## TL;DR
Renew the tracking credential and restart the logging process: the client reads MLFLOW_TRACKING_TOKEN once, so a token that expires mid-run keeps being sent until the process picks up the new one. Issue a fresh token, update the environment or secret the job reads, and for long runs use a credential that outlives the run or a refresh step between stages.

```text
'MLFLOW_TRACKING_TOKEN has expired' error when MLflow run logging failed
```

## Use this when
- The run or call fails with this symptom: MLFLOW_TRACKING_TOKEN has expired when run logging fails.
- You are working on an MLflow client logging to an authenticated remote tracking server and the failure repeats on the same run or configuration.
- You need the failing run, call, or stage isolated before changing code or thresholds.

## Not for this skill when
- A token rejected from the first call because it was issued for a different server, where the fix is minting one for the right audience.
- The error text names a different tool, stage, or root cause. Match the verbatim error first and use that skill.

## Steps
1. Confirm the failure is authentication by making one read call with the same token and noting the exact response. Verify: the server rejects the current token explicitly
2. Issue a fresh token from the tracking server's identity provider and update the place the job reads it from. Verify: the stored credential is replaced, not edited in place
3. Restart the logging process or re-create the client so the new token is actually loaded. Verify: a test log call succeeds with the new credential
4. Record the token's expiry against the job's expected duration and add renewal before the longest stage. Verify: expiry is scheduled to be handled before it can bite again

## Variant phrasings
### mlflow tracking token has expired error
The verbatim phrasing.
### mlflow authentication expired mid run logging
The mid-run phrasing.
### mlflow_tracking_token expired fix refresh
The refresh phrasing.

Compatibility: MLflow 2.x and 3.x tracking with your bearer credential

## Why it happens
Bearer credentials are snapshots: the client loads the value at start and presents it unchanged for the process's life. When its lifetime ends mid-run, every subsequent call fails identically, and editing the environment of a running process changes nothing it sends.

## Edge cases / pitfalls
- Some servers accept the token in a username and password pair instead; a token pasted into the wrong variable reads as expired or invalid.
- Clock skew on the training machine can make a valid token look expired; check the machine time if a fresh token also fails.

## Provenance

Resolved from the public thread: https://vectle.com/posts/pst_7v_PPDWCtXDY0JnHbNEwFw