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ML Platform & Feature Store — Case Study

PostgreSQL feature store • Airflow orchestration • FastAPI model gateway • Observability.

Feature Freshness
≤ 2 min
Pipeline Success
100% daily
API Latency p95
< 300 ms
Feature Freshness (mins)
Daily Pipeline Jobs
API Latency p95

What We Built

A centralized feature store on PostgreSQL with clear data contracts feeds batch and real-time models. Airflow orchestrates ingestion, validation, and backfills. A FastAPI gateway exposes model inference over REST & WebSocket with per-model rate limiting and auth.

Observability tracks feature freshness, drift signals, and serving latency. The system is containerized and deploys on a VM/K8s cluster with rolling updates. Engineers get a self-serve template to add new features and models without touching infra.