Real-World Docker Use Cases

Deploying Web Applications

Containerize full-stack applications with web servers, APIs, and databases for easier scaling and deployment.

Example: Running an NGINX server with your app:

docker run -d -p 80:80 --name webserver nginx

Combine frontend/backend with Docker Compose for multi-service applications.

Running Databases in Docker

Launch SQL and NoSQL databases quickly in isolated containers for testing or small-scale production:

docker run -d --name postgres-db -e POSTGRES_PASSWORD=secret -p 5432:5432 postgres

Use named volumes to persist data between restarts:

docker run -d -v pgdata:/var/lib/postgresql/data postgres

Using Docker for Microservices

• Each microservice runs in its own container
• Easy to scale independently
• Docker Compose or Kubernetes for orchestration

Example docker-compose.yml for microservice architecture:

services:
  users:
    image: user-service
    ports:
      - "5001:5001"

  products:
    image: product-service
    ports:
      - "5002:5002"

Docker in Data Science & Machine Learning

Use Docker to standardize ML environments and speed up experimentation:

• Package Python environments with TensorFlow, PyTorch, etc.
• Ensure GPU access with --gpus all flag
• Share models and notebooks using Docker images

Example Docker command for JupyterLab:

docker run -p 8888:8888 jupyter/datascience-notebook

Docker enables consistent, scalable, and secure deployments across all stages of development. Whether you're building a microservice platform or training ML models, Docker helps ship faster and smarter.