How was the worker with Kafka consumer organized — separately or together with FastAPI?

A Worker with a Kafka consumer is usually organized separately from a FastAPI application. This allows for a separation of responsibilities: FastAPI handles HTTP requests and synchronous interactions, while the worker handles asynchronous message processing from Kafka.

A separate process or service with a Kafka consumer is launched in parallel, listens to Kafka topics, and processes messages. This approach increases fault tolerance and scalability, as the worker can be scaled independently of the web server.

Example structure:

• fastapi_app/
  • main.py # FastAPI application
• kafka_worker/
  • consumer.py # worker with Kafka consumer

Launch:

uvicorn fastapi_app.main:app
python kafka_worker.consumer.py

In rare cases, the consumer can be integrated into FastAPI using background tasks, but this is less flexible and may lead to performance issues.