The Final Check: Verifying the ActiveRequests Endpoint in a Distributed S3 Monitoring System

Introduction

In the course of building and debugging a horizontally scalable S3-compatible storage system for the Filecoin Gateway, a critical moment arrives that is easy to overlook: the verification that every component of the monitoring dashboard actually works. Message 844 in this coding session captures exactly such a moment. The assistant, having just deployed an updated frontend with real-time cluster monitoring features, runs a single command to query the RIBS.ActiveRequests RPC endpoint:

{"jsonrpc":"2.0","method":"RIBS.ActiveRequests","params":[],"id":1}

The response arrives cleanly:

{
  "id": 1,
  "jsonrpc": "2.0",
  "result": {
    "total": 0,
    "reads": 0,
    "writes": 0,
    "multipart": 0,
    "byProxy": {},
    "byStorage": {}
  }
}

On its surface, this is a trivial exchange: a developer queries an API and gets back zeros. But within the context of a multi-hour debugging session that involved fixing HTTP route conflicts, correcting JSON case mismatches, segregating per-node database keyspaces, and debugging container startup failures, this message represents something far more significant. It is the final verification step in a methodical testing protocol, the moment when the last piece of the monitoring puzzle clicks into place.

The Broader Mission: Deploying Cluster Monitoring

To understand why this particular message was written, we must first understand what preceded it. The assistant had just completed a major iteration on the test cluster's monitoring infrastructure. The frontend dashboard, built with React, included several new components: a ClusterTopology view that visually distinguishes S3 frontend proxies (blue) from Kuri storage nodes (green), an IOThroughput chart showing bytes per second, a LatencyDistribution chart with a 350ms SLO threshold, and an ActiveRequests panel showing current in-flight operations.

The deployment of these features was not straightforward. The assistant had to rebuild the Docker image containing the Go backend and the React frontend, restart the entire cluster with docker compose up -d --force-recreate, and then debug a cascade of issues: kuri-2 failed to start because of a missing sp_deal_stats_tmp table, the db-init container reported success but the table wasn't created, and the migration versions had to be checked across both per-node keyspaces (filecoingw_kuri1 and filecoingw_kuri2). Only after restarting kuri-2 did the cluster reach a fully operational state.

Once the cluster was healthy, the assistant began a systematic verification of the monitoring endpoints. The order of operations reveals a clear methodology: first verify the S3 proxy is responding (curl http://localhost:8078/healthz returns ok), then confirm the web UI serves HTML, then generate test traffic (10 uploads and 10 downloads of random 10KB files), and finally check each monitoring RPC endpoint in turn. The IOThroughput endpoint was tested first, showing captured read and write bytes. The LatencyDistribution endpoint followed, returning percentile data. The ClusterTopology endpoint returned detailed node information. And then came the ActiveRequests check — the subject of this article.## Why This Message Matters: The ActiveRequests Endpoint as a System Health Indicator

The ActiveRequests endpoint is not the most visually exciting component of the monitoring dashboard — it shows current in-flight read, write, and multipart operations across the cluster. Unlike the IOThroughput chart (which shows accumulated bytes over time) or the LatencyDistribution chart (which shows percentile response times), ActiveRequests is a point-in-time snapshot. It answers the question: "Is anything happening right now?"

In the context of this debugging session, the endpoint returning all zeros was actually the expected outcome. The assistant had generated test traffic several seconds earlier (the upload and download loop of 10 files each), but those operations had completed. The cluster was now idle. The empty byProxy and byStorage maps confirmed that no requests were currently being routed through the S3 frontend proxy or being processed by the Kuri storage nodes. This was not a bug — it was proof that the request tracking infrastructure was correctly wired up and reporting accurately.

Had the endpoint returned an error (like the RIBS.ThroughputHistory method did moments earlier with "method not found"), the assistant would have needed to investigate further. But the clean response, even with zero values, validated that the ActiveRequests struct was properly serialized with JSON tags, that the RPC method was registered in the backend, that the WebSocket transport was functional, and that the cluster monitoring code path was executing without panics or errors.

