An Uber engineer gave a great talk at Kubecon I have wanted to write about: “...we end up having to think about use cases that can either reside entirely within one cloud provider so that I can put training and serving together, or I need to think about the use cases where it makes sense to actually pull the data from one provider to another, in order to facilitate being able to leverage that compute. It doesn’t make it quite as seamless as it could be, and you have to be purposeful in how you think about what workloads you’re going to be converging together.” Two sentences. They explain why multicloud is complicated. It works! But it's not just "spread stuff everywhere and balance." And when you're thinking about it for yourself, put this in context. Uber has dedicated platform engineering teams , specialized GPU infrastructure groups, and the budget to build custom observability solutions. They still struggle with this.…