Show HN: FeatureLens – Real-time Go monitor for ML feature pipeline quality
github.comFeatureLens is a lightweight, high-performance monitoring tool designed specifically for real-time Machine Learning feature pipelines.
Features: 1) Kafka Consumer 2) Real-time Statistics Calculation Per Feature 3) Threshold-Based Alerting
Roadmap: 1) Integrate with Prometheus/Grafana 2) Advanced Windowing 3) Drift Detection Algorithms
I'm particularly interested in feedback from MLOps experts and enthusiasts on the following points. 1) How critical is lightweight, real-time monitoring specifically for feature pipelines compared to broader model or batch monitoring? 2) What specific types of data quality checks and drift detection metrics/algorithms are most crucial?
Thanks for your reading:)