Use gunicorn

Signed-off-by: Paul Bui-Quang <[email protected]>

Dockerfile

@@ -19,10 +19,4 @@ RUN cp /antares-launcher/requirements.txt /conf/antares-launcher/requirements.tx
 RUN pip3 install --upgrade pip \
     && pip3 install -r /conf/requirements.txt
 
-ENTRYPOINT uvicorn \
-    --workers $UVICORN_WORKERS \
-    --root-path $UVICORN_ROOT_PATH \
-    --timeout-keep-alive $UVICORN_TIMEOUT \
-    --host 0.0.0.0 \
-    --port 5000 \
-    antarest.wsgi:app
+ENTRYPOINT gunicorn --config /conf/gunicorn.py --worker-class=uvicorn.workers.UvicornWorker antarest.wsgi:app

conf/gunicorn.py

@@ -0,0 +1,30 @@
+# Reference: https://github.com/benoitc/gunicorn/blob/master/examples/example_config.py
+
+import multiprocessing
+import os
+
+bind = "0.0.0.0:5000"
+
+"""
+Gunicorn relies on the operating system to provide all of the load balancing
+when handling requests. Generally we recommend (2 x $num_cores) + 1
+as the number of workers to start off with. While not overly scientific,
+the formula is based on the assumption that for a given core,
+one worker will be reading or writing from the socket
+while the other worker is processing a request.
+https://docs.gunicorn.org/en/stable/design.html#how-many-workers
+"""
+
+workers = os.getenv("GUNICORN_WORKERS")
+if workers == "ALL_AVAILABLE" or workers is None:
+    workers = multiprocessing.cpu_count() * 2 + 1
+
+timeout = 10 * 60  # 10 minutes
+keepalive = 24 * 60 * 60  # 1 day
+
+capture_output = True
+
+loglevel = "info"
+errorlog = "-"
+accesslog = "-"
+preload_app = False

requirements.txt

@@ -22,4 +22,5 @@ starlette~=0.14.2
 locust~=1.5.1
 MarkupSafe~=1.1.1
 checksumdir~=1.2.0
-pydantic~=1.8.2
+pydantic~=1.8.2
+gunicorn