Tekton

What is Tekton?

Tekton is a powerful, cloud-native, open-source framework for creating CI/CD systems. As a Kubernetes-native solution, Tekton enables you to build, test, and deploy across cloud providers and on-premises systems by abstracting away the underlying details. Born as an open-source project under the umbrella of the Continuous Delivery Foundation (CDF), Tekton has evolved into one of the most robust and flexible CI/CD platforms available in 2025.

Tekton leverages Kubernetes Custom Resource Definitions (CRDs) to define CI/CD pipeline components as code, providing a declarative approach to DevOps automation. It brings enterprise-grade features like security, compliance, observability, and multi-cloud portability to your CI/CD workflows, making it the preferred choice for organizations adopting cloud-native methodologies.

Why Choose Tekton in 2025?

  • Cloud-Native Architecture: Built from the ground up for Kubernetes environments

  • Vendor Neutral: Works across all major cloud providers (AWS, Azure, GCP) and on-premises

  • Supply Chain Security: Built-in support for SLSA compliance and software supply chain security

  • GitOps Ready: Seamless integration with GitOps workflows and ArgoCD

  • Enterprise Grade: Battle-tested in production by organizations like Google, IBM, Red Hat, and VMware

Key Features and Concepts (2025)

Core Components

1. Tasks The fundamental building blocks of a Tekton pipeline are tasks. Each task represents a specific unit of work, such as building code, running tests, or deploying an application. Tasks can be combined and reused across pipelines, promoting modularity and code sharing.

2. Pipelines Pipelines provide a way to orchestrate tasks in a specific order to create an end-to-end CI/CD workflow. With Tekton, you can define complex pipelines that include multiple stages, parallel execution, and conditional branching.

3. PipelineRuns and TaskRuns These are the runtime instances of Pipelines and Tasks. They represent the actual execution of your defined workflows with specific parameters and workspaces.

4. Workspaces Workspaces allow you to share files between tasks within a pipeline. They provide a mechanism for passing data and artifacts between different stages of the CI/CD workflow. Workspaces ensure isolation and reproducibility, making it easier to manage complex pipelines.

5. Parameters and Results Parameters enable dynamic configuration of tasks and pipelines at runtime, while Results allow tasks to output data that can be consumed by subsequent tasks.

New 2025 Features

Supply Chain Security (SLSA Compliance)

  • Built-in support for generating SLSA provenance

  • Signed task and pipeline execution attestations

  • Integration with Sigstore for keyless signing

Enhanced Security Model

  • Pod Security Standards enforcement

  • Service mesh integration (Istio, Linkerd)

  • RBAC templates for common use cases

Performance Improvements

  • Faster pipeline startup times (50% improvement over 2024)

  • Optimized resource scheduling

  • Better memory management for large pipelines

GitOps Integration

  • Native ArgoCD integration

  • Automated pipeline synchronization

  • Git-based pipeline definitions with auto-discovery

Tekton Architecture 2025

A task can consist of multiple steps, and pipeline may consist of multiple tasks. The tasks may run in parallel or in sequence

Real-World Examples (2025)

Example 1: AWS EKS CI/CD Pipeline with SLSA Compliance

This example demonstrates a complete CI/CD pipeline for deploying to AWS EKS with supply chain security features.

# aws-pipeline.yaml
apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: aws-eks-pipeline
  annotations:
    tekton.dev/description: "Complete CI/CD pipeline for AWS EKS with SLSA compliance"
spec:
  params:
    - name: git-url
      description: Git repository URL
      type: string
    - name: git-revision
      description: Git revision
      type: string
      default: main
    - name: image-tag
      description: Image tag to build
      type: string
    - name: aws-region
      description: AWS region
      type: string
      default: us-west-2
    - name: eks-cluster-name
      description: EKS cluster name
      type: string
  
  workspaces:
    - name: shared-data
    - name: aws-credentials
    - name: signing-secrets
  
  tasks:
    - name: git-clone
      taskRef:
        name: git-clone
        kind: ClusterTask
      params:
        - name: url
          value: $(params.git-url)
        - name: revision
          value: $(params.git-revision)
      workspaces:
        - name: output
          workspace: shared-data
    
