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Adjust the number of gunicorn workers
Given that each gunicorn worker uses ~200-250Mb virtual memory, we should really avoid running too many of them. Here, we reduce the default number of workers to 2. For the LMS and the CMS, this number can be adjusted by setting an environment variable GUNICORN_WORKERS. This is related to #207.
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@ -12,4 +12,4 @@ WORKDIR /openedx/edx-notes-api
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RUN pip install -r requirements/base.txt
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EXPOSE 8000
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CMD gunicorn --workers=3 --name notes --bind=0.0.0.0:8000 --max-requests=1000 notesserver.wsgi:application
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CMD gunicorn --workers=2 --name notes --bind=0.0.0.0:8000 --max-requests=1000 notesserver.wsgi:application
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@ -1,4 +1,4 @@
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import multiprocessing
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import os
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# Set the number of gunicorn workers to the number of CPU
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workers = multiprocessing.cpu_count()
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# Set the number of gunicorn workers
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workers = int(os.environ.get("GUNICORN_WORKERS", "2"))
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@ -12,4 +12,4 @@ WORKDIR /openedx/xqueue
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RUN pip install -r requirements.txt
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EXPOSE 8040
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CMD gunicorn --workers=3 --name xqueue --bind=0.0.0.0:8040 --max-requests=1000 xqueue.wsgi:application
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CMD gunicorn --workers=2 --name xqueue --bind=0.0.0.0:8040 --max-requests=1000 xqueue.wsgi:application
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