Detecting the Unknown Unknowns

How AI Agents powered by observability uncover issues that rules and static monitoring can’t predict.

The Limits of Rule-Based Monitoring

Traditional monitoring depends on thresholds and predefined rules: CPU above 80%, latency over 100ms, disk at 90% full. These guardrails catch the obvious, but they miss the unexpected. In distributed, hybrid environments, many incidents don’t follow predictable patterns—leaving operators blind until users report the problem.

AI Agents as Anomaly Hunters

AI Agents, fueled by observability, go beyond rules. They continuously learn what “normal” looks like across logs, metrics, and traces, then flag subtle deviations that humans would overlook. Whether it’s a slight drift in response times or an unusual pattern in API calls, agents surface anomalies early, giving operators time to act before they escalate.

Resilience Through Early Discovery

Catching the “unknown unknowns” changes the resilience game. Organizations deploying AI-based anomaly detection report up to 40% fewer major incidents and dramatically faster recovery when issues do occur. Instead of reacting to the obvious, operators gain proactive visibility into the hidden risks shaping system health.

Ready to uncover the issues your rules can’t see?Observeasy equips AI Agents to detect unknown anomalies—helping teams move from reactive monitoring to proactive resilience. 👉 Book a demo and discover anomaly detection in action.