    - name: security-scan
      taskRef:
        name: trivy-scanner
      runAfter:
        - git-clone
      params:
        - name: ARGS
          value: ["fs", "--security-checks", "vuln,secret,config"]
      workspaces:
        - name: manifest-dir
          workspace: shared-data
    
    - name: build-and-push
      taskRef:
        name: buildah
        kind: ClusterTask
      runAfter:
        - security-scan
      params:
        - name: IMAGE
          value: "$(params.image-tag)"
        - name: DOCKERFILE
          value: "./Dockerfile"
      workspaces:
        - name: source
          workspace: shared-data
    
    - name: sign-image
      taskRef:
        name: cosign-sign
      runAfter:
        - build-and-push
      params:
        - name: image
          value: "$(params.image-tag)"
      workspaces:
        - name: source
          workspace: shared-data
        - name: cosign-keys
          workspace: signing-secrets
    
    - name: generate-slsa-provenance
      taskRef:
        name: slsa-provenance
      runAfter:
        - sign-image
      params:
        - name: image
          value: "$(params.image-tag)"
        - name: git-url
          value: "$(params.git-url)"
        - name: git-revision
          value: "$(params.git-revision)"
      workspaces:
        - name: source
          workspace: shared-data
    
    - name: deploy-to-eks
      taskRef:
        name: aws-eks-deploy
      runAfter:
        - generate-slsa-provenance
      params:
        - name: cluster-name
          value: "$(params.eks-cluster-name)"
        - name: region
          value: "$(params.aws-region)"
        - name: image
          value: "$(params.image-tag)"
      workspaces:
        - name: source
          workspace: shared-data
        - name: aws-credentials
          workspace: aws-credentials

Example 2: Azure AKS Multi-Environment Pipeline

This pipeline demonstrates deploying to multiple Azure environments with approval gates.

# azure-pipeline.yaml
apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: azure-aks-multienv
  annotations:
    tekton.dev/description: "Multi-environment deployment to Azure AKS"
spec:
  params:
    - name: git-url
      type: string
    - name: git-revision
      type: string
      default: main
    - name: app-name
      type: string
    - name: registry-url
      type: string
    - name: dev-cluster
      type: string
    - name: prod-cluster
      type: string
    - name: resource-group
      type: string
  
  workspaces:
    - name: shared-workspace
    - name: azure-credentials
  
  tasks:
    - name: fetch-source
      taskRef:
        name: git-clone
        kind: ClusterTask
      params:
        - name: url
          value: $(params.git-url)
        - name: revision
          value: $(params.git-revision)
      workspaces:
        - name: output
          workspace: shared-workspace
    
    - name: run-tests
      taskRef:
        name: golang-test
        kind: ClusterTask
      runAfter:
        - fetch-source
      params:
        - name: package
          value: "./..."
        - name: flags
          value: "-v -race -coverprofile=coverage.out"
      workspaces:
        - name: source
          workspace: shared-workspace
    
    - name: build-image
      taskRef:
        name: kaniko
        kind: ClusterTask
      runAfter:
        - run-tests
      params:
        - name: IMAGE
          value: "$(params.registry-url)/$(params.app-name):$(params.git-revision)"
        - name: DOCKERFILE
          value: "./Dockerfile"
      workspaces:
        - name: source
          workspace: shared-workspace
        - name: dockerconfig
          workspace: azure-credentials
    
    - name: deploy-to-dev
      taskRef:
        name: azure-aks-deploy
      runAfter:
        - build-image
      params:
        - name: cluster-name
          value: "$(params.dev-cluster)"
        - name: resource-group
          value: "$(params.resource-group)"
        - name: image
          value: "$(params.registry-url)/$(params.app-name):$(params.git-revision)"
        - name: environment
          value: "development"
      workspaces:
        - name: source
          workspace: shared-workspace
        - name: azure-credentials
          workspace: azure-credentials
    
    - name: integration-tests
      taskRef:
        name: integration-test
      runAfter:
        - deploy-to-dev
      params:
        - name: test-endpoint
          value: "https://$(params.app-name)-dev.azurewebsites.net"
      workspaces:
        - name: source
          workspace: shared-workspace
    
    - name: manual-approval
      taskRef:
        name: manual-approval-task
      runAfter:
        - integration-tests
      params:
        - name: message
          value: "Approve deployment to production?"
        - name: timeout
          value: "3600" # 1 hour timeout
    
    - name: deploy-to-prod
      taskRef:
        name: azure-aks-deploy
      runAfter:
        - manual-approval
      params:
        - name: cluster-name
          value: "$(params.prod-cluster)"
        - name: resource-group
          value: "$(params.resource-group)"
        - name: image
          value: "$(params.registry-url)/$(params.app-name):$(params.git-revision)"
        - name: environment
          value: "production"
      workspaces:
        - name: source
          workspace: shared-workspace
        - name: azure-credentials
          workspace: azure-credentials

Example 3: GCP Cloud Run Serverless Pipeline

This example shows a serverless deployment pipeline for Google Cloud Run with automated scaling.

