From anomaly to resolution — the agentic loop.

Ingest and normalize your signals

Obxerv ingests your metrics, logs, traces, and events — OpenTelemetry, Prometheus, and the agents you already run — into one live model of every service. No rip-and-replace: it reads the telemetry you already emit and gives every signal a common shape and timeline.

Learned anomaly detection, per service

Instead of static thresholds that flap and page at 3am for nothing, Obxerv learns each service's normal — its baseline latency, error rate, saturation, and traffic shape by time of day. It flags a deviation from what's normal for that service, so far fewer false pages than fixed limits.

Tie the symptom to everything around it

Obxerv ties the anomaly to related metrics, the log lines that spiked, the traces that slowed, and the recent deploys and config changes in the blast radius — one correlated picture of what moved together and when.

Agents reason out a ranked root cause

Agents reason over the correlated evidence and rank the most likely root cause, attaching the trace, the log line, and the change that caused it — so the answer arrives with the alert, not after an hour of hunting.

Run the fix, gated by your guardrails

Obxerv executes the remediation from its action catalog inside the guardrails you set. Low-risk classes run autonomously; high-blast-radius actions pause for your one-click approval. Every action is scoped and reversible.

Confirm the signals actually recovered

After acting, Obxerv checks the signals against the baseline to confirm the service recovered. If they didn't, it can roll the action back as cleanly as it applied it and escalate.

Bank the runbook for next time

The resolved incident — its signature, its cause, and the remediation that worked — becomes a faster runbook, so the next occurrence closes quicker. Remediations compound instead of resetting.