The 150-Second Uptime: A Single Metric That Exposed a Phantom Build

In the midst of a frantic production debugging session, a single line of Prometheus metrics became the fulcrum on which an entire investigation turned. The message was deceptively brief:

on the machine -> http://127.0.0.1:2036/debug/metrics | grep curio_harmonytask_uptime -> curio_harmonytask_uptime{version="1.27.3-rc2+mainnet+git_96f6c783_2026-03-11T16:08:33+01:00_psfix2"} 150

This user message ([msg 2000]) arrived at a moment of high tension. The assistant had just deployed a fix for a critical job-ID collision bug in the ProofShare system, only to discover that the cuzk proving engine was still logging the old, broken request format (ps-porep-1000-1). The assistant's first instinct was to verify the deployed binary — but the strings command wasn't available on the remote machine. The user, reading over the assistant's shoulder, provided the answer through an entirely different channel: the application's own Prometheus metrics endpoint.

The Context: A Collision of Identities

To understand why this single metric line carried so much weight, one must understand the crisis that preceded it. The ProofShare system is a distributed proving pipeline for Filecoin's GPU-accelerated proof generation. Multiple concurrent "PSProve" tasks would challenge the same sector (miner=1000, sector=1) with different random seeds, submitting proofs to the cuzk GPU proving engine. The RequestId sent to cuzk was generated as fmt.Sprintf("ps-porep-%d-%d", miner, sector) — meaning every concurrent task produced the exact same identifier. The cuzk engine's partition assembler, which keys its internal state on job_id, would mix partition results from different proofs, producing invalid outputs. The symptom was unmistakable: a "partition 0 already inserted" panic from the Rust engine.

The fix appeared straightforward: add the harmony task ID to the format string, producing ps-porep-%d-%d-%d. The snap computation path already used this pattern. The assistant edited the Go source, rebuilt the Curio binary inside a Docker CUDA environment (tagging it _psfix2), and deployed it to the production vast.ai instance. The version string confirmed the new binary was running.

Then the user reported ([msg 1997]) that cuzk logs still showed ps-porep-1000-1 — the old format, without the task ID. The fix hadn't taken effect.## The Crisis of Confidence

This moment — the user's message — represents a crisis of confidence in the build-and-deploy pipeline. The assistant had done everything right: edited the source code, rebuilt the binary, verified the version string, confirmed the process was running. Yet the evidence from the cuzk logs contradicted the version string. The natural suspicion fell on Docker's build cache. The assistant had used --volumes-from to mount the modified source files into the builder container, but Go's build cache is notoriously aggressive. If the builder container's Go cache still held compiled artifacts from the previous build, the modified source files might never have been recompiled. The binary would carry the new version tag (set via -ldflags -X) but contain the old code.

This is a subtle but devastating class of bug in containerized Go builds: the version string is a linker flag, not a compile-time constant embedded in the source. It gets stamped onto the binary regardless of whether any source files actually changed. A binary can report _psfix2 while executing the _psfix logic. The version tag is a promise, not a proof.

The assistant's first move upon seeing the old format in logs was to verify the binary directly — strings /usr/local/bin/curio | grep "ps-porep-" — but strings (from binutils) wasn't installed on the minimal production image. This left the assistant in a frustrating position: unable to confirm whether the binary contained the fix or not, with only circumstantial evidence (the version tag) suggesting it should.

The User's Intervention

The user's message cut through this uncertainty with surgical precision. Instead of trying to install strings or extract the binary for offline analysis, they queried the running application's own metrics endpoint. The Prometheus metric curio_harmonytask_uptime reports the uptime in seconds for each version of the harmony task system that has been registered. The output was:

curio_harmonytask_uptime{version="1.27.3-rc2+mainnet+git_96f6c783_2026-03-11T16:08:33+01:00_psfix2"} 150

The value 150 means the process had been running for 150 seconds — exactly 2.5 minutes. This was a bombshell. The assistant had deployed the _psfix2 binary approximately 10 minutes earlier (based on the timestamps in the conversation). But the uptime metric showed only 150 seconds. Something had restarted the process after the initial deployment, or the initial deployment had never taken effect and a different process was now running.

