Is the Prometheus middleware compatible with Express?

Yes, it includes a standardized middleware that automatically captures request duration and status codes, including route normalization to avoid high-cardinality issues.

What metrics are included in the monitoring setup?

The skill implements the Four Golden Signals (Latency, Traffic, Errors, Saturation) plus Node.js specific metrics like event loop lag, heap usage, and active connections.

Can this be used with AWS CloudWatch?

Yes, the skill includes a dedicated utility for emitting custom metrics to AWS CloudWatch for applications running in AWS environments.

How does SLO-based alerting work here?

It provides Prometheus AlertManager configurations that track error budget burn rates, ensuring you only get paged when there is a significant threat to your Service Level Objectives.

Node.js Monitoring & Alerting

Name: Node.js Monitoring & Alerting
Author: chavangorakh1999

bychavangorakh1999

0•

分析与监控

Implement comprehensive observability for Node.js applications using Prometheus metrics, Grafana dashboards, and SLO-based alerting strategies.

This skill provides production-grade implementation patterns for instrumenting Node.js applications with the Four Golden Signals—Latency, Traffic, Errors, and Saturation. It includes ready-to-use Prometheus metric definitions, Express.js middleware for automated request tracking, and complex Grafana dashboard queries. Beyond basic monitoring, it offers advanced configurations for Prometheus AlertManager, multi-burn-rate SLO alerting to reduce noise, and AWS CloudWatch integration, making it an essential tool for SREs and DevOps engineers focused on high availability.

主要功能

01SLO-based alerting rules using multi-burn-rate logic to minimize alert fatigue

02Advanced Grafana queries for P99 latency, error rates, and resource saturation

03Cloud-native support for AWS CloudWatch custom metrics and PagerDuty integration

040 GitHub stars

05Pre-configured Prometheus metrics and custom Express middleware for request tracking

06Standardized implementation of the Four Golden Signals for API observability

使用场景

01Reducing on-call noise by transitioning from static thresholds to SLO-based alerting

02Setting up a full-stack observability dashboard for a production Node.js microservice

03Debugging performance issues using event loop lag and heap memory metrics

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add chavangorakh1999/sde-skills monitoring-alerting

For use in Claude.ai and ChatGPT

主要功能

01SLO-based alerting rules using multi-burn-rate logic to minimize alert fatigue

02Advanced Grafana queries for P99 latency, error rates, and resource saturation

03Cloud-native support for AWS CloudWatch custom metrics and PagerDuty integration

040 GitHub stars

05Pre-configured Prometheus metrics and custom Express middleware for request tracking

06Standardized implementation of the Four Golden Signals for API observability

使用场景

01Reducing on-call noise by transitioning from static thresholds to SLO-based alerting

02Setting up a full-stack observability dashboard for a production Node.js microservice

03Debugging performance issues using event loop lag and heap memory metrics