What characterises proactive observability at stage 4?

Problems are detected before users are affected: anomaly detection, trend analysis, SLO and SLA monitoring, and business metrics folded into the same picture.

The building blocks:

• Anomaly detection — the baseline is learned rather than configured, so a deviation is flagged even when no static threshold was crossed.
• Trend analysis — projecting a curve forward: the disk will be full in nine days, the connection pool exhausted at this growth rate by Thursday.
• SLO and SLA monitoring — watching the budget rather than the incident. If a month's allowance of failed requests is being consumed three times faster than normal, that is actionable long before the SLA is breached.
• Integrated business metrics — so a technical anomaly can be weighed by what it costs.

Typical early signals: rising error rates, unusual response times, increased database load. None of these is an outage yet; each is a system announcing that it is about to become one. The result is that problems are recognised early and defused — the first stage at which the team is genuinely ahead of its users.