Week 2 - ML Foundations
Containers Before Kubernetes: The Primitive Behind Modern ML Engineering
A foundations article on containers as reproducible execution worlds for Python and AI workloads.
Abstract: Before orchestration, there is a simpler idea: preserve the conditions under which the program makes sense. Containers give ML engineering a runnable world: image, dependencies, runtime assumptions, ports, files, and repeatable startup. Like an emulator for an old game, the value is not glamour. It is continuity.
LinkedIn angle
Make this a practical “before Kubernetes” post for engineers moving from Python experiments into reliable ML workloads.