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The Rise of AI Agents and the Reinvention of Kubernetes: Ratan Tipirneni’s 2026 Outlook

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.

His predictions describe how production clusters are evolving as AI becomes a core part of enterprise platforms, introducing new requirements for security, networking, and operational control.

Looking toward 2026, Tipirneni expects Kubernetes to move beyond its traditional role of running microservices and stateless applications. Clusters will increasingly support AI-driven components that operate with greater autonomy and interact directly with other services and systems. This shift places new demands on platform teams around workload identity, access control, traffic management, and policy enforcement. It also drives changes in how APIs are governed and how network infrastructure is designed inside the cluster.

Read on to explore Tipirneni’s predictions and what they mean for teams preparing Kubernetes platforms for an AI-driven future.

AI Agents Become First-Class Workloads

By 2026, Tipirneni predicts that Kubernetes environments will increasingly host agent-based workloads rather than only traditional cloud native applications. Continue reading

AI Meets Kubernetes Security: Tigera CEO Reveals What Comes Next for Platform Teams

Kubernetes adoption is growing rapidly, but so are complexity and security risks.

Tigera CEO, Ratan Tipirneni, on Calico AI and the Push for Simpler, Unified Kubernetes Security

Platform teams are tasked with keeping clusters secure and observable while navigating a skills gap. At KubeCon + CloudNativeCon North America, The New Stack spoke with Ratan Tipirneni, President and CEO of Tigera, about the future of Kubernetes security, AI-driven operations, and emerging trends in enterprise networking. The highlights from that discussion are summarized below.

Portions of this article are adapted from a recorded interview between The New Stack’s Heather Joslin and Tigera CEO Ratan Tipirneni. You can watch the full conversation on The New Stack’s YouTube channel. Watch the full interview here

How Can Teams Better Manage the Kubernetes Blast Radius and Skills Gap?

Tipirneni emphasizes the importance of controlling risk in Kubernetes clusters. “You want to be able to microsegment your workloads so that if you do come under an attack, you can actually limit the blast radius,” he says.

Egress traffic is another area of concern. According to Tipirneni, identifying what leaves the cluster is critical for security and compliance. Platform engineers are often navigating complex configurations without decades of Continue reading

KubeCon NA 2025: Three Core Kubernetes Trends and a Calico Feature You Should Use Now

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.
We pulled together observations from our Tigera engineers and product experts in attendance to identify three key trends that are directly influencing how organizations manage Kubernetes today.

🤖 Trend 1: Kubernetes is Central to AI Workload Orchestration

A frequent and significant topic of conversation was the role of Kubernetes in supporting Artificial Intelligence and Machine Learning (AI/ML) infrastructure.
The consensus is clear: Kubernetes is becoming the standard orchestration layer for these specialized workloads. This requires careful consideration of networking and security policies tailored to high-demand environments. Observations from the Tigera team indicated a consistent focus on positioning Kubernetes as the essential orchestration layer for AI workloads. This trend underscores the need for robust, high-performance CNI solutions designed for the future of specialized computing.

🌐 Trend 2: Growth in Edge Deployments Increases Complexity

Conversations pointed to a growing and tangible expansion of Kubernetes beyond central data centers and Continue reading

5 Essential Steps to Strengthen Kubernetes Egress Security

Securing what comes into your Kubernetes cluster often gets top billing. But what leaves your cluster, outbound or egress traffic, can be just as risky. A single compromised pod can exfiltrate data, connect to malicious servers, or propagate threats across your network. Without proper egress controls, workloads can reach untrusted destinations, creating serious security and compliance risks. This guide breaks down five practical steps to strengthen Kubernetes egress security, helping teams protect data, enforce policies, and maintain visibility across clusters.

Why Egress Controls Matter 🔐

By default, Kubernetes allows unrestricted outbound communication, meaning any pod can reach any external destination and dramatically increase the attack surface. Implementing egress controls ensures pods can communicate only with explicitly trusted services, containing the impact of a compromised workload and preventing unauthorized data exfiltration or lateral movement.

Granular egress controls are also essential for meeting security and compliance mandates, providing authorization, logging, and monitoring for all external connections.
The image illustrates how a single routable IP can centralize and control all Kubernetes egress traffic to external services through a single firewall rule.
How a single routable IP can centralize and control all Kubernetes egress traffic to external services through a single firewall rule.

Your Kubernetes Egress Security Checklist

To help teams tackle this challenge, we’ve put together a Kubernetes Egress Security Checklist, based on best practices from real-world Continue reading

When to Use BGP, VXLAN, or IP-in-IP: A Practical Guide for Kubernetes Networking

When deploying a Kubernetes cluster, a critical architectural decision is how pods on different nodes communicate. The choice of networking mode directly impacts performance, scalability, and operational overhead. Selecting the wrong mode for your environment can lead to persistent performance issues, troubleshooting complexity, and scalability bottlenecks.

The core problem is that pod IPs are virtual. The underlying physical or cloud network has no native awareness of how to route traffic to a pod’s IP address, like 10.244.1.5 It only knows how to route traffic between the nodes themselves. This gap is precisely what the Container Network Interface (CNI) must bridge.

The OSI Model
The OSI Model: Understanding Layers 3 and 4 is key to seeing how CNI modes add or avoid packet overhead.

The CNI employs two primary methods to solve this problem:

  1. Overlay Networking (Encapsulation): This method wraps a pod’s packet inside another packet that the underlying network understands. The outer packet is addressed between nodes, effectively creating a tunnel. VXLAN and IP-in-IP are common encapsulation protocols.
  2. Underlay Networking (Routing): This method teaches the network fabric itself how to route traffic directly to pods. It uses a routing protocol like BGP to advertise pod IP routes to the physical Continue reading