# gcp-pipeline.yaml
apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: gcp-cloudrun-pipeline
  annotations:
    tekton.dev/description: "Serverless deployment to Google Cloud Run"
spec:
  params:
    - name: git-url
      type: string
    - name: git-revision
      type: string
      default: main
    - name: service-name
      type: string
    - name: project-id
      type: string
    - name: region
      type: string
      default: us-central1
    - name: max-instances
      type: string
      default: "100"
  
  workspaces:
    - name: source-workspace
    - name: gcp-credentials
  
  tasks:
    - name: clone-repo
      taskRef:
        name: git-clone
        kind: ClusterTask
      params:
        - name: url
          value: $(params.git-url)
        - name: revision
          value: $(params.git-revision)
      workspaces:
        - name: output
          workspace: source-workspace
    
    - name: lint-code
      taskRef:
        name: eslint
      runAfter:
        - clone-repo
      params:
        - name: args
          value: ["src/", "--ext", ".js,.ts"]
      workspaces:
        - name: source
          workspace: source-workspace
    
    - name: unit-tests
      taskRef:
        name: npm
        kind: ClusterTask
      runAfter:
        - lint-code
      params:
        - name: ARGS
          value: ["test"]
      workspaces:
        - name: source
          workspace: source-workspace
    
    - name: build-container
      taskRef:
        name: gcp-cloud-build
      runAfter:
        - unit-tests
      params:
        - name: project-id
          value: "$(params.project-id)"
        - name: image-name
          value: "gcr.io/$(params.project-id)/$(params.service-name):$(params.git-revision)"
        - name: dockerfile
          value: "Dockerfile"
      workspaces:
        - name: source
          workspace: source-workspace
        - name: credentials
          workspace: gcp-credentials
    
    - name: security-scan-image
      taskRef:
        name: gcp-container-analysis
      runAfter:
        - build-container
      params:
        - name: project-id
          value: "$(params.project-id)"
        - name: image-url
          value: "gcr.io/$(params.project-id)/$(params.service-name):$(params.git-revision)"
      workspaces:
        - name: credentials
          workspace: gcp-credentials
    
    - name: deploy-cloud-run
      taskRef:
        name: gcp-cloud-run-deploy
      runAfter:
        - security-scan-image
      params:
        - name: service-name
          value: "$(params.service-name)"
        - name: project-id
          value: "$(params.project-id)"
        - name: region
          value: "$(params.region)"
        - name: image
          value: "gcr.io/$(params.project-id)/$(params.service-name):$(params.git-revision)"
        - name: max-instances
          value: "$(params.max-instances)"
        - name: cpu-limit
          value: "1000m"
        - name: memory-limit
          value: "512Mi"
      workspaces:
        - name: source
          workspace: source-workspace
        - name: credentials
          workspace: gcp-credentials
    
    - name: smoke-tests
      taskRef:
        name: curl-test
      runAfter:
        - deploy-cloud-run
      params:
        - name: url
          value: "$(tasks.deploy-cloud-run.results.service-url)/health"
        - name: expected-status
          value: "200"

---
# Custom Task for GCP Cloud Run Deployment
apiVersion: tekton.dev/v1beta1
kind: Task
metadata:
  name: gcp-cloud-run-deploy
spec:
  params:
    - name: service-name
      type: string
    - name: project-id
      type: string
    - name: region
      type: string
    - name: image
      type: string
    - name: max-instances
      type: string
      default: "100"
    - name: cpu-limit
      type: string
      default: "1000m"
    - name: memory-limit
      type: string
      default: "512Mi"
  
  workspaces:
    - name: source
    - name: credentials
  
  results:
    - name: service-url
      description: The URL of the deployed Cloud Run service
  
  steps:
    - name: authenticate
      image: gcr.io/google.com/cloudsdktool/cloud-sdk:latest
      script: |
        #!/bin/bash
        gcloud auth activate-service-account --key-file=$(workspaces.credentials.path)/key.json
        gcloud config set project $(params.project-id)
    
