How to Deploy a SaaS App to Production

From Vercel free tier to a production infrastructure that handles real DAU - the deployment that doesnt fall over.

Every SaaS app starts on Vercel or Railway. At some point - usually right after a successful launch - the free tier breaks. This guide covers the production deployment setup that handles real traffic: cloud platform selection, containerization, managed database, CDN, monitoring, and the configuration that does not fall over at 500 concurrent users.

No fluff. Production-grade answers from engineers who ship AI into real products.

The Vercel Free Tier Cliff and How to Get Past It

Vercel is excellent for prototypes and low-traffic apps. The limits that matter for SaaS: serverless function timeout (10s on hobby), no persistent connections to database (cold start + connection = slow), bandwidth limits, no background workers, and function concurrency limits. Moving to a proper production setup is not optional - it is a scheduled event that should happen before you need it.

At Valletta.Software, we focus on:

Cloud platform: AWS ECS Fargate or GCP Cloud Run - managed container execution no server management

Database: RDS PostgreSQL or Cloud SQL with connection pooler (PgBouncer) - not direct connections from serverless

Redis: ElastiCache or Memorystore - session storage rate limiting background job queue

Storage: S3 or GCS for user-uploaded files - not local disk on containers

CDN: CloudFront or Cloud CDN - serve static assets from edge not from app server

Environment config: AWS Parameter Store or Secret Manager - not .env files in the repo

Load balancer: ALB or GCP Load Balancer - SSL termination health checks routing

The Production Checklist Before You Go Live

Every item on this list has caused a production incident for a startup that skipped it.

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SSL certificate: ACM or Let's Encrypt with auto-renewal - not self-signed

Health check endpoint: /health that returns 200 with DB connectivity check - required for load balancer

Graceful shutdown: handle SIGTERM correctly - containers get 30s to finish in-flight requests

Database migrations: run migrations before deploying new code not after - never break prod schema

Rate limiting: per-IP and per-user limits at the API level - before the first abuse attempt

Error tracking: Sentry or Datadog APM - know about errors before users report them

Backup verification: restore test on staging monthly - backups that have never been restored dont count

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Set up production infra - CI/CD, Docker, Kubernetes, monitoring - from day one

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How to Deploy a SaaS App to Production - With Engineers Who Have Done It for 100+ Products

Lets keep it simple.

Our engineers use Cursor, Claude Code, and AI-native tooling daily - not just to build AI products, but to ship them to production, maintain them, and scale them.

Lets keep it simple.

Our engineers have deployed SaaS apps to production across AWS GCP and Azure - from the first deploy to multi-region high-availability setups. We know what the vibe-coded app is missing and what to fix first.

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