2.1 Jenkinsfile stages 24 CHAPTER 2 Pipeline as code with Jenkins stage('Deploy'){ echo "Deploying artifact" } stage('Acceptance Tests'){ echo "Running post-integrations tests" } } catch(err){ echo "Handling errors" } finally{ echo "Cleaning up" } } We’ll dive deep into the syntax in the next chapter, but for now, let’s focus on what the stages are doing:  Checkout—Pulls the latest changes from the source code repository, which can be GitHub, Bitbucket, Mercurial, or any SCM.  Quality tests—Contains instructions on how to execute static code analysis to measure code quality, and identify bugs, vulnerabilities, and code smell. It can be automated by integrating external tools like SonarQube to fix code-quality violations and reduce technical debt.  Unit tests—In this stage, unit tests are executed. If tests are successful, a code coverage report will be generated that can be consumed by Jenkins plugins to show a visual overview of the project’s health and keep track of the code coverage metrics as your project grows. Code coverage can be an indication of how much your application code is executed during your tests, and can give some indication as to how well your team is applying good testing practices such testdriven development (TDD) or behavior-driven development (BDD).  Security tests—Responsible for identifying project dependencies and checks if any known, publicly disclosed vulnerabilities exist. A security report will be published with the total number of findings grouped by severity (critical, high, medium, or low). A well-known open source Jenkins plugin is OWASP Dependency-Check (http://mng.bz/MvR7).  Build—In this phase, the needed dependencies will be installed, the source code will be compiled, and an artifact will be built (Docker image, zip file, Maven JAR, and so forth).  Push—The artifact built in the previous stage will be versioned and stored in a remote repository.  Deploy—In this stage, the artifact will be deployed to a sandbox/testing environment for quality assurance or to production after the user has approved the deployment.  Acceptance tests—After the changes are deployed, a series of smoke and validation tests will be executed against the deployed application to verify that the application is running as expected. The tests can be simple health checks with cURL commands or sophisticated API calls. Introducing the Jenkinsfile 25 If any of these stages throws an exception or error, the pipeline build’s status will be set to fail. This default behavior can be overridden by using try-catch blocks. The finally block can be used to clean up the Jenkins workspace (temporary files or build packages) or to execute post-script commands such as sending Slack notifications to alert the development team about the build status.

Q- just for the proof of concept using docker , spring boot , and jenkins give me step by step tutor from spring insilser inter running the pipeline how to create this demo  ?

One of the things that makes Jenkins a leader when it comes to CI tools is the ecosystem behind it. You can customize your Jenkins instance with free open source plugins. A must-have plugin is Pipeline Stage View (https://plugins.jenkins.io/pipeline-restapi), shown in figure 2.2. It allows you to have a visualization of your pipeline stages. This plugin is handy when you have complex build pipelines and want to track the progress of each stage. The pipeline output is organized as a matrix, with each row representing a run of the job, and each column mapped to a defined stage in the pipeline. When you run some builds, the stage view will appear with Checkout, Quality Test, Unit Test, Security Test, Build, Push, and Deploy columns, and one row per build showing the status of those stages. When hovering over a stage cell, you can click the Logs button to see log messages printed in that stage. NOTE Part 3 of this book covers how to create a Jenkins job and define a pipeline like the one in figure 2.2. Figure 2.2 Jenkins Pipeline Stage View 26 CHAPTER 2 Pipeline as code with Jenkins You can take this UI further and install the Blue Ocean plugin (https://plugins .jenkins.io/blueocean/) to have a fast and intuitive comprehension of the CI/CD stages, as shown in figure 2.3. This plugin requires Jenkins version 2.7 or later. Figure 2.3 Blue Ocean plugin’s detailed view of the pipeline NOTE Chapter 5 covers how to install and configure the Jenkins Blue Ocean plugin.

