50,000 Cells. One Network. How Do You Know Which One Is Quietly Breaking?

The outages that hurt the most are not the dramatic ones. A cell that drops from 99% to 40% RRC success rate gets noticed within minutes — alarms fire, dashboards turn red, someone calls someone. Those are survivable. The ones that cause real damage are the cells that drift from 98.4% to 97.1% to 96.3% over four days. Each step looks like noise. The trend is not. By the time a cluster of customer complaints arrives, the problem has been running for a week. This post is about catching that kind of degradation before it becomes visible to anyone outside the operations center. Note: In part one, I ended with this: "The next post builds cell-specific anomaly detection on top of this foundation — how to learn what 'normal' looks like for 50,000 different cells." This is that post. Why Thresholds Always Fail Every network operations team has tried thresholds. If RRC success rate drops below 95%, fire an alert. Simple. Understandable. Wrong for most cells most of the time. A downtown office c