Breaking the Deadlock: Diagnosing a Distributed Proving System's Self-Inflicted Starvation

The Message

In the midst of an intense debugging session spanning multiple production bugs in a Filecoin ProofShare proving system, the user sent the following message to the assistant:

We've ran into another bug - TaskRequestProofs - among the other problems this method has, main one is that in many cases the service only allows taking 1-2 more work asks/slots returning http TooManyRequests, which CreateWorkAsk will poll forever. This is a big issue because if we've taken 2 asks we won't INSERT INTO proofshare_queue until the remaining work ask creations go through, which they won't ever because we never insert into proofshare queue and there is no way for prove tasks to run and free more slots. There seems to be a separate issue that SELECT service_id FROM proofshare_queue can get expensive because completed proofs are never removed, probably should have a routine to remove completed submited proofs older than e.g. 2 days

This message arrived at a critical juncture. The team had just finished deploying a fix for an entirely different production bug — a cuzk job ID collision where concurrent ProofShare challenges all targeted the same miner and sector, causing partition proofs from different jobs to mix and produce invalid results. That fix had required rebuilding the Rust-based GPU proving binary inside a Docker CUDA environment, hot-swapping it onto a remote instance, and auditing every caller of the cuzk RequestId for similar vulnerabilities. Now, with that fire extinguished, the user surfaced a second, equally pernicious problem: the TaskRequestProofs system was deadlocking itself.

Context: The ProofShare Architecture

To understand why this message matters, one must understand the system it describes. ProofShare is a decentralized proof market — a service where storage providers can bid on and compute proofs for rewards. The system involves several interacting components:

CuSVC — the remote service that issues proof challenges. Providers poll this service for work, create "asks" (bids to compute a proof), and the service matches asks to available work requests.
proofshare_queue — a database table that tracks work items fetched from the service. Items in this queue are picked up by compute tasks and, once proven, submitted back to the service.
TaskRequestProofs — the task responsible for polling the service, creating asks, fetching matched work, and inserting it into the queue.
CreateWorkAsk — a helper function that sends HTTP requests to the service to create a new ask slot. The flow is straightforward: TaskRequestProofs polls the service to discover how many work slots are available, creates asks for the needed number, then waits for those asks to be matched to work requests. When matched work appears, it gets inserted into proofshare_queue, where compute tasks can pick it up, prove it, and submit the result.

The Deadlock: A Classic Distributed Systems Trap

The user's message describes a deadlock scenario that is elegant in its viciousness. The service imposes a rate limit — it only allows a provider to have 1-2 active ask slots at a time. Attempting to create more returns HTTP 429 (Too Many Requests). The CreateWorkAsk function, as originally written, would retry 429 responses indefinitely with exponential backoff, never returning until the ask was successfully created.

Here is the trap. The TaskRequestProofs main loop works in phases: first it polls for work, then it inserts any matched work into the queue, then it creates new asks for remaining capacity. Crucially, the insertion into proofshare_queue and the ask creation are sequential within the same loop iteration. If the provider already has 2 active asks (the maximum allowed), and the loop tries to create 6 more, the first CreateWorkAsk call hits 429 immediately. And then it retries. And retries. And retries. Forever.

Meanwhile, those 2 active asks get matched to work requests by the service. But the loop never discovers this because it never reaches the next poll iteration — it is stuck in the retry loop. The matched work never gets inserted into proofshare_queue. Compute tasks have nothing to work on, so they never finish anything, never free up slots. The service sees the provider's slots as perpetually occupied, so it continues returning 429. The deadlock is absolute.

The user confirmed this diagnosis in a follow-up message ([msg 1910]): "confirmed the deadlock by restarting a locked up node, PSProve tasks created because we polled latest state and added to queue." A restart broke the deadlock because the fresh poll discovered the already-matched requests that had been languishing undiscovered.

The Second Bug: Query Performance Degradation

The user also identified a second, subtler issue. The dedup query SELECT service_id FROM proofshare_queue was loading the entire table into memory. Since completed proofs were never removed from the table, this query would grow progressively more expensive over time. The user proposed a pragmatic solution: a routine to delete completed submitted proofs older than two days. This is a classic database maintenance problem — the table accumulates rows that serve no further purpose but still impose a query cost on every poll cycle.

