Cursor storage

File System Operations Failing in Production After Cursor Build

Your Cursor-generated application reads and writes files to the local file system, which works perfectly during local development but fails in production. The app crashes with ENOENT, EACCES, or EROFS errors when trying to create temp files, write uploads, or read generated content.

This is a common trap with AI-generated code. Cursor writes straightforward file system code using fs.writeFile, fs.readFile, or similar APIs because it's the simplest approach. But modern production environments — serverless functions (Vercel, AWS Lambda, Netlify), containerized deployments (Docker, Kubernetes), and PaaS platforms (Heroku, Railway) — either have read-only file systems, ephemeral storage that gets wiped between invocations, or no local disk at all.

The issue often surfaces only after deployment, when the first user triggers a file operation and gets a server error.

Error Messages You Might See

EROFS: read-only file system, open '/var/task/uploads/file.png' ENOENT: no such file or directory, open './data/output.json' EACCES: permission denied, mkdir '/app/temp' Error: ENOSPC: no space left on device EPERM: operation not permitted, write
EROFS: read-only file system, open '/var/task/uploads/file.png'ENOENT: no such file or directory, open './data/output.json'EACCES: permission denied, mkdir '/app/temp'Error: ENOSPC: no space left on deviceEPERM: operation not permitted, write

Common Causes

  • Read-only file system in production — Serverless platforms and containerized environments mount the application directory as read-only
  • Ephemeral storage between invocations — Files written in one Lambda/serverless invocation are gone in the next
  • Hardcoded local paths — Cursor generated paths like /tmp/uploads or ./data that don't exist or aren't writable in production
  • /tmp directory size limits — Even when /tmp is writable (as in Lambda), it has strict size limits (512MB default) that are easily exceeded
  • Missing directory creation — Code writes to nested directories without first creating them with mkdirSync/mkdir -p
  • File path separators — Windows-style backslash paths generated during development fail on Linux production servers

How to Fix It

  1. Replace local file ops with cloud storage — Use S3, Supabase Storage, Cloudflare R2, or Google Cloud Storage instead of the local file system for any persistent file operations
  2. Use /tmp only for transient operations — If you must use local files (e.g., for image processing), write to /tmp and clean up immediately after. Never rely on files persisting
  3. Stream instead of buffering — Instead of writing a file to disk and then uploading it, stream data directly from the source to the destination
  4. Check for platform-specific storage APIs — Vercel has vercel/blob, Netlify has Netlify Blobs. Use platform-native storage when available
  5. Add fallback error handling — Wrap file operations in try/catch and provide meaningful error messages when the file system is unavailable
  6. Use environment detection — Check process.env.NODE_ENV or platform-specific env vars to choose between local and cloud storage

Real developers can help you.

Kingsley Omage Kingsley Omage Fullstack software engineer passionate about AI Agents, blockchain, LLMs. Tejas Chokhawala Tejas Chokhawala Full-stack engineer with 5 years experience building production web apps using React, Next.js and TypeScript. Focused on performance, clean architecture and shipping fast. Experienced with Supabase/Postgres backends, Stripe billing, and building AI-assisted developer tools. David Olverson David Olverson Solo dev shipping production apps with AI-assisted development. I specialize in rescuing broken Lovable/Bolt/Cursor builds and taking them to production. 10+ apps shipped including SaaS CRMs, gaming platforms, real estate tools, and Discord bots. Stack: Next.js 16, TypeScript, Tailwind CSS, FastAPI, PostgreSQL, Prisma. I use Claude Code with 50+ custom skills for rapid delivery. Average turnaround: 2-4 weeks from broken prototype to production. Daniel Vázquez Daniel Vázquez Software Engineer with over 10 years of experience on Startups, Government, big tech industry & consulting. Taufan Taufan I’m a product-focused engineer and tech leader who builds scalable systems and turns ideas into production-ready platforms. Over the past years, I’ve worked across startups and fast-moving teams, leading backend architecture, improving system reliability, and shipping products used by thousands of users. My strength is not just writing code — but connecting product vision, technical execution, and business impact. Pratik Pratik SWE with 15+ years of experience building and maintaining web apps and extensive BE infrastructure Dor Yaloz Dor Yaloz SW engineer with 6+ years of experience, I worked with React/Node/Python did projects with React+Capacitor.js for ios Supabase expert Matthew Jordan Matthew Jordan I've been working at a large software company named Kainos for 2 years, and mainly specialise in Platform Engineering. I regularly enjoy working on software products outside of work, and I'm a huge fan of game development using Unity. I personally enjoy Python & C# in my spare time, but I also specialise in multiple different platform-related technologies from my day job. MFox MFox Full-stack professional senior engineer (15+years). Extensive experience in software development, qa, and IP networking. Jacek Rozanski Jacek Rozanski Senior PHP/Symfony developer and DevOps engineer with 20+ years of professional experience, running opcode.pl (web development agency, est. 2004). Day job: I'm the sole backend developer at merketing company where I own and maintain 11 PHP/Symfony microservices on AWS (ECS Fargate, RDS, S3, CloudFront), handle the full CI/CD pipeline (Bitbucket Pipelines, Docker), and manage monitoring with Sentry and CloudWatch. These services handle high request volumes in production every month. What I bring to AI-built apps: - I audit and fix security issues (OWASP methodology), performance bottlenecks, and architectural problems in codebases generated by Cursor, Claude Code, Lovable, Bolt, and v0 - I refactor AI-generated prototypes into production-grade applications with proper error handling, testing, and clean architecture (SOLID, DDD, hexagonal architecture) - I set up the infrastructure AI tools don't touch: AWS hosting, CI/CD pipelines, automated deployments, database optimization, monitoring, and alerting - I integrate external services: payment providers, email systems, partner APIs, SSO/auth Tech stack: PHP 8.x, Symfony, React, Next.js, PostgreSQL, MySQL, Docker, AWS (ECS, RDS, S3, SQS/SNS, CloudFront), Terraform, Supabase. I also use AI tools daily (Claude Code, Cursor) in my own workflow, so I understand both the strengths and the gaps in AI-generated code. Based in Poland (CET timezone). Available for async work and calls during EU/US business hours.

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Frequently Asked Questions

Can I write files at all in serverless environments?

Most serverless platforms allow writing to the /tmp directory, but the space is limited (512MB on AWS Lambda) and files are deleted between invocations. For persistent storage, use a cloud storage service like S3 or Supabase Storage.

How do I handle file uploads without local storage?

Stream uploads directly to cloud storage using multipart upload APIs. Libraries like multer-s3 for Express or @aws-sdk/lib-storage for direct S3 uploads handle this without writing to disk.

Related Cursor Issues

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