***************

Blue Ocean plugin You can also troubleshoot pipeline failure by clicking the stage in red to easily identify the problem without going through thousands of output logs. One of the big concerns while choosing Jenkins is the user interface, which many users consider outdated, unintuitive, and hard to navigate when you have many projects. That’s why the Jenkins core team launched Blue Ocean in April 2017 for a new, modern Jenkins user experience. Blue Ocean is a new user experience for Jenkins, based on a modern design that allows users to graphically create, personalize, visualize, and diagnose CD pipelines. It comes bundled with the Jenkins Pipeline plugin or as a separate plugin (www.jenkins .io/doc/book/blueocean/getting-started/). NOTE The Jenkins Classic UI exists side-by-side at its usual place at JENKINS_ URL/jenkins. The Blue Ocean plugin is available by appending /blue to the end of the Jenkins server URL. Anyone in your team can create a CI/CD pipeline with just several clicks. Blue Ocean has seamless integration with Git and GitHub. It prompts you for credentials to access Introducing the Jenkinsfile 27 your repositories on the Git server in order to create pipelines based on those repositories (figure 2.4). You can also create a complete CI/CD pipeline from start to finish by using the intuitive and visual pipeline editor (figure 2.5). It’s a great way to write pipeline prototypes and debug pipeline stages before generating a working Jenkinsfile. Figure 2.5 Defining stages with pipeline editor Figure 2.4 New pipeline in Blue Ocean mode 28 CHAPTER 2 Pipeline as code with Jenkins Any pipeline created with the visual editor can also be edited in your favorite text editor, bringing all the benefits of PaC. Figure 2.6 shows an example of the pipeline script generated by pressing Ctrl-S for Windows users and Command-S for macOS users. You can now copy the content and paste it in a new file called Jenkinsfile in your code repository, alongside the source code. Alternatively, you can upload the file directly from the Blue Ocean editor by supplying an appropriate description and the target Git branch (figure 2.7). Figure 2.6 Jenkinsfile generated from the pipeline editor Figure 2.7 Committing the Jenkinsfile to the Git repository Introducing the Jenkinsfile 29 Once the file is committed, the pipeline will be triggered, and the stages defined in the pipeline will be executed. Keep in mind that Blue Ocean doesn’t support all features of Jenkins such as administration, nodes management, or credential settings. However, you can always switch back to the classic Jenkins UI by clicking the exit icon at the top right of the Blue Ocean navigation bar. NOTE This is just a sneak peek of Blue Ocean’s main features. In chapter 7, we will dig deeper into each feature. Now that you’re familiar with how a Jenkinsfile works, let’s see how to write your own pipeline as code with Jenkins. Jenkins 2 allows two styles of structure and syntax for building out workflows. These are referred to as scripted and declarative pipelines.

Scripted pipeline A scripted pipeline is a traditional way of writing pipeline code. In this pipeline, the Jenkinsfile is written on the Jenkins UI instance. The pipeline steps are wrapped in a node block (denoted by the opening and closing braces). Here, a node refers to a Jenkins agent (formerly referred to as a slave instance). The node gets mapped to the Jenkins cluster by using a label. A label is simply an identifier that has been added when configuring the node in Jenkins via the Manage Nodes section, as shown in figure 2.8. Figure 2.8 Assigning labels to Jenkins workers NOTE The next chapter covers how the Jenkins distributed mode works and how node agents can be used to offload work from Jenkins. The steps inside the node block can include and make use of any valid Groovy code. The pipeline can be defined by creating a new pipeline project and typing the code in the Pipeline Editor section, as shown in figure 2.9. 30 CHAPTER 2 Pipeline as code with Jenkins Figure 2.9 Using an inline Jenkinsfile with Pipeline scripts Although this simple node block is technically valid syntax, Jenkins pipelines generally have a further level of granularity—stages. A stage is a way to divide the pipeline into logical functional units. It also serves to group steps and Groovy code together to create targeted functionality. Figure 2.10 shows an example of the preceding pipeline using stages. Figure 2.10 Using the stage keyword to define logical units Introducing the Jenkinsfile 31 The pipeline has two stages:  Checkout—For cloning the project GitHub repository  Build—For building the project Docker image How much of the pipeline’s logic goes into a particular stage is up to the developer. However, the general practice is to create stages that mimic the separate pieces of a traditional pipeline. The scripted pipeline uses stricter Groovy-based syntaxes because it was the first pipeline to be built on the Groovy foundation. Since this Groovy script was not typically desirable to all users, the declarative pipeline was introduced to offer a simpler and more optioned Groovy syntax. NOTE Chapter 14 covers how to write a shared Jenkins library with custom Groovy scripts for code modularity

