Queries and analyzes Prometheus metrics using PromQL to monitor HTTP performance, database latency, and GenAI token usage.
This skill empowers developers to monitor and troubleshoot applications by providing ready-to-use PromQL templates for the Prometheus HTTP API. It handles metric discovery across different OpenTelemetry SDK versions and enables deep insights into request rates, error codes, p95/p99 latency percentiles, and specific GenAI model performance. Whether working with a local stack or Amazon Managed Service for Prometheus (AMP), it streamlines the process of extracting actionable observability data directly within the Claude Code environment, helping teams maintain high system availability and performance.
주요 기능
01Specialized monitoring for GenAI token usage and model operation duration
02Pre-configured templates for HTTP request rates and 5xx error rate ratios
03High-precision latency analysis for p95 and p99 percentiles by service
0421 GitHub stars
05Automated discovery of active metric names across varying OTel SDK versions
06Full support for local Prometheus and AWS Managed Service for Prometheus (AMP)
사용 사례
01Auditing database operation performance to identify slow queries and backend bottlenecks
02Diagnosing sudden spikes in HTTP error rates or latency across distributed microservices
03Monitoring GenAI costs and efficiency by tracking token usage per model and operation