The Moment the Cluster Came Alive: Verifying a Distributed S3 Topology RPC

In the course of building a horizontally scalable S3 storage architecture, there arrives a pivotal moment when theory meets reality. Message 689 in this coding session captures exactly such a moment: the assistant confirms that the ClusterTopology RPC is now returning live data, showing both storage nodes as healthy and reachable. What appears at first glance as a simple verification step—two websocat commands and their JSON responses—is in fact the culmination of a significant debugging and implementation effort that transformed a stub placeholder into a functioning distributed cluster monitoring system.

The Context That Led to This Message

To understand why this message was written, one must trace back through the preceding conversation. The user had noticed that the web UI on port 9010 was only showing a single Kuri node's perspective. The cluster monitoring page was displaying the discouraging message: "No cluster nodes configured. Set up FGW_BACKEND_NODES to see cluster topology." This was not merely a cosmetic issue—it indicated that the cluster awareness feature, a cornerstone of the distributed architecture, was entirely non-functional.

The root cause was discovered in rbstor/diag.go, where the ClusterTopology() method was a stub containing a TODO comment: "Implement actual cluster monitoring when running in distributed mode." The method returned empty slices for both proxies and storage nodes. The Kuri nodes had no mechanism to discover each other, no way to report their health, and no means of presenting a unified cluster view to the operator.

The assistant's response was multi-pronged. First, the ClusterTopology implementation was rewritten to parse the FGW_BACKEND_NODES environment variable, which contains a comma-separated list of peer node addresses. For each address, the code performs an HTTP health check against the /healthz endpoint, populating the Status field based on whether the node responds. The FGW_BACKEND_NODES variable was added to both Kuri nodes' configurations in docker-compose.yml and gen-config.sh, pointing each node at its counterpart. The nginx configuration was also updated to expose kuri-2's web UI on port 9011, giving the operator independent views into each node.

What the Message Actually Shows

The message itself consists of two identical verification tests, differing only in the target port:

echo '{"jsonrpc":"2.0","method":"RIBS.ClusterTopology","params":[],"id":1}' | websocat ws://localhost:9010/rpc/v0

And the same request sent to ws://localhost:9011/rpc/v0. Both return JSON-RPC responses containing a result object with two arrays: Proxies and StorageNodes.

The response from port 9010 (kuri-1's web UI) shows:

The Significance of "Healthy"

The most important word in the entire JSON response is "healthy" appearing four times—once for each proxy entry and once for each storage node entry. This status is not assumed; it is actively determined by the health check logic implemented in the ClusterTopology method. For each backend node address parsed from FGW_BACKEND_NODES, the code makes an HTTP GET request to {address}/healthz with a timeout. If the node responds with "OK" (as verified earlier in message 683 where docker exec test-cluster-kuri-1-1 wget -q -O- http://kuri-2:8078/healthz returned "OK"), the status is set to "healthy". If the request fails or times out, the status would be "unhealthy".

This means the message is not merely reporting configuration—it is reporting the result of a live, cross-container network verification. Kuri-1 successfully reached kuri-2's health endpoint, and vice versa. The Docker internal DNS resolution is working, the S3 proxy containers are listening, and the HTTP health check handler is responding correctly. This is a non-trivial achievement in a distributed system where any number of things could go wrong: network isolation, container startup ordering, port binding failures, or application crashes.

What the Message Does Not Say

The zeros in the response are equally informative. StorageUsed: 0, StorageTotal: 0, ObjectsStored: 0, GroupsCount: 0, DealsCount: 0—these indicate that while the cluster topology and health infrastructure is operational, the system has no data yet. No groups have been created, no objects stored, no deals negotiated. The cluster is alive but empty, ready for the next phase of testing.

The BackendPool: null field for both proxies is another signal. In the ProxyInfo struct, BackendPool is defined as []string—a list of backend node addresses that this proxy routes to. The null value suggests that the proxy's backend pool configuration is either not populated or not yet wired into the ClusterTopology response. This is consistent with the architecture where the S3 frontend proxy (running separately on port 8078) is the actual routing layer, while the Kuri nodes' web UIs are monitoring interfaces.

The Technical Choices on Display

Several design decisions are visible in this brief exchange. The use of WebSocket as the transport for JSON-RPC (rather than plain HTTP POST) reflects a choice made earlier in the project—the RPC endpoint at /rpc/v0 is a WebSocket handler. This is why the assistant had to use websocat rather than curl for testing, and why earlier attempts with curl -X POST returned "Bad Request" or HTML pages.

The JSON field naming is also worth noting. The response uses Go-style PascalCase field names (Proxies, StorageNodes, RequestsPerSecond, ActiveConnections). This is the default serialization of the Go structs defined in iface/iface_ribs.go. The React frontend, however, expects camelCase field names (as noted in the analyzer summary for chunk 0, where JSON tags were added to ensure camelCase serialization). The discrepancy between the raw RPC response shown here and what the frontend expects suggests that either the JSON tags were added after this test, or the frontend has its own mapping layer.

The Broader Implications

This message represents a transition from infrastructure debugging to functional verification. The earlier parts of the session were consumed with fixing crashes (the HTTP route conflict between HEAD / and GET /healthz), correcting database schemas (the missing node_id column in S3Objects), and configuring network exposure (the nginx reverse proxy setup). Message 689 is the first moment where the distributed nature of the cluster is demonstrably working—two independent nodes, each aware of the other, reporting their health through a unified RPC interface.

For an operator monitoring this system, the ClusterTopology RPC is the single source of truth about cluster state. It answers the fundamental questions: Which nodes are part of the cluster? Are they alive? How much storage are they using? How many requests are they handling? Before this message, those questions could only be answered by inspecting each node individually through its own web UI or by reading container logs. Now, a monitoring dashboard can poll this RPC and present a unified view.

Conclusion

Message 689 is deceptively simple—two shell commands, two JSON responses, a brief confirmation. But beneath this surface lies the resolution of a multi-step debugging process, the implementation of a critical distributed system feature, and the first successful end-to-end verification of cluster awareness. The "healthy" status on both nodes is not just a string in a JSON payload; it is the system's declaration that the architecture works as designed. The cluster is no longer a collection of isolated containers but a coordinated, observable distributed system.