observability

MBU is one division, and that is why it is so easy to get wrong. The answer defines both operands precisely on a real server and then shows six ways a dashboard can report a number 30 points off.

Compute acceptance from counter snapshots, reject reset-contaminated windows, and handle EOS before inferring request-step counts. Then decide what a matched-load baseline must measure.

Collectives run at the speed of their slowest link, so one NIC that trained at a quarter of its rate slows every GPU in the instance by the same amount. The answer shows the arithmetic that makes a 4x slower link a 2x slower step, then bisects the cluster to the culprit.

Inspect tokenized prompts and cache-counter deltas to diagnose a TTFT regression. A runnable prefix-boundary check and a routing follow-up test whether the evidence actually supports the diagnosis.

Same model, same image, same instance type, and one replica drags the fleet's p99. The answer first proves the replica is slower at equal load rather than busier, then walks the hardware causes from GPU clocks to a link that trained at the wrong speed.

The KV pool is preallocated, so the growth is somewhere the engine does not budget. The answer splits memory into what is fixed and what can grow, turns a growth rate into bytes per request, and uses that one number to rule out half the suspects.

A dashboard of forty graphs is a dashboard nobody reads at 2 a.m. The answer builds eight panels in the order an incident unfolds, ties each to the action it decides, and shows how two of them check each other with Little's law.