prometheus-monitoring

SKILL.md

Prometheus Monitoring

Table of Contents

Overview

When to Use

Quick Start

Reference Guides

Best Practices

Overview

Implement comprehensive Prometheus monitoring infrastructure for collecting, storing, and querying time-series metrics from applications and infrastructure.

When to Use

Setting up metrics collection

Creating custom application metrics

Configuring scraping targets

Implementing service discovery

Building monitoring infrastructure

Quick Start

Minimal working example:

# /etc/prometheus/prometheus.yml
global:
  scrape_interval: 15s
  evaluation_interval: 15s
  external_labels:
    cluster: production

alerting:
  alertmanagers:
    - static_configs:
        - targets: ["localhost:9093"]

rule_files:
  - "/etc/prometheus/alert_rules.yml"

scrape_configs:
  - job_name: "prometheus"
    static_configs:
      - targets: ["localhost:9090"]

  - job_name: "node"
    static_configs:
      - targets: ["localhost:9100"]

  - job_name: "api-service"
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide
Contents

Prometheus Configuration
Prometheus Configuration

Node.js Metrics Implementation
Node.js Metrics Implementation

Python Prometheus Integration
Python Prometheus Integration

Alert Rules
Alert Rules

Docker Compose Setup
Docker Compose Setup

Best Practices

✅ DO

Use consistent metric naming conventions

Add comprehensive labels for filtering

Set appropriate scrape intervals (10-60s)

Implement retention policies

Monitor Prometheus itself

Test alert rules before deployment

Document metric meanings

❌ DON'T

Add unbounded cardinality labels

Scrape too frequently (< 10s)

Ignore metric naming conventions

Create alerts without runbooks

Store raw event data in Prometheus

Use counters for gauge-like values

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