    - name: deploy
      image: gcr.io/google.com/cloudsdktool/cloud-sdk:latest
      script: |
        #!/bin/bash
        set -e
        
        gcloud run deploy $(params.service-name) \
          --image=$(params.image) \
          --region=$(params.region) \
          --platform=managed \
          --allow-unauthenticated \
          --max-instances=$(params.max-instances) \
          --cpu=$(params.cpu-limit) \
          --memory=$(params.memory-limit) \
          --port=8080 \
          --set-env-vars="ENVIRONMENT=production" \
          --format="value(status.url)" > /tmp/service-url
        
        # Output the service URL
        echo -n "$(cat /tmp/service-url)" | tee $(results.service-url.path)

Example 4: Multi-Cloud GitOps Pipeline

This advanced example demonstrates a GitOps pipeline that can deploy to multiple cloud providers.

# multi-cloud-gitops.yaml
apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: multi-cloud-gitops
  annotations:
    tekton.dev/description: "GitOps pipeline for multi-cloud deployment"
spec:
  params:
    - name: app-git-url
      type: string
    - name: config-git-url
      type: string
    - name: git-revision
      type: string
      default: main
    - name: target-clouds
      type: array
      description: "Array of target clouds: aws, azure, gcp"
    - name: registry-url
      type: string
  
  workspaces:
    - name: app-source
    - name: config-source
    - name: cloud-credentials
  
  tasks:
    - name: fetch-app-source
      taskRef:
        name: git-clone
        kind: ClusterTask
      params:
        - name: url
          value: $(params.app-git-url)
        - name: revision
          value: $(params.git-revision)
      workspaces:
        - name: output
          workspace: app-source
    
    - name: fetch-config-source
      taskRef:
        name: git-clone
        kind: ClusterTask
      params:
        - name: url
          value: $(params.config-git-url)
        - name: revision
          value: main
      workspaces:
        - name: output
          workspace: config-source
    
    - name: build-universal-image
      taskRef:
        name: buildah
        kind: ClusterTask
      runAfter:
        - fetch-app-source
      params:
        - name: IMAGE
          value: "$(params.registry-url)/multi-cloud-app:$(params.git-revision)"
        - name: DOCKERFILE
          value: "./Dockerfile"
      workspaces:
        - name: source
          workspace: app-source
    
    - name: update-manifests
      taskRef:
        name: yq-replace
      runAfter:
        - build-universal-image
        - fetch-config-source
      params:
        - name: files
          value: ["./aws/deployment.yaml", "./azure/deployment.yaml", "./gcp/deployment.yaml"]
        - name: expression
          value: ".spec.template.spec.containers[0].image"
        - name: value
          value: "$(params.registry-url)/multi-cloud-app:$(params.git-revision)"
      workspaces:
        - name: source
          workspace: config-source
    
    - name: deploy-to-clouds
      taskRef:
        name: multi-cloud-deploy
      runAfter:
        - update-manifests
      params:
        - name: target-clouds
          value: $(params.target-clouds)
      workspaces:
        - name: config-source
          workspace: config-source
        - name: credentials
          workspace: cloud-credentials
    
    - name: commit-changes
      taskRef:
        name: git-commit-push
      runAfter:
        - deploy-to-clouds
      params:
        - name: message
          value: "Update image to $(params.git-revision)"
        - name: git-url
          value: $(params.config-git-url)
      workspaces:
        - name: source
          workspace: config-source

Pipeline Triggers and EventListeners (2025)

Modern webhook configuration for GitLab, GitHub, and Azure DevOps:

# modern-triggers.yaml
apiVersion: triggers.tekton.dev/v1beta1
kind: EventListener
metadata:
  name: modern-webhook-listener
spec:
  serviceAccountName: tekton-triggers-sa
  triggers:
    - name: github-push
      interceptors:
        - ref:
            name: "github"
          params:
            - name: "secretRef"
              value:
                secretName: github-secret
                secretKey: token
            - name: "eventTypes"
              value: ["push", "pull_request"]
        - ref:
            name: "cel"
          params:
            - name: "filter"
              value: "body.ref.startsWith('refs/heads/main') || body.action == 'opened'"
      bindings:
        - ref: github-binding
      template:
        ref: aws-eks-pipeline-template
    
