AI Deploy - Tutoriel - Déployer une app simple avec Flask (EN)
Comment construire et utiliser votre propre image Docker contenant une application Flask
Last updated 31st January, 2023.
AI Deploy is in beta. During the beta-testing phase, the infrastructure’s availability and data longevity are not guaranteed. Please do not use this service for applications that are in production, as this phase is not complete.
AI Deploy is covered by OVHcloud Public Cloud Special Conditions.
Objective
Flask is an open-source micro framework for web development in Python.
The purpose of this tutorial is to show you how to build and use a custom Docker image for a Flask application.
Requirements
- Access to the OVHcloud Control Panel;
- An AI Deploy project created inside a Public Cloud project in your OVHcloud account;
- A user for AI Deploy;
- Docker installed on your local computer;
- Some knowledge about building image and Dockerfile.
Instructions
Write a simple Flask application
Create a simple Python file with name app.py.
Inside that file, import your required modules:
from flask import Flask
Create Flask app:
app = Flask(__name__)
Define a simple function:
@app.route('/')
def index():
return 'Web App with Python Flask using AI Deploy!'
Start your app:
if __name__ == '__main__':
# starting app
app.run(debug=True,host='0.0.0.0')
- More information about Flask can be found here.
- Direct link to the full python file can be found here here.
Write the requirements.txt for your applications
The requirements.txt file will allow us to write all the modules needed to make our application work. This file will be useful when writing the Dockerfile.
Flask==1.1.2
Write the Dockerfile for your application
Your Dockerfile should start with the the FROM instruction indicating the parent image to use. In our case we choose to start from a classic Python image.
FROM python
Install the requirements.txt file which contains your needed Python modules using a pip install ... command:
RUN pip install -r requirements.txt
Define your default launching command to start the application.
CMD [ "python" , "/workspace/app.py" ]
Give correct access rights to ovhcloud user (42420:42420):
RUN chown -R 42420:42420 /workspace
ENV HOME=/workspace
- More information about Dockerfiles can be found here.
- Direct link to the full Dockerfile can be found here here.
Build the Docker image from the Dockerfile
Launch the following command from the Dockerfile directory to build your application image:
docker build . -t flask-app:latest
The dot . argument indicates that your build context (place of the Dockerfile and other needed files) is the current directory.
The -t argument allows you to choose the identifier to give to your image. Usually image identifiers are composed of a name and a version tag <name>:<version>. For this example we chose flask-app:latest.
Please make sure that the docker image you will push in order to run containers using AI products respects the linux/AMD64 target architecture. You could, for instance, build your image using buildx as follows:
docker buildx build --platform linux/amd64 ...
Test it locally (optional)
Launch the following docker command to launch your application locally on your computer:
docker run --rm -it -p 5000:5000 --user=42420:42420 flask-app:latest
The -p 5000:5000 argument indicates that you want to execute a port rediction from the port 5000 of your local machine into the port 5000 of the docker container. The port 5000 is the default port used by Flask applications.
Don't forget the --user=42420:42420 argument if you want to simulate the exact same behavior that will occur on AI Deploy apps. It executes the docker container as the specific OVHcloud user (user 42420:42420).
Once started, your application should be available on http://localhost:5000.
Push the image into the shared registry
The shared registry of AI Deploy should only be used for testing purposes. Please consider attaching your own docker registry. More information about this can be found here.
Find the address of your shared registry by launching this command:
ovhai registry list
Log in on the shared registry with your usual OpenStack credentials:
docker login -u <user> -p <password> <shared-registry-address>
Push the compiled image into the shared registry:
docker tag flask-app:latest <shared-registry-address>/flask-app:latest
docker push <shared-registry-address>/flask-app:latest
Launch the AI Deploy app
The following command starts a new app running your Flask application:
ovhai app run --default-http-port 5000 --cpu 1 <shared-registry-address>/flask-app:latest
--default-http-port 5000 indicates that the port to reach on the app url is the 5000.
--cpu 1 indicates that we request 1 cpu for that app.
Consider adding the --unsecure-http attribute if you want your application to be reachable without any authentication.
Once the app is running you can access your Flask application directly from the app's URL.
Go further
- To go further with Flask, imagine creating an app to deploy an Object Detection model. Refer to this tutorial.
- Flask allows you to do sentiment classification on texts using Hugging Face models. Here it is.
Feedback
Please send us your questions, feedback and suggestions to improve the service:
- On the OVHcloud Discord server
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