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# Full local development stack
# Start everything: docker-compose up -d
# View logs: docker-compose logs -f inference-api
# Tear down: docker-compose down -v
services:
# ── Postgres ────────────────────────────────────────────────────────────────
postgres:
image: postgres:15-alpine
environment:
POSTGRES_DB: flights
POSTGRES_USER: admin
POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-localpassword}
ports: ["5432:5432"]
volumes: [postgres_data:/var/lib/postgresql/data]
healthcheck:
test: ["CMD-SHELL", "pg_isready -U admin -d flights"]
interval: 10s
timeout: 5s
retries: 5
# ── MLflow tracking server ───────────────────────────────────────────────────
mlflow:
image: python:3.11-slim
depends_on:
postgres: { condition: service_healthy }
command: >
sh -c "pip install -q mlflow psycopg2-binary boto3 &&
mlflow server
--host 0.0.0.0
--port 5000
--backend-store-uri postgresql://admin:${POSTGRES_PASSWORD:-localpassword}@postgres:5432/flights
--default-artifact-root /mlruns"
ports: ["5000:5000"]
volumes: [mlruns:/mlruns]
environment:
MLFLOW_TRACKING_URI: http://localhost:5000
# ── Airflow (single-container quickstart) ────────────────────────────────────
airflow:
image: apache/airflow:2.9.1-python3.11
depends_on:
postgres: { condition: service_healthy }
environment:
AIRFLOW__CORE__EXECUTOR: LocalExecutor
AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://admin:${POSTGRES_PASSWORD:-localpassword}@postgres:5432/flights
AIRFLOW__CORE__FERNET_KEY: ${AIRFLOW_FERNET_KEY:-}
AIRFLOW__WEBSERVER__SECRET_KEY: ${AIRFLOW_SECRET_KEY:-changeme}
AIRFLOW__CORE__LOAD_EXAMPLES: "false"
MLFLOW_TRACKING_URI: http://mlflow:5000
ports: ["8080:8080"]
volumes:
- ./dags:/opt/airflow/dags
- ./etl:/opt/airflow/etl
- ./ml:/opt/airflow/ml
- ./mlops:/opt/airflow/mlops
- ./data:/opt/airflow/data
command: >
bash -c "airflow db init &&
airflow users create --username admin --password admin
--firstname Admin --lastname User --role Admin --email admin@example.com &&
airflow webserver & airflow scheduler"
# ── Inference API ────────────────────────────────────────────────────────────
inference-api:
build: .
depends_on:
postgres: { condition: service_healthy }
ports: ["8000:8000"]
environment:
DATABASE_URL: postgresql://admin:${POSTGRES_PASSWORD:-localpassword}@postgres:5432/flights
MLFLOW_TRACKING_URI: http://mlflow:5000
MODEL_VERSION: local
volumes:
- ./models:/app/models # mount trained models
- ./data:/app/data
healthcheck:
test: ["CMD-SHELL", "curl -f http://localhost:8000/health || exit 1"]
interval: 30s
timeout: 10s
retries: 3
# ── Prometheus ───────────────────────────────────────────────────────────────
prometheus:
image: prom/prometheus:v2.51.0
ports: ["9090:9090"]
volumes:
- ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml:ro
- prometheus_data:/prometheus
command:
- '--config.file=/etc/prometheus/prometheus.yml'
- '--storage.tsdb.retention.time=15d'
# ── Grafana ──────────────────────────────────────────────────────────────────
grafana:
image: grafana/grafana:10.4.0
depends_on: [prometheus]
ports: ["3000:3000"]
environment:
GF_SECURITY_ADMIN_PASSWORD: ${GRAFANA_PASSWORD:-admin}
volumes:
- grafana_data:/var/lib/grafana
volumes:
postgres_data:
mlruns:
prometheus_data:
grafana_data:
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