1Describe the service, symptoms, metrics, and severity model you want.
2Generate YAML and review expr, for duration, labels, annotations, and runbook text.
3Test the rule in Prometheus or promtool before committing it.
4Tune thresholds against historical data so alerts reflect user impact instead of normal traffic variation.

Cas d’usage

Prometheus alert bootstrapAPI SLO alertingKubernetes alert rulesRunbook documentationObservability pack generation

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FAQ

What makes an alert rule useful?

A useful alert describes user impact, waits long enough to avoid noise, includes ownership labels, and tells responders where to look next.

Should I alert on every metric spike?

No. Prefer symptoms that affect users, such as sustained error rate, latency, or unavailability. Use dashboards for exploratory signals.

How should generated rules be verified?

Run promtool checks, test the expression in Prometheus, compare with historical data, and review annotations with the team that will respond.

Prometheus Alert Rule Generator drafts YAML rules for API latency, error rate, instance availability, Kubernetes workloads, databases, queues, and infrastructure saturation.

Good alert rules need more than a PromQL expression: they should include duration, severity, labels, annotations, and a clear runbook hint.

Use the generated YAML as a starting point, then test it against real metrics and tune thresholds to avoid noisy alerts.

Demo: API error-rate alert with context

A useful API alert combines an expression with enough context for the responder. The annotation should say what is happening and where to start, not just repeat the metric name.

Use a ratio when possible so traffic volume changes do not distort the alert.
Add a for duration to avoid paging on short deploy blips.
Include service, severity, and runbook labels consistently.

groups:
  - name: api.rules
    rules:
      - alert: ApiHighErrorRate
        expr: sum(rate(http_requests_total{status=~"5.."}[5m])) / sum(rate(http_requests_total[5m])) > 0.05
        for: 10m
        labels:
          severity: page
          service: checkout
        annotations:
          summary: "Checkout API 5xx error ratio is above 5%"
          runbook: "Check recent deploys, dependency errors, and upstream payment latency."

The generator should produce YAML that is readable enough to review before promtool validation.

Alert tuning: make generated rules actionable

Generated alert rules should be treated as a starting point. Before enabling them, tune thresholds, for durations, labels, and annotations so the alert tells an on-call engineer what is broken and where to look.

Use for: to avoid paging on short spikes.
Keep labels stable enough for routing and deduplication.
Write annotations with dashboard links, runbook links, and the exact PromQL expression meaning.

- alert: ApiHighErrorRate
  expr: sum(rate(http_requests_total{status=~"5.."}[5m])) / sum(rate(http_requests_total[5m])) > 0.05
  for: 10m
  labels:
    severity: page

Checklist de revue pour Prometheus Alert Rule Generator

Utilisez Prometheus Alert Rule Generator pour inspecter visuellement une source avant documentation, note de PR, post-mortem ou transfert. Generate Prometheus alert rules YAML for APIs, infrastructure, Kubernetes, databases, and queues.

Avant export, vérifiez la lisibilité, les relations, les données sensibles et la cohérence après modification.

Limites et dépannage

Si l'aperçu échoue, réduisez l'entrée au plus petit exemple complet, validez la syntaxe puis réajoutez les sections.

Considérez l'aperçu comme une surface de revue, pas comme une source de vérité. Les résultats critiques doivent être validés.

Exemples à tester

API alerts: Generate Prometheus alert rules for API error rate, p95 latency, traffic drop, and instance down.
Infrastructure: Generate Prometheus alert rules for CPU, memory, disk, filesystem, and node exporter instance health.
Kubernetes: Generate Prometheus alert rules for Kubernetes pod crash loop, deployment replicas unavailable, node pressure, and API server errors.

Maturité de l'outil

AI beta

Beta assistée par AI

Cet outil génère une source modifiable avec AI. Relisez, prévisualisez localement et ajustez avant publication.

Le libellé indique si l'outil convient surtout à l'export stable, au débogage, à l'analyse rapide ou à la génération AI.