Planning the Invisible: How a Todo List Orchestrated L1/L2 Cache Metrics in a Distributed Storage System

The Message

[assistant] [todowrite] {"todos":[{"content":"Add CacheStats struct to iface package","id":"1","priority":"high","status":"in_progress"},{"content":"Add CacheStats method to RIBSDiag interface","id":"2","priority":"high","status":"pending"},{"content":"Implement CacheStats in retrieval provider","id":"3","priority":"high",...
[
  {
    "id": "1",
    "content": "Add CacheStats struct to iface package",
    "status": "in_progress",
    "priority": "high"
  },
  {
    "id": "2",
    "content": "Add CacheStats method to RIBSDiag interface",
    "status": "pending",
    "priority": "high"
  },
  {
    "id": "3",
    "content": "Implement CacheStats in retrieval provider",
    "status": "pending",
    "priority": "high"
  },
  {
    "id": "4",
    "content": "Add CacheStats RPC endpoint",
    "status": "pending",
    "priority": "high"
  },
  {
    "id": "5",
    "content": "Add CacheStatsTile to WebUI Status page",
    "status": "pending",
    "priority": "high"
  }
]

Introduction: The Power of a Checklist

In software engineering, the most dramatic moments are often the ones we see—the pull request merged, the bug fixed, the feature demoed. But the quietest, most consequential moments are the ones where a developer decides what to do next. Message 2748 in this coding session is one such moment. On its surface, it is nothing more than a structured todo list: five items, each with a status and priority, tracking the work required to expose L1 and L2 cache metrics in a WebUI dashboard for a distributed Filecoin storage gateway. But beneath that surface lies a rich tapestry of architectural reasoning, dependency mapping, interface design, and operational philosophy.

This message is a planning artifact—a bridge between a user's high-level request ("UI in dashboard show L1/L2 cache metrics") and the concrete implementation that followed across more than a dozen subsequent edits. Understanding why this message was written, how its decisions were made, and what assumptions it encodes reveals a great deal about how professional software is built in real time, under the guidance of an experienced architect.

Why This Message Was Written: The Context and Motivation

The immediate trigger was the user's command at message 2746: "UI in dashboard show L1/L2 cache metrics." This was not the first request for dashboard improvements in this session. Earlier, the user had asked for a CIDGravity connection status check in the WebUI, which the assistant had implemented by creating a new status check endpoint in the cidgravity package and exposing it via RPC. The pattern was established: the user wanted operational visibility into critical system components, and the assistant was expected to deliver it quickly and correctly.

But the L1/L2 cache request was different in an important way. Unlike the CIDGravity status check, which could be implemented with a relatively self-contained endpoint, cache metrics touched multiple layers of the architecture. The L1 cache (an ARC—Adaptive Replacement Cache—in the rbcache package) and the L2 cache (an SSD-backed cache in the same package) were internal data structures used by the retrieval provider (rbdeal/retr_provider.go). They had their own statistics structures defined deep within the rbcache package, but those structures were not exposed through any diagnostic interface, RPC endpoint, or UI component.

The assistant's first step, at message 2747, was a reconnaissance task: search the codebase for existing cache metrics, stats, and RPC endpoints. The results showed that CacheStats and SSDCacheStats structs already existed in rbcache/arc.go and rbcache/ssd.go, with fields like Size, Capacity, T1Size, T2Size, B1Len, B2Len, P, HitCount, MissCount, HitRate, and similar SSD-specific metrics. These were being updated via Prometheus metrics but were not accessible through the diagnostic RPC layer that the WebUI consumed.

The gap was clear: the data existed but was not plumbed through to the user interface. The todo list in message 2748 was the assistant's plan to bridge that gap.

How Decisions Were Made: The Architecture of the Todo List

The five items in the todo list are not arbitrary. They follow a strict dependency chain that reflects the layered architecture of the system:

  1. Add CacheStats struct to iface package — The iface package defines the shared interface types that cross package boundaries. Before anything else could happen, a unified CacheStats struct needed to exist in iface that could represent both L1 and L2 cache statistics. The assistant chose to create a combined struct rather than exposing the raw rbcache.CacheStats and rbcache.SSDCacheStats types separately, which would have required the UI to understand two different shapes. This was a design decision favoring simplicity and encapsulation.
  2. Add CacheStats method to RIBSDiag interface — The RIBSDiag interface in iface/iface_ribs.go is the diagnostic contract that all storage backends must implement. Adding a CacheStats() method to this interface meant that any backend could provide cache statistics. This was the correct architectural layer: the diagnostic interface is how the RPC layer discovers system state.
  3. Implement CacheStats in retrieval provider — The actual implementation lives in rbdeal/retr_provider.go, where the retrievalProvider struct holds references to both the L1 ARC cache and the L2 SSD cache. The implementation would need to call .Stats() on each cache and return the combined result. This item was marked "in_progress" because the assistant had already begun reading the relevant source files.
  4. Add CacheStats RPC endpoint — The RPC layer in integrations/web/rpc.go exposes diagnostic methods to the WebUI via JSON-RPC. A new CacheStats method on the RIBSRpc struct would delegate to DealDiag().CacheStats(). This is a thin wrapper—the RPC layer adds no logic, only routing.
  5. Add CacheStatsTile to WebUI Status page — Finally, a React component in ribswebapp/src/routes/Status.js would fetch the cache stats from the RPC endpoint and render them in a styled tile, following the same pattern as the existing CIDGravityStatusTile and RetrStats components. The ordering is deliberate: each item depends on the previous one. You cannot implement the RPC endpoint before the interface method exists. You cannot add the UI tile before the RPC endpoint is available. The todo list is a topological sort of the implementation steps.

