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Tools / Monitoring and Observability Interview Questions

What is alerting fatigue and how can you reduce it?

Alerting fatigue occurs when on-call engineers receive so many alerts — many of which are non-actionable, duplicate, or transient — that they begin ignoring or acknowledging them without investigation. It is one of the most damaging failure modes in an observability program because it means real incidents go undetected while engineers burn out.

The root causes are typically: alerting on symptoms rather than user impact, overly sensitive thresholds, missing deduplication, no alert routing (everything goes to one channel), and alerts that fire at 2 AM for issues that can safely wait until morning.

Practical remedies include:

Alert on SLO burn rate, not individual metrics. Instead of alerting when CPU > 80%, alert when the error budget is burning faster than a sustainable rate. This ties every alert to actual user impact.

Use multi-window, multi-burn-rate alerting (as described in the Google SRE Workbook). A fast burn rate fires immediately; a slower burn rate fires after accumulating over a longer window. This avoids noisy one-minute spikes while still catching slow, steady degradation.

Group and deduplicate using Alertmanager's grouping and inhibition rules. One database outage should produce one alert, not 500 alerts from every service that depends on that database.

Regularly prune alerts by reviewing which fired in the last 30 days. Alerts that consistently go unactioned should be removed or turned into tickets.

What is the core principle of SLO-based alerting that makes it less noisy than threshold-based alerting?
In Alertmanager, what feature prevents 500 derivative alerts from firing when a single upstream database goes down?

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