ForestFlow 

[wtm_mlop_cats]

ForestFlow is a scalable policy-based cloud-native machine learning model server. ForestFlow strives to strike a balance between the flexibility it offers data scientists and the adoption of standards while reducing friction between Data Science, Engineering and Operations teams.

ForestFlow is policy-based because we believe automation for Machine Learning/Deep Learning operations is critical to scaling human resources. ForestFlow lends itself well to workflows based on automatic retraining, version control, A/B testing, Canary Model deployments, Shadow testing, automatic time or performance-based model deprecation and time or performance-based model routing in real-time.

Features

Sized to Fit your Needs
Shadow Deployments
Automatic Resource Management
Multi-Tenancy
Policy-Based Routing
Policy-Based Phase-In/Expiration
Cloud Native
Streaming Inference
Payload Logging
Ease of Use

Official website

Tutorial and documentation

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