I blamed the rate limit first because blaming the platform is the comfortable move. For 48 hours I probed a free model endpoint from a free server, and only when the 429s stopped did I count my own retries. The storm was coming from inside my code, and that realization changed how I review retry logic forever. How much of your outage is the upstream, and how much is the loop you wrote around it?
This week someone on DEV argued that we benchmark models but rarely benchmark the harness around them, and my 48 hours agree with that thesis completely. Disclosure: This article was prepared as part of MonkeyCode's product outreach. My probe ran against MonkeyCode's free model access, and the probe itself was deployed on MonkeyCode's free server option, so the experiment was real even if the relationship deserves that label up front. I am deliberately not quoting quotas, model names, or latency numbers, because I spent most of the run measuring my client, not their platform.
The setup: one probe, one naive loop
The first version of the script was the kind we all ship on a Friday afternoon. Every 60 seconds it sends one tiny completion request, records the status code and elapsed time, and retries up to three times with a fixed one-second pause.
