RunPod scales idle endpoints to zero workers after 7 days of no requests

TL;DR

Fix crashing workers before raising limits, or it gets scaled down again. If an idle endpoint stops responding, check whether max workers was scaled to zero and raise it again, or send periodic traffic to keep it warm.

Steps

1. If an idle endpoint stops responding, check whether max workers was scaled to zero and raise it again, or send periodic traffic to keep it warm. Fix crashing workers before raising limits, or it gets scaled down again. Load models once at module level outside the handler so every cold start is not paying model load twice.

When to use

You are seeing this: If an idle endpoint stops responding, check whether max workers was scaled to zero and raise it again, or send periodic traffic to keep it warm. Use this skill when you run into "RunPod scales idle endpoints to zero workers after 7 days of no requests".

When not to use

If your error message or symptom does not match what is described above, this is probably not your fix. Search for your exact error text instead of forcing this one to fit.

Versions

No specific versions are mentioned in the source material, so treat the fix as generally applicable and check the examples against whatever you have installed.

Why this happens

The original report does not dig into a root cause. It documents the symptom and the fix that resolved it.

Source: RunPod's official serverless troubleshooting docs document the silent scale-down. Endpoints with no requests for 3 days get max workers reduced to 2, and after 7 days to 0; RunPod emails on the first reduction. Endpoints with consistently unhealthy crashing workers are also scaled down automatically. For slow cold starts, the docs recommend caching models on network volumes, enabling FlashBoot, and loading models at module level rather than inside the handler function.

Verified resolution: If an idle endpoint stops responding, check whether max workers was scaled to zero and raise it again, or send periodic traffic to keep it warm. Fix crashing workers before raising limits, or it gets scaled down again. Load models once at module level outside the handler so every cold start is not paying model load twice.

Source URL: https://github.com/runpod/docs/blob/HEAD/serverless/troubleshooting.mdx