Docker-based architecture

• Brief description of Docker (containerization platform)
• Why use Docker? (isolation, portability, lightness)
• Container, Image
• Docker Engine
• Docker Hub
• Differences between VMs and containers

Images

• Using Docker Hub to retrieve an image
• Commands: docker pull, docker build, docker tag, docker push
• Practical application
• Containers
• Creating a container from an image
• Basic commands: docker run, docker ps, docker stop, docker rm
• Practical application

Containers

• Creating a container from an image
• Basic commands: docker run, docker ps, docker stop, docker rm
• Practical application

• What is Docker Compose?
• Structure of the docker-compose.yml file
• Example of a simple docker-compose.yml file
• Basic commands: docker-compose up, docker-compose down, docker-compose logs
• Putting it into practice
• Introduction to Swarm

RabbitMQ

• Typical use cases: asynchronous task management and batch processing
• Key concepts: Exchange, Queue, Binding
• Introduction to RabbitMQ Manager
• Practical application

Celery

• Using Celery with RabbitMQ as a broker
• Creating the worker, configuration
• Exposing a task
• Starting and controlling the worker
• Practical application

Celery Client

• Creating the client, configuration
• Exposing the prototype of a task
• Starting a task, obtaining its ID
• Retrieving a task from its ID, finding out its status, result, etc.
• Practical application

Flower

• Overview of features (task monitoring, workers, queues)
• Installing Flower via Docker or pip
• Practical application

Customization and documentation

• Introduction to the possibilities offered by Celery
• Presentation of the documentation
• Example of events

• Presentation of the stack to be deployed: Python worker, RabbitMQ, Celery, PostgreSQL
• Create the docker-compose.yml file
• Launch the stack
• Test an asynchronous task with the Python worker
• Monitoring and queue management

• Summary of concepts and tools covered
• Importance of orchestration with Docker Compose
• How Celery, RabbitMQ, and Docker can be used for distributed architectures