From Build Cache to Docker Push: The Full Arc of a Production Fix in a Distributed GPU Proving System

Introduction

In the world of distributed GPU proving for the Filecoin network, a single missing %d in a format string can bring an entire proof pipeline to its knees. This article traces the complete arc of a production debugging session that began with invalid proofs and ended with a pushed Docker image — passing through Docker build cache battles, silent deployment failures, systematic codebase audits, and the careful consolidation of fixes into a single coherent commit. The journey spans two critical production bugs, five modified files, 822 lines of code changed, and a final artifact that would serve as the canonical deployment for every future GPU proving instance.

The Two Bugs: Deadlock and Collision

The session targeted two distinct but equally dangerous production bugs in the ProofShare system, a distributed proving pipeline where GPU workers generate cryptographic proofs for Filecoin storage providers.

Bug 1 — The Deadlock. The CreateWorkAsk function in provictl.go would retry HTTP 429 (Too Many Requests) responses indefinitely. Because this function was called synchronously within the Do() loop that polls for matched work, a sustained 429 response created a permanent deadlock: no new work could be inserted into the proofshare_queue because the poll loop was stuck retrying the rate-limited request. The fix introduced ErrTooManyRequests as a sentinel error value, allowing the caller to detect the rate-limit condition and apply exponential backoff on no-progress iterations, resetting to a short interval when progress resumed. This broke the retry loop and restored the system's ability to process work even under rate-limiting pressure.

Bug 2 — The Job ID Collision. This was the more insidious bug. The PSProve PoRep RequestId was formatted as fmt.Sprintf("ps-porep-%d-%d", miner, sector). Because all proofshare challenges target the same hardcoded bench sector (miner=1000, sector=1), every concurrent task sent an identical job_id to the cuzk GPU proving engine. The engine's partition assembler keyed on job_id using a HashMap, causing partition results from different proofs to collide — confirmed by a "partition 0 already inserted" panic. The fix appended the harmony task ID to the format string, producing fmt.Sprintf("ps-porep-%d-%d-%d", miner, sector, taskID), making each job identifier unique per invocation.

A third improvement — queue maintenance — was added alongside these fixes: completed rows in proofshare_queue were never cleaned up, causing unbounded table growth. The fix added a periodic purge of rows older than two days, changed orphan cleanup from DELETE to UPDATE (preserving fetched work for reassignment), and scoped the dedup query to only non-submitted rows.

The Build Cache Betrayal

Fixing the bugs in source code was the easy part. Getting those fixes compiled into a running binary on a remote GPU instance proved to be a saga of its own. The assistant's first deployment attempt used docker cp to copy modified source files into a container, then --volumes-from to mount those files for a rebuild. The resulting binary, tagged _psfix2, was deployed to the remote host. The user reported that cuzk logs still showed ps-porep-1000-1 — the old format string without the task ID.

The assistant's reasoning in [msg 2001] is a masterclass in systematic debugging. It generated two hypotheses: either the Go build cache hadn't recompiled task_prove.go with the change, or the docker cp into the volumes-from container hadn't worked as expected. To test these, the assistant reached for grep -ao on the remote binary — a pragmatic substitute for the unavailable strings command. The regex ps-porep-%d-%d[^\\"]* searched the ELF binary for the format string pattern. The output was devastatingly clear: ps-porep-%d-%d with only two format specifiers. The fix had not been compiled in.

The root cause was a subtle Docker semantics issue. The --volumes-from flag only shares volumes explicitly declared in the Dockerfile via VOLUME directives — it does not share the container's entire writable filesystem. The curio-builder image likely had no VOLUME directive for /build, so the files copied via docker cp were invisible to the build container. The Go compiler, seeing no changes to the source files it could access, served up cached compiled objects from the image layer. The version string _psfix2 reflected the build invocation flags, not the code content — a critical lesson that version strings are not reliable indicators of whether source changes were actually compiled.

The breakthrough came when the assistant switched to direct bind mounts using -v ([msg 2005]). Bind mounts override files at the kernel level, ensuring the build process sees the modified source files. This forced Go to detect the changes, invalidate the build cache for the affected packages, and recompile them. The resulting binary (curio-psfix3) contained the correct ps-porep-%d-%d-%d format string, confirmed by inline grep in the build script.

The Silent Deployment Failure

With the correct binary built and uploaded to /tmp/curio-psfix3 on the remote host, the assistant attempted to deploy it using a chained command: kill $(pgrep -f "curio run") 2>/dev/null; sleep 2; mv /tmp/curio-psfix3 /usr/local/bin/curio && .... This command produced no output — a silent failure that the assistant initially missed.

The debugging in [msg 2009] revealed the truth: the psfix3 file was still sitting in /tmp, untouched. The kill + mv chain had failed. The assistant's hypothesis in [msg 2010] — "The kill+mv must have failed because curio respawned or something" — was close but not quite right. The actual mechanism is more subtle. The kill signal is asynchronous; it sends SIGTERM and returns immediately without waiting for the process to actually exit. The sleep 2 provided a brief window, but if the process took longer to terminate (due to cleanup handlers, goroutine shutdown, or GPU resource release), the mv executed while the old process was still alive. The running process held a memory-mapped reference to the binary's inode, preventing replacement. The 2>/dev/null redirection on the kill hid any error messages, and the && chain silently aborted on the first failure.

The assistant's response was a model of operational maturity: abandon the clever chained command in favor of boring, step-by-step execution. The step-by-step approach in [msg 2010] killed the process explicitly by PID, waited three seconds, verified the process was gone with pgrep, and only then proceeded to copy the binary. This separation ensured each step's result was visible and verifiable. The subsequent deployment succeeded, and the new binary (psfix3) was confirmed running with matching hashes and the correct version string.

