ECR Container Registry

# Multi-stage build
FROM python:3.9-slim as builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --user -r requirements.txt

# Production stage  
FROM python:3.9-slim as production
WORKDIR /app

# Copy dependencies
COPY --from=builder /root/.local /root/.local

# Create non-root user
RUN useradd --create-home --shell /bin/bash apiuser
USER apiuser

# Copy application
COPY . .

# Expose port
EXPOSE 8000

# Health check
HEALTHCHECK --interval=30s --timeout=5s --start-period=10s --retries=3 \
    CMD curl -f http://localhost:8000/health || exit 1

# Start application
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

# Navigate to server directory
cd retail-price-sensitivity-prediction/server

# Build Docker image
docker build -t mlops/retail-api:latest .

# Test locally
docker run -d --name test -p 8000:8000 mlops/retail-api:latest
curl http://localhost:8000/health
docker stop test && docker rm test

# 1. Retrieve an authentication token and authenticate Docker client
(Get-ECRLoginCommand).Password | docker login --username AWS --password-stdin 842676018087.dkr.ecr.ap-southeast-1.amazonaws.com

# 2. Build your Docker image
docker build -t mlops/retail-api .

# 3. Tag your image
docker tag mlops/retail-api:latest 842676018087.dkr.ecr.ap-southeast-1.amazonaws.com/mlops/retail-api:latest

# 4. Push image to ECR
docker push 842676018087.dkr.ecr.ap-southeast-1.amazonaws.com/mlops/retail-api:latest

# 1. Retrieve an authentication token and authenticate Docker client
aws ecr get-login-password --region ap-southeast-1 | docker login --username AWS --password-stdin 842676018087.dkr.ecr.ap-southeast-1.amazonaws.com

# 2. Build your Docker image
docker build -t mlops/retail-api .

# 3. Tag your image  
docker tag mlops/retail-api:latest 842676018087.dkr.ecr.ap-southeast-1.amazonaws.com/mlops/retail-api:latest

# 4. Push image to ECR
docker push 842676018087.dkr.ecr.ap-southeast-1.amazonaws.com/mlops/retail-api:latest

# Basic configuration
AWS_DEFAULT_REGION=ap-southeast-1
MODEL_BUCKET=mlops-retail-forecast-models
LOG_LEVEL=INFO
PORT=8000

# Test API container locally
docker run -d \
    --name retail-api-test \
    -p 8000:8000 \
    -e AWS_DEFAULT_REGION=ap-southeast-1 \
    -e MODEL_BUCKET=mlops-retail-prediction-dev-842676018087 \
    842676018087.dkr.ecr.ap-southeast-1.amazonaws.com/mlops/retail-api:latest

# Test health endpoint
curl http://localhost:8000/health

# Test API documentation
open http://localhost:8000/docs

# Clean up
docker stop retail-api-test && docker rm retail-api-test

# Liệt kê images trong repository
aws ecr describe-images --repository-name mlops/retail-api --region ap-southeast-1 --query 'imageDetails[*].[imageDigest,imageTags[0],imagePushedAt]' --output table

# Xóa specific image tag
aws ecr batch-delete-image \
  --repository-name mlops/retail-api \
  --image-ids imageTag=latest \
  --region ap-southeast-1

# Xóa tất cả images trong repository
aws ecr batch-delete-image \
  --repository-name mlops/retail-api \
  --image-ids "$(aws ecr describe-images --repository-name mlops/retail-api --region ap-southeast-1 --query 'imageDetails[*].{imageDigest:imageDigest}' --output json)" \
  --region ap-southeast-1

# Xóa repository (phải trống trước)
aws ecr delete-repository --repository-name mlops/retail-api --region ap-southeast-1 --force

# Verify repository đã bị xóa
aws ecr describe-repositories --region ap-southeast-1 --query 'repositories[?repositoryName==`mlops/retail-api`]'

# Xóa lifecycle policy (tự động xóa khi xóa repository)
aws ecr delete-lifecycle-policy --repository-name mlops/retail-api --region ap-southeast-1

# List remaining repositories
aws ecr describe-repositories --region ap-southeast-1 --query 'repositories[*].[repositoryName,repositoryUri]' --output table

# Remove local Docker images
docker rmi mlops/retail-api:latest
docker rmi 842676018087.dkr.ecr.ap-southeast-1.amazonaws.com/mlops/retail-api:latest

# Clean up Docker build cache
docker system prune -f

# Remove unused images
docker image prune -a -f

#!/bin/bash
# ecr-cleanup.sh

REPOSITORY_NAME="mlops/retail-api"
REGION="ap-southeast-1"

echo "🧹 Cleaning up ECR repository: $REPOSITORY_NAME..."

# 1. Delete all images
echo "Deleting all images..."
IMAGE_IDS=$(aws ecr describe-images --repository-name $REPOSITORY_NAME --region $REGION --query 'imageDetails[*].{imageDigest:imageDigest}' --output json)

if [ "$IMAGE_IDS" != "[]" ]; then
    aws ecr batch-delete-image \
        --repository-name $REPOSITORY_NAME \
        --image-ids "$IMAGE_IDS" \
        --region $REGION
    echo "Images deleted"
else
    echo "No images to delete"
fi

# 2. Delete repository
echo "Deleting repository..."
aws ecr delete-repository \
    --repository-name $REPOSITORY_NAME \
    --region $REGION \
    --force

# 3. Clean up local Docker
echo "Cleaning up local Docker images..."
docker rmi mlops/retail-api:latest 2>/dev/null || true
docker rmi 842676018087.dkr.ecr.ap-southeast-1.amazonaws.com/$REPOSITORY_NAME:latest 2>/dev/null || true

echo "✅ ECR cleanup completed"

# Multi-stage builds giảm image size
FROM node:16 as builder
# ... build steps
FROM node:16-alpine as production  # Smaller base image
COPY --from=builder /app/dist ./dist

# Automated cleanup with lifecycle policies
aws ecr put-lifecycle-policy \
  --repository-name mlops/retail-api \
  --lifecycle-policy-text file://lifecycle-policy.json