When Your AI SRE Runs Out of Telemetry: The Missing-Evidence Problem in Production Debugging
AI SRE systems are getting much better at the first half of incident investigation.
An agent can receive an alert, inspect metrics, search logs, follow distributed traces, check recent deployments, read source code, retrieve runbooks, and compare the current failure with previous incidents. With enough integrations, it can gather in minutes what once required an engineer to move across several tools.
But there is a hard limit to this model.
Sometimes the information required to diagnose an incident is not buried somewhere in your stack. It was never collected in the first place.
A trace may tell you which function failed. A log may tell you which exception was thrown. Deployment history may tell you exactly which commit introduced the behavior. Source code may narrow the investigation to three suspicious lines.
None of those systems can tell you the value of a local variable at the moment of failure if...
Copyright of this story solely belongs to hackernoon.com. To see the full text click HERE
