Persistent Storage and Stateful Application Limitations

Backups and restores - once the realm of simple tarballs or database dumps - become brittle when data lives partly inside volumes, partly on the host, and partly inside temporary layers that disappear on container restart. For a small team, this is operational debt with no upside.

Railway's own production-readiness guidance still tells teams to think about clusters or replica sets for critical data, which is a tacit admission that production data durability is not something you should treat lightly on the base setup.

PostgreSQL needs persistent storage to protect your data when pods restart or move between nodes. Unlike stateless applications, database containers can't be recreated without careful planning. If your Kubernetes storage isn't properly configured, you risk data corruption or loss during routine operations.

Failure to encrypt sensitive data can result in data leaks and compliance violations. Developers must implement encryption mechanisms to protect data at rest and in transit within their AWS environments.

More applications, including databases and other stateful dependencies, are being run inside containers alongside the application itself. This requires robust Persistent Storage and mature disaster recovery/business continuity planning for stateful applications.

Ensuring data integrity, guaranteed backups, configuring data encryption at rest, and replicating storage consistency across multiple hosts cannot be reliably accomplished using only native Docker volume commands. This volume management paradox means Docker is suitable only for simple, ephemeral workloads as a stand-alone solution.