Why is Railway deploying my old code despite a successful push?

Railway uses aggressive Docker caching to speed up builds. If the Dockerfile or layers haven't changed enough, it may reuse old cached layers that contain outdated application code.

How do I force a rebuild in Railway using this skill?

The skill provides a 'force-rebuild.sh' script and a manual method to update a timestamp comment in your Dockerfile, which changes the file hash and triggers a fresh layer build.

What should I look for in Railway build logs to identify cache issues?

Look for 'Using cache' or 'CACHED' indicators in the build logs. If more than 70% of the steps are cached and the code is wrong, you need to use a force rebuild method.

How can I verify if my Railway deployment is actually updated?

The skill automates checking your local version string against your live /health endpoint using curl and jq to ensure they match.

Railway Cache Troubleshooting

Name: Railway Cache Troubleshooting
Author: adaptationio

byadaptationio

0•

Deployment & DevOps

Resolves aggressive Railway Docker caching issues to ensure the latest code version is successfully deployed to production.

This skill provides a comprehensive toolkit for developers using Railway who encounter 'zombie deployments' where old code persists despite successful git pushes. It streamlines the detection of version mismatches between local and live environments, automates cache-busting via Dockerfile timestamping, and provides diagnostic patterns for analyzing Railway build logs. Whether through one-liner scripts or automated health checks, this skill ensures that new features and bug fixes actually reach production by bypassing Railway's persistent build cache and verifying deployment integrity.

Key Features

01Automated Docker cache-busting via timestamp injection

02Version verification between local source and live endpoints

03Deployment validation using automated health check scripts

04Railway build log analysis for cache detection

05Automated one-liner scripts for forced rebuilds and redeployments

060 GitHub stars

Use Cases

01Forcing a clean rebuild when Railway build logs show 'CACHED' for outdated code

02Verifying deployment success by comparing local version numbers with live endpoints

03Debugging missing features in production that appear in local development but not live

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add adaptationio/skrillz railway-troubleshooting

For use in Claude.ai and ChatGPT

Download Skill