monitoring-alerting-commerce

To monitor payment success rate, this Skill provides specific PromQL queries and metric definitions that calculate the ratio of successful transactions to total attempts. It includes example metric names and histogram boundaries for OpenTelemetry instrumentation to track gateway performance.

The best way to alert on checkout funnel drops is by applying symptom-based Prometheus alert rules with non-zero for durations. This Skill provides platform-specific guidance for Shopify, WooCommerce, BigCommerce, and custom storefronts to detect revenue-impacting failures.

This payment monitoring approach works with OpenTelemetry on headless storefronts by providing initialization patterns and custom metric instrumentation for checkout observability. It supports custom storefronts alongside hosted platforms to track P99 order creation latency.

Setting up SLO burn-rate alerts involves configuring Prometheus alert rules with runbook annotations and applying recommendations for routing alerts to prod versus staging environments. This Skill outlines SLO burn-rate considerations to reduce alert fatigue while monitoring decline codes.

Tracking decline codes and payment failures in Grafana uses provided dashboard queries that break down payment success and failure metrics by gateway and decline code. This allows teams to visualize commerce health and identify specific revenue-impacting failures before they hit sales reports.