Assumptions Embedded in the Plan

The assistant made several assumptions, most of which were correct but worth examining:

Assumption 1: The existing cache stats structures were sufficient. The assistant assumed that the CacheStats and SSDCacheStats structs in rbcache already contained the right fields and that the .Stats() methods already worked correctly. This was a reasonable assumption given that these were production data structures with Prometheus metrics already wired up. However, it meant the assistant did not verify that the stats were being updated correctly under load—a potential blind spot.

Assumption 2: The combined struct should flatten L1 and L2 into one response. Rather than having separate RPC calls for L1 and L2 stats, the assistant planned to create a single CacheStats struct in iface that includes fields for both caches. This simplifies the UI but creates a coupling: if a new cache layer is added in the future, the struct must be extended. This was a pragmatic tradeoff for a system with exactly two cache layers.

Assumption 3: The UI tile should follow the existing pattern. The assistant had recently implemented the CIDGravityStatusTile and planned to reuse the same visual style, placement, and data-fetching pattern. This minimized UI-specific decisions and kept the implementation focused on the backend plumbing.

Assumption 4: No new API endpoints were needed. The assistant assumed that the existing JSON-RPC mechanism used by the WebUI was sufficient and that no REST endpoints or authentication changes were required. This was consistent with the system's architecture, where the WebUI communicates exclusively through the RPC layer.

Potential Mistakes and Incorrect Assumptions

While the plan was sound, there were subtle risks:

The interface coupling risk. Adding CacheStats() to the RIBSDiag interface meant that every implementation of that interface—including any future backends or test mocks—would need to implement this method. If a backend doesn't have caches, it would need to return an empty or zeroed struct. The assistant did not consider whether a separate, optional interface might have been more appropriate.

The missing error handling. The todo list did not include error handling for the case where the caches are not initialized or the stats method panics. In the subsequent implementation, the assistant added a nil check for the L2 cache (which is optional), but the plan itself did not account for this edge case.

The UI placement decision. The assistant planned to add the CacheStatsTile to the "External Storage" section of the Status page, near the retrieval stats. This made logical sense (caches are part of the retrieval path), but it assumed that the user would find it there without confusion. A more discoverable location might have been a dedicated "Cache" section.

Input Knowledge Required to Understand This Message

To fully grasp what this todo list means, one must understand:

Output Knowledge Created by This Message

The todo list itself is ephemeral—it was used to guide the implementation and then discarded (or marked complete). But the knowledge it encoded was materialized in the subsequent edits:

The Thinking Process Visible in the Reasoning

The todo list reveals the assistant's thinking process in several ways:

The prioritization of interface over implementation. Item 1 is "Add CacheStats struct to iface package"—the shared interface layer comes first. This reflects a design philosophy where contracts are established before implementations are written. The assistant was thinking top-down, not bottom-up.

The recognition of existing patterns. The assistant noticed that the CIDGravity status feature had followed a similar pipeline (interface → RPC → UI) and was applying the same pattern to cache metrics. This is not explicitly stated but is visible in the parallel structure of the todo items.

The granularity of work units. Each todo item is small enough to be completed in a single edit session (reading a file, making a change, verifying). The assistant was thinking in terms of atomic, verifiable steps rather than large, risky changes.

The sequencing of dependencies. The "in_progress" status on item 1 while items 2-5 are "pending" shows that the assistant understood the dependency chain and was working through it methodically. This is the thinking of a developer who has been burned by out-of-order work before.

Conclusion

Message 2748 is a humble artifact—a todo list in a coding session that lasted only a few minutes. But it captures a moment of architectural reasoning that is invisible in the final code. The code, after all, just works. The todo list shows how someone decided it would work. It reveals the dependencies that were mapped, the patterns that were recognized, the assumptions that were made, and the sequence that was chosen. For anyone studying how complex software is built, these planning artifacts are worth as much attention as the code they produce. They are the blueprint before the building, the map before the journey, the thinking before the typing.