The Docker Push That Sealed the Fix: Deploying a Post-Restart Warmup for GPU Proving Benchmarks

Introduction

In the sprawling, multi-threaded narrative of the opencode coding session — where GPU instances across Europe were being orchestrated to benchmark Filecoin's cuzk proving engine — one message stands out as a quiet but pivotal moment. Message [msg 1179] is deceptively simple: a Docker build, a tag, and a push to Docker Hub. On its surface, it is a routine CI-like operation. But in the context of the session, this message represents the culmination of a multi-hour debugging odyssey, the deployment of a tactical fix for a persistent gRPC transport error, and the final step before the entire system could be validated. This article unpacks why this message was written, the reasoning that led to it, the assumptions embedded within it, and the knowledge it both consumed and produced.

The Crisis That Preceded the Push

To understand message [msg 1179], one must first understand the cascade of failures that preceded it. The session had been working to deploy and benchmark PoRep (Proof of Replication) proving on rented GPU instances from Vast.ai. Two instances were in play: a "Belgium" machine with 2x NVIDIA A40 GPUs and 2TB RAM, and a "Czechia" machine with 2x RTX 3090 GPUs and 251GB RAM. Both were running a custom Docker image (theuser/curio-cuzk:latest) that contained the cuzk proving engine, a benchmark script (benchmark.sh), and an entrypoint that orchestrated parameter fetching, daemon startup, and proof execution.

The failures came in two flavors, and they struck almost simultaneously.

Belgium was killed by the vast-manager's lifecycle monitor. The manager had a 20-minute timeout for the transition from params_done (parameters fetched) to bench_done (benchmark completed). But the benchmark flow on this machine required more than 20 minutes: a warmup proof with PCE (Pre-Compiled Constraint Evaluator) extraction took ~5 minutes, the daemon restart and SRS parameter preload took another ~2 minutes, and the actual 12-proof batch at concurrency 6 took ~15–20 minutes. The total was ~25–30 minutes, well over the 20-minute limit. The manager killed the instance before it could finish.

Czechia suffered a different fate. Its warmup proof completed successfully, and the daemon was restarted with full partition_workers=10. But the very first proof in the batch benchmark immediately failed with a gRPC transport error: Error: Prove RPC failed ... status: Unknown, message: "transport error". The daemon was alive — logs showed it accepting the prove requests and beginning synthesis — but the gRPC client (cuzk-bench) timed out waiting for the first proof to complete. The root cause was that after a daemon restart, GPU kernels need to be compiled and cached, and the first proof takes significantly longer. With two proofs running concurrently (concurrency=2) and 10 partition workers each, the synthesis of 20 partitions simultaneously pushed the first proof completion beyond the gRPC timeout. The result was a bench_rate of 0, and the manager killed the instance.

The Tactical Response

The assistant responded with two tactical fixes. First, the benchmark timeout in the vast-manager was increased from 20 to 45 minutes ([msg 1160]), and the manager was rebuilt and redeployed (<msg id=1161–1162>). Second, a "post-restart warmup" proof was added to benchmark.sh ([msg 1177]): after the daemon restart with full partition workers, a single proof would be run to warm up the GPU kernels before the timed batch. If this warmup proof failed (e.g., due to a broken pipe), the script would retry. The syntax was verified ([msg 1178]).

These fixes were sound in theory, but they existed only as source code on the development machine. They had not yet been deployed to the Docker image that all instances pull from Docker Hub. Without a rebuild and push, every new instance created after this point would still use the old image — the one without the post-restart warmup, without the increased timeout. The fixes would exist in a vacuum, unable to affect the running system.

Message [msg 1179]: The Deployment

This is the context in which message [msg 1179] was written. The assistant executed three commands in sequence:

docker build -f Dockerfile.cuzk -t curio-cuzk:latest .
docker tag curio-cuzk:latest theuser/curio-cuzk:latest
docker push theuser/curio-cuzk:latest

The build produced a new image with SHA 22d2c82a5536, and the push uploaded layers to Docker Hub, resulting in digest sha256:9a9dfb2aa456730407bea30bcb2d7281da3312b16ba615276883c3bc08866513. The output confirms that two layers already existed (cached from previous builds) and two new layers were pushed — corresponding to the changed benchmark.sh script and any other modified files.

Why This Message Matters

On the surface, this is a routine build-and-push. But in the arc of the session, it is the moment where debugging transitions into deployment. Every prior message was about diagnosis, analysis, and code editing. This message is about shipping. It is the bridge between "we know what's wrong" and "the system will now work correctly."

The reasoning behind the message is straightforward: the fixes must be in the Docker image that instances pull at startup. The assistant had already verified the syntax of the updated benchmark.sh ([msg 1178]). The next logical step was to build the image and push it. There was no hesitation, no further analysis — the path was clear.

But there is also an implicit assumption here: that the Docker build would succeed. The assistant had previously encountered build failures in this session — missing jq, broken libcuda.so.1 symlinks, PEP 668 pip restrictions, SPDK pip conflicts, and libcudart_static.a linker errors (see segment 4 and 5 summaries). Each of those had required debugging and fixes to the Dockerfile or entrypoint. By message [msg 1179], those issues had been resolved, and the build was expected to succeed. The output confirms it did: #42 DONE 0.7s — a fast build thanks to layer caching.

