ProfessionAI_MLOps/docker-compose.yml at main · Alez22/ProfessionAI_MLOps · GitHub

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version: '3.8'

services:
  # 1. The Core Application (FastAPI + RoBERTa Model)
  api:
    build: .                          # Builds the Dockerfile in current directory
    container_name: reputation_api    # Fixed name for easy reference
    ports:
      - "8000:7860"                   # Maps Host Port 8000 to Container Port 7860 (HF standard)
    healthcheck:                      # Checks if API is responsive
      test: ["CMD", "curl", "-f", "http://localhost:7860/health"]
      interval: 30s
      timeout: 10s
      retries: 3

  # 2. Metrics Collector (Prometheus)
  prometheus:
    image: prom/prometheus:latest     # Uses official image
    container_name: prometheus
    ports:
      - "9090:9090"                   # Web UI for Prometheus
    volumes:
      # Mount configuration file from local folder to container
      - ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml
    command:
      # Tell Prometheus where config file is
      - '--config.file=/etc/prometheus/prometheus.yml'
    depends_on:
      - api                           # Wait for API to start before starting Prometheus

  # 3. Visualization Dashboard (Grafana)
  grafana:
    image: grafana/grafana-oss:latest # Uses official OSS image
    container_name: grafana
    ports:
      - "3000:3000"                   # Web UI for Grafana
    volumes:
      # Automate setup: Pre-configure Prometheus as data source
      - ./monitoring/grafana/datasource.yml:/etc/grafana/provisioning/datasources/datasource.yml
    environment:
      - GF_SECURITY_ADMIN_PASSWORD=admin # Default password for development
    depends_on:
      - prometheus                    # Grafana needs Prometheus to be ready