As cloud-native environments become more complex, efficiently managing Kubernetes clusters is crucial. This session will explore how AI and machine learning can integrate with Kubernetes to enable predictive scaling and self-tuning of resources. Attendees will learn how AI models can analyze workload patterns, forecast demand, and automatically adjust cluster resources. We’ll cover techniques such as using reinforcement learning for resource allocation and predictive analytics for auto-scaling, ensuring performance while optimizing costs. By allowing Kubernetes to autonomously fine-tune itself, organizations can achieve more efficient, resilient, and cost-effective cloud-native systems. Join us to discover how AI can transform Kubernetes into an autonomous platform for continuous optimization.