Does this skill help determine if my service is healthy?

While it provides the raw resource data, it is best used in combination with the Railway 'service' skill to correlate deployment status with resource consumption for a full health check.

What specific metrics can I track with the Railway Metrics skill?

You can track CPU usage and limits, memory usage and limits (GB), network RX/TX, disk usage, ephemeral disk usage, and backup usage.

Can I view metrics for all services in a Railway environment at once?

Yes, by omitting the specific serviceId and using the 'groupBy' parameter with SERVICE_ID, you can retrieve aggregate or individual metrics for all services in an environment.

How do I specify the time range for the performance data?

The skill requires a startDate in ISO 8601 format (e.g., 2024-01-01T00:00:00Z). You can also provide an optional endDate and sampleRateSeconds to refine the query.

What format are the metric values returned in?

CPU metrics are returned in cores, while memory, network, and disk metrics are provided in Gigabytes (GB).

Railway Metrics

Name: Railway Metrics
Author: railwayapp

byrailwayapp

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Analytics & Monitoring

Monitor and analyze real-time resource usage for Railway services including CPU, memory, network, and disk performance.

About

The Railway Metrics skill enables Claude to query high-resolution performance data for cloud deployments, providing deep visibility into infrastructure health. It allows developers to retrieve and interpret critical time-series data such as CPU cores utilized, memory consumption in GB, network throughput, and disk usage across specific services or entire environments. This skill is essential for diagnosing performance bottlenecks, identifying memory leaks, and making informed decisions about scaling infrastructure directly from the Claude Code interface.

Key Features

Monitor network transmission and reception rates across services
Identify resource limit saturation for proactive scaling
Query real-time CPU usage, memory consumption, and disk utilization
Group performance data by deployment ID, instance, region, or service
Retrieve historical metrics with custom time windows and sample rates
35 GitHub stars

Use Cases

Monitoring resource consumption trends after a new deployment to identify regressions
Debugging service latency or slowness by checking for CPU throttling or memory pressure
Auditing network traffic and disk usage for billing or capacity planning

About

Key Features

Monitor network transmission and reception rates across services
Identify resource limit saturation for proactive scaling
Query real-time CPU usage, memory consumption, and disk utilization
Group performance data by deployment ID, instance, region, or service
Retrieve historical metrics with custom time windows and sample rates
35 GitHub stars

Use Cases

Monitoring resource consumption trends after a new deployment to identify regressions
Debugging service latency or slowness by checking for CPU throttling or memory pressure
Auditing network traffic and disk usage for billing or capacity planning