The 162-Second Gap: Diagnosing CIDgravity API Timeouts in a Distributed Storage System

The Message

[assistant] The API works from kuri1 - it took 2.6 seconds and returned 5.3MB of data. So the API is working, but the kuri service is timing out. Let me check if there's an issue with the client timeout configuration:

>

``bash # Check the logs again for more context - the timeout is 30 seconds but it's taking ~150 seconds echo "=== Recent GOCD timeout details ===" ssh 10.1.232.83 "sudo journalctl -u kuri --since '30 min ago' --no-pager | grep -E 'get-on-chain-deals|deal check loop' | tail -10" ``

>

`` Feb 04 10:25:51 fgw-ribs1 kuri[18116]: 2026-02-04T10:25:51.818Z INFO ribs:rbdeal rbdeal/deal_tracker.go:427 Starting deal check loop cidg check Feb 04 10:28:33 fgw-ribs1 kuri[18116]: 2026-02-04T10:28:33.850Z ERROR ribs:rbdeal rbdeal/deal_tracker.go:52 deal check loop failed {"error": "Post \"https://service.cidgravity.com/private/v1/get-on-chain-deals\": context deadline exceeded (Client.Timeout ex... ``

Introduction: A Pivotal Diagnostic Moment

Message 2262 represents a critical inflection point in a complex debugging session within the Filecoin Gateway (FGW) distributed storage system. The assistant, having been asked by the user to investigate why "rbdeal deals are not flowing," has spent the preceding twenty-two messages systematically probing a production QA cluster spanning three physical nodes. What makes this message particularly significant is the cognitive pivot it captures: the moment when a seemingly intractable problem—persistent API timeouts—is reframed as a configuration or code-level issue rather than a network or API availability problem.

The message is brief—just a shell command and its output—but it encapsulates a profound diagnostic realization. The assistant has just proven that the CIDgravity API endpoint get-on-chain-deals responds correctly in 2.6 seconds when called directly from the kuri1 node with the proper X-API-KEY header. Yet the kuri service itself, running on the same machine, consistently fails with a "context deadline exceeded" error. This contradiction—the API works from the command line but fails from the service—narrows the universe of possible causes dramatically. The problem is no longer "is the API reachable?" but rather "what is different about how the kuri service makes this HTTP call?"

The Reasoning and Motivation Behind the Message

The assistant's motivation in writing this message is fundamentally diagnostic. The broader context reveals a carefully constructed investigative chain spanning messages 2240 through 2261. The user's initial instruction—"First - look at logs and see why rbdeal deals are not flowing, then deploy"—set the assistant on a path of systematic elimination.

The assistant began by examining deal-related logs, discovering that the CIDgravity get-on-chain-deals call was timing out. It then tested connectivity from the node, confirming TCP connectivity to service.cidgravity.com:443. It checked the authentication mechanism, discovering that the code used X-API-KEY rather than Authorization: Bearer—a critical detail that explained why an earlier test with the wrong header returned 401 Unauthorized. It tested the API with the correct header from the node and received a 200 OK response with 5.3MB of data in 2.6 seconds.

Message 2262 represents the next logical step in this chain: having confirmed the API works from the node, the assistant must now understand why the service fails. The comment "the timeout is 30 seconds but it's taking ~150 seconds" reveals the assistant's working hypothesis—that there is a discrepancy between the configured HTTP client timeout (30 seconds, as seen in the code) and the actual observed timeout duration (approximately 162 seconds, calculated from the timestamps 10:25:51 to 10:28:33).

This message is therefore motivated by the need to gather precise timing data. The assistant is testing a specific hypothesis: that the timeout duration is inconsistent with the configured value, which would indicate either a different timeout configuration being applied, a cumulative timeout across multiple API calls, or a completely different failure mechanism than a simple HTTP client timeout.

How Decisions Were Made

Several implicit decisions shaped this message. First, the assistant decided to focus on timing rather than connectivity or authentication. Having eliminated network reachability (the connection establishes) and authentication (the X-API-KEY header works), the remaining variable is the temporal behavior of the request within the service's runtime context.

