Limit CPU and memory usage

In the recommended docker-based setup, Gramps Web uses Gunicorn to serve the backend and Celery for background tasks. In both cases, several worker processes can be run in parallel, which makes the application more responsive from a user perspective. However, increasing the number of workers also increase the amount of RAM used (even when the application is idle) and allowing requests to be processed in parallel can lead to high CPU usage (in particular when many users are using the application simultaneously). Both Gunicorn and Celery allow to limit the number of parallel workers.

Get information about your system

On Linux, you can check the number of cores available on your system with the following command:

lscpu | grep CPU

To see how much memory and swap space you have available, use

free -h

Limiting the number of Gunicorn workers

The easiest way to set the number of Gunicorn workers when using the default Gramps Web docker image is to set the environment variable GUNICORN_NUM_WORKERS, e.g. by declaring it in the docker-compose.yml file, under the "environment".

services:
  grampsweb:
    environment:
      GUNICORN_NUM_WORKERS: 2

See the Gunicorn documentation to decide about the ideal number of workers.

Limiting the number of Celery workers

To set the number of Celery workers, adapt the concurrency setting in the Docker compose file:

  grampsweb_celery:
    command: celery -A gramps_webapi.celery worker --loglevel=INFO --concurrency=2

See the Celery documentation to decide about the ideal number of workers.

Info

If the concurrency flag is omitted (which was the case in the Gramps Web documentation until v2.5.0), it defaults to the number of CPU cores available on the system, which might consume a substantial amount of memory.