The Methodical Verification Protocol

The sequence of commands in messages 836 through 844 reveals a deliberate testing methodology. The assistant is not just randomly poking at endpoints — there is a clear progression from basic connectivity to detailed metrics:

1. Health check (msg 836): curl http://localhost:8078/healthz — verifies the S3 proxy is alive at the most basic level.
2. Web UI accessibility (msg 836): curl http://localhost:9010/ | head -20 — confirms the frontend is serving HTML.
3. Test traffic generation (msg 838-839): Upload and download 10 files each — creates real metrics data.
4. IOThroughput (msg 840): First metrics endpoint — confirms I/O tracking works and captured the test traffic.
5. LatencyDistribution (msg 843): Second metrics endpoint — confirms latency percentile tracking works.
6. ActiveRequests (msg 844): Third metrics endpoint — confirms request tracking infrastructure. This ordering is not accidental. The assistant is building confidence layer by layer. Basic connectivity must work before metrics can be trusted. Metrics must show data before the cluster topology can be meaningful. And only after all other endpoints are verified does the assistant check the ActiveRequests endpoint, which is the most ephemeral — it only shows data when requests are actively in flight.## Contrast and Context: The Failed ThroughputHistory Call The ActiveRequests message gains additional significance when viewed alongside the immediately preceding exchange. In message 842, the assistant queried RIBS.ThroughputHistory and received an error response:

{
  "error": {
    "code": -32601,
    "message": "method 'RIBS.ThroughputHistory' not found"
  },
  "id": 1,
  "jsonrpc": "2.0"
}

This -32601 error code is the standard JSON-RPC "Method not found" error. The assistant did not stop to debug this failure — it simply moved on to the next endpoint, LatencyDistribution, which succeeded. This is a telling moment: the assistant implicitly recognized that ThroughputHistory was either a method that existed in the code but was not registered on the RPC router, or it was a method name that had been renamed or removed during development. The fact that the assistant did not investigate suggests either that this method was known to be deprecated, or that the priority was to verify the endpoints that were expected to work.

This selective debugging — acknowledging a failure but not stopping to fix it — reveals the assistant's prioritization. The core monitoring features (IOThroughput, LatencyDistribution, ClusterTopology, ActiveRequests) were the critical path for the dashboard. A missing method for what appears to be a redundant or renamed endpoint was a lower priority. This is a realistic engineering tradeoff: not every bug needs to be fixed immediately, especially when the core functionality is working.

Architectural Knowledge Required

To fully understand this message, one must grasp the three-layer architecture of the system:

Client → S3 Frontend Proxy (stateless, port 8078) → Kuri Storage Nodes → YugabyteDB

The ActiveRequests endpoint lives in the monitoring subsystem. It collects data from the S3 frontend proxy (which tracks incoming requests) and from the Kuri storage nodes (which track internal operations). The byProxy field would show requests distributed across S3 proxy instances, while the byStorage field would show operations being handled by each Kuri node. In a single-proxy test cluster with no active traffic, both maps are empty — which is exactly what the response shows.

The reader also needs to understand the JSON-RPC transport layer. The assistant uses websocat to send JSON-RPC requests over a WebSocket connection to the web UI at port 9010. The web UI's nginx proxy routes /rpc/v0 to the backend's RPC handler. The RIBS.ActiveRequests method name follows the naming convention RIBS.<MethodName> used throughout the system.

Assumptions and Correctness

The assistant made several implicit assumptions when writing this message:

1. The endpoint exists: Having just verified IOThroughput and LatencyDistribution, the assistant assumed ActiveRequests was also implemented and registered. This assumption proved correct.
2. Zero values are valid: The assistant did not interpret the all-zero response as a failure. This was correct — the cluster was idle, so zero active requests was the expected state.
3. The WebSocket connection is reliable: The assistant used websocat with -n1 (connect once, send one message, exit). This assumes the WebSocket endpoint is reachable and responsive, which it was.
4. jq is available: The assistant piped the response through jq '.' for pretty-printing, assuming the JSON parser was installed. This was a reasonable assumption given the development environment. No mistakes are evident in this particular message. The command is correct, the response is valid, and the interpretation is sound. The only potential issue is that the assistant did not verify the byProxy and byStorage fields under load — but that would be a subsequent testing step, not a failure of this verification.

Output Knowledge Created

This message created several forms of knowledge:

• Verification evidence: The ActiveRequests endpoint is implemented, registered, and returning valid JSON-RPC responses.
• System state: The cluster is currently idle with zero active requests across all proxies and storage nodes.
• Serialization correctness: The Go struct for ActiveRequests (with fields like total, reads, writes, multipart, byProxy, byStorage) is correctly serialized to JSON, confirming that JSON tags were properly added in the iface/iface_ribs.go file.
• No errors: The absence of error codes or panic messages confirms the monitoring code path is stable.

Conclusion

Message 844 is a quiet moment of success in a debugging session filled with failures and fixes. It represents the final check in a systematic verification protocol, confirming that the ActiveRequests monitoring endpoint — the last piece of the cluster monitoring dashboard — is fully operational. The all-zero response is not anticlimactic; it is the correct answer for an idle cluster, and receiving it cleanly is a small but meaningful victory. In the broader narrative of building a horizontally scalable S3 architecture, this message marks the point where the monitoring infrastructure transitions from "implemented" to "verified." The dashboard is complete, the endpoints are live, and the cluster is ready for the next phase: load testing at scale.