The Proactive Audit

At the moment of success — when the assistant reported the fix was running and the user could reasonably declare victory — the user instead asked a question that reveals the difference between fixing a bug and understanding a vulnerability class ([msg 2014]): "Do we have the same issue in other callers to proofshare? Snap, window/winning PoSt?"

This question was grounded in a specific mental model of how the system failed. The root cause was an identity collision: two logically distinct units of work were assigned the same identifier, causing the downstream system to treat them as the same unit. Once the user internalized this failure mode, the natural next step was to ask where else this pattern appears.

The assistant executed a systematic audit, grepping for RequestId: across the codebase and finding six matches across two files (task_prove.go and cuzk_funcs.go). Each caller was analyzed for uniqueness guarantees. The results were reassuring: the proofshare Snap path already included taskID in its format string (ps-snap-%d-%d-%d), normal PoRep and Snap paths used real sector identities that are inherently unique per job, WindowPoSt included both partition ID and a truncated randomness seed, and WinningPoSt included randomness with only one instance per epoch. Only the proofshare PoRep path was vulnerable.

This audit created documented institutional knowledge — a table mapping all six callers to their RequestId formats, uniqueness guarantees, and risk assessments. It established a precedent: after fixing a concurrency bug in a distributed proving system, one should always audit sibling code paths for the same vulnerability pattern.

Consolidation and the Amend

The user's "Success!!" message at [msg 2022] marked the transition from investigation to consolidation. The instruction was precise: "Commit the cuzk/proofsvc changes (one commit)." The assistant executed a git add and git commit with a multi-paragraph message describing all three bugs — the deadlock, the job ID collision, and the queue cleanup — each with its own root cause, symptom, and fix.

But the user noticed something the assistant had missed. Two modified files remained unstaged: extern/cuzk/cuzk-core/src/engine.rs (the self-check gating fix that made the cuzk engine return Failed instead of Completed when proofs failed validation) and lib/proof/porep_vproof_test.go (test infrastructure for PoRep vproof round-trips). The user's question at [msg 2026] — "Why not commit the two remaining modified files?" — prompted a discussion about commit boundaries.

The assistant's reasoning in [msg 2027] revealed a thoughtful judgment: the engine.rs fix was about proof integrity within the cuzk engine itself, while the proofshare fixes were about the distributed coordination layer. In many codebases, these would indeed be separate commits. But the user's answer was succinct: "amend." The assistant performed due diligence first — checking the git author configuration and confirming the commit hadn't been pushed — then executed git add and git commit --amend --no-edit ([msg 2030]). The result was commit 44429bb7, spanning five files with 822 insertions and 208 deletions — a far more accurate representation of the full scope of work.

The Final Artifact

With the consolidated commit in place, the user issued the instruction that would cap the entire debugging marathon: "build/push new docker image" ([msg 2032]). This was not a casual request. It represented a deliberate transition from ad-hoc patching — the fragile workflow of building binaries locally, SCP-ing them to remote hosts, and hot-swapping running processes — to a proper, reproducible deployment artifact.

The Docker build itself took several minutes, involving apt-get installations of runtime dependencies and the multi-stage compilation of the Curio binary, the cuzk GPU proving engine, and supporting tools. Before pushing, the assistant performed a critical verification step: running a container with the entrypoint overridden to check that the binary inside contained the correct format string. The output confirmed ps-porep-%d-%d-%d — three format specifiers, including the task ID. The fix was genuinely compiled into the image.

The push at [msg 2038] uploaded 19 Docker image layers to Docker Hub, all showing "Preparing" status — indicating a completely fresh push, not an incremental update. Each of those 19 layers represented a battle won: against deadlocks, against cache invalidation, against subtle identifier collisions, against the inherent complexity of distributed proving systems. After this push, any instance pulling theuser/curio-cuzk:latest would automatically receive all five fixes.

Conclusion

This chunk of the opencode session is a microcosm of the challenges inherent in patching production GPU-proving systems. Unlike a typical web service where you can git pull && make && systemctl restart, these systems require a specific CUDA-enabled build environment, cross-compilation with architecture-specific flags, hot-swapping binaries on remote machines without full container orchestration, and verifying not just that the binary is running but that the correct code is running.

The build cache defeat was particularly insidious because it produced a binary that looked correct (new version string, same file size, same behavior) but was incorrect (old format string, old job ID generation). It was a silent failure mode that standard deployment verification — checking the version string, checking the process is running — did not catch. The lesson is universal: in complex distributed systems, the deployment pipeline is not a neutral conduit; it is an active participant in the correctness of the system, and it can betray you in ways that no amount of version-string checking will catch.

The session also demonstrated the importance of systematic auditing after fixing a production bug. The user's question about sibling callers transformed a single bug fix into a comprehensive vulnerability assessment, ruling out the same failure pattern across the entire codebase. And the consolidation of all fixes — proofshare deadlock, job ID collision, queue cleanup, engine self-check enforcement, and test infrastructure — into a single amended commit preserved the narrative coherence of the changes, ensuring that future engineers reading git log would see the full story in one entry.

In the end, what began as a "partition 0 already inserted" panic in a Rust GPU engine was resolved through Go format strings, Docker volume semantics, SSH process management, binary grep patterns, git amend operations, and a Docker push. It is a reminder that in distributed systems engineering, the simplest fixes are often the hardest to deploy correctly, and the most important decisions are often encoded not in elaborate design documents, but in the careful, step-by-step execution of commands that transform a broken system into a working one.