Troubleshooting Deployment Errors

Deploys fail for a small number of reasons, and the failure stage tells you most of what you need to know. This guide gives you a practical diagnosis path. Remember two comforting facts first: a failed deploy does not take down the currently live version (Render keeps serving the last healthy deploy), and during platform builds, an automatic repair loop fixes most failures before you ever see them.

Step 1: Identify the stage

Open the failed deploy in Idea to Life or in your Render dashboard and look at where the log stops.

• Failed during "Build": the code did not compile or dependencies did not install.
• Build succeeded, then failed or timed out: the app crashed on startup or never passed the health check at `/api/health`.
• Deploy succeeded but the site misbehaves: a runtime error, usually configuration.

Step 2: Build-stage failures

Look for the first error in the build log — later errors are usually cascade noise.

• "npm ci" failures: lockfile missing or out of sync with package.json. Happens most often after manual edits to the repo.
• TypeScript or "Module not found" errors: a genuine code bug. If it came from a platform build, the repair loop will already be retrying; if it came from a manual commit you pushed, fix the code or revert the commit.
• Out of memory: large builds can exceed small build instances; Render's paid plans have larger build resources.

Step 3: Startup failures

Switch from build logs to runtime logs and read the first stack trace.

• "Missing environment variable" or an immediate throw naming a key: the required variable is absent on the service. Compare the Environment tab against the Environment Variables guide.
• Crash loop (same error repeating): one bug, restarted repeatedly. Only the first occurrence matters.
• Health check timeout with no crash: the server started but is not answering on `/api/health`, or is listening on the wrong port.

Step 4: Runtime misbehavior

The site is up but a feature fails.

• AI features erroring: usually the provider key — revoked, out of credit, or rate-limited. Check your OpenAI or Anthropic dashboard.
• Database errors: on Supabase free tier, check whether the project paused from inactivity; otherwise check credentials and RLS policies.
• Email not sending: check the Resend dashboard logs and domain verification.

What the repair loop does

During AI builds, failures are detected automatically: the platform reads the error, amends the code, and redeploys, up to a retry limit. You see this as build attempts in the progress view. If the limit is reached, the build stops, you are shown the final error in plain language, and the failure is handled fairly on the credits side — see Understanding Credits.