Prometheus

Prometheus Skill

Powering metrics and alerting.

Ecosystem Graph

graph LR
  prometheus["Prometheus"]
  prometheus -- "works well with" --> grafana
  prometheus -- "monitors" --> kubernetes

Quick Start

Prometheus is a pull-based time-series database. It scrapes /metrics endpoints across your infrastructure at regular intervals and stores them.

docker run -p 9090:9090 prom/prometheus

Production Patterns

Exporters

Do not manually instrument standard infrastructure. Use Exporters (e.g., node_exporter for Linux stats, postgres_exporter for DB stats) which automatically expose standard metrics in the Prometheus format.

Architecture & Scaling

Pull vs Push

Prometheus pulls metrics. In serverless environments (like AWS Lambda) where services are ephemeral and cannot be scraped, you must push metrics to a Prometheus Pushgateway, which Prometheus then scrapes.

Error Recovery

Prometheus is heavily memory-bound. If it OOMs, check your label cardinality. High cardinality (e.g., tracking a user ID as a label on every metric) will exponentially explode the TSDB and crash the server.

Security Notes

Prometheus scrape endpoints (/metrics) often contain sensitive infrastructure data. Ensure these endpoints are strictly inaccessible from the public internet (e.g., via internal Kubernetes network policies).

Relationships

Works Well With: grafana

References

• Prometheus Docs

Why use this skill

Use this when your agent works with prometheus — structured patterns beat pasted docs and prevent common hallucinations.

AI pitfalls

• Using outdated SDK or API versions from training data
• Inventing environment variable names
• Omitting error handling and retry logic

Production checklist

• Secrets in environment variables, not source code
• Error handling and logging in place
• Rate limits and timeouts configured

Related skills

• grafana — works well with
• kubernetes — monitors

Last Verified: 2026-07-02