Implementing Tekton: Kubernetes CI/CD Pipeline-as-Code Guide

During our Q3 migration to a fully ephemeral CI/CD environment, we hit a wall where our Jenkins runners were consuming 40% of our cluster's CPU just sitting idle. We needed a shift toward a truly Cloud-Native Build strategy, so we moved to Tekton to gain better resource utilization and native integration with our existing cluster infrastructure.

Why We Moved to Kubernetes Task Pipelines

The primary motivation wasn't just "shiny object syndrome"—it was the need to scale our build concurrency without managing dedicated runner pools. Traditional CI systems often force you to maintain static virtual machines or pre-configured pods, which creates a maintenance nightmare when you're already busy using Kubernetes Cluster API: Automating Node Upgrades with CAPI to handle our infrastructure lifecycle.

Tekton treats CI/CD as a first-class citizen in Kubernetes, using Custom Resource Definitions (CRDs) to define Tasks and Pipelines. Instead of a monolithic controller, every step in your pipeline is a pod. When a build finishes, the pod disappears. It’s clean, efficient, and fits perfectly into a Kubernetes Security: Implementing Policy-as-Code with OPA Gatekeeper workflow, where you can enforce security policies on the build pods themselves.

Implementing Pipeline-as-Code with Tekton

To get started, you’ll need the Tekton Pipelines operator. I prefer installing it via Helm to keep my versions pinned. Once installed, you define a Task that performs a specific unit of work, like building a container image using Kaniko.

YAML
apiVersion: tekton.dev/v1beta1
kind: Task
metadata:
  name: build-app
spec:
  params:
    - name: IMAGE_URL
      type: string
  steps:
    - name: build
      image: gcr.io/kaniko-project/executor:latest
      command: ["/kaniko/executor"]
      args:
        - "--dockerfile=Dockerfile"
        - "--destination=$(params.IMAGE_URL)"

The beauty of this is that the Task is version-controlled alongside your application code. It's Pipeline-as-Code in the purest sense. If you need to change your build logic, you update the Git repository, and the cluster reconciles the new state.

The Trade-offs: When Things Go Wrong

We didn't get this right on the first try. Initially, we tried to mount a host path for the Docker socket to build images, but that violated our security posture and broke when we tightened our constraints using Kubernetes Security: Implementing Zero-Trust with Kyverno and Policies. We then switched to Kaniko, which builds images in user-space, but we ran into issues with local caching.

It took us roughly 14 hours of troubleshooting to realize that the default emptyDir volumes weren't persisting cache across steps efficiently. We eventually implemented a PersistentVolumeClaim (PVC) workspace to share data between tasks, which reduced our build times by around 220 seconds on average. It wasn't the clean, "out of the box" experience the marketing materials suggested, but it was robust.

Operational Realities

Running Tekton in production requires a solid grasp of how Kubernetes handles service accounts and RBAC. Each TaskRun needs permissions to pull source code from your Git provider and push images to your registry. Don't just cluster-admin your pipeline service account; scope it down to the specific namespace and resources it requires.

If you’re managing stateful builds, remember that you’ll need to handle your own backups. I usually recommend pairing your pipeline storage with Kubernetes Backup Strategies: Implementing Velero and MinIO to ensure that if a node fails during a long-running build, you aren't left with orphaned artifacts or corrupted caches.

Still Puzzling Through

I’m still not 100% satisfied with our current observability story. Tekton’s logs are great, but correlating a failed TaskRun with a specific line in a complex pipeline often feels like digging through a haystack. We’ve been experimenting with custom Tekton Results to export metadata to our logging stack, but it’s still a work in progress.

Next time, I’d likely spend more time upfront on a standardized Task library across our teams instead of letting every service owner write their own build definitions. We gained speed, but we also gained a bit of configuration drift that I’m now tasked with cleaning up.

FAQ

Q: Is Tekton overkill for small projects? A: Probably. If you don't need the scaling benefits of Kubernetes native builds, a simpler tool like GitHub Actions might be faster to set up.

Q: How do you handle secrets in Tekton? A: We use Kubernetes Secrets mounted as volumes or environment variables, integrated with the External Secrets Operator to sync them from our vault—similar to the patterns described in Kubernetes Secret Management with HashiCorp Vault and ESO Guide.

Q: Can I run Tekton on a single-node cluster? A: Yes, but keep an eye on resource contention. The overhead of individual pods for every step can lead to CPU throttling if you aren't careful with your limits.