scripts/b2_interference.py is the controlled microbench. It runs two
coroutines against the open proxy bypass (direct vLLM endpoints):
- decode_load: continuous short-prompt requests at fixed QPS into a
designated decode instance, to keep it decode-saturated.
- prefill_injections: N large one-token requests at fixed interval,
pointed at either the same instance (same-worker variant) or a
paired one (different-worker control).
Each cell (variant × prefill_size) gets its own metrics.jsonl plus a
run_window.json containing t_start_unix/t_end_unix. The shared
engine_*.jsonl from the scheduler patch is sliced by that window in
the aggregator.
analysis/characterization/b2_sweep_analysis.py walks the cell tree,
slices the per-worker step log by each cell's window, runs the A5
interference_index() against the slice, and emits a single
b2_sweep_summary.json with one row per cell. This is what feeds the
"interference vs uncached prefill size" figure.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Smoke validation on dash0 surfaced three real bugs that broke
interference and failure-attribution labels end-to-end:
1. endpoint_url in metrics is the proxy URL (e.g. http://h:9200);
the vLLM worker URL lives in breakdown's routed_to. The
interference index and label path were taking endpoint_url first,
so every request looked routed to a non-existent worker and the
overlap counter stayed at zero.
2. _normalize_worker hard-coded base port 8000, so a smoke run on
port 9100 resolved to engine_1100 instead of engine_0. Added a
--worker-map URL=engine_id CLI flag and _resolve_worker() that
prefers the explicit map and falls back to the heuristic.
3. vLLM rewrites the per-step rid as cmpl-<proxy_id>-<i>-<hash>, so
the str equality check between per_req rid and our proxy
request_id never matched -> every prefill step looked like
"other request prefill", which would have flipped overlap to
100%. Added _vllm_rid_matches() that strips the cmpl-/chatcmpl-
prefix.
After the fix, the same smoke run reports interference_index = 22.9
across 24 overlap / 6 clean requests on a single instance, which is
the expected shape for serial dispatch into a cold engine.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
New analysis/characterization/joined_analysis.py joins replayer
metrics.jsonl + proxy breakdown.json + worker_state.jsonl by
request_id, plus engine_*.jsonl by worker_id, and emits:
- joined.jsonl per-request merged record
- reuse_decomposition.json real intra/cross/shared classification
using session_id + hash_ids + cached_tokens
- interference_index.json TPOT_p90(same-worker prefill overlap)
/ TPOT_p90(clean), per Batch 2
- hotspot_index.json max/median worker TTFT-p90, per Batch 3
- failure_label.jsonl per-slow-request cause label, per Batch 5
- failure_breakdown.json label histogram
- window_summary.json SRR warmup/steady/drain aggregates
Closes the analyzer side of Phase A; replaces the
status: unavailable placeholders the existing scaffold emits when
join sources are missing.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
