> The fundamental problem is where the data resides. Microservices are well understood today, but taking them to the edge isn't; there isn't a path to do that f

> The fundamental problem is where the data resides. Microservices are well understood today, but taking them to the edge isn't; there isn't a path to do that for typical apps. So most microservices which are being used at the edge are doing caching/transcoding/resizing etc. If an application follows a Microservice architecture, then it is possible to containerize it and enable its autonomic management through frameworks like Kubernetes and Docker Swarm, which is one way forward to improve performance efficiency of typical apps. Yes, the problem is where the data resides. Migrate portions of it nearer to clients to the Edge, and clients will have the illusion of lower latency. Maintaining data consistency and coherence are yet problems not properly tackled, but in edge computing it means computations happen in these migrated portions of data, and not "all the way" at the cloud (higher latency) anymore. > They keep compute on-vehicle or on-prem. For data services (not media delivery), latency is: Not always. They will use the Edge mostly for inference and for learning from others (transfer learning), but sometimes also for training and model updates. And in cases like this (known as Mobile Edge Cloud), the ability to obtain granular and immediate control by supporting custom logic at the edge of a network is particularly useful in routing traffic to the microservices that make up a service. I agree, GraphQL helps reducing latency, mostly because the amount of data is now "granular" and it is one way to overcome limitations in 'traditional' apps (e.g. Rest APIs). Coalescing may be useful in some cases, but perhaps not in situations where one needs to maintain 95th/99th percentiles up to certain threshold constraints. Together with Edge (as I guess you mentioned), it is a win-win performance-wise. But then again, maintaining consistency and coherence are yet problems to be tackled. And guess what, applications still need to be updated to use GraphQL and use its features. Just like people will do when developing for the Edge.