Use gevent in gunicorn

- Enable gevent worker in gunicorn
  - Enable psycogreen in dci-cs to take full advantage of gevent
  - Only *try* to enable psycogreen if it can be imported. Don't make it
    a hard failure (current deployment in mod_wsgi won't have
    psycogreen)
- Use only one worker in gunicorn, scaling will be handled by creating
  more containers and let haproxy do the load balancing
- Clean all RPMs required only at build time
- Some gunicorn tuning

Change-Id: Ica635b755dad27ca7f53e39423290f866ba6d372

Dockerfile

@@ -12,9 +12,12 @@ COPY requirements.txt setup.py /opt/dci-control-server/
 
 RUN microdnf update && \
   microdnf -y install python3-pip python3-wheel && \
-  microdnf -y install python3-devel gcc postgresql-devel && \
+  rpm -qa | sort > /tmp/rpms_before && \
+  microdnf -y install python3-devel make gcc gcc-c++ postgresql-devel diffutils findutils file && \
+  rpm -qa | sort > /tmp/rpms_after && \
   pip3 --no-cache-dir install -r requirements.txt && \
-  microdnf -y remove python3-devel gcc postgresql-devel && \
+  comm -13 /tmp/rpms_before /tmp/rpms_after | xargs microdnf remove && \
+  rm /tmp/rpms_before /tmp/rpms_after && \
   microdnf -y clean all
 
 # install source after

dci/app.py

@@ -29,6 +29,13 @@
 from sqlalchemy import exc as sa_exc
 from sqlalchemy.orm import sessionmaker
 
+try:
+    import psycogreen.gevent
+
+    psycogreen.gevent.patch_psycopg()
+except ImportError:
+    pass
+
 logger = logging.getLogger(__name__)
 
 zmq_sender = None

gunicorn.conf.py

@@ -1,6 +1,23 @@
-import multiprocessing
 import os
 
-default_nb_workers = multiprocessing.cpu_count() * 2 + 1
-workers = int(os.getenv("DCI_NB_WORKERS", default_nb_workers))
+# Don't manage workers with gunicorn but by spawning more containers and let haproxy handle balancing
+DEFAULT_NB_WORKERS = 1
+workers = int(os.getenv("DCI_NB_WORKERS", DEFAULT_NB_WORKERS))
+worker_connections = int(os.getenv("DCI_GUNICORN_WORKER_CONNECTIONS", 50))
+worker_class = "gevent"
+
+# Restart worker after a certain amount of requests to mitigate memory leaks, etc. …
+max_requests = 1000
+# Add some jitter to avoid all workers restarting at the same time.
+max_requests_jitter = 250
+
 accesslog = "-"
+access_log_format = (
+    '%(h)s:%({x-forwarded-for}i)s %(l)s %(u)s %(t)s "%(r)s" %(s)s %(b)s "%(f)s" "%(a)s"'
+)
+
+# Some default values from gunicorn that might be of interest to tune
+# max_connections = 1000
+# backlog = 2048
+# timeout = 30
+# graceful_timeout = 30

requirements.txt

@@ -5,14 +5,15 @@ pyparsing==2.1.10  # pyparsing-2.1.10-7.el8.src.rpm baseos
 pytz==2017.2  # pytz-2017.2-9.el8.src.rpm appstream
 psycopg2==2.7.5;python_version<="3.6"  # python-psycopg2-2.7.5-7.el8.src.rpm appstream
 psycopg2-binary;python_version>"3.6"
+psycogreen
 pyOpenSSL==19.0.0  # pyOpenSSL-19.0.0-1.el8.src.rpm appstream
 jsonschema==2.6.0  # python-jsonschema-2.6.0-4.el8.src.rpm appstream
 SQLAlchemy==1.3.2  # python-sqlalchemy-1.3.2-2.module_el8.5.0+761+faacb0fb.src.rpm appstream
 
 alembic==1.3.1  # python-alembic-1.3.1-1.el8.src.rpm centos-openstack-train
 six==1.14.0  # python-six-1.14.0-2.el8.src.rpm centos-openstack-train
 requests==2.22.0  # python-requests-2.22.0-7.el8.src.rpm centos-openstack-train
-gunicorn
+gunicorn[gevent]
 
 flask==1.1.1  # python-flask-1.1.1-1.el8.src.rpm centos-openstack-train
 jinja2==2.10.1  # python3-jinja2-2.10.1-5.el8_10.noarch