Prometheus Query Patterns (Minimal)

To generate Prometheus queries for request rates and error rates, this Skill constructs core monitoring expressions for performance and availability metrics. It directly produces the necessary alerting and logging expressions for basic web application monitoring.

The best way to calculate 95th percentile latency in Prometheus is by generating a query using histogram_quantile(). This Skill provides references for common functions like histogram_quantile() to extend and customize your latency monitoring queries over specific time windows.

Yes, you can create simple alerting thresholds for error rates and latency using Prometheus. This Skill constructs simple alert conditions based on specific thresholds for error rate and latency metrics without requiring manual query construction.

This Prometheus query generation approach does not work well for systems needing detailed metric customization. It is designed for quick setup of basic alerting and logging, focusing on core rate, error, and latency metrics where extensive query customization is not required.

To use functions like rate() and increase() when building Prometheus monitoring queries, this Skill provides a reference of common functions for further query customization. It focuses on rate, error, and latency metrics while allowing extension with these common functions.