HTTP 500 in Vercel

Unhandled exception in a Vercel function — check the Runtime Logs; often an unawaited Promise or a missing env var in production.

Why Vercel returns 500

Unhandled exception in a Vercel function — check the Runtime Logs; often an unawaited Promise or a missing env var in production.

How to fix it

Add try/catch around top-level handlers, log to Vercel Log Drains, and validate env vars at build time with a schema (e.g. zod).

Where this surfaces in Vercel

Vercel's Edge Network, serverless function logs, or the deployment dashboard.

Vercel — serverless deployment platform for Next.js and edge apps.

What HTTP 500 means generally

The server encountered an unexpected condition that prevented it from fulfilling the request — the generic catch-all for any unhandled server-side failure.

HTTP 500 Internal Server Error is the universal "something broke on our end" response. It is deliberately vague because the server hit a condition the application code didn't know how to handle: an unhandled exception, a database connection that timed out, a misconfigured config file, an out-of-memory crash, a syntax error in a recent deploy. Unlike 4xx errors (which point the finger at the client), 500 is the server admitting fault. It is the single most common server-side error on the web and almost always means "check the application logs immediately."

Other common causes of 500

SEO impact

Critical SEO impact when persistent. Googlebot retries 500 responses (a brief spike of 500s during a deploy is forgiven), but pages that consistently return 500 for hours or days are deindexed. Worse, a sitewide 500 outage during a Googlebot crawl can cause Google to throttle crawl rate for weeks afterward as a protective measure. Users bouncing immediately from a 500 page also send a strong negative engagement signal. Set up uptime monitoring with sub-5-minute detection so a 500 outage doesn't silently last overnight.

How to catch it next time

LemWatch alerts within seconds when a monitored page starts returning 500. We track error frequency over time and surface patterns (always at 3am? during deploys? under load spikes?) so you can fix root causes instead of just restarting the server.