From Platform Paralysis to Production: Why We Chose Netlify and Railway

Written by pnadagoud | Published 2025/10/01
Tech Story Tags: netlify | railway | web-app-development | deployment | fastapi | cicd | startups | web-hosting

TLDRWhen building a web application, the hardest decision wasn’t about the code, but where to deploy it. After weeks of analysis paralysis and way too many comparison spreadsheets, we finally landed on a deployment stack that got us shipping fast without breaking the bank. We chose Netlify and Railway because of their frontend and backend capabilities.via the TL;DR App

When we started building our web application, the hardest decision wasn’t about the code—it was about where to deploy it. Like most developers, we found ourselves drowning in hosting options, each promising to be “the ultimate solution.” After weeks of analysis paralysis and way too many comparison spreadsheets, we finally landed on a deployment stack that got us shipping fast without breaking the bank: FastAPI + PostgreSQL on Railway paired with React/Tailwind on Netlify.

Here’s the real story of how we escaped platform paralysis and what we learned along the way.


What Are Netlify and Railway?

Before diving into our decision process, let me quickly explain what these platforms actually do.

Netlifyspecializes in static sites and frontend applications. It handles everything from Git deployments to global CDN distribution, plus serverless functions, instant preview URLs, and automatic HTTPS. Basically, it makes frontend deployment feel effortless.**
Railway** focuses on backend infrastructure without the complexity. You can deploy APIs, databases, and services with minimal configuration—often just a few clicks. It handles database provisioning, container deployments, and environment variables, which means less DevOps headaches for growing projects.

The Great Platform Evaluation

We approached this decision like engineers—building a comparison matrix of four realistic and popular stacks:

AWS (Elastic Beanstalk + RDS) offered enterprise-grade everything, but honestly felt like overkill. We’re not Netflix. The platform demanded DevOps expertise we don’t have yet and carried a baseline cost exceeding $40/month before we’d served our first user. Hard pass.

Vercel + Supabase had an incredibly polished developer experience that made me want to love it. But there was a catch—it required completely rewriting our FastAPI backend into serverless functions and migrating our entire PostgreSQL schema to Supabase. We’re talking weeks of work, not days.

DigitalOcean App Platform struck a reasonable middle ground between effort and cost. The “Goldilocks” option, if you will. But it couldn’t match the zero-maintenance CI/CD experience we were targeting for rapid iteration cycles.

Netlify + Railway just clicked immediately. We could deploy our existing FastAPI service with minimal changes, keep our PostgreSQL database exactly as designed, and serve our React frontend through a globally distributed CDN. Both platforms offered generous free tiers with transparent pay-as-you-grow pricing.

The winner became clear when we prioritized shipping over theoretical scalability. Sometimes the best technical decision isn’t the most impressive one—it’s the one that gets your product in front of users fastest.

Why Netlify Won Our Frontend

Our React/Tailwind application found its perfect home on Netlify’s CDN. What really sold us were three things that completely changed how we ship frontend code:

Global distribution happened automatically. Our standard build process (`npm run build` with a simple `netlify.toml`) got worldwide edge caching without any additional configuration. No CDN setup, no edge location mapping—it just worked.

Every pull request generated a shareable preview URL, which completely transformed our UX review process from “deploy and hope” to “see and iterate.” Being able to share a live preview with stakeholders before merging? This is a game changer.

HTTPS and single-page application routing worked out of the box. No server configuration, no certificate management, no redirect rules to debug.

Why Railway Clicked for Our Backend

Railway just made sense for our FastAPI + PostgreSQL stack in ways that surprised me:

Container deployment happened without wrestling with Dockerfile configurations or container orchestration. Our backend deployed in minutes, not hours of troubleshooting.

We got managed PostgreSQL that kept the exact same schema we developed locally, now enhanced with automated backups and one-click scaling capabilities. No migration headaches, no schema translation.

Environment variable management became elegant—secrets across staging and production were as simple as cloning a service and adjusting a few values.

System Architecture

This diagram below emphasizes our “static frontend + API backend” split, with Netlify serving the prebuilt React bundle and Railway handling authenticated API traffic and persistence.

Environment Separation That Actually Works

After accidentally corrupting our staging data twice, we got serious about branch separation. Here’s our current setup:

Branch Structure:

•`master`: Production deployments for both frontend and backend

•`railway-staging`: Backend staging branch feeding Railway’s staging service

•`netlify-staging`: Frontend staging branch connected to Netlify’s staging site

Netlify Configuration:
Our production site tracks the master branch with our main domain, while staging tracks netlify-staging with a dedicated staging URL. Each environment uses distinct REACT_APP_API_BASE_URL values pointing to corresponding Railway endpoints.

Railway Setup:
Production service deploys from master with production database credentials and API keys. Staging service clones the production configuration but overrides critical variables like database URLs and allowed origins. Most importantly, PostgreSQL databases exist in completely separate projects—zero risk of data contamination.


CI/CD Pipeline Architecture

The deployment pipeline automates quality gates while keeping environments isolated:

  1. Development Phase: Feature branches trigger GitHub Actions for comprehensive linting and testing

  2. Staging Validation: Merges to staging branches automatically deploy to respective staging environments for validation

  3. Production Release: Pull requests into master deploy to production only after passing all automated checks

    This sequence diagram highlights how staging and production flows share automation but stay isolated until promotion.

Let’s Talk Numbers

Because cost actually matters when you’re building a sustainable product:

Current State

  • Netlify: Free tier covers our needs comfortably (we’re nowhere near 100GB bandwidth monthly)
  • Railway: We’re on the Hobby plan ($5/month) which gives us the resources we need with predictable scaling as we grow

Future Reality

Even when we hit 10,000+ daily active users, both platforms offer linear scaling without requiring platform migration. Railway supports horizontal scaling, and Netlify provides higher bandwidth tiers—no architectural rewrites needed.

Hard-Won Lessons

After six months in production, here’s what I wish we’d known from day one:

  • Developer experience trumps theoretical scale. We decided to worry about actually getting users before worrying about scaling to millions of them.
  • Environment cloning is incredibly powerful. Railway’s service cloning combined with Netlify’s branch deployments let us create production-like staging environments in seconds, not hours.
  • Data isolation is non-negotiable. Separate database instances eliminated any risk of staging data contaminating production—a lesson learned from previous painful experiences.
  • Document everything. Publishing our branching and deployment requirements directly in the repository keeps team onboarding smooth.


The Bottom Line

Our Netlify and Railway stack gave our web application a dependable, cost-conscious foundation that respected our existing codebase while keeping operational overhead minimal. We can ship features confidently, validate changes in production-like environments, and scale seamlessly when user growth demands it.

The architecture isn’t the most technically impressive solution we could have built—but it’s the one that got our product in front of users fastest while maintaining room to grow. Sometimes that’s exactly what you need.


Written by pnadagoud | Senior Software Engineer with 13+ years of experience building enterprise integrations, APIs, and internal tools at leading tech companies. Passionate about scalable systems, clean architecture.
Published by HackerNoon on 2025/10/01