Operations | Monitoring | ITSM | DevOps | Cloud

There's a support ticket every SRE dreads: "is something wrong with my database?" The outage is bad enough. Worse is the possibility that the customer knew first. At Upstash, we treat that scenario as two failures rather than one: the incident itself, and the uptime monitoring gap that let a customer beat us to it. We write a postmortem for the gap, too.

Monitoring load is not always steady. A team might add a new batch of checks or run several ad hoc tests during a rollout. When that happens, your Private Location agents need to pick up more work at once. If there aren’t enough agents available during a burst, checks start piling up in the queue, which can delay or disrupt check execution. But solving this by running a high number of agents around the clock has the opposite problem: most of that capacity sits idle until the next busy period.

You get an infrastructure alert. Something's off, so you task your agent to investigate, and it ends up grepping through the logs. You both wonder if there's customer impact. There’s a simple rule: AI agents in the incident loop are only as good as the signal you feed them. And logs alone aren't a great signal.