Persistent Memory

Persistent memory (or persistent storage) refers to data storage that survives container restarts, redeployments, crashes, and infrastructure changes. Unlike the ephemeral filesystem inside a container -- which is destroyed every time the container stops -- persistent storage retains its contents indefinitely, ensuring critical application state is never lost.

How It Works

Containers are designed to be disposable. When a container is replaced during a deployment, everything written to its internal filesystem disappears. Persistent storage solves this by decoupling the data layer from the compute layer. The most common implementation is a volume mount, where an external storage device or managed volume is attached to a specific path inside the container. Any files written to that path are stored on the external volume rather than the container's filesystem.

Other approaches include network-attached storage (NAS), where a remote filesystem is mounted over the network, and managed databases, where structured data is stored in a dedicated database service outside the container. Cloud platforms like Railway provide managed persistent volumes that attach to your deployment automatically, abstracting away the underlying storage infrastructure. The key characteristic shared by all these approaches is that the data exists independently of any single container instance.

Why It Matters

For AI assistants, persistent storage is not optional -- it is a hard requirement. An OpenClaw deployment stores several categories of critical data: the openclaw.json configuration file containing provider credentials and gateway settings, authentication tokens that authorize access to the gateway, conversation history that provides context for ongoing interactions, user preferences and trained context that improve assistant behavior over time, and workspace files that the agent creates or modifies during tasks. Without persistent storage, every container restart would reset the assistant to a blank state, forcing reconfiguration and losing all accumulated context. Mounting a volume at a consistent path such as /data and referencing it through environment variables like OPENCLAW_STATE_DIR ensures that your AI assistant maintains continuity across deployments.