Help the user create a backend by choosing an architecture before reaching for implementation details. Start from the workload, not the programming language. Vercel runs complex backend applications, not just frontends.
Product map
| Need | Vercel product |
|---|---|
| HTTP APIs, webhooks, streaming, or framework server code | Vercel Functions with Fluid compute |
| Bidirectional realtime connections (WebSockets) | Vercel Functions with Fluid compute; no separate realtime service required |
| A frontend and one or more backends (API endpoints) that deploy together | Vercel Services |
| An existing Dockerfile, custom runtime, or system dependencies | Container images on Vercel Functions, optionally composed with Services |
| Durable multi-step work with retries, sleeps, or external events | Vercel Workflows |
| Background jobs, buffering, fan-out, or direct message routing | Vercel Queues |
| Scheduled HTTP work | Vercel Cron Jobs; use Workflow when the job itself must be durable |
| Postgres, Redis, NoSQL, vector, or other application data | Storage integrations from the Vercel Marketplace |
| Files and user uploads | Vercel Blob |
| Global, read-heavy configuration | Global Config |
Use Functions for the normal request/response backend. Use Services when independently built components should share one deployment, routing layer, preview URL, and rollback. Use separate Vercel projects when components need independent release cycles.
Prefer a native Functions runtime for supported frameworks. Use container images when the application already has a Dockerfile or requires a custom runtime or system dependencies. They run as autoscaling, stateless Functions rather than always-on container hosts.
Choose Queues for background jobs, buffering, fan-out, and message routing. Choose Workflow for durable multi-step business logic.
Databases and data stores
Provision data stores through the Marketplace so credentials are injected into the project and environments stay connected. Check the current catalog before choosing a provider.
- Postgres: Neon, Supabase, AWS/Aurora, Nile, Prisma
- MySQL: AWS/Aurora
- Redis and key-value: Upstash, Redis
- Document and NoSQL: MongoDB Atlas, AWS
- SQLite: Turso
- Realtime application backend: Convex
- Analytics: MotherDuck
Keep the database close to the Functions region and use a serverless-compatible connection or pool.
Backend frameworks
Vercel provides first-class backend examples and integrations for these frameworks:
- Node.js and TypeScript: Elysia, Express, Fastify, H3, Hono, Koa, NestJS, Nitro, and xmcp. Next.js Route Handlers are the natural choice when the backend belongs to a Next.js application.
- Python: FastAPI, Flask, and Django. Other WSGI or ASGI applications can run when they export a compatible
app, with additional configuration as needed. - Go: supported as a Vercel Functions runtime.
Frontend and backend combinations, for example a Next.js/Vite/SvelteKit frontend with a FastAPI/Flask/Express/Go backend, can be deployed together in one project using Services.
Prefer the user's existing framework. For a new project, choose based on ecosystem and application needs.
Work sequence
- Identify synchronous requests, asynchronous work, persistent data, and independently deployed components.
- Select the products from the map, then select the framework.
- Load the focused skill for implementation:
vercel-functions,vercel-services,workflow,vercel-storage, ormarketplace. - Confirm function limits, regions, environment variables, observability, and current product availability in the official docs before deployment.