Moving a Next.js App From Vercel to AWS: Options and Steps

Good reasons: you need private networking to databases or internal services, compliance requires resources in your own AWS account, your usage makes the bill unattractive, or you want one platform for everything. Weak reasons: general dislike of a vendor, or a belief that AWS is automatically cheaper. You'll be trading a managed platform for your own operations work.

Write down what you'll take on: build pipelines, scaling, cache invalidation, certificates, logs and previews. If nobody on the team wants to own those, the migration cost may outweigh any savings. Estimate engineer time honestly, and compare with your current bill before committing.

Two broad approaches exist:

• Container on ECS (Fargate or EC2): build Next.js in standalone output mode, package it in a Docker image, run it behind a load balancer, and put a CDN in front for static assets. Familiar, predictable, and easy to reason about. You handle scaling rules and image caching yourself. Cost tradeoffs are in ECS Fargate vs EC2 cost.
• Serverless on Lambda with a CDN: community adapters translate Next.js output into functions, storage and CloudFront configuration. It scales to zero and is close to how Vercel works, but you depend on the adapter keeping up with Next.js releases, and debugging spans several services.
• Static export: if your app has no server features, exporting to static files on S3 with CloudFront is the simplest option, but you lose server rendering and route handlers.

For most small teams that need predictability, containers are the lower-risk choice. Choose serverless when scale-to-zero matters and you're comfortable owning the adapter.

List each platform feature your app relies on and decide its replacement:

1. Builds and deploys: a CI pipeline that builds the image, pushes it, and updates the service. See CI/CD pipeline template for Next.js.
2. Caching and ISR: incremental static regeneration needs a shared cache location when you run several instances, so plan a cache store instead of relying on local disk.
3. Image optimization: decide whether your containers handle it, or use a separate image service or CDN feature.
4. Middleware and edge functions: check which runtime they need, since they may not behave identically off the platform.
5. Environment variables and secrets: move them to a secrets store injected at deploy.
6. Preview deployments: build a per-pull-request environment or accept a shared staging site.
7. Logs, analytics and alerts: connect logging and monitoring, since the built-in dashboards go away.

Run the app on AWS behind a temporary hostname and go through every route, including authentication callbacks that have hard-coded domains.

Lower your DNS time-to-live in advance. Move a small share of traffic first if your DNS provider supports weighted routing, then increase. Watch error rate, latency, cache hit ratio and cold starts, and compare against baseline numbers from before the move. Update third-party settings that reference your domain, such as OAuth redirect URLs and webhook endpoints.

Keep the Vercel project deployed and unchanged for a rollback window. DORA's 2024 report describes deployment frequency from on demand down to one every one to six months across its clusters¹, so confirm your new pipeline didn't slow releases. Also plan the account layout early; multi-account AWS setup and the Heroku to ECS checklist cover related steps.

Expect these:

• Stale pages after deploys because the CDN and application caches aren't invalidated together.
• Images that load slowly because optimization now runs on undersized containers.
• Authentication breaking on callback URLs still pointing at the old host.
• Surprise bills from data transfer and NAT gateways.
• No one owning on-call for the new stack. Decide before cutover.

For cloud-choice context, compare AWS vs GCP vs Azure for startups before deepening your commitment to one provider.