The implication was stark: the _psfix2 binary that the assistant carefully built and deployed was not the binary currently serving requests. Either the process had crashed and been restarted by a supervisor (like systemd or a Docker restart policy), reverting to the old binary, or the deployment sequence had a hidden failure — perhaps the mv command that replaced the binary had failed silently, or the running process had been started from a different path.## Assumptions and Their Failure

This episode reveals several assumptions that proved incorrect. The assistant assumed that because the version string contained _psfix2, the binary contained the corresponding code changes. This is a reasonable assumption in most build systems, but the Go toolchain's separation of compile-time and link-time metadata made it fragile. The assistant also assumed that the Docker build process, using --volumes-from to share source files from a data container, would force a recompilation of the modified files. In reality, Go's build cache is keyed on file content hashes, and the way the files were mounted may have preserved the old content or failed to trigger cache invalidation.

The user, by contrast, made no assumptions about the build pipeline. They went straight to the source of truth: the running process's own metrics. This is a powerful operational principle: when you need to know what code is actually executing, ask the process itself, not the filesystem or the build log.

Input Knowledge Required

To interpret this message, one needs to understand several layers of the system:

Prometheus metrics exposition format: The output is a standard Prometheus text format, where curio_harmonytask_uptime is a gauge metric with a label version and a value representing seconds since the task system started.
The harmony task system: Curio's internal task scheduler registers a version string at startup. The uptime metric resets each time the process restarts, making it an effective proxy for process lifetime.
The version string convention: The _psfix2 suffix is a custom build tag injected via -ldflags -X, not a Git tag or commit hash. It indicates the second attempt at fixing the ProofShare system.
The deployment timeline: The assistant had deployed the _psfix2 binary roughly 10 minutes prior. Seeing only 150 seconds of uptime meant the process had been restarted after that deployment — either by a crash, a supervisor, or a manual restart that picked up the old binary.

Output Knowledge Created

This message created a critical piece of operational knowledge: the _psfix2 binary was not actually running the ProofShare proving pipeline. The 150-second uptime contradicted the expected ~600-second uptime. This forced a re-examination of the deployment process. In the subsequent messages (continuing into the next chunk), the assistant would discover that the Docker build cache had indeed prevented the source changes from being compiled. The breakthrough came from switching to direct bind mounts (-v) instead of --volumes-from, which forced a full recompile and produced a binary with the correct format string.

The message also validated the metrics endpoint as a debugging tool. In a production environment where strings and other diagnostic utilities may not be available, the application's own instrumentation becomes the primary window into its behavior. The user's instinct to query Prometheus metrics rather than fight with missing tools is a model of pragmatic debugging.## The Thinking Process Revealed

The assistant's reasoning in the preceding message ([msg 1998]) shows the cognitive struggle in real time. The assistant first suspects the old binary is still running, then realizes the cuzk daemon may have queued jobs from before the restart, then considers whether the new curio is actually sending requests with the updated format. Each hypothesis is examined and discarded. The reasoning reveals a deep understanding of the system's distributed nature: the cuzk engine is a separate daemon with its own job queue, the harmony task system persists tasks in a database, and the proofshare_queue entries survive process restarts. The assistant knows that the fix is correct in principle but cannot confirm it in practice — a frustrating position for any engineer.

The user's message provides the missing piece. It doesn't answer the question "does the binary contain the fix?" directly, but it answers a more fundamental question: "is the process that would use the fix actually running?" The answer is no — or at least, it has only been running for 150 seconds, which is inconsistent with the deployment timeline. This redirects the investigation from "is the fix correct?" to "why isn't the fix deployed correctly?" — a much more productive line of inquiry.

The Broader Lesson

This message, for all its brevity, encapsulates a universal truth about production debugging: the most valuable data often comes from unexpected sources. The assistant was reaching for strings and binary analysis tools; the user reached for a Prometheus metrics endpoint. The metrics endpoint won because it answered a different, more relevant question. The binary might contain the right format string, but if the process running it has only been alive for 150 seconds, something is wrong with the deployment — not the code.

In the end, the fix was real. The Docker build cache had indeed prevented the source changes from being compiled. The version string _psfix2 was a lie — a linker flag stamped onto an old binary. The real fix required switching from --volumes-from to direct bind mounts, which forced Go's build cache to invalidate and recompile the modified files. The resulting binary, confirmed by both strings and correct cuzk logs, finally produced unique job IDs and resolved the partition collision.

But none of that would have been discovered without the user's 150-second uptime metric. It was the thread that, when pulled, unraveled the entire build-cache mystery. In a conversation full of complex code changes, Rust panics, and GPU pipeline debugging, the most impactful message was a single line of Prometheus output — a quiet, unambiguous fact that redirected the entire investigation.