KubeCon EU 2025 Recap: Kubernetes Meets AI - a New Decade of Cloud Native development

KubeCon + CloudNativeCon Europe 2025 landed in London, bringing together thousands of cloud-native engineers, maintainers, and enthusiasts. As a local Distributed Systems Engineer deeply embedded in the Kubernetes ecosystem, attending in person was both energizing and insightful. A central theme emerged across sessions: Kubernetes is rapidly evolving beyond microservices, adapting to support batch workloads, AI/ML training, HPC scenarios, and global-scale multi-cluster deployments. This shift isn’t just technical - it’s reshaping the cloud-native landscape and redefining how we think about workload orchestration, scheduling, and autoscaling. Kubernetes may not have been built for these new frontiers - but it’s catching up fast…

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No borders, no strangers - Stay Human

I grew up in a small town in southern Italy as a child of the Erasmus generation. I never knew borders - not in the way past generations did. Thanks to the European Union, I could move freely, study abroad, live, and work in different countries without a passport or visa. I was never a foreigner - only a person among people. And yet, despite everything we have built together, despite decades of peace…

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A perspective on the current and future state of Kubernetes scheduling

Kubernetes scheduling is the brain of the cluster, deciding which node runs each Pod. In this post, I explore advanced scheduling mechanisms in Kubernetes. I start with how the default scheduler works under the hood, then dive into the scheduler-plugins project for extending its capabilities. I review custom schedulers and plugins in the ecosystem that focus on cost savings, SLA optimization, and performance tuning. Finally, I look at future trends in Kubernetes scheduling, from AI-driven algorithms to multi-cluster and energy-aware schedulers. This post brings together the key ideas from the full series I wrote on Kubernetes scheduling.

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