(End-to-End Practical Implementation)

Today we take the same Intent Classifier model and deploy it using:

Docker + Kubernetes + Ingress + Autoscaling

This is how modern production ML systems are built.

What We Are Building

We are converting our ML model into a cloud-native microservice:

Client
  ↓
Ingress
  ↓
Service
  ↓
Deployment (Pods)
  ↓
Gunicorn
  ↓
Flask API (/predict)
  ↓
ML Model

With:

• Rolling updates
• Horizontal autoscaling
• Health checks
• Self-healing pods

Architecture Overview

Kubernetes Components We’ll Use

• Deployment
• Service (ClusterIP)