Using Goreplay to shadow http service traffic. (Docker container example)
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Updated
Oct 9, 2022 - Go
Using Goreplay to shadow http service traffic. (Docker container example)
End-to-end ML lifecycle platform with reproducible training, policy-based promotion, progressive delivery, and rollback.
Example repo related to a Futurice tech blog post
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.
Enterprise-grade traffic mirroring middleware. Supports Express (Node Streams) and Next.js App Router (Web Standards).
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).
Typed gRPC shadow traffic client. Mirrors requests from a stable primary to an under-test candidate; diffs responses asynchronously; returns the primary to your caller. Sampling, timeouts, pluggable sinks. bufconn-tested.
Python · A/B + canary + shadow · SLO monitor — Multi-model serving: A/B testing with sticky assignment, canary rollout, shadow traffic, per-version SLOs and auto-rollback that knows the difference between a bad canary and an upstream outage. 31 tests.
Five production tools for the lifecycle of Jev and compatible typed decision models.
To associate your repository with the shadow-traffic topic, visit your repo's landing page and select "manage topics."