The Quiet Moment of Deployment: Shipping a One-Line Fix Across a Distributed Cluster

The Message

[assistant] [bash] # Deploy to both kuri nodes
scp /home/theuser/gw/kuri 10.1.232.83:/tmp/kuri && ssh 10.1.232.83 "sudo mv /tmp/kuri /opt/fgw/bin/kuri && sudo systemctl restart kuri"
scp /home/theuser/gw/kuri 10.1.232.84:/tmp/kuri && ssh 10.1.232.84 "sudo mv /tmp/kuri /opt/fgw/bin/kuri && sudo systemctl restart kuri"

On its surface, this message is unremarkable: two shell commands that copy a compiled Go binary to two remote servers and restart a systemd service. It is the kind of mechanical step that experienced operators can execute from muscle memory. Yet in the context of the coding session, this message represents the culmination of a concentrated debugging spiral—the moment when a diagnosis, a code fix, and a build pipeline converge into a single deployment action. Understanding why this message was written, what decisions it encodes, and what assumptions it carries requires unpacking the chain of reasoning that led to it.

The Debugging Spiral That Preceded Deployment

The story begins with a seemingly simple user observation. The cluster monitoring dashboard, which displays a "Storage Nodes" table showing per-node statistics, had stopped working correctly. The user reported: "the /cluster Storage Nodes table doesn't see traffic on the other node, seems to be a regression." This is the kind of vague-but-specific bug report that every distributed systems engineer dreads—something that used to work and now doesn't, with no obvious error message.

The assistant's initial investigation revealed a puzzling asymmetry. When querying the RIBS.ClusterTopology RPC endpoint on kuri_01 (10.1.232.83), the node reported its own storage usage correctly (2.7 GB) but showed zero storage used for kuri_02. Querying kuri_02 produced the mirror image: it saw its own 712 MB but showed zero for kuri_01. Each node could only see itself. The cluster had become a collection of solipsistic singletons.

This is the kind of bug that forces a developer to trace through layers of abstraction. The assistant began reading source code, starting with the RPC handler in integrations/web/rpc.go and then diving into the ClusterTopology() implementation in rbstor/diag.go. The critical line was on line 263:

statsURL := strings.Replace(nodeURL, ":8078", ":9010", 1) + "/api/stats"

This code attempts to fetch statistics from a remote node by taking the node's S3 API URL, replacing the S3 port (8078) with the web UI port (9010), and appending /api/stats. It is a pragmatic but fragile approach—it assumes that the node URL will always contain the string :8078.

The Root Cause: A One-Character Mismatch

The actual backend URLs, as revealed by checking the configuration on kuri_01, used port 8079, not 8078:

FGW_BACKEND_NODES="kuri_01:http://10.1.232.83:8079,kuri_02:http://10.1.232.84:8079"

The strings.Replace call with :8078 as the search string simply did nothing when applied to URLs containing :8079. The replacement failed silently, producing a URL like http://10.1.232.83:8079/api/stats—which hit the S3 API endpoint, not the web UI's /api/stats endpoint. No stats were returned, and the remote node appeared to have zero storage used.

The difference between 8078 and 8079 is a single digit, but in a distributed system, a single digit can mean the difference between a functioning cluster and a broken dashboard. The 8078 port belonged to the S3 frontend proxy layer, while 8079 was the internal S3 port used by the kuri storage nodes themselves. The code had been written against the proxy's port, but the actual deployment used the storage node's port. This is a classic configuration drift bug—the code and the deployment fell out of sync at some point, and nobody noticed until the dashboard broke.

The Fix and the Build Pipeline

The assistant edited rbstor/diag.go to replace :8079 with :9010 instead of :8078. But then came a second debugging spiral: how to build the binary. The assistant first tried go build -o kuri ./cmd/boostd-data, which failed because the build path was wrong. A search for the correct build target led to the Makefile, which revealed the proper command: make kuboribs, which executes go build -o kuri ./integrations/kuri/cmd/kuri. This detour—discovering the project's build system—is a reminder that even simple deployments depend on understanding a project's conventions.

The build succeeded, producing a binary at /home/theuser/gw/kuri. Now the assistant faced the actual deployment.## The Deployment Strategy: Why Two Commands Instead of One

The deployment commands themselves reveal several implicit design decisions. The assistant chose to copy the binary to /tmp/kuri first, then use sudo mv to move it to /opt/fgw/bin/kuri. This two-step approach is deliberate: it avoids writing directly to a privileged location over SCP (which would require root SSH access or special permissions), and it ensures that the binary is fully transferred before replacing the running version. The && chaining guarantees that if the SCP fails, the move and restart never execute.

The restart uses sudo systemctl restart kuri, which sends SIGTERM to the running process and starts the new one. This is a hard restart—not a graceful reload or a blue-green deployment. In a production cluster with two nodes, this means a brief moment where one node is down while the other continues serving. The assistant implicitly trusts that the cluster can tolerate a single-node restart without data loss or service interruption, an assumption that depends on the YugabyteDB-backed persistence layer and the S3 proxy's ability to route around a downed backend.

