Your IPTV reseller panel says server load is forty percent. Your users say everything is buffering. Who is wrong? Neither. The panel shows average load across all servers. The users are on the one server running at ninety percent. Averages hide outliers.
A British IPTV reseller who knows this looks at per-server metrics, not global averages. Your panel almost certainly shows individual server load if you click through. Most resellers never click through. They see forty percent, assume everything is fine, and dismiss user complaints.
Here is how a IPTV reseller UK solved this exact problem. His panel showed sixty percent average load. Users complained constantly. He dug deeper and found that three of his twelve servers were at ninety-five percent load. The other nine were at forty percent. He redistributed users manually. Complaints stopped immediately.
The IPTV reseller panel that shows only averages is dangerous. Demand per-server views from your panel provider or switch to a panel that provides them. The difference between average load and peak load across servers can be fifty percentage points or more. Managing by averages means managing blind.
What actually works is setting per-server alerts, not global alerts. Alert when any server exceeds eighty percent load, regardless of the average. This catches distribution problems before users complain. The configuration takes five minutes. The prevention value is enormous.
Another observation. User complaints often cluster geographically because servers are regional. Users in Manchester complaining while users in London are fine suggests your Manchester server is overloaded. Ask complaining users for their city. Map complaints to server locations.
The pattern that keeps showing up among resellers who trust their panel numbers too much is surprise. "But my panel said everything was fine!" The panel was not lying. It was just showing the wrong number. The reseller did not know which number to trust.
Honestly, panel numbers are tools, not truth. They measure what they measure. User complaints measure something else. When the two diverge, trust the complaints. Your panel might be misconfigured. Your metrics might be wrong. Your interpretation might be flawed. Trust complaints when they conflict with numbers.