Keeping Data Alive on Railway: How to Use Persistent Volumes for Durable Local Storage

The Problem: Ephemeral Filesystems

When you deploy a service on Railway, the container’s root filesystem is temporary. Any file written to /app or /tmp disappears when the instance is replaced during a redeploy, a scale‑up, or a provider‑level restart. For stateless services this is fine, but stateful workloads—databases, file uploads, caches—require a durable storage layer.

Why Persistent Volumes Matter

Railway offers Persistent Volumes as a first‑class feature. A volume is a block device that lives beyond the life cycle of any single container. Once attached to a service and mounted at a path like /data, the contents survive:

• Deploys – new code or configuration changes.
• Instance replacements – when Railway spins up a new container.
• Service restarts – triggered by health‑check failures or manual restarts.

Typical use cases include:

• Local database data directories (e.g., ./var/lib/postgresql/data).
• User uploads or media libraries.
• Application caches or temporary files that should persist across restarts.

Getting Started: Create & Attach a Volume

Below is a step‑by‑step example that demonstrates how to add a durable local storage area to a Railway service. The example assumes you have the Railway CLI installed and are logged in.

1. Create a volume for uploads, 10 GB in size:

   # Run in the terminal, in the root of your Railway project
   railway volume create uploads --size 10
   

   Replace 10 with the desired size in GB. The command outputs the volume ID (e.g., vol-123abc).

2. Attach the volume to a service named api and mount it at /data:

   # Attach the volume
   railway volume attach uploads api --mount-path /data
   

   This binds the volume to the api service. Only one service can use a volume at a time; if you need shared access, consider an external object store.

3. Deploy the service so the mount is active:

   # Deploy the updated configuration
   railway deploy
   

   After the deploy completes, the container will have /data mounted to the volume.

Confirming the Mount Inside the Container

You can verify the mount by opening an interactive shell in the running container:

# Get the service instance name
railway services

# SSH into the running instance
railway ssh api

# Inside the shell, list the mount
ls -l /data

You should see the volume’s mount point listed.

Sizing & Performance Considerations

Volume size is a simple integer in GB, but the underlying provider determines the actual performance characteristics. Railway’s plan tier dictates maximum volume size and IOPS. For example:

Plan	Max Volume Size	Typical IOPS
Starter	50 GB	200 IOPS
Pro	200 GB	400 IOPS
Enterprise	1 TB	800 IOPS

When choosing a size, consider both the peak data volume and the expected growth rate. Over‑provisioning wastes credits; under‑provisioning can lead to throttling.

Testing Persistence

To ensure the volume behaves as expected, perform a simple write‑and‑redeploy test:

1. Write a test file inside the container:

   # SSH into the service
   railway ssh api
   
   # Create a file in the mounted path
   echo "Hello, Railway!" > /data/hello.txt
   
   # Verify it exists
   cat /data/hello.txt
   

2. Trigger a redeploy (e.g., commit a trivial change or run railway deploy):

   # Make a non‑functional change
   sed -i 's/placeholder/placeholder/' README.md
   railway deploy
   

3. After the deploy completes, **SSH back in** and confirm the file is still there:

   # SSH again
   railway ssh api
   
   # Check the file
   cat /data/hello.txt
   

   If the file is present, the volume survived the redeploy.

Limitations & Trade‑offs

• Single‑service attachment: A volume can only be attached to one service at a time. If you need multi‑replica access, you must use an external storage solution or implement application‑level sharding.
• No automatic replication: Volumes are not replicated across availability zones or regions. If your service fails in the region where the volume lives, the data is lost unless you have backup procedures.
• No built‑in backups: Railway does not snapshot volumes automatically. You must export or snapshot the data yourself (e.g., using railway volume export or a custom script).
• Region‑bound: Moving a service to a different Railway region requires manual migration of the volume’s data.

Actionable Takeaways

• Use railway volume create to provision durable storage for stateful workloads.
• Attach the volume to one service and mount it at a clear, predictable path.
• Always test persistence by writing a file, redeploying, and verifying the file remains.
• Plan for backups and regional failover if your application requires high availability.
• Document the volume size and mount path in your project README so new team members understand the storage layout.

Persistent volumes give you the simplicity of local storage without the hassle of configuring external object stores. With careful sizing, testing, and awareness of the limitations, you can confidently run stateful services on Railway.