 Declarative pipeline
A declarative pipeline is a relatively new feature (introduced in Pipeline 2.5, https://
plugins.jenkins.io/workflow-aggregator) that supports the PaC approach. It makes
the pipeline code easier to read and write for new Jenkins users.
 This code is written in a Jenkinsfile that can be checked into a version-control system (VCS) such as SVN or an SCM system such as GitHub, GitLab, Bitbucket, or others. Figure 2.11 is an example of a Jenkinsfile located at the root folder of a GitHub
repository.
Figure 2.11 A Jenkinsfile stored in a source-control repository
32 CHAPTER 2 Pipeline as code with Jenkins
In declarative syntax, you cannot use Groovy code such as variables, loops, or conditions. You are restricted to the structured sections/blocks and the DSL (Jenkins
domain-specific language) steps.
 Figure 2.12 shows the differences between scripted and declarative pipelines.
Declarative pipelines are restricted and have well-defined structures (for example, all
DSL statements must be enclosed in a steps directive).
Figure 2.12 Differences between scripted and declarative pipelines
node('node label'){
stage('id #1'){
//DSL statements
}
stage('id #2'){
//DSL statements
}
// OR
//DSL statements without stage block
// OR
//Loops, conditions, variables, etc
def variable = value
if(variable){
//DSL statements
}else{
//DSL statements
}
def list = []
for(int i=0;i<list.size();i++){
//DSL statements
}
}
pipeline{
agent{
label 'node label'
}
environment{
ENV_VARIABLE_A = 'va
}
stages{
stage('id #1'){
agent{
label 'node label 1
}
environment{}
steps{
//DSL statements
}
}
stage('id #2'){
agent{
label 'node label 2
}
environment{}
steps{
//DSL statements
}
}
}
post {
always {
//DSL statements
}
success {
//DSL statements
}
failure {
//DSL statements
}
}
}
Scripted Declarative
Introducing the Jenkinsfile 33
Declarative pipelines provide a more restrictive syntax, as each pipeline must use
these predefined block attributes or sections:
agent
environment
post
stages
steps
The agent section defines the worker or machine where the pipeline will be executed. This section must be defined at the top level inside the pipeline block or overridden at the stage level. The agent can be any of the following:
Jenkins worker or node (refer to chapter 3 for distributed builds on Jenkins)
Docker container based on a Docker image or a custom Dockerfile (covered in
chapter 9)
Pod deployed on a Kubernetes cluster (covered in chapter 14)
For example, you can define the pipeline to run on a custom Docker container, as
shown in the following listing.
pipeline{
 agent {
 node {
 label 'workers'
 }
 dockerfile {
 filename 'Dockerfile'
 label 'workers'
 }
 kubernetes {
 label 'workers'
 yaml """
 kind: Pod
 metadata:
 name: jenkins-worker
 spec:
 containers:
 - name: nodejs
 image: node:lts
 tty: true
 """
 }
 }
}
NOTE Refer to the official documentation for more information about the
agent syntax: www.jenkins.io/doc/book/pipeline/syntax/.
Listing 2.2 Declarative pipeline agents definition
34 CHAPTER 2 Pipeline as code with Jenkins
The environment section contains a set of environment variables needed to run the
pipeline steps. The variables can be defined as sequences of key-value pairs. These will
be available for all steps if the environment block is defined at the pipeline top level;
otherwise, the variables can be stage-specific. You can also reference credential variables by using a helper method credentials(), which takes as a parameter the ID of
the target credential, as shown in the following listing.
pipeline{
 environment {
 REGISTRY_CREDENTIALS= credentials('DOCKER_REGISTRY')
 REGISTRY_URL = 'https://registry.domain.com'
 }
 stages {
 stage('Push'){
 steps{
 sh 'docker login $REGISTRY_URL --username
$REGISTRY_CREDENTIALS_USR --password $REGISTRY_CREDENTIALS_PSW'
 }
 }
 }
}
The Docker registry username and password are accessible automatically by referencing the REGISTRY_CREDENTIALS_USR and REGISTRY_CREDENTIALS_PSW environment variables. Those credentials are then passed to the docker login command to
authenticate with the Docker Registry before pushing a Docker image.
 The post section contains commands or scripts that will be run upon the completion of a pipeline or stage run, depending on the location of this section within the
pipeline. However, conventionally the post section should be placed at the end of the
pipeline. Examples of commands that can be used within the post section are those
that provide Slack notifications, clean up the job workspace, and execute post-scripts
based on the build status. The pipeline build status can be fetched by using either the
currentBuild.result variable or the post-condition blocks always, success,
unstable, failure, and so forth.
 The following listing is an example Slack notification. The instructions wrapped by
the always directive will run no matter the status of the build and will not interfere
with the final status.
pipeline{
 post {
 always {
 echo 'Cleaning up workspace'
 }
Listing 2.3 Environment variables definition
Listing 2.4 Post build actions in a declarative pipeline
Introducing the Jenkinsfile 35
 success {
 slackSend (color: 'GREEN', message: \
 "${env.JOB_NAME} Successful build")
 }
 failure {
 slackSend (color: 'RED', message: "${env.JOB_NAME} Failed build")
 }
 }
}
This code references the env.JOB_NAME variable, which contains the Jenkins job name.
NOTE Chapter 10 has a dedicated section on how to implement Slack notifications with Jenkins.
The stages section is the core of the pipeline. This section defines what is to be done
at a high level. It contains a sequence of more stage directives for each discrete part of
the CI/CD workflow.
 Finally, the steps section contains a series of more steps to be executed in a given
stage directive. The following listing defines a Test stage with instructions to run unit
tests and generate code coverage reports.
pipeline{
 agent any
 stages {
 stage('Test'){
 steps {
 sh 'npm run test'
 sh 'npm run coverage'
 }
 }
 }
}
These are the most used directives and sections while writing a declarative pipeline.
Additional directives will be covered throughout this book. For an overview of all available blocks, refer to Pipeline Syntax documentation (www.jenkins.io/doc/book/pipe
line/syntax/#stages).
 Both declarative and scripted styles can be used to build CI/CD pipelines in either
the web UI or with a Jenkinsfile. However, it’s generally considered a best practice to
create a Jenkinsfile and check it into the source-control repository to have a single
source of truth and be able to track all changes (auditing) that your pipeline went
through.
NOTE In chapters 7 through 11, you will learn how to write a scripted pipeline from scratch for various application architectures and how to convert a
Jenkinsfile from a scripted to a declarative format.

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