#Pipelines

A Pipeline is a collection of Tasks that execute in a defined order to implement a CI/CD workflow. Pipelines define the execution flow of Tasks, including their dependencies, parameters, and workspaces, allowing you to create complex automation workflows.

#Why Pipelines are Needed

#Traditional CI/CD Challenges

Traditional CI/CD systems often face challenges in creating complex workflows:

• Complexity Management: Difficulty in managing dependencies between different stages
• Reusability: Limited ability to reuse workflow components across projects
• Flexibility: Constraints in adapting workflows to different requirements
• Visibility: Limited insight into workflow execution and progress

#Tekton's Solution

Tekton Pipelines address these challenges by:

• Declarative Definition: Pipelines are defined as Kubernetes Custom Resources
• Task Orchestration: Pipelines manage the execution order and dependencies between Tasks
• Data Sharing: Pipelines facilitate data sharing between Tasks through Workspaces and Results
• Reusability: Pipeline components can be shared and reused across projects
• Flexibility: Pipelines support conditional execution and dynamic parameters

#Advantages

• Modularity: Break down complex workflows into reusable Tasks
• Dependency Management: Define clear dependencies between Tasks
• Parallelism: Execute independent Tasks concurrently
• Conditional Execution: Run Tasks based on conditions
• Result Sharing: Pass data between Tasks through Results
• Workspace Sharing: Share files and data between Tasks through Workspaces
• Reusability: Create reusable workflow templates

#Scenarios

Pipelines are useful in various scenarios, including:

• CI/CD Workflows: Building, testing, and deploying applications
• Multi-environment Deployments: Deploying to development, staging, and production
• Complex Build Processes: Managing dependencies between build steps
• Release Management: Coordinating release activities across multiple components
• Infrastructure Automation: Orchestrating infrastructure provisioning and configuration

#Pipeline Execution Model

When a Pipeline is executed through a PipelineRun:

1. Tekton analyzes the Pipeline to determine the execution order of Tasks
2. Tasks with no dependencies start executing immediately
3. Tasks with dependencies wait until their dependencies complete
4. Tasks that can run in parallel execute concurrently
5. The Pipeline completes when all Tasks have completed or when a critical Task fails

#Key Concepts

#Task Dependencies

Tasks in a Pipeline can depend on each other in two ways:

1. Ordering Dependencies: Using the runAfter field to specify that a Task should run after another Task
2. Data Dependencies: When one Task uses the Results of another Task

Example:

apiVersion: tekton.dev/v1
kind: Pipeline
metadata:
  name: order-tasks
spec:
  tasks:
    - name: task1
      taskRef:
        name: task1
    - name: task2
      taskRef:
        name: task2
      runAfter:
        - task1
      params:
        - name: param1
          value: "$(tasks.task1.results.result)"
    - name: task3
      taskRef:
        name: task3
      params:
        - name: param1
          value: "$(tasks.task2.results.result)"

#Parameters

Parameters allow you to pass values to a Pipeline during execution. They can be used to customize the behavior of Tasks within the Pipeline.

#Use Cases

• Configuring build options
• Specifying deployment targets
• Setting version numbers
• Controlling feature flags

#Principles

Parameters are:

• Declared in the Pipeline specification
• Passed when creating a PipelineRun
• Made available to Tasks within the Pipeline
• Can have default values

#Configuration Example

apiVersion: tekton.dev/v1
kind: Pipeline
metadata:
  name: build-and-deploy
spec:
  params:
    - name: image-name
      type: string
      description: The name of the image to build
    - name: environment
      type: string
      description: The environment to deploy to
      default: "development"
  tasks:
    - name: build
      taskRef:
        name: build-image
      params:
        - name: image
          value: "$(params.image-name)"

#Workspaces

Workspaces allow Tasks in a Pipeline to share data. They are declared at the Pipeline level and then mapped to individual Tasks.

