DevOps & Infrastructure

Prometheus Metrics

Set up Prometheus for metrics collection with service discovery, PromQL queries, recording rules, and alerting for production systems.

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Overview

Prometheus is the industry-standard open-source monitoring system for cloud-native applications. It uses a pull-based model to scrape metrics from instrumented services, stores them in a time-series database, and provides PromQL for powerful querying. AI agents can generate Prometheus configurations, write PromQL queries, create recording rules for pre-aggregation, and set up alerting rules for production monitoring.

AI coding agents are effective with Prometheus because its configuration is YAML-based and its query language (PromQL) follows consistent patterns. Your agent can generate scrape configurations with service discovery for Kubernetes, Docker, or static targets, write complex PromQL queries that calculate rates, percentiles, and aggregations, and create recording rules that pre-compute expensive queries for dashboard performance.

For teams instrumenting their own applications, your AI agent can generate client library code to expose custom metrics (counters, gauges, histograms, summaries) in Node.js, Python, Go, or Java. The agent can also create alerting rules based on SLO definitions, configure Alertmanager for routing and silencing, and implement best practices for metric naming and labeling.

Who Is This For?

SRE teams setting up Prometheus for production monitoring
Developers instrumenting applications with custom Prometheus metrics
DevOps engineers writing PromQL queries for dashboards and alerts
Teams implementing SLO-based alerting with Prometheus recording rules

Installation

Setup for Claude Code

Install Prometheus: brew install prometheus (macOS) or use Docker image prom/prometheus
Claude Code generates prometheus.yml and alerting rules

Configuration

# prometheus.yml
global:
  scrape_interval: 15s
  evaluation_interval: 15s

rule_files:
  - "alerts.yml"

scrape_configs:
  - job_name: "node-app"
    static_configs:
      - targets: ["localhost:3000"]
    metrics_path: /metrics

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