metrics

Query Railway service CPU, memory, network, and disk metrics via GraphQL.

303|36|Updated Jan 4, 2026
One-click install
npx skills add https://github.com/railwayapp/railway-skills --skill metrics-railwayapp
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: metrics
Source: https://github.com/railwayapp/railway-skills/tree/main/plugins/railway/skills/metrics
Command: npx skills add https://github.com/railwayapp/railway-skills --skill metrics-railwayapp

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill helps teams monitor Railway service resource usage (CPU, memory, network, and disk) and identify performance issues, enabling proactive optimization.

Core Features & Use Cases

  • Track CPU, memory, network, and disk usage across environments and services.
  • Compare metrics across deployments, identify bottlenecks, and debug slow services.
  • Use in operations dashboards and incident response to verify service health and capacity.

Quick Start

Query current CPU, memory, and network metrics for a selected Railway service.

Frequently Asked Questions about metrics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I monitor Railway service metrics like CPU and memory usage?

To monitor Railway service metrics, you can query and analyze CPU, memory, network, and disk usage per service or environment. This enables trend analysis and health checks to identify performance bottlenecks.

What do I need to check Railway resource usage for my deployments?

Checking Railway resource usage requires the environmentId and serviceId from the status --json command. These identifiers allow you to target specific deployments and apply optional grouping for deeper analysis.

Can I compare metrics across different Railway environments?

Yes, you can compare metrics across different Railway environments and services. This capability helps identify bottlenecks, debug slow services, and verify service health during incident response operations.

How does querying Railway metrics with GraphQL work?

Querying Railway metrics with GraphQL involves requesting specific resource data like CPU, memory, network, and disk usage. It applies to per-service or per-environment scenarios, enabling detailed trend analysis and health checks.

What is the best way to debug slow Railway services using performance data?

The best way to debug slow Railway services is by tracking CPU, memory, network, and disk usage across environments. Comparing these metrics across deployments helps identify bottlenecks and verify capacity issues.