Diagnosing a Deal Flow Stall: Peering into Group Metadata on a Distributed Storage Cluster

Introduction

In distributed storage systems, the gap between "the system is running" and "the system is doing useful work" can be vast. A cluster may report healthy nodes, responsive APIs, and ample capacity, yet remain stuck at a critical juncture—unable to translate stored data into Filecoin deals. This article examines a single diagnostic message from an opencode coding session where an assistant, responding to a user's request to investigate stalled deal flow, drills into the metadata of individual storage groups on a running Kuri node. The message is a masterclass in targeted investigation: it takes a high-level anomaly ("deals are not flowing") and transforms it into concrete, group-level data that reveals the precise state of each storage group, setting the stage for deeper code-level diagnosis.

Context and Motivation

The session leading up to this message had been intensely productive. The assistant had just completed a major refactoring effort: removing the Lassie/Graphsync retrieval dependency, rewriting the repair worker to use HTTP-only retrieval from storage providers, and updating the Ansible deployment configuration to support repair workers with a dedicated staging path. The commit message read "feat: enable HTTP-only repair workers and remove Lassie dependency." The binary had been built, the Ansible syntax checked, and the deployment verified as healthy across three nodes—an S3 frontend proxy and two Kuri storage nodes.

But the user's focus was elsewhere. The deals—Filecoin storage deals that represent the core economic activity of the system—were not flowing. In message 2240, the user directed: "First - look at logs and see why rbdeal deals are not flowing, then deploy." This reframed the priority from deploying new code to understanding a production behavior problem.

The assistant's initial investigation in messages 2241–2244 revealed two critical findings. First, the CIDgravity API—the external service used to query on-chain deal states—was timing out with context deadline exceeded errors. Second, despite the cluster having two storage groups (IDs 101 and 1), the deal summary returned zeros across the board: NonFailed: 0, InProgress: 0, Done: 0, Failed: 0. No deals existed at all. The group states showed [101, 1], confirming the groups existed, but the deal pipeline was completely empty.

This is the precise moment the subject message (index 2245) arrives. The assistant has established that there are groups but no deals. The next logical question is: what is the state of these groups? Are they ready for deals? Are they still being written to? Are they in some error state? The only way to answer these questions is to query the per-group metadata through the RIBS RPC API.

The Message: Probing Group Metadata

The message begins with a plain-English summary of the situation: "There are 2 groups (101 and 1) but 0 deals." This framing is important—it crystallizes the puzzle. The assistant then executes two curl commands against the Kuri node's RPC endpoint at http://10.1.232.83:9010/rpc/v0, calling the RIBS.GroupMeta method with parameters [1] and [101] respectively.

The response for Group 1 is rich with detail:

{
  "State": 3,
  "MaxBlocks": 20971520,
  "MaxBytes": 30932992000,
  "Blocks": 66254,
  "Bytes": 30932700100,
  "ReadBlocks": 0,
  "ReadBytes": 0,
  "WriteBlocks": 56314,
  "WriteBytes": 28189284096,
  "PieceCID": "baga6ea4seaqbyyqnwbaxicunh5r63sujse6mtyrep7i2ff6da2z3ip3cfrns6ja",
  "RootCID": "bafyreib5f7rocr5syfslpx7cy5vshzq436qfstrpphzr4ntekbhxrialri",
  "DealCarSize": 30938001445
}

The message is cut off at "=== Group 1..." in the conversation data, but we can see from the subsequent message (index 2246) that the assistant was able to interpret this data. The key fields are:

Reasoning and Decision-Making

The thinking process visible in this message follows a clear investigative pattern:

  1. Observation: There are groups but zero deals.
  2. Hypothesis: The groups may not be in the correct state to receive deals, or there may be a configuration or external dependency issue.
  3. Test: Query per-group metadata to check each group's state, size, and readiness indicators.
  4. Interpretation: State 3 means "ready for deals" for Group 1; State 0 means "still writable" for Group 101. The assistant's decision to query group metadata rather than, say, checking network connectivity or wallet balance again, shows an understanding of the system's state machine. The deal pipeline has a precondition: groups must reach a specific state (GroupStateLocalReadyForDeals) before the system will attempt to make deals for them. By checking the group state directly, the assistant can determine whether the deal pipeline is being blocked by a missing precondition or by something else. This is a critical distinction. If both groups were in State 0 (writable), the answer would be "the groups aren't ready yet—wait for them to fill and seal." But Group 1 is in State 3, meaning it should be getting deals. The fact that it has zero deals despite being ready points to a different class of problem: either the deal-making logic is failing, or an external dependency (like the CIDgravity API) is preventing it from proceeding.

