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AWS MLOps Retail Prediction Platform

End-to-end MLOps pipeline cho Retail Prediction với Infrastructure as Code và Model Deployment

👨‍💻 Tác giả 1

Nguyễn Thanh Nhân

Cloud Engineer

👩‍💻 Tác giả 2

Hà Khả Nguyên

Data Engineer

🛒 Retail Prediction MLOps Technology Stack

�️ Infrastructure
Terraform + EKS + VPC + IAM
🤖 ML Training
SageMaker + Model Registry + S3
🐳 Containers
EKS + ECR + Docker + HPA
💾 Data & Storage
S3 Data Lake + Versioning + Lifecycle
🚀 CI/CD & Automation
Jenkins + Pipeline Automation
📊 Monitoring & Security
CloudWatch + KMS + CloudTrail

📚 Retail Prediction MLOps Workshop

12 Tasks MLOps hoàn chỉnh cho Retail Prediction

End-to-end MLOps pipeline từ Infrastructure as Code đến Model Deployment với Monitoring và Cost Optimization cho Retail Prediction

🏗️ Infrastructure
🤖 ML Training
� Deployment
� Monitoring
🚀 CI/CD
� Cost Optimization

🏗️ Infrastructure Foundation

🤖 ML Training & Registry

Container Deployment

Security & Audit

Cost & Optimization

🚀 Bắt đầu Retail Prediction MLOps Workshop

📋 Prerequisites
AWS Account, Terraform, kubectl, Docker
⏱️ Thời gian
12-15 giờ (MLOps end-to-end)
📈 Level
Intermediate to Advanced
🎯 Bắt đầu với Task 1: Retail Prediction Architecture Overview

✨ Điểm nổi bật của Retail Prediction MLOps Workshop

🏗️
Infrastructure as Code
Terraform automation cho toàn bộ AWS resources
🤖
SageMaker Training
Distributed ML training cho retail prediction
EKS Deployment
Kubernetes cho retail prediction API
🔒
Security-first
KMS encryption + CloudTrail audit
🔄
CI/CD Pipeline
Automated build → train → deploy
💰
Cost Optimized
Auto-scaling + spot instances
⬆️