The assistant also deployed to both nodes sequentially in a single message, rather than waiting for the first restart to complete before starting the second. This parallel deployment minimizes total downtime but increases risk: if the new binary has a startup crash, both nodes could fail simultaneously. The assistant's confidence in the fix—a one-character port change—justified this risk.

Input Knowledge Required to Understand This Message

To fully grasp what this message accomplishes, a reader needs to understand several layers of context:

1. The architecture: The FGW (Filecoin Gateway) system has a three-tier architecture: S3 frontend proxies (port 8078) that route requests to kuri storage nodes (port 8079), which store data in YugabyteDB. The web UI and RPC endpoints run on port 9010.
2. The bug: The ClusterTopology code used a hardcoded port replacement (:8078 → :9010) that didn't match the actual backend URLs (:8079), causing cross-node stats to fail silently.
3. The build system: The Go project uses a Makefile with a kuboribs target that builds the kuri binary from ./integrations/kuri/cmd/kuri. The assistant had to discover this after a failed build attempt.
4. The deployment topology: Two physical nodes (10.1.232.83 and 10.1.232.84) running the kuri service under systemd, with binaries stored at /opt/fgw/bin/kuri and configuration in /data/fgw/config/settings.env.
5. The access model: The assistant uses SSH to a head node (10.1.232.82) and then SCP/SSH to the kuri nodes. The sudo escalation is required for writing to /opt/fgw/bin/ and for restarting systemd services.

Output Knowledge Created by This Message

This message produces several tangible outcomes:

1. Two updated binaries: The old kuri binary on each node is replaced with a new one containing the port fix.
2. Two service restarts: The systemd kuri service is restarted on both nodes, causing a brief service interruption.
3. A fixed cluster topology view: After the restart, the ClusterTopology RPC should correctly fetch remote stats, and the Storage Nodes table in the dashboard should show accurate cross-node data.
4. Verification opportunity: The deployment creates a state where the assistant (or user) can immediately verify the fix by querying the topology endpoint again. The message also implicitly documents the deployment procedure: the sequence of SCP → sudo mv → systemctl restart is a repeatable pattern that could be automated further (e.g., in an Ansible playbook), but is here performed manually for a hotfix.

Assumptions and Potential Mistakes

The assistant made several assumptions in this deployment:

• That the binary is the only changed artifact: The fix was in rbstor/diag.go, which is part of the kuri binary. No configuration files, database schemas, or other components needed updating.
• That the restart is safe: The assistant assumed that restarting the kuri service would not cause data corruption, lost requests, or cascade failures. This is reasonable for a storage node backed by YugabyteDB, but it's an assumption nonetheless.
• That both nodes have identical environments: The same binary is deployed to both nodes without any node-specific customization. This works because the fix is architecture-neutral.
• That the build is correct: The assistant didn't run tests or verify the binary locally before deploying. The one-character nature of the fix made this low-risk, but it's still a leap of faith.
• That the user has the context to understand what happened: The message provides no explanation, no status update, no verification step. It assumes the user is following the conversation closely enough to know that this deployment fixes the topology bug. One subtle mistake in the earlier reasoning was the initial assumption that the port replacement was targeting :8078 (the proxy port) when in fact the backend URLs used :8079. This misalignment between the code's assumption and the deployment reality is the very bug being fixed. The assistant correctly identified this during debugging but the original code author had made the same assumption—that backend URLs would always use port 8078.

The Thinking Process Visible in the Reasoning

The assistant's reasoning, visible in the preceding messages, follows a classic debugging pattern:

1. Observe symptom: "Storage Nodes table doesn't see traffic on the other node"
2. Gather data: Query ClusterTopology RPC from both nodes, revealing asymmetric stats
3. Form hypothesis: "Each node only sees its own stats, not the other node's. This is a regression—the nodes aren't fetching stats from each other."
4. Locate the code: Search for ClusterTopology implementation, find rbstor/diag.go
5. Read the relevant logic: Identify the strings.Replace call that constructs the stats URL
6. Verify against reality: Check the actual FGW_BACKEND_NODES config to confirm the port mismatch
7. Fix: Edit the port number in the Replace call
8. Build: Discover the correct build target via the Makefile
9. Deploy: Copy and restart on both nodes This is textbook debugging, but the assistant's willingness to trace through unfamiliar code (the rbstor package), to verify configuration on live nodes, and to recover from a failed build command shows the iterative, exploratory nature of real-world systems engineering. The deployment message itself is the final step in this chain—the payoff after the diagnosis and the fix.

Conclusion

A deployment command is never just a deployment command. This message, two lines of shell script, carries the weight of a debugging session that traversed user reports, RPC queries, source code analysis, configuration verification, build system navigation, and finally the risky act of restarting production services. The one-character fix—8078 to 8079—is almost invisible in the diff, but the process of finding it required understanding the entire architecture of the distributed S3 system. In distributed systems, the smallest fixes often demand the deepest understanding.