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
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
- 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
- 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
- Stream instead of buffering — Instead of writing a file to disk and then uploading it, stream data directly from the source to the destination
- Check for platform-specific storage APIs — Vercel has vercel/blob, Netlify has Netlify Blobs. Use platform-native storage when available
- Add fallback error handling — Wrap file operations in try/catch and provide meaningful error messages when the file system is unavailable
- Use environment detection — Check
process.env.NODE_ENVor platform-specific env vars to choose between local and cloud storage
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Get HelpFrequently 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.