Second, the assistant chose to examine the journal logs with a specific filter—grep -E 'get-on-chain-deals|deal check loop'—rather than examining raw logs or broader patterns. This decision reflects a narrowing of scope: the assistant is no longer exploring broadly but testing a specific hypothesis about timeout duration.

Third, the assistant decided to present the raw log output rather than summarizing it. The two log lines—one at 10:25:51 showing the start of the CIDgravity check, and one at 10:28:33 showing the error—are presented without commentary. This is a deliberate rhetorical choice: the data speaks for itself. The 162-second gap between these timestamps is the key observation, and the assistant trusts the reader (or their own future reasoning) to recognize its significance.

Assumptions Made by the User and Agent

Several assumptions are embedded in this exchange. The assistant assumes that the HTTP client timeout configured in the code is 30 seconds—an assumption derived from earlier reading of the get_deal_states.go source file, which showed a 30-second timeout on the HTTP client. However, the observed 162-second timeout contradicts this, suggesting either that the assumption is wrong (perhaps a different timeout is being applied) or that the failure mechanism is not a simple per-request timeout.

The assistant also assumes that the CIDgravity API call is the only thing happening in the deal check loop. The log shows "Starting deal check loop cidg check" at 10:25:51 and the error at 10:28:33, with nothing in between. This suggests the entire 162 seconds is consumed by a single API call (or a sequence of calls) to get-on-chain-deals. But the assistant's earlier test showed a single call takes 2.6 seconds. The discrepancy implies either multiple calls are being made, or the call is being retried with a backoff, or something else is happening within the runCidGravityDealCheckLoop function.

The user, for their part, assumed that the deal flow stall was a deployment issue that could be fixed by deploying the new binary. The assistant's investigation revealed a more nuanced problem: even the old binary's deal flow was blocked by CIDgravity API timeouts, independent of the repair worker and Lassie cleanup changes in the new build.

Mistakes and Incorrect Assumptions

The most significant potential mistake in this message is the implicit assumption that the 30-second timeout mentioned in the code comment is the actual timeout being applied. The assistant writes "the timeout is 30 seconds but it's taking ~150 seconds," suggesting a belief that the configured timeout is 30 seconds. However, the actual timeout might be configured differently—perhaps the HTTP client is created with a different timeout elsewhere, or the context passed to the HTTP call has a different deadline.

Another subtle issue is the assistant's framing of the problem. By focusing on the timeout duration discrepancy, the assistant may be overlooking the possibility that the API call is succeeding but something downstream in the processing pipeline is slow. The 5.3MB response from the API suggests a substantial payload—perhaps the service is spending most of the 162 seconds processing the response rather than waiting for it.

There is also an assumption that the command-line test is representative of the service's runtime environment. The curl command run via SSH uses the same network path and the same token, but it runs as root rather than as the fgw user, and it doesn't have the same connection pooling, rate limiting, or concurrency constraints that the service operates under. The CIDgravity client code uses a semaphore to limit connections (CIDGRAVITY_MAX_CONNECTIONS="4"), and if other parts of the system are also making CIDgravity calls concurrently, the semaphore could introduce queuing delays that manifest as timeouts.

Input Knowledge Required to Understand This Message

To fully grasp the significance of message 2262, one needs substantial context from the preceding conversation. The reader must understand:

  1. The system architecture: The FGW cluster consists of an S3 proxy node (10.1.232.82) that routes requests to two Kuri storage nodes (10.1.232.83 and 10.1.232.84), which store data in groups and manage Filecoin deals through CIDgravity.
  2. The deal flow: Groups transition through states (Writable → LocalReadyForDeals → etc.), and when a group is ready for deals, the deal tracker calls CIDgravity's get-on-chain-deals and get-best-available-providers APIs to find storage providers and propose deals.
  3. The CIDgravity integration: The system uses CIDgravity as a deal-making intermediary. The API token is stored in /home/fgw/.ribswallet/cidg.token and loaded at runtime. The authentication uses X-API-KEY header, not Authorization: Bearer.
  4. The debugging history: The assistant has already checked group states (groups 1 and 101 exist, group 1 is in state 3 = GroupStateLocalReadyForDeals), wallet balance (374 TiB datacap, 1 FIL market balance), and confirmed that the API responds from the node.
  5. The code structure: The deal check loop in rbdeal/deal_tracker.go first calls runCidGravityDealCheckLoop, and if that fails, the subsequent runDealCheckCleanupLoop (which actually proposes new deals) never executes. This means a single failing CIDgravity call blocks the entire deal-making pipeline. Without this context, the message appears to be a simple log check. With it, the message becomes a crucial piece of forensic evidence in a complex debugging puzzle.

