ConfigsApr 15, 2026·3 min read

Tekton Pipelines — Cloud-Native CI/CD Primitives for Kubernetes

Tekton Pipelines is a powerful, flexible, open-source framework for creating CI/CD systems. It runs pipelines as native Kubernetes resources using Tasks, Pipelines and TaskRuns.

TL;DR
Tekton models CI/CD pipelines as Kubernetes CRDs, running each step in its own container.
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What it is

Tekton Pipelines is an open-source framework for creating CI/CD systems that run as native Kubernetes resources. Originally born from Knative Build at Google, Tekton became a standalone CNCF project and now powers pipeline engines in Jenkins X, OpenShift Pipelines, and IBM Cloud.

Tekton is built for platform engineers and DevOps teams who want their CI/CD system to be a first-class citizen in Kubernetes rather than a bolt-on monolithic server.

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How it saves time or tokens

Tekton eliminates the need to maintain a separate CI server. Because Tasks and Pipelines are Kubernetes CRDs, they inherit cluster scheduling, resource limits, and RBAC. Each step runs in its own container, so language and tooling isolation is free. Typed parameters, results, and workspaces enforce contracts between steps, reducing debugging time on data-passing bugs.

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How to use

  1. Install Tekton Pipelines into your cluster:
kubectl apply -f https://storage.googleapis.com/tekton-releases/pipeline/latest/release.yaml
  1. Install the tkn CLI for interacting with pipeline runs:
brew install tektoncd-cli
  1. Create and run a simple TaskRun:
apiVersion: tekton.dev/v1
kind: TaskRun
metadata:
  generateName: hello-
spec:
  taskSpec:
    steps:
      - name: echo
        image: alpine
        script: echo Hello Tekton
kubectl apply -f taskrun.yaml
tkn taskrun logs --last -f
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Example

A minimal pipeline that clones a repo, runs tests, and builds a container image:

apiVersion: tekton.dev/v1
kind: Pipeline
metadata:
  name: build-and-test
spec:
  params:
    - name: repo-url
      type: string
  workspaces:
    - name: shared-data
  tasks:
    - name: fetch-source
      taskRef:
        name: git-clone
      workspaces:
        - name: output
          workspace: shared-data
      params:
        - name: url
          value: $(params.repo-url)
    - name: run-tests
      runAfter: [fetch-source]
      taskRef:
        name: run-tests
      workspaces:
        - name: source
          workspace: shared-data
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Related on TokRepo

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Common pitfalls

  • Forgetting to set resource requests on TaskRun steps, which can cause scheduling failures on constrained clusters
  • Not using workspaces for data passing between tasks; relying on results alone hits size limits quickly
  • Overlooking Tekton Chains for supply-chain security; without it, pipeline outputs lack signed provenance

Frequently Asked Questions

What is the difference between a Task and a Pipeline in Tekton?+

A Task is a single unit of work with one or more sequential steps, each running in its own container. A Pipeline composes multiple Tasks into a directed acyclic graph, defining ordering, parameters, and data flow between them via workspaces and results.

Does Tekton replace Jenkins or GitHub Actions?+

Tekton provides the primitives, not a full CI/CD product with a UI. Projects like Jenkins X and OpenShift Pipelines build on Tekton to offer a Jenkins-like or GitHub Actions-like experience. You can use Tekton directly for maximum control or adopt a higher-level product built on it.

How does Tekton handle secrets and credentials?+

Tekton uses standard Kubernetes Secrets. You mount them into Task steps via workspaces or environment variables. Tekton also supports annotation-based credential selection where Secrets are matched to ServiceAccounts automatically.

Can Tekton run outside Kubernetes?+

No. Tekton is deeply integrated with the Kubernetes API and scheduler. Every TaskRun is a set of Pods. If you need CI/CD without Kubernetes, tools like GitHub Actions or Dagger are better suited.

What is Tekton Chains?+

Tekton Chains is a companion project that automatically signs TaskRun results and generates in-toto attestations for SLSA compliance. It observes completed TaskRuns and produces signed provenance metadata without modifying your pipeline definitions.

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