Input Knowledge Required

To fully understand this message, a reader needs several pieces of context:

  1. The Docker build system: The Dockerfile.cuzk is a multi-stage build that compiles Rust code, installs CUDA dependencies, and packages the cuzk proving engine along with supporting scripts. The --entrypoint override trick used in earlier messages (e.g., [msg 1174]) shows that the assistant knows the image's internal structure.
  2. The image tagging convention: curio-cuzk:latest is the local tag, and theuser/curio-cuzk:latest is the Docker Hub tag. The theuser/ prefix indicates a Docker Hub repository under the user theuser. The push makes the image publicly available (or at least accessible to the Vast.ai instances that pull it).
  3. The layer caching behavior: The output shows "Layer already exists" for two layers and "Pushed" for two others. This tells us that the Docker build system cached intermediate layers from previous builds, and only the layers corresponding to changed files were rebuilt and pushed. This is standard Docker behavior but is visible evidence of the incremental nature of the build.
  4. The failure modes being addressed: Without knowing about the gRPC transport error on Czechia and the benchmark timeout on Belgium, the push seems like a routine operation. With that context, it becomes a critical deployment of a targeted fix.

Output Knowledge Created

This message produces several forms of knowledge:

  1. A new Docker image digest: sha256:9a9dfb2aa456730407bea30bcb2d7281da3312b16ba615276883c3bc08866513. This digest uniquely identifies the image and can be used for verification, rollback, or auditing. Any instance pulling theuser/curio-cuzk:latest after this push will receive this specific image.
  2. Confirmation that the build succeeds: The build completed in 0.7s for the final export step, and the push succeeded. This confirms that the Dockerfile and all dependencies are in a working state — no missing packages, no compilation errors, no broken symlinks.
  3. Evidence of the fix being deployed: The two pushed layers correspond to the changes in benchmark.sh (the post-restart warmup) and possibly other modified files. The fact that they pushed successfully means the fix is now live and will be used by all new instances.
  4. A checkpoint in the session timeline: After this message, the assistant can create new instances that will use the fixed image. The next messages in the session confirm this: a new Belgium instance is created ([msg 1180]), and the assistant begins monitoring its progress.

Assumptions and Potential Mistakes

The assistant makes several assumptions in this message:

The build is correct: The assistant assumes that the Docker build produces a working image. The syntax check on benchmark.sh passed, but that only validates shell syntax, not runtime behavior. The post-restart warmup logic could still have bugs — incorrect variable references, wrong retry logic, or unexpected interactions with the daemon's state. The assistant is implicitly trusting the build process and the correctness of the code.

The push is sufficient: The assistant assumes that pushing to theuser/curio-cuzk:latest is enough to make the fix available. This requires that the Vast.ai instances are configured to pull theuser/curio-cuzk:latest (not a pinned digest or a different tag). The instance creation commands in earlier messages (e.g., [msg 1163]) use --image theuser/curio-cuzk:latest, confirming this assumption is correct.

No rollback needed: The assistant does not keep the previous image tagged or backed up. If the new image has a bug, there is no easy way to roll back to the previous version. The "Layer already exists" output suggests that the previous image's layers are still in the Docker cache on the build machine, but the Docker Hub tag now points to the new image.

The fix addresses the root cause: The post-restart warmup is a workaround, not a root-cause fix. The underlying issue — that the first proof after a daemon restart takes too long and exceeds the gRPC timeout — is not resolved. The warmup merely masks it by running a single proof before the timed batch. If the warmup proof itself times out (which it could, since it's the same "first proof after restart" scenario), the retry logic would handle it, but the total benchmark time would increase.

The Thinking Process Visible in the Reasoning

The assistant's reasoning leading up to this message is visible in the preceding messages. In [msg 1176], the assistant analyzes the Czechia failure:

"The real fix for the broken pipe issue is at the Rust level (not something we can control). But we can work around it by: 1. Reducing concurrency for the first batch (or running a single 'warm proof' after restart before the batch) 2. Or accepting that the first proof after a cold restart may timeout and adding retry logic to the benchmark batch"

This is a pragmatic engineering decision. The assistant recognizes that the gRPC timeout is a library-level default in the Rust tonic framework, not something configurable via cuzk-bench flags (confirmed in [msg 1175]). Rather than attempting to modify the Rust code (which would require a full recompile and introduce complexity), the assistant chooses a workaround at the shell script level. This is a classic trade-off: fix the symptom quickly rather than the root cause slowly.

The assistant also shows awareness of the system's state machine. The benchmark timeout fix (45 minutes) and the post-restart warmup are complementary: one addresses the total time budget, the other addresses the first-proof latency spike. Together, they cover two distinct failure modes.

Conclusion

Message [msg 1179] is a Docker push — a routine operation in any containerized workflow. But in the context of this coding session, it is the moment when debugging becomes deployment, when analysis becomes action. The assistant had spent hours diagnosing why GPU instances were failing benchmarks — killed by timeouts, broken by gRPC errors. The fixes were written, the syntax was checked, and then this message sealed them into a new Docker image and pushed it to the world. The layers that were pushed contain the post-restart warmup logic, the increased timeout, and the accumulated wisdom of a long debugging session. The next instances created would pull this image and, hopefully, survive their benchmarks. The push was the final step before validation — a quiet but essential act of deployment.