The Glue That Connects Backend to Frontend: Adding an RPC Endpoint for Cache Metrics

The Message

[assistant] Now let me add the RPC endpoint:
[read] /home/theuser/gw/integrations/web/rpc.go
<file>
00131| }
00132| 
00133| func (rc *RIBSRpc) RepairStats() (map[int]iface2.RepairJob, error) {
00134| 	return rc.ribs.DealDiag().RepairStats()
00135| }
00136| 
00137| func (rc *RIBSRpc) CIDGravityStatus(ctx context.Context) (iface2.CIDGravityStatus, error) {
00138| 	return rc.ribs.DealDiag().CIDGravityStatus(ctx), nil
00139| }
00140| 
00141| func (rc *RIBSRpc) ParallelWriteStats(ctx context.Context) (iface2.ParallelWriteStats, error) {
00142| 	return rc.ribs.StorageDiag().ParallelWriteStats()
00143| }

Context and Motivation

This message, index 2767 in the conversation, represents a pivotal integration moment in the development of the Filecoin Gateway (FGW) project. To understand why this message matters, we must trace the chain of events that led to it.

The user had issued a straightforward request at message 2746: "UI in dashboard show L1/L2 cache metrics." On its surface, this seems like a simple feature request—add some numbers to a dashboard. But beneath that simplicity lies a complex architectural journey. The Filecoin Gateway is a distributed storage system with a multi-layered caching architecture: an L1 ARC (Adaptive Replacement Cache) in memory and an L2 SSD-backed cache for persistent storage. These caches are critical to system performance, reducing retrieval latency and network load. Exposing their metrics in the WebUI would give operators real-time visibility into cache efficiency, hit rates, and capacity utilization—essential data for tuning and capacity planning.

The assistant's response to this request was methodical. First came reconnaissance: searching the codebase for existing cache metrics, stats structures, and RPC patterns (message 2747). Then came planning: a todo list was created with four items: add a CacheStats struct to the iface package, add a CacheStats method to the RIBSDiag interface, implement CacheStats in the retrieval provider, and add a CacheStats RPC endpoint (message 2748). Each of these steps built on the previous one, forming a clean layered architecture.

By message 2767, the assistant had completed the first three tasks. The CacheStats struct had been added to the shared interface package, defining the shape of the data that would flow from backend to frontend. The RIBSDiag interface had been extended with a new method signature, establishing the contract that any diagnostic implementation must fulfill. The retrievalProvider—the component that actually manages the L1 and L2 caches—had been given a concrete CacheStats() method that collects real-time statistics from the ARC cache and SSD cache structures.

Now came the final integration step: exposing this data through the RPC layer so the WebUI could fetch it.## The Architecture of the RPC Layer

To appreciate what this message accomplishes, one must understand the layered architecture of the FGW system. The project follows a clean separation of concerns:

  1. The iface package defines shared data types and interface contracts. It is the lingua franca of the system—any component that needs to communicate with another does so through types defined here. The RIBSDiag interface, which now includes the CacheStats() method, is the diagnostic contract that any component providing operational insights must implement.
  2. The rbdeal package contains the business logic for deal-making and retrieval. Within it, the retrievalProvider manages the actual L1 (memory) and L2 (SSD) caches. This is where cache hits and misses happen, where data is promoted from L1 to L2, and where the raw statistics live.
  3. The integrations/web package contains the HTTP/RPC layer that serves the WebUI. The RIBSRpc struct is the RPC handler—it receives JSON-RPC calls from the frontend and delegates them to the appropriate backend component.
  4. The React frontend in ribswebapp consumes these RPC endpoints and renders them as dashboard tiles. The message at index 2767 is the bridge between layers 2/3 and 4. Without this RPC endpoint, the cache statistics collected by the retrievalProvider would remain trapped in the backend, visible only through logs or Prometheus metrics. The RPC endpoint is the final gateway that makes this data accessible to the human operator through the WebUI.

The Thinking Process Visible in the Message

The message itself is deceptively simple—just a read command to inspect the existing RPC file, followed by the file content. But the thinking process behind it is rich and worth examining.

