Alerting and Dashboards: Thresholds and What to Watch
~12 min read
Observability is only useful if someone acts on it. Good dashboards surface the key metrics at a glance, and good alerts fire on the few conditions that genuinely need a human — without drowning the team in noise.
Alerting and Dashboards: Thresholds and What to Watch is a Pro topic
Sign in, then upgrade to Pro or Power to unlock this topic and the full AI Engineering curriculum.
Key points
- •Observability only pays off if someone acts on it — the last mile is scannable dashboards plus actionable alerts
- •Layer dashboards: a top-level health view (rate, p95 latency, error/refusal rate, TPS, cost), then breakdowns by model/feature/customer, then links to traces
- •Avoid both alert fatigue (too many pages, real incident missed) and blind spots (users report your outages) — alert only on conditions needing human action
- •Prefer sustained breaches and rate-of-change over instantaneous spikes; set thresholds off healthy baselines, and always include cost alerts
- •Attach context (service, model, dashboard + trace links) and severity to every alert so on-call starts debugging immediately, not hunting