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Among the AI features in SRE dashboards, alert correlation is the one with demonstrated value: it groups dependent alerts from a single incident, cutting time to acknowledge and fatigue during a crisis. Automatic incident summaries help too. The real problem was never a shortage of information, it was separating signal from noise and correlating scattered symptoms.
Uptime Kuma installs with Docker Compose in about ten minutes: define a service with the official louislam/uptime-kuma image, a persistent volume at /app/data and port 3001, bring the container up with docker compose up -d, then create the admin user on first access from the browser.
To write Prometheus alerts that won't get ignored, alert on customer-observable symptoms (latency, error rate, saturation) instead of internal causes like CPU or memory, define SLOs with multi-window burn rate to scale severity, add a watchdog alert that confirms the system is still alive, and review the signal-to-noise ratio every quarter.
