ML ENG WORKBENCH

ML System Pre-Modeling Feasibility Simulator

Production Archetypes:
Operational Architecture Topology (5 Pre-Modeling Gates)
SLA: 35ms Budget Bottleneck: Gate 2
Operational Gate Parameters Reactive Stress-Testing
Gate 1: Heuristic Rule Coverage 92%
% of cases accurately addressed by simple deterministic business rules.
Gate 2: Label Feedback Arrival 48 hours
Time required to confirm ground-truth outcome (settlement, dispute, conversion).
Gate 3: Serving Latency SLA 35 ms
Strict p99 online inference budget including network + feature hydration.
Gate 4: Feature Store Freshness 2 sec
Online feature hydration staleness (1s streaming vs 24h batch ETL).
Gate 5: Circuit Breaker Precision 84.5%
Precision floor when falling back to heuristic on model timeout/failure.
Required Minimum Lift over Heuristic 15%
Minimum statistical lift needed to justify ML training & maintenance overhead.
Feasibility Audit & Readiness Scorecard Live
76 / 100
Warning: Delayed Feedback Loop
Inference SLA and Fallback circuit breaker are compliant, but a 48h ground-truth arrival lag prevents real-time online adaptation. Training a continuous online model will suffer from label delay debt.
Architecture Trade-off: Deterministic Rule vs Full ML
Dimension Deterministic Heuristic Proposed ML Pipeline
Coverage / Target Catch 92.0% 97.8% (+5.8% lift)
Serving Latency p99 < 1.5 ms 28.0 ms (SLA: 35ms)
Failure Mode Risk Zero cold-start; hard-coded rules Degrades to Heuristic (84.5% prec)
Annual Maintenance Cost $15k (Rule engine tuning) $140k (Infra, drift alerts, GPU)
Exportable Architecture Decision Record (ADR / RFC) Markdown & JSON Ready
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