AI workloads thrive on cloud-native platforms like Kubernetes because they offer the scalability, portability, and speed needed for modern machine learning—but building and running this infrastructure is highly complex and distracts from core AI work. The post argues that unless your business is infrastructure engineering, teams should avoid spending precious time managing Kubernetes and instead leverage managed Kubernetes services to handle platform operations.