Input Knowledge Required

To fully grasp this message, one needs to understand several things:

The ProofShare protocol: How work asks, requests, and matching work in a distributed proof market. The concept of rate-limited ask slots is central.
The Curio task system: How harmony tasks poll for work, interact with a database queue, and how task lifecycle works (compute → submit → completion).
HTTP 429 semantics: The Too Many Requests status code and how it signals rate limiting.
Database query performance: How an unbounded SELECT on a growing table creates a slow leak of performance degradation.
The concept of deadlock in concurrent systems: Specifically, a resource starvation deadlock where progress in one part of the system depends on progress in another part, and both are blocked waiting on each other.

Output Knowledge Created

This message created several critical pieces of knowledge:

A precise deadlock diagnosis: The user articulated the exact chain of events — 429 → infinite retry → no queue insertion → no compute → no slot freeing → permanent 429. This is the kind of diagnosis that is nearly impossible to make without deep system understanding.
A concrete fix direction: The user implicitly specified the fix by describing what was broken. If CreateWorkAsk blocks forever on 429, the fix is to make it not block forever. If queue rows are never cleaned up, the fix is to add cleanup.
A prioritization signal: By describing the deadlock as the "main one" and the query issue as "a separate issue," the user communicated what needed immediate attention versus what could wait.
Operational validation: The user's confirmation that a restart broke the deadlock provided empirical evidence for the theory, ruling out alternative explanations like data corruption or protocol mismatches.

Assumptions and Their Validity

The user made several implicit assumptions, all of which proved correct:

The service's 429 behavior is intentional rate limiting, not a transient error: This assumption was critical because if 429 could resolve on its own without action, the retry loop might eventually succeed. But the user understood that the 429 was a consequence of the system's own state — the provider had too many active asks — and that state would not change until the provider processed work, which it couldn't do because it was stuck.
The deadlock is structural, not a race condition: The user assumed that the deadlock would occur reliably, not intermittently. This was confirmed by the restart test: the locked-up node immediately began processing work after restart, proving the deadlock was deterministic given the right conditions.
The queue cleanup is a separate concern: The user correctly separated the two issues, recognizing that even after fixing the deadlock, the unbounded query would eventually cause performance problems.

The Thinking Process Revealed

The user's message reveals a sophisticated mental model of the system. They didn't just report a symptom ("it's stuck") — they traced the causal chain backward from the symptom to the root cause. The phrase "if we've taken 2 asks we won't INSERT INTO proofshare_queue until the remaining work ask creations go through" shows an understanding of the sequential nature of the loop. The phrase "which they won't ever because we never insert into proofshare queue and there is no way for prove tasks to run and free more slots" shows an understanding of the circular dependency that creates the deadlock.

This is diagnostic reasoning at its finest: the user didn't need to read the code to know what the code was doing. They inferred the behavior from the system's observable properties — the rate limit, the sequential processing, the dependency chain — and constructed a complete theory of the failure mode.

The Broader Significance

This message is a case study in a class of distributed systems bugs that are notoriously hard to debug. The deadlock is not a lock contention or a mutex issue — it is a protocol-level starvation where the system's own retry logic prevents it from making progress. The fix, which the assistant would go on to implement, was elegant: make CreateWorkAsk return a sentinel ErrTooManyRequests error on 429 instead of retrying forever, and handle that error in the main loop by breaking out of the ask-creation loop and returning to the poll cycle. This breaks the circular dependency because the loop can now discover matched work even when ask creation is rate-limited.

The user also demonstrated a crucial operational insight: the restart test. By restarting the locked-up node and observing that it immediately began processing work, they confirmed that the deadlock was real and that the system was otherwise healthy. This is a textbook debugging technique — perturb the system and observe the response — applied to a production outage.

Conclusion

The user's message at [msg 1907] is a masterclass in distributed systems debugging. It identifies a self-inflicted deadlock with precision, separates it from a secondary performance issue, provides empirical validation, and implicitly specifies the fix. The message reflects deep knowledge of the ProofShare protocol, the Curio task system, and the operational behavior of the deployed system. It transformed an opaque production outage ("it's stuck") into a well-understood failure mode with a clear path to resolution, enabling the assistant to implement targeted fixes that broke the deadlock and prevented future occurrences.