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shadow-traffic

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Ships ML models in stages - shadow, then 1/5/25/50% of traffic - and rolls a bad one back automatically. The guardrails stay valid under constant checking: 0.6% false rollback with two identical models, where a repeatedly-read A/B test acts wrongly 36.7% of the time.

  • Updated Oct 12, 2026
  • Python

This project is a FastAPI + ONNX Runtime microservice that serves image inference with A/B routing, optional shadow traffic, token-bucket rate limiting, payload size guards, and end-to-end observability (Prometheus metrics, Grafana dashboards, structured logs, request tracing).

  • Updated Sep 16, 2025
  • Python

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