The Numbers Don’t Lie: Jenkins Is Losing Its Grip
I’ve been watching the CI/CD landscape for over a decade, and I can tell you this: when CloudBees reports a 34% drop in Jenkins enterprise licenses while Red Hat simultaneously sees Tekton adoption surge 156% among Fortune 500 companies, we’re not looking at a blip. We’re seeing how platform engineering teams really think about continuous integration these days.
The writing has been on the wall since 2023, but 2025 marked the tipping point. GitLab processed 23,000 Jenkins-to-GitLab CI migrations in just Q4 alone—a 67% increase from the previous quarter. That’s not gradual evolution. That’s migration at scale.
Here’s what’s fascinating: this isn’t happening because Jenkins suddenly became terrible overnight. It’s the same reliable workhorse it’s always been. The problem is that the world around Jenkins evolved faster than Jenkins itself could adapt. Platform engineering teams are finally saying “enough” to the maintenance burden that comes with keeping legacy CI/CD infrastructure running.
The Maintenance Nightmare That Broke the Camel’s Back
According to the Linux Foundation’s 2025 survey, 42% of platform engineering teams cited “pipeline maintenance overhead” as their primary driver for abandoning Jenkins. Having spent countless nights debugging Jenkins plugin conflicts and wrestling with Groovy pipeline scripts, this number doesn’t surprise me one bit.
Here’s the thing about Jenkins that nobody talks about in the marketing materials: it’s incredibly powerful, but that power comes at the cost of complexity that compounds over time. Every plugin adds potential failure points. Every custom script becomes technical debt. Every upgrade becomes a game of “will this break our existing pipelines?”
I’ve seen teams spend more time maintaining their Jenkins infrastructure than actually improving their deployment processes. When your CI/CD system requires its own dedicated team just to keep the lights on, you’ve fundamentally missed the point of automation. Platform engineering teams are realizing they can’t afford to burn engineering cycles on infrastructure that should be commodity by now.
The cloud-native alternatives like Tekton don’t just solve the maintenance problem—they eliminate entire categories of problems by design. When your pipeline definitions are declarative Kubernetes resources, you get observability, scalability, and reliability baked in rather than bolted on through a constellation of plugins.
Tekton and the Cloud-Native Advantage
Spotify’s engineering team published a compelling case study in November 2025 that perfectly illustrates why teams are making this shift. Their migration to Tekton reduced pipeline maintenance time by 58% while simultaneously improving deployment frequency by 31%. Those aren’t incremental improvements. Those are the kind of gains that make CFOs pay attention.
What makes Tekton particularly appealing is its Kubernetes-native design philosophy. Instead of fighting against the orchestration layer, it leverages it. Pipeline steps run as pods, which means you get all the benefits of Kubernetes scheduling, resource management, and observability without additional configuration overhead.
The Tekton official documentation makes it clear that this isn’t just another CI/CD tool. It’s a complete rethinking of how continuous integration should work in a cloud-native world. Tasks are reusable, pipelines are composable, and everything is defined as code in a way that actually makes sense to both developers and platform engineers.
But here’s where I’ll inject some healthy skepticism: Tekton isn’t a magic bullet. It requires teams to be comfortable with Kubernetes concepts and YAML engineering. If your team is still learning kubectl, jumping to Tekton might be premature. The cloud-native approach comes with its own learning curve, even if that curve leads to a much more maintainable destination.
The Performance Gap Widens
The Puppet State of DevOps Report 2025 dropped a statistic that should make every engineering leader pause: teams using cloud-native CI/CD tools deploy 4.2x more frequently than Jenkins-based teams. That’s not a marginal difference. That’s the difference between weekly releases and multiple deployments per day.
This performance gap stems from fundamental architectural differences. Jenkins was designed when deployment meant copying files to servers and restarting services. Cloud-native CI/CD tools were built from the ground up for containerized, API-driven infrastructure where deployment is a declarative operation rather than a procedural script.
What’s particularly interesting is how this performance difference compounds over time. Teams that can deploy more frequently can experiment more, gather feedback faster, and iterate more effectively. The CI/CD system stops being a bottleneck and becomes an enabler of engineering velocity.
What Went Wrong (And What’s Coming Next)
Jenkins didn’t fail because it was bad technology. It failed because it succeeded too well at solving 2010’s problems while the industry moved on to 2025’s challenges. The plugin ecosystem that made Jenkins flexible also made it fragile. The scriptability that made it powerful also made it unpredictable.
The platform engineering movement represents a fundamental shift toward treating developer tooling as product rather than project. Teams want CI/CD systems that provide excellent developer experience out of the box, not systems that require months of customization to become usable. Jenkins requires too much assembly. Cloud-native alternatives ship ready to use.
Looking forward, I expect this migration to accelerate through 2026. The network effects are starting to kick in. As more teams share cloud-native pipeline patterns and tooling, the switching costs continue to decrease while the benefits become more obvious. Organizations that delay this transition will find themselves increasingly isolated on legacy infrastructure.
The real question isn’t whether Jenkins will survive in some form. It will, particularly in environments where regulatory requirements or existing investments make migration prohibitive. The question is whether teams building new platform capabilities will choose the path of least resistance or the path of least maintenance. Based on the trends we’re seeing, that choice seems increasingly clear.
Have you been through a CI/CD migration recently? I’m curious about your experiences with the transition challenges and whether the promised benefits actually materialized in practice.
