How do you make a flask app scalable?

How to make a Scalable Python Web App using Flask, Gunicorn, NGINX on Ubuntu 14.04

1. Time Matters!
2. Install PIP.
3. Install Python Development.
4. Install Flask.
5. Install Gunicorn.
6. Create a Python Flask Application.
7. Create a pre-fork Gunicorn startup script to run your Flask Application.
8. Create a Gunicorn upstart script.

Is flask good for scalable?

Flask is highly scalable. It can process a high number of requests each day, as it gets popular. It has been able to process up to 12 billion requests every day by using Flask. Flask modularizes the code so that developers can segregate them as independent chunks and use them as the code base grows.

How many concurrent requests can flask handle?

The reason your 4 worker processes will be able to handle more than 4 requests is that they will fire off threads to handle more and more requests. The actual request limit depends on HTTP server chosen, I/O, OS, hardware, network connection etc.

Is Gunicorn scalable?

Gunicorn allows us to run multiple worker processes of a single app. It’s really simple, and we can easily scale up or down our number of workers. Hardware permitting, you can scale up the number of workers. For our service, 2 was all the server could handle.

How do you structure a large Flask app?

Creating A Module / Component

1. Step 1: Structuring The Module.
2. Step 2: Define The Module Data Model(s)
3. Step 3: Define Module Forms.
4. Step 4: Define Application Controllers (Views)
5. Step 5: Set Up The Application in “app/init.py”
6. Step 6: Create The Templates.
7. Step 7: See Your Module In Action.

Can Flask handle multiple users?

2 Answers. Yes, deploy your application on a different WSGI server, see the Flask deployment options documentation. The server component that comes with Flask is really only meant for when you are developing your application; even though it can be configured to handle concurrent requests with app.

What is the difference between Gunicorn and Flask?

Gunicorn works by internally handing the calling of your flask code. This is done by having workers ready to handle the requests instead of the sequential one-at-a-time model that the default flask server provides. The end result is your app can handle more requests per second. Faster flask FTW!