release-train: develop -> staging - #652
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… it times their rank count (#650) The comment on DefaultTraining said the value was "quietly wrong above world_size 1" and that per-job-vs-per-rank was an open question. Since client-runtime#500 that is no longer what the runtime does with the number: a GPU pod's rank count is its nvidia.com/gpu limit, and the runtime stamps this per-rank base times that count, capped so the node's GPU pods still pack, refusing admission on a single-node edge when the scaled envelope can never be placed (client-runtime#483). A CPU pod runs a CPU-only torch, so its world_size is 1 by construction. Records the shipped behaviour where the number lives; changes no code. The package caveat about GPU pods being BestEffort is narrowed to the case where that is still true (single-GPU pods with the bound dark). Co-authored-by: Claude Fable 5.1 <noreply@anthropic.com>
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Reviewed by Cursor Bugbot for commit e812c5a. Configure here.
Functional review — staging batch, 2026-09-09 (FR reviewer: LukasWodka; self-signoff per RFC-BACKEND-1405 D6)Decision: PASS. Every card this promotion carried that sat at
The 4 red fleet legs are not staging regressions. The same four tasks are red on What this evidence does not cover, per the README, and is advanced anyway on the operator's (Lukas's) explicit instruction to clear the FR queue for a prod hop: interactive/TTY CLI prompt behaviour; per-ticket behaviour (one journey verdict is shared by every card in the batch); design-system-v2 visual output beyond Tests green and the npm Performed by the release-train operator session; mirror→card mapping derived from |
Automated promotion by the release train (RFC-0008 D14). Head is the train-managed
release-train/to-stagingbranch (a mirror ofdevelop), so it never collides with a human PR. Merged only when the fr-gate is green.Note
Low Risk
Comment-only changes with no runtime or CLI behavior changes.
Overview
Documentation-only update to
internal/resources/resources.gocomments so they match how client-runtime actually applies training resource envelopes.The package header now states that GPU pods use the per-rank base multiplied by
nvidia.com/gpuonce bounded (with BestEffort behavior until then), and that the documented value is the CPU-pod ceiling.The
DefaultTrainingcomment is expanded to spell out per-rank base vs runtime scaling: CPU pods carry the value as-is; GPU pods get base × GPU count (with packing caps and admission rules); in-pod CPU is still split across ranks via engine thread-pool sizing. It also clarifies thattracebloc resources showreports the per-rank base, not the stamped multi-GPU envelope.Reviewed by Cursor Bugbot for commit e812c5a. Bugbot is set up for automated code reviews on this repo. Configure here.