Monitoring Query Analysis & Troubleshooting
Master Prometheus queries and troubleshoot alerts with AI-powered monitoring guidance
What You Can Do
Write complex PromQL queries, debug misfiring alert rules, and diagnose performance anomalies in seconds. Claude analyzes your metrics and monitoring configuration to identify root causes, optimize queries, and recommend alerting strategies that actually catch real problems.
Features
Example Output
PromQL Query Result:
histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m]))
This calculates the 95th percentile response time across your API endpoints.
Alert Debugging:
Your HighMemoryUsage alert fires because the threshold (80%) is too sensitive. Recommendation: Raise to 85% or add a for: 10m clause to reduce false positives.
Anomaly Analysis:
Your latency spike was caused by GC pauses (visible in go_gc_duration_seconds). Root cause: Increased heap allocation without corresponding memory cleanup.
What's Included
- SKILL.md: Complete monitoring troubleshooting workflow and prompt patterns
- PromQL Query Templates: Pre-built queries for common scenarios (latency, errors, throughput)
- Alert Rule Checklist: Validation criteria for reliable, low-noise alert rules
- Troubleshooting Decision Tree: Step-by-step guide to diagnose metric anomalies
- Metric Optimization Worksheet: Identify redundant or low-value metrics
Who It's For
- DevOps and Site Reliability Engineers (SREs) debugging production alerts
- Platform engineers optimizing monitoring infrastructure and dashboards
- On-call engineers diagnosing incidents under time pressure
- Systems administrators tuning performance and reliability thresholds
Best For
- Writing and validating PromQL queries without trial-and-error
- Debugging alert rules that fire incorrectly or miss real issues
- Root cause analysis when metrics spike unexpectedly
- Optimizing metric collection to reduce storage costs
- Learning Prometheus best practices for your specific architecture
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