MLOps Learning

Roadmap

Phase1 Cloud Iac

IAM Basics
IAM Roles & Service Accounts
S3 Fundamentals
VPC Fundamentals
EC2 Fundamentals
Introduction to Terraform
Terraform State Management
Terraform Modules

Phase2 Containers K8s

Docker Deep Dive
Kubernetes Core Concepts
Kubernetes Hands-On with Kind
Kubernetes YAML Manifests
EKS Cluster Setup with Terraform
GitHub Actions Fundamentals
Complete CI/CD Pipeline

Phase3 Ml Lifecycle

ML Fundamentals for MLOps
MLflow Experiment Tracking
MLflow Model Registry
Model Serving with FastAPI
Airflow Fundamentals
ML Pipeline with Airflow

Phase4 Capstone

Capstone Architecture Design
Capstone Infrastructure Setup
Deploy MLflow to Kubernetes
Capstone Training Pipeline
Capstone Model Serving
Monitoring and Observability
Data and Model Drift Detection
Capstone CI/CD Integration
Documentation and Portfolio

Phase2 Containers K8s

Kubernetes Hands-On with Kind

Introduction

Now that you understand the concepts, let's get hands-on with a local Kubernetes cluster. We'll use Kind (Kubernetes in Docker) — it runs a full Kubernetes cluster inside Docker containers on your machine.

Why This Matters

You need a safe environment to experiment before touching a real cloud cluster. Kind gives you a real Kubernetes cluster that behaves like production but: - Costs nothing - Can be destroyed and recreated in seconds - Won't affect anyone else - Lets you make mistakes safely Everything you learn here transfers directly to EKS, GKE, or any other Kubernetes.

Tasks

Install Kind

Hint: brew install kind (Mac) or follow kind.sigs.k8s.io

Install kubectl (the Kubernetes CLI)

Hint: brew install kubectl

Create a Kind cluster: kind create cluster --name mlops-learning

Verify: kubectl cluster-info and kubectl get nodes

Deploy nginx: kubectl create deployment nginx --image=nginx

Check the deployment: kubectl get deployments, kubectl get pods

Expose it: kubectl expose deployment nginx --port=80 --type=NodePort

Get the service: kubectl get services

Scale the deployment: kubectl scale deployment nginx --replicas=3

Watch pods: kubectl get pods -w (observe new pods appearing)

Delete a pod manually and watch Kubernetes recreate it

View logs: kubectl logs <pod-name>

Execute into a pod: kubectl exec -it <pod-name> -- /bin/bash

Delete the deployment and service (cleanup)

Check Understanding

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