Besides its generative capabilities, AI is also a tool that blurs software lifecycle boundaries, shifting you toward self-service platforms. Dev and Ops emerge into platform engineering, powered by fast-consumable knowledge from AI assistants. Still, layering abstractions on top of abstractions raises many questions as complexity increases.

In this session, we'll explore how modern platform engineering changes the way Java applications are built, deployed, and operated. We'll look at the evolution from traditional DevOps practices to GitOps workflows, self-service environments, and developer experience as a first-class engineering concern.

Through real-world examples, we'll examine how platform teams abstract Kubernetes and cloud infrastructure, without taking absolute control away from developers. We'll discuss common platform engineering patterns, Java deployment optimizations, startup probes, JVM and container memory, Autoscaling myths, and debugging production issues.