AI workloads are increasingly running on Kubernetes in production, but for many teams, the path from a working model to a reliable system remains unclear. The cloud native ecosystem – its projects, patterns, and community – offers a growing set of building blocks that help teams bridge these two worlds.
From model to systems
AI Engineering is the discipline of building reliable, production-grade s...
The article presents a pattern of integration between the cloud native ecosystem and AI Engineering, acknowledging the growing need for reliable infrastructure to support AI models in production. The focus on composability, portability, and community-driven evolution emphasizes the importance of open source and vendor-neutral governance in this context. However, it also highlights a potential divide between AI practitioners and cloud native practitioners, suggesting that bridging this gap could ...