Machine learning has a habit of making cloud bills grow faster than expected. A small experiment might need one CPU instance for a few hours. A production deep-learning project can suddenly require dozens of GPUs,…
MLOps
How Cloud-Native Architecture Supports Large-Scale AI Deployment
Building a machine-learning model in a notebook can be surprisingly easy. Running that same model for millions of users is a completely different engineering problem. Production AI needs accelerators, model servers, storage, networking, monitoring, security,…