Event-Driven ML Feature Store Client | Apache Kafka & Python

Published: 21 August 2026
on channel: SARVESWARA RAO KOSURI (Sarvea)

Project Demo: Event-Driven Machine Learning Feature Store Client

In this video, I demonstrate a real-time, event-driven data pipeline built to solve the "stale features" problem in modern MLOps. This system ingests raw user events via Apache Kafka, processes them instantly using a resilient background consumer, handles idempotency in PostgreSQL, and serves the computed features to ML models via a low-latency FastAPI endpoint.

🔗 GitHub Repository:https://github.com/sarvea45/Event-Dri...

⏱️ Video Chapters: 0:00 - Introduction & Problem Statement 1:00 - Architecture & Code Walkthrough 2:30 - Infrastructure Startup (Docker Compose) 4:00 - Simulating 10,000 Real-Time Events (Producer) 5:30 - Testing the API & Explaining Idempotency 6:30 - Automated Testing (Pytest) & Graceful Shutdown

🛠️ Tech Stack Used: • Python 3 • Apache Kafka & Zookeeper • PostgreSQL • FastAPI & Pydantic • Docker & Docker Compose • Pytest

#MachineLearning #DataEngineering #ApacheKafka #FastAPI #Python #MLOps #EventDrivenArchitecture

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