2026 Gartner® Magic Quadrant™ for Container Management recognized Kubermatic for the second year.
Across the vendors evaluated in the report, Gartner provided insights into their strengths, as well as areas where there is room for improvement. Here’s how we’re addressing our report inclusion.
Limited ecosystem - true, and mostly by design
KKP doesn’t have the third-party plugin marketplace that AWS, Azure, or GCP have built over a decade of hyperscaler gravity. If you’re used to browsing a catalog for every integration, KKP’s ecosystem will feel smaller.
Here’s the trade we made instead. KKP is API-first and open source at its core (Apache-2.0, CE included), which means it doesn’t try to own the tooling layer above it. Teams bring their existing GitOps stack (Flux, ArgoCD), their own CI/CD, their own image registries, and their own IaC pipelines, and KKP integrates through the Kubernetes API rather than through a proprietary marketplace. That’s less convenient than a one-click app store. It’s also why KKP runs on 20+ infrastructure providers, from AWS and vSphere to OpenStack and bare metal, without having to rebuild an integration for each one from scratch.
We believe this openness is more valuable than building a closed ecosystem around KKP. We didn’t build a walled garden, so teams can keep the tools they already trust. It gives platform teams the freedom to choose the technologies that fit their environment rather than forcing every organization into the same stack. That approach does come with a trade-off, though: not every integration is available as a one-click experience. We’re continuing to expand integrations and improve the overall platform experience while keeping interoperability at the core of KKP.
Operational Complexity - During implementation, not daily use
Running Kubernetes at fleet scale across multiple clouds and edge sites requires real expertise. KKP doesn’t pretend otherwise. It centralizes and automates much of that complexity, but the team responsible for the platform still needs to understand what sits underneath it. The important distinction is between implementing the platform and using it day to day.
For implementation, Kubernetes expertise is still required - but teams don’t have to build all of that expertise themselves. Kubermatic is a CNCF Kubernetes Certified Service Provider and one of the first Kubernetes Training Partners, with Cloud Native Labs offering consulting, accelerators, and structured training. The Kubermatic Kubernetes Subscription also provides 24x7 business-critical support.
WOBCOM, for example, went from zero to production in three weeks with this approach. Every environment is different, but the experience shows that the learning curve can be shortened with the right expertise and support.
For day-to-day use, the goal is different: keep Kubernetes complexity with the platform team and make the platform simple for users. End users don’t need Kubernetes expertise to manage their environments. For example, at the Berlin Institute of Health, bioinformaticians can manage their own clusters and upgrades in a few clicks, without needing to understand the underlying infrastructure.
The learning curve doesn’t disappear for the team building the platform. Our goal is to make sure it doesn’t become everyone else’s problem. KKP puts the complexity where the expertise belongs, backed by the support and services needed to get there.
No native image and storage management - a deliberate boundary
KKP does not provide native container image management, image building, container-native storage, or CVE scanning.
That is by design. KKP is a cluster lifecycle and fleet management platform, not an application platform. Its role is to provision and manage clusters, control planes, and policy consistently across environments, not to replace the tools teams already use for images, security, and storage.
So the dependency is explicit rather than hidden. If you need image scanning, you can integrate tools such as Trivy or Grype into your existing CI/CD and security pipelines. If you need container-native storage, you can use a CSI-compatible storage solution that fits your infrastructure and operational model.
There is a trade-off here. KKP could bundle a registry, scanning, and storage layer, but that would also mean choosing defaults that every customer would have to adopt, replace, or work around. For enterprises that already have standardized registries, security pipelines, and storage platforms, that would add more constraints than value.
We deliberately chose interoperability over bundling. The result is that customers do need to select and integrate their own image and storage tooling. That is a real responsibility, but it is also a conscious architectural choice: KKP provides the cluster and fleet management foundation while allowing teams to keep the tools and standards they have already chosen.
What we’re building toward
Kubernetes environments are becoming more distributed and more diverse. Organizations are running workloads across public cloud, private infrastructure, edge locations, and increasingly specialized environments for AI.
That raises the bar for the platforms managing them.
We’re continuing to invest in making KKP easier to deploy, easier to operate, and easier to integrate—while maintaining the open, infrastructure-independent approach at its core.
We believe the best Kubernetes platform is not the one that tries to own every layer. It’s the one that gives platform teams control over the infrastructure underneath, flexibility in the tools around it, and a simpler experience for everyone who depends on it.
If you’re evaluating Kubernetes management at scale, have a chat with our experts and explore how KKP can simplify operations across your environments.
Read the full Gartner® evaluation
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