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Alert Rules Specification

Define monitoring thresholds, trigger conditions, and escalation rules to catch data anomalies without false positives.

Updated June 2026
The prompt
Metric: {{metric_name}}. Baseline: {{baseline}}. SLA: {{sla_target}}. False positive tolerance: {{fp_tolerance}}%. Current false positive rate: {{current_fp_rate}}%.

Design alert rules:
1. Rule 1 (Static): {{metric_name}} drops below {{static_threshold}} for {{static_window}}
2. Rule 2 (Dynamic): {{metric_name}} deviates > {{std_threshold}} std devs for {{dynamic_window}}
3. Rule 3 (Rate of change): {{metric_name}} changes >{{pct_change}}% hour-over-hour
4. Rule 4 (Interaction): when {{metric_name}} AND {{related_metric}} both trigger
5. False positive suppression: skip alerts during {{exception_windows}}
6. Escalation: Slack if {{low_severity}}, PagerDuty if {{high_severity}}, daily digest if {{medium_severity}}
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Variables

Metric to monitor
Current baseline value
SLA target
Acceptable false positive %
Current false positive rate %
Absolute threshold value
Duration (e.g., 10 minutes)
Std dev multiplier (e.g., 2.5)
Window for dynamic check
% change threshold
Correlated metric for compound rule
Times to suppress alerts (maintenance, deploy, etc.)
Low severity condition
High severity condition
Medium severity condition

Details

Author

AI Khazna

License

Security

Type

prompt

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