A signup handler has to send a welcome email, and sending it inline puts a third-party API call inside your request. So you move it into a background job, and the usual next step is Redis, a client library, a worker process, a dashboard, and a note in the deploy docs about what happens to queued jobs when Redis restarts without persistence. If the app runs on one machine, you’ve added a second stateful service to look after a table’s worth of data.

A user signs up on Monday. If they haven’t activated by Wednesday, you send a nudge email, and if the email provider times out, you try a few more times before flagging the account. That’s the whole spec. Most teams build it as a cron job that scans for users in the wrong state, a nullable nudge_sent_at column and a retry loop written late on a Friday. It holds until the cron overlaps itself, or a deploy lands mid-loop, or the provider times out after actually sending the message and one customer gets three emails.

A command-line tool should run only one copy of its nightly export at a time. A small web app wants to cap each user at 60 requests a minute. A desktop app needs to remember when it last synced. All three are state: an integer, a timestamp, an owner. All three usually get solved by adding Redis, because Redis has the verbs for them: INCR, SET NX PX, EXPIRE. The app needed the verbs and got a server along with them, a port and a persistence config included.

Most sites run a thin slice of nginx in front of their application: TLS termination, serving static files from a folder, a couple of routes to a backend service, health checks, and the occasional reload. The configuration grows anyway, one regular expression at a time, until nobody is quite sure which block handles a given URL, and a change that looks safe to one person breaks something in production that another person didn’t know existed.

Most dashboards ask the same few questions all day long: requests per endpoint, month-to-date usage for one customer, error rates by status code. The usual setup recounts raw rows from scratch on every refresh, or ships every row to a hosted analytics service that bills by the gigabyte. A dashboard that needs to answer quickly on demand either waits for a database query to finish, or pays for a service that stores everything.

Every mobile app that does anything interesting eventually needs a backend. Authentication, data storage, push notifications, file uploads, real-time updates — the list of backend requirements grows quickly once an app moves beyond a local-only experience. The decision of how to provide that backend is one of the most consequential architectural choices a mobile development team makes, and it is one that becomes substantially harder to reverse after significant user data has accumulated.