I Migrated My AI Agents from Azure to AWS — Here's the Minimal Setup You Actually Need

After migrating my agent-based document processing system from Azure to AWS, one thing became obvious: Most cloud setups are wildly over-engineered for development. You don’t need half the services people default to just to build and test a distributed system. Here’s the minimal AWS architecture you actually need to develop and run an agent-based pipeline end-to-end — plus what each piece maps to if you’re coming from Azure. The System Before we even touch the cloud layer, here’s what’s actually running. At its core, this is a pipeline of independent Python workers processing documents in stages. Each worker listens to its own queue, does one job well, and hands off to the next stage. In front of that sits a hybrid FastAPI gateway exposing both REST and GraphQL endpoints, depending on the consumer. Five containers total: gateway ai-core collector exporter redis [insert architecture diagram here] Core Services — What You Actually Need If you're building something similar on AWS, these a