Securing and Governing AI/ML Workloads on Amazon EKS with Agentic AI, Nirmata & Kyverno

As organizations deploy more AI and machine learning workloads on Amazon EKS, ensuring robust governance, security, and compliance becomes essential. This workshop demonstrates how Agentic AI, together with Nirmata’s policy management platform and Kyverno, the leading Kubernetes-native policy engine, delivers comprehensive governance for AI/ML workloads on EKS.

Join us to learn how to:

• Implement guardrails for GPU resource allocation and utilization
• Enforce security policies tailored to AI/ML containers and frameworks
• Use agentic AI to auto-generate, validate, and test Kyverno policies, reducing misconfigurations and manual effort
• Automate cluster governance on EKS with Kyverno’s policy-as-code approach enhanced by Nirmata’s AI-driven management
• Monitor and audit AI workload behavior and compute resource consumption

We’ll work through real-world examples of policy-as-code implementation using Kyverno to secure AI applications, prevent misconfigurations, and optimize resource usage so you can learn how to do this in the wild. You’ll also see how Nirmata’s AI policy management capabilities enhance visibility and control over your AI infrastructure while maintaining development velocity.

This session is ideal for Cloud Architects, Platform Engineers, Security and DevOps professionals who are responsible for Kubernetes and AI workloads on Amazon EKS and want to implement strong governance and automation without slowing down delivery or innovation.