docker-compose.yml

version: '3.8'

services:
  # Main application
  app:
    build:
      context: .
      dockerfile: Dockerfile
    container_name: transaction-anomaly-detection
    ports:
      - "8000:8000"
    environment:
      - ENVIRONMENT=development
      - LOG_LEVEL=DEBUG
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - AZURE_STORAGE_CONNECTION_STRING=${AZURE_STORAGE_CONNECTION_STRING}
      - KAFKA_BOOTSTRAP_SERVERS=kafka:9092
      - REDIS_HOST=redis
      - REDIS_PORT=6379
      - MLFLOW_TRACKING_URI=http://mlflow:5000
    volumes:
      - ./output:/app/output
      - ./logs:/app/logs
      - ./data:/app/data
      - ./feature_store:/app/feature_store
      - ./mlruns:/app/mlruns
    depends_on:
      - redis
      - kafka
      - mlflow
    networks:
      - aml-network
    restart: unless-stopped

  # Redis for caching and online features
  redis:
    image: redis:7-alpine
    container_name: aml-redis
    ports:
      - "6379:6379"
    volumes:
      - redis-data:/data
    command: redis-server --appendonly yes
    networks:
      - aml-network
    restart: unless-stopped

  # Kafka for stream processing
  zookeeper:
    image: confluentinc/cp-zookeeper:7.4.0
    container_name: aml-zookeeper
    environment:
      ZOOKEEPER_CLIENT_PORT: 2181
      ZOOKEEPER_TICK_TIME: 2000
    networks:
      - aml-network
    restart: unless-stopped

  kafka:
    image: confluentinc/cp-kafka:7.4.0
    container_name: aml-kafka
    ports:
      - "9092:9092"
    environment:
      KAFKA_BROKER_ID: 1
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://kafka:9092
      KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1
      KAFKA_AUTO_CREATE_TOPICS_ENABLE: "true"
    depends_on:
      - zookeeper
    networks:
      - aml-network
    restart: unless-stopped

  # MLflow for experiment tracking
  mlflow:
    image: ghcr.io/mlflow/mlflow:v2.8.1
    container_name: aml-mlflow
    ports:
      - "5000:5000"
    environment:
      - BACKEND_STORE_URI=sqlite:///mlflow.db
      - DEFAULT_ARTIFACT_ROOT=./mlruns
    volumes:
      - mlflow-data:/mlflow
    command: mlflow server --host 0.0.0.0 --port 5000
    networks:
      - aml-network
    restart: unless-stopped

  # Prometheus for monitoring
  prometheus:
    image: prom/prometheus:latest
    container_name: aml-prometheus
    ports:
      - "9090:9090"
    volumes:
      - ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml
      - prometheus-data:/prometheus
    command:
      - '--config.file=/etc/prometheus/prometheus.yml'
      - '--storage.tsdb.path=/prometheus'
    networks:
      - aml-network
    restart: unless-stopped

  # Grafana for visualization
  grafana:
    image: grafana/grafana:latest
    container_name: aml-grafana
    ports:
      - "3000:3000"
    environment:
      - GF_SECURITY_ADMIN_PASSWORD=admin
      - GF_INSTALL_PLUGINS=grafana-piechart-panel
    volumes:
      - grafana-data:/var/lib/grafana
      - ./monitoring/grafana/dashboards:/etc/grafana/provisioning/dashboards
    depends_on:
      - prometheus
    networks:
      - aml-network
    restart: unless-stopped

networks:
  aml-network:
    driver: bridge

volumes:
  redis-data:
  mlflow-data:
  prometheus-data:
  grafana-data: