Chunk 72.2

## Summary of this chunk The session began with a production incident: after a restart, under real agentic load (~100s of requests with tool rounds), some requests got stuck while others flowed normally. The user suspected the overlap-schedule change, but the assistant systematically refuted that through evidence: `--disable-overlap-schedule` was live, decode GPUs were idle (0%/165W) rather than spinning on a collective, and the NIXL abort-fix was present. The decisive clue was that prefill had run continuously for 17 hours while decode was restarted multiple times that day for A/B work, degrading the prefill↔decode NIXL bootstrap state. This caused silent transfer failures (21 on prefill vs 0 on decode), with requests stuck in prefill inflight and timing out, while decode sat idle with no error logs. The fix was a full clean co-restart of the PD pair (prefill → decode → router), which re-established the bootstrap from scratch. Post-fix verification showed 8/8 sequential requests at ~0.59s, an agentic repro with 30/30 sessions clean (0% corruption, 0 errors), transfer_failed held at 0, and prefill inflight draining normally from 17→0. All deployed improvements (TARGET_CTAS=512, MULTI_STREAM_OVERLAP=0, cuda-graph-max-bs 96, overlap-off) were confirmed live and innocent. The incident was documented in `DSV4_PD_DEADLOCK_ISSUE.md` with operational guidance: never restart decode alone against a long-running prefill, monitor `num_transfer_failed_reqs_total`, and consider installing py-spy and a liveness watchdog for deeper diagnosis if it recurs. The overarching theme is evidence-based incident response under production pressure: the assistant resisted the user's plausible hunch (overlap), gathered live process state, queue metrics, and timing evidence to identify the actual mechanism (degraded bootstrap from decode-only restarts), applied a targeted fix (full PD co-restart) that preserved all performance improvements, and produced actionable operational documentation. The work balances thorough investigation with production urgency, and the outcome is a stable system with all recent gains retained plus clear guidance to prevent recurrence.

From Corruption Fix to Throughput Scaling: A Production Debugging Odyssey Across CUDA Graphs, TBO, and Overlap Schedules 2214 words

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