Moving an AI workload to another cloud means bringing more than a model and its data. Your serving layer, observability dashboards, security controls, and storage systems have to work together on the new infrastructure. For platform teams, proving those connections under real traffic can become the slowest and riskiest part of the move. As a stack grows across vendors and clouds, each project adds more integration questions. A compatible specification is a starting point. It doesn’t guarantee a tool will behave as expected in production, or that the runbooks and security workflows built...

Source: The New Stack