Operations | Monitoring | ITSM | DevOps | Cloud

Prediction: The next evolution of Kubernetes is not about scale alone, but about intelligence, autonomy, and governance. As part of the article ‘AI and Enterprise Technology Predictions from Industry Experts for 2026′, published by Solutions Review, Ratan Tipirneni, CEO of Tigera, shares his perspective on how AI and cloud-native technologies are shaping the future of Kubernetes.

The world of Kubernetes networking can sometimes be confusing. What’s a CNI? A service mesh? Do I need one? Both? And how do they interact in my cluster? The questions can go on and on. Even for seasoned platform engineers, making sense of where these two components overlap and where the boundaries of responsibility end can be challenging. Seemingly bewildering obstacles can stand in the way of getting the most out of their complementary features.

For years, platform teams have known what a service mesh can provide: strong workload identity, authorization, mutual TLS authentication and encryption, fine-grained traffic control, and deep observability across distributed systems. In theory, Istio checked all the boxes. In practice though, many teams hit a wall. Across industries like financial services, media, retail, and SaaS, organizations told a similar story. They wanted mTLS between services to meet regulatory or security requirements.

Ingress NGINX Controller, the trusty staple of countless platform engineering toolkits, is about to be put out to pasture. This news was announced by the Kubernetes community recently, and very quickly circulated throughout the cloud-native space. It’s big news for any platform team that currently uses the NGINX Controller because, as of March 26, 2026, there will be no more bug fixes, no more critical vulnerability patches and no more enhancements when Kubernetes continues to release new versions.

Organizations are struggling with rising operational complexity, fragmented tools, and inconsistent security enforcement as Kubernetes becomes the foundation for modern application platforms. As a result of this complexity and fragmentation, platform teams are increasingly burdened by the need to stitch together separate solutions for networking, network security, and observability.

If you’ve managed traffic in Kubernetes, you’ve likely worked with Ingress controllers. For years, Ingress has been the standard way to expose HTTP and HTTPS services. But in practice, it often came with trade-offs. Controller-specific annotations were required to unlock critical features, the line between infrastructure and application responsibilities was unclear, and configurations often became tied to the implementation rather than the intent.

The Tigera team recently returned from KubeCon + CloudNativeCon North America and CalicoCon 2025 in Atlanta, Georgia. It was great, as always, to attend these events, feel the energy of our community, and hold in-depth discussions at the booth and in our dedicated sessions that revealed specific, critical shifts shaping the future of cloud-native platforms.

When your Kubernetes cluster handles thousands of workloads, every millisecond counts. And that pressure is no longer the exception; it is the norm. According to a recent CNCF survey, 93% of organizations are using, piloting, or evaluating Kubernetes, revealing just how pervasive it has become. Kubernetes has grown from a promising orchestration tool into the backbone of modern infrastructure. As adoption climbs, so does pressure to keep performance high, networking efficient, and security airtight.

The Ingress NGINX Controller is approaching retirement, which has pushed many teams to evaluate their long-term ingress strategy. The familiar Ingress resource has served well, but it comes with clear limits: annotations that differ by vendor, limited extensibility, and few options for separating operator and developer responsibilities. The Gateway API addresses these challenges with a more expressive, standardized, and portable model for service networking.

Kubernetes has transformed how teams build and scale applications, but it has also introduced new layers of complexity. Platform and DevOps teams must now integrate and manage multiple technologies: CNI, ingress and egress gateways, service mesh, and more across increasingly large and dynamic environments.