#Use Cases

• Sharing source code between Tasks
• Passing build artifacts between Tasks
• Sharing configuration files
• Maintaining state across Pipeline executions

#Principles

Workspaces in Pipelines are:

• Declared in the Pipeline specification
• Mapped to Task workspaces
• Bound to actual storage when creating a PipelineRun
• Can be shared between multiple Tasks

#Configuration Example

apiVersion: tekton.dev/v1
kind: Pipeline
metadata:
  name: build-test-deploy
spec:
  workspaces:
    - name: source-code
      description: The workspace containing the source code
  tasks:
    - name: fetch-source
      taskRef:
        name: git-clone
      workspaces:
        - name: output
          workspace: source-code
    - name: build
      taskRef:
        name: build-app
      workspaces:
        - name: source
          workspace: source-code
      runAfter:
        - fetch-source

#Results

Results allow Tasks to produce output values that can be consumed by other Tasks in the Pipeline.

#Use Cases

• Passing build version information
• Sharing generated artifact paths
• Communicating test results
• Passing deployment URLs

#Principles

Results in Pipelines are:

• Produced by Tasks
• Referenced using the $(tasks.taskName.results.resultName) syntax
• Used as inputs to subsequent Tasks
• Can be included in Pipeline results

#Configuration Example

apiVersion: tekton.dev/v1
kind: Pipeline
metadata:
  name: build-and-deploy
spec:
  tasks:
    - name: generate-version
      taskRef:
        name: semver
      results:
        - name: version
    - name: build
      taskRef:
        name: build-image
      params:
        - name: version
          value: "$(tasks.generate-version.results.version)"
      runAfter:
        - generate-version
  results:
    - name: build-version
      value: "$(tasks.generate-version.results.version)"

#Finally Tasks

Finally Tasks are executed after all other Tasks in the Pipeline have completed, regardless of success or failure. They are useful for cleanup operations or notifications.

#Use Cases

• Cleaning up resources
• Sending notifications
• Archiving logs
• Generating reports

#Principles

Finally Tasks:

• Run after all other Tasks have completed
• Run regardless of whether the Pipeline succeeded or failed
• Cannot depend on other Tasks
• Cannot be depended on by other Tasks

#Configuration Example

apiVersion: tekton.dev/v1
kind: Pipeline
metadata:
  name: build-test-deploy
spec:
  tasks:
    - name: build
      taskRef:
        name: build-app
    - name: test
      taskRef:
        name: run-tests
      runAfter:
        - build
  finally:
    - name: cleanup
      taskRef:
        name: cleanup-resources
    - name: notify
      taskRef:
        name: send-notification

#Conditional Execution

Tasks can be conditionally executed using the when field, which allows you to specify conditions based on Parameters or Results.

#Use Cases

• Deploying only on specific branches
• Running tests based on code changes
• Executing tasks based on user input
• Skipping tasks based on previous results

#Principles

Conditional execution:

• Is defined using the when field
• Can reference Parameters and Results
• Supports various operators (in, notin)
• Can combine multiple conditions

#Configuration Example

apiVersion: tekton.dev/v1
kind: Pipeline
metadata:
  name: build-test-deploy
spec:
  params:
    - name: environment
      type: string
  tasks:
    - name: build
      taskRef:
        name: build-app
    - name: deploy-to-production
      taskRef:
        name: deploy
      runAfter:
        - build
      when:
        - input: "$(params.environment)"
          operator: in
          values: ["production"]

#Constraints and Limitations

• Pipelines cannot have circular dependencies between Tasks
• A Pipeline cannot modify its own definition during execution
• Task Results must be produced before they can be consumed by other Tasks
• The size of Task Results is limited (typically to a few kilobytes)
• Pipelines have limited ability to handle dynamic Task creation

#References

• Tekton Pipelines Official Documentation
• Tekton Pipelines GitHub Repository
• Kubernetes Custom Resources