    - name: gitlab-webhook
      interceptors:
        - ref:
            name: "gitlab"
          params:
            - name: "secretRef"
              value:
                secretName: gitlab-secret
                secretKey: token
            - name: "eventTypes"
              value: ["Push Hook", "Merge Request Hook"]
      bindings:
        - ref: gitlab-binding
      template:
        ref: azure-aks-pipeline-template
---
apiVersion: triggers.tekton.dev/v1beta1
kind: TriggerBinding
metadata:
  name: github-binding
spec:
  params:
    - name: git-url
      value: $(body.repository.clone_url)
    - name: git-revision
      value: $(body.after)
    - name: repository-name
      value: $(body.repository.name)
---
apiVersion: triggers.tekton.dev/v1beta1
kind: TriggerTemplate
metadata:
  name: aws-eks-pipeline-template
spec:
  params:
    - name: git-url
    - name: git-revision
    - name: repository-name
  resourcetemplates:
    - apiVersion: tekton.dev/v1beta1
      kind: PipelineRun
      metadata:
        generateName: aws-pipeline-run-
        labels:
          tekton.dev/pipeline: aws-eks-pipeline
      spec:
        pipelineRef:
          name: aws-eks-pipeline
        params:
          - name: git-url
            value: $(tt.params.git-url)
          - name: git-revision
            value: $(tt.params.git-revision)
          - name: image-tag
            value: "your-registry.com/$(tt.params.repository-name):$(tt.params.git-revision)"
          - name: eks-cluster-name
            value: "production-cluster"
        workspaces:
          - name: shared-data
            volumeClaimTemplate:
              spec:
                accessModes:
                  - ReadWriteOnce
                resources:
                  requests:
                    storage: 5Gi
          - name: aws-credentials
            secret:
              secretName: aws-credentials
          - name: signing-secrets
            secret:
              secretName: cosign-keys

These examples showcase:

  1. SLSA Compliance: Supply chain security with image signing and provenance generation

  2. Multi-Environment Deployments: Proper staging with approval gates

  3. Serverless Deployments: Cloud Run with auto-scaling configuration

  4. GitOps Integration: Configuration management with automated updates

  5. Modern Webhooks: Advanced event filtering and processing

  6. Security Scanning: Container vulnerability assessments

  7. Multi-Cloud Support: Unified pipelines across cloud providers

Installation Guide (2025)

Prerequisites

  • Kubernetes cluster 1.28+ (recommended: 1.29 or later)

  • kubectl configured to access your cluster

  • Cluster-admin permissions

  • At least 2GB of available memory and 2 CPU cores

Installing Tekton Pipelines (v0.55.0+)

To install Tekton Pipelines on a Kubernetes cluster:

  1. Install the latest stable release:

# Install Tekton Pipelines
kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/latest/release.yaml

# Verify installation
kubectl get pods --namespace tekton-pipelines

  1. For specific versions or alternative installations:

# Install specific version (example: v0.55.0)
kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/previous/v0.55.0/release.yaml

# Install nightly build (for testing latest features)
kubectl apply --filename https://storage.googleapis.com/tekton-releases-nightly/pipeline/latest/release.yaml

# For environments without image digest support
kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/latest/release.notags.yaml

  1. Monitor the installation:

kubectl get pods --namespace tekton-pipelines --watch

When all components show 1/1 under the READY column, the installation is complete.

