splunk-secure.yml

version: '2'

services:

  # PostgreSQL database
  postgres:
    container_name: "postgres"
    image: postgres:10.4-alpine
    hostname: postgres
    env_file:
      - ./envs/postgres-dev.env
    ports:
      - "5432:5432"
    volumes:
      - ./data/postgres:/var/lib/postgresql/data

  # pgAdmin
  pgadmin:
    container_name: "pgadmin"
    image: jayjohnson/pgadmin4:1.0.0
    hostname: pgadmin
    env_file:
      - ./envs/pgadmin-dev.env
    ports:
      - "83:5050"
    volumes:
      - ./data/pgadmin:/data
  
  # Redis
  redis:
    container_name: "redis"
    hostname: redis
    image: redis:4.0.10-alpine
    ports:
      - "6379:6379"

  # Jupyter notebooks, converted noteooks as presentation html slides, and tensorboard
  jupyter:
    container_name: "jupyter"
    hostname: jupyter
    image: jayjohnson/antinex-jupyter:latest
    network_mode: "host"
    env_file:
      - ./envs/splunk.env
    environment:
      - JUPYTER_PASS=admin
      - SHARED_DIR=/opt/data
      - BROKER_URL=redis://0.0.0.0:6379/6
      - LOG_NAME=nb
      - ENV_NAME=aws
      - DEPLOY_CONFIG=1
    ports:
      - "8888:8888"
      - "8889:8889"
      - "8890:8890"
      - "6006:6006"
    entrypoint: "/opt/antinex/core/docker/jupyter/start-container.sh"

  # AntiNex Celery Worker for using pre-trained models
  core:
    container_name: "core"
    hostname: core
    image: jayjohnson/antinex-core:latest
    network_mode: "host"
    env_file:
      - ./envs/splunk.env
    environment:
      - SHARED_DIR=/opt/data
      - BROKER_URL=redis://0.0.0.0:6379/6
      - LOG_NAME=core
      - ENV_NAME=aws
      - DEPLOY_CONFIG=1
    volumes:
      - /tmp:/tmp
    depends_on:
      - postgres
      - redis
    entrypoint: "/bin/sh -c 'cd /opt/antinex/api && 
                 /opt/antinex/core/run-antinex-core.sh'"

  # Django Rest Framework + JWT + Swagger
  api:
    container_name: "api"
    hostname: api
    image: jayjohnson/antinex-api:latest
    network_mode: "host"
    environment:
      # for nginx hosting the statics need to be
      # deployed on startup to the mounted volume
      - SKIP_COLLECT_STATICS=0
      - LOG_NAME=api
      - ENV_NAME=aws
      - DEPLOY_CONFIG=1
    env_file:
      - ./envs/splunk.env
    ports:
      - "8010:8010"
    volumes:
      - /tmp:/tmp
      - /opt/antinex/static:/opt/antinex/api/webapp/staticfiles
      - ./run-django.sh:/opt/antinex/api/run-django.sh
    depends_on:
      - postgres
      - redis
    entrypoint: "/bin/sh -c 'cd /opt/antinex/api && 
                 /opt/antinex/api/run-django.sh'"

  # Django Rest Framework Celery Worker
  worker:
    container_name: "worker"
    hostname: worker
    image: jayjohnson/antinex-worker:latest
    network_mode: "host"
    env_file:
      - ./envs/splunk.env
    environment:
      - LOG_NAME=worker
      - ENV_NAME=aws
      - DEPLOY_CONFIG=1
    volumes:
      - /tmp:/tmp
    depends_on:
      - api
      - postgres
      - redis
    entrypoint: "/bin/sh -c 'cd /opt/antinex/api && 
                 /opt/antinex/api/run-worker.sh'"
  
  # Network Pipeline Packet Processor
  # auto-publishes to the Django Rest Framework 
  # for making predictions on network traffic
  # using pre-trained deep neural networks
  # running in the AntiNex Core
  pipeline:
    container_name: "pipeline"
    hostname: pipeline
    image: jayjohnson/antinex-pipeline:latest
    network_mode: "host"
    env_file:
      - ./envs/pipeline-dev.env
    environment:
      - LOG_NAME=pipe
      - ENV_NAME=aws
      - DEPLOY_CONFIG=1
    volumes:
      - /tmp:/tmp
    depends_on:
      - api
      - core
      - postgres
      - redis
    entrypoint: "/bin/sh -c 'cd /opt/antinex/pipeline && 
                 . /opt/venv/bin/activate &&
                 /opt/antinex/pipeline/network_pipeline/scripts/packets_redis.py'"