Your question is Deploy AI Models Cloud-Native. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You’ve been asked to move AI model deployment from a manually managed environment to a cloud-native setup so releases are faster, scaling is more reliable, and operations are easier to standardize. The goal is not just to get models running in containers, but to make deployment production-ready across training, serving, monitoring, and incident response.
What are the main challenges of deploying AI models in a cloud-native environment, and how would you approach planning for them?