For a scalable, cost‑efficient architecture I’d split the system into stateless microservices, each in its own Docker container. Use an API gateway or service mesh to route traffic, so you can add or remove services without touching the client side. Keep the codebase modular with a shared library for common utilities, but version‑control that library separately so updates are easy to roll out. Use a container orchestrator like Kubernetes to manage scaling automatically—pods spin up when CPU or memory hits a threshold, and spin down when the load drops. Add a horizontal load balancer in front of the gateway to spread traffic evenly. Persist data in a cloud‑native database that supports sharding or horizontal scaling, like CockroachDB or a managed NoSQL store. Cache hot data in Redis or a CDN so the services stay lightweight. Automate everything: CI/CD pipelines that run unit tests, build images, and deploy to a staging environment, then to production with zero‑downtime rolling updates. With this layered, modular setup you can add new features or scale out specific services without touching the whole stack, keeping costs down and performance up.