.

Author: mapattacker

docker.rst

@@ -404,11 +404,14 @@ Inside the docker container, if there is a need to view any files, we have to in
 
 **Console Log**
 
-+-----------------------------------+--------------------------------------------------------+
-| ``docker logs -f container_name`` | prints out console log of a container in detached mode |
-+-----------------------------------+--------------------------------------------------------+
-
-
+Any console prints will be added to the docker log, 
+and it will grow without a limit, unless you assigned one to it
+
++----------------------------------------------------------------------------------------------+--------------------------------------------------------+
+| ``docker logs -f container_name``                                                            | prints out console log of a container in detached mode |
++----------------------------------------------------------------------------------------------+--------------------------------------------------------+
+| ``docker run -d --log-opt max-size=5m --log-opt max-file=10 --name containername imagename`` | limit log file size to 5Mb and 10 log files            |
++----------------------------------------------------------------------------------------------+--------------------------------------------------------+
 
 
 Small Efficient Images

fastapi.rst

@@ -112,7 +112,7 @@ We do the same for the request schema and place them in the routing function.
     import numpy as np
 
     @app.post('/api', response_model= RESPONSE_SCHEMA)
-    def human_detection(request: REQUEST_SCHEMA):
+    async def human_detection(request: REQUEST_SCHEMA):
 
         JScontent = json.loads(request.json())
         encodedImage = JScontent['requests'][0]['image']['content']

flask.rst

@@ -247,6 +247,23 @@ Here's one complete request with data
         --data '{"username":"xyz","password":"xyz"}' \
         http://localhost:5000/api
 
+To run multiple requests in parallel for stress testing
+
+.. code:: bash
+
+    curl --header "Content-Type: application/json" \
+        --request POST \
+        --data '{"username":"xyz","password":"xyz"}' \
+        http://localhost:5000/api &
+    curl --header "Content-Type: application/json" \
+        --request POST \
+        --data '{"username":"xyz","password":"xyz"}' \
+        http://localhost:5000/api &
+    curl --header "Content-Type: application/json" \
+        --request POST \
+        --data '{"username":"xyz","password":"xyz"}' \
+        http://localhost:5000/api &
+    wait
 
 File Upload
 -----------
@@ -565,6 +582,32 @@ Apache's httpd.conf file.
     CMD /etc/mod_wsgi-express/apachectl start -D FOREGROUND
 
 
+Gunicorn is another popular, and extremely easy to use WSGI. 
+We can just install as ``pip install gunicorn``.
+and start it with the simple command.
+
+.. code::
+
+    # gunicorn -w 2 pythonScriptName:flaskAppName
+    # it uses port 8000 by default, but we can change it
+    gunicorn --bind 0.0.0.0:5000 -w 2 app:app
+
+
+``
+sudo apt-get install nginx
+# ubuntu firewall
+sudo ufw status
+sudo ufw enable
+sudo ufw nginx http
+sudo ufw status
+sudo ufw allow ssh
+
+systemctl status nginx
+systemctl start nginx
+systemctl stop nginx
+systemctl restart nginx
+``
+
 
 * https://www.appdynamics.com/blog/engineering/a-performance-analysis-of-python-wsgi-servers-part-2/