Blogging

DevOps Death Watch: Why Platform Engineering Teams Are Abandoning Jenkins for Tekton (And What Went Wrong)

The Great Migration Has Begun

I’ve been watching the Jenkins ecosystem for over a decade, and 2025 feels like a tipping point. CloudBees reported a 34% drop in enterprise license sales this year while Red Hat documented a 156% surge in Tekton adoption among Fortune 500 companies. These aren’t just numbers on a spreadsheet. They represent real engineering teams making hard decisions about their CI/CD infrastructure.

The migration isn’t happening in a vacuum. GitLab processed 23,000 Jenkins-to-GitLab CI migrations in the fourth quarter alone, a 67% jump from the previous quarter. When I see numbers like that, I know something fundamental has shifted in how we think about continuous delivery.

Jenkins Showed Its Age at the Worst Possible Time

Jenkins was revolutionary when it emerged. I remember the excitement of moving from CruiseControl and other primitive build systems to something with actual plugins and a decent UI. But that plugin architecture, once Jenkins’ greatest strength, became its weakness in the cloud-native era.

The Linux Foundation’s 2025 survey revealed that 42% of platform engineering teams cited pipeline maintenance overhead as their primary reason for abandoning Jenkins. I’ve lived this pain. Managing Jenkins plugins across multiple environments becomes a nightmare when you’re dealing with hundreds of microservices and teams that deploy multiple times per day.

The Groovy-based pipeline syntax that felt powerful in 2015 now feels clunky compared to YAML-native alternatives. When your platform team spends more time debugging Jenkins issues than improving developer experience, you know it’s time to re-evaluate.

Tekton’s Cloud-Native Promise Actually Delivered

Tekton caught my attention because it was designed for Kubernetes from day one, not retrofitted for it. The Tekton official documentation shows a system built around cloud-native principles: immutable task definitions, declarative pipeline specifications, and true horizontal scaling.

Spotify’s engineering team published compelling numbers in November 2025. Their Tekton migration reduced pipeline maintenance time by 58% while improving deployment frequency by 31%. These metrics match what I’ve seen in my own migrations. When your CI/CD system runs as Kubernetes-native resources, you get all the benefits of Kubernetes operators, scaling, and observability for free.

The real breakthrough is how Tekton handles pipeline composition. Instead of monolithic Jenkinsfiles that become unmaintainable, you get reusable tasks that teams can share across the organization. I’ve seen this eliminate the “copy-paste pipeline config” problem that plagued Jenkins environments.

The Performance Gap Became Undeniable

Data from the Puppet State of DevOps Report 2025 showed teams using cloud-native CI/CD tools deployed 4.2 times more frequently than Jenkins-based teams. That’s not a marginal improvement. That’s the difference between staying competitive and falling behind.

The performance gap comes from architectural differences. Jenkins executors are stateful and resource-heavy. Tekton task pods are ephemeral and can scale to zero when not in use. I’ve watched Jenkins clusters struggle under load while Tekton environments gracefully handle traffic spikes.

Security also became a major factor. Jenkins’ plugin ecosystem, while extensive, created attack surfaces that cloud-native alternatives simply don’t have. When your pipeline execution happens in isolated containers with minimal privileges, your security posture improves dramatically.

The Path Forward Isn’t Simple

Migration isn’t trivial. Jenkins has thousands of plugins and established workflows that took years to build. Teams don’t abandon that investment lightly. The organizations succeeding with Tekton migrations are those that view it as platform engineering work, not just a tool swap.

I’ve seen successful migrations follow a pattern: start with new services on Tekton while gradually moving existing pipelines. Focus on standardizing common patterns before attempting complex legacy migrations. Most importantly, invest in tooling to make the migration feel like an upgrade, not a step backward.

The writing is on the wall for Jenkins in large-scale, cloud-native environments. The question isn’t whether to migrate, but when and how. Teams that start planning now will be ahead of the curve when the maintenance burden becomes truly unsustainable.

What’s your experience with Jenkins migrations? I’m particularly interested in hearing about the challenges you’ve faced with legacy pipeline conversions and how you’ve approached team adoption of new tooling.