Installing Tekton Triggers (v0.26.0+)

  1. Install Tekton Triggers for webhook and event-driven pipelines:

# Install Triggers
kubectl apply --filename https://storage.googleapis.com/tekton-releases/triggers/latest/release.yaml

# Install Interceptors
kubectl apply --filename https://storage.googleapis.com/tekton-releases/triggers/latest/interceptors.yaml

# Verify installation
kubectl get pods --namespace tekton-pipelines

Installing Tekton Dashboard (v0.40.0+)

  1. Install the web-based dashboard:

# Install Dashboard
kubectl apply --filename https://storage.googleapis.com/tekton-releases/dashboard/latest/release.yaml

# Access the dashboard (port-forward)
kubectl port-forward -n tekton-pipelines svc/tekton-dashboard 9097:9097

Installing Tekton CLI (tkn) v0.35.0+

# Linux (x86_64)
curl -LO https://github.com/tektoncd/cli/releases/latest/download/tkn_Linux_x86_64.tar.gz
sudo tar xvzf tkn_Linux_x86_64.tar.gz -C /usr/local/bin/ tkn

# macOS (Intel)
brew install tektoncd-cli

# macOS (ARM64)
curl -LO https://github.com/tektoncd/cli/releases/latest/download/tkn_Darwin_arm64.tar.gz
sudo tar xvzf tkn_Darwin_arm64.tar.gz -C /usr/local/bin/ tkn

# Windows (PowerShell)
choco install tektoncd-cli

# Verify installation
tkn version

Installation on Different Operating Systems

Linux Installation

# Prerequisites
sudo apt update
sudo apt install -y curl kubectl

# Install kubectl if not present
curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
sudo install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl

# Install Tekton CLI
curl -LO https://github.com/tektoncd/cli/releases/latest/download/tkn_Linux_x86_64.tar.gz
sudo tar xvzf tkn_Linux_x86_64.tar.gz -C /usr/local/bin/ tkn

WSL (Windows Subsystem for Linux) Installation

# Update WSL package list
sudo apt update

# Install dependencies
sudo apt install -y curl wget

# Install kubectl
curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
sudo install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl

# Install Tekton CLI
curl -LO https://github.com/tektoncd/cli/releases/latest/download/tkn_Linux_x86_64.tar.gz
sudo tar xvzf tkn_Linux_x86_64.tar.gz -C /usr/local/bin/ tkn

# Verify installations
kubectl version --client
tkn version

NixOS Installation

# Configuration.nix approach
{ config, pkgs, ... }:
{
  environment.systemPackages = with pkgs; [
    kubectl
    tektoncd-cli
    # Additional tools for Tekton development
    yq-go
    jq
    git
    docker
  ];
  
  # Enable Docker for building containers
  virtualisation.docker.enable = true;
  
  # Add user to docker group
  users.users.yourusername.extraGroups = [ "docker" ];
}

# Using nix-shell for development
nix-shell -p kubectl tektoncd-cli yq-go jq git docker

# Using Home Manager (home.nix)
{ config, pkgs, ... }:
{
  home.packages = with pkgs; [
    kubectl
    tektoncd-cli
    yq-go
    jq
  ];
  
  programs.git.enable = true;
}

Best Practices for Tekton in 2025

  1. Security First

    • Always use signed images and SLSA provenance

    • Implement proper RBAC and security contexts

    • Regularly scan for vulnerabilities

  2. Resource Management

    • Use resource quotas and limits

    • Implement proper workspace management

    • Monitor pipeline performance

  3. GitOps Integration

    • Store pipeline definitions in Git

    • Use automated synchronization

    • Implement proper branching strategies

  4. Observability

    • Enable comprehensive logging

    • Use distributed tracing

    • Implement monitoring and alerting

Getting Started with Your First Pipeline

# Create a new namespace
kubectl create namespace tekton-getting-started

# Create a simple task
cat <<EOF | kubectl apply -f -
apiVersion: tekton.dev/v1beta1
kind: Task
metadata:
  name: hello-world
  namespace: tekton-getting-started
spec:
  steps:
    - name: echo
      image: alpine
      script: |
        #!/bin/sh
        echo "Hello World from Tekton!"
        echo "Current date: \$(date)"
        echo "Environment: \$(env | sort)"
EOF

# Run the task
cat <<EOF | kubectl apply -f -
apiVersion: tekton.dev/v1beta1
kind: TaskRun
metadata:
  name: hello-world-run
  namespace: tekton-getting-started
spec:
  taskRef:
    name: hello-world
EOF

# Check the results
tkn taskrun logs hello-world-run -n tekton-getting-started

DevOps Joke: Why did the developer choose Tekton over other CI/CD tools? Because they wanted their pipelines to be as declarative as their love for Kubernetes - and just like their relationship status, everything had to be defined in YAML! 😄

At least with Tekton, when your pipeline fails, you can blame it on the cluster and not your code... most of the time!

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