I Stress-Tested My OpenClaw Config for 48 Hours
Most people test OpenClaw for five minutes. They send a few messages. If it works, they call it production-ready.
I did something different. I left my agent running for a full weekend.
I found three silent failures. They did not crash the system. They just cost me money and time.
Here is what broke and how I fixed it.
- Context Decay After 18 hours, the model responses became thin and short. It did not error out. It simply ran out of context space. The session history grew too large. The model started being economical with its words to save space.
The fix: Set a session purge policy.
- Limit history to 50 messages.
- Reset the session every 12 hours. This keeps the context fresh without manual work.
- Task Backlogs I used a cron job to run tasks every 15 minutes. Sometimes a task took longer than 15 minutes due to slow APIs. The next task would start while the first one was still running. This created a growing queue of jobs.
The fix: Add a mutex guard with a lockfile.
- Check if a lockfile exists.
- If the lockfile is less than 15 minutes old, skip the new run.
- This prevents tasks from piling up.
- Invisible Costs When my primary model hit a rate limit, OpenClaw switched to a fallback model. The task finished successfully. However, the fallback model cost 4x more per token. The logs said everything was fine, but my budget was draining fast.
The fix: Add explicit cost tracking.
- Log token usage and cost after every run.
- Review costs per model weekly.
OpenClaw is reliable until it is not. The failures usually happen when you are not watching.
I spent 2 hours fixing these issues. The 48-hour test cost me 20 dollars in tokens. That is a fair trade to ensure my system runs for days without supervision.
If you do not stress-test your config for at least a full day, you are not ready for production.
Optional learning community: https://t.me/GyaanSetuAi