Output Knowledge Created by This Message

Message 2262 produces several important pieces of knowledge:

  1. Precise timing data: The log timestamps establish that the CIDgravity check takes approximately 162 seconds (from 10:25:51 to 10:28:33) before timing out. This is significantly longer than the 30-second timeout the assistant expected, and dramatically longer than the 2.6-second response time observed from the command line.
  2. Confirmation of the blocking behavior: The log shows that the deal check loop starts the CIDgravity check and then nothing else happens until the error. This confirms that the runCidGravityDealCheckLoop function is blocking the entire deal pipeline, preventing any new deals from being proposed.
  3. Evidence of a configuration or code bug: The discrepancy between the command-line success (2.6s) and the service failure (162s timeout) strongly suggests a bug in the service's HTTP client configuration or in the runCidGravityDealCheckLoop function itself. The assistant now has a clear direction for further investigation: examine how the HTTP client is constructed, what timeout is actually set, and whether there are retry loops or other mechanisms that could extend the effective timeout.
  4. A refined hypothesis: The assistant can now hypothesize that the issue is not with the CIDgravity API but with how the kuri service interacts with it. This shifts the debugging focus from external API debugging to internal code and configuration analysis.

The Thinking Process Visible in Reasoning

The assistant's reasoning in this message is revealed through the structure of the investigation and the specific choices made. The comment "the timeout is 30 seconds but it's taking ~150 seconds" is particularly revealing. It shows that the assistant has already done the mental arithmetic: 10:28:33 minus 10:25:51 equals approximately 162 seconds. The assistant is comparing this to the expected 30-second timeout and finding a discrepancy.

This reasoning follows a pattern common in distributed systems debugging: when a component fails in a way that contradicts direct observation, the most likely explanation is a difference in configuration, context, or code path between the direct test and the failing component. The assistant is essentially saying: "The API works from here. The service fails from there. What's different?"

The assistant also demonstrates a preference for gathering concrete data before forming conclusions. Rather than immediately diving into the code to find the timeout configuration, the assistant first checks the logs to confirm the timing hypothesis. This is a disciplined debugging approach—verify the observable behavior before investigating the code that produces it.

The message also reveals the assistant's mental model of the system. The assistant understands that the deal check loop is a sequential pipeline: CIDgravity check first, then SP deal check, then cleanup. A failure in the first stage blocks the entire pipeline. This understanding informs the diagnostic strategy: fix the CIDgravity timeout, and the deal flow will resume.

Broader Significance

Message 2262 is a textbook example of a diagnostic pivot in distributed systems debugging. The assistant has moved from external probing (testing the API from the node) to internal analysis (examining the service's behavior). The key insight—that the API works but the service times out—transforms the problem from a network/API issue to a code/configuration issue.

This message also illustrates the importance of precise timing data in debugging distributed systems. The 162-second gap between start and error is not just a number; it's a clue that points toward the root cause. Is there a retry loop with exponential backoff? Is the HTTP client using a different timeout than expected? Is there a connection pool exhaustion issue? Each of these questions can be investigated based on the timing data.

For the reader unfamiliar with the Filecoin Gateway system, this message serves as a window into the realities of production debugging: the slow, methodical process of eliminating possibilities, the importance of direct verification, and the moment when a confusing failure starts to make sense. The assistant hasn't solved the problem yet, but it has narrowed the search space dramatically—and that is the essential work of debugging.