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from typing import Any
from .models import SimulationConfig
def diagnose_run(summary: dict[str, Any], latency: dict[str, Any], resource: dict[str, Any], cfg: SimulationConfig) -> dict[str, Any]:
"""Explain the simulator's limiting regime from its own state.
Diagnostics are heuristic labels over simulated telemetry; they are not
hardware-counter measurements and must be interpreted with the profile
provenance attached to every run.
"""
target = cfg.slo_attainment_target
attainment = float(summary.get("slo_attainment", 0.0))
ttft_attainment = float(summary.get("ttft_slo_attainment", 0.0))
e2e_attainment = float(summary.get("e2e_slo_attainment", 0.0))
unfinished = int(summary.get("requests_unfinished", 0))
busy = float(summary.get("busy_fraction", 0.0))
kv_util = float(resource.get("peak_kv_utilization", 0.0))
queue_p95 = float(latency.get("queue_ms", {}).get("p95", 0.0))
prefill_busy = float(resource.get("prefill_busy_fraction", 0.0))
decode_busy = float(resource.get("decode_busy_fraction", 0.0))
transfer_busy = float(resource.get("transfer_busy_fraction", 0.0))
topology = str(resource.get("topology", cfg.topology))
code = "mixed_pressure"
label = "Mixed SLO pressure"
explanation = "Several constraints are active; inspect queueing, KV pressure, and tail latency together."
recommendation = "Compare schedulers and run the capacity planner to isolate the limiting regime."
if topology == "disaggregated_pd" and transfer_busy >= 0.85 and attainment < target:
code, label = "kv_transfer_pressure", "KV transfer pressure"
explanation = "The simulated P/D interconnect is highly utilized and transfer time is contributing to first-token latency."
recommendation = "Increase link bandwidth, reduce prompt pressure, or compare against colocated serving."
elif topology == "disaggregated_pd" and prefill_busy >= 0.92 and prefill_busy > decode_busy + 0.08:
code, label = "prefill_pool_pressure", "Prefill pool pressure"
explanation = "Prefill workers are the hottest role in the disaggregated pipeline."
recommendation = "Add prefill capacity, use prefix reuse, or reduce prompt-side pressure."
elif topology == "disaggregated_pd" and decode_busy >= 0.92 and decode_busy > prefill_busy + 0.08:
code, label = "decode_pool_pressure", "Decode pool pressure"
explanation = "Decode workers are the hottest role in the disaggregated pipeline."
recommendation = "Add decode capacity or reduce output-length / offered-load pressure."
elif unfinished > 0 and kv_util >= 0.85:
code, label = "kv_pressure", "KV memory pressure"
explanation = "Requests remain unfinished while the simulated KV cache approaches its configured capacity."
recommendation = "Reduce sequence pressure, lower offered load, use a smaller KV block, or choose a larger-memory profile."
elif unfinished > 0 and busy >= 0.92:
code, label = "over_capacity", "Offered load above capacity"
explanation = "The virtual serving system remains busy while the workload fails to drain."
recommendation = "Reduce offered load or use the capacity planner to find a sustainable operating point."
elif unfinished > 0:
code, label = "admission_stall", "Admission stall"
explanation = "Some requests cannot be admitted or completed under the current serving constraints."
recommendation = "Inspect batch-token and KV-cache limits, then compare a less restrictive configuration."
elif attainment >= target:
if busy >= 0.90:
code, label = "healthy_near_saturation", "Healthy, little headroom"
explanation = "The workload meets the configured SLO target, but simulated resource utilization is already high."
recommendation = "Run the capacity planner before increasing traffic; the current point is close to saturation."
else:
code, label = "healthy", "Healthy"
explanation = "The workload drains and meets the configured SLO-attainment target with visible headroom."
recommendation = "Use the capacity planner or design explorer to quantify additional headroom."
elif kv_util >= 0.90:
code, label = "kv_pressure", "KV memory pressure"
explanation = "Peak simulated KV utilization is high enough to constrain admission and batching flexibility."
recommendation = "Reduce sequence pressure, use smaller KV blocks, enable reusable prefixes, or select a larger-memory profile."
elif ttft_attainment < target and queue_p95 >= max(25.0, cfg.slo_ttft_ms * 0.20):
code, label = "queue_prefill_pressure", "Queue / prefill pressure"
explanation = "TTFT misses coincide with substantial queueing before prefill begins."
recommendation = "Lower offered load, increase safe batching capacity, or try chunked prefill / SLO-aware scheduling."
elif ttft_attainment < target:
code, label = "ttft_pressure", "TTFT pressure"
explanation = "First-token latency is the dominant SLO failure even though queueing is not the only contributor."
recommendation = "Compare prefill-oriented scheduling, prefix reuse, and P/D disaggregation scenarios."
elif e2e_attainment < target:
code, label = "decode_pressure", "Decode / E2E pressure"
explanation = "Most first tokens arrive within target, but end-to-end latency still misses the configured SLO."
recommendation = "Reduce output-length pressure or offered load; larger decode capacity may help when memory allows."
elif busy >= 0.95:
code, label = "compute_saturation", "Compute saturation"
explanation = "The simulated serving resources are effectively saturated even though no single SLO component dominates."
recommendation = "Reduce load or switch to a higher-throughput accelerator profile."
return {
"code": code,
"label": label,
"explanation": explanation,
"recommendation": recommendation,
"evidence": {
"slo_attainment": attainment,
"ttft_slo_attainment": ttft_attainment,
"e2e_slo_attainment": e2e_attainment,
"busy_fraction": busy,
"peak_kv_utilization": kv_util,
"queue_p95_ms": queue_p95,
"unfinished_requests": unfinished,
"prefill_busy_fraction": prefill_busy,
"decode_busy_fraction": decode_busy,
"transfer_busy_fraction": transfer_busy,
},
"provenance": "heuristic-simulator-diagnosis",
}
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