First, the assistant says "Now let me add the RPC endpoint." This "now" is significant. It signals that the assistant recognizes a natural progression: the interface has been defined, the implementation has been written, and now the final wiring must be completed. The assistant is working through a mental checklist, and this is the last item.

Second, the assistant chooses to read the file rather than edit it immediately. This is a deliberate decision to gather context before making changes. By reading the file, the assistant can see the exact patterns used by existing RPC methods—how they delegate to rc.ribs.DealDiag() or rc.ribs.StorageDiag(), what parameters they accept, what return types they use. This pattern-matching approach ensures consistency. The new CacheStats endpoint will follow the same conventions as RepairStats, CIDGravityStatus, and ParallelWriteStats.

Third, the assistant reads the file at a specific location (lines 131-143). This is not random—the assistant is looking at the end of the RPC method definitions, where new methods are typically added. The file shows three existing methods: RepairStats, CIDGravityStatus, and ParallelWriteStats. These are all diagnostic endpoints that return operational statistics. The CacheStats endpoint will join this family.

Input Knowledge Required

To understand this message, one needs knowledge of:

Output Knowledge Created

This message, combined with the edit that immediately follows it (message 2768), creates several pieces of output knowledge:

  1. A new RPC endpoint exists: The WebUI can now call CacheStats() via JSON-RPC and receive real-time L1 and L2 cache statistics.
  2. A documented pattern for adding future RPC endpoints: Future developers can look at this method and see exactly how to wire a new diagnostic endpoint—add the method to RIBSDiag, implement it in the backend, add a delegating method to RIBSRpc.
  3. A bridge between monitoring layers: Before this message, cache statistics were available through Prometheus metrics (for automated alerting) and Go code (for internal use). After this message, they are also available through the WebUI (for human operators). This completes the observability triad: metrics, logs, and UI.
  4. A testable contract: The RPC endpoint creates a clear contract between backend and frontend. The frontend can be developed and tested independently, as long as it respects the shape of iface.CacheStats. The backend can be refactored without breaking the frontend, as long as it continues to satisfy the RIBSDiag interface.

The Broader Significance

This message is a microcosm of the development philosophy that pervades the entire FGW project. The assistant consistently follows a pattern: understand the request, survey the existing code, plan the changes in dependency order, implement each layer, and verify at each step. The message at index 2767 is the culmination of that process—the moment when all the preparatory work pays off and the final connection is made.

It also illustrates the importance of interfaces in distributed systems. The RIBSDiag interface acts as a contract that decouples the data producer (the cache implementation) from the data consumer (the WebUI). The RPC layer is the thin adapter that bridges these worlds. Without this layered architecture, adding a new dashboard metric would require touching every component in the system. With it, the change is localized and clean.

Finally, this message demonstrates the value of reading before writing. The assistant reads the existing RPC file to understand the patterns, conventions, and placement before making any changes. This habit of gathering context before acting is a hallmark of disciplined software development—it reduces the risk of introducing inconsistencies or breaking existing patterns.

What Comes Next

The immediate next step (message 2768) is the actual edit: adding the CacheStats method to RIBSRpc. The assistant will write something like:

func (rc *RIBSRpc) CacheStats(ctx context.Context) (iface2.CacheStats, error) {
    return rc.ribs.DealDiag().CacheStats()
}

Following that, the assistant will update the todo list (message 2769) marking the RPC endpoint as completed, and then move on to the final task: adding the Cache Stats tile to the React frontend (message 2770). The full chain—from user request to UI tile—spans approximately 25 messages, with this message serving as the critical integration point.

In the end, a single user request ("UI in dashboard show L1/L2 cache metrics") triggers a cascade of changes across four packages (iface, rbdeal, integrations/web, ribswebapp), touching Go interfaces, implementation code, RPC wiring, and React components. The message at index 2767 is the moment when the backend work is complete and the frontend connection is about to be made—a small but essential step in the journey from data to dashboard.