How do we pick SLOs if we don’t have great historical data?

Start with your most critical user journeys (checkout, login, API POST /orders). Choose a conservative 99% target and instrument SLIs you can query today (error rate, latency p95/p99). Iterate monthly. The biggest win is moving to burn-rate style alerts, not picking the perfect number on day one.

Won’t automation cause more incidents if it acts on bad alerts?

Scope automation to high-confidence remediations with clear rollbacks (scale a deployment, pause a rollout, toggle a feature flag). Gate actions behind multi-window conditions and short ‘for’ durations, and always notify the on-call with exactly what changed.

We’re on Datadog/New Relic, not Prometheus—does this still apply?

Yes. The principles are vendor-agnostic: compute burn rates, enrich with ownership, group and inhibit alerts, and wire notifications to triage and rollout APIs. Datadog monitors and event pipelines support the same patterns; so do New Relic workflows and Honeycomb triggers.

How do we handle noisy flapping alerts during incidents?

Use Alertmanager grouping and inhibition to collapse downstream symptoms. Increase group_wait to 30–60s to coalesce bursts. Add rate-of-change or consecutive evaluation windows so a single blip doesn’t page. After the incident, run a noise retro and fix or delete the loudest rules.

Reliability-observability · Oct 6, 2025 · 9 minute read

Stop Paging the Whole Org: Intelligent Alert Routing That Predicts Incidents and Drives Rollbacks

Cut 50–70% of pages by routing on leading indicators, not vanity metrics—and wire those alerts to triage bots and safe rollbacks.

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Stop Paging the Whole Org: Intelligent Alert Routing That Predicts Incidents and Drives Rollbacks

Key takeaways

Implementation checklist