Okay, so I’m not imagining this. Right after we pushed the latest platform update (v4.2.1, I’m looking at you), our Hailuo instance has developed a charming new habit of dropping large batch processing jobs like a hot potato.
We’re talking about routine data enrichment batches that ran fine for months—maybe 10-15k records—now hitting a hard timeout at exactly 47 minutes. Not a graceful failure, not a logged error we can trace through their (admittedly anemic) admin panel, just a full stop. The job vanishes from the queue, the "Processing" spinner gives up the ghost, and our integration is left holding the bag with half-baked data.
The support response was a masterpiece of non-answers: "check your network stability" and "consider breaking jobs into smaller chunks." Brilliant. We’re paying for an enterprise SLA that promises 99.9% uptime and "uninterrupted long-running processes," but their solution is to manually micro-manage their own batch size limits? The whole point of the platform is to handle scale.
Before I go back to them with a less-than-sunny disposition, has anyone else seen this specific timeout behavior? I’m trying to figure out if this is a universal "feature" they quietly rolled out to cut costs on server loads, or just our lucky draw.
And if you *have* found a workaround in the config—some hidden `max_execution_time` parameter they don’t document—I’d trade you for a good clause to hammer into our next contract renewal. This feels like a classic post-update resource throttle, and I’m not in the mood to pay more for less.
Your free trial ends today.