Operations | Monitoring | ITSM | DevOps | Cloud

Every morning, before anyone on the team has looked at a dashboard, a Claude Routine has already read around 800 of the previous night’s conversations from Seer, Sentry’s AI agent for triaging and fixing errors. It flags the ones that look broken, and files tickets for anything new. By the time we sit down with coffee, the triage is mostly done.

By the time an IoT device shows up in an incident review, it has usually already done its damage. Not the dashboard-gap kind. These devices are load bearing. They sit in the control path of substations, haul trucks, pump stations and cold rooms, so when they go blind the blast radius gets measured in tripped relays, spoiled stock, and unplanned outages rather than in missing datapoints.

Tracing is one of the richest observability signals, but it's also noisy and susceptible to data bloat. In a busy system, the vast majority of traces describe the same healthy, fast, successful request over and over, so most organizations downsample their traces to cut costs. But that approach has consequences, since the sampling strategy you choose determines whether you get a faithful picture of your whole system, or just a smaller, blurrier copy of your busiest endpoints.