Assumptions and Their Validity

The assistant makes several assumptions in this message:

  1. The RPC endpoint is authoritative: The assistant assumes that querying RIBS.GroupMeta on kuri_01 (10.1.232.83) gives an accurate, up-to-date view of group state. Given that the cluster topology shows both nodes as healthy and the data is stored in a shared YugabyteDB, this is a reasonable assumption.
  2. Group state determines deal eligibility: The assistant assumes that the group state machine is the primary gate for deal creation. This is confirmed by later code reading (message 2249), where line 310 of deal_tracker.go shows if gs.State != ribs2.GroupStateLocalReadyForDeals { continue }—the deal check loop explicitly skips groups not in the ready state.
  3. The metadata response is complete enough: The assistant only queries GroupMeta for the two known group IDs. This assumes that there aren't additional groups in other states that might reveal more about the system's behavior.
  4. The CIDgravity timeout is a separate issue: By focusing on group metadata, the assistant implicitly assumes that the CIDgravity timeout and the zero-deal count are related but distinct investigations. The timeout explains why the deal check loop might be failing, but the group metadata query addresses whether the groups are even eligible. These assumptions are largely valid. The one potential blind spot is that the assistant doesn't yet check whether the deal-making logic has any other preconditions—like wallet balance, datacap availability, or provider availability—that might also block deals. However, those checks come in subsequent messages (2247–2248), showing a methodical breadth-first investigation.

Input Knowledge Required

To fully understand this message, a reader needs:

  1. RIBS RPC API familiarity: Knowing that RIBS.GroupMeta returns per-group metadata including state, size, and content identifiers. The endpoint is a JSON-RPC interface on port 9010.
  2. Group state machine understanding: The group lifecycle includes states like GroupStateWritable (accepting data), GroupStateLocalReadyForDeals (sealed and ready for Filecoin deals), and potentially others like GroupStateDealInProgress or GroupStateDealDone. State 3 corresponds to the ready-for-deals state.
  3. Filecoin deal mechanics: Groups are collections of data that get committed to Filecoin storage deals. A PieceCID identifies the data piece, and DealCarSize is the size of the CAR archive that would be stored on Filecoin.
  4. The CIDgravity context: From earlier messages, the reader knows that the CIDgravity API (service.cidgravity.com/private/v1/get-on-chain-deals) is timing out. This external API is used to check the on-chain status of existing deals and is called before the system attempts to make new ones.
  5. The deployment topology: Two Kuri nodes (kuri_01 at 10.1.232.83, kuri_02 at 10.1.232.84), an S3 proxy at 10.1.232.82, and a shared YugabyteDB backend.

Output Knowledge Created

This message produces several concrete outputs:

  1. Group 1 is ready for deals but has none: State 3 with ~30.9 GB of data, a valid PieceCID, and a DealCarSize of ~30.9 GB. This is a group that should be actively entering the deal pipeline but isn't.
  2. Group 101 is still writable: State 0 with data still being written. This group is not yet eligible for deals, which is expected behavior.
  3. The deal stall is not caused by group immaturity: Since Group 1 is in the ready state, the problem must lie elsewhere—either in the deal-making logic itself, in external API failures, or in configuration.
  4. A clear next investigative step: The assistant now knows to look at the deal tracker code (which it does in messages 2249–2251) to understand why a ready group isn't getting deals. This leads to discovering that the CIDgravity check loop runs first and its timeout blocks the entire deal check loop from reaching the SP (storage provider) deal-making logic.

Broader Significance

This message exemplifies a pattern common in distributed systems debugging: the need to translate a cluster-level symptom ("no deals") into per-component state information. The assistant doesn't guess or speculate—it queries the system's own introspection APIs to get ground-truth data about each group's state. This approach is only possible because the RIBS system was designed with observability in mind, exposing group metadata through a structured RPC interface.

The message also highlights the importance of state machines in distributed storage. The group state is not just a status flag—it's a gate that controls whether the deal pipeline will even consider a group. By checking the state first, the assistant avoids chasing red herrings and narrows the investigation to the correct layer of the system.

Finally, this message is a reminder that "the system is running" and "the system is healthy" are not the same thing. Both Kuri nodes showed healthy status, the S3 proxy was responding, and the cluster topology was consistent. Yet the core business function—making Filecoin deals—was completely stalled. The assistant's methodical drill-down from cluster health to group metadata to code logic demonstrates the multi-layered thinking required to debug real-world distributed systems.