Can I see logs for past deployments?

Yes, you can access historical logs by providing a specific deployment ID, for example: 'railway logs --deployment '.

Does this skill support structured logging?

Yes, it provides patterns and best practices for outputting single-line JSON logs which are fully searchable in both the Railway dashboard and CLI.

How do I filter logs for specific HTTP error codes?

You can use the Railway filter syntax '@httpStatus:5xx' to catch server errors or combine filters like '@httpStatus:500 AND @path:"/api"' for targeted debugging.

How do I view logs for a specific Railway service?

You can use 'railway logs --service ' or link the specific service using 'railway link -s ' before running log commands.

Can I export Railway logs to external platforms like Datadog?

Yes, the skill covers multiple export methods including the Locomotive sidecar, OpenTelemetry (OTEL) integration, and custom streaming scripts.

Railway Log Management

Name: Railway Log Management
Author: adaptationio

byadaptationio

Analytics & Monitoring

Accesses and analyzes Railway build, deployment, and runtime logs for debugging and monitoring applications.

About

This skill provides a comprehensive toolkit for managing observability within Railway deployments. It enables developers to stream real-time logs, filter through build and deployment failures, and analyze HTTP request patterns directly within their workflow. Beyond basic viewing, the skill guides users through advanced log filtering syntax, structured JSON logging best practices, and integration with external observability stacks like Datadog, Axiom, and BetterStack, ensuring that application health and performance are always visible and actionable.

Key Features

Stream real-time build, deployment, and runtime logs via CLI
Analysis of HTTP request metadata, status codes, and latency
External log export configuration for third-party monitoring tools
Structured JSON logging implementation for improved searchability
0 GitHub stars
Advanced log filtering using Railway's specific query syntax

Use Cases

Analyzing API performance and identifying slow HTTP endpoints
Debugging failed deployments or compilation errors during the build phase
Investigating production runtime errors and application crashes

About

Key Features

Stream real-time build, deployment, and runtime logs via CLI
Analysis of HTTP request metadata, status codes, and latency
External log export configuration for third-party monitoring tools
Structured JSON logging implementation for improved searchability
0 GitHub stars
Advanced log filtering using Railway's specific query syntax

Use Cases

Analyzing API performance and identifying slow HTTP endpoints
Debugging failed deployments or compilation errors during the build phase
Investigating production runtime errors and application crashes